Functional Clustering: Identifying Strongly Interactive Brain Regions in Neuroimaging Data
@article{Tononi1998FunctionalCI, title={Functional Clustering: Identifying Strongly Interactive Brain Regions in Neuroimaging Data}, author={Giulio Tononi and Anthony Randal Mcintosh and D. P. Russell and Gerald M. Edelman}, journal={NeuroImage}, year={1998}, volume={7}, pages={133-149} }
Brain imaging data are generally used to determine which brain regions are most active in an experimental paradigm or in a group of subjects. Theoretical considerations suggest that it would also be of interest to know which set of brain regions are most interactive in a given task or group of subjects. A subset of regions that are much more strongly interactive among themselves than with the rest of the brain is called here a functional cluster. Functional clustering can be assessed by…
Figures and Tables from this paper
273 Citations
Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions
- BiologyIPMI
- 2013
This work introduces a new group-level brain mapping strategy to differentiate many regions reflecting the variety of brain network configurations observed in the population, using a dictionary-learning formulation that can be solved efficiently with on-line algorithms, scaling to arbitrary large datasets.
Neural networks approach to clustering of activity in fMRI data
- Computer ScienceIEEE Transactions on Medical Imaging
- 2005
Exploiting the intracluster correlations, it is shown that regions of substantial correlation with an external stimulus can be unambiguously separated from other activity.
An efficient method for effective connectivity of brain regions
- Biology
- 2012
The authors present a novel and highly efficient modeling approach to detect effective connectivity of the brain regions based on multivariate autoregressive (MAR) model, which allows for the identification of effective connectivity by combining graphical modeling methods with the concept of Granger causality.
Connectivity-based parcellation of putamen region using resting state fMRI
- Computer Science
- 2015
A novel framework for parcellation of a brain region into functional subunits based on their connectivity patterns with other reference brain regions is presented, which takes the prior neurological information into consideration and aims at finding spatially continuous and functionally consistent subregions in a given brain region.
Functional connectivity analysis of fMRI data based on regularized multiset canonical correlation analysis
- Computer ScienceJournal of Neuroscience Methods
- 2011
Information Processing Architecture of Functionally Defined Clusters in the Macaque Cortex
- Biology, PsychologyThe Journal of Neuroscience
- 2012
Together, the data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture, and shows how this architecture contributes to the global organizational principles of both functional specialization and integration.
A Connectivity-Based Method for Defining Regions-of-Interest in fMRI Data
- BiologyIEEE Transactions on Image Processing
- 2009
A new methodology for defining brain regions-of-interset (ROIs) in functional magnetic resonance imaging (fMRI) data that relies on a spatially regularized canonical correlation analysis for identifying maximally correlated signals.
A Spatio-temporal Model for fMRI Data
- Biology
- 2004
This paper presents a spatio-temporal point process model approach for fMRI data where the temporal and spatial activation are modelled simultaneously and discusses statistical inference in the model based on mean value, variance and covariance.
Adaptive integration of local region information to detect fine-scale brain activity patterns
- Psychology
- 2008
Experiments with simulated and real fMRI data demonstrate that the proposed method dramatically increases the sensitivity of detection of fine-scale brain activity patterns which contain the subtle information about experimental conditions.
References
SHOWING 1-10 OF 45 REFERENCES
Spatial Pattern Analysis of Functional Brain Images Using Partial Least Squares
- PsychologyNeuroImage
- 1996
Partial least squares serves as an important extension by extracting new information from imaging data that is not accessible through other currently used univariate and multivariate image analysis tools.
Network analysis of cortical visual pathways mapped with PET
- PsychologyThe Journal of neuroscience : the official journal of the Society for Neuroscience
- 1994
A network analysis was performed on data obtained from a PET study that examined both the changes in regional cerebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot- location matching) task.
Functional topography: multidimensional scaling and functional connectivity in the brain.
- PsychologyCerebral cortex
- 1996
A simple variant of multidimensional scaling (principal coordinates analysis; Gower, 1966) that uses functional connectivity as its metric is described that represents a descriptive characterization of anatomically distributed changes in the brain that reveals the structure of corticocortical interactions in terms of functional correlations.
A measure for brain complexity: relating functional segregation and integration in the nervous system.
- BiologyProceedings of the National Academy of Sciences of the United States of America
- 1994
A measure, called neural complexity (CN), that captures the interplay between functional segregation and functional integration in brains of higher vertebrates and may prove useful in analyzing complexity in other biological domains such as gene regulation and embryogenesis.
A complexity measure for selective matching of signals by the brain.
- Psychology, Computer ScienceProceedings of the National Academy of Sciences of the United States of America
- 1996
A related statistical measure, matching complexity (CM), which reflects the change in CN that occurs after a neural system receives signals from the environment, and is shown to be low when the intrinsic connectivity of a simulated cortical area is randomly organized.
Statistical parametric maps in functional imaging: A general linear approach
- Mathematics
- 1994
Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of…
Principles of human brain organization derived from split-brain studies
- Psychology, MedicineNeuron
- 1995
Structural equation modeling and its application to network analysis in functional brain imaging
- Biology
- 1994
It is suggested that neural covariances may be a more accurate way to examine the dynamic functional organization of the central nervous system.
Characterising the complexity of neuronal interactions
- Computer Science
- 1995
This work addresses the complexity of neuronal interactions, the nature of this complexity and how it can be characterised in real neurophysiological processes with a measure of complexity based on the profile of entropies of different sized regions of the brain.
Changes in limbic and prefrontal functional interactions in a working memory task for faces.
- Psychology, BiologyCerebral cortex
- 1996
Regional cerebral blood flow, measured with positron emission tomography, was used to identify brain regions that play a special role(s) in a working memory task for faces, suggesting recruitment of some of the same circuits primarily involved in face perception.