Article
Computer Science, Artificial Intelligence
Luyao Wang, Jian Zhang, Tiantian Liu, Duanduan Chen, Dikun Yang, Ritsu Go, Jinglong Wu, Tianyi Yan
Summary: This study investigates the relationship between resting state and task state using electroencephalography (EEG) data. The findings suggest that connectivity networks constructed in the time and frequency domains can predict neural activation and spectral power, indicating intrinsic organization across the two states and different levels of neuronal activation reflected in different domains.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Eric Lacosse, Klaus Scheffler, Gabriele Lohmann, Georg Martius
Summary: Cognitive fMRI research aims to predict task activation from rsfMRI using machine learning methods, but most approaches underperform against baseline models. A proposed modification based on single-vertex approach improves performance, addressing this issue. Further investigation into individual prediction scores and behavioral differences is conducted based on empirical observations.
SCIENTIFIC REPORTS
(2021)
Article
Neurosciences
Ruben Sanchez-Romero, Takuya Ito, Ravi D. Mill, Stephen Jose Hanson, Michael W. Cole
Summary: Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. These models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models.
Article
Engineering, Biomedical
Francesca Miraglia, Fabrizio Vecchio, Francesca Alu, Alessandro Orticoni, Elda Judica, Maria Cotelli, Paolo Maria Rossini
Summary: The study aimed to investigate the brain rhythms characteristics in resting state condition before a visuo-motor task in healthy adults. The results showed a negative correlation between brain activity and reaction times to the task, suggesting a potential tool for exploring brain state characterization for task performance.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Peiying Liu, Gongkai Liu, Marco C. Pinho, Zixuan Lin, Binu P. Thomas, Melissa Rundle, Denise C. Park, Judy Huang, Babu G. Welch, Hanzhang Lu
Summary: The study optimized and evaluated a resting-state BOLD functional MRI technique to measure cerebrovascular reactivity and demonstrated its relationship to neurosurgical treatment. The results showed that the technique provided a task-free method to assess cerebrovascular reserve and depicted the treatment effect of revascularization surgery in patients with Moyamoya disease, comparable to the reference standard of CO2 inhalation MRI.
Article
Behavioral Sciences
Zaira Romeo, Dante Mantini, Eugenia Durgoni, Laura Passarini, Francesca Meneghello, Marco Zorzi
Summary: Localized brain damage can lead to specific cognitive deficits, while stroke lesions can also alter the functional connectivity of intrinsic brain networks, impacting behavior. By analyzing the relationship between EEG patterns and cognitive performance, researchers identified specific EEG frequency bands associated with distinct cognitive impairments.
Article
Anatomy & Morphology
Claire Deshayes, Veronique Paban, Marie-Helene Ferrer, Beatrice Alescio-Lautier, Caroline Chambon
Summary: Through studying cognitive function and brain resting functional connectivity, this research explored the definition of creative potential. The analysis showed distinct differences in cognitive function and brain connectivity between groups with high and low creative potential.
BRAIN STRUCTURE & FUNCTION
(2021)
Article
Neurosciences
Liandong Lin, Da Chang, Donghui Song, Yiran Li, Ze Wang
Summary: This study investigates the relationship between brain entropy during resting state and brain activations and deactivations during task performance. The results show that lower brain entropy at rest is associated with stronger activations and deactivations in brain regions engaged by the tasks. Higher workload leads to more extensive negative correlations between resting brain entropy and task activations. These findings suggest that resting brain activity can predict task-related brain activity and may facilitate both task activations and deactivations.
Article
Neurosciences
Shachar Gal, Yael Coldham, Niv Tik, Michal Bernstein-Eliav, Ido Tavor
Summary: The search for an ideal approach to investigate functional connections in the human brain is a challenge for neuroscience. Recent studies have found that using naturalistic stimuli to collect functional connectivity data predicts cognitive and emotional scores more accurately than using resting-state data. Furthermore, activation maps predicted using naturalistic stimuli are better predictors of individual intelligence scores than those predicted using resting-state data.
