scholarly journals An encoding model of temporal processing in human visual cortex

2017 ◽  
Author(s):  
Anthony Stigliani ◽  
Brianna Jeska ◽  
Kalanit Grill-Spector

ABSTRACTHow is temporal information processed in human visual cortex? There is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli, then implemented a novel 2 temporal-channel encoding model to estimate the contributions of each channel. The model predicts cortical responses to time-varying stimuli from milliseconds to seconds and reveals that (i) lateral occipito-temporal regions and peripheral early visual cortex are dominated by transient responses, and (ii) ventral occipito-temporal regions and central early visual cortex are not only driven by both channels, but that transient responses exceed the sustained. These findings resolve an outstanding debate and elucidate temporal processing in human visual cortex. Importantly, this approach has vast implications because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain.

2017 ◽  
Vol 114 (51) ◽  
pp. E11047-E11056 ◽  
Author(s):  
Anthony Stigliani ◽  
Brianna Jeska ◽  
Kalanit Grill-Spector

How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain.


2021 ◽  
pp. 1-12
Author(s):  
Joonkoo Park ◽  
Sonia Godbole ◽  
Marty G. Woldorff ◽  
Elizabeth M. Brannon

Abstract Whether and how the brain encodes discrete numerical magnitude differently from continuous nonnumerical magnitude is hotly debated. In a previous set of studies, we orthogonally varied numerical (numerosity) and nonnumerical (size and spacing) dimensions of dot arrays and demonstrated a strong modulation of early visual evoked potentials (VEPs) by numerosity and not by nonnumerical dimensions. Although very little is known about the brain's response to systematic changes in continuous dimensions of a dot array, some authors intuit that the visual processing stream must be more sensitive to continuous magnitude information than to numerosity. To address this possibility, we measured VEPs of participants viewing dot arrays that changed exclusively in one nonnumerical magnitude dimension at a time (size or spacing) while holding numerosity constant and compared this to a condition where numerosity was changed while holding size and spacing constant. We found reliable but small neural sensitivity to exclusive changes in size and spacing; however, changing numerosity elicited a much more robust modulation of the VEPs. Together with previous work, these findings suggest that sensitivity to magnitude dimensions in early visual cortex is context dependent: The brain is moderately sensitive to changes in size and spacing when numerosity is held constant, but sensitivity to these continuous variables diminishes to a negligible level when numerosity is allowed to vary at the same time. Neurophysiological explanations for the encoding and context dependency of numerical and nonnumerical magnitudes are proposed within the framework of neuronal normalization.


2017 ◽  
Vol 118 (6) ◽  
pp. 3194-3214 ◽  
Author(s):  
Rosemary A. Cowell ◽  
Krystal R. Leger ◽  
John T. Serences

Identifying an object and distinguishing it from similar items depends upon the ability to perceive its component parts as conjoined into a cohesive whole, but the brain mechanisms underlying this ability remain elusive. The ventral visual processing pathway in primates is organized hierarchically: Neuronal responses in early stages are sensitive to the manipulation of simple visual features, whereas neuronal responses in subsequent stages are tuned to increasingly complex stimulus attributes. It is widely assumed that feature-coding dominates in early visual cortex whereas later visual regions employ conjunction-coding in which object representations are different from the sum of their simple feature parts. However, no study in humans has demonstrated that putative object-level codes in higher visual cortex cannot be accounted for by feature-coding and that putative feature codes in regions prior to ventral temporal cortex are not equally well characterized as object-level codes. Thus the existence of a transition from feature- to conjunction-coding in human visual cortex remains unconfirmed, and if a transition does occur its location remains unknown. By employing multivariate analysis of functional imaging data, we measure both feature-coding and conjunction-coding directly, using the same set of visual stimuli, and pit them against each other to reveal the relative dominance of one vs. the other throughout cortex. Our results reveal a transition from feature-coding in early visual cortex to conjunction-coding in both inferior temporal and posterior parietal cortices. This novel method enables the use of experimentally controlled stimulus features to investigate population-level feature and conjunction codes throughout human cortex. NEW & NOTEWORTHY We use a novel analysis of neuroimaging data to assess representations throughout visual cortex, revealing a transition from feature-coding to conjunction-coding along both ventral and dorsal pathways. Occipital cortex contains more information about spatial frequency and contour than about conjunctions of those features, whereas inferotemporal and parietal cortices contain conjunction coding sites in which there is more information about the whole stimulus than its component parts.


2015 ◽  
Vol 113 (9) ◽  
pp. 3159-3171 ◽  
Author(s):  
Caroline D. B. Luft ◽  
Alan Meeson ◽  
Andrew E. Welchman ◽  
Zoe Kourtzi

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex.


2021 ◽  
Vol 15 ◽  
Author(s):  
Yun Lin ◽  
Xi Zhou ◽  
Yuji Naya ◽  
Justin L. Gardner ◽  
Pei Sun

The linearity of BOLD responses is a fundamental presumption in most analysis procedures for BOLD fMRI studies. Previous studies have examined the linearity of BOLD signal increments, but less is known about the linearity of BOLD signal decrements. The present study assessed the linearity of both BOLD signal increments and decrements in the human primary visual cortex using a contrast adaptation paradigm. Results showed that both BOLD signal increments and decrements kept linearity to long stimuli (e.g., 3 s, 6 s), yet, deviated from linearity to transient stimuli (e.g., 1 s). Furthermore, a voxel-wise analysis showed that the deviation patterns were different for BOLD signal increments and decrements: while the BOLD signal increments demonstrated a consistent overestimation pattern, the patterns for BOLD signal decrements varied from overestimation to underestimation. Our results suggested that corrections to deviations from linearity of transient responses should consider the different effects of BOLD signal increments and decrements.


