InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

Furcila, Diana; Garcia, M. Teresa Cepero; Cosmin-Toader, Nicusor; Morales, Juan; LaTorre, Antonio; Rodríguez, Antonio; Pastor, Luis; DeFelipe, Javier; Alonso‐Nanclares, Lidia

doi:10.3389/fnana.2019.00028

Cited by 3 publications

(2 citation statements)

References 44 publications

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“…The ability to study functional connectivity dynamics without the practical or ethical complications of symptom provocation has allowed psychiatric data collection in enormous quantity and quality. Indeed, so much data is now available that analysis has surpassed collection as the biggest challenge in neuroscience (Burns et al, 2013;Furcila et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Complexity changes in functional state dynamics suggest focal connectivity reductions

Blair

Soriano‐Mas

Cabral

et al. 2022

Front. Hum. Neurosci.

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The past two decades have seen an explosion in the methods and directions of neuroscience research. Along with many others, complexity research has rapidly gained traction as both an independent research field and a valuable subdiscipline in computational neuroscience. In the past decade alone, several studies have suggested that psychiatric disorders affect the spatiotemporal complexity of both global and region-specific brain activity (Liu et al., 2013; Adhikari et al., 2017; Li et al., 2018). However, many of these studies have not accounted for the distributed nature of cognition in either the global or regional complexity estimates, which may lead to erroneous interpretations of both global and region-specific entropy estimates. To alleviate this concern, we propose a novel method for estimating complexity. This method relies upon projecting dynamic functional connectivity into a low-dimensional space which captures the distributed nature of brain activity. Dimension-specific entropy may be estimated within this space, which in turn allows for a rapid estimate of global signal complexity. Testing this method on a recently acquired obsessive-compulsive disorder dataset reveals substantial increases in the complexity of both global and dimension-specific activity versus healthy controls, suggesting that obsessive-compulsive patients may experience increased disorder in cognition. To probe the potential causes of this alteration, we estimate subject-level effective connectivity via a Hopf oscillator-based model dynamic model, the results of which suggest that obsessive-compulsive patients may experience abnormally high connectivity across a broad network in the cortex. These findings are broadly in line with results from previous studies, suggesting that this method is both robust and sensitive to group-level complexity alterations.

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Section: Introductionmentioning

confidence: 99%

Complexity changes in functional state dynamics suggest focal connectivity reductions

Blair

Soriano‐Mas

Cabral

et al. 2022

Front. Hum. Neurosci.

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“…[ASO*16] developed an exploratory tool integrating selected visualization components for MRI‐derived measurements and clinical data while Furcilia et al . [FGT*19] focus on tabular neuroscience data. Angelelli et al .…”

Section: Related Workmentioning

confidence: 99%

VisualNeuro: A Hypothesis Formation and Reasoning Application for Multi‐Variate Brain Cohort Study Data

Jonsson

Bergström

Forsell

et al. 2020

Computer Graphics Forum

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We present an application, and its development process, for interactive visual analysis of brain imaging data and clinical measurements. The application targets neuroscientists interested in understanding the correlations between active brain regions and physiological or psychological factors. The application has been developed in a participatory design process and has subsequently been released as the free software ‘VisualNeuro’. From initial observations of the neuroscientists' workflow, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration requiring the use of many tools side by side. Consequently, our application has been designed to simplify the workflow combining statistical analysis with interactive visual exploration. The resulting environment comprises parallel coordinates for effective overview and selection, Welch's t‐test to filter out brain regions with statistically significant differences and multiple visualizations for comparison between brain regions and clinical parameters. These exploration concepts enable neuroscientists to interactively explore the complex bidirectional interplay between clinical and brain measurements and easily compare different patient groups. A qualitative user study has been performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights and is an effective tool for hypothesis formation.

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EzLang: A C Based Programming Language

Sesha,

Bairagi,

Abhishek

et al. 2023

2023 7th International Conference on Computing, Communication, Control and Automation (ICCUBEA)

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InTool Explorer: An Interactive Exploratory Analysis Tool for Versatile Visualizations of Neuroscientific Data

Cited by 3 publications

References 44 publications

Complexity changes in functional state dynamics suggest focal connectivity reductions

Complexity changes in functional state dynamics suggest focal connectivity reductions

VisualNeuro: A Hypothesis Formation and Reasoning Application for Multi‐Variate Brain Cohort Study Data

EzLang: A C Based Programming Language

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