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Author(s):  
Sunyoung Park ◽  
John T. Serences

Top-down spatial attention enhances cortical representations of behaviorally relevant visual information and increases the precision of perceptual reports. However, little is known about the relative precision of top-down attentional modulations in different visual areas, especially compared to the highly precise stimulus-driven responses that are observed in early visual cortex. For example, the precision of attentional modulations in early visual areas may be limited by the relatively coarse spatial selectivity and the anatomical connectivity of the areas in prefrontal cortex that generate and relay the top-down signals. Here, we used fMRI and human participants to assess the precision of bottom-up spatial representations evoked by high contrast stimuli across the visual hierarchy. Then, we examined the relative precision of top-down attentional modulations in the absence of spatially-specific bottom-up drive. While V1 showed the largest relative difference between the precision of top-down attentional modulations and the precision of bottom-up modulations, mid-level areas such as V4 showed relatively smaller differences between the precision of top-down and bottom-up modulations. Overall, this interaction between visual areas (e.g. V1 vs V4) and the relative precision of top-down and bottom-up modulations suggests that the precision of top-down attentional modulations is limited by the representational fidelity of areas that generate and relay top-down feedback signals.


2022 ◽  
Author(s):  
Jun Kai Ho ◽  
Tomoyasu Horikawa ◽  
Kei Majima ◽  
Yukiyasu Kamitani

The sensory cortex is characterized by general organizational principles such as topography and hierarchy. However, measured brain activity given identical input exhibits substantially different patterns across individuals. While anatomical and functional alignment methods have been proposed in functional magnetic resonance imaging (fMRI) studies, it remains unclear whether and how hierarchical and fine-grained representations can be converted between individuals while preserving the encoded perceptual contents. In this study, we evaluated machine learning models called neural code converters that predict one's brain activity pattern (target) from another's (source) given the same stimulus by the decoding of hierarchical visual features and the reconstruction of perceived images. The training data for converters consisted of fMRI data obtained with identical sets of natural images presented to pairs of individuals. Converters were trained using the whole visual cortical voxels from V1 through the ventral object areas, without explicit labels of visual areas. We decoded the converted brain activity patterns into hierarchical visual features of a deep neural network (DNN) using decoders pre-trained on the target brain and then reconstructed images via the decoded features. Without explicit information about visual cortical hierarchy, the converters automatically learned the correspondence between the visual areas of the same levels. DNN feature decoding at each layer showed higher decoding accuracies from corresponding levels of visual areas, indicating that hierarchical representations were preserved after conversion. The viewed images were faithfully reconstructed with recognizable silhouettes of objects even with relatively small amounts of data for converter training. The conversion also allows pooling data across multiple individuals, leading to stably high reconstruction accuracy compared to those converted between individuals. These results demonstrate that the conversion learns hierarchical correspondence and preserves the fine-grained representations of visual features, enabling visual image reconstruction using decoders trained on other individuals.


Author(s):  
Lucija Rapan ◽  
Meiqi Niu ◽  
Ling Zhao ◽  
Thomas Funck ◽  
Katrin Amunts ◽  
...  

AbstractExisting cytoarchitectonic maps of the human and macaque posterior occipital cortex differ in the number of areas they display, thus hampering identification of homolog structures. We applied quantitative in vitro receptor autoradiography to characterize the receptor architecture of the primary visual and early extrastriate cortex in macaque and human brains, using previously published cytoarchitectonic criteria as starting point of our analysis. We identified 8 receptor architectonically distinct areas in the macaque brain (mV1d, mV1v, mV2d, mV2v, mV3d, mV3v, mV3A, mV4v), and their respective counterpart areas in the human brain (hV1d, hV1v, hV2d, hV2v, hV3d, hV3v, hV3A, hV4v). Mean densities of 14 neurotransmitter receptors were quantified in each area, and ensuing receptor fingerprints used for multivariate analyses. The 1st principal component segregated macaque and human early visual areas differ. However, the 2nd principal component showed that within each species, area-specific differences in receptor fingerprints were associated with the hierarchical processing level of each area. Subdivisions of V2 and V3 were found to cluster together in both species and were segregated from subdivisions of V1 and from V4v. Thus, comparative studies like this provide valuable architectonic insights into how differences in underlying microstructure impact evolutionary changes in functional processing of the primate brain and, at the same time, provide strong arguments for use of macaque monkey brain as a suitable animal model for translational studies.


