Summary
- Google Scholar (h-index: 27; citations: 3000+) | Semantic Scholar
- ORCiD | PubMed | ResearchGate | Academia.edu | Publons | PapersWithCode
- Neuroscience: Sound, Hearing, Speech, Language, Time, Music, Memory
- AI: Speech, NLP, NLU, Fake News, Content moderation, Chatbot, Transformer
Papers
Gupta A, Sukumaran R, John K, Teki S (2021)
Hostility Detection and Covid-19 Fake News Detection in Social Media
CONSTRAINT Workshop, AAAI 2021 (non-archival) [link] [conference]
With the advent of social media, there has been an extremely rapid increase in the content shared online. Consequently, the propagation of fake news and hostile messages on social media platforms has also skyrocketed. In this paper, we address the problem of detecting hostile and fake content in the Devanagari (Hindi) script as a multi-class, multi-label problem. Using NLP techniques, we build a model that makes use of an abusive language detector coupled with features extracted via Hindi BERT and Hindi FastText models and metadata. Our model achieves a 0.97 F1 score on coarse grain evaluation on Hostility detection task. Additionally, we built models to identify fake news related to Covid-19 in English tweets. We leverage entity information extracted from the tweets along with textual representations learned from word embeddings and achieve a 0.93 F1 score on the English fake news detection task.
Hostility Detection and Covid-19 Fake News Detection in Social Media
CONSTRAINT Workshop, AAAI 2021 (non-archival) [link] [conference]
With the advent of social media, there has been an extremely rapid increase in the content shared online. Consequently, the propagation of fake news and hostile messages on social media platforms has also skyrocketed. In this paper, we address the problem of detecting hostile and fake content in the Devanagari (Hindi) script as a multi-class, multi-label problem. Using NLP techniques, we build a model that makes use of an abusive language detector coupled with features extracted via Hindi BERT and Hindi FastText models and metadata. Our model achieves a 0.97 F1 score on coarse grain evaluation on Hostility detection task. Additionally, we built models to identify fake news related to Covid-19 in English tweets. We leverage entity information extracted from the tweets along with textual representations learned from word embeddings and achieve a 0.93 F1 score on the English fake news detection task.
Brahma AK, Potluri P, Kanapaneni M, Prabhu S, Teki S (2021)
Identification of Food Quality Descriptors in Customer Chat Conversations using Named Entity Recognition
CODS-COMAD 2021 Research Track. [link]
Chatbots are increasingly being used for providing customer support. One of the fundamental challenges for a bot, or for that matter any human agent, is to understand the context of a customer message. Chat conversations are typically associated with agrammatical structure, spelling mistake/variants, informal and slang words, and code-mixing, i.e., the use of words from more than one language. We focused on a use case related to the conversations between customers and agents regarding issues with the quality of food delivered by an online food delivery company. Accurate identification of words that describe the poor quality of food can immensely benefit prompt resolution of the issue and also provide vital feedback to the company and its partner restaurants. This feature can be used in a chatbot to effectively resolve customers’ food quality related concerns. This paper presents a named entity recognition (NER) approach to identify the food quality descriptors in a given message. On an internal benchmark dataset, we achieved an F1 score of 0.93 while outperforming classical baseline approaches in NER.
Identification of Food Quality Descriptors in Customer Chat Conversations using Named Entity Recognition
CODS-COMAD 2021 Research Track. [link]
Chatbots are increasingly being used for providing customer support. One of the fundamental challenges for a bot, or for that matter any human agent, is to understand the context of a customer message. Chat conversations are typically associated with agrammatical structure, spelling mistake/variants, informal and slang words, and code-mixing, i.e., the use of words from more than one language. We focused on a use case related to the conversations between customers and agents regarding issues with the quality of food delivered by an online food delivery company. Accurate identification of words that describe the poor quality of food can immensely benefit prompt resolution of the issue and also provide vital feedback to the company and its partner restaurants. This feature can be used in a chatbot to effectively resolve customers’ food quality related concerns. This paper presents a named entity recognition (NER) approach to identify the food quality descriptors in a given message. On an internal benchmark dataset, we achieved an F1 score of 0.93 while outperforming classical baseline approaches in NER.
Vijjali R, Potluri P, Iyer S, Teki S (2020)
Two Stage Transformer model for Covid-19 Fake News Detection and Fact Checking
NLP for Internet Freedom Workshop co-located at COLING 2020 [link] [data] [conference]
The rapid advancement of technology in online communication via social media platforms has led to a prolific rise in the spread of misinformation and fake news. Fake news is especially rampant in the current COVID-19 pandemic, leading to people believing in false and potentially harmful claims and stories. Detecting fake news quickly can alleviate the spread of panic, chaos and potential health hazards. We developed a two stage automated pipeline for COVID-19 fake news detection using state of the art machine learning models for natural language processing. The first model leverages a novel fact checking algorithm that retrieves the most relevant facts concerning user claims about particular COVID-19 claims. The second model verifies the level of truth in the claim by computing the textual entailment between the claim and the true facts retrieved from a manually curated COVID-19 dataset. The dataset is based on a publicly available knowledge source consisting of more than 5000 COVID-19 false claims and verified explanations, a subset of which was internally annotated and cross-validated to train and evaluate our models. We evaluate a series of models based on classical text-based features to more contextual Transformer based models and observe that a model pipeline based on BERT and ALBERT for the two stages respectively yields the best results.
Two Stage Transformer model for Covid-19 Fake News Detection and Fact Checking
NLP for Internet Freedom Workshop co-located at COLING 2020 [link] [data] [conference]
The rapid advancement of technology in online communication via social media platforms has led to a prolific rise in the spread of misinformation and fake news. Fake news is especially rampant in the current COVID-19 pandemic, leading to people believing in false and potentially harmful claims and stories. Detecting fake news quickly can alleviate the spread of panic, chaos and potential health hazards. We developed a two stage automated pipeline for COVID-19 fake news detection using state of the art machine learning models for natural language processing. The first model leverages a novel fact checking algorithm that retrieves the most relevant facts concerning user claims about particular COVID-19 claims. The second model verifies the level of truth in the claim by computing the textual entailment between the claim and the true facts retrieved from a manually curated COVID-19 dataset. The dataset is based on a publicly available knowledge source consisting of more than 5000 COVID-19 false claims and verified explanations, a subset of which was internally annotated and cross-validated to train and evaluate our models. We evaluate a series of models based on classical text-based features to more contextual Transformer based models and observe that a model pipeline based on BERT and ALBERT for the two stages respectively yields the best results.
Rangan P*, Teki S* (2020) [*Equal contribution as first authors]
Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification
1st Workshop on Spoken Language Technologies for Multilingual Communities, INTERSPEECH 2020 [link1][link2]
Spoken language Identification (LID) systems are needed to identify the language(s) present in a given audio sample, and typically could be the first step in many speech processing related tasks such as automatic speech recognition (ASR). Automatic identification of the languages present in a speech signal is not only scientifically interesting, but also of practical importance in a multilingual country such as India. In many of the Indian cities, when people interact with each other, as many as three languages may get mixed. These may include the official language of that province, Hindi and English (at times the languages of the neighboring provinces may also get mixed during these interactions). This makes the spoken LID task extremely challenging in Indian context. While quite a few LID systems in the context of Indian languages have been implemented, most such systems have used small scale speech data collected internally within an organization. In the current work, we perform spoken LID on three Indian languages (Gujarati, Telugu, and Tamil) code-mixed with English. This task was organized by the Microsoft research team as a spoken LID challenge. In our work, we modify the usual spectral augmentation approach and propose a language mask that discriminates the language ID pairs, which leads to a noise robust spoken LID system. The proposed method gives a relative improvement of approximately 3-5% in the LID accuracy over a baseline system proposed by Microsoft on the three language pairs for two shared tasks suggested in the challenge.
Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification
1st Workshop on Spoken Language Technologies for Multilingual Communities, INTERSPEECH 2020 [link1][link2]
Spoken language Identification (LID) systems are needed to identify the language(s) present in a given audio sample, and typically could be the first step in many speech processing related tasks such as automatic speech recognition (ASR). Automatic identification of the languages present in a speech signal is not only scientifically interesting, but also of practical importance in a multilingual country such as India. In many of the Indian cities, when people interact with each other, as many as three languages may get mixed. These may include the official language of that province, Hindi and English (at times the languages of the neighboring provinces may also get mixed during these interactions). This makes the spoken LID task extremely challenging in Indian context. While quite a few LID systems in the context of Indian languages have been implemented, most such systems have used small scale speech data collected internally within an organization. In the current work, we perform spoken LID on three Indian languages (Gujarati, Telugu, and Tamil) code-mixed with English. This task was organized by the Microsoft research team as a spoken LID challenge. In our work, we modify the usual spectral augmentation approach and propose a language mask that discriminates the language ID pairs, which leads to a noise robust spoken LID system. The proposed method gives a relative improvement of approximately 3-5% in the LID accuracy over a baseline system proposed by Microsoft on the three language pairs for two shared tasks suggested in the challenge.
Teki S (2019)
Internationalization of NLP Models for Sensitive Content Detection in Alexa Utterances
Amazon Machine Learning Conference
Internationalization of NLP Models for Sensitive Content Detection in Alexa Utterances
Amazon Machine Learning Conference
Vatakis A, Teki S (2024)
Creating a Home for Timing Researchers: Then, Now, and the Future
Neurobiology of Interval Timing (Second Edition) [link]
Creating a Home for Timing Researchers: Then, Now, and the Future
Neurobiology of Interval Timing (Second Edition) [link]
Kim SG, Overath T, Sedley W, Kumar S, Teki S, Kikuchi Y, Patterson R, Griffiths TD (2022)
MEG Correlates of Temporal Regularity Relevant to Pitch Perception in Human Auditory Cortex
Neuroimage, 118879 [link]
We recorded neural responses in human participants to three types of pitch-evoking regular stimuli at rates below and above the lower limit of pitch using magnetoencephalography (MEG). These bandpass filtered (1–4 kHz) stimuli were harmonic complex tones (HC), click trains (CT), and regular interval noise (RIN). Trials consisted of noise-regular-noise (NRN) or regular-noise-regular (RNR) segments in which the repetition rate (or fundamental frequency F0) was either above (250 Hz) or below (20 Hz) the lower limit of pitch. Neural activation was estimated and compared at the senor and source levels.
