Why Does the Brain Have So Many Visual Areas?

1989 ◽  
Vol 1 (2) ◽  
pp. 121-135 ◽  
Author(s):  
Jon H. Kaas
Keyword(s):  
Species Differences ◽  
Visual Area ◽  
Common Mechanism ◽  
Functional Requirements ◽  
Specific Stimulus ◽  
Stimulus Attribute ◽  
Cortical Areas ◽  
Visual Areas ◽  
Stimulus Parameters ◽  
The Brain

Mammals vary in number of visual areas from a few to 20 or more as a result of new visual areas being added to the middle levels of processing hierarchies. Having more visual areas probably increases visual abilities, perhaps in part by allowing more stimulus parameters to be considered. Proposals that each visual area computes and thereby “detects” a specific stimulus attribute have so far dealt with attributes that most mammals can detect and thus do not relate to the issue of species differences in numbers of areas. The problem of forming and maintaining complex patterns of interconnections between many different sets of distinct processing models within an area may limit multiplying functions within a field. In addition, the adding of new visual areas is a way of avoiding constraints on modifying existing visual areas that are imposed by the ongoing functional requirements. Thus, increasing the number of visual or other cortical areas is an effective and apparently common mechanism for evolving new capacities.

scholarly journals Decision-related feedback in visual cortex lacks spatial selectivity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Katrina R. Quinn ◽  
Lenka Seillier ◽  
Daniel A. Butts ◽  
Hendrikje Nienborg
Keyword(s):  
Contextual Information ◽  
Relevant Information ◽  
Common Mechanism ◽  
Spatial Selectivity ◽  
Population Responses ◽  
Stimulus Choice ◽  
Visual Areas ◽  
Computational Work ◽  
Feature Based ◽  
The Brain

AbstractFeedback in the brain is thought to convey contextual information that underlies our flexibility to perform different tasks. Empirical and computational work on the visual system suggests this is achieved by targeting task-relevant neuronal subpopulations. We combine two tasks, each resulting in selective modulation by feedback, to test whether the feedback reflected the combination of both selectivities. We used visual feature-discrimination specified at one of two possible locations and uncoupled the decision formation from motor plans to report it, while recording in macaque mid-level visual areas. Here we show that although the behavior is spatially selective, using only task-relevant information, modulation by decision-related feedback is spatially unselective. Population responses reveal similar stimulus-choice alignments irrespective of stimulus relevance. The results suggest a common mechanism across tasks, independent of the spatial selectivity these tasks demand. This may reflect biological constraints and facilitate generalization across tasks. Our findings also support a previously hypothesized link between feature-based attention and decision-related activity.

Location, architecture, and retinotopy of the anteromedial lateral suprasylvian visual area (AMLS) of the ferret (Mustela putorius)

2008 ◽  
Vol 25 (1) ◽  
pp. 27-37 ◽  
Author(s):  
PAUL R. MANGER ◽  
GERHARD ENGLER ◽  
CHRISTIAN K.E. MOLL ◽  
ANDREAS K. ENGEL
Keyword(s):  
Visual Area ◽  
Domestic Cat ◽  
Lower Visual Field ◽  
Mustela Putorius ◽  
Cortical Areas ◽  
Architectural Features ◽  
Visual Areas ◽  
Retinotopic Organization ◽  
Visual Cortical ◽  
Cortical Visual Areas

The present paper describes the results of architectural and electrophysiological mapping observations of the medial bank of the suprasylvian sulcus of the ferret immediately caudal to somatosensory regions. The aim was to determine if the ferret possessed a homologous cortical area to the anteromedial lateral suprasylvian visual area (AMLS) of the domestic cat. We studied the architectural features and visuotopic organization of a region that we now consider to be a homologue to the cat AMLS. This area showed a distinct architecture and retinotopic organization. The retinotopic map was complex in nature with a bias towards representation of the lower visual field. These features indicate that the region described here as AMLS in the ferret is indeed a direct homologue of the previously described cat AMLS and forms part of a hierarchy of cortical areas processing motion in the ferret visual cortex. With the results of the present study and those of earlier studies a total of twelve cortical visual areas have been determined presently for the ferret, all of which appear to have direct homologues with visual cortical areas in the cat (which has a total of eighteen areas).