2021 ◽  
Author(s):  
Yiyi Yu ◽  
Jeffrey N. Stirman ◽  
Christopher R. Dorsett ◽  
Spencer L. Smith

Mice have a constellation of higher visual areas, but their functional specializations are unclear. Here, we used a data-driven approach to examine neuronal representations of complex visual stimuli across mouse higher visual areas, measured using large field-of-view two-photon calcium imaging. Using specialized stimuli, we found higher fidelity representations of texture in area LM, compared to area AL. Complementarily, we found higher fidelity representations of motion in area AL, compared to area LM. We also observed this segregation of information in response to naturalistic videos. Finally, we explored how popular models of visual cortical neurons could produce the segregated representations of texture and motion we observed. These selective representations could aid in behaviors such as visually guided navigation.


2021 ◽  
Vol 15 ◽  
Author(s):  
Sergio Delle Monache ◽  
Iole Indovina ◽  
Myrka Zago ◽  
Elena Daprati ◽  
Francesco Lacquaniti ◽  
...  

Gravity is a physical constraint all terrestrial species have adapted to through evolution. Indeed, gravity effects are taken into account in many forms of interaction with the environment, from the seemingly simple task of maintaining balance to the complex motor skills performed by athletes and dancers. Graviceptors, primarily located in the vestibular otolith organs, feed the Central Nervous System with information related to the gravity acceleration vector. This information is integrated with signals from semicircular canals, vision, and proprioception in an ensemble of interconnected brain areas, including the vestibular nuclei, cerebellum, thalamus, insula, retroinsula, parietal operculum, and temporo-parietal junction, in the so-called vestibular network. Classical views consider this stage of multisensory integration as instrumental to sort out conflicting and/or ambiguous information from the incoming sensory signals. However, there is compelling evidence that it also contributes to an internal representation of gravity effects based on prior experience with the environment. This a priori knowledge could be engaged by various types of information, including sensory signals like the visual ones, which lack a direct correspondence with physical gravity. Indeed, the retinal accelerations elicited by gravitational motion in a visual scene are not invariant, but scale with viewing distance. Moreover, the “visual” gravity vector may not be aligned with physical gravity, as when we watch a scene on a tilted monitor or in weightlessness. This review will discuss experimental evidence from behavioral, neuroimaging (connectomics, fMRI, TMS), and patients’ studies, supporting the idea that the internal model estimating the effects of gravity on visual objects is constructed by transforming the vestibular estimates of physical gravity, which are computed in the brainstem and cerebellum, into internalized estimates of virtual gravity, stored in the vestibular cortex. The integration of the internal model of gravity with visual and non-visual signals would take place at multiple levels in the cortex and might involve recurrent connections between early visual areas engaged in the analysis of spatio-temporal features of the visual stimuli and higher visual areas in temporo-parietal-insular regions.


2021 ◽  
Vol 15 ◽  
Author(s):  
Trung Quang Pham ◽  
Shota Nishiyama ◽  
Norihiro Sadato ◽  
Junichi Chikazoe

Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region decoding technique, we examined whether the information represented in the visual areas can be explained by those represented in the other visual areas. We first predicted the brain activity patterns of an area on the visual pathway from the others, then subtracted the predicted patterns from their originals. Subsequently, the visual features were derived from these residuals. During the visual perception task, the elimination of the top-down signals enhanced the simple visual features represented in the early visual cortices. By contrast, the elimination of the bottom-up signals enhanced the complex visual features represented in the higher visual cortices. The directions of such modulation effects varied across visual perception/imagery tasks, indicating that the information flow across the visual cortices is dynamically altered, reflecting the contents of visual processing. These results demonstrated that the distillation approach is a useful tool to estimate the hidden content of information conveyed across brain regions.


2021 ◽  
Vol 15 ◽  
Author(s):  
Megan Roussy ◽  
Diego Mendoza-Halliday ◽  
Julio C. Martinez-Trujillo

Visual perception occurs when a set of physical signals emanating from the environment enter the visual system and the brain interprets such signals as a percept. Visual working memory occurs when the brain produces and maintains a mental representation of a percept while the physical signals corresponding to that percept are not available. Early studies in humans and non-human primates demonstrated that lesions of the prefrontal cortex impair performance during visual working memory tasks but not during perceptual tasks. These studies attributed a fundamental role in working memory and a lesser role in visual perception to the prefrontal cortex. Indeed, single cell recording studies have found that neurons in the lateral prefrontal cortex of macaques encode working memory representations via persistent firing, validating the results of lesion studies. However, other studies have reported that neurons in some areas of the parietal and temporal lobe—classically associated with visual perception—similarly encode working memory representations via persistent firing. This prompted a line of enquiry about the role of the prefrontal and other associative cortices in working memory and perception. Here, we review evidence from single neuron studies in macaque monkeys examining working memory representations across different areas of the visual hierarchy and link them to studies examining the role of the same areas in visual perception. We conclude that neurons in early visual areas of both ventral (V1-V2-V4) and dorsal (V1-V3-MT) visual pathways of macaques mainly encode perceptual signals. On the other hand, areas downstream from V4 and MT contain subpopulations of neurons that encode both perceptual and/or working memory signals. Differences in cortical architecture (neuronal types, layer composition, and synaptic density and distribution) may be linked to the differential encoding of perceptual and working memory signals between early visual areas and higher association areas.


Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3162
Author(s):  
Maël Duménieu ◽  
Béatrice Marquèze-Pouey ◽  
Michaël Russier ◽  
Dominique Debanne

Visual plasticity is classically considered to occur essentially in the primary and secondary cortical areas. Subcortical visual areas such as the dorsal lateral geniculate nucleus (dLGN) or the superior colliculus (SC) have long been held as basic structures responsible for a stable and defined function. In this model, the dLGN was considered as a relay of visual information travelling from the retina to cortical areas and the SC as a sensory integrator orienting body movements towards visual targets. However, recent findings suggest that both dLGN and SC neurons express functional plasticity, adding unexplored layers of complexity to their previously attributed functions. The existence of neuronal plasticity at the level of visual subcortical areas redefines our approach of the visual system. The aim of this paper is therefore to review the cellular and molecular mechanisms for activity-dependent plasticity of both synaptic transmission and cellular properties in subcortical visual areas.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ilka Boehm ◽  
Holger Mohr ◽  
Joseph A. King ◽  
Julius Steding ◽  
Daniel Geisler ◽  
...  

AbstractAnorexia nervosa (AN) has been associated with altered reward processing. We recently reported greater neural response in secondary visual areas when processing visual food stimuli in acutely underweight AN patients (acAN). In order to examine whether the observed alterations are indicative of acute undernutrition or a potential trait marker of AN, we set out to assess neural responses in acAN and in individuals weight-recovered from AN (recAN). FMRI data were collected from a total of 126 female volunteers, 35 acAN, 33 recAN, and 58 age-matched healthy controls (HC) while they viewed streams of food, social and neutral stimuli. A standard general linear model (GLM) was used to interrogate neural responses to the different stimuli in recAN vs. age-matched HC. Moreover, within-subject multivoxel pattern analyses (MVPA) in the two matched samples (acAN/HC and recAN/HC) were used to estimate neural representation of food vs. neutral, and social vs. neutral stimuli. A multiple regression analysis was conducted to test associations between the accuracy of the neural representation and treatment outcome. The GLM revealed no group differences between recAN and HC. The MVPAs showed greater classification accuracy of food stimuli in the posterior fusiform gyrus in acAN but not recAN. Classification accuracy was associated with better treatment outcome. Our findings suggest that the neural representation of food stimuli is altered in secondary visual areas in acAN and normalizes with weight recovery. Possibly this altered representation reflects attentional engagement motivating food intake, which may promote the recovery process.


2021 ◽  
Author(s):  
Shenqin Yao ◽  
Quanxin Wang ◽  
Karla Hirokawa ◽  
Benjamin Ouellette ◽  
Ruweida Ahmed ◽  
...  

Abstract Identification of the structural connections between neurons is a prerequisite to understanding brain function. We developed a pipeline to systematically map brain-wide monosynaptic inputs to specific neuronal populations using Cre-driver mouse lines and the recombinant rabies tracing system. We first improved the rabies virus tracing strategy to accurately identify starter cells and to efficiently quantify presynaptic inputs. We then mapped brain-wide presynaptic inputs to different excitatory and inhibitory neuron subclasses in the primary visual cortex and seven higher visual areas. Our results reveal quantitative target-, layer- and cell-class-specific differences in the retrograde connectomes, despite similar global input patterns to different neuronal populations in the same anatomical area. The retrograde connectivity we define is consistent with the presence of the ventral and dorsal visual information processing streams and reveals further subnetworks within the dorsal stream. The hierarchical organization of the entire visual cortex can be derived from intracortical feedforward and feedback pathways mediated by upper- and lower-layer input neurons, respectively. This study expands our knowledge of the brain-wide inputs regulating visual areas and demonstrates that our improved rabies virus tracing strategy can be used to scale up the effort in dissecting connectivity of genetically defined cell populations in the whole mouse brain.


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