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Expected TMS excites the motor system less effectively than unexpected stimulation

NEUROIMAGE 2021年 226卷 117541-117541页

作者： Tran, Dominic M. D. McNair, Nicolas A. Harris, Justin A. Livesey, Evan J. Univ Sydney Sch Psychol Camperdown NSW Australia

The brain's response to sensory input is modulated by prediction. For example, sounds that are produced by one's own actions, or those that are strongly predicted by environmental cues, elicit an attenuated N1 component in the auditory evoked potential. It has been suggested that this form of sensory attenuation to stimulation produced by one's own actions is the reason we are unable to tickle ourselves. Here we examined whether the neural response to direct stimulation of the brain is attenuated by prediction in a similar manner. Transcranial magnetic stimulation (TMS) applied over primary motor cortex can be used to gauge the excitability of the motor system. Motor-evoked potentials (MEPs), elicited by TMS and measured in peripheral muscles, are larger when actions are being prepared and smaller when actions are voluntarily suppressed. We tested whether the amplitude of MEPs was attenuated under circumstances where the TMS pulse can be reliably predicted, even though control of the relevant motor effector was never required. Self-initiation of the TMS pulse and reliable cuing of the TMS pulse both produced attenuated MEP amplitudes, compared to those generated programmatically in an unpredictable manner. These results suggest that predictive coding may be governed by domain-general mechanisms responsible for all forms predictive learning. The findings also have important methodological implications for designing TMS experiments that control for the predictability of TMS pulses.

关键词： predictive coding Temporal expectation Sensory attenuation Motor system Transcranial magnetic stimulation

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Cortical mapping of mismatch responses to independent acoustic features

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HEARING RESEARCH 2021年 399卷 107894-107894页

作者： An, HyunJung Auksztulewicz, Ryszard Kang, Hijee Schnupp, Jan W. H. City Univ Hong Kong Dept Biomed Sci Hong Kong Peoples R China Max Planck Inst Empir Aesthet Dept Neurosci Frankfurt Germany

predictive coding is an influential theory of neural processing underlying perceptual inference. However, it is unknown to what extent prediction violations of different sensory features are mediated in different regions in auditory cortex, with different dynamics, and by different mechanisms. This study investigates the neural responses to synthesized acoustic syllables, which could be expected or unexpected, along several features. By using electrocorticography (ECoG) in rat auditory cortex (subjects: adult female Wistar rats with normal hearing), we aimed at mapping regional differences in mismatch responses to different stimulus features. Continuous streams of morphed syllables formed roving oddball sequences in which each stimulus was repeated several times (thereby forming a standard) and subsequently replaced with a deviant stimulus which differed from the standard along one of several acoustic features: duration, pitch, interaural level differences (ILD), or consonant identity. Each of these features could assume one of several different levels, and the resulting change from standard to deviant could be larger or smaller. The deviant stimuli were then repeated to form new standards. We analyzed responses to the first repetition of a new stimulus (deviant) and its last repetition in a stimulus train (standard). For the ECoG recording, we implanted urethane-anaesthetized rats with 8 x 8 surface electrode arrays covering a 3 x 3 mm cortical patch encompassing primary and higher-order auditory cortex. We identified the response topographies and latencies of population activity evoked by acoustic stimuli in the rat auditory regions, and mapped their sensitivity to expectation violations along different acoustic features. For all features, the responses to deviant stimuli increased in amplitude relative to responses to standard stimuli. Deviance magnitude did not further modulate these mismatch responses. Mismatch responses to different feature violations showed a

关键词： predictive coding Mismatch negativity (MMN) Stimulus-specific adaptation (SSA) Multiple sensory features Electrocorticography (ECoG) Auditory event-related Potential (ERP)

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Brain activity predicts future learning success in intensive second language listening training

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BRAIN AND LANGUAGE 2021年 212卷 104839页

作者： Kajiura, Mayumi Jeong, Hyeonjeong Kawata, Natasha Y. S. Yu, Shaoyun Kinoshita, Toru Kawashima, Ryuta Sugiura, Motoaki Aichi Shukutoku Univ Div Foreign Language Educ Nagoya Aichi Japan Tohoku Univ Grad Sch Int Cultural Studies Sendai Miyagi Japan Tohoku Univ Inst Dev Aging & Canc Sendai Miyagi Japan Nagoya Univ Grad Sch Humanities Nagoya Aichi Japan Tohoku Univ Int Res Inst Disaster Sci Sendai Miyagi Japan

