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Leaman K, Yusif Rodriguez N, Ahuja A, Basu D, McKim TH, Desrochers TM. Monkey lateral prefrontal cortex subregions differentiate between perceptual exposure to visual stimuli. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.28.605513. [PMID: 39131320 PMCID: PMC11312473 DOI: 10.1101/2024.07.28.605513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
In everyday life, humans must parse visual stimuli with highly variable amounts of perceptual experience, ranging from incredibly familiar to entirely new. Even when choosing a novel to buy at a bookstore, one is exposed to covers they have seen numerous times intermixed with recently released titles. Visual exposure to stimuli is known to have distinct neural correlates in the lateral prefrontal cortex (LPFC) of nonhuman primates. However, it is currently unknown if this function may be localized to specific subregions within the LPFC. Specifically, we aimed to determine whether the posterior fundus of area 46 (p46f), an area that responds to deviations from a learned sequence, also responds to less frequently presented stimuli outside of the sequential context. We compare responses in p46f to the adjacent subregion, posterior ventral area 46 (p46v), which we propose may be more likely to show exposure-dependent responses due to its proximity to known novelty responsive regions. To test whether p46f or p46v represent perceptual exposure, we performed awake functional magnetic resonance imaging (fMRI) on three male monkeys as they observed visual stimuli that varied in their number of daily presentations. Here we show that p46v, but not p46f, shows preferential activation to stimuli with low perceptual exposure, which further localizes exposure-dependent effects in monkey LPFC. These results align with previous research that has found novelty responses in ventral LPFC and are consistent with the designation of p46f as having a sequence-specific function. Further, they expand on our knowledge of the specific role of LPFC subregions and localize perceptual exposure processing within this broader brain region.
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Affiliation(s)
| | | | - Aarit Ahuja
- Department of Neuroscience, Brown University
| | - Debaleena Basu
- Department of Neuroscience, Brown University
- Department of Biosciences and Bioengineering, IIT Bombay, Mumbai, Maharashtra, India
| | - Theresa H. McKim
- Department of Biology & Institute for Neuroscience, University of Nevada, Reno
| | - Theresa M. Desrochers
- Department of Neuroscience, Brown University
- Department of Psychiatry and Human Behavior, Brown University
- Robert J. and Nancy D. Carney Institute for Brain Sciences, Brown University
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2
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Nitzan N, Bennett C, Movshon JA, Olsen SR, Buzsáki G. Mixing novel and familiar cues modifies representations of familiar visual images and affects behavior. Cell Rep 2024; 43:114521. [PMID: 39024104 DOI: 10.1016/j.celrep.2024.114521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 04/15/2024] [Accepted: 07/03/2024] [Indexed: 07/20/2024] Open
Abstract
While visual responses to familiar and novel stimuli have been extensively studied, it is unknown how neuronal representations of familiar stimuli are affected when they are interleaved with novel images. We examined a large-scale dataset from mice performing a visual go/no-go change detection task. After training with eight images, six novel images were interleaved with two familiar ones. Unexpectedly, we found that the behavioral performance in response to familiar images was impaired when they were mixed with novel images. When familiar images were interleaved with novel ones, the dimensionality of their representation increased, indicating a perturbation of their neuronal responses. Furthermore, responses to familiar images in the primary visual cortex were less predictive of responses in higher-order areas, indicating less efficient communication. Spontaneous correlations between neurons were predictive of responses to novel images, but less so to familiar ones. Our study demonstrates the modification of representations of familiar images by novelty.
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Affiliation(s)
- Noam Nitzan
- New York University Neuroscience Institute, New York University, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA
| | | | - J Anthony Movshon
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - György Buzsáki
- New York University Neuroscience Institute, New York University, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
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3
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Hu A, Liu S, Yang H, Hu Y, Gu F. Investigating app icon recognition with event-related potentials. Neuroreport 2023; 34:521-525. [PMID: 37270845 DOI: 10.1097/wnr.0000000000001918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
In modern society, visual symbols such as logos, icons, and letters have become essential for communication and cognition, playing a crucial role in daily life. This study focuses on app icons, a frequently encountered type of symbol, and aims to investigate the neural mechanisms involved in their recognition. Specifically, our objective is to identify the timing and location of brain activity associated with this process. We presented participants with familiar and unfamiliar app icons and asked them to perform a repetition detection task while recording the event-related potentials (ERPs) elicited by these stimuli. Statistical analysis revealed a significant difference in the ERPs between familiar and unfamiliar icons, occurring around 220 ms in the parietooccipital scalp region. The source analysis indicated that this ERP difference originated in the ventral occipitotemporal cortex, specifically the fusiform gyrus. These findings suggest that the recognition of familiar app icons results in the activation of the ventral occipitotemporal cortex approximately 220 ms after exposure. Additionally, our findings, in conjunction with previous research on visual word recognition, suggest that the lexical orthographic processing of visual words is dependent on general visual processing mechanisms that are also involved in the recognition of familiar app icons. In essence, the ventral occipitotemporal cortex likely plays a crucial role in memorizing and recognizing visual symbols and objects, including familiar visual words.
