scholarly journals Brain Networks Sensitive to Object Novelty, Value, and Their Combination

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Ali Ghazizadeh ◽  
Mohammad Amin Fakharian ◽  
Arash Amini ◽  
Whitney Griggs ◽  
David A Leopold ◽  
...  
Keyword(s):  
Brain Networks ◽  
Temporal Cortex ◽  
Common Currency ◽  
Brain Responses ◽  
Activation Dynamics ◽  
Fractal Patterns ◽  
The Common ◽  
Ventral Temporal Cortex ◽  
Value Coding ◽  
The Brain

Abstract Novel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain responses to visual fractal patterns varying in either novelty or value dimensions and compared the results with the structure of functionally connected brain networks determined at rest. The results show that different brain networks possess unique combinations of novelty and value coding. One network identified in the ventral temporal cortex preferentially encoded object novelty, whereas another in the parietal cortex encoded the learned value. A third network, broadly composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, encoded both dimensions with similar activation dynamics. Our results support the emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

scholarly journals Object novelty and value coding segregate across functionally connected brain networks

2019 ◽  
Author(s):  
Ali Ghazizadeh ◽  
MohammadAmin Fakharian ◽  
Arash Amini ◽  
Whitney Griggs ◽  
David A. Leopold ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Networks ◽  
Temporal Cortex ◽  
Common Currency ◽  
Activation Dynamics ◽  
Fractal Patterns ◽  
The Common ◽  
Ventral Temporal Cortex ◽  
Value Coding ◽  
The Brain

AbstractNovel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain activity to fractal patterns varying in either novelty or value dimensions in the context of functionally connected brain networks determined at rest. Results show unique combinations of novelty and value coding across the brain networks. Networks in the ventral temporal cortex and in the parietal cortex showed preferential coding of novelty and value dimensions, respectively, while a wider network composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, responded to both dimensions with similar activation dynamics. Our results support emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

NEUROECONOMICS, NEUROPHYSIOLOGY AND THE COMMON CURRENCY HYPOTHESIS

2008 ◽  
Vol 24 (3) ◽  
pp. 419-429 ◽  
Author(s):  
Anthony Landreth ◽  
John Bickle
Keyword(s):  
Rational Choice ◽  
Dopamine Release ◽  
Research Programme ◽  
Neural Mechanism ◽  
The Other ◽  
Common Currency ◽  
The Common ◽  
The Brain ◽  
Electrophysiological Methods

We briefly describe ways in which neuroeconomics has made contributions to its contributing disciplines, especially neuroscience, and a specific way in which it could make future contributions to both. The contributions of a scientific research programme can be categorized in terms of (1) description and classification of phenomena, (2) the discovery of causal relationships among those phenomena, and (3) the development of tools to facilitate (1) and (2). We consider ways in which neuroeconomics has advanced neuroscience and economics along each line. Then, focusing on electrophysiological methods, we consider a puzzle within neuroeconomics whose solution we believe could facilitate contributions to both neuroscience and economics, in line with category (2). This puzzle concerns how the brain assigns reward values to otherwise incomparable stimuli. According to the common currency hypothesis, dopamine release is a component of a neural mechanism that solves comparability problems. We review two versions of the common currency hypothesis, one proposed by Read Montague and colleagues, the other by William Newsome and colleagues, and fit these hypotheses into considerations of rational choice.

scholarly journals Attention enhances category representations across the brain with strengthened residual correlations to ventral temporal cortex

2021 ◽  
Author(s):  
Arielle S Keller ◽  
Akshay V Jagadeesh ◽  
Lior Bugatus ◽  
Leanne M Williams ◽  
Kalanit Grill-Spector
Keyword(s):  
Selective Attention ◽  
Temporal Cortex ◽  
Relevant Information ◽  
Cortical Region ◽  
Visual Responses ◽  
Attention Task ◽  
Category Information ◽  
Ventral Temporal Cortex ◽  
Residual Correlations ◽  
The Brain

