scholarly journals Posterior inferotemporal cortex cells use multiple visual pathways to complement fine and coarse discriminations

2016 ◽  
Author(s):  
C. R. Ponce ◽  
S. G. Lomber ◽  
M. S. Livingstone
Keyword(s):  
Visual Recognition ◽  
Temporal Cortex ◽  
Macaque Monkey ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Visual Areas ◽  
Cortical Cooling ◽  
Feature Selectivity ◽  
Pit Cells

ABSTRACTIn the macaque monkey brain, posterior inferior temporal cortex (PIT) cells are responsible for visual object recognition. They receive concurrent inputs from visual areas V4, V3 and V2. We asked how these different anatomical pathways contribute to PIT response properties by deactivating them while monitoring PIT activity. Using cortical cooling of areas V2/V3 or V4 and a hierarchical model of visual recognition, we conclude that these distinct pathways do not transmit different classes of visual features, but serve instead to maintain a balance of local-and global-feature selectivity in IT.

A Cortical Mechanism for Triggering Top-Down Facilitation in Visual Object Recognition

2003 ◽  
Vol 15 (4) ◽  
pp. 600-609 ◽  
Author(s):  
Moshe Bar
Keyword(s):  
Object Recognition ◽  
Visual Recognition ◽  
Temporal Cortex ◽  
Input Image ◽  
Initial Guess ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Top Down ◽  
Bottom Up ◽  
Level Information

The majority of the research related to visual recognition has so far focused on bottom-up analysis, where the input is processed in a cascade of cortical regions that analyze increasingly complex information. Gradually more studies emphasize the role of top-down facilitation in cortical analysis, but it remains something of a mystery how such processing would be initiated. After all, top-down facilitation implies that high-level information is activated earlier than some relevant lower-level information. Building on previous studies, I propose a specific mechanism for the activation of top-down facilitation during visual object recognition. The gist of this hypothesis is that a partially analyzed version of the input image (i.e., a blurred image) is projected rapidly from early visual areas directly to the prefrontal cortex (PFC). This coarse representation activates in the PFC expectations about the most likely interpretations of the input image, which are then back-projected as an “initial guess” to the temporal cortex to be integrated with the bottom-up analysis. The top-down process facilitates recognition by substantially limiting the number of object representations that need to be considered. Furthermore, such a rapid mechanism may provide critical information when a quick response is necessary.

Organization of local horizontal functional interactions between neurons in the inferior temporal cortex of macaque monkeys

2014 ◽  
Vol 111 (12) ◽  
pp. 2589-2602 ◽  
Author(s):  
Hiroshi Tamura ◽  
Yoshiya Mori ◽  
Hidekazu Kaneko
Keyword(s):  
Neuronal Activity ◽  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Detailed Knowledge ◽  
Visual Response ◽  
Stimulus Preference ◽  
Macaque Monkeys ◽  
Functional Interactions ◽  
Cross Correlation Analysis

Detailed knowledge of neuronal circuitry is necessary for understanding the mechanisms underlying information processing in the brain. We investigated the organization of horizontal functional interactions in the inferior temporal cortex of macaque monkeys, which plays important roles in visual object recognition. Neuronal activity was recorded from the inferior temporal cortex using an array of eight tetrodes, with spatial separation between paired neurons up to 1.4 mm. We evaluated functional interactions on a time scale of milliseconds using cross-correlation analysis of neuronal activity of the paired neurons. Visual response properties of neurons were evaluated using responses to a set of 100 visual stimuli. Adjacent neuron pairs tended to show strong functional interactions compared with more distant neuron pairs, and neurons with similar stimulus preferences tended to show stronger functional interactions than neurons with different stimulus preferences. Thus horizontal functional interactions in the inferior temporal cortex appear to be organized according to both cortical distances and similarity in stimulus preference between neurons. Furthermore, the relationship between strength of functional interactions and similarity in stimulus preference observed in distant neuron pairs was more prominent than in adjacent pairs. The results suggest that functional circuitry is specifically organized, depending on the horizontal distances between neurons. Such specificity endows each circuit with unique functions.