scholarly journals Altered Functional Connectivity of the Primary Visual Cortex in Subjects with Amblyopia

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Kun Ding ◽  
Yong Liu ◽  
Xiaohe Yan ◽  
Xiaoming Lin ◽  
Tianzi Jiang
Keyword(s):  
Functional Connectivity ◽  
Activity Patterns ◽  
Brain Regions ◽  
Visual Area ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Blurred Vision ◽  
Visual Areas ◽  
Connectivity Patterns ◽  
The Brain

Amblyopia, which usually occurs during early childhood and results in poor or blurred vision, is a disorder of the visual system that is characterized by a deficiency in an otherwise physically normal eye or by a deficiency that is out of proportion with the structural or functional abnormalities of the eye. Our previous study demonstrated alterations in the spontaneous activity patterns of some brain regions in individuals with anisometropic amblyopia compared to subjects with normal vision. To date, it remains unknown whether patients with amblyopia show characteristic alterations in the functional connectivity patterns in the visual areas of the brain, particularly the primary visual area. In the present study, we investigated the differences in the functional connectivity of the primary visual area between individuals with amblyopia and normal-sighted subjects using resting functional magnetic resonance imaging. Our findings demonstrated that the cerebellum and the inferior parietal lobule showed altered functional connectivity with the primary visual area in individuals with amblyopia, and this finding provides further evidence for the disruption of the dorsal visual pathway in amblyopic subjects.

scholarly journals Visual category-driven differences in memory

2021 ◽  
Author(s):  
Adam Steel ◽  
Edward Silson
Keyword(s):  
Visual Cortex ◽  
Human Memory ◽  
Memory Systems ◽  
Neural Mechanisms ◽  
Neural Responses ◽  
Cortical Areas ◽  
Visual Areas ◽  
High Level ◽  
Human Categorization ◽  
The Brain

Categorizing classes of stimuli in the real-world is thought to underlie features of general intelligence, including our ability to infer identities of new objects, environments, and people never encountered before. Our understanding of human categorization, and the neural mechanisms that underlie this ability, was initially described in the context of visual perception. It is now broadly accepted that a network of high-level visual areas on the ventral and lateral surfaces of the brain exhibit some level of ‘domain (or category)-selective’ activity: preferential neural responses to visual stimuli of one category more than another (e.g., larger responses to faces compared to scenes or manipulable objects). Inspired by this robust and intuitive organization, recent studies have begun investigating the extent to which human memory systems also exhibit a category-selective organization. Surprisingly, this work has revealed strong evidence for the existence of category-selective areas in swaths of cortex previously considered to be domain-general. These results suggest that category-selectivity is a general organizing principle not only of visual cortex, but also for higher-level cortical areas involved in memory. In this chapter we review the evidence for the manifestation of visual category preferences in memory systems, and how this relates to the well-established category-selectivity exhibited within visual cortex.

scholarly journals Efficient generation of reciprocal signals by inhibition

2012 ◽  
Vol 107 (9) ◽  
pp. 2453-2462 ◽  
Author(s):  
Sung-min Park ◽  
Esra Tara ◽  
Kamran Khodakhah
Keyword(s):  
Purkinje Cells ◽  
Granule Cell ◽  
Granule Cells ◽  
Mossy Fiber ◽  
Cell Activity ◽  
Common Mechanism ◽  
Input Output ◽  
Firing Rates ◽  
Neuronal Computation ◽  
The Brain

