scholarly journals Emotional learning promotes perceptual predictions by remodeling stimulus representation in visual cortex

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
E. Meaux ◽  
V. Sterpenich ◽  
P. Vuilleumier
Keyword(s):  
Visual Cortex ◽  
Temporal Cortex ◽  
Visual Stream ◽  
Identity Information ◽  
Neuronal Populations ◽  
Stimulus Representation ◽  
Sensory Cortices ◽  
Sensory Predictions ◽  
Ventral Visual Stream ◽  
Specific Identity

AbstractEmotions exert powerful effects on perception and memory, notably by modulating activity in sensory cortices so as to capture attention. Here, we examine whether emotional significance acquired by a visual stimulus can also change its cortical representation by linking neuronal populations coding for different memorized versions of the same stimulus, a mechanism that would facilitate recognition across different appearances. Using fMRI, we show that after pairing a given face with threat through conditioning, viewing this face activates the representation of another viewpoint of the same person, which itself was never conditioned, leading to robust repetition-priming across viewpoints in the ventral visual stream (including medial fusiform, lateral occipital, and anterior temporal cortex). We also observed a functional-anatomical segregation for coding view-invariant and view-specific identity information. These results indicate emotional signals may induce plasticity of stimulus representations in visual cortex, serving to generate new sensory predictions about different appearances of threat-associated stimuli.

Using Convolutional Neural Networks to measure the contribution of visual features to the representation of object animacy in the brain

2019 ◽  
Author(s):  
Sushrut Thorat
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Temporal Cortex ◽  
Large Degree ◽  
Visual Features ◽  
Visual Feature ◽  
Visual Stream ◽  
Feature Information ◽  
Ventral Visual Stream ◽  
Animal Images

A mediolateral gradation in neural responses for images spanning animals to artificial objects is observed in the ventral temporal cortex (VTC). Which information streams drive this organisation is an ongoing debate. Recently, in Proklova et al. (2016), the visual shape and category (“animacy”) dimensions in a set of stimuli were dissociated using a behavioural measure of visual feature information. fMRI responses revealed a neural cluster (extra-visual animacy cluster - xVAC) which encoded category information unexplained by visual feature information, suggesting extra-visual contributions to the organisation in the ventral visual stream. We reassess these findings using Convolutional Neural Networks (CNNs) as models for the ventral visual stream. The visual features developed in the CNN layers can categorise the shape-matched stimuli from Proklova et al. (2016) in contrast to the behavioural measures used in the study. The category organisations in xVAC and VTC are explained to a large degree by the CNN visual feature differences, casting doubt over the suggestion that visual feature differences cannot account for the animacy organisation. To inform the debate further, we designed a set of stimuli with animal images to dissociate the animacy organisation driven by the CNN visual features from the degree of familiarity and agency (thoughtfulness and feelings). Preliminary results from a new fMRI experiment designed to understand the contribution of these non-visual features are presented.

scholarly journals Visual exposure optimizes stimulus encoding in primary visual cortex

2018 ◽  
Author(s):  
Andreea Lazar ◽  
Chris Lewis ◽  
Pascal Fries ◽  
Wolf Singer ◽  
Danko Nikolić
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Neuronal Response ◽  
Extended Period ◽  
Sensory Cells ◽  
Neuronal Populations ◽  
Visual Exposure ◽  
Early Visual Cortex ◽  
Sensory Cortices

SummarySensory exposure alters the response properties of individual neurons in primary sensory cortices. However, it remains unclear how these changes affect stimulus encoding by populations of sensory cells. Here, recording from populations of neurons in cat primary visual cortex, we demonstrate that visual exposure enhances stimulus encoding and discrimination. We find that repeated presentation of brief, high-contrast shapes results in a stereotyped, biphasic population response consisting of a short-latency transient, followed by a late and extended period of reverberatory activity. Visual exposure selectively improves the stimulus specificity of the reverberatory activity, by increasing the magnitude and decreasing the trial-to-trial variability of the neuronal response. Critically, this improved stimulus encoding is distributed across the population and depends on precise temporal coordination. Our findings provide evidence for the existence of an exposure-driven optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.

scholarly journals Unsupervised Models of Mouse Visual Cortex

2021 ◽  
Author(s):  
Aran Nayebi ◽  
Nathan C. L. Kong ◽  
Chengxu Zhuang ◽  
Justin L. Gardner ◽  
Anthony M. Norcia ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Network Architectures ◽  
Deep Convolutional Neural Networks ◽  
Visual Stream ◽  
Computational Theory ◽  
Visual Coding ◽  
Ventral Visual Stream ◽  
Mouse Visual Cortex ◽  
Image Transformations

