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 Fine-scale computations for adaptive processing in the human brain

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Elisa Zamboni ◽  
Valentin G Kemper ◽  
Nuno Reis Goncalves ◽  
Ke Jia ◽  
Vasilis M Karlaftis ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Brain Plasticity ◽  
Sensory Information ◽  
Adaptive Processing ◽  
Fine Scale ◽  
Brain Responses ◽  
Efficient Information ◽  
High Field Imaging ◽  
Higher Visual Areas

Adapting 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 capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

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

2020 ◽  
Author(s):  
Elisa Zamboni ◽  
Valentin G Kemper ◽  
Nuno Reis Goncalves ◽  
Ke Jia ◽  
Vasilis M Karlaftis ◽  
...  
Keyword(s):  
Human Brain ◽  
Author Response ◽  
Adaptive Processing ◽  
Fine Scale

scholarly journals Distance estimation from monocular cues in an ethological visuomotor task

2021 ◽  
Author(s):  
Philip R L Parker ◽  
Eliott T T Abe ◽  
Natalie T Beatie ◽  
Emmalyn S P Leonard ◽  
Dylan M Martins ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Stereo Vision ◽  
Visual Processing ◽  
Motion Parallax ◽  
Sensory Information ◽  
Distance Estimation ◽  
Motor Output ◽  
Head Movements ◽  
Visuomotor Task ◽  
Head Fixation

In natural contexts, sensory processing and motor output are closely coupled, which is reflected in the fact that many brain areas contain both sensory and movement signals. However, standard reductionist paradigms decouple sensory decisions from their natural motor consequences, and head-fixation prevents the natural sensory consequences of self-motion. In particular, movement through the environment provides a number of depth cues beyond stereo vision that are poorly understood. To study the integration of visual processing and motor output in a naturalistic task, we investigated distance estimation in freely moving mice. We found that mice use vision to accurately jump across a variable gap, thus directly coupling a visual computation to its corresponding ethological motor output. Monocular eyelid suture did not affect performance, thus mice can use cues that do not depend on binocular disparity and stereo vision. Under monocular conditions, mice performed more vertical head movements, consistent with the use of motion parallax cues, and optogenetic suppression of primary visual cortex impaired task performance. Together, these results show that mice can use monocular cues, relying on visual cortex, to accurately judge distance. Furthermore, this behavioral paradigm provides a foundation for studying how neural circuits convert sensory information into ethological motor output.

Temporal Analysis of the Flow From V1 to the Extrastriate Cortex in Humans

2006 ◽  
Vol 96 (2) ◽  
pp. 775-784 ◽  
Author(s):  
Koji Inui ◽  
Ryusuke Kakigi
Keyword(s):  
Visual Cortex ◽  
Visual Processing ◽  
Early Stage ◽  
Sensory Information ◽  
Temporal Analysis ◽  
Cortical Activity ◽  
Extrastriate Cortex ◽  
Cortical Processing ◽  
Occipital Area ◽  
Biphasic Waveform

We previously examined the cortical processing in response to somatosensory, auditory and noxious stimuli, using magnetoencephalography in humans. Here, we performed a similar analysis of the processing in the human visual cortex for comparative purposes. After flash stimuli applied to the right eye, activations were found in eight cortical areas: the left medial occipital area around the calcarine fissure (primary visual cortex, V1), the left dorsomedial area around the parietooccipital sulcus (DM), the ventral (MOv) and dorsal (MOd) parts of the middle occipital area of bilateral hemispheres, the left temporo-occipito-parietal cortex corresponding to human MT/V5 (hMT), and the ventral surface of the medial occipital area (VO) of the bilateral hemispheres. The mean onset latencies of each cortical activity were (in ms): 27.5 (V1), 31.8 (DM), 32.8 (left MOv), 32.2 (right MOv), 33.4 (left MOd), 32.3 (right MOv), 37.8 (hMT), 46.9 (left VO), and 46.4 (right VO). Therefore the cortico-cortical connection time of visual processing at the early stage was 4–6 ms, which is very similar to the time delay between sequential activations in somatosensory and auditory processing. In addition, the activities in V1, MOd, DM, and hMT showed a similar biphasic waveform with a reversal of polarity after 10 ms, which is a common activation profile of the cortical activity for somatosensory, auditory, and pain-evoked responses. These results suggest similar mechanisms of the serial cortico-cortical processing of sensory information among all sensory areas of the cortex.

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.

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 Identifying task-relevant spectral signatures of perceptual categorization in the human cortex

2018 ◽  
Author(s):  
Ilya Kuzovkin ◽  
Juan R. Vidal ◽  
Marcela Perrone-Bertlotti ◽  
Philippe Kahane ◽  
Sylvain Rheims ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Sensory Information ◽  
Classification Model ◽  
Artificial System ◽  
Local Networks ◽  
Random Forest Classification ◽  
Spectral Signatures ◽  
Forest Classification ◽  
Sensory Cortices

Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks' selectivity for categorical information processing is still unknown. By mimicking the decoding of the sensory information with machine learning we can obtain accurate artificial decoding models. Having the artificial system functionally on par with the biological one we can analyze the mechanics of the artificial system to gain insights into the inner workings of its biological counterpart. In this work we train a Random Forest classification model to decode eight perceptual categories from visual stimuli given a broad spectrum of human intracranial signals 4-150 Hz obtained during a visual perception task, and analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low 4-50 Hz and high 50-150 Hz frequency bands. We demonstrate that the locations and patterns of activity that are identified by the algorithm not only coincide with the known spectro-spatial signatures, but extend our knowledge by uncovering additional spectral signatures describing neural mechanisms of visual category perception in human brain.

Language processing is not a race against time

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Language Processing ◽  
Cognitive Functions ◽  
Memory Systems ◽  
Language System ◽  
Moderating Factors

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.

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