This study explores neural mechanisms underlying how prior knowledge gained from pre-listening transcript reading helps comprehend fast-rate speech in a second language (L2) and applies to L2 learning. Top-down predictive processing by prior knowledge may play an important role in L2 speech comprehension and improving listening skill. By manipulating the pre-listening transcript effect (pre-listening transcript reading [TR] vs. no transcript reading [NTR]) and type of languages (first language (L1) vs. L2), we measured brain activity in L2 learners, who performed fast-rate listening comprehension tasks during functional magnetic resonance imaging. Thereafter, we examined whether TR_L2-specific brain activity can predict individual learning success after an intensive listening training. The left angular and superior temporal gyri were key areas responsible for integrating prior knowledge to sensory input. Activity in these areas correlated significantly with gain scores on subsequent training, indicating that brain activity related to prior knowledge-sensory input integration predicts future learning success.

关键词： Prior knowledge predictive coding Second language acquisition fMRI Speech perception Fast-rate listening Pre-listening transcript reading Intensive second language listening training

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Computational framework for investigating predictive processing in auditory perception

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JOURNAL OF NEUROSCIENCE METHODS 2021年第0期360卷 109177-109177页

作者： Skerritt-Davis, Benjamin Elhilali, Mounya Johns Hopkins Univ 3400 N Charles St Baltimore MD 21218 USA

Background: The brain tracks sound sources as they evolve in time, collecting contextual information to predict future sensory inputs. Previous work in predictive coding typically focuses on the perception of predictable stimuli, leaving the implementation of these same neural processes in more complex, real-world environments containing randomness and uncertainty up for debate. New Method: To facilitate investigation into the perception of less tightly-controlled listening scenarios, we present a computational model as a tool to ask targeted questions about the underlying predictive processes that connect complex sensory inputs to listener behavior and neural responses. In the modeling framework, observed sound features (e.g. pitch) are tracked sequentially using Bayesian inference. Sufficient statistics are inferred from past observations at multiple time scales and used to make predictions about future observation while tracking the statistical structure of the sensory input. Results: Facets of the model are discussed in terms of their application to perceptual research, and examples taken from real-world audio demonstrate the model's flexibility to capture a variety of statistical structures along various perceptual dimensions. Comparison with Existing Methods: Previous models are often targeted toward interpreting a particular experimental paradigm (e.g., oddball paradigm), perceptual dimension (e.g., pitch processing), or task (e.g., speech segregation), thus limiting their ability to generalize to other domains. The presented model is designed as a flexible and practical tool for broad application. Conclusion: The model is presented as a general framework for generating new hypotheses and guiding investigation into the neural processes underlying predictive coding of complex scenes.

关键词： predictive coding Statistical inference Bayesian inference uncertainty neural decoding

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Deviance detection in physiologically identified cell types in the rat auditory cortex

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HEARING RESEARCH 2021年 399卷 107997-107997页

作者： Perez-Gonzalez, David Parras, Gloria G. Morado-Diaz, Camilo J. Aedo-Sanchez, Cristian Carbajal, Guillermo V. Malmierca, Manuel S. Univ Salamanca Inst Neurosci Castilla & Leon INCYL Cognit & Auditory Neurosci Lab Lab 1 Salamanca Spain Inst Biomed Res Salamanca IBSAL Salamanca Spain Univ Salamanca Fac Med Dept Cell Biol & Pathol Salamanca Spain

Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression. (C) 2020 Elsevier B.V. All rights reserved.

关键词： predictive coding Stimulus-specific adaptation Spike width analysis Inhibitory Pyramidal Fast spiking neurons Regular spiking neurons

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Violation of rhythmic expectancies can elicit late frontal gamma activity nested in theta oscillations

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PSYCHOPHYSIOLOGY 2021年第11期58卷 13909-13909页

作者： Edalati, M. Mahmoudzadeh, M. Safaie, J. Wallois, F. Moghimi, S. CURS Grp Rech Anal Multimodale Fonct Cerebrale INSERM UMR1105 F-80036 Amiens France Ferdowsi Univ Mashhad Elect Engn Dept Mashhad Razavi Khorasan Iran CHU Amiens Sud EFSN Pediat INSERM UMR1105 Amiens France

