scholarly journals Hierarchical Organization of Corticothalamic Projections to the Pulvinar

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Reza Abbas Farishta ◽  
Denis Boire ◽  
Christian Casanova
Keyword(s):  
Higher Order ◽  
Hierarchical Organization ◽  
Hierarchical Level ◽  
Thalamic Nuclei ◽  
Cortical Areas ◽  
Visual Areas ◽  
Cortical Hierarchy ◽  
Area 21A ◽  
Extrastriate Areas ◽  
Corticothalamic Projections

Abstract Signals from lower cortical visual areas travel to higher-order areas for further processing through cortico-cortical projections, organized in a hierarchical manner. These signals can also be transferred between cortical areas via alternative cortical transthalamic routes involving higher-order thalamic nuclei like the pulvinar. It is unknown whether the organization of transthalamic pathways may reflect the cortical hierarchy. Two axon terminal types have been identified in corticothalamic (CT) pathways: the types I (modulators) and II (drivers) characterized by thin axons with small terminals and by thick axons and large terminals, respectively. In cats, projections from V1 to the pulvinar complex comprise mainly type II terminals, whereas those from extrastriate areas include a combination of both terminals suggesting that the nature of CT terminals varies with the hierarchical order of visual areas. To test this hypothesis, distribution of CT terminals from area 21a was charted and compared with 3 other visual areas located at different hierarchical levels. Results demonstrate that the proportion of modulatory CT inputs increases along the hierarchical level of cortical areas. This organization of transthalamic pathways reflecting cortical hierarchy provides new and fundamental insights for the establishment of more accurate models of cortical signal processing along transthalamic cortical pathways.

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 Corticothalamic Projections Gate Alpha Rhythms in the Pulvinar

2021 ◽  
Vol 15 ◽  
Author(s):  
Nelson Cortes ◽  
Reza Abbas Farishta ◽  
Hugo J. Ladret ◽  
Christian Casanova
Keyword(s):  
Cortical Area ◽  
Hierarchical Level ◽  
Oscillatory Activity ◽  
Excitatory Postsynaptic Potential ◽  
Area 17 ◽  
Cortical Areas ◽  
Area 21A ◽  
Spiking Activity

Two types of corticothalamic (CT) terminals reach the pulvinar nucleus of the thalamus, and their distribution varies according to the hierarchical level of the cortical area they originate from. While type 2 terminals are more abundant at lower hierarchical levels, terminals from higher cortical areas mostly exhibit type 1 axons. Such terminals also evoke different excitatory postsynaptic potential dynamic profiles, presenting facilitation for type 1 and depression for type 2. As the pulvinar is involved in the oscillatory regulation between intercortical areas, fundamental questions about the role of these different terminal types in the neuronal communication throughout the cortical hierarchy are yielded. Our theoretical results support that the co-action of the two types of terminals produces different oscillatory rhythms in pulvinar neurons. More precisely, terminal types 1 and 2 produce alpha-band oscillations at a specific range of connectivity weights. Such oscillatory activity is generated by an unstable transition of the balanced state network’s properties that it is found between the quiescent state and the stable asynchronous spike response state. While CT projections from areas 17 and 21a are arranged in the model as the empirical proportion of terminal types 1 and 2, the actions of these two cortical connections are antagonistic. As area 17 generates low-band oscillatory activity, cortical area 21a shifts pulvinar responses to stable asynchronous spiking activity and vice versa when area 17 produces an asynchronous state. To further investigate such oscillatory effects through corticothalamo-cortical projections, the transthalamic pathway, we created a cortical feedforward network of two cortical areas, 17 and 21a, with CT connections to a pulvinar-like network with two cortico-recipient compartments. With this model, the transthalamic pathway propagates alpha waves from the pulvinar to area 21a. This oscillatory transfer ceases when reciprocal connections from area 21a reach the pulvinar, closing the CT loop. Taken together, results of our model suggest that the pulvinar shows a bi-stable spiking activity, oscillatory or regular asynchronous spiking, whose responses are gated by the different activation of cortico-pulvinar projections from lower to higher-order areas such as areas 17 and 21a.

scholarly journals Characterization of Feedback Neurons in the High-Level Visual Cortical Areas That Project Directly to the Primary Visual Cortex in the Cat

2021 ◽  
Vol 14 ◽  
Author(s):  
Huijun Pan ◽  
Shen Zhang ◽  
Deng Pan ◽  
Zheng Ye ◽  
Hao Yu ◽  
...  
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Higher Order ◽  
Top Down ◽  
Cortical Areas ◽  
Area 21A ◽  
High Level ◽  
Visual Cortical

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat’s high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II–III, IV, V, and VI, with a higher proportion in layer II–III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support “reverse hierarchy theory” or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.