scholarly journals Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes

2012 ◽  
Vol 108 (11) ◽  
pp. 3073-3086 ◽  
Author(s):  
Arjun K. Bansal ◽  
Jedediah M. Singer ◽  
William S. Anderson ◽  
Alexandra Golby ◽  
Joseph R. Madsen ◽  
...  
Keyword(s):  
Visual Recognition ◽  
Cortical Plasticity ◽  
Temporal Stability ◽  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Field Potentials ◽  
Long Time ◽  
Degree Of Stability ◽  
The Stability ◽  
External Stimuli

The cerebral cortex needs to maintain information for long time periods while at the same time being capable of learning and adapting to changes. The degree of stability of physiological signals in the human brain in response to external stimuli over temporal scales spanning hours to days remains unclear. Here, we quantitatively assessed the stability across sessions of visually selective intracranial field potentials (IFPs) elicited by brief flashes of visual stimuli presented to 27 subjects. The interval between sessions ranged from hours to multiple days. We considered electrodes that showed robust visual selectivity to different shapes; these electrodes were typically located in the inferior occipital gyrus, the inferior temporal cortex, and the fusiform gyrus. We found that IFP responses showed a strong degree of stability across sessions. This stability was evident in averaged responses as well as single-trial decoding analyses, at the image exemplar level as well as at the category level, across different parts of visual cortex, and for three different visual recognition tasks. These results establish a quantitative evaluation of the degree of stationarity of visually selective IFP responses within and across sessions and provide a baseline for studies of cortical plasticity and for the development of brain-machine interfaces.

The Neural Correlates of Object Familiarity and Domain Specificity in the Human Visual Cortex: An fMRI Study

2011 ◽  
Vol 23 (10) ◽  
pp. 2878-2891 ◽  
Author(s):  
Gian Daniele Zannino ◽  
Francesco Barban ◽  
Emiliano Macaluso ◽  
Carlo Caltagirone ◽  
Giovanni A. Carlesimo
Keyword(s):  
Functional Organization ◽  
Temporal Cortex ◽  
Visual Noise ◽  
Visual Object ◽  
Structural Description ◽  
Visual Object Recognition ◽  
Living Things ◽  
Fmri Study ◽  
Functional Locus ◽  
Object Familiarity

Ventral occipito-temporal cortex is known to play a major role in visual object recognition. Still unknown is whether object familiarity and semantic domain are critical factors in its functional organization. Most models assume a functional locus where exemplars of familiar categories are represented: the structural description system. On the assumption that familiarity should modulate the effect of visual noise on form recognition, we attempted to individualize the structural description system by scanning healthy subjects while they looked at familiar (living and nonliving things) and novel 3-D objects, either with increasing or decreasing visual noise. Familiarity modulated the visual noise effect (particularly when familiar items were living things), revealing a substrate for the structural description system in right occipito-temporal cortex. These regions also responded preferentially to living as compared to nonliving items. Overall, these results suggest that living items are particularly reliant on the structural description system.

scholarly journals Visual recognition of the female body axis drives spatial elements of male courtship in Drosophila melanogaster

2019 ◽  
Author(s):  
Ross M McKinney ◽  
Yehuda Ben-Shahar
Keyword(s):  
Visual Cues ◽  
Visual Recognition ◽  
Virgin Female ◽  
Mechanistic Explanation ◽  
Visual Object ◽  
Projection Neurons ◽  
Visual Object Recognition ◽  
Male Courtship ◽  
Courtship Behaviors ◽  
Spatial Locations

