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The effect of prior visual information on recognition of speech and sounds

CEREBRAL CORTEX 2008年第3期18卷 598-609页

作者： Noppeney, Uta Josephs, Oliver Hocking, Julia Price, Cathy J. Friston, Karl J. Max Planck Inst Biol Cybernet D-72076 Tubingen Germany Inst Neurol Wellcome Dept Imaging Neurosci London WC1N 3BG England

To identify and categorize complex stimuli such as familiar objects or speech, the human brain integrates information that is abstracted at multiple levels from its sensory inputs. Using cross-modal priming for spoken words and sounds, this functional magnetic resonance imaging study identified 3 distinct classes of visuoauditory incongruency effects: visuoauditory incongruency effects were selective for 1) spoken words in the left superior temporal sulcus (STS), 2) environmental sounds in the left angular gyrus (AG), and 3) both words and sounds in the lateral and medial prefrontal cortices (IFS/mPFC). From a cognitive perspective, these incongruency effects suggest that prior visual information influences the neural processes underlying speech and sound recognition at multiple levels, with the STS being involved in phonological, AG in semantic, and mPFC/IFS in higher conceptual processing. In terms of neural mechanisms, effective connectivity analyses (dynamic causal modeling) suggest that these incongruency effects may emerge via greater bottom-up effects from early auditory regions to intermediate multisensory integration areas (i.e., STS and AG). This is consistent with a predictive coding perspective on hierarchical Bayesian inference in the cortex where the domain of the prediction error (phonological vs. semantic) determines its regional expression (middle temporal gyrus/STS vs. AG/intraparietal sulcus).

关键词： cross-modal priming dynamic causal modeling effective connectivity multisensory integration predictive coding semantics

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Dynamic EEG analysis during language comprehension reveals interactive cascades between perceptual processing and sentential expectations

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BRAIN AND LANGUAGE 2020年 211卷 104875页

作者： Sarrett, McCall E. McMurray, Bob Kapnoula, Efthymia C. Univ Iowa Interdisciplinary Grad Program Neurosci 356 Med Res Ctr Iowa City IA 52242 USA Univ Iowa Dept Psychol & Brain Sci W311 Seashore Hall Iowa City IA 52242 USA Basque Ctr Cognit Brain & Language Mikeletegi Pasealekua 69 Donostia San Sebastian 20009 Gipuzkoa Spain

Understanding spoken language requires analysis of the rapidly unfolding speech signal at multiple levels: acoustic, phonological, and semantic. However, there is not yet a comprehensive picture of how these levels relate. We recorded electroencephalography (EEG) while listeners (N = 31) heard sentences in which we manipulated acoustic ambiguity (e.g., a bees/peas continuum) and sentential expectations (e.g., Honey is made by bees). EEG was analyzed with a mixed effects model over time to quantify how language processing cascades proceed on a millisecond-by-millisecond basis. Our results indicate: (1) perceptual processing and memory for fine-grained acoustics is preserved in brain activity for up to 900 msec;(2) contextual analysis begins early and is graded with respect to the acoustic signal;and (3) top-down predictions influence perceptual processing in some cases, however, these predictions are available simultaneously with the veridical signal. These mechanistic in-sights provide a basis for a better understanding of the cortical language network.

关键词： Electroencephalography Speech perception N100 N400 Semantic integration Top-down effects predictive coding

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predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model

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NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 2022年 132卷 1-22页

作者： Tarasi, Luca Trajkovic, Jelena Diciotti, Stefano di Pellegrino, Giuseppe Ferri, Francesca Ursino, Mauro Romei, Vincenzo Alma Mater Studiorum Univ Bologna Ctr Studi & Ric Neurosci Cognit Dipartimento Psicol Campus CesenaVia Rasi & Spinelli 176 I-47521 Cesena Italy Univ Bologna Dept Elect Elect & Informat Engn Guglielmo Marcon Cesena Italy Univ Bologna Alma Mater Res Inst Human Ctr Artificial Intellig Bologna Italy G dAnnunzio Univ Chieti Pescara Dept Neurosci Imaging & Clin Sci Chieti Italy IRCCS Fdn Santa Lucia I-00179 Rome Italy