Reciprocal activity between populations of neurons has been widely observed in the brain and is essential for neuronal computation. The different mechanisms by which reciprocal neuronal activity is generated remain to be established. A common motif in neuronal circuits is the presence of afferents that provide excitation to one set of principal neurons and, via interneurons, inhibition to a second set of principal neurons. This circuitry can be the substrate for generation of reciprocal signals. Here we demonstrate that this equivalent circuit in the cerebellar cortex enables the reciprocal firing rates of Purkinje cells to be efficiently generated from a common set of mossy fiber inputs. The activity of a mossy fiber is relayed to Purkinje cells positioned immediately above it by excitatory granule cells. The firing rates of these Purkinje cells increase as a linear function of mossy fiber, and thus granule cell, activity. In addition to exciting Purkinje cells positioned immediately above it, the activity of a mossy fiber is relayed to laterally positioned Purkinje cells by a disynaptic granule cell → molecular layer interneuron pathway. Here we show in acutely prepared cerebellar slices that the input-output relationship of these laterally positioned Purkinje cells is linear and reciprocal to the first set. A similar linear input-output relationship between decreases in Purkinje cell firing and strength of stimulation of laterally positioned granule cells was also observed in vivo. Use of interneurons to generate reciprocal firing rates may be a common mechanism by which the brain generates reciprocal signals.

First order connections of the visual sector of the thalamic reticular nucleus in marmoset monkeys (Callithrix jacchus)

2007 ◽  
Vol 24 (6) ◽  
pp. 857-874 ◽  
Author(s):  
THOMAS FITZGIBBON ◽  
BRETT A. SZMAJDA ◽  
PAUL R. MARTIN
Keyword(s):  
Visual Field ◽  
Callithrix Jacchus ◽  
Higher Order ◽  
Dorsal Lateral Geniculate Nucleus ◽  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Lower Visual Field ◽  
First Order ◽  
Cortical Areas ◽  
Visual Areas

The thalamic reticular nucleus (TRN) supplies an important inhibitory input to the dorsal thalamus. Previous studies in non-primate mammals have suggested that the visual sector of the TRN has a lateral division, which has connections with first-order (primary) sensory thalamic and cortical areas, and a medial division, which has connections with higher-order (association) thalamic and cortical areas. However, the question whether the primate TRN is segregated in the same manner is controversial. Here, we investigated the connections of the TRN in a New World primate, the marmoset (Callithrix jacchus). The topography of labeled cells and terminals was analyzed following iontophoretic injections of tracers into the primary visual cortex (V1) or the dorsal lateral geniculate nucleus (LGNd). The results show that rostroventral TRN, adjacent to the LGNd, is primarily connected with primary visual areas, while the most caudal parts of the TRN are associated with higher order visual thalamic areas. A small region of the TRN near the caudal pole of the LGNd (foveal representation) contains connections where first (lateral TRN) and higher order visual areas (medial TRN) overlap. Reciprocal connections between LGNd and TRN are topographically organized, so that a series of rostrocaudal injections within the LGNd labeled cells and terminals in the TRN in a pattern shaped like rostrocaudal overlapping “fish scales.” We propose that the dorsal areas of the TRN, adjacent to the top of the LGNd, represent the lower visual field (connected with medial LGNd), and the more ventral parts of the TRN contain a map representing the upper visual field (connected with lateral LGNd).

scholarly journals Neuroplasticity in visual impairments

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Paulo Ramiler Silva ◽  
Tiago Farias ◽  
Fernando Cascio ◽  
Levi Dos Santos ◽  
Vinícius Peixoto ◽  
...  
Keyword(s):  
Systematic Review ◽  
Visual Acuity ◽  
Visual Impairment ◽  
Visual Impairments ◽  
Cortical Reorganization ◽  
Pubmed Database ◽  
Visual Areas ◽  
Visual Acuity Loss ◽  
The Brain

The visual acuity loss enables the brain to access new pathways in the quest to overcome the visual limitation and this is wellknown as neuroplasticity which have mechanisms to cortical reorganization. In this review, we related the evidences about the neuroplasticity as well as cortical anatomical differences and functional repercussions in visual impairments. We performed a systematic review of PUBMED database, without date or status publication restrictions. The findings demonstrate that the visual impairment produce a compensatory sensorial effect, in which non-visual areas are related to both cross (visual congenital) and multimodal (late blind) neuroplasticity.

scholarly journals Brain hierarchy score: Which deep neural networks are hierarchically brain-like?