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Affiliation(s)
- Axu Hu
- Key Laboratory of Language and Cultural Computing of Ministry of Education, Northwest Minzu University, Lanzhou
| | - Shu Liu
- Key Laboratory of Language and Cultural Computing of Ministry of Education, Northwest Minzu University, Lanzhou
| | - Hong Yang
- Neurocognitive Laboratory for Linguistics and Semiotics, College of Literature and Journalism, Sichuan University
- Digital Convergence Laboratory of Chinese Cultural Inheritance and Global Communication, Sichuan University, Chengdu, China
| | - Yirong Hu
- Neurocognitive Laboratory for Linguistics and Semiotics, College of Literature and Journalism, Sichuan University
- Digital Convergence Laboratory of Chinese Cultural Inheritance and Global Communication, Sichuan University, Chengdu, China
| | - Feng Gu
- Neurocognitive Laboratory for Linguistics and Semiotics, College of Literature and Journalism, Sichuan University
- Digital Convergence Laboratory of Chinese Cultural Inheritance and Global Communication, Sichuan University, Chengdu, China
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4
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Koyano KW, Esch EM, Hong JJ, Waidmann EN, Wu H, Leopold DA. Progressive neuronal plasticity in primate visual cortex during stimulus familiarization. SCIENCE ADVANCES 2023; 9:eade4648. [PMID: 36961903 PMCID: PMC10038346 DOI: 10.1126/sciadv.ade4648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
The primate brain is equipped to learn and remember newly encountered visual stimuli such as faces and objects. In the macaque inferior temporal (IT) cortex, neurons mark the familiarity of a visual stimulus through response modification, often involving a decrease in spiking rate. Here, we investigate the emergence of this neural plasticity by longitudinally tracking IT neurons during several weeks of familiarization with face images. We found that most neurons in the anterior medial (AM) face patch exhibited a gradual decline in their late-phase visual responses to multiple stimuli. Individual neurons varied from days to weeks in their rates of plasticity, with time constants determined by the number of days of exposure rather than the cumulative number of presentations. We postulate that the sequential recruitment of neurons with experience-modified responses may provide an internal and graded measure of familiarity strength, which is a key mnemonic component of visual recognition.
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Affiliation(s)
- Kenji W. Koyano
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Elena M. Esch
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Julie J. Hong
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Elena N. Waidmann
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Haitao Wu
- Chemistry and Synthesis Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - David A. Leopold
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda MD 20892, USA
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5
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Sihn D, Kim SP. Spatio-Temporally Efficient Coding Assigns Functions to Hierarchical Structures of the Visual System. Front Comput Neurosci 2022; 16:890447. [PMID: 35694611 PMCID: PMC9184804 DOI: 10.3389/fncom.2022.890447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 05/09/2022] [Indexed: 11/17/2022] Open
Abstract
Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given that visual hierarchical structures contain both bottom-up and top-down pathways, the derived principles should encompass these bidirectional pathways. However, existing principles such as predictive coding do not provide an effective principle for bidirectional pathways. Therefore, we propose a novel computational principle for visual hierarchical structures as spatio-temporally efficient coding underscored by the efficient use of given resources in both neural activity space and processing time. This coding principle optimises bidirectional information transmissions over hierarchical structures by simultaneously minimising temporal differences in neural responses and maximising entropy in neural representations. Simulations demonstrated that the proposed spatio-temporally efficient coding was able to assign the function of appropriate neural representations of natural visual scenes to visual hierarchical structures. Furthermore, spatio-temporally efficient coding was able to predict well-known phenomena, including deviations in neural responses to unlearned inputs and bias in preferred orientations. Our proposed spatio-temporally efficient coding may facilitate deeper mechanistic understanding of the computational processes of hierarchical brain structures.