The brain is a predictive machine. Converging data suggests a diametric predictive strategy from autism spec-trum disorders (ASD) to schizophrenic spectrum disorders (SSD). Whereas perceptual inference in ASD is rigidly shaped by incoming sensory information, the SSD population is prone to overestimate the precision of their priors' models. Growing evidence considers brain oscillations pivotal biomarkers to understand how top-down predictions integrate bottom-up input. Starting from the conceptualization of ASD and SSD as oscillopathies, we introduce an integrated perspective that ascribes the maladjustments of the predictive mechanism to dys-regulation of neural synchronization. According to this proposal, disturbances in the oscillatory profile do not allow the appropriate trade-off between descending predictive signal, overweighted in SSD, and ascending prediction errors, overweighted in ASD. These opposing imbalances both result in an ill-adapted reaction to external challenges. This approach offers a neuro-computational model capable of linking predictive coding theories with electrophysiological findings, aiming to increase knowledge on the neuronal foundations of the two spectra features and stimulate hypothesis-driven rehabilitation/research perspectives.

关键词： Autism Spectrum Disorder (ASD) Schizophrenic Spectrum Disorder (SSD) Autistic-schizophrenic continuum Decision-making predictive coding Brain oscillations Brain connectivity Oscillopathies

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Synaesthesia and autism: Different developmental outcomes from overlapping mechanisms?

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COGNITIVE NEUROPSYCHOLOGY 2020年第7-8期37卷 433-449页

作者： van Leeuwen, Tessa M. Neufeld, Janina Hughes, James Ward, Jamie Radboud Univ Nijmegen Donders Inst Brain Cognit Behav Nijmegen Netherlands Karolinska Inst & Stockholm Hlth Care Services Ctr Neurodevelopmental Disorders Centre Psychiat ResDept Women'sKIND Children's HlthReg Stockholm Stockholm Sweden Univ Sussex Sch Psychology Brighton England Radboud Univ Nijmegen Donders Inst BrainCONTACTTessa MLeeuwenCognit BehavMontessorilaan 3 Nijmegen Netherlands

Synaesthesia, a mixing of the senses, is more common in individuals with autism. Here, we review the evidence for the association between synaesthesia and autism with regard to their genetic background, brain connectivity, perception, cognitive mechanisms and their contribution to exceptional talents. Currently, the overlap between synaesthesia and autism is established most convincingly at the level of alterations in sensory sensitivity and perception, with synaesthetes showing autism-like profiles of sensory sensitivity and a bias towards details in perception. Shared features may include a predominance of local over global connectivity in the brain. When autism and synaesthesia co-occur in the same individual, the chance of developing heightened cognitive and memory abilities is increased. We discuss how the same theoretical models could potentially explain both conditions. Given the evidence, we believe the phenotypical overlap between autism and synaesthesia has been established clearly enough to invite future research to confirm overlapping mechanisms.

关键词： Synesthesia sensory sensitivity savant talent autism quotient predictive coding

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Prediction in the service of comprehension: Modulated early brain responses to omitted speech segments

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CORTEX 2014年第1期53卷 9-26页

作者： Bendixen, Alexandra Scharinger, Mathias Strauss, Antje Obleser, Jonas Univ Leipzig Inst Psychol D-04109 Leipzig Germany Carl von Ossietzky Univ Oldenburg Dept Psychol Auditory Psychophysiol Lab Cluster Excellence Hearing4a11European Med Sch D-26129 Oldenburg Germany Max Planck Inst Human Cognit & Brain Sci Max Planck Res Grp Auditory Cognit Leipzig Germany

Speech signals are often compromised by disruptions originating from external (e.g., masking noise) or internal (e.g., inaccurate articulation) sources. Speech comprehension thus entails detecting and replacing missing information based on predictive and restorative neural mechanisms. The present study targets predictive mechanisms by investigating the influence of a speech segment's predictability on early, modality-specific electrophysiological responses to this segment's omission. Predictability was manipulated in simple physical terms in a single-word framework (Experiment 1) or in more complex semantic terms in a sentence framework (Experiment 2). In both experiments, final consonants of the German words Lachs ([laks], salmon) or Latz ([lats], bib) were occasionally omitted, resulting in the syllable La ([lab no semantic meaning), while brain responses were measured with multi-channel electroencephalography (EEG). In both experiments, the occasional presentation of the fragment La elicited a larger omission response when the final speech segment had been predictable. The omission response occurred similar to 125-165 msec after the expected onset of the final segment and showed characteristics of the omission mismatch negativity (MMN), with generators in auditory cortical areas. Suggestive of a general auditory predictive mechanism at work, this main observation was robust against varying source of predictive information or attentional allocation, differing between the two experiments. Source localization further suggested the omission response enhancement by predictability to emerge from left superior temporal gyrus and left angular gyrus in both experiments, with additional experiment-specific contributions. These results are consistent with the existence of predictive coding mechanisms in the central auditory system, and suggestive of the general predictive properties of the auditory system to support spoken word recognition. (C) 2014 Elsevier Ltd. All rights