Rhythm processing involves building expectations according to the hierarchical temporal structure of auditory events. Although rhythm processing has been addressed in the context of predictive coding, the properties of the oscillatory response in different cortical areas are still not clear. We explored the oscillatory properties of the neural response to rhythmic incongruence and the cross-frequency coupling between multiple frequencies to further investigate the mechanisms underlying rhythm perception. We designed an experiment to investigate the neural response to rhythmic deviations in which the tone either arrived earlier than expected or the tone in the same metrical position was omitted. These two manipulations modulate the rhythmic structure differently, with the former creating a larger violation of the general structure of the musical stimulus than the latter. Both deviations resulted in an MMN response, whereas only the rhythmic deviant resulted in a subsequent P3a. Rhythmic deviants due to the early occurrence of a tone, but not omission deviants, seemed to elicit a late high gamma response (60-80 Hz) at the end of the P3a over the left frontal region, which, interestingly, correlated with the P3a amplitude over the same region and was also nested in theta oscillations. The timing of the elicited high-frequency gamma oscillations related to rhythmic deviation suggests that it might be related to the update of the predictive neural model, corresponding to the temporal structure of the events in higher-level cortical areas.

关键词： event-related potential mismatch negativity phase-amplitude coupling prediction error predictive coding

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The habenula clock influences response to a stressor

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NEUROBIOLOGY OF STRESS 2021年 15卷 100403页

作者： Basnakova, Adriana Cheng, Ruey-Kuang Chia, Joanne Shu Ming D'Agostino, Giuseppe Suryadi Tan, Germaine Jia Hui Langley, Sarah R. Jesuthasan, Suresh Univ Manchester Sch Biol Sci Manchester Lancs England Inst Mol & Cell Biol Singapore Singapore Nanyang Technol Univ Lee Kong Chian Sch Med 59 Nanyang Dr Singapore 636921 Singapore Nanyang Technol Univ Sch Phys & Math Sci Singapore Singapore

The response of an animal to a sensory stimulus depends on the nature of the stimulus and on expectations, which are mediated by spontaneous activity. Here, we ask how circadian variation in the expectation of danger, and thus the response to a potential threat, is controlled. We focus on the habenula, a mediator of threat response that functions by regulating neuromodulator release, and use zebrafish as the experimental system. Single cell transcriptomics indicates that multiple clock genes are expressed throughout the habenula, while quantitative in situ hybridization confirms that the clock oscillates. Two-photon calcium imaging indicates a circadian change in spontaneous activity of habenula neurons. To assess the role of this clock, a truncated clocka gene was specifically expressed in the habenula. This partially inhibited the clock, as shown by changes in per3 expression as well as altered day-night variation in dopamine, serotonin and acetylcholine levels. Behaviourally, anxiety-like responses evoked by an alarm pheromone were reduced. Circadian effects of the pheromone were disrupted, such that responses in the day resembled those at night. Behaviours that are regulated by the pineal clock and not triggered by stressors were unaffected. We suggest that the habenula clock regulates the expectation of danger, thus providing one mechanism for circadian change in the response to a stressor.

关键词： Anxiety Circadian clock Habenula Spontaneous activity predictive coding

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Statistical Inference in Auditory Perception

Statistical Inference in Auditory Perception

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作者： Skerritt-Davis, Benjamin M Johns Hopkins University

学位级别：博士

The human auditory system effortlessly parses complex sensory inputs despite the ever-present randomness and uncertainty in real-world scenes. To achieve this, the brain tracks sounds as they evolve in time, collecting contextual information to construct an internal model of the external world for predicting future events. Previous work has shown the brain is sensitive to many predictable (and often complex) patterns in sequential sounds. However, real-world environments exhibit a broader spectrum of predictability, and moreover, the level of predictability is constantly in flux. How does the brain build robust internal representations of such stochastic and dynamic acoustic environments? This question is addressed through the lens of a computational model based in statistical inference. Embodying theories from Bayesian perception and predictive coding, the model posits the brain collects statistical estimates from sounds and maintains multiple hypotheses for the degree of context to include in predictive processes. As a potential computational solution for perception of complex and dynamic sounds, this model is used to connect sensory inputs with listeners' responses in a series of human behavioral and electroencephalography (EEG) experiments incorporating uncertainty. Experimental results point toward the underlying sufficient statistics collected by the brain, and the extension of these statistical representations to multiple dimensions is examined along spectral and spatial dimensions. The computational model guides interpretation of behavioral and neural responses, revealing multiplexed responses in the brain corresponding to different levels of predictive processing. In addition, the model is used to explain individual differences across listeners highlighted by uncertainty. The proposed computational model was developed based on first principles, and its usefulness is not limited to the experiments presented here. The model was used to replicate a range of pr

