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Brands AM, Devore S, Devinsky O, Doyle W, Flinker A, Friedman D, Dugan P, Winawer J, Groen IIA. Temporal dynamics of short-term neural adaptation across human visual cortex. PLoS Comput Biol 2024; 20:e1012161. [PMID: 38815000 PMCID: PMC11166327 DOI: 10.1371/journal.pcbi.1012161] [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: 09/28/2023] [Revised: 06/11/2024] [Accepted: 05/12/2024] [Indexed: 06/01/2024] Open
Abstract
Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses between lower and higher visual brain areas and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences.
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Affiliation(s)
| | - Sasha Devore
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Orrin Devinsky
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Werner Doyle
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Adeen Flinker
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Daniel Friedman
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Patricia Dugan
- New York University Grossman School of Medicine, New York, New York, United States of America
| | - Jonathan Winawer
- Department of Psychology, New York University, New York, New York, United States of America
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Nagy B, Kojouharova P, Protzner AB, Gaál ZA. Investigating the Effect of Contextual Cueing with Face Stimuli on Electrophysiological Measures in Younger and Older Adults. J Cogn Neurosci 2024; 36:776-799. [PMID: 38437174 DOI: 10.1162/jocn_a_02135] [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] [Indexed: 03/06/2024]
Abstract
Extracting repeated patterns from our surroundings plays a crucial role in contextualizing information, making predictions, and guiding our behavior implicitly. Previous research showed that contextual cueing enhances visual search performance in younger adults. In this study, we investigated whether contextual cueing could also improve older adults' performance and whether age-related differences in the neural processes underlying implicit contextual learning could be detected. Twenty-four younger and 25 older participants performed a visual search task with contextual cueing. Contextual information was generated using repeated face configurations alongside random new configurations. We measured RT difference between new and repeated configurations; ERPs to uncover the neural processes underlying contextual cueing for early (N2pc), intermediate (P3b), and late (r-LRP) processes; and multiscale entropy and spectral power density analyses to examine neural dynamics. Both younger and older adults showed similar contextual cueing benefits in their visual search efficiency at the behavioral level. In addition, they showed similar patterns regarding contextual information processing: Repeated face configurations evoked decreased finer timescale entropy (1-20 msec) and higher frequency band power (13-30 Hz) compared with new configurations. However, we detected age-related differences in ERPs: Younger, but not older adults, had larger N2pc and P3b components for repeated compared with new configurations. These results suggest that contextual cueing remains intact with aging. Although attention- and target-evaluation-related ERPs differed between the age groups, the neural dynamics of contextual learning were preserved with aging, as both age groups increasingly utilized more globally grouped representations for repeated face configurations during the learning process.
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Affiliation(s)
- Boglárka Nagy
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
- Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary
| | - Petia Kojouharova
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Zsófia Anna Gaál
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
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3
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Brands AM, Devore S, Devinsky O, Doyle W, Flinker A, Friedman D, Dugan P, Winawer J, Groen IIA. Temporal dynamics of short-term neural adaptation across human visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.13.557378. [PMID: 37745548 PMCID: PMC10515883 DOI: 10.1101/2023.09.13.557378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses across the human visual hierarchy and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences.
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Reber TP, Mackay S, Bausch M, Kehl MS, Borger V, Surges R, Mormann F. Single-neuron mechanisms of neural adaptation in the human temporal lobe. Nat Commun 2023; 14:2496. [PMID: 37120437 PMCID: PMC10148801 DOI: 10.1038/s41467-023-38190-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 04/13/2023] [Indexed: 05/01/2023] Open
Abstract
A central function of the human brain is to adapt to new situations based on past experience. Adaptation is reflected behaviorally by shorter reaction times to repeating or similar stimuli, and neurophysiologically by reduced neural activity in bulk-tissue measurements with fMRI or EEG. Several potential single-neuron mechanisms have been hypothesized to cause this reduction of activity at the macroscopic level. We here explore these mechanisms using an adaptation paradigm with visual stimuli bearing abstract semantic similarity. We recorded intracranial EEG (iEEG) simultaneously with spiking activity of single neurons in the medial temporal lobes of 25 neurosurgical patients. Recording from 4917 single neurons, we demonstrate that reduced event-related potentials in the macroscopic iEEG signal are associated with a sharpening of single-neuron tuning curves in the amygdala, but with an overall reduction of single-neuron activity in the hippocampus, entorhinal cortex, and parahippocampal cortex, consistent with fatiguing in these areas.
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Affiliation(s)
- Thomas P Reber
- Faculty of Psychology, UniDistance Suisse, Brig, Switzerland.