关键词： predictive coding Semantic expectation Auditory processing Omission mismatch negativity (MMN) Source localization

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Anterior insular cortex and emotional awareness

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JOURNAL OF COMPARATIVE NEUROLOGY 2013年第15期521卷 3371-3388页

作者： Gu, Xiaosi Hof, Patrick R. Friston, Karl J. Fan, Jin UCL Wellcome Trust Ctr Neuroimaging London WC1N 3BG England Virginia Tech Caril Res Inst Roanoke VA 24011 USA Mt Sinai Icahn Sch Med Fishberg Dept Neurosci New York NY 10029 USA Mt Sinai Icahn Sch Med Friedman Brain Inst New York NY 10029 USA Mt Sinai Icahn Sch Med Dept Psychiat New York NY 10029 USA CUNY Queens Coll Dept Psychol Flushing NY 11367 USA

This paper reviews the foundation for a role of the human anterior insular cortex (AIC) in emotional awareness, defined as the conscious experience of emotions. We first introduce the neuroanatomical features of AIC and existing findings on emotional awareness. Using empathy, the awareness and understanding of other people's emotional states, as a test case, we then present evidence to demonstrate: 1) AIC and anterior cingulate cortex (ACC) are commonly coactivated as revealed by a meta-analysis, 2) AIC is functionally dissociable from ACC, 3) AIC integrates stimulus-driven and top-down information, and 4) AIC is necessary for emotional awareness. We propose a model in which AIC serves two major functions: integrating bottom-up interoceptive signals with top-down predictions to generate a current awareness state and providing descending predictions to visceral systems that provide a point of reference for autonomic reflexes. We argue that AIC is critical and necessary for emotional awareness. J. Comp. Neurol. 521:3371-3388, 2013. (c) 2013 Wiley Periodicals, Inc.

关键词： anterior insular cortex emotional awareness empathy fMRI meta-analysis top-down bottom-up predictive coding

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Historical pitfalls and new directions in the neuroscience of emotion

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NEUROSCIENCE LETTERS 2019年第0期693卷 9-18页

作者： Barrett, Lisa Feldman Satpute, Ajay B. Northeastern Univ Dept Psychol 360 Huntington Ave Boston MA 02115 USA Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Charlestown MA USA Massachusetts Gen Hosp Dept Psychiat Charlestown MA USA Harvard Med Sch Charlestown MA USA Pomona Coll Dept Psychol Claremont CA 91711 USA Pomona Coll Dept Neurosci Claremont CA 91711 USA

In this article, we offer a brief history summarizing the last century of neuroscientific study of emotion, highlighting dominant themes that run through various schools of thought. We then summarize the current state of the field, followed by six key points for scientific progress that are inspired by a multi-level constructivist theory of emotion. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Emotion Affect fmri Construction Active inference predictive coding Allostasis Interoception Theory of constructed emotion

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Timing of repetition suppression of event-related potentials to unattended objects

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EUROPEAN JOURNAL OF NEUROSCIENCE 2020年第11期52卷 4432-4441页

作者： Stefanics, Gabor Heinzle, Jakob Czigler, Istvan Valentini, Elia Stephan, Klaas E. Univ Zurich Inst Biomed Engn Translat Neuromodeling Unit TNU Zurich Switzerland Swiss Fed Inst Technol Zurich Switzerland Univ Zurich Dept Econ Lab Social & Neural Syst Res Zurich Switzerland Hungarian Acad Sci Res Ctr Nat Sci Inst Cognit Neurosci & Psychol Budapest Hungary Univ Essex Dept Psychol Colchester Essex England UCL Wellcome Trust Ctr Neuroimaging London England

