Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition

Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks. Although our results reconfirm the presence of math-selective hubs within the VTC and LPC, we report here a remarkable heterogeneity of neural responses within each region at both millimeter and millisecond scales. Moreover, we show that the heterogeneity of response profiles within each hub mirrors the distinct patterns of functional coupling between them. Our results support the existence of multiple bidirectional functional loops operating between discrete populations of neurons within the VTC and LPC during the visual processing of numerals and the performance of arithmetic functions. These findings reveal information about the dynamics of numerical processing in the brain and also provide insight into the fine-grained functional architecture and connectivity within the human brain.

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The physiology of perception in human temporal lobe is specialized for contextual novelty

Journal of Neurophysiology ◽

10.1152/jn.00131.2015 ◽

2015 ◽

Vol 114 (1) ◽

pp. 256-263 ◽

Cited By ~ 5

Author(s):

Kai J. Miller ◽

Dora Hermes ◽

Nathan Witthoft ◽

Rajesh P. N. Rao ◽

Jeffrey G. Ojemann

Keyword(s):

Temporal Cortex ◽

Total Activity ◽

Neuronal Population ◽

Electrode Arrays ◽

Stimulus Class ◽

Population Activity ◽

Visual Inputs ◽

The Face ◽

Ventral Temporal Cortex ◽

Increased Activity

The human ventral temporal cortex has regions that are known to selectively process certain categories of visual inputs; they are specialized for the content (“faces,” “places,” “tools”) and not the form (“line,” “patch”) of the image being seen. In our study, human patients with implanted electrocorticography (ECoG) electrode arrays were shown sequences of simple face and house pictures. We quantified neuronal population activity, finding robust face-selective sites on the fusiform gyrus and house-selective sites on the lingual/parahippocampal gyri. The magnitude and timing of single trials were compared between novel (“house-face”) and repeated (“face-face”) stimulus-type responses. More than half of the category-selective sites showed significantly greater total activity for novel stimulus class. Approximately half of the face-selective sites (and none of the house-selective sites) showed significantly faster latency to peak (∼50 ms) for novel stimulus class. This establishes subregions within category-selective areas that are differentially tuned to novelty in sequential context, where novel stimuli are processed faster in some regions, and with increased activity in others.

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Combined neural tuning in human ventral temporal cortex resolves the perceptual ambiguity of morphed 2-D images

10.1101/460337 ◽

2018 ◽

Author(s):

Mona Rosenke ◽

Nicolas Davidenko ◽

Kalanit Grill-Spector ◽

Kevin S. Weiner

Keyword(s):

Temporal Cortex ◽

Behavioral Model ◽

Behavioral Performance ◽

Neural Responses ◽

Domain Specific ◽

Estimated Parameters ◽

Adjacent Face ◽

Ventral Temporal Cortex ◽

Cortical Regions ◽

The Relationship

ABSTRACTWe have an amazing ability to categorize objects in the world around us. Nevertheless, how cortical regions in human ventral temporal cortex (VTC), which is critical for categorization, support this behavioral ability, is largely unknown. Here, we examined the relationship between neural responses and behavioral performance during the categorization of morphed silhouettes of faces and hands, which are animate categories processed in cortically adjacent regions in VTC. Our results reveal that the combination of neural responses from VTC face- and body-selective regions more accurately explains behavioral categorization than neural responses from either region alone. Furthermore, we built a model that predicts a person’s behavioral performance using estimated parameters of brain-behavioral relationships from a different group of people. We further show that this brain-behavioral model generalizes to adjacent face- and body-selective regions in lateral occipito-temporal cortex. Thus, while face- and body-selective regions are located within functionally-distinct domain-specific networks, cortically adjacent regions from both networks likely integrate neural responses to resolve competing and perceptually ambiguous information from both categories.

