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Mathematical Derivation of Wave Propagation Properties in Hierarchical Neural Networks with predictive coding Feedback Dynamics

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BULLETIN OF MATHEMATICAL BIOLOGY 2023年第9期85卷 80-80页

作者： Faye, Gregory Fouilhe, Guilhem VanRullen, Rufin Univ Toulouse Inst Math Toulouse UPS IMT UMR5219 F-31062 Toulouse 9 France Univ Toulouse Ctr Rech Cerveau & Cognit CerCo UMR5549 F-31052 Toulouse France Univ Toulouse ANITI F-31062 Toulouse France

Sensory perception (e.g., vision) relies on a hierarchy of cortical areas, in which neural activity propagates in both directions, to convey information not only about sensory inputs but also about cognitive states, expectations and predictions. At the macroscopic scale, neurophysiological experiments have described the corresponding neural signals as both forward and backward-travelling waves, sometimes with characteristic oscillatory signatures. It remains unclear, however, how such activity patterns relate to specific functional properties of the perceptual apparatus. Here, we present a mathematical framework, inspired by neural network models of predictive coding, to systematically investigate neural dynamics in a hierarchical perceptual system. We show that stability of the system can be systematically derived from the values of hyper-parameters controlling the different signals (related to bottom-up inputs, top-down prediction and error correction). Similarly, it is possible to determine in which direction, and at what speed neural activity propagates in the system. Different neural assemblies (reflecting distinct eigenvectors of the connectivity matrices) can simultaneously and independently display different properties in terms of stability, propagation speed or direction. We also derive continuous-limit versions of the system, both in time and in neural space. Finally, we analyze the possible influence of transmission delays between layers, and reveal the emergence of oscillations.

关键词： Hierarchical neural networks predictive coding Wave propagation

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Beta- and gamma-band activity reflect predictive coding in the processing of causal events

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SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE 2016年第6期11卷 973-980页

作者： van Pelt, Stan Heil, Lieke Kwisthout, Johan Ondobaka, Sasha van Rooij, Iris Bekkering, Harold Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Montessorilaan 3 NL-6525 HR Nijmegen Netherlands UCL Wellcome Trust Ctr Neuroimaging London England UCL Sobell Dept London England

In daily life, complex events are perceived in a causal manner, suggesting that the brain relies on predictive processes to model them. Within predictive coding theory, oscillatory beta-band activity has been linked to top-down predictive signals and gamma-band activity to bottom-up prediction errors. However, neurocognitive evidence for predictive coding outside lower-level sensory areas is scarce. We used magnetoencephalography to investigate neural activity during probabilitydependent action perception in three areas pivotal for causal inference, superior temporal sulcus, temporoparietal junction and medial prefrontal cortex, using bowling action animations. Within this network, Granger-causal connectivity in the beta-band was found to be strongest for backward top-down connections and gamma for feed-forward bottom-up connections. Moreover, beta-band power in TPJ increased parametrically with the predictability of the action kinematics-outcome sequences. Conversely, gamma-band power in TPJ and MPFC increased with prediction error. These findings suggest that the brain utilizes predictive-coding-like computations for higher-order cognition such as perception of causal events.

关键词： causal inference action perception predictive coding magnetoencephalography connectivity

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A predictive coding approach to modelling the perceived complexity of popular music drum patterns

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HELIYON 2023年第4期9卷 e15199页

作者： Senn, Olivier Lucerne Univ Appl Sci & Arts Mus Dept Arsenalstr 28a CH-6010 Kriens Switzerland

This study presents a method to estimate the complexity of popular music drum patterns based on a core idea from predictive coding. Specifically, it postulates that the complexity of a drum pattern depends on the quantity of surprisal it causes in the listener. Surprisal, according to predictive coding theory, is a numerical measure that takes large values when the perceiver's internal model of the surrounding world fails to predict the actual stream of sensory data (i.e. when the perception surprises the perceiver), and low values if model predictions and sensory data agree. The proposed new method first approximates a listener's internal model of a popular music drum pattern (using ideas on enculturation and a Bayesian learning process). It then quantifies the listener's surprisal evaluating the discrepancies between the predictions of the internal model and the actual drum pattern. It finally estimates drum pattern complexity from surprisal. The method was optimised and tested using a set of forty popular music drum patterns, for which empirical perceived complexity measurements are available. The new method provided complexity estimates that had a good fit with the empirical measurements (R2 = .852). The method was implemented as an R script that can be used to estimate the complexity of popular music drum patterns in the future. Simulations indicate that we can expect the method to predict perceived complexity with a good fit (R2 >= .709) in 99% of drum pattern sets randomly drawn from the Western popular music repertoire. These results suggest that surprisal indeed captures essential aspects of complexity, and that it may serve as a basis for a general theory of perceived complexity.

