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Differential Covariance: A New Method to Estimate Functional Connectivity in fMRI.

• Authors : Lin, Tiger W. (AUTHOR); Chen, Yusi (AUTHOR); Bukhari, Qasim (AUTHOR)

Subjects: FUNCTIONAL connectivity; FUNCTIONAL magnetic resonance imaging; ARTIFICIAL neural networks

• Source: Neural Computation. Dec2020, Vol. 32 Issue 12, p2339-2371. 33p. 1 Color Photograph, 2 Charts, 14 Graphs.

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On the Search for Data-Driven and Reproducible Schizophrenia Subtypes Using Resting State fMRI Data From Multiple Sites.

• Authors : Krohne, Lærke Gebser (AUTHOR); Hansen, Ingeborg Helbech (AUTHOR); Madsen, Kristoffer H. (AUTHOR)

Subjects: SYMPTOMS; FUNCTIONAL connectivity; PEOPLE with schizophrenia

• Source: Neural Computation. Sep2024, Vol. 36 Issue 9, p1799-1831. 33p.

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Multi-Input, Multi-Output Neuronal Mode Network Approach to Modeling the Encoding Dynamics and Functional Connectivity of Neural Systems.

• Authors : Geng, Kunling (AUTHOR); Shin, Dae C. (AUTHOR); Song, Dong (AUTHOR)

Subjects: ESTIMATION bias; FUNCTIONAL analysis; EPISTOLARY fiction

• Source: Neural Computation. Jul2019, Vol. 31 Issue 7, p1327-1355. 29p. 3 Diagrams, 1 Chart, 8 Graphs.

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Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis.

• Authors : Jun-ichiro Hirayama; Takeshi Ogawa; Hyvärinen, Aapo

Subjects: BLIND source separation; CLUSTER analysis (Statistics); MAGNETOENCEPHALOGRAPHY

• Source: Neural Computation. 2015, Vol. 27 Issue 7, p1373-1404. 32p. 2 Diagrams, 9 Graphs.

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Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach.

• Authors : Seif Eldawlatly; Rong Jin; Karim G. Oweiss

Subjects: NEURAL transmission; NERVOUS system; NEURONS

• Source: Neural Computation. Feb2009, Vol. 21 Issue 2, p450-477. 28p. 2 Diagrams, 9 Graphs.

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Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity.

• Authors : Okatan, Murat; Wilson, Matthew A.; Brown, Emery N.

Subjects: NEURONS; NERVOUS system; NEUROSCIENCES

• Source: Neural Computation. Sep2005, Vol. 17 Issue 9, p1927-1961. 35p.

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Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis.

• Authors : Hirayama J; Advanced Telecommunications Research Institute International (ATR), Soraku-gun, Kyoto, 619-0288, Japan .; Ogawa T

• Source: Neural computation [Neural Comput] 2015 Jul; Vol. 27 (7), pp. 1373-404. Date of Electronic Publication: 2015 May 14.Publisher: MIT Press Country of Publication: United States NLM ID: 9426182 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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Identifying functional connectivity in large-scale neural ensemble recordings: a multiscale data mining approach.

• Authors : Eldawlatly S; Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA. ; Jin R

Subjects: Models, Neurological*; Action Potentials/Action Potentials/Action Potentials/*physiology ; Neurons/Neurons/Neurons/*physiology

• Source: Neural computation [Neural Comput] 2009 Feb; Vol. 21 (2), pp. 450-77.Publisher: MIT Press Country of Publication: United States NLM ID: 9426182 Publication Model: Print Cited Medium: Print ISSN: 0899-7667 (Print)

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The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI.

• Authors : Churchill, Nathan W.; Madsen, Kristoffer; Mørup, Morten

Subjects: MAGNETIC resonance imaging of the brain; BRAIN physiology; GAUSSIAN mixture models

• Source: Neural Computation. 2016, Vol. 28 Issue 10, p2050-2090. 41p. 1 Diagram, 1 Chart, 10 Graphs.

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Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings.

• Authors : Das, Anup; Sampson, Aaron L.; Lainscsek, Claudia

Subjects: BRAIN imaging; SLEEP spindles; NON-REM sleep

• Source: Neural Computation. Mar2017, Vol. 29 Issue 3, p603-642. 40p. 7 Diagrams, 1 Chart, 7 Graphs.

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