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany.
| | - Sina Mackay
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Marcel Bausch
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Marcel S Kehl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Valeri Borger
- Department of Neurosurgery, University of Bonn Medical Centre, Bonn, Germany
| | - Rainer Surges
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Florian Mormann
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
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Mitsuhashi T, Sonoda M, Firestone E, Sakakura K, Jeong JW, Luat AF, Sood S, Asano E. Temporally and functionally distinct large-scale brain network dynamics supporting task switching. Neuroimage 2022; 254:119126. [PMID: 35331870 PMCID: PMC9173207 DOI: 10.1016/j.neuroimage.2022.119126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 02/25/2022] [Accepted: 03/20/2022] [Indexed: 11/04/2022] Open
Abstract
Objective: Our daily activities require frequent switches among competing responses at the millisecond time scale. We determined the spatiotemporal characteristics and functional significance of rapid, large-scale brain network dynamics during task switching. Methods: This cross-sectional study investigated patients with drug-resistant focal epilepsy who played a Lumosity cognitive flexibility training game during intracranial electroencephalography (iEEG) recording. According to a given task rule, unpredictably switching across trials, participants had to swipe the screen in the direction the stimulus was pointing or moving. Using this data, we described the spatiotemporal characteristics of iEEG high-gamma augmentation occurring more intensely during switch than repeat trials, unattributable to the effect of task rule (pointing or moving), within-stimulus congruence (the direction of stimulus pointing and moving was same or different in a given trial), or accuracy of an immediately preceding response. Diffusion-weighted imaging (DWI) tractography determined whether distant cortical regions showing enhanced activation during task switch trials were directly connected by white matter tracts. Trial-by-trial iEEG analysis deduced whether the intensity of task switch-related high-gamma augmentation was altered through practice and whether high-gamma amplitude predicted the accuracy of an upcoming response among switch trials. Results: The average number of completed trials during five-minute gameplay was 221.4 per patient (range: 171–285). Task switch trials increased the response times, whereas later trials reduced them. Analysis of iEEG signals sampled from 860 brain sites effectively elucidated the distinct spatiotemporal characteristics of task switch, task rule, and post-error-specific high-gamma modulations. Post-cue, task switch-related high-gamma augmentation was initiated in the right calcarine cortex after 260 ms, right precuneus after 330 ms, right entorhinal after 420 ms, and bilateral anterior middle-frontal gyri after 450 ms. DWI tractography successfully showed the presence of direct white matter tracts connecting the right visual areas to the precuneus and anterior middle-frontal regions but not between the right precuneus and anterior middle-frontal regions. Task-related high-gamma amplitudes in later trials were reduced in the calcarine, entorhinal and anterior middle-frontal regions, but increased in the precuneus. Functionally, enhanced post-cue precuneus high-gamma augmentation improved the accuracy of subsequent responses among switch trials. Conclusions: Our multimodal analysis uncovered two temporally and functionally distinct network dynamics supporting task switching. High-gamma augmentation in the visual-precuneus pathway may reflect the neural process facilitating an attentional shift to a given updated task rule. High-gamma activity in the visual-dorsolateral prefrontal pathway, rapidly reduced through practice, may reflect the cost of executing appropriate stimulus-response translation.
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Affiliation(s)
- Takumi Mitsuhashi
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurosurgery, Juntendo University, Tokyo, 1138421, Japan
| | - Masaki Sonoda
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurosurgery, Yokohama City University, Yokohama, 2360004, Japan
| | - Ethan Firestone
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Physiology, Wayne State University, Detroit, MI 48201, USA
| | - Kazuki Sakakura
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurosurgery, University of Tsukuba, Tsukuba, 3058575, Japan
| | - Jeong-Won Jeong
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA
| | - Aimee F Luat
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Pediatrics, Central Michigan University, Mount Pleasant, MI, 48858, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI, 48201, USA.
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Tivadar RI, Knight RT, Tzovara A. Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing. Front Hum Neurosci 2021; 15:702520. [PMID: 34489663 PMCID: PMC8416526 DOI: 10.3389/fnhum.2021.702520] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/12/2021] [Indexed: 01/22/2023] Open
Abstract
The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.
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Affiliation(s)
| | - Robert T. Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Athina Tzovara
- Institute of Computer Science, University of Bern, Bern, Switzerland
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Sleep-Wake Epilepsy Center | NeuroTec, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Babo-Rebelo M, Puce A, Bullock D, Hugueville L, Pestilli F, Adam C, Lehongre K, Lambrecq V, Dinkelacker V, George N. Visual Information Routes in the Posterior Dorsal and Ventral Face Network Studied with Intracranial Neurophysiology and White Matter Tract Endpoints. Cereb Cortex 2021; 32:342-366. [PMID: 34339495 PMCID: PMC8754371 DOI: 10.1093/cercor/bhab212] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 05/03/2021] [Accepted: 06/02/2021] [Indexed: 11/13/2022] Open
Abstract
Occipitotemporal regions within the face network process perceptual and socioemotional information, but the dynamics and information flow between different nodes of this network are still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight into the timing of face and social cue processing in the occipitotemporal brain and anchor the superior temporal cortex in dynamic gaze processing.
