Dataset Information

Blockwise Human Brain Network Visual Comparison Using NodeTrix Representation.

ABSTRACT: Visually comparing human brain networks from multiple population groups serves as an important task in the field of brain connectomics. The commonly used brain network representation, consisting of nodes and edges, may not be able to reveal the most compelling network differences when the reconstructed networks are dense and homogeneous. In this paper, we leveraged the block information on the Region Of Interest (ROI) based brain networks and studied the problem of blockwise brain network visual comparison. An integrated visual analytics framework was proposed. In the first stage, a two-level ROI block hierarchy was detected by optimizing the anatomical structure and the predictive comparison performance simultaneously. In the second stage, the NodeTrix representation was adopted and customized to visualize the brain network with block information. We conducted controlled user experiments and case studies to evaluate our proposed solution. Results indicated that our visual analytics method outperformed the commonly used node-link graph and adjacency matrix design in the blockwise network comparison tasks. We have shown compelling findings from two real-world brain network data sets, which are consistent with the prior connectomics studies.

SUBMITTER: Yang X

PROVIDER: S-EPMC5293509 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Blockwise Human Brain Network Visual Comparison Using NodeTrix Representation.

Yang Xinsong X Shi Lei L Daianu Madelaine M Tong Hanghang H Liu Qingsong Q Thompson Paul P

IEEE transactions on visualization and computer graphics 20160805 1

Visually comparing human brain networks from multiple population groups serves as an important task in the field of brain connectomics. The commonly used brain network representation, consisting of nodes and edges, may not be able to reveal the most compelling network differences when the reconstructed networks are dense and homogeneous. In this paper, we leveraged the block information on the Region Of Interest (ROI) based brain networks and studied the problem of blockwise brain network visual ...[more]

PMID: 27514058

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Project description:In the mammalian brain, the insula is the primary cortical substrate involved in the perception of taste. Recent imaging studies in rodents have identified a "gustotopic" organization in the insula, whereby distinct insula regions are selectively responsive to one of the five basic tastes. However, numerous studies in monkeys have reported that gustatory cortical neurons are broadly-tuned to multiple tastes, and tastes are not represented in discrete spatial locations. Neuroimaging studies in humans have thus far been unable to discern between these two models, though this may be because of the relatively low spatial resolution used in taste studies to date. In the present study, we examined the spatial representation of taste within the human brain using ultra-high resolution functional magnetic resonance imaging (MRI) at high magnetic field strength (7-tesla). During scanning, male and female participants tasted sweet, salty, sour, and tasteless liquids, delivered via a custom-built MRI-compatible tastant-delivery system. Our univariate analyses revealed that all tastes (vs tasteless) activated primary taste cortex within the bilateral dorsal mid-insula, but no brain region exhibited a consistent preference for any individual taste. However, our multivariate searchlight analyses were able to reliably decode the identity of distinct tastes within those mid-insula regions, as well as brain regions involved in affect and reward, such as the striatum, orbitofrontal cortex, and amygdala. These results suggest that taste quality is not represented topographically, but by a distributed population code, both within primary taste cortex as well as regions involved in processing the hedonic and aversive properties of taste.SIGNIFICANCE STATEMENT The insula is the primary cortical substrate involved in taste perception, yet some question remains as to whether this region represents distinct tastes topographically or via a population code. Using high field (7-tesla), high-resolution functional magnetic resonance imaging in humans, we examined the representation of different tastes delivered during scanning. All tastes activated primary taste cortex within the bilateral mid-insula, but no brain region exhibited any consistent taste preference. However, multivariate analyses reliably decoded taste quality within the bilateral mid-insula as well as the striatum, orbitofrontal cortex, and bilateral amygdala. This suggests that taste quality is represented by a spatial population code within regions involved in sensory and appetitive properties of taste.

Dataset Information

Blockwise Human Brain Network Visual Comparison Using NodeTrix Representation.

Publications

Blockwise Human Brain Network Visual Comparison Using NodeTrix Representation.

Similar Datasets

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