The pitch-relevant regular stimuli (F0 = 250 Hz) were all associated with marked evoked responses at around 140 ms after noise-to-regular transitions at both sensor and source levels. In particular, greater evoked responses to pitch-relevant stimuli than pitch-irrelevant stimuli (F0 = 20 Hz) were localized along the Heschl's sulcus around 140 ms. The regularity-onset responses for RIN were much weaker than for the other types of regular stimuli (HC, CT). This effect was localized over planum temporale, planum polare, and lateral Heschl's gyrus. Importantly, the effect of pitch did not interact with the stimulus type. That is, we did not find evidence to support different responses for different types of regular stimuli from the spatiotemporal cluster of the pitch effect (∼140 ms).
The current data demonstrate cortical sensitivity to temporal regularity relevant to pitch that is consistently present across different pitch-relevant stimuli in the Heschl's sulcus between Heschl's gyrus and planum temporale, both of which have been identified as a “pitch center” based on different modalities.
MEG Correlates of Temporal Regularity Relevant to Pitch Perception in Human Auditory Cortex
Neuroimage, 118879 [link]
We recorded neural responses in human participants to three types of pitch-evoking regular stimuli at rates below and above the lower limit of pitch using magnetoencephalography (MEG). These bandpass filtered (1–4 kHz) stimuli were harmonic complex tones (HC), click trains (CT), and regular interval noise (RIN). Trials consisted of noise-regular-noise (NRN) or regular-noise-regular (RNR) segments in which the repetition rate (or fundamental frequency F0) was either above (250 Hz) or below (20 Hz) the lower limit of pitch. Neural activation was estimated and compared at the senor and source levels.
The pitch-relevant regular stimuli (F0 = 250 Hz) were all associated with marked evoked responses at around 140 ms after noise-to-regular transitions at both sensor and source levels. In particular, greater evoked responses to pitch-relevant stimuli than pitch-irrelevant stimuli (F0 = 20 Hz) were localized along the Heschl's sulcus around 140 ms. The regularity-onset responses for RIN were much weaker than for the other types of regular stimuli (HC, CT). This effect was localized over planum temporale, planum polare, and lateral Heschl's gyrus. Importantly, the effect of pitch did not interact with the stimulus type. That is, we did not find evidence to support different responses for different types of regular stimuli from the spatiotemporal cluster of the pitch effect (∼140 ms).
The current data demonstrate cortical sensitivity to temporal regularity relevant to pitch that is consistently present across different pitch-relevant stimuli in the Heschl's sulcus between Heschl's gyrus and planum temporale, both of which have been identified as a “pitch center” based on different modalities.
King A, Teki S, Willmore BDB (2018)
Recent advances in understanding the auditory cortex
F1000 Research 7 (F1000 Faculty Rev): 1555 [link]
Our ability to make sense of the auditory world results from neural processing that begins in the ear, goes through multiple subcortical areas, and continues in the cortex. The specific contribution of the auditory cortex to this chain of processing is far from understood. Although many of the properties of neurons in the auditory cortex resemble those of subcortical neurons, they show somewhat more complex selectivity for sound features, which is likely to be important for the analysis of natural sounds, such as speech, in real-life listening conditions. Furthermore, recent work has shown that auditory cortical processing is highly context-dependent, integrates auditory inputs with other sensory and motor signals, depends on experience, and is shaped by cognitive demands, such as attention. Thus, in addition to being the locus for more complex sound selectivity, the auditory cortex is increasingly understood to be an integral part of the network of brain regions responsible for prediction, auditory perceptual decision-making, and learning. In this review, we focus on three key areas that are contributing to this understanding: the sound features that are preferentially represented by cortical neurons, the spatial organization of those preferences, and the cognitive roles of the auditory cortex.
Recent advances in understanding the auditory cortex
F1000 Research 7 (F1000 Faculty Rev): 1555 [link]
Our ability to make sense of the auditory world results from neural processing that begins in the ear, goes through multiple subcortical areas, and continues in the cortex. The specific contribution of the auditory cortex to this chain of processing is far from understood. Although many of the properties of neurons in the auditory cortex resemble those of subcortical neurons, they show somewhat more complex selectivity for sound features, which is likely to be important for the analysis of natural sounds, such as speech, in real-life listening conditions. Furthermore, recent work has shown that auditory cortical processing is highly context-dependent, integrates auditory inputs with other sensory and motor signals, depends on experience, and is shaped by cognitive demands, such as attention. Thus, in addition to being the locus for more complex sound selectivity, the auditory cortex is increasingly understood to be an integral part of the network of brain regions responsible for prediction, auditory perceptual decision-making, and learning. In this review, we focus on three key areas that are contributing to this understanding: the sound features that are preferentially represented by cortical neurons, the spatial organization of those preferences, and the cognitive roles of the auditory cortex.
Rajendran VG, Teki S*, Schnupp JWH* (2017) [* Equal contribution as senior authors]
Temporal Processing in Audition: Insights from Music
Neuroscience (Special issue on Sequence Processing) [link]
Music is a curious example of a temporally patterned acoustic stimulus, and a compelling pan-cultural phenomenon. This review strives to bring some insights from decades of music psychology and sensorimotor synchronization (SMS) literature into the mainstream auditory domain, arguing that musical rhythm perception is shaped in important ways by temporal processing mechanisms in the brain. The feature that unites these disparate disciplines is an appreciation of the central importance of timing, sequencing, and anticipation. Perception of musical rhythms relies on an ability to form temporal predictions, a general feature of temporal processing that is equally relevant to auditory scene analysis, pattern detection, and speech perception. By bringing together findings from the music and auditory literature, we hope to inspire researchers to look beyond the conventions of their respective fields and consider the cross-disciplinary implications of studying auditory temporal sequence processing.
We begin by highlighting music as an interesting sound stimulus that may provide clues to how temporal patterning in sound drives perception. Next, we review the SMS literature and discuss possible neural substrates for the perception of, and synchronization to, musical beat. We then move away from music to explore the perceptual effects of rhythmic timing in pattern detection, auditory scene analysis, and speech perception. Finally, we review the neurophysiology of general timing processes that may underlie aspects of the perception of rhythmic patterns. We conclude with a brief summary and outlook for future research.
Temporal Processing in Audition: Insights from Music
Neuroscience (Special issue on Sequence Processing) [link]
Music is a curious example of a temporally patterned acoustic stimulus, and a compelling pan-cultural phenomenon. This review strives to bring some insights from decades of music psychology and sensorimotor synchronization (SMS) literature into the mainstream auditory domain, arguing that musical rhythm perception is shaped in important ways by temporal processing mechanisms in the brain. The feature that unites these disparate disciplines is an appreciation of the central importance of timing, sequencing, and anticipation. Perception of musical rhythms relies on an ability to form temporal predictions, a general feature of temporal processing that is equally relevant to auditory scene analysis, pattern detection, and speech perception. By bringing together findings from the music and auditory literature, we hope to inspire researchers to look beyond the conventions of their respective fields and consider the cross-disciplinary implications of studying auditory temporal sequence processing.
We begin by highlighting music as an interesting sound stimulus that may provide clues to how temporal patterning in sound drives perception. Next, we review the SMS literature and discuss possible neural substrates for the perception of, and synchronization to, musical beat. We then move away from music to explore the perceptual effects of rhythmic timing in pattern detection, auditory scene analysis, and speech perception. Finally, we review the neurophysiology of general timing processes that may underlie aspects of the perception of rhythmic patterns. We conclude with a brief summary and outlook for future research.
Teki S, Gu BM, Meck WH (2017)
The Persistence of Memory: How the Brain encodes Time in Memory
Current Opinion in Behavioral Sciences 17: 178-185. (Special issue on Memory in Time and Space) [link]
Time and memory are inextricably linked, but it is far from clear how event durations and temporal sequences are encoded in memory. In this review, we focus on resource allocation models of working memory which suggest that memory resources can be flexibly distributed amongst several items such that the precision of working memory decreases with the number of items to be encoded. This type of model is consistent with human performance in working memory tasks based on visual, auditory as well as temporal stimulus patterns. At the neural-network level, we focus on excitatory–inhibitory oscillatory processes that are able to encode both interval timing and working memory in a coupled excitatory–inhibitory network. This modification of the striatal beat-frequency model of interval timing shows how memories for multiple time intervals are represented by neural oscillations and can also be used to explain the mechanisms of resource allocation in working memory.
The Persistence of Memory: How the Brain encodes Time in Memory
Current Opinion in Behavioral Sciences 17: 178-185. (Special issue on Memory in Time and Space) [link]
Time and memory are inextricably linked, but it is far from clear how event durations and temporal sequences are encoded in memory. In this review, we focus on resource allocation models of working memory which suggest that memory resources can be flexibly distributed amongst several items such that the precision of working memory decreases with the number of items to be encoded. This type of model is consistent with human performance in working memory tasks based on visual, auditory as well as temporal stimulus patterns. At the neural-network level, we focus on excitatory–inhibitory oscillatory processes that are able to encode both interval timing and working memory in a coupled excitatory–inhibitory network. This modification of the striatal beat-frequency model of interval timing shows how memories for multiple time intervals are represented by neural oscillations and can also be used to explain the mechanisms of resource allocation in working memory.
Woodhead ZVJ, Crinion J, Teki S, Penny W, Price CJ, Leff AP (2017)
Auditory therapy re-tunes linguistic representations in left superior temporal gyri of Wernicke’s aphasia patients
Journal of Neurology, Neurosurgery and Psychiatry 88(7): 586-594 [link]
Introduction Aphasia is one of the most disabling sequelae after stroke, occurring in 25%–40% of stroke survivors. However, there remains a lack of good evidence for the efficacy or mechanisms of speech comprehension rehabilitation.
Trial Design This within-subjects trial tested two concurrent interventions in 20 patients with chronic aphasia with speech comprehension impairment following left hemisphere stroke: (1) phonological training using ‘Earobics’ software and (2) a pharmacological intervention using donepezil, an acetylcholinesterase inhibitor. Donepezil was tested in a double-blind, placebo-controlled, cross-over design using block randomisation with bias minimisation.