How does attention enhance neural representations of goal-relevant stimuli while suppressing representations of ignored stimuli across regions of the brain? While prior studies have shown that attention enhances visual responses, we lack a cohesive understanding of how selective attention modulates visual representations across the brain. Here, we used functional magnetic resonance imaging (fMRI) while participants performed a selective attention task on superimposed stimuli from multiple categories and used a data-driven approach to test how attention affects both decodability of category information and residual correlations (after regressing out stimulus-driven variance) with category-selective regions of ventral temporal cortex (VTC). Our data reveal three main findings. First, when two objects are simultaneously viewed, the category of the attended object can be decoded more readily than the category of the ignored object, with the greatest attentional enhancements observed in occipital and temporal lobes. Second, after accounting for the response to the stimulus, the correlation in the residual brain activity between a cortical region and a category-selective region of VTC was elevated when that region's preferred category was attended vs. ignored, and more so in the right occipital, parietal, and frontal cortices. Third, we found that the stronger the residual correlations between a given region of cortex and VTC, the better visual category information could be decoded from that region. These findings suggest that heightened residual correlations by selective attention may reflect the sharing of information between sensory regions and higher-order cortical regions to provide attentional enhancement of goal-relevant information.

scholarly journals Principles governing the topological organization of object selectivities in ventral temporal cortex

2021 ◽  
Author(s):  
Yiyuan Zhang ◽  
Ke Zhou ◽  
Pinglei Bao ◽  
Jia Liu
Keyword(s):  
Visual Processing ◽  
Temporal Cortex ◽  
High Dimensional ◽  
Complex Object ◽  
Object Space ◽  
Minimization Principle ◽  
Topological Organization ◽  
Ventral Temporal Cortex ◽  
Dimensional Object ◽  
The Brain

To achieve the computational goal of rapidly recognizing miscellaneous objects in the environment despite large variations in their appearance, our mind represents objects in a high-dimensional object space to provide separable category information and enable the extraction of different kinds of information necessary for various levels of the visual processing. To implement this abstract and complex object space, the ventral temporal cortex (VTC) develops different object-selective regions with a certain topological organization as the physical substrate. However, the principle that governs the topological organization of object selectivities in the VTC remains unclear. Here, equipped with the wiring cost minimization principle constrained by the wiring length of neurons in the human temporal lobe, we constructed a hybrid self-organizing map (SOM) model as an artificial VTC (VTC-SOM) to explain how the abstract and complex object space is faithfully implemented in the brain. In two in silico experiments with the empirical brain imaging and single-unit data, our VTC-SOM predicted the topological structure of fine-scale functional regions (face-, object-, body-, and place-selective regions) and the boundary (i.e., middle Fusiform Sulcus) in large-scale abstract functional maps (animate vs. inanimate, real-word large-size vs. small-size, central vs. peripheral), with no significant loss in functionality (e.g., categorical selectivity, a hierarchy of view-invariant representations). These findings illustrated that the simple principle utilized in our model, rather than multiple hypotheses such as temporal associations, conceptual knowledge, and computational demands together, was apparently sufficient to determine the topological organization of object-selectivities in the VTC. In this way, the high-dimensional object space is implemented in a two-dimensional cortical surface of the brain faithfully.

scholarly journals Behavioral and neural decomposition of skull-induced death awareness

2020 ◽  
Author(s):  
Tianyu Gao ◽  
Yue Pu ◽  
Jingyi Zhou ◽  
Guo Zheng ◽  
Yuqing Zhou ◽  
...  
Keyword(s):  
Temporal Cortex ◽  
Two Stage ◽  
Psychological Constructs ◽  
Neural Modulation ◽  
Death Awareness ◽  
Brain Responses ◽  
Neural Processes ◽  
Ventral Temporal Cortex ◽  
Human Skulls ◽  
Induced Changes