Current theories of object perception emphasize the automatic nature of perceptual inference. Repetition suppression (RS), the successive decrease of brain responses to repeated stimuli, is thought to reflect the optimization of perceptual inference through neural plasticity. While functional imaging studies revealed brain regions that show suppressed responses to the repeated presentation of an object, little is known about the intra-trial time course of repetition effects to everyday objects. Here, we used event-related potentials (ERPs) to task-irrelevant line-drawn objects, while participants engaged in a distractor task. We quantified changes in ERPs over repetitions using three general linear models that modeled RS by an exponential, linear, or categorical "change detection" function in each subject. Our aim was to select the model with highest evidence and determine the within-trial time-course and scalp distribution of repetition effects using that model. Model comparison revealed the superiority of the exponential model indicating that repetition effects are observable for trials beyond the first repetition. Model parameter estimates revealed a sequence of RS effects in three time windows (86-140, 322-360, and 400-446 ms) and with occipital, temporoparietal, and frontotemporal distribution, respectively. An interval of repetition enhancement (RE) was also observed (320-340 ms) over occipitotemporal sensors. Our results show that automatic processing of task-irrelevant objects involves multiple intervals of RS with distinct scalp topographies. These sequential intervals of RS and RE might reflect the short-term plasticity required for optimization of perceptual inference and the associated changes in prediction errors and predictions, respectively, over stimulus repetitions during automatic object processing.

关键词： event‐ related potential general linear modeling object recognition predictive coding repetition enhancement

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Duration estimation entails predicting when

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NEUROIMAGE 2015年 106卷 272-283页

作者： van Wassenhove, Virginie Lecoutre, Lucille CEA DSV I2BM NeuroSpin INSERMU992Cognit Neuroimaging Unit F-91191 Gif Sur Yvette France

The estimation of duration can be affected by context and surprise. Using MagnetoEncephaloGraphy (MEG), we tested whether increased neural activity during surprise and following neural suppression in two different contexts supported subjective time dilation (Eagleman and Pariyadath, 2009;Pariyadath and Eagleman, 2012). Sequences of three 300 ms frequency-modulated (FM, control) or pure tones (test) were presented and followed by a fourth FM varying in duration. In test, the last FM was perceived as significantly longer than veridical duration (Tse et al., 2004) but did not differ from the perceived duration in control. Several novel and distinct neural signatures were observed in duration estimation: first, neural suppression of standard stimuli was observed for the onset but not for the offset auditory evoked responses. Second, ramping activity increased with veridical duration in control where as at the same latency in test, the amplitude of the midlatency response increased with the distance of deviant durations. Third, in both conditions, the amplitude of the offset auditory evoked responses accounted well for participants' performance: the longer the perceived duration, the larger the offset response. Fourth, neural duration demarcated by the peak latencies of the onset and ramping evoked activities indexed a systematic time compression that reliably predicted subjective time perception. Our findings suggest that interval timing undergoes time compression by capitalizing on the predicted offset of an auditory event. (C) 2014 Elsevier Inc. All rights reserved.

关键词： MMN predictive coding Ramping activity Midlatency response Interval timing

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A neuro-cognitive process model of emotional intelligence

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BIOLOGICAL PSYCHOLOGY 2018年第0期139卷 131-151页

作者： Smith, Ryan Killgore, William D. S. Alkozei, Anna Lane, Richard D. Univ Arizona Dept Psychiat Tucson AZ USA Laureate Inst Brain Res 6655 South Yale Ave Tulsa OK 74136 USA

The construct of emotional intelligence (EI) broadly reflects the idea that individuals differ in their disposition/ability to adaptively generate, recognize, understand, and regulate the emotions of self and others. However, while the neural processes underlying such differences have begun to receive investigation, no brain-based model of EI has yet been proposed to help guide the design and interpretation of neuroimaging research in this area. In this article, we propose a neural model of EI to fill this need. This model incorporates recent insights from emotion theory, computational neuroscience, and large-scale network models of brain function. It also highlights several domain general processes - including those underlying conceptualization, automatic attention, habit formation, and cognitive control - that offer plausible targets for improving EI with training. Our model offers considerable promise in advancing understanding of intelligent emotional functioning and in guiding future neuroscience research on EI.

关键词： Emotional intelligence Neural systems Emotion perception Emotion regulation Emotional awareness predictive coding Active inference

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