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Englitz B, Akram S, Elhilali M, Shamma S. Decoding contextual influences on auditory perception from primary auditory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.24.573229. [PMID: 38187523 PMCID: PMC10769425 DOI: 10.1101/2023.12.24.573229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair's perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the opposite of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.
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Gafoor SA, Uppunda AK. Sensory Gating in the Auditory System: Classical and Novel Stimulus Paradigms. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2024; 67:989-1001. [PMID: 38386055 DOI: 10.1044/2023_jslhr-22-00680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
PURPOSE Sensory gating is a phenomenon where the cortical response to the second stimulus in a pair of identical stimuli is inhibited. It is most often assessed in a conditioning-testing paradigm. Both active and passive neuronal mechanisms have been implicated in sensory gating. The present study aimed to assess if sensory gating is caused by an active neural mechanism associated with stimulus redundancy. METHOD The study was carried out on 20 young neurotypical adults. We assessed the gating phenomenon using identical and nonidentical stimuli pairs presented in an electrophysiological conditioning-testing paradigm. We hypothesized that the novel stimulus in the nonidentical stimulus pair would not exhibit the sensory gating effects (reduction in the amplitude of cortical potentials to the second stimuli in the pair), owing to stimulus novelty. RESULTS Contrary to our expectations, the response analyses of the cortical auditory evoked potentials revealed that adults gated repetitive and novel stimuli similarly. CONCLUSIONS The findings are discussed in relation to the significance of methodological factors in evaluating sensory gating. We believe that additional research using oddball presentation of novel stimuli along with appropriate analysis methods is necessary before drawing any conclusions on the mechanisms underlying sensory gating.
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Affiliation(s)
- Shezeen Abdul Gafoor
- Department of Audiology and Center for Hearing Science, All India Institute of Speech and Hearing, Mysore
| | - Ajith Kumar Uppunda
- Department of Audiology and Center for Hearing Science, All India Institute of Speech and Hearing, Mysore
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3
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Wang J, Rao X, Huang S, Wang Z, Niu X, Zhu M, Wang S, Shi L. Detection of a temporal salient object benefits from visual stimulus-specific adaptation in avian midbrain inhibitory nucleus. Integr Zool 2024; 19:288-306. [PMID: 36893724 DOI: 10.1111/1749-4877.12715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
Food and predators are the most noteworthy objects for the basic survival of wild animals, and both are often deviant in both spatial and temporal domains and quickly attract an animal's attention. Although stimulus-specific adaptation (SSA) is considered a potential neural basis of salient sound detection in the temporal domain, related research on visual SSA is limited and its relationship with temporal saliency is uncertain. The avian nucleus isthmi pars magnocellularis (Imc), which is central to midbrain selective attention network, is an ideal site to investigate the neural correlate of visual SSA and detection of a salient object in the time domain. Here, the constant order paradigm was applied to explore the visual SSA in the Imc of pigeons. The results showed that the firing rates of Imc neurons gradually decrease with repetitions of motion in the same direction, but recover when a motion in a deviant direction is presented, implying visual SSA to the direction of a moving object. Furthermore, enhanced response for an object moving in other directions that were not presented ever in the paradigm is also observed. To verify the neural mechanism underlying these phenomena, we introduced a neural computation model involving a recoverable synaptic change with a "center-surround" pattern to reproduce the visual SSA and temporal saliency for the moving object. These results suggest that the Imc produces visual SSA to motion direction, allowing temporal salient object detection, which may facilitate the detection of the sudden appearance of a predator.
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Affiliation(s)
- Jiangtao Wang
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Xiaoping Rao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Shuman Huang
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Zhizhong Wang
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Xiaoke Niu
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Minjie Zhu
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Songwei Wang
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
| | - Li Shi
- Department of Automation, Zhengzhou University School of Electrical Engineering, Zhengzhou, China
- Department of Automation, Tsinghua University, Beijing, China
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4
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Pérez-González D, Lao-Rodríguez AB, Aedo-Sánchez C, Malmierca MS. Acetylcholine modulates the precision of prediction error in the auditory cortex. eLife 2024; 12:RP91475. [PMID: 38241174 PMCID: PMC10942646 DOI: 10.7554/elife.91475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024] Open
Abstract
A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.
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Affiliation(s)
- David Pérez-González
- Cognitive and Auditory Neuroscience Laboratory, Institute of Neuroscience of Castilla y León, Calle Pintor Fernando GallegoSalamancaSpain
- Institute for Biomedical Research of Salamanca (IBSAL)SalamancaSpain
- Department of Basic Psychology, Psychobiology and Behavioural Science Methodology, Faculty of Psychology, Campus Ciudad Jardín, University of SalamancaSalamancaSpain
| | - Ana Belén Lao-Rodríguez
- Cognitive and Auditory Neuroscience Laboratory, Institute of Neuroscience of Castilla y León, Calle Pintor Fernando GallegoSalamancaSpain
- Institute for Biomedical Research of Salamanca (IBSAL)SalamancaSpain
| | - Cristian Aedo-Sánchez
- Cognitive and Auditory Neuroscience Laboratory, Institute of Neuroscience of Castilla y León, Calle Pintor Fernando GallegoSalamancaSpain
- Institute for Biomedical Research of Salamanca (IBSAL)SalamancaSpain
| | - Manuel S Malmierca
- Cognitive and Auditory Neuroscience Laboratory, Institute of Neuroscience of Castilla y León, Calle Pintor Fernando GallegoSalamancaSpain
- Institute for Biomedical Research of Salamanca (IBSAL)SalamancaSpain
- Department of Biology and Pathology, Faculty of Medicine, Campus Miguel de Unamuno, University of SalamancaSalamancaSpain
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5
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Valerio P, Rechenmann J, Joshi S, De Franceschi G, Barkat TR. Sequential maturation of stimulus-specific adaptation in the mouse lemniscal auditory system. SCIENCE ADVANCES 2024; 10:eadi7624. [PMID: 38170771 PMCID: PMC10776000 DOI: 10.1126/sciadv.adi7624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024]
Abstract
Stimulus-specific adaptation (SSA), the reduction of neural activity to a common stimulus that does not generalize to other, rare stimuli, is an essential property of our brain. Although well characterized in adults, it is still unknown how it develops during adolescence and what neuronal circuits are involved. Using in vivo electrophysiology and optogenetics in the lemniscal pathway of the mouse auditory system, we observed SSA to be stable from postnatal day 20 (P20) in the inferior colliculus, to develop until P30 in the auditory thalamus and even later in the primary auditory cortex (A1). We found this maturation process to be experience-dependent in A1 but not in thalamus and to be related to alterations in deep but not input layers of A1. We also identified corticothalamic projections to be implicated in thalamic SSA development. Together, our results reveal different circuits underlying the sequential SSA maturation and provide a unique perspective to understand predictive coding and surprise across sensory systems.
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Affiliation(s)
- Patricia Valerio
- Department of Biomedicine, Basel University, 4056 Basel, Switzerland
| | - Julien Rechenmann
- Department of Biomedicine, Basel University, 4056 Basel, Switzerland
| | - Suyash Joshi
- Department of Biomedicine, Basel University, 4056 Basel, Switzerland
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Poublan-Couzardot A, Lecaignard F, Fucci E, Davidson RJ, Mattout J, Lutz A, Abdoun O. Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response. PLoS Comput Biol 2023; 19:e1010557. [PMID: 38091350 PMCID: PMC10752554 DOI: 10.1371/journal.pcbi.1010557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/27/2023] [Accepted: 11/20/2023] [Indexed: 12/28/2023] Open
Abstract
Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.
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Affiliation(s)
- Arnaud Poublan-Couzardot
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Françoise Lecaignard
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Enrico Fucci
- 2 Institute for Globally Distributed Open Research and Education (IGDORE), Sweden
| | - Richard J. Davidson
- Center for Healthy Minds, University of Wisconsin, Madison, Wisconsin, United States of America
- Department of Psychology, University of Wisconsin, Madison, Wisconsin, United States of America
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, Wisconsin, United States of America
- Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Jérémie Mattout
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Antoine Lutz
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
| | - Oussama Abdoun
- Cente de Recherche en Neurosciences de Lyon (CRNL), CNRS UMRS5292, INSERM U1028, Université Claude Bernard Lyon 1, Bron, France
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7
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Suri H, Salgado-Puga K, Wang Y, Allen N, Lane K, Granroth K, Olivei A, Nass N, Rothschild G. A Cortico-Striatal Circuit for Sound-Triggered Prediction of Reward Timing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.21.568134. [PMID: 38045246 PMCID: PMC10690153 DOI: 10.1101/2023.11.21.568134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
A crucial aspect of auditory perception is the ability to use sound cues to predict future events and to time actions accordingly. For example, distinct smartphone notification sounds reflect a call that needs to be answered within a few seconds, or a text that can be read later; the sound of an approaching vehicle signals when it is safe to cross the street. Other animals similarly use sounds to plan, time and execute behaviors such as hunting, evading predation and tending to offspring. However, the neural mechanisms that underlie sound-guided prediction of upcoming salient event timing are not well understood. To address this gap, we employed an appetitive sound-triggered reward time prediction behavior in head-fixed mice. We find that mice trained on this task reliably estimate the time from a sound cue to upcoming reward on the scale of a few seconds, as demonstrated by learning-dependent well-timed increases in reward-predictive licking. Moreover, mice showed a dramatic impairment in their ability to use sound to predict delayed reward when the auditory cortex was inactivated, demonstrating its causal involvement. To identify the neurophysiological signatures of auditory cortical reward-timing prediction, we recorded local field potentials during learning and performance of this behavior and found that the magnitude of auditory cortical responses to the sound prospectively encoded the duration of the anticipated sound-reward time interval. Next, we explored how and where these sound-triggered time interval prediction signals propagate from the auditory cortex to time and initiate consequent action. We targeted the monosynaptic projections from the auditory cortex to the posterior striatum and found that chemogenetic inactivation of these projections impairs animal's ability to predict sound-triggered delayed reward. Simultaneous neural recordings in the auditory cortex and posterior striatum during task performance revealed coordination of neural activity across these regions during the sound cue predicting the time interval to reward. Collectively, our findings identify an auditory cortical-striatal circuit supporting sound-triggered timing-prediction behaviors.