关键词： predictive coding EEG Psychophysics Bayesian inference Uncertainty Computational model

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The posterior auditory field is the chief generator of prediction error signals in the auditory cortex

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NEUROIMAGE 2021年 242卷 118446-118446页

作者： Parras, Gloria G. Casado-Roman, Lorena Schroeger, Erich Malmierca, Manuel S. Univ Salamanca Inst Neurosci Castilla Leon INCYL Cognit & Auditory Neurosci Lab CANELAB Salamanca 37007 Spain Inst Biomed Res Salamanca IBSAL Salamanca Spain Univ Leipzig Inst Psychol Leipzig Germany Univ Salamanca Dept Cell Biol & Pathol Fac Med Salamanca Spain

The auditory cortex (AC) encompasses distinct fields subserving partly different aspects of sound processing. One essential function of the AC is the detection of unpredicted sounds, as revealed by differential neural activity to predictable and unpredictable sounds. According to the predictive coding framework, this effect can be explained by repetition suppression and/or prediction error signaling. The present study investigates functional specialization of the rat AC fields in repetition suppression and prediction error by combining a tone frequency oddball paradigm (involving high-probable standard and low-probable deviant tones) with two different control sequences (many-standards and cascade). Tones in the control sequences were comparable to deviant events with respect to neural adaptation but were not violating a regularity. Therefore, a difference in the neural activity between deviant and control tones indicates a prediction error effect, whereas a difference between control and standard tones indicates a repetition suppression effect. Single-unit recordings revealed by far the largest prediction error effects for the posterior auditory field, while the primary auditory cortex, the anterior auditory field, the ventral auditory field, and the suprarhinal auditory field were dominated by repetition suppression effects. Statistically significant repetition suppression effects occurred in all AC fields, whereas prediction error effects were less robust in the primary auditory cortex and the anterior auditory field. Results indicate that the non-lemniscal, posterior auditory field is more engaged in context-dependent processing underlying deviancedetection than the other AC fields, which are more sensitive to stimulus-dependent effects underlying differential degrees of neural adaptation.

关键词： Stimulus-specific adaptation Mismatch negativity predictive coding Repetition suppression Auditory cortical fields Single units

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Is prediction nothing more than multi-scale pattern completion of the future?

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BRAIN RESEARCH 2021年第0期1768卷 147578-147578页

作者： Falandays, J. Benjamin Nguyen, Benjamin Spivey, Michael J. Univ Calif Merced Dept Cognit & Informat Sci 5200 N Lake Rd Merced CA 95343 USA

While the notion of the brain as a prediction machine has been extremely influential and productive in cognitive science, there are competing accounts of how best to model and understand the predictive capabilities of brains. One prominent framework is of a "Bayesian brain" that explicitly generates predictions and uses resultant errors to guide adaptation. We suggest that the prediction-generation component of this framework may involve little more than a pattern completion process. We first describe pattern completion in the domain of visual perception, highlighting its temporal extension, and show how this can entail a form of prediction in time. Next, we describe the forward momentum of entrained dynamical systems as a model for the emergence of predictive processing in non-predictive systems. Then, we apply this reasoning to the domain of language, where explicitly predictive models are perhaps most popular. Here, we demonstrate how a connectionist model, TRACE, exhibits hallmarks of predictive processing without any representations of predictions or errors. Finally, we present a novel neural network model, inspired by reservoir computing models, that is entirely unsupervised and memoryless, but nonetheless exhibits prediction-like behavior in its pursuit of homeostasis. These explorations demonstrate that brain-like systems can get prediction "for free," without the need to posit formal logical representations with Bayesian probabilities or an inference machine that holds them in working memory.

关键词： predictive processing predictive coding Pattern completion Language Dynamical systems theory Neural networks

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