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A novel method for tri-clustering dynamic functional network connectivity (dFNC) identifies significant schizophrenia effects across multiple states in distinct subgroups of individuals [article]

Md Abdur Rahaman, Eswar Damaraju, Jessica Turner, Theo G.M. van Erp, Daniel Mathalon, Jatin Vaidya, Bryon Muller, Godfrey D Pearlson, Vince D. Calhoun
2020 bioRxiv   pre-print
State-of-the-art methods for analyzing dynamic functional network connectivity (dFNC) subdivide the entire time course into several (possibly overlapping) connectivity states (i.e., sliding window clusters  ...  Results: Resulting tri-clusters show significant differences between schizophrenia (SZ) and healthy control (HC) in distinct brain regions.  ...  In our study, the tri-clusters are more precisely sorted for a subset of subjects showing minimum heterogeneity in their connectivity pattern and show significant group differences across multiple brain  ... 
doi:10.1101/2020.08.06.239152 fatcat:y3ufx554zrfhfe3ko7yg7ll4wi

Statelets: high dimensional predominant shapes in dynamic functional network connectivity [article]

Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Sergey M. Plis, Vince Calhoun
2020 bioRxiv   pre-print
Here, we seek an improved understanding of these connectivity states and the mechanism through which their dynamics vary across individuals.  ...  Dynamic functional network connectivity (dFNC) analysis has been attracting interest over the past years by elucidating crucial details of brain activation patterns in severe neurological or psychiatric  ...  We tried to address it in our summarization framework by capturing state shapes representation of all intrinsic subgroups.  ... 
doi:10.1101/2020.08.16.252999 fatcat:3quvhptuobgljdf3tca5jiu2ze

Search for schizophrenia and bipolar biotypes using functional network properties

Inés Fernández‐Linsenbarth, Álvaro Planchuelo‐Gómez, Rosa M. Beño‐Ruiz‐de‐la‐Sierra, Alvaro Díez, Antonio Arjona, Adela Pérez, Alberto Rodríguez‐Lorenzana, Pilar del Valle, Rodrigo Luis‐García, Guido Masciliano, Pedro Holgado‐Madera, Rafael Segarra‐Echevarría (+6 others)
2021 Brain and Behavior  
The other cluster of patients did not show significant differences with controls in the functional network properties.  ...  These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.  ...  EEG network parameters A significant effect of the group was found for all variables of the functional network (4.44 < F < 62.48; .01 > p > .0001).  ... 
doi:10.1002/brb3.2415 pmid:34758203 pmcid:PMC8671779 fatcat:km64r627wnaw5egvcfrirkukyu

Dissecting psychiatric spectrum disorders by generative embedding

Kay H. Brodersen, Lorenz Deserno, Florian Schlagenhauf, Zhihao Lin, Will D. Penny, Joachim M. Buhmann, Klaas E. Stephan
2014 NeuroImage: Clinical  
model of network dynamics such as DCM.  ...  model of network dynamics such as DCM.  ...  the CRPP 'Multiple Sclerosis' (KES), and the René and Susanne Braginsky Foundation (KES).  ... 
doi:10.1016/j.nicl.2013.11.002 pmid:24363992 pmcid:PMC3863808 fatcat:geo3xr4bmjddzd6ib4kfvhpmoe

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity

Siyi Li, Na Hu, Wenjing Zhang, Bo Tao, Jing Dai, Yao Gong, Youguo Tan, Duanfang Cai, Su Lui
2019 Frontiers in Psychiatry  
Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial.  ...  The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates.  ...  FIGURE 2 | 2 Meta-analysis of abnormal resting-state function connectivity (rsFC) in schizophrenia.  ... 
doi:10.3389/fpsyt.2019.00482 pmid:31354545 pmcid:PMC6639431 fatcat:5xmtzwbvsnfarkmf4utkvmqo3e

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis

Paola Valsasina, Milagros Hidalgo de la Cruz, Massimo Filippi, Maria A. Rocca
2019 Frontiers in Neuroscience  
Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions.  ...  Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism.  ...  In psychiatric diseases, disruption of fronto-parietal network connectivity seems to be the common fingerprint across distinct forms of pathology (Baker et al., 2019) .  ... 
doi:10.3389/fnins.2019.00618 pmid:31354402 pmcid:PMC6636554 fatcat:lezpk4273ne6jma6z45k6bsvii

Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders

Gustavo Deco, Morten L. Kringelbach
2014 Neuron  
and function of the healthy brain.  ...  The study of human brain networks with in vivo neuroimaging has given rise to the field of connectomics, furthered by advances in network science and graph theory informing our understanding of the topology  ...  The research reported herein was supported by the Brain Network Recovery Group through the James S. McDonnell Foundation.  ... 
doi:10.1016/j.neuron.2014.08.034 pmid:25475184 fatcat:kx7rohtyljc7heuahmvoqyorgq

Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging

Yuhui Du, Zening Fu, Vince D. Calhoun
2018 Frontiers in Neuroscience  
We survey the state-of-the-art FC analysis methods including widely used static functional connectivity (SFC) and more recently proposed dynamic functional connectivity (DFC).  ...  Temporal correlations among regions of interest (ROIs), data-driven spatial network and functional network connectivity (FNC) are often computed to reflect SFC from different angles.  ...  Science Foundation of China (Grant No. 61703253, to YD) and Natural Science Foundation of Shanxi Province (Grant No. 2016021077, to YD).  ... 
doi:10.3389/fnins.2018.00525 pmid:30127711 pmcid:PMC6088208 fatcat:b7hdtmrz4vehlhjw4fo2bewhwq

Approaching a network connectivity-driven classification of the psychosis continuum: a selective review and suggestions for future research