Article
Neurosciences
Kerem Kemik, Emel Ada, Berrin Cavusoglu, Cansu Aykac, Derya Durusu Emek-Savas, Gorsev Yener
Summary: This study investigated neural activity changes in patients with Amnestic mild cognitive impairment (aMCI) using functional magnetic resonance imaging (fMRI). The results showed alterations in the visual network in resting-state and task-based fMRI, indicating that these changes may serve as early biomarkers for aMCI.
CNS NEUROSCIENCE & THERAPEUTICS
(2023)
Article
Psychology, Multidisciplinary
Sonia Di Tella, Matteo De Marco, Francesca Baglio, Maria Caterina Silveri, Annalena Venneri
Summary: This study investigated the impact of cognitive reserve on functional connectivity in patients with Parkinson's disease and found that individuals with low cognitive reserve had weaker functional connectivity in the prefrontal cortex and basal ganglia. They also exhibited downregulation of attentional control networks and compensatory upregulation of medial frontal regions. These findings enhance our understanding of the mechanisms underlying cognitive impairments in Parkinson's disease.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Neurosciences
Xin Hao, Taicheng Huang, Yiying Song, Xiangzhen Kong, Jia Liu
Summary: The study reveals age-related changes in the navigation network organization, with increasing modularity under resting-state and increasing flexibility under task-state. Task-modulated FC changes were found to be greater in adults than in children, suggesting differences in network organization between age groups during tasks.
Article
Neurosciences
Nisha Chetana Sastry, Dipanjan Roy, Arpan Banerjee
Summary: This study investigates the temporal stability of dynamic functional connectivity (dFC) in resting-state, movie-viewing, and sensorimotor tasks across the lifespan. The results demonstrate differences in temporal stability between task conditions and age groups, suggesting an age-related decline in the stability of neurocognitive networks.
Article
Clinical Neurology
Jinxian Deng, Boxin Sun, Voyko Kavcic, Mingyan Liu, Bruno Giordani, Tongtong Li
Summary: This study used resting-state EEG to develop a soft discrimination model that showed high sensitivity and reliability for detecting MCI and predicting individuals at risk of MCI before clinical symptoms occur.
ALZHEIMERS & DEMENTIA
(2023)
Article
Geriatrics & Gerontology
Cheshire Hardcastle, Hanna K. Hausman, Jessica N. Kraft, Alejandro Albizu, Andrew O'Shea, Emanuel M. Boutzoukas, Nicole D. Evangelista, Kailey Langer, Emily J. Van Etten, Pradyumna K. Bharadwaj, Hyun Song, Samantha G. Smith, Eric Porges, Steven T. DeKosky, Georg A. Hishaw, Samuel S. Wu, Michael Marsiske, Ronald Cohen, Gene E. Alexander, Adam J. Woods
Summary: Prior randomized control trials have demonstrated that cognitive training interventions lead to improved task performance, functioning, and reduced dementia risk in healthy older adults. This study aimed to investigate the changes in resting state network connectivity after cognitive training and its relation to improvement in task performance. The results showed that the frontoparietal control network strengthened after multidomain cognitive training interventions, and this network may underlie improvements in divided attention and speed-of-processing tasks.
Article
Neurosciences
Ruben Sanchez-Romero, Michael W. Cole
Summary: Cognition and behavior are influenced by interactions within brain networks, emphasizing the importance of causal interactions in studying brain function. Traditional bivariate methods for functional connectivity analysis lack consideration of confounders, leading to false positives. A new combined FC method (CombinedFC) was proposed to incorporate both simple bivariate and partial correlation measures, providing more valid causal inferences and improving upon existing methods.
JOURNAL OF COGNITIVE NEUROSCIENCE
(2021)
Article
Neurosciences
Marjolein Spronk, Brian P. Keane, Takuya Ito, Kaustubh Kulkarni, Jie Lisa Ji, Alan Anticevic, Michael W. Cole
Summary: This study found that while the whole-brain resting-state functional network organization is highly similar across individuals with various mental disorders, subtle differences in network graph distance can predict diagnosis. The results suggest a need to reevaluate neurocognitive theories of mental illness, with a focus on subtle functional brain network changes.