Methods The primary outcome measure was speech comprehension score on the comprehensive aphasia test. Magnetoencephalography (MEG) with an established index of auditory perception, the mismatch negativity response, tested whether the therapies altered effective connectivity at the lower (primary) or higher (secondary) level of the auditory network.
Results Phonological training improved speech comprehension abilities and was particularly effective for patients with severe deficits. No major adverse effects of donepezil were observed, but it had an unpredicted negative effect on speech comprehension. The MEG analysis demonstrated that phonological training increased synaptic gain in the left superior temporal gyrus (STG). Patients with more severe speech comprehension impairments also showed strengthening of bidirectional connections between the left and right STG.
Conclusions Phonological training resulted in a small but significant improvement in speech comprehension, whereas donepezil had a negative effect. The connectivity results indicated that training reshaped higher order phonological representations in the left STG and (in more severe patients) induced stronger interhemispheric transfer of information between higher levels of auditory cortex.
Auditory therapy re-tunes linguistic representations in left superior temporal gyri of Wernicke’s aphasia patients
Journal of Neurology, Neurosurgery and Psychiatry 88(7): 586-594 [link]
Introduction Aphasia is one of the most disabling sequelae after stroke, occurring in 25%–40% of stroke survivors. However, there remains a lack of good evidence for the efficacy or mechanisms of speech comprehension rehabilitation.
Trial Design This within-subjects trial tested two concurrent interventions in 20 patients with chronic aphasia with speech comprehension impairment following left hemisphere stroke: (1) phonological training using ‘Earobics’ software and (2) a pharmacological intervention using donepezil, an acetylcholinesterase inhibitor. Donepezil was tested in a double-blind, placebo-controlled, cross-over design using block randomisation with bias minimisation.
Methods The primary outcome measure was speech comprehension score on the comprehensive aphasia test. Magnetoencephalography (MEG) with an established index of auditory perception, the mismatch negativity response, tested whether the therapies altered effective connectivity at the lower (primary) or higher (secondary) level of the auditory network.
Results Phonological training improved speech comprehension abilities and was particularly effective for patients with severe deficits. No major adverse effects of donepezil were observed, but it had an unpredicted negative effect on speech comprehension. The MEG analysis demonstrated that phonological training increased synaptic gain in the left superior temporal gyrus (STG). Patients with more severe speech comprehension impairments also showed strengthening of bidirectional connections between the left and right STG.
Conclusions Phonological training resulted in a small but significant improvement in speech comprehension, whereas donepezil had a negative effect. The connectivity results indicated that training reshaped higher order phonological representations in the left STG and (in more severe patients) induced stronger interhemispheric transfer of information between higher levels of auditory cortex.
Teki S, Kononowicz T (2016)
Commentary: Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery
Frontiers in Neuroscience: Auditory Cognitive Neuroscience 10: 389 [link]
(Special issue on The Evolution of Rhythm Cognition: Timing in Music and Speech)
The ability to predict the timing of natural sounds is essential for accurate comprehension of speech and music (Allman et al., 2014). Rhythmic activity in the beta range (12–30 Hz) is crucial for encoding the temporal structure of regular sound sequences (Fujioka et al., 2009, 2012; Bartolo et al., 2014; Teki, 2014; Bartolo and Merchant, 2015). Specifically, the power of induced beta oscillations in the auditory cortex is dynamically modulated according to the temporal pattern of beats (Fujioka et al., 2012), such that beat-related induced beta power decreases after the beat and then increases preceding the next beat as depicted in Figure 1A. However, it is not known whether beta oscillations encode the beat positions in metrical sequences with physically or subjectively accented beats (i.e., “upbeat” and “downbeat”) and whether this is accomplished in a predictive manner or not.
Commentary: Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery
Frontiers in Neuroscience: Auditory Cognitive Neuroscience 10: 389 [link]
(Special issue on The Evolution of Rhythm Cognition: Timing in Music and Speech)
The ability to predict the timing of natural sounds is essential for accurate comprehension of speech and music (Allman et al., 2014). Rhythmic activity in the beta range (12–30 Hz) is crucial for encoding the temporal structure of regular sound sequences (Fujioka et al., 2009, 2012; Bartolo et al., 2014; Teki, 2014; Bartolo and Merchant, 2015). Specifically, the power of induced beta oscillations in the auditory cortex is dynamically modulated according to the temporal pattern of beats (Fujioka et al., 2012), such that beat-related induced beta power decreases after the beat and then increases preceding the next beat as depicted in Figure 1A. However, it is not known whether beta oscillations encode the beat positions in metrical sequences with physically or subjectively accented beats (i.e., “upbeat” and “downbeat”) and whether this is accomplished in a predictive manner or not.
Teki S (2016)
A citation-based analysis and review of significant papers on timing and time perception.
Frontiers in Neuroscience 10: 330 (Special issue on The Evolution of Rhythm Cognition) [link]
Time is an important dimension of brain function, but little is yet known about the underlying cognitive principles and neurobiological mechanisms. The field of timing and time perception has witnessed tremendous growth and multidisciplinary interest in the recent years with the advent of modern neuroimaging and neurophysiological approaches. In this article, I used a data mining approach to analyze the timing literature published by a select group of researchers (n = 202) during the period 2000–2015 and highlight important reviews as well as empirical articles that meet the criterion of a minimum of 100 citations. The qualifying articles (n = 150) are listed in a table along with key details such as number of citations, names of authors, year and journal of publication as well as a short summary of the findings of each study. The results of such a data-driven approach to literature review not only serve as a useful resource to any researcher interested in timing, but also provides a means to evaluate key papers that have significantly influenced the field and summarize recent progress and popular research trends in the field. Additionally, such analyses provides food for thought about future scientific directions and raises important questions about improving organizational structures to boost open science and progress in the field. I discuss exciting avenues for future research that have the potential to significantly advance our understanding of the neurobiology of timing, and propose the establishment of a new society, the Timing Research Forum, to promote open science and collaborative work within the highly diverse and multidisciplinary community of researchers in the field of timing and time perception.
A citation-based analysis and review of significant papers on timing and time perception.
Frontiers in Neuroscience 10: 330 (Special issue on The Evolution of Rhythm Cognition) [link]
Time is an important dimension of brain function, but little is yet known about the underlying cognitive principles and neurobiological mechanisms. The field of timing and time perception has witnessed tremendous growth and multidisciplinary interest in the recent years with the advent of modern neuroimaging and neurophysiological approaches. In this article, I used a data mining approach to analyze the timing literature published by a select group of researchers (n = 202) during the period 2000–2015 and highlight important reviews as well as empirical articles that meet the criterion of a minimum of 100 citations. The qualifying articles (n = 150) are listed in a table along with key details such as number of citations, names of authors, year and journal of publication as well as a short summary of the findings of each study. The results of such a data-driven approach to literature review not only serve as a useful resource to any researcher interested in timing, but also provides a means to evaluate key papers that have significantly influenced the field and summarize recent progress and popular research trends in the field. Additionally, such analyses provides food for thought about future scientific directions and raises important questions about improving organizational structures to boost open science and progress in the field. I discuss exciting avenues for future research that have the potential to significantly advance our understanding of the neurobiology of timing, and propose the establishment of a new society, the Timing Research Forum, to promote open science and collaborative work within the highly diverse and multidisciplinary community of researchers in the field of timing and time perception.
Rajendran VG, Teki S (2016)
Periodicity versus Prediction in Sensory Perception.
Journal of Neuroscience 36(28): 7343-7345 [link]
The importance of temporal expectation for sensory perception has been demonstrated across diverse paradigms and multiple modalities. Overall, the findings are consistent: temporal expectation results in greater encoding precision, higher perceptual sensitivity, and decreased response times during behavioral tasks. Temporal expectation itself can take several forms. “Controlled” expectation arises when a symbolic cue indicates that a stimulus will occur at a particular time in the future (Rohenkohl et al., 2012). Temporal expectations also arise through rhythmic sensory stimulation (McAuley and Jones, 2003). Finally, a form of “automatic” temporal expectation builds up over time if a sensory event is expected but precisely when it will occur is unknown (Nobre et al., 2007).
Periodicity versus Prediction in Sensory Perception.
Journal of Neuroscience 36(28): 7343-7345 [link]
The importance of temporal expectation for sensory perception has been demonstrated across diverse paradigms and multiple modalities. Overall, the findings are consistent: temporal expectation results in greater encoding precision, higher perceptual sensitivity, and decreased response times during behavioral tasks. Temporal expectation itself can take several forms. “Controlled” expectation arises when a symbolic cue indicates that a stimulus will occur at a particular time in the future (Rohenkohl et al., 2012). Temporal expectations also arise through rhythmic sensory stimulation (McAuley and Jones, 2003). Finally, a form of “automatic” temporal expectation builds up over time if a sensory event is expected but precisely when it will occur is unknown (Nobre et al., 2007).
Teki S, Barascud N, Picard S, Payne C, Griffiths TD, Chait M (2016)
Neural correlates of auditory figure-ground segregation based on temporal coherence.
Cerebral Cortex 26(9): 3369-80 [link]
To make sense of natural acoustic environments, listeners must parse complex mixtures of sounds that vary in frequency, space, and time. Emerging work suggests that, in addition to the well-studied spectral cues for segregation, sensitivity to temporal coherence—the coincidence of sound elements in and across time—is also critical for the perceptual organization of acoustic scenes. Here, we examine pre-attentive, stimulus-driven neural processes underlying auditory figure-ground segregation using stimuli that capture the challenges of listening in complex scenes where segregation cannot be achieved based on spectral cues alone. Signals (“stochastic figure-ground”: SFG) comprised a sequence of brief broadband chords containing random pure tone components that vary from 1 chord to another. Occasional tone repetitions across chords are perceived as “figures” popping out of a stochastic “ground.” Magnetoencephalography (MEG) measurement in naïve, distracted, human subjects revealed robust evoked responses, commencing from about 150 ms after figure onset that reflect the emergence of the “figure” from the randomly varying “ground.” Neural sources underlying this bottom-up driven figure-ground segregation were localized to planum temporale, and the intraparietal sulcus, demonstrating that this area, outside the “classic” auditory system, is also involved in the early stages of auditory scene analysis.”