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8
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Tomana E, Härtwich N, Rozmarynowski A, König R, May PJC, Sielużycki C. Optimising a computational model of human auditory cortex with an evolutionary algorithm. Hear Res 2023; 439:108879. [PMID: 37826916 DOI: 10.1016/j.heares.2023.108879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 08/16/2023] [Accepted: 08/21/2023] [Indexed: 10/14/2023]
Abstract
We demonstrate how the structure of auditory cortex can be investigated by combining computational modelling with advanced optimisation methods. We optimise a well-established auditory cortex model by means of an evolutionary algorithm. The model describes auditory cortex in terms of multiple core, belt, and parabelt fields. The optimisation process finds the optimum connections between individual fields of auditory cortex so that the model is able to reproduce experimental magnetoencephalographic (MEG) data. In the current study, this data comprised the auditory event-related fields (ERFs) recorded from a human subject in an MEG experiment where the stimulus-onset interval between consecutive tones was varied. The quality of the match between synthesised and experimental waveforms was 98%. The results suggest that neural activity caused by feedback connections plays a particularly important role in shaping ERF morphology. Further, ERFs reflect activity of the entire auditory cortex, and response adaptation due to stimulus repetition emerges from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Our findings constitute the first stage in establishing a new non-invasive method for uncovering the organisation of the human auditory cortex.
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Affiliation(s)
- Ewelina Tomana
- Department of Biomedical Engineering, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland.
| | - Nina Härtwich
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118, Magdeburg, Germany
| | - Adam Rozmarynowski
- Department of Biomedical Engineering, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland
| | - Reinhard König
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118, Magdeburg, Germany
| | - Patrick J C May
- Department of Psychology, Lancaster University, LA1 4YR, Lancaster, United Kingdom
| | - Cezary Sielużycki
- Department of Biomedical Engineering, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland
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9
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Coy N, Bendixen A, Grimm S, Roeber U, Schröger E. Deviants violating higher-order auditory regularities can become predictive and facilitate behaviour. Atten Percept Psychophys 2023; 85:2731-2750. [PMID: 37532882 PMCID: PMC10600044 DOI: 10.3758/s13414-023-02763-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/07/2023] [Indexed: 08/04/2023]
Abstract
The human auditory system is believed to represent regularities inherent in auditory information in internal models. Sounds not matching the standard regularity (deviants) elicit prediction error, alerting the system to information not explainable within currently active models. Here, we examine the widely neglected characteristic of deviants bearing predictive information themselves. In a modified version of the oddball paradigm, using higher-order regularities, we set up different expectations regarding the sound following a deviant. Higher-order regularities were defined by the relation of pitch within tone pairs (rather than absolute pitch of individual tones). In a deviant detection task participants listened to oddball sequences including two deviant types following diametrically opposed rules: one occurred mostly in succession (high repetition probability) and the other mostly in isolation (low repetition probability). Participants in Experiment 1 were not informed (naïve), whereas in Experiment 2 they were made aware of the repetition rules. Response times significantly decreased from first to second deviant when repetition probability was high-albeit more in the presence of explicit rule knowledge. There was no evidence of a facilitation effect when repetition probability was low. Significantly more false alarms occurred in response to standards following high compared with low repetition probability deviants, but only in participants aware of the repetition rules. These findings provide evidence that not only deviants violating lower- but also higher-order regularities can inform predictions about auditory events. More generally, they confirm the utility of this new paradigm to gather further insights into the predictive properties of the human brain.
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Affiliation(s)
- Nina Coy
- Wilhelm-Wundt-Institute of Psychology, University of Leipzig, Leipzig, Germany.
- Max Planck School of Cognition, Leipzig, Germany.
| | - Alexandra Bendixen
- Cognitive Systems Lab, Institute of Physics, Chemnitz University of Technology, Chemnitz, Germany
| | - Sabine Grimm
- Cognitive Systems Lab, Institute of Physics, Chemnitz University of Technology, Chemnitz, Germany
- Physics of Cognition Lab, Institute of Physics, Chemnitz University of Technology, Chemnitz, Germany
| | - Urte Roeber
- Wilhelm-Wundt-Institute of Psychology, University of Leipzig, Leipzig, Germany
| | - Erich Schröger
- Wilhelm-Wundt-Institute of Psychology, University of Leipzig, Leipzig, Germany
- Max Planck School of Cognition, Leipzig, Germany
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10
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Audette NJ, Schneider DM. Stimulus-Specific Prediction Error Neurons in Mouse Auditory Cortex. J Neurosci 2023; 43:7119-7129. [PMID: 37699716 PMCID: PMC10601367 DOI: 10.1523/jneurosci.0512-23.2023] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/07/2023] [Accepted: 09/04/2023] [Indexed: 09/14/2023] Open
Abstract
Comparing expectation with experience is an important neural computation performed throughout the brain and is a hallmark of predictive processing. Experiments that alter the sensory outcome of an animal's behavior reveal enhanced neural responses to unexpected self-generated stimuli, indicating that populations of neurons in sensory cortex may reflect prediction errors (PEs), mismatches between expectation and experience. However, enhanced neural responses to self-generated stimuli could also arise through nonpredictive mechanisms, such as the movement-based facilitation of a neuron's inherent sound responses. If sensory prediction error neurons exist in sensory cortex, it is unknown whether they manifest as general error responses, or respond with specificity to errors in distinct stimulus dimensions. To answer these questions, we trained mice of either sex to expect the outcome of a simple sound-generating behavior and recorded auditory cortex activity as mice heard either the expected sound or sounds that deviated from expectation in one of multiple distinct dimensions. Our data reveal that the auditory cortex learns to suppress responses to self-generated sounds along multiple acoustic dimensions simultaneously. We identify a distinct population of auditory cortex neurons that are not responsive to passive sounds or to the expected sound but that encode prediction errors. These prediction error neurons are abundant only in animals with a learned motor-sensory expectation, and encode one or two specific violations rather than a generic error signal. Together, these findings reveal that cortical predictions about self-generated sounds have specificity in multiple simultaneous dimensions and that cortical prediction error neurons encode specific violations from expectation.SIGNIFICANCE STATEMENT Audette et. al record neural activity in the auditory cortex while mice perform a sound-generating forelimb movement and measure neural responses to sounds that violate an animal's expectation in different ways. They find that predictions about self-generated sounds are highly specific across multiple stimulus dimensions and that a population of typically nonsound-responsive neurons respond to sounds that violate an animal's expectation in a specific way. These results identify specific prediction error (PE) signals in the mouse auditory cortex and suggest that errors may be calculated early in sensory processing.
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Affiliation(s)
- Nicholas J Audette
- Center for Neural Science, New York University, New York, New York 10003
| | - David M Schneider
- Center for Neural Science, New York University, New York, New York 10003
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11
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. Neuron 2023; 111:3255-3269.e6. [PMID: 37543037 PMCID: PMC10592405 DOI: 10.1016/j.neuron.2023.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/07/2023] [Accepted: 07/06/2023] [Indexed: 08/07/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA.
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12
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Kern FB, Chao ZC. Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks. PLoS Comput Biol 2023; 19:e1011554. [PMID: 37831721 PMCID: PMC10599548 DOI: 10.1371/journal.pcbi.1011554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 10/25/2023] [Accepted: 09/29/2023] [Indexed: 10/15/2023] Open
Abstract
Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD.
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Affiliation(s)
- Felix Benjamin Kern
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan
| | - Zenas C. Chao
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan
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13
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Kang H, Auksztulewicz R, Chan CH, Cappotto D, Rajendran VG, Schnupp JWH. Cross-modal implicit learning of random time patterns. Hear Res 2023; 438:108857. [PMID: 37639922 DOI: 10.1016/j.heares.2023.108857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 07/12/2023] [Accepted: 07/21/2023] [Indexed: 08/31/2023]
Abstract
Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, implicit learning of temporal patterns in one modality can also improve their processing in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers using electroencephalography (EEG), while participants were exposed to brief sequences of randomly timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment across both modalities (Transfer) or only within a modality (Control), enabling implicit learning in one modality and its transfer. Using a novel method of analysis of single-trial EEG responses, we showed that learning temporal structures within and across modalities is reflected in neural learning curves. These putative neural correlates of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. The modality-specific mechanisms for learning of temporal information and general mechanisms which mediate learning transfer across modalities had distinct physiological signatures: temporal learning within modalities relied on modality-specific brain regions while learning transfer affected beta-band activity in frontal regions.
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Affiliation(s)
- HiJee Kang
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryszard Auksztulewicz
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R; Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany
| | - Chi Hong Chan
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R
| | - Drew Cappotto
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R; UCL Ear Institute, University College London, London, United Kingdom
| | - Vani G Rajendran
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R; Department of Cognitive Neuroscience, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, NM
| | - Jan W H Schnupp
- Department of Neuroscience, City University of Hong Kong, Hong Kong S.A.R.