2018 ◽  
Author(s):  
Andreea Lazar ◽  
Chris Lewis ◽  
Pascal Fries ◽  
Wolf Singer ◽  
Danko Nikolić

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.


Cortex ◽  
2014 ◽  
Vol 59 ◽  
pp. 1-11 ◽  
Author(s):  
Christianne Jacobs ◽  
Tom A. de Graaf ◽  
Alexander T. Sack

2022 ◽  
Author(s):  
Andrea Kóbor ◽  
Karolina Janacsek ◽  
Petra Hermann ◽  
Zsofia Zavecz ◽  
Vera Varga ◽  
...  

Previous research recognized that humans could extract statistical regularities of the environment to automatically predict upcoming events. However, it has remained unexplored how the brain encodes the distribution of statistical regularities if it continuously changes. To investigate this question, we devised an fMRI paradigm where participants (N = 32) completed a visual four-choice reaction time (RT) task consisting of statistical regularities. Two types of blocks involving the same perceptual elements alternated with one another throughout the task: While the distribution of statistical regularities was predictable in one block type, it was unpredictable in the other. Participants were unaware of the presence of statistical regularities and of their changing distribution across the subsequent task blocks. Based on the RT results, although statistical regularities were processed similarly in both the predictable and unpredictable blocks, participants acquired less statistical knowledge in the unpredictable as compared with the predictable blocks. Whole-brain random-effects analyses showed increased activity in the early visual cortex and decreased activity in the precuneus for the predictable as compared with the unpredictable blocks. Therefore, the actual predictability of statistical regularities is likely to be represented already at the early stages of visual cortical processing. However, decreased precuneus activity suggests that these representations are imperfectly updated to track the multiple shifts in predictability throughout the task. The results also highlight that the processing of statistical regularities in a changing environment could be habitual.


2010 ◽  
Vol 22 (11) ◽  
pp. 2417-2426 ◽  
Author(s):  
Stephanie A. McMains ◽  
Sabine Kastner

Multiple stimuli that are present simultaneously in the visual field compete for neural representation. At the same time, however, multiple stimuli in cluttered scenes also undergo perceptual organization according to certain rules originally defined by the Gestalt psychologists such as similarity or proximity, thereby segmenting scenes into candidate objects. How can these two seemingly orthogonal neural processes that occur early in the visual processing stream be reconciled? One possibility is that competition occurs among perceptual groups rather than at the level of elements within a group. We probed this idea using fMRI by assessing competitive interactions across visual cortex in displays containing varying degrees of perceptual organization or perceptual grouping (Grp). In strong Grp displays, elements were arranged such that either an illusory figure or a group of collinear elements were present, whereas in weak Grp displays the same elements were arranged randomly. Competitive interactions among stimuli were overcome throughout early visual cortex and V4, when elements were grouped regardless of Grp type. Our findings suggest that context-dependent grouping mechanisms and competitive interactions are linked to provide a bottom–up bias toward candidate objects in cluttered scenes.


2018 ◽  
Author(s):  
Anthony Stigliani ◽  
Brianna Jeska ◽  
Kalanit Grill-Spector

ABSTRACTHow do high-level visual regions process the temporal aspects of our visual experience? While the temporal sensitivity of early visual cortex has been studied with fMRI in humans, temporal processing in high-level visual cortex is largely unknown. By modeling neural responses with millisecond precision in separate sustained and transient channels, and introducing a flexible encoding framework that captures differences in neural temporal integration time windows and response nonlinearities, we predict fMRI responses across visual cortex for stimuli ranging from 33 ms to 20 s. Using this innovative approach, we discovered that lateral category-selective regions respond to visual transients associated with stimulus onsets and offsets but not sustained visual information. Thus, lateral category-selective regions compute moment-tomoment visual transitions, but not stable features of the visual input. In contrast, ventral category-selective regions respond to both sustained and transient components of the visual input. Responses to sustained stimuli exhibit adaptation, whereas responses to transient stimuli are surprisingly larger for stimulus offsets than onsets. This large offset transient response may reflect a memory trace of the stimulus when it is no longer visible, whereas the onset transient response may reflect rapid processing of new items. Together, these findings reveal previously unconsidered, fundamental temporal mechanisms that distinguish visual streams in the human brain. Importantly, our results underscore the promise of modeling brain responses with millisecond precision to understand the underlying neural computations.AUTHOR SUMMARYHow does the brain encode the timing of our visual experience? Using functional magnetic resonance imaging (fMRI) and a temporal encoding model with millisecond resolution, we discovered that visual regions in the lateral and ventral processing streams fundamentally differ in their temporal processing of the visual input. Regions in lateral temporal cortex process visual transients associated with stimulus onsets and offsets but not the unchanging aspects of the visual input. That is, they compute moment-to-moment changes in the visual input. In contrast, regions in ventral temporal cortex process both stable and transient components, with the former exhibiting adaptation. Surprisingly, in these ventral regions responses to stimulus offsets were larger than onsets. We suggest that the former may reflect a memory trace of the stimulus, when it is no longer visible, and the latter may reflect rapid processing of new items at stimulus onset. Together, these findings (i) reveal a fundamental temporal mechanism that distinguishes visual streams and (ii) highlight both the importance and utility of modeling brain responses with millisecond precision to understand the temporal dynamics of neural computations in the human brain.


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