scholarly journals High-level visual object representations in inferior temporal cortex

2011 ◽  
Author(s):  
M.C. Mur
Keyword(s):  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Object Representations ◽  
High Level

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.

Reaction Time for Object Categorization Is Predicted by Representational Distance

2014 ◽  
Vol 26 (1) ◽  
pp. 132-142 ◽  
Author(s):  
Thomas A. Carlson ◽  
J. Brendan Ritchie ◽  
Nikolaus Kriegeskorte ◽  
Samir Durvasula ◽  
Junsheng Ma
Keyword(s):  
Decision Making ◽  
Temporal Cortex ◽  
Internal Representation ◽  
Inferior Temporal Cortex ◽  
Object Categorization ◽  
Object Representations ◽  
Multivariate Pattern Analysis ◽  
Individual Object ◽  
Multivariate Pattern ◽  
The Brain

How does the brain translate an internal representation of an object into a decision about the object's category? Recent studies have uncovered the structure of object representations in inferior temporal cortex (IT) using multivariate pattern analysis methods. These studies have shown that representations of individual object exemplars in IT occupy distinct locations in a high-dimensional activation space, with object exemplar representations clustering into distinguishable regions based on category (e.g., animate vs. inanimate objects). In this study, we hypothesized that a representational boundary between category representations in this activation space also constitutes a decision boundary for categorization. We show that behavioral RTs for categorizing objects are well described by our activation space hypothesis. Interpreted in terms of classical and contemporary models of decision-making, our results suggest that the process of settling on an internal representation of a stimulus is itself partially constitutive of decision-making for object categorization.

scholarly journals Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey

Neuron ◽  
2008 ◽  
Vol 60 (6) ◽  
pp. 1126-1141 ◽  
Author(s):  
Nikolaus Kriegeskorte ◽  
Marieke Mur ◽  
Douglas A. Ruff ◽  
Roozbeh Kiani ◽  
Jerzy Bodurka ◽  
...  
Keyword(s):  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Object Representations

scholarly journals The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks

2017 ◽  
Author(s):  
B. B. Bankson ◽  
M.N. Hebart ◽  
I.I.A. Groen ◽  
C.I. Baker
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Stimulus Onset ◽  
Visual Object ◽  
Object Representations ◽  
Object Processing ◽  
Low Level ◽  
Conceptual Representations ◽  
Brain Responses ◽  
High Level

AbstractVisual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categorical or conceptual representations. Here, we aimed to estimate a lower temporal bound for the emergence of conceptual representations by defining two criteria that characterize such representations: 1) conceptual object representations should generalize across different exemplars of the same object, and 2) these representations should reflect high-level behavioral judgments. To test these criteria, we compared magnetoencephalography (MEG) recordings between two groups of participants (n = 16 per group) exposed to different exemplar images of the same object concepts. Further, we disentangled low-level from high-level MEG responses by estimating the unique and shared contribution of models of behavioral judgments, semantics, and different layers of deep neural networks of visual object processing. We find that 1) both generalization across exemplars as well as generalization of object-related signals across time increase after 150 ms, peaking around 230 ms; 2) behavioral judgments explain the most unique variance in the response after 150 ms. Collectively, these results suggest a lower bound for the emergence of conceptual object representations around 150 ms following stimulus onset.

scholarly journals High-Level Visual Object Representations Are Constrained by Position

2010 ◽  
Vol 20 (12) ◽  
pp. 2916-2925 ◽  
Author(s):  
Dwight J. Kravitz ◽  
Nikolaus Kriegeskorte ◽  
Chris I. Baker
Keyword(s):  
Visual Object ◽  
Object Representations ◽  
High Level

scholarly journals Learning Warps Object Representations in the Ventral Temporal Cortex

2016 ◽  
Vol 28 (7) ◽  
pp. 1010-1023 ◽  
Author(s):  
Alex Clarke ◽  
Philip J. Pell ◽  
Charan Ranganath ◽  
Lorraine K. Tyler
Keyword(s):  
Critical Role ◽  
Temporal Cortex ◽  
Real Life ◽  
Visual Object ◽  
Object Representations ◽  
Pattern Similarity ◽  
Contextual Associations ◽  
Ventral Temporal Cortex ◽  
Pattern Information ◽  
The Impact

The human ventral temporal cortex (VTC) plays a critical role in object recognition. Although it is well established that visual experience shapes VTC object representations, the impact of semantic and contextual learning is unclear. In this study, we tracked changes in representations of novel visual objects that emerged after learning meaningful information about each object. Over multiple training sessions, participants learned to associate semantic features (e.g., “made of wood,” “floats”) and spatial contextual associations (e.g., “found in gardens”) with novel objects. fMRI was used to examine VTC activity for objects before and after learning. Multivariate pattern similarity analyses revealed that, after learning, VTC activity patterns carried information about the learned contextual associations of the objects, such that objects with contextual associations exhibited higher pattern similarity after learning. Furthermore, these learning-induced increases in pattern information about contextual associations were correlated with reductions in pattern information about the object's visual features. In a second experiment, we validated that these contextual effects translated to real-life objects. Our findings demonstrate that visual object representations in VTC are shaped by the knowledge we have about objects and show that object representations can flexibly adapt as a consequence of learning with the changes related to the specific kind of newly acquired information.