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14
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Schröger E, Roeber U, Coy N. Markov chains as a proxy for the predictive memory representations underlying mismatch negativity. Front Hum Neurosci 2023; 17:1249413. [PMID: 37771348 PMCID: PMC10525344 DOI: 10.3389/fnhum.2023.1249413] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/22/2023] [Indexed: 09/30/2023] Open
Abstract
Events not conforming to a regularity inherent to a sequence of events elicit prediction error signals of the brain such as the Mismatch Negativity (MMN) and impair behavioral task performance. Events conforming to a regularity lead to attenuation of brain activity such as stimulus-specific adaptation (SSA) and behavioral benefits. Such findings are usually explained by theories stating that the information processing system predicts the forthcoming event of the sequence via detected sequential regularities. A mathematical model that is widely used to describe, to analyze and to generate event sequences are Markov chains: They contain a set of possible events and a set of probabilities for transitions between these events (transition matrix) that allow to predict the next event on the basis of the current event and the transition probabilities. The accuracy of such a prediction depends on the distribution of the transition probabilities. We argue that Markov chains also have useful applications when studying cognitive brain functions. The transition matrix can be regarded as a proxy for generative memory representations that the brain uses to predict the next event. We assume that detected regularities in a sequence of events correspond to (a subset of) the entries in the transition matrix. We apply this idea to the Mismatch Negativity (MMN) research and examine three types of MMN paradigms: classical oddball paradigms emphasizing sound probabilities, between-sound regularity paradigms manipulating transition probabilities between adjacent sounds, and action-sound coupling paradigms in which sounds are associated with actions and their intended effects. We show that the Markovian view on MMN yields theoretically relevant insights into the brain processes underlying MMN and stimulates experimental designs to study the brain's processing of event sequences.
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Affiliation(s)
- Erich Schröger
- Wilhelm Wundt Institute for Psychology, Leipzig University, Leipzig, Germany
| | - Urte Roeber
- Wilhelm Wundt Institute for Psychology, Leipzig University, Leipzig, Germany
| | - Nina Coy
- Wilhelm Wundt Institute for Psychology, Leipzig University, Leipzig, Germany
- Max Planck School of Cognition, Leipzig, Germany
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15
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Agarwalla S, De A, Bandyopadhyay S. Predictive Mouse Ultrasonic Vocalization Sequences: Uncovering Behavioral Significance, Auditory Cortex Neuronal Preferences, and Social-Experience-Driven Plasticity. J Neurosci 2023; 43:6141-6163. [PMID: 37541836 PMCID: PMC10476644 DOI: 10.1523/jneurosci.2353-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 07/29/2023] [Accepted: 07/31/2023] [Indexed: 08/06/2023] Open
Abstract
Mouse ultrasonic vocalizations (USVs) contain predictable sequential structures like bird songs and speech. Neural representation of USVs in the mouse primary auditory cortex (Au1) and its plasticity with experience has been largely studied with single-syllables or dyads, without using the predictability in USV sequences. Studies using playback of USV sequences have used randomly selected sequences from numerous possibilities. The current study uses mutual information to obtain context-specific natural sequences (NSeqs) of USV syllables capturing the observed predictability in male USVs in different contexts of social interaction with females. Behavioral and physiological significance of NSeqs over random sequences (RSeqs) lacking predictability were examined. Female mice, never having the social experience of being exposed to males, showed higher selectivity for NSeqs behaviorally and at cellular levels probed by expression of immediate early gene c-fos in Au1. The Au1 supragranular single units also showed higher selectivity to NSeqs over RSeqs. Social-experience-driven plasticity in encoding NSeqs and RSeqs in adult females was probed by examining neural selectivities to the same sequences before and after the above social experience. Single units showed enhanced selectivity for NSeqs over RSeqs after the social experience. Further, using two-photon Ca2+ imaging, we observed social experience-dependent changes in the selectivity of sequences of excitatory and somatostatin-positive inhibitory neurons but not parvalbumin-positive inhibitory neurons of Au1. Using optogenetics, somatostatin-positive neurons were identified as a possible mediator of the observed social-experience-driven plasticity. Our study uncovers the importance of predictive sequences and introduces mouse USVs as a promising model to study context-dependent speech like communications.SIGNIFICANCE STATEMENT Humans need to detect patterns in the sensory world. For instance, speech is meaningful sequences of acoustic tokens easily differentiated from random ordered tokens. The structure derives from the predictability of the tokens. Similarly, mouse vocalization sequences have predictability and undergo context-dependent modulation. Our work investigated whether mice differentiate such informative predictable sequences (NSeqs) of communicative significance from RSeqs at the behavioral, molecular, and neuronal levels. Following a social experience in which NSeqs occur as a crucial component, mouse auditory cortical neurons become more sensitive to differences between NSeqs and RSeqs, although preference for individual tokens is unchanged. Thus, speech-like communication and its dysfunction may be studied in circuit, cellular, and molecular levels in mice.
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Affiliation(s)
- Swapna Agarwalla
- Information Processing Laboratory, Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
| | - Amiyangshu De
- Information Processing Laboratory, Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
- Advanced Technology Development Centre, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
| | - Sharba Bandyopadhyay
- Information Processing Laboratory, Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
- Advanced Technology Development Centre, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
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16
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Merchie A, Gomot M. Habituation, Adaptation and Prediction Processes in Neurodevelopmental Disorders: A Comprehensive Review. Brain Sci 2023; 13:1110. [PMID: 37509040 PMCID: PMC10377027 DOI: 10.3390/brainsci13071110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Habituation, the simplest form of learning preserved across species and evolution, is characterized by a response decrease as a stimulus is repeated. This adaptive function has been shown to be altered in some psychiatric and neurodevelopmental disorders such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or schizophrenia. At the brain level, habituation is characterized by a decrease in neural activity as a stimulation is repeated, referred to as neural adaptation. This phenomenon influences the ability to make predictions and to detect change, two processes altered in some neurodevelopmental and psychiatric disorders. In this comprehensive review, the objectives are to characterize habituation, neural adaptation, and prediction throughout typical development and in neurodevelopmental disorders; and to evaluate their implication in symptomatology, specifically in sensitivity to change or need for sameness. A summary of the different approaches to investigate adaptation will be proposed, in which we report the contribution of animal studies as well as electrophysiological studies in humans to understanding of underlying neuronal mechanisms.
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Affiliation(s)
| | - Marie Gomot
- UMR 1253 iBrain, Université de Tours, INSERM, 37000 Tours, France
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17
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Sawicki J, Berner R, Loos SAM, Anvari M, Bader R, Barfuss W, Botta N, Brede N, Franović I, Gauthier DJ, Goldt S, Hajizadeh A, Hövel P, Karin O, Lorenz-Spreen P, Miehl C, Mölter J, Olmi S, Schöll E, Seif A, Tass PA, Volpe G, Yanchuk S, Kurths J. Perspectives on adaptive dynamical systems. CHAOS (WOODBURY, N.Y.) 2023; 33:071501. [PMID: 37486668 DOI: 10.1063/5.0147231] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023]
Abstract
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Rico Berner
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Sarah A M Loos
- DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
| | - Mehrnaz Anvari
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53757 Sankt-Augustin, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Wolfram Barfuss
- Transdisciplinary Research Area: Sustainable Futures, University of Bonn, 53113 Bonn, Germany
- Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
| | - Nicola Botta
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Nuria Brede
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science, University of Potsdam, An der Bahn 2, 14476 Potsdam, Germany
| | - Igor Franović
- Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
| | - Daniel J Gauthier
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Sebastian Goldt
- Department of Physics, International School of Advanced Studies (SISSA), Trieste, Italy
| | - Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Philipp Hövel
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Omer Karin
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philipp Lorenz-Spreen
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Christoph Miehl
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Jan Mölter
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany
| | - Simona Olmi
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Alireza Seif
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California 94304, USA
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Serhiy Yanchuk
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
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18
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Viswanathan V, Bharadwaj HM, Heinz MG, Shinn-Cunningham BG. Induced alpha and beta electroencephalographic rhythms covary with single-trial speech intelligibility in competition. Sci Rep 2023; 13:10216. [PMID: 37353552 PMCID: PMC10290148 DOI: 10.1038/s41598-023-37173-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 06/17/2023] [Indexed: 06/25/2023] Open
Abstract
Neurophysiological studies suggest that intrinsic brain oscillations influence sensory processing, especially of rhythmic stimuli like speech. Prior work suggests that brain rhythms may mediate perceptual grouping and selective attention to speech amidst competing sound, as well as more linguistic aspects of speech processing like predictive coding. However, we know of no prior studies that have directly tested, at the single-trial level, whether brain oscillations relate to speech-in-noise outcomes. Here, we combined electroencephalography while simultaneously measuring intelligibility of spoken sentences amidst two different interfering sounds: multi-talker babble or speech-shaped noise. We find that induced parieto-occipital alpha (7-15 Hz; thought to modulate attentional focus) and frontal beta (13-30 Hz; associated with maintenance of the current sensorimotor state and predictive coding) oscillations covary with trial-wise percent-correct scores; importantly, alpha and beta power provide significant independent contributions to predicting single-trial behavioral outcomes. These results can inform models of speech processing and guide noninvasive measures to index different neural processes that together support complex listening.
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Affiliation(s)
- Vibha Viswanathan
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
| | - Hari M Bharadwaj
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Michael G Heinz
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, 47907, USA
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19
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Ketkar MD, Shao S, Gjorgjieva J, Silies M. Multifaceted luminance gain control beyond photoreceptors in Drosophila. Curr Biol 2023:S0960-9822(23)00619-X. [PMID: 37285845 DOI: 10.1016/j.cub.2023.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/09/2023]
Abstract
Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents the underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.
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Affiliation(s)
- Madhura D Ketkar
- Institute of Developmental and Neurobiology, Johannes-Gutenberg University Mainz, Hanns-Dieter-Hüsch-Weg 15, 55128 Mainz, Germany
| | - Shuai Shao
- Max Planck Institute for Brain Research, Max-von-Laue-Straße 4, 60438 Frankfurt am Main, Germany; Department of Neurophysiology, Radboud University, Heyendaalseweg 135, 6525 EN Nijmegen, the Netherlands
| | - Julijana Gjorgjieva
- Max Planck Institute for Brain Research, Max-von-Laue-Straße 4, 60438 Frankfurt am Main, Germany; School of Life Sciences, Technical University Munich, Maximus-von-Imhof-Forum 3, 85354 Freising, Germany.
| | - Marion Silies
- Institute of Developmental and Neurobiology, Johannes-Gutenberg University Mainz, Hanns-Dieter-Hüsch-Weg 15, 55128 Mainz, Germany.