Article
Neurosciences
Michael W. Cole, Takuya Ito, Carrisa Cocuzza, Ruben Sanchez-Romero
Summary: Resting-state functional connectivity provides insights into brain network organization, but the functional importance of task-related changes remains unclear. Task-state functional connectivity can predict cognitive task activations better, driven by individual-specific functional connectivity patterns. These findings suggest task-related changes play a role in reshaping brain network organization and altering neural activity flow during task performance.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Neurosciences
Matthew F. Singh, Anxu Wang, Michael Cole, ShiNung Ching, Todd S. Braver
Summary: This study introduces a method to improve estimation of task-evoked brain activity by filtering out the propagation of previous activity from the BOLD signal using MINDy models. Results demonstrate that this simple operation significantly increases the statistical power and temporal precision of estimated group-level effects, while also enhancing the similarity of neural activation profiles and prediction accuracy of individual differences in behavior.
Article
Multidisciplinary Sciences
Takuya Ito, Guangyu Robert Yang, Patryk Laurent, Douglas H. Schultz, Michael W. Cole
Summary: The authors built a task-performing neural network model based on human brain data, using recent advances in functional connectivity research. They verified the importance of conjunction hubs in flexible cognitive computations.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Ravi D. Mill, Julia L. Hamilton, Emily C. Winfield, Nicole Lalta, Richard H. Chen, Michael W. Cole
Summary: Understanding how cognitive task behavior is generated by brain network interactions is a central question in neuroscience. This study presents a novel network modeling approach using noninvasive functional neuroimaging data to capture neural signatures of task information with high spatial and temporal precision. The approach combines MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA) to dynamically decode task information in the human brain. The modeling approach, called dynamic activity flow modeling, then simulates the flow of task-evoked activity over resting-state functional connections, providing insights into the network processes underlying sensory-motor information flow in the brain.
Article
Neurosciences
Brian P. Keane, Bart Krekelberg, Ravi D. Mill, Steven M. Silverstein, Judy L. Thompson, Megan R. Serody, Deanna M. Barch, Michael W. Cole
Summary: A study using functional magnetic resonance imaging (fMRI) found that there are differences in brain network activity during visual shape completion between individuals with schizophrenia and other groups, which may be related to abnormal attention-related feedback signals.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2023)
Article
Neurosciences
Takuya Ito, John D. Murray
Summary: The study reveals the computational and functional architectures of human cognition by characterizing the geometry and topography of multitask representations in the human cortex using functional magnetic resonance imaging. The results show that multitask representations are organized along a gradient from sensory to association to motor processing, and the dimensions of these representations undergo compression-then-expansion. Neural network models trained in a rich learning regime replicate the compression-then-expansion organization observed in empirical data, suggesting that optimized representations and noise robustness play a crucial role in multitask cognition.
NATURE NEUROSCIENCE
(2023)
Article
Biology
Kai Hwang, James M. Shine, Michael W. Cole, Evan Sorenson
Summary: Thalamocortical interaction plays a vital role in supporting various cognitive abilities. This study explores the organization of task-evoked thalamic activity and its connection with cortical systems. The results demonstrate task-specific activity patterns in the thalamus that overlap with cortical network hubs. A data-driven thalamocortical model accurately predicts cortical task activity, outperforming models built on other brain regions. Lesions to the multi-task thalamic hub regions impair task activity prediction, consistent with neuropsychological impairments in human patients with focal thalamic lesions.
Article
Behavioral Sciences
Angela M. Dietsch, Ross M. Westemeyer, Douglas H. Schultz
Summary: By administering precisely formulated taste stimuli to healthy adults, researchers found that brain activity in regions relevant to swallowing can be enhanced. These findings are critical for understanding the effects of taste on brain activity and swallowing function, as well as for improving recovery for individuals with swallowing disorders.
BRAIN AND BEHAVIOR
(2023)
Article
Neurosciences
Ruben Sanchez-Romero, Takuya Ito, Ravi D. Mill, Stephen Jose Hanson, Michael W. Cole
Summary: Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. These models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models.
Meeting Abstract
Neurosciences
Brian Keane, Bart Krekelberg, Ravi Mill, Steven Silverstein, Judith Thompson, Megan Serody, Deanna Barch, Michael Cole
BIOLOGICAL PSYCHIATRY
(2022)