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Affiliation(s)
- M Babo-Rebelo
- Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre de Neuroimagerie de Recherche, CENIR, Centre MEG-EEG and STIM Platform, Paris F-75013, France.,Sorbonne Université, Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Experimental Neurosurgery Team, Paris F-75013, France.,Institute of Cognitive Neuroscience, University College London, WC1N 3AZ, London, UK
| | - A Puce
- Department of Psychological and Brain Sciences, Programs in Neuroscience, Cognitive Science, Indiana University, Bloomington, IN 47401, USA
| | - D Bullock
- Department of Psychological and Brain Sciences, Programs in Neuroscience, Cognitive Science, Indiana University, Bloomington, IN 47401, USA
| | - L Hugueville
- Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre de Neuroimagerie de Recherche, CENIR, Centre MEG-EEG and STIM Platform, Paris F-75013, France
| | - F Pestilli
- Department of Psychological and Brain Sciences, Programs in Neuroscience, Cognitive Science, Indiana University, Bloomington, IN 47401, USA
| | - C Adam
- Neurophysiology Department, AP-HP, GH Pitié-Salpêtrière-Charles Foix, Paris F-75013, France
| | - K Lehongre
- Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre de Neuroimagerie de Recherche, CENIR, Centre MEG-EEG and STIM Platform, Paris F-75013, France
| | - V Lambrecq
- Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre de Neuroimagerie de Recherche, CENIR, Centre MEG-EEG and STIM Platform, Paris F-75013, France.,Neurophysiology Department, AP-HP, GH Pitié-Salpêtrière-Charles Foix, Paris F-75013, France
| | - V Dinkelacker
- Department of Neurology, Rothschild Foundation, Paris F-75019, France
| | - N George
- Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre de Neuroimagerie de Recherche, CENIR, Centre MEG-EEG and STIM Platform, Paris F-75013, France.,Sorbonne Université, Institut du Cerveau-Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Experimental Neurosurgery Team, Paris F-75013, France
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Feuerriegel D, Vogels R, Kovács G. Evaluating the evidence for expectation suppression in the visual system. Neurosci Biobehav Rev 2021; 126:368-381. [PMID: 33836212 DOI: 10.1016/j.neubiorev.2021.04.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 02/16/2021] [Accepted: 04/02/2021] [Indexed: 01/25/2023]
Abstract
Reports of expectation suppression have shaped the development of influential predictive coding-based theories of visual perception. However recent work has highlighted confounding factors that may mimic or inflate expectation suppression effects. In this review, we describe four confounds that are prevalent across experiments that tested for expectation suppression: effects of surprise, attention, stimulus repetition and adaptation, and stimulus novelty. With these confounds in mind we then critically review the evidence for expectation suppression across probabilistic cueing, statistical learning, oddball, action-outcome learning and apparent motion designs. We found evidence for expectation suppression within a specific subset of statistical learning designs that involved weeks of sequence learning prior to neural activity measurement. Across other experimental contexts, whereby stimulus appearance probabilities were learned within one or two testing sessions, there was inconsistent evidence for genuine expectation suppression. We discuss how an absence of expectation suppression could inform models of predictive processing, repetition suppression and perceptual decision-making. We also provide suggestions for designing experiments that may better test for expectation suppression in future work.
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Affiliation(s)
- Daniel Feuerriegel
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
| | - Rufin Vogels
- Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Gyula Kovács
- Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
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Typical visual unfamiliar face individuation in left and right mesial temporal epilepsy. Neuropsychologia 2020; 147:107583. [PMID: 32771474 DOI: 10.1016/j.neuropsychologia.2020.107583] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 07/07/2020] [Accepted: 08/05/2020] [Indexed: 12/14/2022]
Abstract
Patients with chronic mesial temporal lobe epilepsy have difficulties at identifying familiar faces as well as at explicit old/new face recognition tasks. However, the extent to which these difficulties can be attributed to visual individuation of faces, independently of general explicit learning and semantic memory processes, is unknown. We tested 42 mesial temporal lobe epilepsy patients divided into two groups according to the side of epilepsy (left and right) and 42 matched controls on an extensive series of individuation tasks of unfamiliar faces and control visual stimuli, as well as on face detection, famous face recognition and naming, and face and non-face learning. Overall, both patient groups had difficulties at identifying and naming famous faces, and at explicitly learning face and non-face images. However, there was no group difference in accuracy between patients and controls at the two most widely used neuropsychological tests assessing visual individuation of unfamiliar faces (Benton Facial Recognition Test and Cambridge Face Memory Test). While patients with right mesial temporal lobe epilepsy were slowed down at all tasks, this effect was not specific to faces or even high-level stimuli. Importantly, both groups showed the same profile of response as typical participants across various stimulus manipulations, showing no evidence of qualitative processing impairments. Overall, these results point to largely preserved visual face individuation processes in patients with mesial temporal lobe epilepsy, with semantic and episodic memory difficulties being consistent with the localization of the neural structures involved in their epilepsy (anterior temporal cortex and hippocampus). These observations have implications for the prediction of neuropsychological outcomes in the case of surgery and support the validity of intracranial electroencephalographic recordings performed in this population to understand neural mechanisms of human face individuation, notably through intracranial electrophysiological recordings and stimulations.
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