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20
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DiTullio RW, Parthiban C, Piasini E, Chaudhari P, Balasubramanian V, Cohen YE. Time as a supervisor: temporal regularity and auditory object learning. Front Comput Neurosci 2023; 17:1150300. [PMID: 37216064 PMCID: PMC10192587 DOI: 10.3389/fncom.2023.1150300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 03/30/2023] [Indexed: 05/24/2023] Open
Abstract
Sensory systems appear to learn to transform incoming sensory information into perceptual representations, or "objects," that can inform and guide behavior with minimal explicit supervision. Here, we propose that the auditory system can achieve this goal by using time as a supervisor, i.e., by learning features of a stimulus that are temporally regular. We will show that this procedure generates a feature space sufficient to support fundamental computations of auditory perception. In detail, we consider the problem of discriminating between instances of a prototypical class of natural auditory objects, i.e., rhesus macaque vocalizations. We test discrimination in two ethologically relevant tasks: discrimination in a cluttered acoustic background and generalization to discriminate between novel exemplars. We show that an algorithm that learns these temporally regular features affords better or equivalent discrimination and generalization than conventional feature-selection algorithms, i.e., principal component analysis and independent component analysis. Our findings suggest that the slow temporal features of auditory stimuli may be sufficient for parsing auditory scenes and that the auditory brain could utilize these slowly changing temporal features.
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Affiliation(s)
- Ronald W. DiTullio
- David Rittenhouse Laboratory, Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, United States
- Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA, United States
- Computational Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA, United States
| | - Chetan Parthiban
- David Rittenhouse Laboratory, Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, United States
| | - Eugenio Piasini
- Computational Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA, United States
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
| | - Pratik Chaudhari
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Vijay Balasubramanian
- David Rittenhouse Laboratory, Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, United States
- Computational Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA, United States
- Santa Fe Institute, Santa Fe, NM, United States
| | - Yale E. Cohen
- Departments of Otorhinolaryngology, Neuroscience, and Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
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21
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Gill NK, Francis NA. Repetition plasticity in primary auditory cortex occurs across long timescales for spectrotemporally randomized pure-tones. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.26.538446. [PMID: 37162964 PMCID: PMC10168329 DOI: 10.1101/2023.04.26.538446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Repetition plasticity is a ubiquitous property of sensory systems in which repetitive sensation causes either a decrease ("repetition suppression", i.e. "adaptation") or increase ("repetition enhancement", i.e. "facilitation") in the amplitude of neural responses. Timescales of repetition plasticity for sensory neurons typically span milliseconds to tens of seconds, with longer durations for cortical vs subcortical regions. Here, we used 2-photon (2P) imaging to study repetition plasticity in mouse primary auditory cortex (A1) layer 2/3 (L2/3) during the presentation of spectrotemporally randomized pure-tone frequencies. Our study revealed subpopulations of neurons with repetition plasticity for equiprobable frequencies spaced minutes apart over a 20-minute period. We found both repetition suppression and enhancement in individual neurons and on average across populations. Each neuron tended to show repetition plasticity for 1-2 pure-tone frequencies near the neuron's best frequency. Moreover, we found correlated changes in neural response amplitude and latency across stimulus repetitions. Together, our results highlight cortical specialization for pattern recognition over long timescales in complex acoustic sequences.
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Affiliation(s)
- Nasiru K Gill
- Department of Biology, University of Maryland, College Park, MD, 20742
| | - Nikolas A Francis
- Department of Biology, University of Maryland, College Park, MD, 20742
- Brain and Behavior Institute, University of Maryland, College Park, MD, 20742
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22
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Willmore BDB, King AJ. Adaptation in auditory processing. Physiol Rev 2023; 103:1025-1058. [PMID: 36049112 PMCID: PMC9829473 DOI: 10.1152/physrev.00011.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recurring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by continually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the auditory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adaptation to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.
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Affiliation(s)
- Ben D. B. Willmore
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Andrew J. King
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
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23
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Kang H, Kanold PO. Auditory memory of complex sounds in sparsely distributed, highly correlated neurons in the auditory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526903. [PMID: 36778416 PMCID: PMC9915716 DOI: 10.1101/2023.02.02.526903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Listening in complex sound environments requires rapid segregation of different sound sources e.g., speakers from each other, speakers from other sounds, or different instruments in an orchestra, and also adjust auditory processing on the prevailing sound conditions. Thus, fast encoding of inputs and identifying and adapting to reoccurring sounds are necessary for efficient and agile sound perception. This adaptation process represents an early phase of developing implicit learning of sound statistics and thus represents a form of auditory memory. The auditory cortex (ACtx) is known to play a key role in this encoding process but the underlying circuits and if hierarchical processing exists are not known. To identify ACtx regions and cells involved in this process, we simultaneously imaged population of neurons in different ACtx subfields using in vivo 2-photon imaging in awake mice. We used an experimental stimulus paradigm adapted from human studies that triggers rapid and robust implicit learning to passively present complex sounds and imaged A1 Layer 4 (L4), A1 L2/3, and A2 L2/3. In this paradigm, a frozen spectro-temporally complex 'Target' sound would be randomly re-occurring within a stream of random other complex sounds. We find distinct groups of cells that are specifically responsive to complex acoustic sequences across all subregions indicating that even the initial thalamocortical input layers (A1 L4) respond to complex sounds. Cells in all imaged regions showed decreased response amplitude for reoccurring Target sounds indicating that a memory signature is present even in the thalamocortical input layers. On the population level we find increased synchronized activity across cells to the Target sound and that this synchronized activity was more consistent across cells regardless of the duration of frozen token within Target sounds in A2, compared to A1. These findings suggest that ACtx and its input layers play a role in auditory memory for complex sounds and suggest a hierarchical structure of processes for auditory memory.
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Affiliation(s)
- HiJee Kang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 20215
| | - Patrick O Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 20215
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24
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Weise A, Grimm S, Maria Rimmele J, Schröger E. Auditory representations for long lasting sounds: Insights from event-related brain potentials and neural oscillations. BRAIN AND LANGUAGE 2023; 237:105221. [PMID: 36623340 DOI: 10.1016/j.bandl.2022.105221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 12/26/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
The basic features of short sounds, such as frequency and intensity including their temporal dynamics, are integrated in a unitary representation. Knowledge on how our brain processes long lasting sounds is scarce. We review research utilizing the Mismatch Negativity event-related potential and neural oscillatory activity for studying representations for long lasting simple versus complex sounds such as sinusoidal tones versus speech. There is evidence for a temporal constraint in the formation of auditory representations: Auditory edges like sound onsets within long lasting sounds open a temporal window of about 350 ms in which the sounds' dynamics are integrated into a representation, while information beyond that window contributes less to that representation. This integration window segments the auditory input into short chunks. We argue that the representations established in adjacent integration windows can be concatenated into an auditory representation of a long sound, thus, overcoming the temporal constraint.
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Affiliation(s)
- Annekathrin Weise
- Department of Psychology, Ludwig-Maximilians-University Munich, Germany; Wilhelm Wundt Institute for Psychology, Leipzig University, Germany.
| | - Sabine Grimm
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany.
| | - Johanna Maria Rimmele
- Department of Neuroscience, Max-Planck-Institute for Empirical Aesthetics, Germany; Center for Language, Music and Emotion, New York University, Max Planck Institute, Department of Psychology, 6 Washington Place, New York, NY 10003, United States.
| | - Erich Schröger
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany.
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25
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Mischler G, Keshishian M, Bickel S, Mehta AD, Mesgarani N. Deep neural networks effectively model neural adaptation to changing background noise and suggest nonlinear noise filtering methods in auditory cortex. Neuroimage 2023; 266:119819. [PMID: 36529203 PMCID: PMC10510744 DOI: 10.1016/j.neuroimage.2022.119819] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/28/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
The human auditory system displays a robust capacity to adapt to sudden changes in background noise, allowing for continuous speech comprehension despite changes in background environments. However, despite comprehensive studies characterizing this ability, the computations that underly this process are not well understood. The first step towards understanding a complex system is to propose a suitable model, but the classical and easily interpreted model for the auditory system, the spectro-temporal receptive field (STRF), cannot match the nonlinear neural dynamics involved in noise adaptation. Here, we utilize a deep neural network (DNN) to model neural adaptation to noise, illustrating its effectiveness at reproducing the complex dynamics at the levels of both individual electrodes and the cortical population. By closely inspecting the model's STRF-like computations over time, we find that the model alters both the gain and shape of its receptive field when adapting to a sudden noise change. We show that the DNN model's gain changes allow it to perform adaptive gain control, while the spectro-temporal change creates noise filtering by altering the inhibitory region of the model's receptive field. Further, we find that models of electrodes in nonprimary auditory cortex also exhibit noise filtering changes in their excitatory regions, suggesting differences in noise filtering mechanisms along the cortical hierarchy. These findings demonstrate the capability of deep neural networks to model complex neural adaptation and offer new hypotheses about the computations the auditory cortex performs to enable noise-robust speech perception in real-world, dynamic environments.
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Affiliation(s)
- Gavin Mischler
- Mortimer B. Zuckerman Mind Brain Behavior, Columbia University, New York, United States; Department of Electrical Engineering, Columbia University, New York, United States
| | - Menoua Keshishian
- Mortimer B. Zuckerman Mind Brain Behavior, Columbia University, New York, United States; Department of Electrical Engineering, Columbia University, New York, United States
| | - Stephan Bickel
- Hofstra Northwell School of Medicine, Manhasset, New York, United States
| | - Ashesh D Mehta
- Hofstra Northwell School of Medicine, Manhasset, New York, United States
| | - Nima Mesgarani
- Mortimer B. Zuckerman Mind Brain Behavior, Columbia University, New York, United States; Department of Electrical Engineering, Columbia University, New York, United States.