关键词： predictive coding Music perception Complexity Popular music Drums Modelling Rhythm

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Dysfunctions in striatal microstructure can enhance perceptual decision making through deficits in predictive coding

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BRAIN STRUCTURE & FUNCTION 2017年第8期222卷 3807-3817页

作者： Beste, Christian Mueckschel, Moritz Rosales, Raymond Domingo, Aloysius Lee, Lillian Ng, Arlene Klein, Christine Muenchau, Alexander Tech Univ Dresden Dept Child & Adolescent Psychiat Cognit Neurophysiol Fac Med Fetscherstr 74 D-01307 Dresden Germany Natl Inst Mental Hlth Expt Neurobiol Klecany Czech Republic Philippine Childrens Med Ctr XDP Study Grp Quezon City Philippines Univ Lubeck Inst Neurogenet Lubeck Germany Univ Santo Tomas Fac Neurol & Psychiat Manila Philippines

An important brain function is to predict upcoming events on the basis of extracted regularities of previous inputs. These predictive coding processes can disturb performance in concurrent perceptual decision-making and are known to depend on fronto-striatal circuits. However, it is unknown whether, and if so, to what extent striatal microstructural properties modulate these processes. We addressed this question in a human disease model of striosomal dysfunction, i.e. X-linked dystonia-parkinsonism (XDP), using high-density EEG recordings and source localization. The results show faster and more accurate perceptual decision-making performance during distraction in XDP patients compared to healthy controls. The electrophysiological data show that sensory memory and predictive coding processes reflected by the mismatch negativity related to lateral prefrontal brain regions were weakened in XDP patients and thus induced less cognitive conflict than in controls as reflected by the N2 event-related potential (ERP). Consequently, attentional shifting (P3a ERP) and reorientation processes (RON ERP) were less pronounced in the XDP group. Taken together, these results suggests that striosomal dysfunction is related to predictive coding deficits leading to a better performance in concomitant perceptual decision-making, probably because predictive coding does not interfere with perceptual decision-making processes. These effects may reflect striatal imbalances between the striosomes and the matrix compartment.

关键词： Sensory memory predictive coding Striosomes EEG Basal ganglia Perceptual decision making X-linked dystonia parkinsonism

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Systemic neurophysiological signals of auditory predictive coding

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PSYCHOPHYSIOLOGY 2024年第6期61卷 e14544页

作者： Munoz-Caracuel, Manuel Munoz, Vanesa Ruiz-Martinez, Francisco J. Vazquez Morejon, Antonio J. Gomez, Carlos M. Univ Seville Dept Expt Psychol Seville Spain Hosp Univ Virgen Rocio Mental Hlth Unit Seville Spain Univ Seville Dept Personal Evaluat & Psychol Treatments Seville Spain Univ Seville Expt Psychol Dept Human Psychobiol Lab Calle Camilo Jose Cela S-N Seville 41018 Spain

predictive coding framework posits that our brain continuously monitors changes in the environment and updates its predictive models, minimizing prediction errors to efficiently adapt to environmental demands. However, the underlying neurophysiological mechanisms of these predictive phenomena remain unclear. The present study aimed to explore the systemic neurophysiological correlates of predictive coding processes during passive and active auditory processing. Electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and autonomic nervous system (ANS) measures were analyzed using an auditory pattern-based novelty oddball paradigm. A sample of 32 healthy subjects was recruited. The results showed shared slow evoked potentials between passive and active conditions that could be interpreted as automatic predictive processes of anticipation and updating, independent of conscious attentional effort. A dissociated topography of the cortical hemodynamic activity and distinctive evoked potentials upon auditory pattern violation were also found between both conditions, whereas only conscious perception leading to imperative responses was accompanied by phasic ANS responses. These results suggest a systemic-level hierarchical reallocation of predictive coding neural resources as a function of contextual demands in the face of sensory stimulation. Principal component analysis permitted to associate the variability of some of the recorded signals. The predictive coding framework posits that our brain is a continuously active inferential system. Our findings provide empirical evidence of shared predictive coding brain signals between passive and active auditory processing that supports this hypothesis and reveals distinct multimodal neurophysiological responses to passively and actively processed prediction errors that suggest a systemic-level hierarchical optimization of neural resources according to contextual demands in the face of auditory stimulation.

