scholarly journals Gray Matter Thinning in Ventral Temporal Cortex from Childhood to Adulthood is Associated with Increased Myelination

2018 ◽  
Vol 18 (10) ◽  
pp. 542 ◽  
Author(s):  
Vaidehi Natu ◽  
Jesse Gomez ◽  
Michael Barnett ◽  
Brianna Jeska ◽  
Zonglei Zhen ◽  
...  
Keyword(s):  
Gray Matter ◽  
Temporal Cortex ◽  
Ventral Temporal Cortex

scholarly journals White matter fascicles and cortical microstructure predict reading-related responses in human ventral temporal cortex

2020 ◽  
Author(s):  
Mareike Grotheer ◽  
Jason Yeatman ◽  
Kalanit Grill-Spector
Keyword(s):  
White Matter ◽  
Gray Matter ◽  
Linear Models ◽  
Temporal Cortex ◽  
Spatial Relationship ◽  
Spatial Layout ◽  
Proton Relaxation ◽  
Imaging Data ◽  
Data Driven Approach ◽  
Ventral Temporal Cortex

AbstractReading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain’s fascicles and to map their endpoints density in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint density of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. Next, in the remaining 20 participants (validation set), we showed that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual’s reading-related responses in lateral VTC.HighlightsThe ILF, AF, and VOF predict the spatial layout of reading-related responses in VTCGray matter microstructure improves the prediction of reading-related responsesFascicles and gray matter structure together predict the location of the VWFA

scholarly journals How learning to read affects the function and structure of ventral temporal cortex

2019 ◽  
Vol 19 (10) ◽  
pp. 4c
Author(s):  
Kalanit Grill-Spector ◽  
Marisa Nordt ◽  
Vaidehi Natu ◽  
Jesse Gomez ◽  
Brianna Jeska ◽  
...  
Keyword(s):  
Temporal Cortex ◽  
Learning To Read ◽  
Ventral Temporal Cortex

scholarly journals Near-perfect prediction of reaction time for face gender judgments based on activity in ventral temporal cortex

2015 ◽  
Vol 15 (12) ◽  
pp. 753
Author(s):  
Kalanit Grill-Spector ◽  
Kevin Weiner ◽  
Nikolaus Kriegeskorte ◽  
Kendrick Kay
Keyword(s):  
Reaction Time ◽  
Temporal Cortex ◽  
Ventral Temporal Cortex

scholarly journals Real-world size of objects serves as an axis of object space

2021 ◽  
Author(s):  
Taicheng Huang ◽  
Yiying Song ◽  
Jia Liu
Keyword(s):  
Real World ◽  
Temporal Cortex ◽  
Principal Component ◽  
Physical World ◽  
Task Demands ◽  
Deep Convolutional Neural Networks ◽  
Object Space ◽  
The Real ◽  
Ventral Temporal Cortex ◽  
Dimensional Object

Our mind can represent various objects from the physical world metaphorically into an abstract and complex high-dimensional object space, with a finite number of orthogonal axes encoding critical object features. Previous fMRI studies have shown that the middle fusiform sulcus in the ventral temporal cortex separates the real-world small-size map from the large-size map. Here we asked whether the feature of objects' real-world size constructed an axis of object space with deep convolutional neural networks (DCNNs) based on three criteria of sensitivity, independence and necessity that are impractical to be examined altogether with traditional approaches. A principal component analysis on features extracted by the DCNNs showed that objects' real-world size was encoded by an independent component, and the removal of this component significantly impaired DCNN's performance in recognizing objects. By manipulating stimuli, we found that the shape and texture of objects, rather than retina size, co-occurrence and task demands, accounted for the representation of the real-world size in the DCNNs. A follow-up fMRI experiment on humans further demonstrated that the shape, but not the texture, was used to infer the real-world size of objects in humans. In short, with both computational modeling and empirical human experiments, our study provided the first evidence supporting the feature of objects' real-world size as an axis of object space, and devised a novel paradigm for future exploring the structure of object space.

scholarly journals The nature of the animacy organization in human ventral temporal cortex

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Sushrut Thorat ◽  
Daria Proklova ◽  
Marius V Peelen
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Temporal Cortex ◽  
Behavioral Experiments ◽  
Diagnostic Features ◽  
Social Agents ◽  
Independent Components ◽  
Ventral Temporal Cortex ◽  
Organizing Principles ◽  
The Continuum

The principles underlying the animacy organization of the ventral temporal cortex (VTC) remain hotly debated, with recent evidence pointing to an animacy continuum rather than a dichotomy. What drives this continuum? According to the visual categorization hypothesis, the continuum reflects the degree to which animals contain animal-diagnostic features. By contrast, the agency hypothesis posits that the continuum reflects the degree to which animals are perceived as (social) agents. Here, we tested both hypotheses with a stimulus set in which visual categorizability and agency were dissociated based on representations in convolutional neural networks and behavioral experiments. Using fMRI, we found that visual categorizability and agency explained independent components of the animacy continuum in VTC. Modeled together, they fully explained the animacy continuum. Finally, clusters explained by visual categorizability were localized posterior to clusters explained by agency. These results show that multiple organizing principles, including agency, underlie the animacy continuum in VTC.

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