Increase in internetwork functional connectivity in the human brain with attention capture

The selective properties of attention have been extensively studied. There are some circumstances in which attention can have widespread and systemic effects, however, such as when it is captured by an unexpected, salient stimulus or event. How are such effects propagated in the human brain? Using graph theory analysis of fMRI data, we show here that salient task-irrelevant events produced a global increase in the functional integration of the brain’s neural networks.

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Comparative Analysis of Methods for Calculating the Interactions Between the Human Brain Regions Based on Resting-State FMRI Data to Build Long-Term Cognitive Architectures

Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020 - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-030-65596-9_46 ◽

2020 ◽

pp. 380-390

Author(s):

Alexey Poyda ◽

Maksim Sharaev ◽

Vyacheslav Orlov ◽

Stanislav Kozlov ◽

Irina Enyagina ◽

...

Keyword(s):

Comparative Analysis ◽

Human Brain ◽

Resting State ◽

Resting State Fmri ◽

Brain Regions ◽

Fmri Data ◽

Cognitive Architectures

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Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson’s Disease

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.729677 ◽

2021 ◽

Vol 15 ◽

Author(s):

Chengyuan Wu ◽

Caio Matias ◽

Thomas Foltynie ◽

Patricia Limousin ◽

Ludvic Zrinzo ◽

...

Keyword(s):

Graph Theory ◽

Deep Brain Stimulation ◽

Brain Stimulation ◽

Theory Analysis ◽

Whole Brain ◽

Network Properties ◽

Brain States ◽

Graph Theory Analysis ◽

Stn Dbs ◽

Deep Brain

Background: Neuronal loss in Parkinson’s Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored.Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD.Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states.Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state – STN-DBS was negatively correlated with network assortativity.Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.

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Systemic Effects of Selection History on Learned Ignoring

10.31234/osf.io/zca2b ◽

2021 ◽

Author(s):

Andy Jeesu Kim ◽

Brian A. Anderson

Keyword(s):

Eye Movements ◽

Reaction Time ◽

Young Adult ◽

High Probability ◽

Time Course ◽

Systemic Effects ◽

Reduced Frequency ◽

Selection History ◽

Adult Participants ◽

Task Irrelevant

Despite our best intentions, physically salient but entirely task-irrelevant stimuli can sometimes capture our attention. With learning, it is possible to more efficiently ignore such stimuli, although specifically how the visual system accomplishes this remains to be clarified. Using a sample of young-adult participants, we examined the time course of eye movements to targets and distractors. We replicate a reduced frequency of eye movements to the distractor when appearing in a location at which distractors are frequently encountered. This reduction was observed even for the earliest saccades, when selection tends to be most stimulus-driven. When the distractor appeared at the high-probability location, saccadic reaction time was slowed specifically for distractor-going saccades, suggesting a slowing of priority accumulation at this location. In the event that the distractor was fixated, disengagement from the distractor was also faster when it appeared in the high-probability location. Both proactive and reactive mechanisms of distractor suppression work together to minimize attentional capture by frequently-encountered distractors.

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