关键词： ANS auditory processes ERPs fNIRS predictive coding systemic response

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Suppression of the auditory N1-component for heartbeat-related sounds reflects interoceptive predictive coding

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BIOLOGICAL PSYCHOLOGY 2014年第1期99卷 172-182页

作者： van Elk, Michiel Lenggenhager, Bigna Heydrich, Lukas Blanke, Olaf Ecole Polytech Fed Lausanne Brain Mind Inst Lab Cognit Neurosci CH-1015 Lausanne Switzerland Univ Amsterdam Dept Psychol NL-1012 WX Amsterdam Netherlands Univ Zurich Hosp Dept Neurol Neuropsychol Unit Zurich Switzerland Univ Hosp Geneva Dept Neurol Geneva Switzerland Ecole Polytech Fed Lausanne Ctr Neuroprosthet CH-1015 Lausanne Switzerland

Although many studies have elucidated the neurocognitive mechanisms supporting the processing of externally generated sensory signals, less is known about the processing of interoceptive signals related to the viscera. Drawing a parallel with research on agency and the perception of self-generated action effects, in the present EEG study we report a reduced auditory N1 component when participants listened to heartbeat-related sounds compared to externally generated sounds. The auditory suppression for heartbeat sounds was robust and persisted after controlling for ECG-related artifacts, the number of trials involved and the phase of the cardiac cycle. In addition, the auditory N1 suppression for heartbeat-related sounds had a comparable scalp distribution as the N1 suppression observed for actively generated sounds. This finding indicates that the brain automatically differentiates between heartbeat-related and externally generated sounds through a process of sensory suppression, suggesting that a comparable predictive mechanism may underlie the processing of heartbeat and action-related information. Extending recent behavioral data about cardio-visual integration, the present cardio-auditory EEG data reveal that the processing of sounds in auditory cortex is systematically modulated by an interoceptive cardiac signal. The findings are discussed with respect to theories of interoceptive awareness, emotion, predictive coding, and their relevance to bodily self-consciousness. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Interoception predictive coding Auditory N1 Sensory suppression EEG Agency

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Do rat auditory event related potentials exhibit human mismatch negativity attributes related to predictive coding?

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HEARING RESEARCH 2021年 399卷 107992-107992页

作者： Jalewa, Jaishree Todd, Juanita Michie, Patricia T. Hodgson, Deborah M. Harms, Lauren Univ Newcastle Sch Psychol Callaghan NSW Australia Univ Newcastle Prior Res Ctr Brain & Mental Hlth Res Callaghan NSW Australia Hunter Med Res Inst New Lambton Hts NSW Australia Univ Newcastle Sch Biomed Sci & Pharm Callaghan NSW Australia

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either 'uniquely human' or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable 'biomarker' for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Mismatch negativity Schizophrenia Mismatch responses Electroencephalogram Deviance Probability Jitter predictive coding

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The Neuronal Basis of predictive coding Along the Auditory Pathway: From the Subcortical Roots to Cortical Deviance Detection

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TRENDS IN HEARING 2018年第22期22卷 2331216518784822页

作者： Carbajal, Guillermo V. Malmierca, Manuel S. Univ Salamanca Inst Neurosci Castile & Leon Auditory Neurosci Lab Lab 1 Salamanca 37001 Castile & Leon Spain Salamanca Inst Biomed Res Salamanca Spain Univ Salamanca Fac Med Dept Cell Biol & Pathol Salamanca Spain