2020 ◽  
Author(s):  
Soma Nonaka ◽  
Kei Majima ◽  
Shuntaro C. Aoki ◽  
Yukiyasu Kamitani
Keyword(s):  
Neural Networks ◽  
Image Recognition ◽  
High Performance ◽  
Deep Neural Networks ◽  
Recognition Performance ◽  
Brain Activity ◽  
Spatial Integration ◽  
Hierarchical Processing ◽  
Visual Areas ◽  
The Brain

SummaryAchievement of human-level image recognition by deep neural networks (DNNs) has spurred interest in whether and how DNNs are brain-like. Both DNNs and the visual cortex perform hierarchical processing, and correspondence has been shown between hierarchical visual areas and DNN layers in representing visual features. Here, we propose the brain hierarchy (BH) score as a metric to quantify the degree of hierarchical correspondence based on the decoding of individual DNN unit activations from human brain activity. We find that BH scores for 29 pretrained DNNs with varying architectures are negatively correlated with image recognition performance, indicating that recently developed high-performance DNNs are not necessarily brain-like. Experimental manipulations of DNN models suggest that relatively simple feedforward architecture with broad spatial integration is critical to brain-like hierarchy. Our method provides new ways for designing DNNs and understanding the brain in consideration of their representational homology.

scholarly journals The relative coding strength of object identity and nonidentity features in human occipito-temporal cortex and convolutional neural networks

2020 ◽  
Author(s):  
Yaoda Xu ◽  
Maryam Vaziri-Pashkam
Keyword(s):  
Visual Processing ◽  
Visual Pathway ◽  
Feature Representation ◽  
Object Categorization ◽  
Object Identity ◽  
Visual Areas ◽  
Ventral Visual Pathway ◽  
Identity Representation ◽  
The Brain ◽  
Early Human

ABSTRACTAny given visual object input is characterized by multiple visual features, such as identity, position and size. Despite the usefulness of identity and nonidentity features in vision and their joint coding throughout the primate ventral visual processing pathway, they have so far been studied relatively independently. Here we document the relative coding strength of object identity and nonidentity features in a brain region and how this may change across the human ventral visual pathway. We examined a total of four nonidentity features, including two Euclidean features (position and size) and two non-Euclidean features (image statistics and spatial frequency content of an image). Overall, identity representation increased and nonidentity feature representation decreased along the ventral visual pathway, with identity outweighed the non-Euclidean features, but not the Euclidean ones, in higher levels of visual processing. A similar analysis was performed in 14 convolutional neural networks (CNNs) pretrained to perform object categorization with varying architecture, depth, and with/without recurrent processing. While the relative coding strength of object identity and nonidentity features in lower CNN layers matched well with that in early human visual areas, the match between higher CNN layers and higher human visual regions were limited. Similar results were obtained regardless of whether a CNN was trained with real-world or stylized object images that emphasized shape representation. Together, by measuring the relative coding strength of object identity and nonidentity features, our approach provided a new tool to characterize feature coding in the human brain and the correspondence between the brain and CNNs.SIGNIFICANCE STATEMENTThis study documented the relative coding strength of object identity compared to four types of nonidentity features along the human ventral visual processing pathway and compared brain responses with those of 14 CNNs pretrained to perform object categorization. Overall, identity representation increased and nonidentity feature representation decreased along the ventral visual pathway, with the coding strength of the different nonidentity features differed at higher levels of visual processing. While feature coding in lower CNN layers matched well with that of early human visual areas, the match between higher CNN layers and higher human visual regions were limited. Our approach provided a new tool to characterize feature coding in the human brain and the correspondence between the brain and CNNs.

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