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A Probabilistic Functional Atlas of Human Occipito-Temporal Visual Cortex

Cerebral Cortex ◽

10.1093/cercor/bhaa246 ◽

2020 ◽

Vol 31 (1) ◽

pp. 603-619 ◽

Cited By ~ 1

Author(s):

Mona Rosenke ◽

Rick van Hoof ◽

Job van den Hurk ◽

Kalanit Grill-Spector ◽

Rainer Goebel

Keyword(s):

Visual Cortex ◽

Visual Processing ◽

Large Body ◽

Temporal Cortex ◽

Region Of Interest ◽

Brain Regions ◽

Functional Region ◽

Accurate Localization ◽

Imaging Research ◽

Ventral Temporal Cortex

Abstract Human visual cortex contains many retinotopic and category-specific regions. These brain regions have been the focus of a large body of functional magnetic resonance imaging research, significantly expanding our understanding of visual processing. As studying these regions requires accurate localization of their cortical location, researchers perform functional localizer scans to identify these regions in each individual. However, it is not always possible to conduct these localizer scans. Here, we developed and validated a functional region of interest (ROI) atlas of early visual and category-selective regions in human ventral and lateral occipito-temporal cortex. Results show that for the majority of functionally defined ROIs, cortex-based alignment results in lower between-subject variability compared to nonlinear volumetric alignment. Furthermore, we demonstrate that 1) the atlas accurately predicts the location of an independent dataset of ventral temporal cortex ROIs and other atlases of place selectivity, motion selectivity, and retinotopy. Next, 2) we show that the majority of voxel within our atlas is responding mostly to the labeled category in a left-out subject cross-validation, demonstrating the utility of this atlas. The functional atlas is publicly available (download.brainvoyager.com/data/visfAtlas.zip) and can help identify the location of these regions in healthy subjects as well as populations (e.g., blind people, infants) in which functional localizers cannot be run.

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Combined Neural Tuning in Human Ventral Temporal Cortex Resolves the Perceptual Ambiguity of Morphed 2D Images

Cerebral Cortex ◽

10.1093/cercor/bhaa081 ◽

2020 ◽

Vol 30 (9) ◽

pp. 4882-4898

Author(s):

Mona Rosenke ◽

Nicolas Davidenko ◽

Kalanit Grill-Spector ◽

Kevin S Weiner

Keyword(s):

Temporal Cortex ◽

Behavioral Performance ◽

Neural Responses ◽

Domain Specific ◽

Estimated Parameters ◽

Adjacent Face ◽

Ventral Temporal Cortex ◽

Cortical Regions ◽

Brain Behavior ◽

The Relationship

Abstract We have an amazing ability to categorize objects in the world around us. Nevertheless, how cortical regions in human ventral temporal cortex (VTC), which is critical for categorization, support this behavioral ability, is largely unknown. Here, we examined the relationship between neural responses and behavioral performance during the categorization of morphed silhouettes of faces and hands, which are animate categories processed in cortically adjacent regions in VTC. Our results reveal that the combination of neural responses from VTC face- and body-selective regions more accurately explains behavioral categorization than neural responses from either region alone. Furthermore, we built a model that predicts a person’s behavioral performance using estimated parameters of brain–behavior relationships from a different group of people. Moreover, we show that this brain–behavior model generalizes to adjacent face- and body-selective regions in lateral occipitotemporal cortex. Thus, while face- and body-selective regions are located within functionally distinct domain-specific networks, cortically adjacent regions from both networks likely integrate neural responses to resolve competing and perceptually ambiguous information from both categories.

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Diverse Temporal Dynamics of Repetition Suppression Revealed by Intracranial Recordings in the Human Ventral Temporal Cortex

Cerebral Cortex ◽

10.1093/cercor/bhaa173 ◽

2020 ◽

Vol 30 (11) ◽

pp. 5988-6003 ◽

Cited By ~ 1

Author(s):

Vinitha Rangarajan ◽

Corentin Jacques ◽

Robert T Knight ◽

Kevin S Weiner ◽

Kalanit Grill-Spector

Keyword(s):