Task-optimized deep convolutional neural networks are the most quantitatively accurate models of the primate ventral visual stream. However, such networks are implausible as a model of the mouse visual system because mouse visual cortex has a known shallower hierarchy and the supervised objectives these networks are typically trained with are likely neither ethologically relevant in content nor in quantity. Here we develop shallow network architectures that are more consistent with anatomical and physiological studies of mouse visual cortex than current models. We demonstrate that hierarchically shallow architectures trained using contrastive objective functions applied to visual-acuity-adapted images achieve neural prediction performance that exceed those of the same architectures trained in a supervised manner and result in the most quantitatively accurate models of the mouse visual system. Moreover, these models' neural predictivity significantly surpasses those of supervised, deep architectures that are known to correspond well to the primate ventral visual stream. Finally, we derive a novel measure of inter-animal consistency, and show that the best models closely match this quantity across visual areas. Taken together, our results suggest that contrastive objectives operating on shallow architectures with ethologically-motivated image transformations may be a biologically-plausible computational theory of visual coding in mice.

scholarly journals The lexical categorization model: A computational model of left-ventral occipito-temporal cortex activation in visual word recognition

2016 ◽  
Author(s):  
Benjamin Gagl ◽  
Fabio Richlan ◽  
Philipp Ludersdorfer ◽  
Jona Sassenhagen ◽  
Susanne Eisenhauer ◽  
...  
Keyword(s):  
Temporal Cortex ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Functional Magnetic Resonance ◽  
Linguistic Processing ◽  
Visual Stream ◽  
Frontal Brain ◽  
Ventral Visual Stream ◽  
Better Than ◽  
Categorization Model

AbstractTo characterize the left-ventral occipito-temporal cortex (lvOT) role during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filter out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging. Empirically, using functional magnetic resonance imaging, we demonstrate that quantitative LCM simulations predict lvOT activation across three studies better than alternative models. Besides, we found that word-likeness, which is assumed as input to LCM, is represented posterior to lvOT. In contrast, a dichotomous word/non-word contrast, which is assumed as the LCM’s output, could be localized to upstream frontal brain regions. Finally, we found that training lexical categorization results in more efficient reading. Thus, we propose a ventral-visual-stream processing framework for reading involving word-likeness extraction followed by lexical categorization, before meaning extraction.

scholarly journals Development differentially sculpts receptive fields across human visual cortex

2017 ◽  
Author(s):  
Jesse Gomez ◽  
Vaidehi Natu ◽  
Brianna Jeska ◽  
Michael Barnett ◽  
Kalanit Grill-Spector
Keyword(s):  
Visual Cortex ◽  
Visual Field ◽  
Right Hemisphere ◽  
Receptive Fields ◽  
Visual Stream ◽  
Differential Development ◽  
Processing Information ◽  
Ventral Visual Stream ◽  
Visual Field Maps ◽  
The Right

ABSTRACTReceptive fields (RFs) processing information in restricted parts of the visual field are a key property of neurons in the visual system. However, how RFs develop in humans is unknown. Using fMRI and population receptive field (pRF) modeling in children and adults, we determined where and how pRFs develop across the ventral visual stream. We find that pRF properties in visual field maps, V1 through VO1, are adult-like by age 5. However, pRF properties in face- and word-selective regions develop into adulthood, increasing the foveal representation and the visual field coverage for faces in the right hemisphere and words in the left hemisphere. Eye-tracking indicates that pRF changes are related to changing fixation patterns on words and faces across development. These findings suggest a link between viewing behavior of faces and words and the differential development of pRFs across visual cortex, potentially due to competition on foveal coverage.

scholarly journals Suppressed sensory response to predictable object stimuli throughout the ventral visual stream

2017 ◽  
Author(s):  
David Richter ◽  
Matthias Ekman ◽  
Floris P. de Lange
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Object Perception ◽  
Sensory Response ◽  
Neural Basis ◽  
Visual Stream ◽  
Lateral Occipital Complex ◽  
Sensory Representation ◽  
Statistical Regularities ◽  
Ventral Visual Stream

AbstractPrediction plays a crucial role in perception, as prominently suggested by predictive coding theories. However, the exact form and mechanism of predictive modulations of sensory processing remain unclear, with some studies reporting a downregulation of the sensory response for predictable input, while others observed an enhanced response. In a similar vein, downregulation of the sensory response for predictable input has been linked to either sharpening or dampening of the sensory representation, which are opposite in nature. In the present study we set out to investigate the neural consequences of perceptual expectation of object stimuli throughout the visual hierarchy, using fMRI in human volunteers. Participants (n=24) were exposed to pairs of sequentially presented object images in a statistical learning paradigm, in which the first object predicted the identity of the second object. Image transitions were not task relevant; thus all learning of statistical regularities was incidental. We found strong suppression of neural responses to expected compared to unexpected stimuli throughout the ventral visual stream, including primary visual cortex (V1), lateral occipital complex (LOC), and anterior ventral visual areas. Expectation suppression in LOC, but not V1, scaled positively with image preference, lending support to the dampening account of expectation suppression in object perception.Significance StatementStatistical regularities permeate our world and help us to perceive and understand our surroundings. It has been suggested that the brain fundamentally relies on predictions and constructs models of the world in order to make sense of sensory information. Previous research on the neural basis of prediction has documented expectation suppression, i.e. suppressed responses to expected compared to unexpected stimuli. In the present study we queried the presence and characteristics of expectation suppression throughout the ventral visual stream. We demonstrate robust expectation suppression in the entire ventral visual pathway, and underlying this suppression a dampening of the sensory representation in object-selective visual cortex, but not in primary visual cortex. Taken together, our results provide novel evidence in support of theories conceptualizing perception as an active inference process, which selectively dampens cortical representations of predictable objects. This dampening may support our ability to automatically filter out irrelevant, predictable objects.