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Affiliation(s)
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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Peter A, Stauch BJ, Shapcott K, Kouroupaki K, Schmiedt JT, Klein L, Klon-Lipok J, Dowdall JR, Schölvinck ML, Vinck M, Schmid MC, Fries P. Stimulus-specific plasticity of macaque V1 spike rates and gamma. Cell Rep 2021; 37:110086. [PMID: 34879273 PMCID: PMC8674536 DOI: 10.1016/j.celrep.2021.110086] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 06/28/2021] [Accepted: 11/11/2021] [Indexed: 11/02/2022] Open
Abstract
When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here, we show in awake macaque area V1 that both repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects show some persistence on the timescale of minutes. Gamma increases are specific to the presented stimulus location. Further, repetition effects on gamma and on firing rates generalize to images of natural objects. These findings support the notion that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters.
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Affiliation(s)
- Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; International Max Planck Research School for Neural Circuits, 60438 Frankfurt, Germany.
| | - Benjamin Johannes Stauch
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; International Max Planck Research School for Neural Circuits, 60438 Frankfurt, Germany
| | - Katharine Shapcott
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Frankfurt Institute for Advanced Studies, 60438 Frankfurt, Germany
| | - Kleopatra Kouroupaki
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Joscha Tapani Schmiedt
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Liane Klein
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; International Max Planck Research School for Neural Circuits, 60438 Frankfurt, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Johanna Klon-Lipok
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Jarrod Robert Dowdall
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; International Max Planck Research School for Neural Circuits, 60438 Frankfurt, Germany
| | - Marieke Louise Schölvinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Michael Christoph Schmid
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; University of Fribourg, Faculty of Science and Medicine, Chemin du Musée 5, 1700 Fribourg, Switzerland; Newcastle University, Biosciences Institute, Faculty of Medical Sciences, Framlington Place, Newcastle NE2 4HH, UK
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; International Max Planck Research School for Neural Circuits, 60438 Frankfurt, Germany; Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, the Netherlands.
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Stauch BJ, Peter A, Schuler H, Fries P. Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity. eLife 2021; 10:e68240. [PMID: 34473058 PMCID: PMC8412931 DOI: 10.7554/elife.68240] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 08/11/2021] [Indexed: 11/13/2022] Open
Abstract
Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ≈10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, increases induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.
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Affiliation(s)
- Benjamin J Stauch
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
- International Max Planck Research School for Neural CircuitsFrankfurtGermany
- Brain Imaging Center, Goethe University FrankfurtFrankfurtGermany
| | - Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
- International Max Planck Research School for Neural CircuitsFrankfurtGermany
| | - Heike Schuler
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurtGermany
- International Max Planck Research School for Neural CircuitsFrankfurtGermany
- Brain Imaging Center, Goethe University FrankfurtFrankfurtGermany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
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8
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Solomon SS, Tang H, Sussman E, Kohn A. Limited Evidence for Sensory Prediction Error Responses in Visual Cortex of Macaques and Humans. Cereb Cortex 2021; 31:3136-3152. [PMID: 33683317 DOI: 10.1093/cercor/bhab014] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 12/06/2020] [Accepted: 01/15/2021] [Indexed: 11/14/2022] Open
Abstract
A recent formulation of predictive coding theory proposes that a subset of neurons in each cortical area encodes sensory prediction errors, the difference between predictions relayed from higher cortex and the sensory input. Here, we test for evidence of prediction error responses in spiking responses and local field potentials (LFP) recorded in primary visual cortex and area V4 of macaque monkeys, and in complementary electroencephalographic (EEG) scalp recordings in human participants. We presented a fixed sequence of visual stimuli on most trials, and violated the expected ordering on a small subset of trials. Under predictive coding theory, pattern-violating stimuli should trigger robust prediction errors, but we found that spiking, LFP and EEG responses to expected and pattern-violating stimuli were nearly identical. Our results challenge the assertion that a fundamental computational motif in sensory cortex is to signal prediction errors, at least those based on predictions derived from temporal patterns of visual stimulation.