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.30.526211. [PMID: 36778279 PMCID: PMC9915496 DOI: 10.1101/2023.01.30.526211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation, but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, distinct mechanisms are engaged following brief and prolonged stimulus presentation and together enable flexible control of sensory encoding across a wide range of time scales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
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Luo D, Liu J, Auksztulewicz R, Wing Yip TK, Kanold PO, Schnupp JW. Hierarchical Deviant Processing in Auditory Cortex of Awake Mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524413. [PMID: 36711896 PMCID: PMC9882249 DOI: 10.1101/2023.01.18.524413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Detecting patterns, and noticing unexpected pattern changes, in the environment is a vital aspect of sensory processing. Adaptation and prediction error responses are two components of neural processing related to these tasks, and previous studies in the auditory system in rodents show that these two components are partially dissociable in terms of the topography and latency of neural responses to sensory deviants. However, many previous studies have focused on repetitions of single stimuli, such as pure tones, which have limited ecological validity. In this study, we tested whether the auditory cortical activity shows adaptation to repetition of more complex sound patterns (bisyllabic pairs). Specifically, we compared neural responses to violations of sequences based on single stimulus probability only, against responses to more complex violations based on stimulus order. We employed an auditory oddball paradigm and monitored the auditory cortex (ACtx) activity of awake mice (N=8) using wide-field calcium imaging. We found that cortical responses were sensitive both to single stimulus probabilities and to more global stimulus patterns, as mismatch signals were elicited following both substitution deviants and transposition deviants. Notably, A2 area elicited larger mismatch signaling to those deviants than primary ACtx (A1), which suggests a hierarchical gradient of prediction error signaling in the auditory cortex. Such a hierarchical gradient was observed for late but not early peaks of calcium transients to deviants, suggesting that the late part of the deviant response may reflect prediction error signaling in response to more complex sensory pattern violations.
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Shilling-Scrivo K, Mittelstadt J, Kanold PO. Decreased Modulation of Population Correlations in Auditory Cortex Is Associated with Decreased Auditory Detection Performance in Old Mice. J Neurosci 2022; 42:9278-9292. [PMID: 36302637 PMCID: PMC9761686 DOI: 10.1523/jneurosci.0955-22.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/17/2022] [Accepted: 10/24/2022] [Indexed: 02/02/2023] Open
Abstract
Age-related hearing loss (presbycusis) affects one-third of the world's population. One hallmark of presbycusis is difficulty hearing in noisy environments. Presbycusis can be separated into two components: the aging ear and the aging brain. To date, the role of the aging brain in presbycusis is not well understood. Activity in the primary auditory cortex (A1) during a behavioral task is because of a combination of responses representing the acoustic stimuli, attentional gain, and behavioral choice. Disruptions in any of these aspects can lead to decreased auditory processing. To investigate how these distinct components are disrupted in aging, we performed in vivo 2-photon Ca2+ imaging in both male and female mice (Thy1-GCaMP6s × CBA/CaJ mice) that retain peripheral hearing into old age. We imaged A1 neurons of young adult (2-6 months) and old mice (16-24 months) during a tone detection task in broadband noise. While young mice performed well, old mice performed worse at low signal-to-noise ratios. Calcium imaging showed that old animals have increased prestimulus activity, reduced attentional gain, and increased noise correlations. Increased correlations in old animals exist regardless of cell tuning and behavioral outcome, and these correlated networks exist over a much larger portion of cortical space. Neural decoding techniques suggest that this prestimulus activity is predictive of old animals making early responses. Together, our results suggest a model in which old animals have higher and more correlated prestimulus activity and cannot fully suppress this activity, leading to the decreased representation of targets among distracting stimuli.SIGNIFICANCE STATEMENT Aging inhibits the ability to hear clearly in noisy environments. We show that the aging auditory cortex is unable to fully suppress its responses to background noise. During an auditory behavior, fewer neurons were suppressed in the old relative to young animals, which leads to higher prestimulus activity and more false alarms. We show that this excess activity additionally leads to increased correlations between neurons, reducing the amount of relevant stimulus information in the auditory cortex. Future work identifying the lost circuits that are responsible for proper background suppression could provide new targets for therapeutic strategies to preserve auditory processing ability into old age.
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Affiliation(s)
- Kelson Shilling-Scrivo
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, Maryland 21230
| | - Jonah Mittelstadt
- Department of Biology, University of Maryland, College Park, Maryland 20742
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
| | - Patrick O Kanold
- Department of Biology, University of Maryland, College Park, Maryland 20742
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
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Stein J, von Kriegstein K, Tabas A. Predictive encoding of pure tones and FM-sweeps in the human auditory cortex. Cereb Cortex Commun 2022; 3:tgac047. [PMID: 36545253 PMCID: PMC9764222 DOI: 10.1093/texcom/tgac047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 11/05/2022] [Accepted: 11/10/2022] [Indexed: 11/17/2022] Open
Abstract
Expectations substantially influence perception, but the neural mechanisms underlying this influence are not fully understood. A prominent view is that sensory neurons encode prediction error with respect to expectations on upcoming sensory input. Although the encoding of prediction error has been previously demonstrated in the human auditory cortex (AC), previous studies often induced expectations using stimulus repetition, potentially confounding prediction error with neural habituation. These studies also measured AC as a single population, failing to consider possible predictive specializations of different AC fields. Moreover, the few studies that considered prediction error to stimuli other than pure tones yielded conflicting results. Here, we used functional magnetic resonance imaging (fMRI) to systematically investigate prediction error to subjective expectations in auditory cortical fields Te1.0, Te1.1, Te1.2, and Te3, and two types of stimuli: pure tones and frequency modulated (FM) sweeps. Our results show that prediction error is elicited with respect to the participants' expectations independently of stimulus repetition and similarly expressed across auditory fields. Moreover, despite the radically different strategies underlying the decoding of pure tones and FM-sweeps, both stimulus modalities were encoded as prediction error in most fields of AC. Altogether, our results provide unequivocal evidence that predictive coding is the general encoding mechanism in AC.
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Affiliation(s)
| | - Katharina von Kriegstein
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technical University Dresden, Bamberger Str. 7, Dresden 01187, Germany
| | - Alejandro Tabas
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technical University Dresden, Bamberger Str. 7, Dresden 01187, Germany
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Ito Y, Shiramatsu TI, Ishida N, Oshima K, Magami K, Takahashi H. Spontaneous beat synchronization in rats: Neural dynamics and motor entrainment. SCIENCE ADVANCES 2022; 8:eabo7019. [PMID: 36367945 PMCID: PMC9651867 DOI: 10.1126/sciadv.abo7019] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Beat perception and synchronization within 120 to 140 beats/min (BPM) are common in humans and frequently used in music composition. Why beat synchronization is uncommon in some species and the mechanism determining the optimal tempo are unclear. Here, we examined physical movements and neural activities in rats to determine their beat sensitivity. Close inspection of head movements and neural recordings revealed that rats displayed prominent beat synchronization and activities in the auditory cortex within 120 to 140 BPM. Mathematical modeling suggests that short-term adaptation underlies this beat tuning. Our results support the hypothesis that the optimal tempo for beat synchronization is determined by the time constant of neural dynamics conserved across species, rather than the species-specific time constant of physical movements. Thus, latent neural propensity for auditory motor entrainment may provide a basis for human entrainment that is much more widespread than currently thought. Further studies comparing humans and animals will offer insights into the origins of music and dancing.
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31
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O'Reilly JA. Recurrent Neural Network Model of Human Event-related Potentials in Response to Intensity Oddball Stimulation. Neuroscience 2022; 504:63-74. [DOI: 10.1016/j.neuroscience.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/27/2022] [Accepted: 10/03/2022] [Indexed: 10/31/2022]
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Taddeo S, Schulz M, Andermann M, Rupp A. Neuromagnetic representation of melodic contour processing in human auditory cortex. Front Hum Neurosci 2022; 16:909159. [PMID: 36393993 PMCID: PMC9644163 DOI: 10.3389/fnhum.2022.909159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/05/2022] [Indexed: 11/25/2022] Open
Abstract
The pattern of ups and downs in a sequence with varying pitch can be heard as a melodic contour. Contrary to single pitch, the neural representation of melodic contour information in the auditory cortex is rarely investigated, and it is not clear whether the processing entails a hemispheric asymmetry. The present magnetoencephalography study assessed the neuromagnetic responses of N = 18 normal-hearing adults to four-note sequences with fixed vs. varying pitch that were presented either monaurally or diotically; data were analyzed using minimum-norm reconstructions. The first note of the sequences elicited prominent transient activity in posterior auditory regions (Planum temporale), especially contralateral to the ear of entry. In contrast, the response to the subsequent notes originated from more anterior areas (Planum polare) and was larger for melodic contours than for fixed pitch sequences, independent from the ear of entry and without hemispheric asymmetry. Together, the results point to a gradient in the early cortical processing of melodic contours, both in spatial and functional terms, where posterior auditory activity reflects the onset of a pitch sequence and anterior activity reflects its subsequent notes, including the difference between sequences with fixed pitch and melodic contours.