Neural correlates of auditory figure-ground segregation based on temporal coherence.
Cerebral Cortex 26(9): 3369-80 [link]
To make sense of natural acoustic environments, listeners must parse complex mixtures of sounds that vary in frequency, space, and time. Emerging work suggests that, in addition to the well-studied spectral cues for segregation, sensitivity to temporal coherence—the coincidence of sound elements in and across time—is also critical for the perceptual organization of acoustic scenes. Here, we examine pre-attentive, stimulus-driven neural processes underlying auditory figure-ground segregation using stimuli that capture the challenges of listening in complex scenes where segregation cannot be achieved based on spectral cues alone. Signals (“stochastic figure-ground”: SFG) comprised a sequence of brief broadband chords containing random pure tone components that vary from 1 chord to another. Occasional tone repetitions across chords are perceived as “figures” popping out of a stochastic “ground.” Magnetoencephalography (MEG) measurement in naïve, distracted, human subjects revealed robust evoked responses, commencing from about 150 ms after figure onset that reflect the emergence of the “figure” from the randomly varying “ground.” Neural sources underlying this bottom-up driven figure-ground segregation were localized to planum temporale, and the intraparietal sulcus, demonstrating that this area, outside the “classic” auditory system, is also involved in the early stages of auditory scene analysis.”
Teki S, Griffiths TD (2016)
Brain bases of working memory for time intervals in rhythmic sequences.
Frontiers in Neuroscience 10: 239 (Special issue on The Evolution of Rhythm Cognition) [link]
Perception of auditory time intervals is critical for accurate comprehension of natural sounds like speech and music. However, the neural substrates and mechanisms underlying the representation of time intervals in working memory are poorly understood. In this study, we investigate the brain bases of working memory for time intervals in rhythmic sequences using functional magnetic resonance imaging. We used a novel behavioral paradigm to investigate time-interval representation in working memory as a function of the temporal jitter and memory load of the sequences containing those time intervals. Human participants were presented with a sequence of intervals and required to reproduce the duration of a particular probed interval. We found that perceptual timing areas including the cerebellum and the striatum were more or less active as a function of increasing and decreasing jitter of the intervals held in working memory respectively whilst the activity of the inferior parietal cortex is modulated as a function of memory load. Additionally, we also analyzed structural correlations between gray and white matter density and behavior and found significant correlations in the cerebellum and the striatum, mirroring the functional results. Our data demonstrate neural substrates of working memory for time intervals and suggest that the cerebellum and the striatum represent core areas for representing temporal information in working memory.
Brain bases of working memory for time intervals in rhythmic sequences.
Frontiers in Neuroscience 10: 239 (Special issue on The Evolution of Rhythm Cognition) [link]
Perception of auditory time intervals is critical for accurate comprehension of natural sounds like speech and music. However, the neural substrates and mechanisms underlying the representation of time intervals in working memory are poorly understood. In this study, we investigate the brain bases of working memory for time intervals in rhythmic sequences using functional magnetic resonance imaging. We used a novel behavioral paradigm to investigate time-interval representation in working memory as a function of the temporal jitter and memory load of the sequences containing those time intervals. Human participants were presented with a sequence of intervals and required to reproduce the duration of a particular probed interval. We found that perceptual timing areas including the cerebellum and the striatum were more or less active as a function of increasing and decreasing jitter of the intervals held in working memory respectively whilst the activity of the inferior parietal cortex is modulated as a function of memory load. Additionally, we also analyzed structural correlations between gray and white matter density and behavior and found significant correlations in the cerebellum and the striatum, mirroring the functional results. Our data demonstrate neural substrates of working memory for time intervals and suggest that the cerebellum and the striatum represent core areas for representing temporal information in working memory.
Teki S, Kumar S, Griffiths TD (2016)
Large-scale analysis of auditory segregation behavior crowdsourced via a smartphone app.
PLoS One 11(4): e0153916 [link]
The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders.
Large-scale analysis of auditory segregation behavior crowdsourced via a smartphone app.
PLoS One 11(4): e0153916 [link]
The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders.
Joseph S, Teki S, Kumar S, Husain M, Griffiths TD (2016)
Resource allocation models of auditory working memory.
Brain Research 1640: 183-192 (Special issue on Auditory working memory) [link]
Auditory working memory (WM) is the cognitive faculty that allows us to actively hold and manipulate sounds in mind over short periods of time. We develop here a particular perspective on WM for non-verbal, auditory objects as well as for time based on the consideration of possible parallels to visual WM. In vision, there has been a vigorous debate on whether WM capacity is limited to a fixed number of items or whether it represents a limited resource that can be allocated flexibly across items. Resource allocation models predict that the precision with which an item is represented decreases as a function of total number of items maintained in WM because a limited resource is shared among stored objects. We consider here auditory work on sequentially presented objects of different pitch as well as time intervals from the perspective of dynamic resource allocation. We consider whether the working memory resource might be determined by perceptual features such as pitch or timbre, or bound objects comprising multiple features, and we speculate on brain substrates for these behavioural models.
Resource allocation models of auditory working memory.
Brain Research 1640: 183-192 (Special issue on Auditory working memory) [link]
Auditory working memory (WM) is the cognitive faculty that allows us to actively hold and manipulate sounds in mind over short periods of time. We develop here a particular perspective on WM for non-verbal, auditory objects as well as for time based on the consideration of possible parallels to visual WM. In vision, there has been a vigorous debate on whether WM capacity is limited to a fixed number of items or whether it represents a limited resource that can be allocated flexibly across items. Resource allocation models predict that the precision with which an item is represented decreases as a function of total number of items maintained in WM because a limited resource is shared among stored objects. We consider here auditory work on sequentially presented objects of different pitch as well as time intervals from the perspective of dynamic resource allocation. We consider whether the working memory resource might be determined by perceptual features such as pitch or timbre, or bound objects comprising multiple features, and we speculate on brain substrates for these behavioural models.
Helbling S, Teki S, Callaghan MF, Sedley W, Mohammadi S, Griffiths TD, Weiskopf N, Barnes GR (2015)
Structure predicts function: combining non-invasive electrophysiology with in-vivo histology.
NeuroImage 108: 377-385 [link]
We present an approach for combining high resolution MRI-based myelin mapping with functional information from electroencephalography (EEG) or magnetoencephalography(MEG). The main contribution to the primary currents detectable with EEG and MEG comes from ionic currents in the apical dendrites of cortical pyramidal cells, aligned perpendicularly to the local cortical surface. We provide evidence from an in-vivo experiment that the variation in MRI-based myeloarchitecture measures across the cortex predicts the variation of the current density over individuals and thus is of functional relevance. Equivalent current dipole locations and moments due to pitch onset evoked response fields (ERFs) were estimated by means of a variational Bayesian algorithm. The myeloarchitecture was estimated indirectly from individual high resolution quantitative multi-parameter maps (MPMs) acquired at 800 μm isotropic resolution. Myelin estimates across cortical areas correlated positively with dipole magnitude. This correlation was spatially specific: regions of interest in the auditory cortex provided significantly better models than those covering whole hemispheres. Based on the MPM data we identified the auditory cortical area TE1.2 as the most likely origin of the pitch ERFs measured by MEG. We can now proceed to exploit the higher spatial resolution of quantitative MPMs to identify the cortical origin of M/EEG signals, inform M/EEG source reconstruction and explore structure–function relationships at a fine structural level in the living human brain.
Structure predicts function: combining non-invasive electrophysiology with in-vivo histology.
NeuroImage 108: 377-385 [link]
We present an approach for combining high resolution MRI-based myelin mapping with functional information from electroencephalography (EEG) or magnetoencephalography(MEG). The main contribution to the primary currents detectable with EEG and MEG comes from ionic currents in the apical dendrites of cortical pyramidal cells, aligned perpendicularly to the local cortical surface. We provide evidence from an in-vivo experiment that the variation in MRI-based myeloarchitecture measures across the cortex predicts the variation of the current density over individuals and thus is of functional relevance. Equivalent current dipole locations and moments due to pitch onset evoked response fields (ERFs) were estimated by means of a variational Bayesian algorithm. The myeloarchitecture was estimated indirectly from individual high resolution quantitative multi-parameter maps (MPMs) acquired at 800 μm isotropic resolution. Myelin estimates across cortical areas correlated positively with dipole magnitude. This correlation was spatially specific: regions of interest in the auditory cortex provided significantly better models than those covering whole hemispheres. Based on the MPM data we identified the auditory cortical area TE1.2 as the most likely origin of the pitch ERFs measured by MEG. We can now proceed to exploit the higher spatial resolution of quantitative MPMs to identify the cortical origin of M/EEG signals, inform M/EEG source reconstruction and explore structure–function relationships at a fine structural level in the living human brain.
Teki S, Griffiths TD (2014)
Working memory for time intervals in rhythmic auditory sequences.
Frontiers in Auditory Cognitive Neuroscience 5: 1329 (Special issue on Functions of Musical Rhythm) [link]
The brain can hold information about multiple objects in working memory. It is not known, however, whether intervals of time can be stored in memory as distinct items. Here, we developed a novel paradigm to examine temporal memory where listeners were required to reproduce the duration of a single probed interval from a sequence of intervals. We demonstrate that memory performance significantly varies as a function of temporal structure (better memory in regular vs. irregular sequences), interval size (better memory for sub- vs. supra-second intervals), and memory load (poor memory for higher load). In contrast memory performance is invariant to attentional cueing. Our data represent the first systematic investigation of temporal memory in sequences that goes beyond previous work based on single intervals. The results support the emerging hypothesis that time intervals are allocated a working memory resource that varies with the amount of other temporal information in a sequence.
Working memory for time intervals in rhythmic auditory sequences.