Temporal Dynamics ◽

Human Subjects ◽

Temporal Cortex ◽

Theoretical Models ◽

High Temporal Resolution ◽

Neural Responses ◽

Repetition Suppression ◽

Temporal Features ◽

Ventral Temporal Cortex ◽

Intracranial Electrodes

Abstract Repeated stimulus presentations commonly produce decreased neural responses—a phenomenon known as repetition suppression (RS) or adaptation—in ventral temporal cortex (VTC) of humans and nonhuman primates. However, the temporal features of RS in human VTC are not well understood. To fill this gap in knowledge, we utilized the precise spatial localization and high temporal resolution of electrocorticography (ECoG) from nine human subjects implanted with intracranial electrodes in the VTC. The subjects viewed nonrepeated and repeated images of faces with long-lagged intervals and many intervening stimuli between repeats. We report three main findings: 1) robust RS occurs in VTC for activity in high-frequency broadband (HFB), but not lower-frequency bands; 2) RS of the HFB signal is associated with lower peak magnitude (PM), lower total responses, and earlier peak responses; and 3) RS effects occur early within initial stages of stimulus processing and persist for the entire stimulus duration. We discuss these findings in the context of early and late components of visual perception, as well as theoretical models of repetition suppression.

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

10.1101/2021.09.15.460220 ◽

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.

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Diverse temporal dynamics of repetition suppression revealed by intracranial recordings in human ventral temporal cortex

10.1101/711523 ◽

2019 ◽

Author(s):

Vinitha Rangarajan ◽

Corentin Jacques ◽

Robert T. Knight ◽

Kevin S. Weiner ◽

Kalanit Grill-Spector

Keyword(s):

Temporal Dynamics ◽

Human Subjects ◽

Temporal Cortex ◽

Theoretical Models ◽

High Temporal Resolution ◽

Neural Responses ◽

Repetition Suppression ◽

Temporal Features ◽

Ventral Temporal Cortex ◽

Intracranial Electrodes

AbstractRepeated stimulus presentations commonly produce decreased neural responses - a phenomenon known as repetition suppression (RS) or adaptation – in ventral temporal cortex (VTC) in humans and nonhuman primates. However, the temporal features of RS in human VTC are not well understood. To fill this gap in knowledge, we utilized the precise spatial localization and high temporal resolution of electrocorticography (ECoG) from 9 human subjects implanted with intracranial electrodes in VTC. Subjects viewed non-repeated and repeated images of faces with long-lagged intervals and many intervening stimuli between repeats. We report three main findings: (i) robust RS occurs in VTC for activity in high-frequency broadband (HFB), but not lower frequency bands, (ii) RS of the HFB signal is associated with lower peak magnitude, lower total responses, and earlier peak responses, and (iii) RS effects occur early within initial stages of stimulus processing and persist for the entire stimulus duration. We discuss these findings in the context of early and late components of visual perception, as well as theoretical models of repetition suppression.

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Sulcal Depth in the Medial Ventral Temporal Cortex Predicts the Location of a Place-Selective Region in Macaques, Children, and Adults

Cerebral Cortex ◽

10.1093/cercor/bhaa203 ◽

2020 ◽

Vol 31 (1) ◽

pp. 48-61 ◽

Cited By ~ 1

Author(s):

Vaidehi S Natu ◽

Michael J Arcaro ◽

Michael A Barnett ◽

Jesse Gomez ◽

Margaret Livingstone ◽

...

Keyword(s):

Age Groups ◽

Temporal Cortex ◽

Developmental Differences ◽

Functional Coupling ◽

Cortical Folding ◽

Functional Region ◽

Functional Relationships ◽

Major Interest ◽

Ventral Temporal Cortex ◽

Sulcal Depth

Abstract The evolution and development of anatomical–functional relationships in the cerebral cortex is of major interest in neuroscience. Here, we leveraged the fact that a functional region selective for visual scenes is located within a sulcus in the medial ventral temporal cortex (VTC) in both humans and macaques to examine the relationship between sulcal depth and place selectivity in the medial VTC across species and age groups. To do so, we acquired anatomical and functional magnetic resonance imaging scans in 9 macaques, 26 human children, and 28 human adults. Our results revealed a strong structural–functional coupling between sulcal depth and place selectivity across age groups and species in which selectivity was strongest near the deepest sulcal point (the sulcal pit). Interestingly, this coupling between sulcal depth and place selectivity strengthens from childhood to adulthood in humans. Morphological analyses suggest that the stabilization of sulcal–functional coupling in adulthood may be due to sulcal deepening and areal expansion with age as well as developmental differences in cortical curvature at the pial, but not the white matter surfaces. Our results implicate sulcal features as functional landmarks in high-level visual cortex and highlight that sulcal–functional relationships in the medial VTC are preserved between macaques and humans despite differences in cortical folding.