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Affiliation(s)
- Sabrina Taddeo
- Department of Otolaryngology, Head and Neck Surgery, University Medical Center of Tübingen, Tübingen, Germany
| | - Martin Schulz
- Section of Biomagnetism, Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Andermann
- Section of Biomagnetism, Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - André Rupp
- Section of Biomagnetism, Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
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Olsen T, Hasenstaub AR. Offset Responses in the Auditory Cortex Show Unique History Dependence. J Neurosci 2022; 42:7370-7385. [PMID: 35999053 PMCID: PMC9525174 DOI: 10.1523/jneurosci.0494-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 08/10/2022] [Accepted: 08/13/2022] [Indexed: 11/21/2022] Open
Abstract
Sensory responses typically vary depending on the recent history of sensory experience. This is essential for processes, including adaptation, efficient coding, and change detection. In the auditory cortex (AC), the short-term history dependence of sound-evoked (onset) responses has been well characterized. Yet many AC neurons also respond to sound terminations, and little is known about the history dependence of these "offset" responses, whether the short-term dynamics of onset and offset responses are correlated, or how these properties are distributed among cell types. Here we presented awake male and female mice with repeating noise burst stimuli while recording single-unit activity from primary AC. We identified parvalbumin and somatostatin interneurons through optotagging, and also separated narrow-spiking from broad-spiking units. We found that offset responses are typically less depressive than onset responses, and this result was robust to a variety of stimulus parameters, controls, measurement types, and selection criteria. Whether a cell's onset response facilitates or depresses does not predict whether its offset response facilitates or depresses. Cell types differed in the dynamics of their onset responses, and in the prevalence, but not the dynamics, of their offset responses. Finally, we clustered cells according to spiking responses and found that response clusters were associated with cell type. Each cluster contained cells of several types, but even within a cluster, cells often showed cell type-specific response dynamics. We conclude that onset and offset responses are differentially influenced by recent sound history, and discuss the implications of this for the encoding of ongoing sound stimuli.SIGNIFICANCE STATEMENT Sensory neuron responses depend on stimulus history. This history dependence is crucial for sensory processing, is precisely controlled at individual synapses and circuits, and is adaptive to the specific requirements of different sensory systems. In the auditory cortex, neurons respond to sound cessation as well as to sound itself, but how history dependence is used along this separate, "offset" information stream is unknown. We show that offset responses are more facilitatory than sound responses, even in neurons where sound responses depress. In contrast to sound onset responses, offset responses are absent in many cells, are relatively homogeneous, and show no cell type-specific differences in history dependence. Offset responses thus show unique response dynamics, suggesting their unique functions.
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Affiliation(s)
- Timothy Olsen
- Coleman Memorial Laboratory
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, California 94143
| | - Andrea R Hasenstaub
- Coleman Memorial Laboratory
- Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, California 94143
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34
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O'Reilly JA. Modelling mouse auditory response dynamics along a continuum of consciousness using a deep recurrent neural network. J Neural Eng 2022; 19. [DOI: 10.1088/1741-2552/ac9257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 09/15/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective Understanding neurophysiological changes that accompany transitions between anaesthetized and conscious states is a key objective of anesthesiology and consciousness science. This study aimed to characterize the dynamics of auditory-evoked potential morphology in mice along a continuum of consciousness. Approach Epidural field potentials were recorded from above the primary auditory cortices of two groups of laboratory mice: urethane-anaesthetized (A, n = 14) and conscious (C, n = 17). Both groups received auditory stimulation in the form of a repeated pure-tone stimulus, before and after receiving 10 mg/kg i.p. ketamine (AK and CK). Evoked responses were then ordered by ascending sample entropy into AK, A, CK, and C, considered to reflect physiological correlates of awareness. These data were used to train a recurrent neural network (RNN) with an input parameter encoding state. Model outputs were compared with grand-average event-related potential (ERP) waveforms. Subsequently, the state parameter was varied to simulate changes in the ERP that occur during transitions between states, and relationships with dominant peak amplitudes were quantified. Main results The RNN synthesized output waveforms that were in close agreement with grand-average ERPs for each group (r2 > 0.9, p < 0.0001). Varying the input state parameter generated model outputs reflecting changes in ERP morphology predicted to occur between states. Positive peak amplitudes within 25 to 50 ms, and negative peak amplitudes within 50 to 75 ms post-stimulus-onset, were found to display a sigmoidal characteristic during the transition from anaesthetized to conscious states. In contrast, negative peak amplitudes within 0 to 25 ms displayed greater linearity. Significance This study demonstrates a method for modelling changes in ERP morphology that accompany transitions between states of consciousness using a RNN. In future studies, this approach may be applied to human data to support the clinical use of ERPs to predict transition to consciousness.
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Eckert D, Reichert C, Bien CG, Heinze HJ, Knight RT, Deouell LY, Dürschmid S. Distinct interacting cortical networks for stimulus-response and repetition-suppression. Commun Biol 2022; 5:909. [PMID: 36064744 PMCID: PMC9445181 DOI: 10.1038/s42003-022-03861-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 08/19/2022] [Indexed: 11/29/2022] Open
Abstract
Non-invasive studies consider the initial neural stimulus response (SR) and repetition suppression (RS) - the decreased response to repeated sensory stimuli - as engaging the same neurons. That is, RS is a suppression of the SR. We challenge this conjecture using electrocorticographic (ECoG) recordings with high spatial resolution in ten patients listening to task-irrelevant trains of auditory stimuli. SR and RS were indexed by high-frequency activity (HFA) across temporal, parietal, and frontal cortices. HFASR and HFARS were temporally and spatially distinct, with HFARS emerging later than HFASR and showing only a limited spatial intersection with HFASR: most HFASR sites did not demonstrate HFARS, and HFARS was found where no HFASR could be recorded. β activity was enhanced in HFARS compared to HFASR cortical sites. θ activity was enhanced in HFASR compared to HFARS sites. Furthermore, HFASR sites propagated information to HFARS sites via transient θ:β phase-phase coupling. In contrast to predictive coding (PC) accounts our results indicate that HFASR and HFARS are functionally linked but have minimal spatial overlap. HFASR might enable stable and rapid perception of environmental stimuli across extended temporal intervals. In contrast HFARS might support efficient generation of an internal model based on stimulus history.
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Affiliation(s)
- David Eckert
- Department of Neurology, Otto-von-Guericke University of Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Brenneckestr. 6, 39120, Magdeburg, Germany
| | - Christoph Reichert
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Brenneckestr. 6, 39120, Magdeburg, Germany
| | - Christian G Bien
- Department. of Epileptology, Krankenhaus Mara, Bielefeld University, Maraweg 21, 33617, Bielefeld, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto-von-Guericke University of Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Brenneckestr. 6, 39120, Magdeburg, Germany
- Forschungscampus STIMULATE, Otto-von-Guericke University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany
- CBBS - center of behavioral brain sciences, Otto-von-Guericke University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Robert T Knight
- Department of Psychology, University of California Berkeley, 130 Barker Hall, Berkeley, 94720, CA, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, 94720, CA, USA
| | - Leon Y Deouell
- Department of Psychology and Edmond and Lily Safra Center for brain sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Stefan Dürschmid
- Department of Neurology, Otto-von-Guericke University of Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany.
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Brenneckestr. 6, 39120, Magdeburg, Germany.
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Pastyrik JD, Firzlaff U. Object specific adaptation in the auditory cortex of bats. J Neurophysiol 2022; 128:556-567. [PMID: 35946795 DOI: 10.1152/jn.00151.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
To identify behaviourally relevant sounds is an important function of the auditory system. Echolocating bats have to negotiate a wealth of sounds in the context of navigation and foraging. They must be able to detect relatively rare but behaviourally important echoes and segregate them from a large number of unimportant background echoes. For this, the bat auditory system might rely on neural deviance detection, a process influencing the excitability of a neuron depending on the frequency of occurrence of a stimulus. To investigate neural deviance detection in the auditory cortex (AC) of anaesthetised bats (Phyllostomus discolor), we designed sequences of repetitive naturalistic virtual echoes differing in spectro-temporal envelope, resembling those bats might perceive in their natural environment. In these sequences, one echo (standard) was repeated ten times and another echo (deviant) was presented at the end. Temporal intervals between echoes within the sequences varied. Our results show, that neurons in the AC of the bat P. discolor are sensitive to novel virtual echoes presented at the end of these repetitive sequences: In 49 % (62/126) of cortical neurons, extracellularly recorded responses adapted to the standard echo, but showed a strong response to the finally presented deviant echo. This effect depended strongly on the temporal intervals between echoes, with stronger adaptation at shorter intervals. This type of response behavior might represent a form of neuronal deviance detection in the AC that could help the bats to detect echoes of novel and potentially important objects within a stream of homogeneous background echoes.
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Affiliation(s)
- Jan David Pastyrik
- Chair of Zoology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Uwe Firzlaff
- Chair of Zoology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
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Insa S, Felix L, Peters A, Maximilian B, Thomas S. Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation. Neuroimage 2022; 262:119530. [DOI: 10.1016/j.neuroimage.2022.119530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/07/2022] [Accepted: 08/01/2022] [Indexed: 10/31/2022] Open
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Hajizadeh A, Matysiak A, Wolfrum M, May PJC, König R. Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation. BIOLOGICAL CYBERNETICS 2022; 116:475-499. [PMID: 35718809 PMCID: PMC9287241 DOI: 10.1007/s00422-022-00936-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.
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Affiliation(s)
- Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Artur Matysiak
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Matthias Wolfrum
- Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin, Germany
| | - Patrick J. C. May
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
- Department of Psychology, Lancaster University, Lancaster, LA1 4YF UK
| | - Reinhard König
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
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Suri H, Rothschild G. Enhanced stability of complex sound representations relative to simple sounds in the auditory cortex. eNeuro 2022; 9:ENEURO.0031-22.2022. [PMID: 35868858 PMCID: PMC9347310 DOI: 10.1523/eneuro.0031-22.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/29/2022] [Accepted: 06/30/2022] [Indexed: 11/29/2022] Open
Abstract
Typical everyday sounds, such as those of speech or running water, are spectrotemporally complex. The ability to recognize complex sounds (CxS) and their associated meaning is presumed to rely on their stable neural representations across time. The auditory cortex is critical for processing of CxS, yet little is known of the degree of stability of auditory cortical representations of CxS across days. Previous studies have shown that the auditory cortex represents CxS identity with a substantial degree of invariance to basic sound attributes such as frequency. We therefore hypothesized that auditory cortical representations of CxS are more stable across days than those of sounds that lack spectrotemporal structure such as pure tones (PTs). To test this hypothesis, we recorded responses of identified L2/3 auditory cortical excitatory neurons to both PTs and CxS across days using two-photon calcium imaging in awake mice. Auditory cortical neurons showed significant daily changes of responses to both types of sounds, yet responses to CxS exhibited significantly lower rates of daily change than those of PTs. Furthermore, daily changes in response profiles to PTs tended to be more stimulus-specific, reflecting changes in sound selectivity, as compared to changes of CxS responses. Lastly, the enhanced stability of responses to CxS was evident across longer time intervals as well. Together, these results suggest that spectrotemporally CxS are more stably represented in the auditory cortex across time than PTs. These findings support a role of the auditory cortex in representing CxS identity across time.Significance statementThe ability to recognize everyday complex sounds such as those of speech or running water is presumed to rely on their stable neural representations. Yet, little is known of the degree of stability of single-neuron sound responses across days. As the auditory cortex is critical for complex sound perception, we hypothesized that the auditory cortical representations of complex sounds are relatively stable across days. To test this, we recorded sound responses of identified auditory cortical neurons across days in awake mice. We found that auditory cortical responses to complex sounds are significantly more stable across days as compared to those of simple pure tones. These findings support a role of the auditory cortex in representing complex sound identity across time.