Novel Cognitive Functions Arise at the Convergence of Macroscale Gradients

2021 ◽  
pp. 1-16
Author(s):  
Heejung Jung ◽  
Tor D. Wager ◽  
R. McKell Carter
Keyword(s):  
Brain Regions ◽  
Higher Order ◽  
Hierarchical Organization ◽  
Functional Modules ◽  
Cortical Areas ◽  
Future Space ◽  
Close Proximity ◽  
Sensory Cortices ◽  
Developmental Characteristics ◽  
The Brain

Abstract Functions in higher-order brain regions are the source of extensive debate. Although past trends have been to describe the brain—especially posterior cortical areas—in terms of a set of functional modules, a new emerging paradigm focuses on the integration of proximal functions. In this review, we synthesize emerging evidence that a variety of novel functions in the higher-order brain regions are due to convergence: convergence of macroscale gradients brings feature-rich representations into close proximity, presenting an opportunity for novel functions to arise. Using the TPJ as an example, we demonstrate that convergence is enabled via three properties of the brain: (1) hierarchical organization, (2) abstraction, and (3) equidistance. As gradients travel from primary sensory cortices to higher-order brain regions, information becomes abstracted and hierarchical, and eventually, gradients meet at a point maximally and equally distant from their sensory origins. This convergence, which produces multifaceted combinations, such as mentalizing another person's thought or projecting into a future space, parallels evolutionary and developmental characteristics in such regions, resulting in new cognitive and affective faculties.

scholarly journals Visual Interhemispheric and Striate-Extrastriate Cortical Connections in the Rabbit: A Multiple Tracer Study

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Adrian K. Andelin ◽  
David J. Bruning ◽  
Daniel J. Felleman ◽  
Jaime F. Olavarria
Keyword(s):  
Visual Processing ◽  
Alternative Model ◽  
Tracer Study ◽  
Cortical Areas ◽  
Callosal Connections ◽  
Cortical Connections ◽  
Visual Areas ◽  
Cortical Visual Processing ◽  
Rats And Mice ◽  
Extrastriate Areas

Previous studies in rabbits identified an array of extrastriate cortical areas anatomically connected with V1 but did not describe their internal topography. To address this issue, we injected multiple anatomical tracers into different regions in V1 of the same animal and analyzed the topography of resulting extrastriate labeled fields with reference to the patterns of callosal connections and myeloarchitecture revealed in tangential sections of the flattened cortex. Our results extend previous studies and provide further evidence that rabbit extrastriate areas resemble the visual areas in rats and mice not only in their general location with respect to V1 but also in their internal topography. Moreover, extrastriate areas in the rabbit maintain a constant relationship with myeloarchitectonic borders and features of the callosal pattern. These findings highlight the rabbit as an alternative model to rats and mice for advancing our understanding of cortical visual processing in mammals, especially for projects benefiting from a larger brain.

Single Units and Visual Cortical Organization

Perception ◽  
1998 ◽  
Vol 27 (8) ◽  
pp. 889-935 ◽  
Author(s):  
Peter Lennie
Keyword(s):  
Visual System ◽  
Striate Cortex ◽  
Occipital Cortex ◽  
Relevant Information ◽  
Hierarchical Organization ◽  
Cortical Organization ◽  
Visual Areas ◽  
The World ◽  
Visual Cortical ◽  
Extrastriate Areas

The visual system has a parallel and hierarchical organization, evident at every stage from the retina onwards. Although the general benefits of parallel and hierarchical organization in the visual system are easily understood, it has not been easy to discern the function of the visual cortical modules. I explore the view that striate cortex segregates information about different attributes of the image, and dispatches it for analysis to different extrastriate areas. I argue that visual cortex does not undertake multiple relatively independent analyses of the image from which it assembles a unified representation that can be interrogated about the what and where of the world. Instead, occipital cortex is organized so that perceptually relevant information can be recovered at every level in the hierarchy, that information used in making decisions at one level is not passed on to the next level, and, with one rather special exception (area MT), through all stages of analysis all dimensions of the image remain intimately coupled in a retinotopic map. I then offer some explicit suggestions about the analyses undertaken by visual areas in occipital cortex, and conclude by examining some objections to the proposals.

scholarly journals Multiscale Organization of Landscape Structure in the Middle Taiga of European Russia

2019 ◽  
Vol 66 ◽  
pp. 1-19 ◽  
Author(s):  
Alexander V. Khoroshev
Keyword(s):  
Spatial Heterogeneity ◽  
Landscape Structure ◽  
Higher Order ◽  
Hierarchical Organization ◽  
European Russia ◽  
Morphological Properties ◽  
Middle Taiga ◽  
Hierarchical Level ◽  
Response Surface Regression ◽  
Landscape Ecological

