Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits.

Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Research Abstract Details 

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Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Abstract Text:

Ransom Winder,Carlos R Cortes,James A Reggia,M-A Tagamets,

Although progress has been made in relating neuronal events to changes in brain metabolism and blood flow, the interpretation of functional neuroimaging data in terms of the underlying brain circuits is still poorly understood. Computational modeling of connection patterns both among and within regions can be helpful in this interpretation. We present a neural network model of the ventral visual pathway and its relevant functional connections. This includes a new learning method that adjusts the magnitude of interregional connections in order to match experimental results of an arbitrary functional magnetic resonance imaging (fMRI) data set. We demonstrate that this method finds the appropriate connection strengths when trained on a model system with known, randomly chosen connection weights. We then use the method for examining fMRI results from a one-back matching task in human subjects, both healthy and those with schizophrenia. The results discovered by the learning method support previous findings of a disconnection between left temporal and frontal cortices in the group with schizophrenia and a concomitant increase of right-sided temporo-frontal connection strengths. We then demonstrate that the disconnection may be explained by reduced local recurrent circuitry in frontal cortex. This method extends currently available methods for estimating functional connectivity from human imaging data by including both local circuits and features of interregional connections, such as topography and sparseness, in addition to total connection strengths. Furthermore, our results suggest how fronto-temporal functional disconnection in schizophrenia can result from reduced local synaptic connections within frontal cortex rather than compromised interregional connections.

Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Publishing Authors By Initials

R Winder,CR Cortes,JA Reggia,MA Tagamets,

For similar nervous system: neural pathways research abstracts see: nervous system: neural pathways research

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Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: NeuroImage

VOLUME: 34

Page Numbers: 1093-107

Journal Abbreviation: Neuroimage

ISSN: 1053-8119

DAY: 28

MONTH: 11

YEAR: 2006

Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Information

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LANGUAGE: eng

NlmUniqueID: 9215515

Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Keywords Mesh Terms:

KEYWORDS: Neural Pathways

MESH TERMS: physiology

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Grant and Affiliation Information for Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits.

AFFILIATION: Department of Computer Science, University of Maryland at College Park, MD, USA.

Country: United States

AGENCY: United States NINDS

GRANT: R01NS35460

ACRONYM: NS

MEDLINETA: Neuroimage

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