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Affiliation(s)
- Harini Suri
- Department of Psychology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Gideon Rothschild
- Department of Psychology, University of Michigan, Ann Arbor, MI, 48109, USA
- Kresge Hearing Research Institute and Department of Otolaryngology - Head and Neck Surgery, University of Michigan, Ann Arbor, MI 48109, USA
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40
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Xue B, Alipio JB, Kao JPY, Kanold PO. Perinatal Opioid Exposure Results in Persistent Hypoconnectivity of Excitatory Circuits and Reduced Activity Correlations in Mouse Primary Auditory Cortex. J Neurosci 2022; 42:3676-3687. [PMID: 35332087 PMCID: PMC9053845 DOI: 10.1523/jneurosci.2542-21.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 03/14/2022] [Indexed: 11/21/2022] Open
Abstract
Opioid use by pregnant women results in neonatal opioid withdrawal syndrome (NOWS) and lifelong neurobehavioral deficits including language impairments. Animal models of NOWS show impaired performance in a two-tone auditory discrimination task, suggesting abnormalities in sensory processing in the auditory cortex. To investigate the consequences of perinatal opioid exposure on auditory cortex circuits, we administered fentanyl to mouse dams in their drinking water throughout gestation and until litters were weaned at postnatal day (P)21. We then used in vivo two-photon Ca2+ imaging in adult animals of both sexes to investigate how primary auditory cortex (A1) function was altered. Perinatally exposed animals showed fewer sound-responsive neurons in A1, and the remaining sound-responsive cells exhibited lower response amplitudes but normal frequency selectivity and stimulus-specific adaptation (SSA). Populations of nearby layer 2/3 (L2/3) cells in exposed animals showed reduced correlated activity, suggesting a reduction of shared inputs. We then investigated A1 microcircuits to L2/3 cells by performing laser-scanning photostimulation (LSPS) combined with whole-cell patch-clamp recordings from A1 L2/3 cells. L2/3 cells in exposed animals showed functional hypoconnectivity of excitatory circuits of ascending inputs from L4 and L5/6 to L2/3, while inhibitory connections were unchanged, leading to an altered excitatory/inhibitory balance. These results suggest a specific reduction in excitatory ascending interlaminar cortical circuits resulting in decreased activity correlations after fentanyl exposure. We speculate that these changes in cortical circuits contribute to the impaired auditory discrimination ability after perinatal opioid exposure.SIGNIFICANCE STATEMENT This is the first study to investigate the functional effects of perinatal fentanyl exposure on the auditory cortex. Experiments show that perinatal fentanyl exposure results in decreased excitatory functional circuits and altered population activity in primary sensory areas in adult mice. These circuit changes might underlie the observed language and cognitive deficits in infants exposed to opioids.
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Affiliation(s)
- Binghan Xue
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
- Department of Biology, University of Maryland, College Park, Maryland 20742
| | - Jason B Alipio
- Department of Anatomy and Neurobiology, Program in Neuroscience, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Joseph P Y Kao
- Center for Biomedical Engineering and Technology, and Department of Physiology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Patrick O Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 20215
- Department of Biology, University of Maryland, College Park, Maryland 20742
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41
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Kadosh O, Bonneh YS. Involuntary oculomotor inhibition markers of saliency and deviance in response to auditory sequences. J Vis 2022; 22:8. [PMID: 35475911 PMCID: PMC9055552 DOI: 10.1167/jov.22.5.8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Our eyes move constantly but are often inhibited momentarily in response to external stimuli (oculomotor inhibition [OMI]), depending on the stimulus saliency, anticipation, and attention. Previous studies have shown prolonged OMI for auditory oddballs; however, they required counting the oddballs, possibly reflecting voluntary attention. Here, we investigated whether the “passive” OMI response to auditory deviants can provide a quantitative measure of deviance strength (pitch difference) and studied its dependence on the inter-trial interval (ITI). Participants fixated centrally and passively listened to repeated short sequences of pure tones that contained a deviant tone either regularly or with 20% probability (oddballs). In an “active” control experiment, participants counted the deviant or the standard. As in previous studies, the results showed prolonged microsaccade inhibition and increased pupil dilation following the rare deviant tone. Earlier inhibition onset was found in proportion to the pitch deviance (the saliency effect), and a later release was found for oddballs, but only for ITI <2.5 seconds. The active control experiment showed similar results when counting the deviant but longer OMI for the standard when counting it. Taken together, these results suggest that OMI provides involuntary markers of saliency and deviance, which can be obtained without the participant's response.
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Affiliation(s)
- Oren Kadosh
- School of Optometry and Vision Science, Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.,
| | - Yoram S Bonneh
- School of Optometry and Vision Science, Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel., https://yorambonneh.wixsite.com/bonneh-lab
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Lustenberger C, Ferster ML, Huwiler S, Brogli L, Werth E, Huber R, Karlen W. Auditory deep sleep stimulation in older adults at home: a randomized crossover trial. COMMUNICATIONS MEDICINE 2022; 2:30. [PMID: 35603302 PMCID: PMC9053232 DOI: 10.1038/s43856-022-00096-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Abstract
Background Auditory stimulation has emerged as a promising tool to enhance non-invasively sleep slow waves, deep sleep brain oscillations that are tightly linked to sleep restoration and are diminished with age. While auditory stimulation showed a beneficial effect in lab-based studies, it remains unclear whether this stimulation approach could translate to real-life settings. Methods We present a fully remote, randomized, cross-over trial in healthy adults aged 62-78 years (clinicaltrials.gov: NCT03420677). We assessed slow wave activity as the primary outcome and sleep architecture and daily functions, e.g., vigilance and mood as secondary outcomes, after a two-week mobile auditory slow wave stimulation period and a two-week Sham period, interleaved with a two-week washout period. Participants were randomized in terms of which intervention condition will take place first using a blocked design to guarantee balance. Participants and experimenters performing the assessments were blinded to the condition. Results Out of 33 enrolled and screened participants, we report data of 16 participants that received identical intervention. We demonstrate a robust and significant enhancement of slow wave activity on the group-level based on two different auditory stimulation approaches with minor effects on sleep architecture and daily functions. We further highlight the existence of pronounced inter- and intra-individual differences in the slow wave response to auditory stimulation and establish predictions thereof. Conclusions While slow wave enhancement in healthy older adults is possible in fully remote settings, pronounced inter-individual differences in the response to auditory stimulation exist. Novel personalization solutions are needed to address these differences and our findings will guide future designs to effectively deliver auditory sleep stimulations using wearable technology.
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Affiliation(s)
- Caroline Lustenberger
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
| | - M. Laura Ferster
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Stephanie Huwiler
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Luzius Brogli
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Institute of Biomedical Engineering, Universität Ulm, Ulm, Germany
| | - Esther Werth
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Reto Huber
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Child Development Centre, University Children’s Hospital, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Walter Karlen
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Institute of Biomedical Engineering, Universität Ulm, Ulm, Germany
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Yeark M, Paton B, Brown A, Raal A, Todd J. Primacy biases endure the addition of frequency variability. Neuropsychologia 2022; 171:108233. [DOI: 10.1016/j.neuropsychologia.2022.108233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 11/16/2022]
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Norman-Haignere SV, Long LK, Devinsky O, Doyle W, Irobunda I, Merricks EM, Feldstein NA, McKhann GM, Schevon CA, Flinker A, Mesgarani N. Multiscale temporal integration organizes hierarchical computation in human auditory cortex. Nat Hum Behav 2022; 6:455-469. [PMID: 35145280 PMCID: PMC8957490 DOI: 10.1038/s41562-021-01261-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 11/18/2021] [Indexed: 01/11/2023]
Abstract
To derive meaning from sound, the brain must integrate information across many timescales. What computations underlie multiscale integration in human auditory cortex? Evidence suggests that auditory cortex analyses sound using both generic acoustic representations (for example, spectrotemporal modulation tuning) and category-specific computations, but the timescales over which these putatively distinct computations integrate remain unclear. To answer this question, we developed a general method to estimate sensory integration windows-the time window when stimuli alter the neural response-and applied our method to intracranial recordings from neurosurgical patients. We show that human auditory cortex integrates hierarchically across diverse timescales spanning from ~50 to 400 ms. Moreover, we find that neural populations with short and long integration windows exhibit distinct functional properties: short-integration electrodes (less than ~200 ms) show prominent spectrotemporal modulation selectivity, while long-integration electrodes (greater than ~200 ms) show prominent category selectivity. These findings reveal how multiscale integration organizes auditory computation in the human brain.
