scholarly journals Human visual cortex is organized along two genetically opposed hierarchical gradients with unique developmental and evolutionary origins

2018 ◽  
Author(s):  
Jesse Gomez ◽  
Zonglei Zhen ◽  
Kevin Weiner
Keyword(s):  
Gene Expression ◽  
Visual Cortex ◽  
Human Brain ◽  
Visual Processing ◽  
Tissue Characterization ◽  
Cortical Folding ◽  
Processing Stage ◽  
Human Visual Cortex ◽  
Functional Features ◽  
Expression Gradients

Human visual cortex is organized with striking consistency across individuals. While recent findings demonstrate an unexpected coupling between functional and cytoarchitectonic regions relative to the folding of human visual cortex, a unifying principle linking these anatomical and functional features of cortex remains elusive. To fill this gap in knowledge, we combined independent and ground truth measurements of human cytoarchitectonic regions and genetic tissue characterization within the visual processing hierarchy. Using a data-driven approach, we examined if differential gene expression among cortical areas could explain the organization of the visual processing hierarchy into early, middle, and late processing stages. This approach revealed that the visual processing hierarchy is explained by two opposing gene expression gradients: one that contains a series of genes with expression magnitudes that ascend from the first processing stage (e.g. area hOc1, or V1) to the last processing stage (e.g. area FG4) and another that contains a separate series of genes that show a descending gradient. In the living human brain, each of these gradients correlates strongly with anatomical variations along the visual hierarchy such as the thickness or myelination of cortex. We further reveal that these genetic gradients emerge along unique trajectories in human development: the ascending gradient is present at 10- 12 gestational weeks, while the descendent gradient emerges later (19-24 gestational weeks). Interestingly, it is not until early childhood (before 5 years of age) that the two expression gradients achieve their adult-like mean expression values. Finally, additional analyses in non-human primates (NHP) reveal the surprising finding that only the ascending, but not the descending, expression gradient is evolutionarily conserved. These findings create one of the first models bridging macroscopic features of human cytoarchitectonic areas in visual cortex with microscopic features of cellular organization and genetic expression, revealing that the hierarchy of human visual cortex, its cortical folding, and the cytoarchitecture underlying its computations, can be described by a sparse subset (~200) of genes, roughly one-third of which are not shared with NHP. These findings help pinpoint the genes contributing to both healthy cortical development and the cortical biology distinguishing humans from other primates, establishing essential groundwork for understanding future work linking genetic mutations with the function and development of the human brain.

scholarly journals A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Justin L. Balsor ◽  
Keon Arbabi ◽  
Desmond Singh ◽  
Rachel Kwan ◽  
Jonathan Zaslavsky ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Human Brain ◽  
Small Sample ◽  
Postmortem Brain ◽  
High Dimensional ◽  
Clustering Methods ◽  
Sample Sizes ◽  
Human Visual Cortex ◽  
Age Related ◽  
Postmortem Brain Tissue

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.

scholarly journals Fine-scale computations for adaptive processing in the human brain

2020 ◽  
Author(s):  
E Zamboni ◽  
VG Kemper ◽  
NR Goncalves ◽  
K Jia ◽  
VM Karlaftis ◽  
...  
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Human Brain ◽  
Visual Processing ◽  
Brain Plasticity ◽  
Sensory Information ◽  
Adaptive Processing ◽  
Fine Scale ◽  
Efficient Information ◽  
High Field Imaging

AbstractAdapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalize on the sub-millimetre resolution afforded by ultra-high field imaging to examine BOLD-fMRI signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive visual processing. We demonstrate suppressive recurrent processing within visual cortex, as indicated by stronger BOLD decrease in superficial than middle and deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show dissociable connectivity mechanisms for adaptive processing: enhanced feedforward connectivity within visual cortex, while feedback occipito-parietal connectivity, reflecting top-down influences on visual processing. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

scholarly journals Encoding model of temporal processing in human visual cortex

2017 ◽  
Vol 114 (51) ◽  
pp. E11047-E11056 ◽  
Author(s):  
Anthony Stigliani ◽  
Brianna Jeska ◽  
Kalanit Grill-Spector
Keyword(s):  
Visual Cortex ◽  
Temporal Processing ◽  
Visual Processing ◽  
Ventral Stream ◽  
Visual Input ◽  
Time Varying ◽  
Transient Responses ◽  
Human Visual Cortex ◽  
Cortical Responses ◽  
Prevailing View

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.

scholarly journals Feature-coding transitions to conjunction-coding with progression through human visual cortex

2017 ◽  
Vol 118 (6) ◽  
pp. 3194-3214 ◽  
Author(s):  
Rosemary A. Cowell ◽  
Krystal R. Leger ◽  
John T. Serences
Keyword(s):  
Visual Cortex ◽  
Visual Processing ◽  
Temporal Cortex ◽  
Complex Stimulus ◽  
Imaging Data ◽  
Neuronal Responses ◽  
Human Visual Cortex ◽  
Early Visual Cortex ◽  
Parietal Cortices ◽  
Object Level

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.

scholarly journals The Normalization Model Captures the Effects of Object-based Attention in the Human Visual Cortex

2021 ◽  
Author(s):  
Narges Doostani ◽  
Gholam-Ali Hossein-Zadeh ◽  
Maryam Vaziri-Pashkam
Keyword(s):  
Visual Cortex ◽  
Human Brain ◽  
Human Visual Cortex ◽  
Visual Hierarchy ◽  
Primate Brain ◽  
Object Based

Here, we report that normalization model can capture the effects of object-based attention across the visual hierarchy in the human brain. We used superimposed pairs of objects and asked participants to attend to different targets. Modeling voxel responses, we demonstrated that the normalization model outperforms other models in predicting voxel responses in the presence of attention. Our results propose normalization as a canonical computation operating in the primate brain.

scholarly journals Modulation of visual processing by attention and emotion: windows on causal interactions between human brain regions

2007 ◽  
Vol 362 (1481) ◽  
pp. 837-855 ◽  
Author(s):  
Patrik Vuilleumier ◽  
Jon Driver
Keyword(s):  
Visual Cortex ◽  
Human Brain ◽  
Visual Processing ◽  
Brain Structures ◽  
Brain Regions ◽  
Normal Brain ◽  
Focal Lesions ◽  
Emotional Modulation ◽  
Current Task ◽  
Visual Properties

Visual processing is not determined solely by retinal inputs. Attentional modulation can arise when the internal attentional state (current task) of the observer alters visual processing of the same stimuli. This can influence visual cortex, boosting neural responses to an attended stimulus. Emotional modulation can also arise, when affective properties (emotional significance) of stimuli, rather than their strictly visual properties, influence processing. This too can boost responses in visual cortex, as for fear-associated stimuli. Both attentional and emotional modulation of visual processing may reflect distant influences upon visual cortex, exerted by brain structures outside the visual system per se . Hence, these modulations may provide windows onto causal interactions between distant but interconnected brain regions. We review recent evidence, noting both similarities and differences between attentional and emotional modulation. Both can affect visual cortex, but can reflect influences from different regions, such as fronto-parietal circuits versus the amygdala. Recent work on this has developed new approaches for studying causal influences between human brain regions that may be useful in other cognitive domains. The new methods include application of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) measures in brain-damaged patients to study distant functional impacts of their focal lesions, and use of transcranial magnetic stimulation concurrently with fMRI or EEG in the normal brain. Cognitive neuroscience is now moving beyond considering the putative functions of particular brain regions, as if each operated in isolation, to consider, instead, how distinct brain regions (such as visual cortex, parietal or frontal regions, or amygdala) may mutually influence each other in a causal manner.

Sign in / Sign up

Export Citation Format

Share Document