AbstractDeath awareness influences multiple aspects of human lives, but its psychological constructs and underlying brain mechanisms remain unclear. We address these by measuring behavioral and brain responses to images of human skulls. We show that skulls relative to control stimuli delay responses to life-related words but speed responses to death-related words. Skulls compared to the control stimuli induce early deactivations in the posterior ventral temporal cortex followed by activations in the posterior and anterior ventral temporal cortices. The early and late neural modulations by perceived skulls respectively predict skull-induced changes of behavioral responses to life- and death-related words and the early neural modulation further predicts death anxiety. Our findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life.One sentence summaryBehavioral and brain imaging findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life.

scholarly journals Multivoxel Neural Reinforcement Changes Resting-State Functional Connectivity Within the Threat Regulation Network

2020 ◽  
Author(s):  
Vincent Taschereau-Dumouchel ◽  
Toshinori Chiba ◽  
Ai Koizumi ◽  
Mitsuo Kawato ◽  
Hakwan Lau
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Temporal Cortex ◽  
Physiological Reactivity ◽  
Resting State Functional Connectivity ◽  
Double Blind ◽  
Brain Responses ◽  
Regulation Network ◽  
Before And After ◽  
Ventral Temporal Cortex

AbstractUsing neural reinforcement, participants can be trained to pair a reward with the activation of specific multivoxel patterns in their brains. In a double-blind placebo-controlled experiment, we previously showed that this intervention can decrease the physiological reactivity associated with naturally feared animals. However, the mechanisms behind the effect remain incompletely understood and its usefulness for treatment remains unclear. If the intervention fundamentally changed the brain responses, we might expect to observe relatively stable changes in the functional connectivity within the threat regulation network. To evaluate this possibility, we conducted functional magnetic resonance imaging (fMRI) sessions while subjects were at rest, before and after neural reinforcement, and quantified the changes in resting-state functional connectivity accordingly. Our results indicate that neural reinforcement increased the connectivity of prefrontal regulatory regions with the amygdala and the ventral temporal cortex (where the visual representations of phobic targets are). Surprisingly, we found no evidence of Hebbian-like learning during neural reinforcement, contrary to what one may expect based on previous neurofeedback studies. These results suggest that multivoxel neural reinforcement, also known as decoded neurofeedback (DecNef), may operate via unique mechanisms, distinct from those involved in conventional neurofeedback.

scholarly journals Attention enhances category representations across the brain with strengthened residual correlations to ventral temporal cortex

NeuroImage ◽  
2022 ◽  
pp. 118900
Author(s):  
Arielle S. Keller ◽  
Akshay Jagadeesh ◽  
Lior Bugatus ◽  
Leanne M. Williams ◽  
Kalanit Grill-Spector
Keyword(s):  
Temporal Cortex ◽  
Ventral Temporal Cortex ◽  
Residual Correlations ◽  
The Brain

scholarly journals Finding decodable information that is read out in behaviour

2018 ◽  
Author(s):  
Tijl Grootswagers ◽  
Radoslaw M. Cichy ◽  
Thomas A. Carlson
Keyword(s):  
Temporal Cortex ◽  
Brain Activation ◽  
Object Perception ◽  
Neural Activation ◽  
Experimental Conditions ◽  
Activation Patterns ◽  
Visual Objects ◽  
Neuroimaging Data ◽  
Ventral Temporal Cortex ◽  
The Brain

AbstractMultivariate decoding methods applied to neuroimaging data have become the standard in cognitive neuroscience for unravelling statistical dependencies between brain activation patterns and experimental conditions. The current challenge is to demonstrate that information decoded as such by the experimenter is in fact used by the brain itself to guide behaviour. Here we demonstrate a promising approach to do so in the context of neural activation during object perception and categorisation behaviour. We first localised decodable information about visual objects in the human brain using a spatially-unbiased multivariate decoding analysis. We then related brain activation patterns to behaviour using a machine-learning based extension of signal detection theory. We show that while there is decodable information about visual category throughout the visual brain, only a subset of those representations predicted categorisation behaviour, located mainly in anterior ventral temporal cortex. Our results have important implications for the interpretation of neuroimaging studies, highlight the importance of relating decoding results to behaviour, and suggest a suitable methodology towards this aim.