In this review, we attempt to integrate the empirical evidence regarding stimulus-specific adaptation (SSA) and mismatch negativity (MMN) under a predictive coding perspective (also known as Bayesian or hierarchical-inference model). We propose a renewed methodology for SSA study, which enables a further decomposition of deviance detection into repetition suppression and prediction error, thanks to the use of two controls previously introduced in MMN research: the many-standards and the cascade sequences. Focusing on data obtained with cellular recordings, we explain how deviance detection and prediction error are generated throughout hierarchical levels of processing, following two vectors of increasing computational complexity and abstraction along the auditory neuraxis: from subcortical toward cortical stations and from lemniscal toward nonlemniscal divisions. Then, we delve into the particular characteristics and contributions of subcortical and cortical structures to this generative mechanism of hierarchical inference, analyzing what is known about the role of neuromodulation and local microcircuitry in the emergence of mismatch signals. Finally, we describe how SSA and MMN are occurring at similar time frame and cortical locations, and both are affected by the manipulation of N-methyl-D-aspartate receptors. We conclude that there is enough empirical evidence to consider SSA and MMN, respectively, as the microscopic and macroscopic manifestations of the same physiological mechanism of deviance detection in the auditory cortex. Hence, the development of a common theoretical framework for SSA and MMN is all the more recommendable for future studies. In this regard, we suggest a shared nomenclature based on the predictive coding interpretation of deviance detection.

关键词： SSA MMN predictive coding deviance detection repetition suppression

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predictive Skim: Contrastive predictive coding for Low-Latency Online Speech Separation

Predictive Skim: Contrastive Predictive Coding for Low-Laten...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chenda Li Yifei Wu Yanmin Qian Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence AI Institute X-LANCE Lab Shanghai Jiao Tong University China

In online speech separation, there is a trade-off between inherent latency and speech separation performance. When processing the current input audio, looking ahead to more future context usually brings better speech separation performance but increases the algorithm latency, and vice versa. In the requirements of extremely low latency, the future context is expensive for the algorithm latency and may not be available. In this work, we apply the contrastive predictive coding (CPC) method to the previously proposed online Skipping Memory (SkiM) speech separation model, which is a low-latency model for online speech separation. During the training stage, the SkiM model is required to predict the future memory states given the history memory. By using CPC training, the predictive SkiM model shows stronger causal sequence modeling capacity in the online speech separation task. In addition, we explore a local context codec (LCC) method to reduce the computational cost, and we make qualitative analyses on it. Our best online predictive SkiM equipped with CPC and LCC gets 15.5 dB SI-SNR improvement on WSJ02-mix benchmark with 3-ms actual latency tested on a single-core CPU, which should be the state-of-the-art results among causal models.

关键词： Training Speech coding Computational modeling Memory management predictive models predictive coding Prediction algorithms

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A predictive coding account of value-based learning in PTSD: Implications for precision treatments

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NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 2022年 138卷 104704页

作者： Putica, Andrea Felmingham, Kim L. Garrido, Marta I. O'Donnell, Meaghan L. Van Dam, Nicholas T. Univ Melbourne Phoenix Australia Ctr Posttraumat Mental Hlth Dept Psychiat Parkville Vic Australia Univ Melbourne Melbourne Sch Psychol Sci Parkville Vic Australia Australian Ctr Posttraumat Mental Hlth 3-161 Barry St Carlton Vic 3053 Australia

While there are a number of recommended first-line interventions for posttraumatic stress disorder (PTSD), treatment efficacy has been less than ideal. Generally, PTSD treatment models explain symptom manifestation via associative learning, treating the individual as a passive organism -acted upon -rather than self as agent. At their core, predictive coding (PC) models introduce the fundamental role of self-conceptualisation and hierar-chical processing of one's sensory context in safety learning. This theoretical article outlines how predictive coding models of emotion offer a parsimonious framework to explain PTSD treatment response within a value-based decision-making framework. Our model integrates the predictive coding elements of the perceived: self, world and self-in the world and how they impact upon one or more discrete stages of value-based decision-making: (1) mental representation;(2) emotional valuation;(3) action selection and (4) outcome valuation. We discuss treatment and research implications stemming from our hypotheses.

关键词： Active inference Perceptual inference Bayesian brain Posttraumatic stress disorder predictive coding Interoception

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