André Schmidt, Vaibhav A. Diwadkar, Renata Smieskova, Fabienne Harrisberger, Undine E. Lang, Philip McGuire, Paolo Fusar-Poli, Stefan Borgwardt
2015 Frontiers in Human Neuroscience  
A critical point is that brain connectivity abnormalities, including altered resting state connectivity within the fronto-parietal (FP) network, are already observed in non-help-seeking individuals with  ...  Brain changes in schizophrenia evolve along a dynamic trajectory, emerging before disease onset and proceeding with ongoing illness.  ...  A recent resting state fMRI network study in chronic patients identified a non-linear measure of functional connectivity, akin to mutual information.  ... 
doi:10.3389/fnhum.2014.01047 pmid:25628553 pmcid:PMC4292722 fatcat:ezkeipbmebhxnlcukngpslzwnq

Neural networks of aggression: ALE meta-analyses on trait and elicited aggression

Ting Yat Wong, Azah Sid, Tobias Wensing, Simon B. Eickhoff, Ute Habel, Ruben C. Gur, Thomas Nickl-Jockschat
2018 Brain Structure and Function  
resting-state functional connectivity (RSFC) to further characterize their physiological functions.  ...  Finally, we obtained a data-driven functional characterization of the ensuing clusters and their networks.  ...  Compliance with Ethical Standards The authors declare that they have no existing conflict of interest. 31  ... 
doi:10.1007/s00429-018-1765-3 pmid:30291479 fatcat:ptac6kbfvvbpfoj5jtyg4dwkdq

Modern Views of Machine Learning for Precision Psychiatry [article]

Zhe Sage Chen, Prathamesh Kulkarni, Isaac R. Galatzer-Levy, Benedetta Bigio, Carla Nasca, Yu Zhang
2022 arXiv   pre-print
In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and  ...  Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment.  ...  Declaration of interests The authors declare no competing financial interests. References  ... 
arXiv:2204.01607v2 fatcat:coo557v2jzh6debycy3mhccfze

Large-Scale Brain Network Dynamics Supporting Adolescent Cognitive Control

D. B. Dwyer, B. J. Harrison, M. Yucel, S. Whittle, A. Zalesky, C. Pantelis, N. B. Allen, A. Fornito
2014 Journal of Neuroscience  
This literature implies that individual differences in cognitive control are determined either by activation or functional connectivity of CCN regions, deactivation or functional connectivity of DMN regions  ...  These results indicate that individual differences in adolescent cognitive control are not solely attributable to the functioning of any single region or network, but are instead dependent on a dynamic  ...  Subnetworks of functional connections showing statistically significant correlations ( p Ͻ 0.05, corrected) with the MSIT interference effect during task-related and resting-state conditions were identified  ... 
doi:10.1523/jneurosci.1634-14.2014 pmid:25319705 pmcid:PMC6705292 fatcat:jxhefubnyba4hkvztwngwdeahy

Better Than Mermaids and Stray Dogs? Subtyping Auditory Verbal Hallucinations and Its Implications for Research and Practice

Simon McCarthy-Jones, Neil Thomas, Clara Strauss, Guy Dodgson, Nev Jones, Angela Woods, Chris R. Brewin, Mark Hayward, Massoud Stephane, Jack Barton, David Kingdon, Iris E. Sommer
2014 Schizophrenia Bulletin  
We suggest other facets of AVH, including negative content and form (eg, commands), may be best treated as dimensional constructs that vary across subtypes.  ...  must not be sold in any format or medium without the formal permission of the copyright holders.  ...  The authors have declared that there are no conflicts of interest in relation to the subject of this study.  ... 
doi:10.1093/schbul/sbu018 pmid:24936087 pmcid:PMC4141311 fatcat:loaiu7jcp5ewjn6geiyzhyvc4e

Generalizable prediction of stimulus-independent, task-unrelated thought from functional brain networks [article]

Aaron Kucyi, Michael Esterman, James Capella, Allison Green, Mai Uchida, Joseph Biederman, John D.E. Gabrieli, Eve M Valera, Susan Whitfield-Gabrieli
2021 bioRxiv   pre-print
In three additional resting-state fMRI studies (total n=1,115), including healthy and ADHD populations, we demonstrated further prediction of SITUT (at modest effect sizes) defined using multiple trait-level  ...  Our findings suggest that SITUT is represented within a common pattern of brain network interactions across time scales, populations, and contexts.  ...  This work was completed in part using the Discovery cluster, supported by Northeastern University's Research Computing team.  ... 
doi:10.1101/2021.01.25.428126 fatcat:idb7sdh34jg2jhbqmxhz3xayyy

Computational neuroimaging strategies for single patient predictions

K.E. Stephan, F. Schlagenhauf, Q.J.M. Huys, S. Raman, E.A. Aponte, K.H. Brodersen, L. Rigoux, R.J. Moran, J. Daunizeau, R.J. Dolan, K.J. Friston, A. Heinz
2017 NeuroImage  
An alternative to machine learning, which tries to establish predictive links between features of the observed data and clinical variables, is the deployment of computational models for inferring on the  ...  This paper discusses the rationale behind a computational approach to neuroimaging-based single-subject inference, focusing on its potential for characterising disease mechanisms in individual subjects  ...  We acknowledge support by the René and Susanne Braginsky Foundation (KES), the University of Zurich (KES), the UZH Clinical Research Priority Programs (CRPP) "Molecular Imaging" (KES) and "Multiple Sclerosis  ... 
doi:10.1016/j.neuroimage.2016.06.038 pmid:27346545 fatcat:otpdvzdgrrdwtnkiv3kf3f4jlm
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