Comprehending Prehending: Neural Correlates of Processing Verbs with Motor Stems

2007 ◽  
Vol 19 (5) ◽  
pp. 855-865 ◽  
Author(s):  
Shirley-Ann Rüschemeyer ◽  
Marcel Brass ◽  
Angela D. Friederici
Keyword(s):  
Motor System ◽  
Figurative Language ◽  
Temporal Cortex ◽  
Neural Correlates ◽  
Residual Effects ◽  
Brain Responses ◽  
Complex Verbs ◽  
The Right ◽  
Action Verbs ◽  
The Brain

The interaction between language and action systems has become an increasingly interesting topic of discussion in cognitive neuroscience. Several recent studies have shown that processing of action verbs elicits activation in the cerebral motor system in a somatotopic manner. The current study extends these findings to show that the brain responses for processing of verbs with specific motor meanings differ not only from that of other motor verbs, but, crucially, that the comprehension of verbs with motor meanings (i.e., greifen, to grasp) differs fundamentally from the processing of verbs with abstract meanings (i.e., denken, to think). Second, the current study investigated the neural correlates of processing morphologically complex verbs with abstract meanings built on stems with motor versus abstract meanings (i.e., begreifen, to comprehend vs. bedenken, to consider). Although residual effects of motor stem meaning might have been expected, we see no evidence for this in our data. Processing of morphologically complex verbs built on motor stems showed no differences in involvement of the motor system when compared with processing complex verbs with abstract stems. Complex verbs built on motor stems did show increased activation compared with complex verbs built on abstract stems in the right posterior temporal cortex. This result is discussed in light of the involvement of the right temporal cortex in comprehension of metaphoric or figurative language.

Dynamic Domain Specificity In Human Ventral Temporal Cortex

2020 ◽  
Author(s):  
Brett B. Bankson ◽  
Matthew J. Boring ◽  
R. Mark Richardson ◽  
Avniel Singh Ghuman
Keyword(s):  
Visual Processing ◽  
Temporal Cortex ◽  
Processing System ◽  
Neural Representation ◽  
Domain Specificity ◽  
Individual Level ◽  
Ventral Temporal Cortex ◽  
Intracranial Recordings ◽  
Dynamic Domain ◽  
The Brain

ABSTRACTAn enduring neuroscientific debate concerns the extent to which neural representation is restricted to networks of patches specialized for particular domains of perceptual input (Kaniwsher et al., 1997; Livingstone et al., 2019), or distributed outside of these patches to broad areas of cortex as well (Haxby et al., 2001; Op de Beeck, 2008). A critical level for this debate is the localization of the neural representation of the identity of individual images, (Spiridon & Kanwisher, 2002) such as individual-level face or written word recognition. To address this debate, intracranial recordings from 489 electrodes throughout ventral temporal cortex across 17 human subjects were used to assess the spatiotemporal dynamics of individual word and face processing within and outside cortical patches strongly selective for these categories of visual information. Individual faces and words were first represented primarily only in strongly selective patches and then represented in both strongly and weakly selective areas approximately 170 milliseconds later. Strongly and weakly selective areas contributed non-redundant information to the representation of individual images. These results can reconcile previous results endorsing disparate poles of the domain specificity debate by highlighting the temporally segregated contributions of different functionally defined cortical areas to individual level representations. Taken together, this work supports a dynamic model of neural representation characterized by successive domain-specific and distributed processing stages.SIGNIFICANCE STATEMENTThe visual processing system performs dynamic computations to differentiate visually similar forms, such as identifying individual words and faces. Previous models have localized these computations to 1) circumscribed, specialized portions of the brain, or 2) more distributed aspects of the brain. The current work combines machine learning analyses with human intracranial recordings to determine the neurodynamics of individual face and word processing in and outside of brain regions selective for these visual categories. The results suggest that individuation involves computations that occur first in primarily highly selective parts of the visual processing system, then later recruits highly and non-highly selective regions. These results mediate between extant models of neural specialization by suggesting a dynamic domain specificity model of visual processing.

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