scholarly journals Action-specific feature processing in the human visual cortex

2018 ◽  
Author(s):  
Simona Monaco ◽  
Ying Chen ◽  
Nicholas Menghi ◽  
J Douglas Crawford
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Temporal Cortex ◽  
Action Planning ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Cortical Processing ◽  
Visual Stream ◽  
Dorsal Visual Stream

AbstractSensorimotor integration involves feedforward and reentrant processing of sensory input. Grasp-related motor activity precedes and is thought to influence visual object processing. Yet, while the importance of reentrant feedback is well established in perception, the top-down modulations for action and the neural circuits involved in this process have received less attention. Do action-specific intentions influence the processing of visual information in the human cortex? Using a cue-separation fMRI paradigm, we found that action-specific instruction (manual alignment vs. grasp) influences the cortical processing of object orientation several seconds after the object had been viewed. This influence occurred as early as in the primary visual cortex and extended to ventral and dorsal visual stream areas. Importantly, this modulation was unrelated to non-specific action planning. Further, the primary visual cortex showed stronger functional connectivity with frontal-parietal areas and the inferior temporal cortex during the delay following orientation processing for align than grasping movements, strengthening the idea of reentrant feedback from dorsal visual stream areas involved in action. To our knowledge, this is the first demonstration that intended manual actions have such an early, pervasive, and differential influence on the cortical processing of vision.

scholarly journals Representational content of oscillatory brain activity during object recognition

2020 ◽  
Author(s):  
Leila Reddy ◽  
Radoslaw Martin Cichy ◽  
Rufin VanRullen
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Representational Content ◽  
Stimulus Presentation ◽  
Visual Object ◽  
Object Representations ◽  
Beta Band ◽  
Whole Brain ◽  
Frequency Bands ◽  
High Level

AbstractNumerous theories propose a key role for brain oscillations in visual perception. Most of these theories postulate that sensory information is encoded in specific oscillatory components (e.g., power or phase) of specific frequency bands. These theories are often tested with whole-brain recording methods of low spatial resolution (EEG or MEG), or depth recordings that provide a local, incomplete view of the brain. Opportunities to bridge the gap between local neural populations and whole-brain signals are rare. Here, using representational similarity analysis we ask which MEG oscillatory components (power and phase, across various frequency bands) correspond to low or high-level visual object representations, using brain representations from fMRI, or layer-wise representations in Deep Neural Networks (DNNs) as a template for low/high-level object representations. The results showed that around stimulus onset and offset, most transient oscillatory signals correlated with low-level brain patterns (V1). During stimulus presentation, sustained beta (∼20Hz) and gamma (>60Hz) power best correlated with V1, while oscillatory phase components correlated with IT representations. Surprisingly, this pattern of results did not always correspond to low- or high-level DNN layer activity. In particular, sustained beta-band oscillatory power reflected high-level DNN layers, suggestive of a feed-back component. These results begin to bridge the gap between whole-brain oscillatory signals and object representations supported by local neuronal activations.

scholarly journals Neurons in the inferior temporal cortex of macaque monkeys are sensitive to multiple surface features from natural objects

2016 ◽  
Author(s):  
Hiroshi Tamura ◽  
Haruki Otsuka ◽  
Yukako Yamane
Keyword(s):  
Visual Processing ◽  
Neuronal Response ◽  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Visual Object ◽  
Response Properties ◽  
Surface Features ◽  
Hierarchical Processing ◽  
Structure Degradation ◽  
Surface Images

AbstractObject surfaces contain a variety of visual features that help us to recognize them. To understand how this information is represented and processed in the brain, we prepared a set of images from natural object surfaces that maintained surface features but lacked contours. We examined spiking responses of neurons in the inferior temporal (IT) cortex of monkeys, which is a crucial structure needed for visual object recognition. About half of IT neurons responded to surface images with sharp selectivity, indicating that a significant fraction of these neurons contribute to object surface representation in a sparse manner. Responses of IT neurons were susceptible to image manipulations, including color removal, removal of luminance contrasts, and spatial structure degradation. This shows that multiple features are required for IT responses to surface images. Comparing neuronal response properties among IT, visual area 4 (V4), and primary visual cortex (V1) revealed properties of IT neurons that differed from those in the other visual processing regions. Additionally, some neuronal response properties were similar between IT and V4, but differed from those in V1, indicating that responses of IT neurons to surface images are constructed by hierarchical processing throughout the ventral visual pathway.

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