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Sulcal depth in medial ventral temporal cortex predicts the location of a place-selective region in macaques, children, and adults

10.1101/2020.01.27.921346 ◽

2020 ◽

Cited By ~ 1

Author(s):

Vaidehi S. Natu ◽

Michael J. Arcaro ◽

Michael A. Barnett ◽

Jesse Gomez ◽

Margaret Livingstone ◽

...

Keyword(s):

Age Groups ◽

Temporal Cortex ◽

Developmental Differences ◽

Functional Coupling ◽

Cortical Folding ◽

Functional Region ◽

Functional Relationships ◽

Major Interest ◽

Ventral Temporal Cortex ◽

Sulcal Depth

AbstractThe evolution and development of anatomical-functional relationships in the cerebral cortex is of major interest in neuroscience. Here, we leveraged the fact that a functional region selective for visual scenes is located within a sulcus in medial ventral temporal cortex (VTC) in both humans and macaques to examine the relationship between sulcal depth and place-selectivity in medial VTC across species and age groups. To do so, we acquired anatomical and functional magnetic resonance imaging scans in 9 macaques, 26 human children, and 28 human adults. Our results revealed a strong structural-functional coupling between sulcal depth and place-selectivity across age groups and species in which selectivity was strongest at the deepest sulcal point (the sulcal pit). Interestingly, this coupling between sulcal depth and place-selectivity strengthens from childhood to adulthood in humans. Morphological analyses suggest that the stabilization of sulcal-functional coupling in adulthood may be due to sulcal deepening and areal expansion with age as well as developmental differences in cortical curvature at the pial, but not the white matter surfaces. Our results implicate sulcal features as functional landmarks in high-level visual cortex and highlight that sulcal-functional relationships in medial VTC are preserved between macaques and humans despite differences in cortical folding.

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Representational Connectivity Analysis: Identifying Networks of Shared Changes in Representational Strength through Jackknife Resampling

10.1101/2020.05.28.103077 ◽

2020 ◽

Author(s):

Marc N. Coutanche ◽

Essang Akpan ◽

Rae R. Buckser

Keyword(s):

Visual Processing ◽

Temporal Cortex ◽

Brain Regions ◽

Statistical Technique ◽

Second Order ◽

Seed Region ◽

Connectivity Analysis ◽

Representational Space ◽

Classic Form ◽

Ventral Temporal Cortex

AbstractThe structure of information in the brain is crucial to cognitive function. The representational space of a brain region can be identified through Representational Similarity Analysis (RSA) applied to functional magnetic resonance imaging (fMRI) data. In its classic form, RSA collapses the time-series of each condition, eliminating fluctuations in similarity over time. We propose a method for identifying representational connectivity (RC) networks, which share fluctuations in representational strength, in an analogous manner to functional connectivity (FC), which tracks fluctuations in BOLD signal, and informational connectivity, which tracks fluctuations in pattern discriminability. We utilize jackknife resampling, a statistical technique in which observations are removed in turn to determine their influence. We applied the jackknife technique to an existing fMRI dataset collected as participants viewed videos of animals (Nastase et al., 2017). We used ventral temporal cortex (VT) as a seed region, and compared the resulting network to a second-order RSA, in which brain regions’ representational spaces are compared, and to the network identified through FC. The novel representational connectivity analysis identified a network comprising regions associated with lower-level visual processing, spatial cognition, perceptual-motor integration, and visual attention, indicating that these regions shared fluctuations in representational similarity strength with VT. RC, second-order RSA and FC identified areas unique to each method, indicating that analyzing shared fluctuations in the strength of representational similarity reveals previously undetectable networks of regions. The RC analysis thus offers a new way to understand representational similarity at the network level.

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