Frontiers in Auditory Cognitive Neuroscience 5: 1329 (Special issue on Functions of Musical Rhythm) [link]
The brain can hold information about multiple objects in working memory. It is not known, however, whether intervals of time can be stored in memory as distinct items. Here, we developed a novel paradigm to examine temporal memory where listeners were required to reproduce the duration of a single probed interval from a sequence of intervals. We demonstrate that memory performance significantly varies as a function of temporal structure (better memory in regular vs. irregular sequences), interval size (better memory for sub- vs. supra-second intervals), and memory load (poor memory for higher load). In contrast memory performance is invariant to attentional cueing. Our data represent the first systematic investigation of temporal memory in sequences that goes beyond previous work based on single intervals. The results support the emerging hypothesis that time intervals are allocated a working memory resource that varies with the amount of other temporal information in a sequence.
Teki S (2014)
Beta drives brain beats.
Frontiers in Systems Neuroscience 8: 155 [link]
Beta-band oscillations in basal ganglia-cortical loops have been shown to be linked to motor function in both healthy and pathological states (Brown, 2007; Engel and Fries, 2010). As well as coordinating motor activity, for instance when we synchronize our movements to a beat, the basal ganglia including the putamen and the caudate are said to contain specialized timekeeping mechanisms for perceptual timing (Buhusi and Meck, 2005). However, the exact neurophysiological role of beta-band oscillatory activity in the striatum in interval timing is not yet known.
Beta drives brain beats.
Frontiers in Systems Neuroscience 8: 155 [link]
Beta-band oscillations in basal ganglia-cortical loops have been shown to be linked to motor function in both healthy and pathological states (Brown, 2007; Engel and Fries, 2010). As well as coordinating motor activity, for instance when we synchronize our movements to a beat, the basal ganglia including the putamen and the caudate are said to contain specialized timekeeping mechanisms for perceptual timing (Buhusi and Meck, 2005). However, the exact neurophysiological role of beta-band oscillatory activity in the striatum in interval timing is not yet known.
Kumar S, Bonnici H, Teki S, Agus TR, Pressnitzer D, Maguire EA, Griffiths TD (2014)
Representations of Specific Acoustic Patterns in the Auditory Cortex and Hippocampus.
Proceedings of the Royal Society B 281, 20141000 [link]
Previous behavioural studies have shown that repeated presentation of a randomly chosen acoustic pattern leads to the unsupervised learning of some of its specific acoustic features. The objective of our study was to determine the neural substrate for the representation of freshly learnt acoustic patterns. Subjects first performed a behavioural task that resulted in the incidental learning of three different noise-like acoustic patterns. During subsequent high-resolution functional magnetic resonance imaging scanning, subjects were then exposed again to these three learnt patterns and to others that had not been learned. Multi-voxel pattern analysis was used to test if the learnt acoustic patterns could be ‘decoded’ from the patterns of activity in the auditory cortex and medial temporal lobe. We found that activity in planum temporale and the hippocampus reliably distinguished between the learnt acoustic patterns. Our results demonstrate that these structures are involved in the neural representation of specific acoustic patterns after they have been learnt.
Representations of Specific Acoustic Patterns in the Auditory Cortex and Hippocampus.
Proceedings of the Royal Society B 281, 20141000 [link]
Previous behavioural studies have shown that repeated presentation of a randomly chosen acoustic pattern leads to the unsupervised learning of some of its specific acoustic features. The objective of our study was to determine the neural substrate for the representation of freshly learnt acoustic patterns. Subjects first performed a behavioural task that resulted in the incidental learning of three different noise-like acoustic patterns. During subsequent high-resolution functional magnetic resonance imaging scanning, subjects were then exposed again to these three learnt patterns and to others that had not been learned. Multi-voxel pattern analysis was used to test if the learnt acoustic patterns could be ‘decoded’ from the patterns of activity in the auditory cortex and medial temporal lobe. We found that activity in planum temporale and the hippocampus reliably distinguished between the learnt acoustic patterns. Our results demonstrate that these structures are involved in the neural representation of specific acoustic patterns after they have been learnt.
Kumar S, Sedley W, Barnes GR, Teki S, Friston KJ, Griffiths TD (2014)
A brain basis for musical hallucinations.
Cortex 52: 86-97 [link]
The physiological basis for musical hallucinations (MH) is not understood. One obstacle to understanding has been the lack of a method to manipulate the intensity of hallucination during the course of experiment. Residual inhibition, transient suppression of a phantom percept after the offset of a masking stimulus, has been used in the study of tinnitus. We report here a human subject whose MH were residually inhibited by short periods of music. Magnetoencephalography (MEG) allowed us to examine variation in the underlying oscillatory brain activity in different states. Source-space analysis capable of single-subject inference defined left-lateralised power increases, associated with stronger hallucinations, in the gamma band in left anterior superior temporal gyrus, and in the beta band in motor cortex and posteromedial cortex. The data indicate that these areas form a crucial network in the generation of MH, and are consistent with a model in which MH are generated by persistent reciprocal communication in a predictive coding hierarchy.
A brain basis for musical hallucinations.
Cortex 52: 86-97 [link]
The physiological basis for musical hallucinations (MH) is not understood. One obstacle to understanding has been the lack of a method to manipulate the intensity of hallucination during the course of experiment. Residual inhibition, transient suppression of a phantom percept after the offset of a masking stimulus, has been used in the study of tinnitus. We report here a human subject whose MH were residually inhibited by short periods of music. Magnetoencephalography (MEG) allowed us to examine variation in the underlying oscillatory brain activity in different states. Source-space analysis capable of single-subject inference defined left-lateralised power increases, associated with stronger hallucinations, in the gamma band in left anterior superior temporal gyrus, and in the beta band in motor cortex and posteromedial cortex. The data indicate that these areas form a crucial network in the generation of MH, and are consistent with a model in which MH are generated by persistent reciprocal communication in a predictive coding hierarchy.
Allman MJ, Teki S, Griffiths TD, Meck WH (2014)
Properties of the Internal Clock: First- and Second-Order Principles of Subjective Time.
Annual Review of Psychology 65: 743-71 [link]
Humans share with other animals an ability to measure the passage of physical time and subjectively experience a sense of time passing. Subjective time has hallmark qualities, akin to other senses, which can be accounted for by formal, psychological, and neurobiological models of the internal clock. These include first-order principles, such as changes in clock speed and how temporal memories are stored, and second-order principles, including timescale invariance, multisensory integration, rhythmical structure, and attentional time-sharing. Within these principles there are both typical individual differences—influences of emotionality, thought speed, and psychoactive drugs—and atypical differences in individuals affected with certain clinical disorders (e.g., autism, Parkinson's disease, and schizophrenia). This review summarizes recent behavioral and neurobiological findings and provides a theoretical framework for considering how changes in the properties of the internal clock impact time perception and other psychological domains.
Properties of the Internal Clock: First- and Second-Order Principles of Subjective Time.
Annual Review of Psychology 65: 743-71 [link]
Humans share with other animals an ability to measure the passage of physical time and subjectively experience a sense of time passing. Subjective time has hallmark qualities, akin to other senses, which can be accounted for by formal, psychological, and neurobiological models of the internal clock. These include first-order principles, such as changes in clock speed and how temporal memories are stored, and second-order principles, including timescale invariance, multisensory integration, rhythmical structure, and attentional time-sharing. Within these principles there are both typical individual differences—influences of emotionality, thought speed, and psychoactive drugs—and atypical differences in individuals affected with certain clinical disorders (e.g., autism, Parkinson's disease, and schizophrenia). This review summarizes recent behavioral and neurobiological findings and provides a theoretical framework for considering how changes in the properties of the internal clock impact time perception and other psychological domains.
Woodhead Z, Barnes GR, Penny W, Moran RJ, Teki S, Price CJ, Leff AP (2014)
Reading front to back: MEG evidence for early feedback effects during word recognition.
Cerebral Cortex 24(3): 817-25 [link]
Magnetoencephalography studies in humans have shown word-selective activity in the left inferior frontal gyrus (IFG) approximately 130 ms after word presentation ( Pammer et al. 2004; Cornelissen et al. 2009; Wheat et al. 2010). The role of this early frontal response is currently not known. We tested the hypothesis that the IFG provides top-down constraints on word recognition using dynamic causal modeling of magnetoencephalography data collected, while subjects viewed written words and false font stimuli. Subject-specific dipoles in left and right occipital, ventral occipitotemporal and frontal cortices were identified using Variational Bayesian Equivalent Current Dipole source reconstruction. A connectivity analysis tested how words and false font stimuli differentially modulated activity between these regions within the first 300 ms after stimulus presentation. We found that left inferior frontal activity showed stronger sensitivity to words than false font and a stronger feedback connection onto the left ventral occipitotemporal cortex (vOT) in the first 200 ms. Subsequently, the effect of words relative to false font was observed on feedforward connections from left occipital to ventral occipitotemporal and frontal regions. These findings demonstrate that left inferior frontal activity modulates vOT in the early stages of word processing and provides a mechanistic account of top-down effects during word recognition.
Reading front to back: MEG evidence for early feedback effects during word recognition.
Cerebral Cortex 24(3): 817-25 [link]
Magnetoencephalography studies in humans have shown word-selective activity in the left inferior frontal gyrus (IFG) approximately 130 ms after word presentation ( Pammer et al. 2004; Cornelissen et al. 2009; Wheat et al. 2010). The role of this early frontal response is currently not known. We tested the hypothesis that the IFG provides top-down constraints on word recognition using dynamic causal modeling of magnetoencephalography data collected, while subjects viewed written words and false font stimuli. Subject-specific dipoles in left and right occipital, ventral occipitotemporal and frontal cortices were identified using Variational Bayesian Equivalent Current Dipole source reconstruction. A connectivity analysis tested how words and false font stimuli differentially modulated activity between these regions within the first 300 ms after stimulus presentation. We found that left inferior frontal activity showed stronger sensitivity to words than false font and a stronger feedback connection onto the left ventral occipitotemporal cortex (vOT) in the first 200 ms. Subsequently, the effect of words relative to false font was observed on feedforward connections from left occipital to ventral occipitotemporal and frontal regions. These findings demonstrate that left inferior frontal activity modulates vOT in the early stages of word processing and provides a mechanistic account of top-down effects during word recognition.