scholarly journals Sensitivity to timing and order in human visual cortex

2015 ◽  
Vol 113 (5) ◽  
pp. 1656-1669 ◽  
Author(s):  
Jedediah M. Singer ◽  
Joseph R. Madsen ◽  
William S. Anderson ◽  
Gabriel Kreiman
Keyword(s):  
Visual Cortex ◽  
Visual Recognition ◽  
Visual Stimulation ◽  
Stimulus Presentation ◽  
Neural Representation ◽  
Visual Signals ◽  
Rapid Progression ◽  
Visual Responses ◽  
Visual Stream ◽  
Ventral Visual Stream

Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information must progress from stage to stage very quickly. This rapid progression of information suggests that fine temporal details of the neural response may be important to the brain's encoding of visual signals. We investigated how changes in the relative timing of incoming visual stimulation affect the representation of object information by recording intracranial field potentials along the human ventral visual stream while subjects recognized objects whose parts were presented with varying asynchrony. Visual responses along the ventral stream were sensitive to timing differences as small as 17 ms between parts. In particular, there was a strong dependency on the temporal order of stimulus presentation, even at short asynchronies. From these observations we infer that the neural representation of complex information in visual cortex can be modulated by rapid dynamics on scales of tens of milliseconds.

scholarly journals Hierarchical stimulus processing in rodent primary and lateral visual cortex as assessed through neuronal selectivity and repetition suppression

2018 ◽  
Vol 120 (3) ◽  
pp. 926-941 ◽  
Author(s):  
Dzmitry A. Kaliukhovich ◽  
Hans Op de Beeck
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Neuronal Response ◽  
Brain Area ◽  
Visual Stream ◽  
Hierarchical Processing ◽  
Repetition Suppression ◽  
Ventral Visual Stream ◽  
Long Evans

Similar to primates, visual cortex in rodents appears to be organized in two distinct hierarchical streams. However, there is still little known about how visual information is processed along those streams in rodents. In this study, we examined how repetition suppression and position and clutter tolerance of the neuronal representations evolve along the putative ventral visual stream in rats. To address this question, we recorded multiunit spiking activity in primary visual cortex (V1) and the more downstream visual laterointermediate (LI) area of head-restrained Long-Evans rats. We employed a paradigm reminiscent of the continuous carry-over design used in human neuroimaging. In both areas, stimulus repetition attenuated the early phase of the neuronal response to the repeated stimulus, with this response suppression being greater in area LI. Furthermore, stimulus preferences were more similar across positions (position tolerance) in area LI than in V1, even though the absolute responses in both areas were very sensitive to changes in position. In contrast, the neuronal representations in both areas were equally good at tolerating the presence of limited visual clutter, as modeled by the presentation of a single flank stimulus. When probing tolerance of the neuronal representations with stimulus-specific adaptation, we detected no position tolerance in either examined brain area, whereas, on the contrary, we revealed clutter tolerance in both areas. Overall, our data demonstrate similarities and discrepancies in processing of visual information along the ventral visual stream of rodents and primates. Moreover, our results stress caution in using neuronal adaptation to probe tolerance of the neuronal representations. NEW & NOTEWORTHY Rodents are emerging as a popular animal model that complement primates for studying higher level visual functions. Similar to findings in primates, we demonstrate a greater repetition suppression and position tolerance of the neuronal representations in the downstream laterointermediate area of Long-Evans rats compared with primary visual cortex. However, we report no difference in the degree of clutter tolerance between the areas. These findings provide additional evidence for hierarchical processing of visual stimuli in rodents.

scholarly journals Action-specific feature processing in the human visual cortex

2018 ◽  
Author(s):  
Simona Monaco ◽  
Ying Chen ◽  
Nicholas Menghi ◽  
J Douglas Crawford
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Temporal Cortex ◽  
Action Planning ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Cortical Processing ◽  
Visual Stream ◽  
Dorsal Visual Stream

AbstractSensorimotor integration involves feedforward and reentrant processing of sensory input. Grasp-related motor activity precedes and is thought to influence visual object processing. Yet, while the importance of reentrant feedback is well established in perception, the top-down modulations for action and the neural circuits involved in this process have received less attention. Do action-specific intentions influence the processing of visual information in the human cortex? Using a cue-separation fMRI paradigm, we found that action-specific instruction (manual alignment vs. grasp) influences the cortical processing of object orientation several seconds after the object had been viewed. This influence occurred as early as in the primary visual cortex and extended to ventral and dorsal visual stream areas. Importantly, this modulation was unrelated to non-specific action planning. Further, the primary visual cortex showed stronger functional connectivity with frontal-parietal areas and the inferior temporal cortex during the delay following orientation processing for align than grasping movements, strengthening the idea of reentrant feedback from dorsal visual stream areas involved in action. To our knowledge, this is the first demonstration that intended manual actions have such an early, pervasive, and differential influence on the cortical processing of vision.

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