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Affiliation(s)
- Selina S Solomon
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Huizhen Tang
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Otorhinolaryngology - Head & Neck Surgery, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Elyse Sussman
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Otorhinolaryngology - Head & Neck Surgery, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Adam Kohn
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Ophthalmology and Vision Sciences, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
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9
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Vergnieux V, Vogels R. Statistical Learning Signals for Complex Visual Images in Macaque Early Visual Cortex. Front Neurosci 2020; 14:789. [PMID: 32848562 PMCID: PMC7411161 DOI: 10.3389/fnins.2020.00789] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 07/06/2020] [Indexed: 12/21/2022] Open
Abstract
Animals of several species, including primates, learn the statistical regularities of their environment. In particular, they learn the temporal regularities that occur in streams of visual images. Previous human neuroimaging studies reported discrepant effects of such statistical learning, ranging from stronger occipito-temporal activations for sequences in which image order was fixed, compared with sequences of randomly ordered images, to weaker activations for fixed-order sequences compared with sequences that violated the learned order. Several single-unit studies in macaque monkeys reported that after statistical learning of temporal regularities, inferior temporal (IT) neurons show reduced responses to learned fixed-order sequences of visual images compared with random or mispredicted sequences. However, it is unknown how other macaque brain areas respond to such temporal statistical regularities. To address this gap, we exposed rhesus monkeys (Macaca mulatta) to two types of sequences of complex images. The “regular” sequences consisted of a continuous stream of quartets, and within each quartet, the image order was fixed. The quartets themselves were displayed, uninterrupted, in a random order. The same monkeys were exposed to sequences of other images having a pseudorandomized order (“random” sequence). After exposure, both monkeys were scanned with functional MRI (fMRI) using a block design with three conditions: regular sequence, random sequence, and fixation-only blocks. A whole-brain analysis showed a reduced activation in mainly the occipito-temporal cortex for the regular compared to the random sequences. Marked response reductions for the regular sequence were observed in early extrastriate visual cortical areas, including area V2, despite the use of rather complex images of animals. These data suggest that statistical learning signals are already present in early visual areas of monkeys, even for complex visual images. These monkey fMRI data are in line with recent human fMRI studies that showed a reduced activation in early visual areas for predicted compared with mispredicted complex images.
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Affiliation(s)
- Victor Vergnieux
- Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Rufin Vogels
- Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Brain Institute, KU Leuven, Leuven, Belgium
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Manahova ME, Spaak E, de Lange FP. Familiarity Increases Processing Speed in the Visual System. J Cogn Neurosci 2019; 32:722-733. [PMID: 31765601 DOI: 10.1162/jocn_a_01507] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Familiarity with a stimulus leads to an attenuated neural response to the stimulus. Alongside this attenuation, recent studies have also observed a truncation of stimulus-evoked activity for familiar visual input. One proposed function of this truncation is to rapidly put neurons in a state of readiness to respond to new input. Here, we examined this hypothesis by presenting human participants with target stimuli that were embedded in rapid streams of familiar or novel distractor stimuli at different speeds of presentation, while recording brain activity using magnetoencephalography and measuring behavioral performance. We investigated the temporal and spatial dynamics of signal truncation and whether this phenomenon bears relationship to participants' ability to categorize target items within a visual stream. Behaviorally, target categorization performance was markedly better when the target was embedded within familiar distractors, and this benefit became more pronounced with increasing speed of presentation. Familiar distractors showed a truncation of neural activity in the visual system. This truncation was strongest for the fastest presentation speeds and peaked in progressively more anterior cortical regions as presentation speeds became slower. Moreover, the neural response evoked by the target was stronger when this target was preceded by familiar distractors. Taken together, these findings demonstrate that item familiarity results in a truncated neural response, is associated with stronger processing of relevant target information, and leads to superior perceptual performance.
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Affiliation(s)
- Mariya E Manahova
- Radboud University, Donders Institute for Brain, Cognition, and Behaviour
| | - Eelke Spaak
- Radboud University, Donders Institute for Brain, Cognition, and Behaviour
| | - Floris P de Lange
- Radboud University, Donders Institute for Brain, Cognition, and Behaviour
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Abstract
Information flow between the prefrontal and visual cortices is critical for visual behaviors such as visual search. To investigate its mechanisms, we simultaneously recorded spike and local field potential (LFP) signals in the frontal eye field (FEF) and area V4 while monkeys performed a free-gaze visual search task. During free-gaze search, spike-LFP coherence between FEF and V4 was enhanced in the theta rhythm (4-8 Hz) but suppressed in the alpha rhythm (8-13 Hz). Cross-frequency couplings during the Cue period before the search phase were related to monkey performance, with higher FEF theta-V4 gamma coupling and lower FEF alpha-V4 gamma coupling associated with faster search. Finally, feature-based attention during search enhanced spike-LFP coherence between FEF and V4 in the gamma and beta rhythms, whereas overt spatial attention reduced coherence at frequencies up to 30 Hz. These results suggest that oscillatory coupling may play an important role in mediating interactions between the prefrontal and visual cortices during visual search.
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Affiliation(s)
- Ting Yan
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen Guangdong 518055, China; E-mail:
| | - Hui-Hui Zhou
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen Guangdong 518055, China; E-mail:
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