Teki S, Chait M, Kumar S, Shamma S, Griffiths TD (2013)
Segregation of complex acoustic scenes based on temporal coherence.
eLife 2: e00699 [link]
In contrast to the complex acoustic environments we encounter everyday, most studies of auditory segregation have used relatively simple signals. Here, we synthesized a new stimulus to examine the detection of coherent patterns (‘figures’) from overlapping ‘background’ signals. In a series of experiments, we demonstrate that human listeners are remarkably sensitive to the emergence of such figures and can tolerate a variety of spectral and temporal perturbations. This robust behavior is consistent with the existence of automatic auditory segregation mechanisms that are highly sensitive to correlations across frequency and time. The observed behavior cannot be explained purely on the basis of adaptation-based models used to explain the segregation of deterministic narrowband signals. We show that the present results are consistent with the predictions of a model of auditory perceptual organization based on temporal coherence. Our data thus support a role for temporal coherence as an organizational principle underlying auditory segregation.
Segregation of complex acoustic scenes based on temporal coherence.
eLife 2: e00699 [link]
In contrast to the complex acoustic environments we encounter everyday, most studies of auditory segregation have used relatively simple signals. Here, we synthesized a new stimulus to examine the detection of coherent patterns (‘figures’) from overlapping ‘background’ signals. In a series of experiments, we demonstrate that human listeners are remarkably sensitive to the emergence of such figures and can tolerate a variety of spectral and temporal perturbations. This robust behavior is consistent with the existence of automatic auditory segregation mechanisms that are highly sensitive to correlations across frequency and time. The observed behavior cannot be explained purely on the basis of adaptation-based models used to explain the segregation of deterministic narrowband signals. We show that the present results are consistent with the predictions of a model of auditory perceptual organization based on temporal coherence. Our data thus support a role for temporal coherence as an organizational principle underlying auditory segregation.
Teki S, Barnes GR, Penny W, Iverson PI, Woodhead Z, Griffiths TD, Leff AP (2013)
The right hemisphere supports but does not replace left hemisphere function in patients with persisting aphasia.
Brain 136(6): 1901-1912 [link]
In this study, we used magnetoencephalography and a mismatch paradigm to investigate speech processing in stroke patients with auditory comprehension deficits and age-matched control subjects. We probed connectivity within and between the two temporal lobes in response to phonemic (different word) and acoustic (same word) oddballs using dynamic causal modelling. We found stronger modulation of self-connections as a function of phonemic differences for control subjects versus aphasics in left primary auditory cortex and bilateral superior temporal gyrus. The patients showed stronger modulation of connections from right primary auditory cortex to right superior temporal gyrus (feed-forward) and from left primary auditory cortex to right primary auditory cortex (interhemispheric). This differential connectivity can be explained on the basis of a predictive coding theory which suggests increased prediction error and decreased sensitivity to phonemic boundaries in the aphasics’ speech network in both hemispheres. Within the aphasics, we also found behavioural correlates with connection strengths: a negative correlation between phonemic perception and an inter-hemispheric connection (left superior temporal gyrus to right superior temporal gyrus), and positive correlation between semantic performance and a feedback connection (right superior temporal gyrus to right primary auditory cortex). Our results suggest that aphasics with impaired speech comprehension have less veridical speech representations in both temporal lobes, and rely more on the right hemisphere auditory regions, particularly right superior temporal gyrus, for processing speech. Despite this presumed compensatory shift in network connectivity, the patients remain significantly impaired.
The right hemisphere supports but does not replace left hemisphere function in patients with persisting aphasia.
Brain 136(6): 1901-1912 [link]
In this study, we used magnetoencephalography and a mismatch paradigm to investigate speech processing in stroke patients with auditory comprehension deficits and age-matched control subjects. We probed connectivity within and between the two temporal lobes in response to phonemic (different word) and acoustic (same word) oddballs using dynamic causal modelling. We found stronger modulation of self-connections as a function of phonemic differences for control subjects versus aphasics in left primary auditory cortex and bilateral superior temporal gyrus. The patients showed stronger modulation of connections from right primary auditory cortex to right superior temporal gyrus (feed-forward) and from left primary auditory cortex to right primary auditory cortex (interhemispheric). This differential connectivity can be explained on the basis of a predictive coding theory which suggests increased prediction error and decreased sensitivity to phonemic boundaries in the aphasics’ speech network in both hemispheres. Within the aphasics, we also found behavioural correlates with connection strengths: a negative correlation between phonemic perception and an inter-hemispheric connection (left superior temporal gyrus to right superior temporal gyrus), and positive correlation between semantic performance and a feedback connection (right superior temporal gyrus to right primary auditory cortex). Our results suggest that aphasics with impaired speech comprehension have less veridical speech representations in both temporal lobes, and rely more on the right hemisphere auditory regions, particularly right superior temporal gyrus, for processing speech. Despite this presumed compensatory shift in network connectivity, the patients remain significantly impaired.
Kumar S, Joseph S, Pearson B, Teki S, Griffiths TD, Husain M (2013)
Resource allocation and prioritization in auditory working memory.
Cognitive Neuroscience 4(1): 12-20 [link]
A prevalent view of working memory (WM) considers it to be capacity-limited, fixed to a set number of items. However, recent shared resource models of WM have challenged this “quantized” account using measures of recall precision. Although this conceptual framework can account for several features of visual WM, it remains to be established whether it also applies to auditory WM.
We used a novel pitch-matching paradigm to probe participants' memory of pure tones in sequences of varying length, and measured their precision of recall. Crucially, this provides an index of the variability of memory representation around its true value, rather than a binary “yes/no” recall measure typically used in change detection paradigms. We show that precision of auditory WM varies with both memory load and serial order. Moreover, auditory WM resources can be prioritized to cued items, improving precision of recall, but with a concomitant cost to other items, consistent with a resource model account.
Resource allocation and prioritization in auditory working memory.
Cognitive Neuroscience 4(1): 12-20 [link]
A prevalent view of working memory (WM) considers it to be capacity-limited, fixed to a set number of items. However, recent shared resource models of WM have challenged this “quantized” account using measures of recall precision. Although this conceptual framework can account for several features of visual WM, it remains to be established whether it also applies to auditory WM.
We used a novel pitch-matching paradigm to probe participants' memory of pure tones in sequences of varying length, and measured their precision of recall. Crucially, this provides an index of the variability of memory representation around its true value, rather than a binary “yes/no” recall measure typically used in change detection paradigms. We show that precision of auditory WM varies with both memory load and serial order. Moreover, auditory WM resources can be prioritized to cued items, improving precision of recall, but with a concomitant cost to other items, consistent with a resource model account.
Sedley W, Teki S, Kumar S, Barnes GR, Bamiou D-E, Griffiths TD (2012)
Single subject oscillatory gamma responses in tinnitus.
Brain 135(10): 3089-3100 [link]
This study used magnetoencephalography to record oscillatory activity in a group of 17 patients with chronic tinnitus. Two methods, residual inhibition and residual excitation, were used to bring about transient changes in spontaneous tinnitus intensity in order to measure dynamic tinnitus correlates in individual patients. In residual inhibition, a positive correlation was seen between tinnitus intensity and both delta/theta (6/14 patients) and gamma band (8/14 patients) oscillations in auditory cortex, suggesting an increased thalamocortical input and cortical gamma response, respectively, associated with higher tinnitus states. Conversely, 4/4 patients exhibiting residual excitation demonstrated an inverse correlation between perceived tinnitus intensity and auditory cortex gamma oscillations (with no delta/theta changes) that cannot be explained by existing models. Significant oscillatory power changes were also identified in a variety of cortical regions, most commonly midline lobar regions in the default mode network, cerebellum, insula and anterior temporal lobe. These were highly variable across patients in terms of areas and frequency bands involved, and in direction of power change. We suggest a model based on a local circuit function of cortical gamma-band oscillations as a process of mutual inhibition that might suppress abnormal cortical activity in tinnitus. The work implicates auditory cortex gamma-band oscillations as a fundamental intrinsic mechanism for attenuating phantom auditory perception.
Single subject oscillatory gamma responses in tinnitus.
Brain 135(10): 3089-3100 [link]
This study used magnetoencephalography to record oscillatory activity in a group of 17 patients with chronic tinnitus. Two methods, residual inhibition and residual excitation, were used to bring about transient changes in spontaneous tinnitus intensity in order to measure dynamic tinnitus correlates in individual patients. In residual inhibition, a positive correlation was seen between tinnitus intensity and both delta/theta (6/14 patients) and gamma band (8/14 patients) oscillations in auditory cortex, suggesting an increased thalamocortical input and cortical gamma response, respectively, associated with higher tinnitus states. Conversely, 4/4 patients exhibiting residual excitation demonstrated an inverse correlation between perceived tinnitus intensity and auditory cortex gamma oscillations (with no delta/theta changes) that cannot be explained by existing models. Significant oscillatory power changes were also identified in a variety of cortical regions, most commonly midline lobar regions in the default mode network, cerebellum, insula and anterior temporal lobe. These were highly variable across patients in terms of areas and frequency bands involved, and in direction of power change. We suggest a model based on a local circuit function of cortical gamma-band oscillations as a process of mutual inhibition that might suppress abnormal cortical activity in tinnitus. The work implicates auditory cortex gamma-band oscillations as a fundamental intrinsic mechanism for attenuating phantom auditory perception.
Teki S, Kumar S, von Kriegstein K, Stewart L, Lyness CR, Moore BCJ, Capleton B, Griffiths TD (2012)
Navigating the auditory scene: an expert role for the hippocampus.
Journal of Neuroscience 32(35): 12251-12257 [link]
Over a typical career piano tuners spend tens of thousands of hours exploring a specialized acoustic environment. Tuning requires accurate perception and adjustment of beats in two-note chords that serve as a navigational device to move between points in previously learned acoustic scenes. It is a two-stage process that depends on the following: first, selective listening to beats within frequency windows, and, second, the subsequent use of those beats to navigate through a complex soundscape. The neuroanatomical substrates underlying brain specialization for such fundamental organization of sound scenes are unknown.