Dominant landscape-ecological models either focus on the hierarchical organization of a single phenomenon or describe relations at a single hierarchical level. We proposed the tool MALS (Multiscale Analysis of Landscape Structure) to reveal  multiple independent hierarchies based on the interactions between properties of relief, soils and vegetation and tested it on the example of the middle-taiga landscape in European Russia. Morphological properties of soils and abundance of plant species were measured in operational territorial units. Multidimensional scaling was used to reveal ecological drivers. Combinations of landforms from DEM were used to describe spatial heterogeneity in the higher-order geosystems. Response surface regression was applied to relate soils and vegetation to each other and to relief of several hypothetic higher-order geosystems. Spatial extent of a higher-order geosystem was determined from the series of equations. Then we compared contributions of external (inter-level) and internal (intra-level) interactions to spatial variability of soils and vegetation. Herbs, low shrubs, and morphologic soil properties turned out to be controlled mainly by the geosystems with the linear size 1200 m, while trees, shrubs, and sediments – by the geosystems with size 2000 m. From 2 to 5 levels of the higher-order geosystems should be considered in order to obtain the proper explanation of spatial heterogeneity.

scholarly journals Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

2019 ◽  
Author(s):  
Hsiang-Yun Sherry Chien ◽  
Christopher J. Honey
Keyword(s):  
Higher Order ◽  
Hierarchical Organization ◽  
Temporal Context ◽  
Neural Responses ◽  
Prior Context ◽  
New Information ◽  
Cortical Hierarchy ◽  
Linear Integration ◽  
Sensory Cortices ◽  
Cortical Regions

SummaryHow does information from seconds earlier affect neocortical responses to new input? Here, we used empirical measurements and computational modeling to study the integration and forgetting of prior information. We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different, but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while higher-order cortical regions aligned last. In some higher order regions, responses to the same sentence took more than 10 seconds to align. What kinds of computations can explain this hierarchical organization of contextual alignment? Passive linear integration models predict that regions which are slower to integrate new information should also be slower to forget old information. However, we found that higher order regions could rapidly forget prior context. The data were better captured by a model composed of hierarchical autoencoders in time (HAT). In HAT, cortical regions maintain a temporal context representation which is actively integrated with input at each moment, and this integration is gated by prediction error. These data and models suggest that sequences of information are combined throughout the cortical hierarchy using an active and gated integration process.

scholarly journals Corticothalamic Projections Gate Alpha Rhythms in the Pulvinar

2021 ◽  
Author(s):  
Nelson Cortes ◽  
Reza Abbas Farishta ◽  
Hugo Ladret ◽  
Christian Casanova
Keyword(s):  
Cortical Area ◽  
Hierarchical Level ◽  
Oscillatory Activity ◽  
Excitatory Postsynaptic Potential ◽  
Area 17 ◽  
Cortical Areas ◽  
Area 21A ◽  
Spiking Activity

AbstractTwo types of corticothalamic (CT) terminals reach the pulvinar nucleus of the thalamus, and their distribution varies according to the hierarchical level of the cortical area they originate from. While type 2 terminals are more abundant at lower hierarchical levels, terminals from higher cortical areas mostly exhibit type 1 axons. Such terminals also evoke different excitatory postsynaptic potential dynamic profiles, presenting facilitation for type 1 and depression for type 2. As the pulvinar is involved in the oscillatory regulation between intercortical areas, fundamental questions about the role of these different terminal types in the neuronal communication throughout the cortical hierarchy are yielded. Our theoretical results support that the co-action of the two types of terminals produces different oscillatory rhythms in pulvinar neurons. More precisely, terminal types 1 and 2 produce alpha-band oscillations at a specific range of connectivity weights. Such oscillatory activity is generated by an unstable transition of the balanced state network’s properties that it is found between the quiescent state and the stable asynchronous spike response state. While CT projections from areas 17 and 21a are arranged in the model as the empirical proportion of terminals types 1 and 2, the actions of these two cortical connections are antagonistic. As area 17 generates low-band oscillatory activity, cortical area 21a shifts pulvinar responses to stable asynchronous spiking activity and vice-versa when area 17 produces an asynchronous state. To further investigate such oscillatory effects through corticothalamo-cortical projections, the transthalamic pathway, we created a cortical feedforward network of two cortical areas, 17 and 21a, with CT connections to a pulvinar-like network. With this model, the transthalamic pathway propagates alpha waves from the pulvinar to area 21a. This oscillatory transfer ceases when reciprocal connections from area 21a reach the pulvinar, closing the cortico-thalamic loop. Taken together, results of our model suggest that the pulvnar shows a bi-stable spiking activity, oscillatory or regular asynchronous spiking, whose responses are gated by the different activation of cortico-pulvinar projections from lower to higher-order areas such as areas 17 and 21a.

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