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Affiliation(s)
- Sam V Norman-Haignere
- Zuckerman Mind, Brain, Behavior Institute, Columbia University,HHMI Postdoctoral Fellow of the Life Sciences Research Foundation
| | - Laura K. Long
- Zuckerman Mind, Brain, Behavior Institute, Columbia University,Doctoral Program in Neurobiology and Behavior, Columbia University
| | - Orrin Devinsky
- Department of Neurology, NYU Langone Medical Center,Comprehensive Epilepsy Center, NYU Langone Medical Center
| | - Werner Doyle
- Comprehensive Epilepsy Center, NYU Langone Medical Center,Department of Neurosurgery, NYU Langone Medical Center
| | - Ifeoma Irobunda
- Department of Neurology, Columbia University Irving Medical Center
| | | | - Neil A. Feldstein
- Department of Neurological Surgery, Columbia University Irving Medical Center
| | - Guy M. McKhann
- Department of Neurological Surgery, Columbia University Irving Medical Center
| | | | - Adeen Flinker
- Department of Neurology, NYU Langone Medical Center,Comprehensive Epilepsy Center, NYU Langone Medical Center,Department of Biomedical Engineering, NYU Tandon School of Engineering
| | - Nima Mesgarani
- Zuckerman Mind, Brain, Behavior Institute, Columbia University,Doctoral Program in Neurobiology and Behavior, Columbia University,Department of Electrical Engineering, Columbia University
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45
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Novel stimuli evoke excess activity in the mouse primary visual cortex. Proc Natl Acad Sci U S A 2022; 119:2108882119. [PMID: 35101916 PMCID: PMC8812573 DOI: 10.1073/pnas.2108882119] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/14/2021] [Indexed: 01/03/2023] Open
Abstract
Rapid detection and processing of stimulus novelty are key elements of adaptive behavior. Predictive coding theories postulate that novel stimuli should be encoded differently from familiar stimuli. Here, we show that the majority of neurons in layer 2/3 of the mouse primary visual cortex exhibit a significant excess response to novel visual stimuli. The distinction between novel and familiar images developed rapidly, requiring only a few repeated presentations. We show that this phenomenon can be described by a model of cascading adaptation. This ubiquitous mechanism makes it likely that similar computations could be carried out in many brain areas. To explore how neural circuits represent novel versus familiar inputs, we presented mice with repeated sets of images with novel images sparsely substituted. Using two-photon calcium imaging to record from layer 2/3 neurons in the mouse primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. This novelty response rapidly emerged, arising with a time constant of 2.6 ± 0.9 s. When a new image set was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which decayed to steady state with a time constant of 1.4 ± 0.4 s. When we increased the number of images in the set, the novelty response’s amplitude decreased, defining a capacity to store ∼15 familiar images under our conditions. These results could be explained quantitatively using an adaptive subunit model in which presynaptic neurons have individual tuning and gain control. This result shows that local neural circuits can create different representations for novel versus familiar inputs using generic, widely available mechanisms.
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46
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May PJC. The Adaptation Model Offers a Challenge for the Predictive Coding Account of Mismatch Negativity. Front Hum Neurosci 2021; 15:721574. [PMID: 34867238 PMCID: PMC8640521 DOI: 10.3389/fnhum.2021.721574] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/11/2021] [Indexed: 11/25/2022] Open
Abstract
An unpredictable stimulus elicits a stronger event-related response than a high-probability stimulus. This differential in response magnitude is termed the mismatch negativity (MMN). Over the past decade, it has become increasingly popular to explain the MMN terms of predictive coding, a proposed general principle for the way the brain realizes Bayesian inference when it interprets sensory information. This perspective article is a reminder that the issue of MMN generation is far from settled, and that an alternative model in terms of adaptation continues to lurk in the wings. The adaptation model has been discounted because of the unrealistic and simplistic fashion in which it tends to be set up. Here, simulations of auditory cortex incorporating a modern version of the adaptation model are presented. These show that locally operating short-term synaptic depression accounts both for adaptation due to stimulus repetition and for MMN responses. This happens even in cases where adaptation has been ruled out as an explanation of the MMN (e.g., in the stimulus omission paradigm and the multi-standard control paradigm). Simulation models that would demonstrate the viability of predictive coding in a similarly multifaceted way are currently missing from the literature, and the reason for this is discussed in light of the current results.
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Affiliation(s)
- Patrick J C May
- Department of Psychology, Lancaster University, Lancaster, United Kingdom
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47
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Foucault C, Meyniel F. Gated recurrence enables simple and accurate sequence prediction in stochastic, changing, and structured environments. eLife 2021; 10:71801. [PMID: 34854377 PMCID: PMC8735865 DOI: 10.7554/elife.71801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 12/01/2021] [Indexed: 11/13/2022] Open
Abstract
From decision making to perception to language, predicting what is coming next is crucial. It is also challenging in stochastic, changing, and structured environments; yet the brain makes accurate predictions in many situations. What computational architecture could enable this feat? Bayesian inference makes optimal predictions but is prohibitively difficult to compute. Here, we show that a specific recurrent neural network architecture enables simple and accurate solutions in several environments. This architecture relies on three mechanisms: gating, lateral connections, and recurrent weight training. Like the optimal solution and the human brain, such networks develop internal representations of their changing environment (including estimates of the environment’s latent variables and the precision of these estimates), leverage multiple levels of latent structure, and adapt their effective learning rate to changes without changing their connection weights. Being ubiquitous in the brain, gated recurrence could therefore serve as a generic building block to predict in real-life environments.
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Affiliation(s)
- Cédric Foucault
- INSERM, CEA, Université Paris-Saclay, Gif sur Yvette, France
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48
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Heurteloup C, Merchie A, Roux S, Bonnet-Brilhault F, Escera C, Gomot M. Neural repetition suppression to vocal and non-vocal sounds. Cortex 2021; 148:1-13. [DOI: 10.1016/j.cortex.2021.11.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/02/2021] [Accepted: 11/19/2021] [Indexed: 11/29/2022]
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Jia S, Xing D, Yu Z, Liu JK. Dissecting cascade computational components in spiking neural networks. PLoS Comput Biol 2021; 17:e1009640. [PMID: 34843460 PMCID: PMC8659421 DOI: 10.1371/journal.pcbi.1009640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 12/09/2021] [Accepted: 11/14/2021] [Indexed: 01/15/2023] Open
Abstract
Finding out the physical structure of neuronal circuits that governs neuronal responses is an important goal for brain research. With fast advances for large-scale recording techniques, identification of a neuronal circuit with multiple neurons and stages or layers becomes possible and highly demanding. Although methods for mapping the connection structure of circuits have been greatly developed in recent years, they are mostly limited to simple scenarios of a few neurons in a pairwise fashion; and dissecting dynamical circuits, particularly mapping out a complete functional circuit that converges to a single neuron, is still a challenging question. Here, we show that a recent method, termed spike-triggered non-negative matrix factorization (STNMF), can address these issues. By simulating different scenarios of spiking neural networks with various connections between neurons and stages, we demonstrate that STNMF is a persuasive method to dissect functional connections within a circuit. Using spiking activities recorded at neurons of the output layer, STNMF can obtain a complete circuit consisting of all cascade computational components of presynaptic neurons, as well as their spiking activities. For simulated simple and complex cells of the primary visual cortex, STNMF allows us to dissect the pathway of visual computation. Taken together, these results suggest that STNMF could provide a useful approach for investigating neuronal systems leveraging recorded functional neuronal activity. It is well known that the computation of neuronal circuits is carried out through the staged and cascade structure of different types of neurons. Nevertheless, the information, particularly sensory information, is processed in a network primarily with feedforward connections through different pathways. A peculiar example is the early visual system, where light is transcoded by the retinal cells, routed by the lateral geniculate nucleus, and reached the primary visual cortex. One meticulous interest in recent years is to map out these physical structures of neuronal pathways. However, most methods so far are limited to taking snapshots of a static view of connections between neurons. It remains unclear how to obtain a functional and dynamical neuronal circuit beyond the simple scenarios of a few randomly sampled neurons. Using simulated spiking neural networks of visual pathways with different scenarios of multiple stages, mixed cell types, and natural image stimuli, we demonstrate that a recent computational tool, named spike-triggered non-negative matrix factorization, can resolve these issues. It enables us to recover the entire structural components of neural networks underlying the computation, together with the functional components of each individual neuron. Utilizing it for complex cells of the primary visual cortex allows us to reveal every underpinning of the nonlinear computation. Our results, together with other recent experimental and computational efforts, show that it is possible to systematically dissect neural circuitry with detailed structural and functional components.
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Affiliation(s)
- Shanshan Jia
- Institute for Artificial Intelligence, Department of Computer Science and Technology, Peking University, Beijing, China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhaofei Yu
- Institute for Artificial Intelligence, Department of Computer Science and Technology, Peking University, Beijing, China
- * E-mail: (ZY); (JKL)
| | - Jian K. Liu
- School of Computing, University of Leeds, Leeds, United Kingdom
- * E-mail: (ZY); (JKL)
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50
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Regev TI, Markusfeld G, Deouell LY, Nelken I. Context Sensitivity across Multiple Time scales with a Flexible Frequency Bandwidth. Cereb Cortex 2021; 32:158-175. [PMID: 34289019 DOI: 10.1093/cercor/bhab200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/29/2021] [Accepted: 06/07/2021] [Indexed: 12/15/2022] Open
Abstract
Everyday auditory streams are complex, including spectro-temporal content that varies at multiple timescales. Using EEG, we investigated the sensitivity of human auditory cortex to the content of past stimulation in unattended sequences of equiprobable tones. In 3 experiments including 82 participants overall, we found that neural responses measured at different latencies after stimulus onset were sensitive to frequency intervals computed over distinct timescales. Importantly, early responses were sensitive to a longer history of stimulation than later responses. To account for these results, we tested a model consisting of neural populations with frequency-specific but broad tuning that undergo adaptation with exponential recovery. We found that the coexistence of neural populations with distinct recovery rates can explain our results. Furthermore, the adaptation bandwidth of these populations depended on spectral context-it was wider when the stimulation sequence had a wider frequency range. Our results provide electrophysiological evidence as well as a possible mechanistic explanation for dynamic and multiscale context-dependent auditory processing in the human cortex.
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Affiliation(s)
- Tamar I Regev
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,MIT Department of Brain and Cognitive Sciences, Cambridge, MA 02139, USA
| | - Geffen Markusfeld
- Department of Psychology, The Hebrew University of Jerusalem, Jerusalem 9190501, Israel
| | - Leon Y Deouell
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Department of Psychology, The Hebrew University of Jerusalem, Jerusalem 9190501, Israel
| | - Israel Nelken
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Department of Neurobiology, The Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
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