Here, we demonstrate that professional piano tuners are significantly better than controls matched for age and musical ability on a psychophysical task simulating active listening to beats within frequency windows that is based on amplitude modulation rate discrimination. Tuners show a categorical increase in gray matter volume in the right frontal operculum and right superior temporal lobe. Tuners also show a striking enhancement of gray matter volume in the anterior hippocampus, parahippocampal gyrus, and superior temporal gyrus, and an increase in white matter volume in the posterior hippocampus as a function of years of tuning experience. The relationship with gray matter volume is sensitive to years of tuning experience and starting age but not actual age or level of musicality. Our findings support a role for a core set of regions in the hippocampus and superior temporal cortex in skilled exploration of complex sound scenes in which precise sound “templates” are encoded and consolidated into memory over time in an experience-dependent manner.
Navigating the auditory scene: an expert role for the hippocampus.
Journal of Neuroscience 32(35): 12251-12257 [link]
Over a typical career piano tuners spend tens of thousands of hours exploring a specialized acoustic environment. Tuning requires accurate perception and adjustment of beats in two-note chords that serve as a navigational device to move between points in previously learned acoustic scenes. It is a two-stage process that depends on the following: first, selective listening to beats within frequency windows, and, second, the subsequent use of those beats to navigate through a complex soundscape. The neuroanatomical substrates underlying brain specialization for such fundamental organization of sound scenes are unknown.
Here, we demonstrate that professional piano tuners are significantly better than controls matched for age and musical ability on a psychophysical task simulating active listening to beats within frequency windows that is based on amplitude modulation rate discrimination. Tuners show a categorical increase in gray matter volume in the right frontal operculum and right superior temporal lobe. Tuners also show a striking enhancement of gray matter volume in the anterior hippocampus, parahippocampal gyrus, and superior temporal gyrus, and an increase in white matter volume in the posterior hippocampus as a function of years of tuning experience. The relationship with gray matter volume is sensitive to years of tuning experience and starting age but not actual age or level of musicality. Our findings support a role for a core set of regions in the hippocampus and superior temporal cortex in skilled exploration of complex sound scenes in which precise sound “templates” are encoded and consolidated into memory over time in an experience-dependent manner.
Teki S, Grube M, Griffiths TD (2012)
A unified model of time perception accounts for duration-based and beat-based timing mechanisms.
Frontiers in Integrative Neuroscience 5: 90 (Special issue on Interval Timing & Time-based Decision Making) [link]
Accurate timing is an integral aspect of sensory and motor processes such as the perception of speech and music and the execution of skilled movement. Neuropsychological studies of time perception in patient groups and functional neuroimaging studies of timing in normal participants suggest common neural substrates for perceptual and motor timing. A timing system is implicated in core regions of the motor network such as the cerebellum, inferior olive, basal ganglia, pre-supplementary, and supplementary motor area, pre-motor cortex as well as higher-level areas such as the prefrontal cortex. In this article, we assess how distinct parts of the timing system subserve different aspects of perceptual timing. We previously established brain bases for absolute, duration-based timing and relative, beat-based timing in the olivocerebellar and striato-thalamo-cortical circuits respectively (Teki et al., 2011). However, neurophysiological and neuroanatomical studies provide a basis to suggest that timing functions of these circuits may not be independent. Here, we propose a unified model of time perception based on coordinated activity in the core striatal and olivocerebellar networks that are interconnected with each other and the cerebral cortex through multiple synaptic pathways. Timing in this unified model is proposed to involve serial beat-based striatal activation followed by absolute olivocerebellar timing mechanisms.
A unified model of time perception accounts for duration-based and beat-based timing mechanisms.
Frontiers in Integrative Neuroscience 5: 90 (Special issue on Interval Timing & Time-based Decision Making) [link]
Accurate timing is an integral aspect of sensory and motor processes such as the perception of speech and music and the execution of skilled movement. Neuropsychological studies of time perception in patient groups and functional neuroimaging studies of timing in normal participants suggest common neural substrates for perceptual and motor timing. A timing system is implicated in core regions of the motor network such as the cerebellum, inferior olive, basal ganglia, pre-supplementary, and supplementary motor area, pre-motor cortex as well as higher-level areas such as the prefrontal cortex. In this article, we assess how distinct parts of the timing system subserve different aspects of perceptual timing. We previously established brain bases for absolute, duration-based timing and relative, beat-based timing in the olivocerebellar and striato-thalamo-cortical circuits respectively (Teki et al., 2011). However, neurophysiological and neuroanatomical studies provide a basis to suggest that timing functions of these circuits may not be independent. Here, we propose a unified model of time perception based on coordinated activity in the core striatal and olivocerebellar networks that are interconnected with each other and the cerebral cortex through multiple synaptic pathways. Timing in this unified model is proposed to involve serial beat-based striatal activation followed by absolute olivocerebellar timing mechanisms.
Sedley W, Teki S, Kumar S, Overath T, Barnes GR, Griffiths TD (2012)
Gamma band pitch responses in human auditory cortex measured with magnetoencephalography.
NeuroImage 59(2): 1904-1911 [link]
We have previously used direct electrode recordings in two human subjects to identify neural correlates of the perception of pitch (Griffiths, Kumar, Sedley et al., Direct recordings of pitch responses from human auditory cortex, Curr. Biol. 22 (2010), pp. 1128–1132). The present study was carried out to assess virtual-electrode measures of pitch perception based on non-invasive magnetoencephalography (MEG). We recorded pitch responses in 13 healthy volunteers using a passive listening paradigm and the same pitch-evoking stimuli (regular interval noise; RIN) as in the previous study. Source activity was reconstructed using a beamformer approach, which was used to place virtual electrodes in auditory cortex. Time-frequency decomposition of these data revealed oscillatory responses to pitch in the gamma frequency band to occur, in Heschl's gyrus, from 60 Hz upwards. Direct comparison of these pitch responses to the previous depth electrode recordings shows a striking congruence in terms of spectrotemporal profile and anatomical distribution. These findings provide further support that auditory high gamma oscillations occur in association with RIN pitch stimuli, and validate the use of MEG to assess neural correlates of normal and abnormal pitch perception.
Gamma band pitch responses in human auditory cortex measured with magnetoencephalography.
NeuroImage 59(2): 1904-1911 [link]
We have previously used direct electrode recordings in two human subjects to identify neural correlates of the perception of pitch (Griffiths, Kumar, Sedley et al., Direct recordings of pitch responses from human auditory cortex, Curr. Biol. 22 (2010), pp. 1128–1132). The present study was carried out to assess virtual-electrode measures of pitch perception based on non-invasive magnetoencephalography (MEG). We recorded pitch responses in 13 healthy volunteers using a passive listening paradigm and the same pitch-evoking stimuli (regular interval noise; RIN) as in the previous study. Source activity was reconstructed using a beamformer approach, which was used to place virtual electrodes in auditory cortex. Time-frequency decomposition of these data revealed oscillatory responses to pitch in the gamma frequency band to occur, in Heschl's gyrus, from 60 Hz upwards. Direct comparison of these pitch responses to the previous depth electrode recordings shows a striking congruence in terms of spectrotemporal profile and anatomical distribution. These findings provide further support that auditory high gamma oscillations occur in association with RIN pitch stimuli, and validate the use of MEG to assess neural correlates of normal and abnormal pitch perception.
Teki S, Grube M, Kumar S, Griffiths TD (2011)
Distinct neural substrates of duration-based and beat-based auditory timing.
Journal of Neuroscience 31(10): 3805-3812 [link]
Research on interval timing strongly implicates the cerebellum and the basal ganglia as part of the timing network of the brain. Here we tested the hypothesis that the brain uses differential timing mechanisms and networks—specifically, that the cerebellum subserves the perception of the absolute duration of time intervals, whereas the basal ganglia mediate perception of time intervals relative to a regular beat.
In a functional magnetic resonance imaging experiment, we asked human subjects to judge the difference in duration of two successive time intervals as a function of the preceding context of an irregular sequence of clicks (where the task relies on encoding the absolute duration of time intervals) or a regular sequence of clicks (where the regular beat provides an extra cue for relative timing). We found significant activations in an olivocerebellar network comprising the inferior olive, vermis, and deep cerebellar nuclei including the dentate nucleus during absolute, duration-based timing and a striato-thalamo-cortical network comprising the putamen, caudate nucleus, thalamus, supplementary motor area, premotor cortex, and dorsolateral prefrontal cortex during relative, beat-based timing. Our results support two distinct timing mechanisms and underlying subsystems: first, a network comprising the inferior olive and the cerebellum that acts as a precision clock to mediate absolute, duration-based timing, and second, a distinct network for relative, beat-based timing incorporating a striato-thalamo-cortical network.
Distinct neural substrates of duration-based and beat-based auditory timing.
Journal of Neuroscience 31(10): 3805-3812 [link]
Research on interval timing strongly implicates the cerebellum and the basal ganglia as part of the timing network of the brain. Here we tested the hypothesis that the brain uses differential timing mechanisms and networks—specifically, that the cerebellum subserves the perception of the absolute duration of time intervals, whereas the basal ganglia mediate perception of time intervals relative to a regular beat.
In a functional magnetic resonance imaging experiment, we asked human subjects to judge the difference in duration of two successive time intervals as a function of the preceding context of an irregular sequence of clicks (where the task relies on encoding the absolute duration of time intervals) or a regular sequence of clicks (where the regular beat provides an extra cue for relative timing). We found significant activations in an olivocerebellar network comprising the inferior olive, vermis, and deep cerebellar nuclei including the dentate nucleus during absolute, duration-based timing and a striato-thalamo-cortical network comprising the putamen, caudate nucleus, thalamus, supplementary motor area, premotor cortex, and dorsolateral prefrontal cortex during relative, beat-based timing. Our results support two distinct timing mechanisms and underlying subsystems: first, a network comprising the inferior olive and the cerebellum that acts as a precision clock to mediate absolute, duration-based timing, and second, a distinct network for relative, beat-based timing incorporating a striato-thalamo-cortical network.
Teki S, Chait M, Kumar S, von Kriegstein K, Griffiths TD (2011)
Brain bases for auditory stimulus-driven, figure-ground segregation.