SummaryLike other mating behaviors, the courtship ritual exhibited by male Drosophila towards a virgin female is comprised of spatiotemporal sequences of innate behavioral elements. Yet, the specific stimuli and neural circuits that determine when and where males release individual courtship elements are not well understood. Here, we investigated the role of visual object recognition in the release of specific behavioral elements during bouts of male courtship. By using a computer vision and machine learning based approach for high-resolution analyses of the male courtship ritual, we show that the release of distinct behavioral elements occur at stereotyped locations around the female and depends on the ability of males to recognize visual landmarks present on the female. Specifically, we show that independent of female motion, males utilize unique populations of visual projection neurons to recognize the eyes of a target female, which is essential for the release of courtship behaviors at their appropriate spatial locations. Together, these results provide a mechanistic explanation for how relatively simple visual cues could play a role in driving both spatially- and temporally-complex social interactions.

scholarly journals Orthogonal Representations of Object Shape and Category in Deep Convolutional Neural Networks and Human Visual Cortex

2019 ◽  
Author(s):  
Astrid A. Zeman ◽  
J. Brendan Ritchie ◽  
Stefania Bracci ◽  
Hans Op de Beeck
Keyword(s):  
Neural Networks ◽  
Visual Cortex ◽  
Convolutional Neural Networks ◽  
Network Performance ◽  
Temporal Cortex ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Deep Convolutional Neural Networks ◽  
Shape Information ◽  
Category Information

AbstractDeep Convolutional Neural Networks (CNNs) are gaining traction as the benchmark model of visual object recognition, with performance now surpassing humans. While CNNs can accurately assign one image to potentially thousands of categories, network performance could be the result of layers that are tuned to represent the visual shape of objects, rather than object category, since both are often confounded in natural images. Using two stimulus sets that explicitly dissociate shape from category, we correlate these two types of information with each layer of multiple CNNs. We also compare CNN output with fMRI activation along the human visual ventral stream by correlating artificial with biological representations. We find that CNNs encode category information independently from shape, peaking at the final fully connected layer in all tested CNN architectures. Comparing CNNs with fMRI brain data, early visual cortex (V1) and early layers of CNNs encode shape information. Anterior ventral temporal cortex encodes category information, which correlates best with the final layer of CNNs. The interaction between shape and category that is found along the human visual ventral pathway is echoed in multiple deep networks. Our results suggest CNNs represent category information independently from shape, much like the human visual system.

Minimal Recognizable Configurations Elicit Category-selective Responses in Higher Order Visual Cortex

2019 ◽  
Vol 31 (9) ◽  
pp. 1354-1367
Author(s):  
Yael Holzinger ◽  
Shimon Ullman ◽  
Daniel Harari ◽  
Marlene Behrmann ◽  
Galia Avidan
Keyword(s):  
Visual Cortex ◽  
Object Recognition ◽  
Visual Recognition ◽  
Recognition Performance ◽  
Occipital Cortex ◽  
Building Blocks ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Face Area ◽  
Early Visual Cortex

Visual object recognition is performed effortlessly by humans notwithstanding the fact that it requires a series of complex computations, which are, as yet, not well understood. Here, we tested a novel account of the representations used for visual recognition and their neural correlates using fMRI. The rationale is based on previous research showing that a set of representations, termed “minimal recognizable configurations” (MIRCs), which are computationally derived and have unique psychophysical characteristics, serve as the building blocks of object recognition. We contrasted the BOLD responses elicited by MIRC images, derived from different categories (faces, objects, and places), sub-MIRCs, which are visually similar to MIRCs, but, instead, result in poor recognition and scrambled, unrecognizable images. Stimuli were presented in blocks, and participants indicated yes/no recognition for each image. We confirmed that MIRCs elicited higher recognition performance compared to sub-MIRCs for all three categories. Whereas fMRI activation in early visual cortex for both MIRCs and sub-MIRCs of each category did not differ from that elicited by scrambled images, high-level visual regions exhibited overall greater activation for MIRCs compared to sub-MIRCs or scrambled images. Moreover, MIRCs and sub-MIRCs from each category elicited enhanced activation in corresponding category-selective regions including fusiform face area and occipital face area (faces), lateral occipital cortex (objects), and parahippocampal place area and transverse occipital sulcus (places). These findings reveal the psychological and neural relevance of MIRCs and enable us to make progress in developing a more complete account of object recognition.

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