Visual processing pathways in the cerebral cortex of monkeys and humans

1991 ◽  
Vol 16 ◽  
pp. IX
Author(s):  
Leslie G. Ungerleider
Author(s):  
JAMES V. HAXBY ◽  
CHERYL L. GRADY ◽  
BARRY HORWITZ ◽  
JUDY SALERNO ◽  
LESLIE G. UNGERLEIDER ◽  
...  

1993 ◽  
Vol 10 (1) ◽  
pp. 59-72 ◽  
Author(s):  
Joan S. Baizer ◽  
Robert Desimone ◽  
Leslie G. Ungerleider

AbstractTo investigate the subcortical connections of the object vision and spatial vision cortical processing pathways, we injected the inferior temporal and posterior parietal cortex of six Rhesus monkeys with retrograde or anterograde tracers. The temporal injections included area TE on the lateral surface of the hemisphere and adjacent portions of area TEO. The parietal injections covered the posterior bank of the intraparietal sulcus, including areas VIP and LIP. Our results indicate that several structures project to both the temporal and parietal cortex, including the medial and lateral pulvinar, claustrum, and nucleus basalis. However, the cells in both the pulvinar and claustrum that project to the two systems are mainly located in different parts of those structures, as are the terminals which arise from the temporal and parietal cortex. Likewise, the projections from the temporal and parietal cortex to the caudate nucleus and putamen are largely segregated. Finally, we found projections to the pons and superior colliculus from parietal but not temporal cortex, whereas we found the lateral basal and medial basal nuclei of the amygdala to be reciprocally connected with temporal but not parietal cortex. Thus, the results show that, like the cortical connections of the two visual processing systems, the subcortical connections are remarkably segregated.


2016 ◽  
Vol 26 (07) ◽  
pp. 1650030 ◽  
Author(s):  
Pablo Martínez-Cañada ◽  
Christian Morillas ◽  
Begoña Pino ◽  
Eduardo Ros ◽  
Francisco Pelayo

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.


2002 ◽  
Vol 87 (2) ◽  
pp. 845-858 ◽  
Author(s):  
Stefano Ferraina ◽  
Martin Paré ◽  
Robert H. Wurtz

Many neurons in the frontal eye field (FEF) and lateral intraparietal (LIP) areas of cerebral cortex are active during the visual-motor events preceding the initiation of saccadic eye movements: they respond to visual targets, increase their activity before saccades, and maintain their activity during intervening delay periods. Previous experiments have shown that the output neurons from both LIP and FEF convey the full range of these activities to the superior colliculus (SC) in the brain stem. These areas of cerebral cortex also have strong interconnections, but what signals they convey remains unknown. To determine what these cortico-cortical signals are, we identified the LIP neurons that project to FEF by antidromic activation, and we studied their activity during a delayed-saccade task. We then compared these cortico-cortical signals to those sent subcortically by also identifying the LIP neurons that project to the intermediate layers of the SC. Of 329 FEF projection neurons and 120 SC projection neurons, none were co-activated by both FEF and SC stimulation. FEF projection neurons were encountered more superficially in LIP than SC projection neurons, which is consistent with the anatomical projection of many cortical layer III neurons to other cortical areas and of layer V neurons to subcortical structures. The estimated conduction velocities of FEF projection neurons (16.7 m/s) were significantly slower that those of SC projection neurons (21.7 m/s), indicating that FEF projection neurons have smaller axons. We identified three main differences in the discharge properties of FEF and SC projection neurons: only 44% of the FEF projection neurons changed their activity during the delayed-saccade task compared with 69% of the SC projection neurons; only 17% of the task-related FEF projection neurons showed saccadic activity, whereas 42% of the SC projection neurons showed such increases; 78% of the FEF projection neurons had a visual response but no saccadic activity, whereas only 55% of the SC projection neurons had similar activity. The FEF and SC projection neurons had three similarities: both had visual, delay, and saccadic activity, both had stronger delay and saccadic activity with visually guided than with memory-guided saccades, and both had broadly tuned responses for disparity stimuli, suggesting that their visual receptive fields have a three-dimensional configuration. These observations indicate that the activity carried between parietal and frontal cortical areas conveys a spectrum of signals but that the preponderance of activity conveyed might be more closely related to earlier visual processing than to the later saccadic stages that are directed to the SC.


1991 ◽  
Vol 88 (5) ◽  
pp. 1621-1625 ◽  
Author(s):  
J. V. Haxby ◽  
C. L. Grady ◽  
B. Horwitz ◽  
L. G. Ungerleider ◽  
M. Mishkin ◽  
...  

2002 ◽  
Vol 14 (12) ◽  
pp. 2857-2881 ◽  
Author(s):  
Angela J. Yu ◽  
Martin A. Giese ◽  
Tomaso A. Poggio

Visual processing in the cortex can be characterized by a predominantly hierarchical architecture, in which specialized brain regions along the processing pathways extract visual features of increasing complexity, accompanied by greater invariance in stimulus properties such as size and position. Various studies have postulated that a nonlinear pooling function such as the maximum (MAX) operation could be fundamental in achieving such selectivity and invariance. In this article, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Different canonical models are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we compare the performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each model and discuss the relevant physiological considerations.


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