Journal of Neuroscience 31(1): 164-171 [link]
Auditory figure–ground segregation, listeners' ability to selectively hear out a sound of interest from a background of competing sounds, is a fundamental aspect of scene analysis. In contrast to the disordered acoustic environment we experience during everyday listening, most studies of auditory segregation have used relatively simple, temporally regular signals. We developed a new figure–ground stimulus that incorporates stochastic variation of the figure and background that captures the rich spectrotemporal complexity of natural acoustic scenes. Figure and background signals overlap in spectrotemporal space, but vary in the statistics of fluctuation, such that the only way to extract the figure is by integrating the patterns over time and frequency. Our behavioral results demonstrate that human listeners are remarkably sensitive to the appearance of such figures.
In a functional magnetic resonance imaging experiment, aimed at investigating preattentive, stimulus-driven, auditory segregation mechanisms, naive subjects listened to these stimuli while performing an irrelevant task. Results demonstrate significant activations in the intraparietal sulcus (IPS) and the superior temporal sulcus related to bottom-up, stimulus-driven figure–ground decomposition. We did not observe any significant activation in the primary auditory cortex. Our results support a role for automatic, bottom-up mechanisms in the IPS in mediating stimulus-driven, auditory figure–ground segregation, which is consistent with accumulating evidence implicating the IPS in structuring sensory input and perceptual organization.
Brain bases for auditory stimulus-driven, figure-ground segregation.
Journal of Neuroscience 31(1): 164-171 [link]
Auditory figure–ground segregation, listeners' ability to selectively hear out a sound of interest from a background of competing sounds, is a fundamental aspect of scene analysis. In contrast to the disordered acoustic environment we experience during everyday listening, most studies of auditory segregation have used relatively simple, temporally regular signals. We developed a new figure–ground stimulus that incorporates stochastic variation of the figure and background that captures the rich spectrotemporal complexity of natural acoustic scenes. Figure and background signals overlap in spectrotemporal space, but vary in the statistics of fluctuation, such that the only way to extract the figure is by integrating the patterns over time and frequency. Our behavioral results demonstrate that human listeners are remarkably sensitive to the appearance of such figures.
In a functional magnetic resonance imaging experiment, aimed at investigating preattentive, stimulus-driven, auditory segregation mechanisms, naive subjects listened to these stimuli while performing an irrelevant task. Results demonstrate significant activations in the intraparietal sulcus (IPS) and the superior temporal sulcus related to bottom-up, stimulus-driven figure–ground decomposition. We did not observe any significant activation in the primary auditory cortex. Our results support a role for automatic, bottom-up mechanisms in the IPS in mediating stimulus-driven, auditory figure–ground segregation, which is consistent with accumulating evidence implicating the IPS in structuring sensory input and perceptual organization.
Karayannis T, Elfant D, Huerta-Ocampo I, Teki S, Scott R, Rusakov D, Jones MV, Capogna M (2010)
Receptor desensitization shapes synaptic responses evoked by hippocampal neurogliaform cells.
Journal of Neuroscience 30(29): 9898-9909 [link]
The kinetics of GABAergic synaptic currents can vary by an order of magnitude depending on the cell type. The neurogliaform cell (NGFC) has recently been identified as a key generator of slow GABAAreceptor-mediated volume transmission in the isocortex. However, the mechanisms underlying slow GABAA receptor-mediated IPSCs and their use-dependent plasticity remain unknown. Here, we provide experimental and modeling data showing that hippocampal NGFCs generate an unusually prolonged (tens of milliseconds) but low-concentration (micromolar range) GABA transient, which is responsible for the slow response kinetics and which leads to a robust desensitization of postsynaptic GABAA receptors. This strongly contributes to the use-dependent synaptic depression elicited by various patterns of NGFC activity including the one detected during theta network oscillations in vivo. Synaptic depression mediated by NGFCs is likely to play an important modulatory role in the feedforward inhibition of CA1 pyramidal cells provided by the entorhinal cortex.
Preprints
Teki S (2015)
Observations on recent progress in the field of timing and time perception.
arXiv preprint arXiv: 1512.00058
Observations on recent progress in the field of timing and time perception.
arXiv preprint arXiv: 1512.00058
Conference proceedings
Teki S (2016)
Sampling of time intervals in rhythmic sound sequences: a Beta version.
International Journal of Psychophysiology 108, 18
Sampling of time intervals in rhythmic sound sequences: a Beta version.
International Journal of Psychophysiology 108, 18
Kruger H, Collins T, Pressnitzer D, Kang H, Teki S, Cavanagh P (2015)
Evidence for the common coding of location in auditory and visual space.
Journal of Vision 15(12): 368-368
Evidence for the common coding of location in auditory and visual space.
Journal of Vision 15(12): 368-368
Oliver-Roth G, Iverson P, Teki S, Leff AP (2014)
Non-native vowel processing as reflected by neuronal: Dynamic causal modeling of the magnetic mismatch response.
The Journal of the Acoustical Society of America 135(4): 2353-2353
Non-native vowel processing as reflected by neuronal: Dynamic causal modeling of the magnetic mismatch response.
The Journal of the Acoustical Society of America 135(4): 2353-2353
Kumar S, Sedley W, Barnes GR, Teki S, Friston KJ, Griffiths TD (2014)
Neural bases of Musical Hallucinations.
Journal of Neurology, Neurosurgery & Psychiatry 85: e3-e3
Neural bases of Musical Hallucinations.
Journal of Neurology, Neurosurgery & Psychiatry 85: e3-e3
Teki S, Griffiths TD (2014)
Neural nasis of working memory for time intervals.
Procedia - Social and Behavioral Sciences 126: 269-270
Neural nasis of working memory for time intervals.
Procedia - Social and Behavioral Sciences 126: 269-270
PhD Thesis
Teki S (2013)
Cognitive Analysis of Complex Acoustic Scenes.
PhD Thesis. University College London. [link]
Natural auditory scenes consist of a rich variety of temporally overlapping sounds that originate from multiple sources and locations and are characterized by distinct acoustic features. It is an important biological task to analyze such complex scenes and extract sounds of interest. The thesis addresses this question, also known as the “cocktail party problem” by developing an approach based on analysis of a novel stochastic signal contrary to deterministic narrowband signals used in previous work.
This low-level signal, known as the Stochastic Figure-Ground (SFG) stimulus captures the spectrotemporal complexity of natural sound scenes and enables parametric control of stimulus features. In a series of experiments based on this stimulus, I have investigated specific behavioural and neural correlates of human auditory figure-ground segregation.
This thesis is presented in seven sections. Chapter 1 reviews key aspects of auditory processing and existing models of auditory segregation. Chapter 2 presents the principles of the techniques used including psychophysics, modeling, functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Experimental work is presented in the following chapters and covers figure-ground segregation behaviour (Chapter 3), modeling of the SFG stimulus based on a temporal coherence model of auditory perceptual organization (Chapter 4), analysis of brain activity related to detection of salient targets in the SFG stimulus using fMRI (Chapter 5), and MEG respectively (Chapter 6). Finally, Chapter 7 concludes with a general discussion of the results and future directions for research. Overall, this body of work emphasizes the use of stochastic signals for auditory scene analysis and demonstrates an automatic, highly robust segregation mechanism in the auditory system that is sensitive to temporal correlations across frequency channels.
Cognitive Analysis of Complex Acoustic Scenes.
PhD Thesis. University College London. [link]
Natural auditory scenes consist of a rich variety of temporally overlapping sounds that originate from multiple sources and locations and are characterized by distinct acoustic features. It is an important biological task to analyze such complex scenes and extract sounds of interest. The thesis addresses this question, also known as the “cocktail party problem” by developing an approach based on analysis of a novel stochastic signal contrary to deterministic narrowband signals used in previous work.
This low-level signal, known as the Stochastic Figure-Ground (SFG) stimulus captures the spectrotemporal complexity of natural sound scenes and enables parametric control of stimulus features. In a series of experiments based on this stimulus, I have investigated specific behavioural and neural correlates of human auditory figure-ground segregation.
This thesis is presented in seven sections. Chapter 1 reviews key aspects of auditory processing and existing models of auditory segregation. Chapter 2 presents the principles of the techniques used including psychophysics, modeling, functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Experimental work is presented in the following chapters and covers figure-ground segregation behaviour (Chapter 3), modeling of the SFG stimulus based on a temporal coherence model of auditory perceptual organization (Chapter 4), analysis of brain activity related to detection of salient targets in the SFG stimulus using fMRI (Chapter 5), and MEG respectively (Chapter 6). Finally, Chapter 7 concludes with a general discussion of the results and future directions for research. Overall, this body of work emphasizes the use of stochastic signals for auditory scene analysis and demonstrates an automatic, highly robust segregation mechanism in the auditory system that is sensitive to temporal correlations across frequency channels.
Contributions to Scholarpedia
Barnes G, Hillebrand A (2010)
Magnetoencephalogram.
Scholarpedia 5:3172 [link]
Marreiros AC, Stephan KE, Friston KJ (2010)
Dynamic Causal Modeling.
Scholarpedia 5: 9568 [link]
Taube J (2009)
Head direction cells.
Scholarpedia 4: 1787 [link]
Balbus SA (2009)
Magnetorotational instability.
Scholarpedia 4: 2409 [link]
Constable RL (2009)
Computational type theory.
Scholarpedia 4: 7618 [link]
LeDoux JE (2008)
Amygdala.
Scholarpedia 3: 2698 [link]
Meszaros P (2008)
Gamma ray bursts theory.
Scholarpedia 3: 4337 [link]
Izhikevich M (2006)
Scholarpedia.
Scholarpedia 1:1 [link]
Magnetoencephalogram.
Scholarpedia 5:3172 [link]
Marreiros AC, Stephan KE, Friston KJ (2010)
Dynamic Causal Modeling.
Scholarpedia 5: 9568 [link]
Taube J (2009)
Head direction cells.
Scholarpedia 4: 1787 [link]
Balbus SA (2009)
Magnetorotational instability.
Scholarpedia 4: 2409 [link]
Constable RL (2009)
Computational type theory.
Scholarpedia 4: 7618 [link]
LeDoux JE (2008)
Amygdala.
Scholarpedia 3: 2698 [link]
Meszaros P (2008)
Gamma ray bursts theory.
Scholarpedia 3: 4337 [link]
Izhikevich M (2006)
Scholarpedia.
Scholarpedia 1:1 [link]