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Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis

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      Abstract

      Functional magnetic resonance imaging (fMRI) techniques have contributed significantly to our understanding of brain function. Current methods are based on the analysis of gradual and continuous changes in the brain blood oxygenated level dependent (BOLD) signal. Departing from that approach, recent work has shown that equivalent results can be obtained by inspecting only the relatively large amplitude BOLD signal peaks, suggesting that relevant information can be condensed in discrete events. This idea is further explored here to demonstrate how brain dynamics at resting state can be captured just by the timing and location of such events, i.e., in terms of a spatiotemporal point process. The method allows, for the first time, to define a theoretical framework in terms of an order and control parameter derived from fMRI data, where the dynamical regime can be interpreted as one corresponding to a system close to the critical point of a second order phase transition. The analysis demonstrates that the resting brain spends most of the time near the critical point of such transition and exhibits avalanches of activity ruled by the same dynamical and statistical properties described previously for neuronal events at smaller scales. Given the demonstrated functional relevance of the resting state brain dynamics, its representation as a discrete process might facilitate large-scale analysis of brain function both in health and disease.

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      Most cited references 47

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      Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

      The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.
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        Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.

        Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.
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          Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI.

          Recent functional imaging studies have revealed coactivation in a distributed network of cortical regions that characterizes the resting state, or default mode, of the human brain. Among the brain regions implicated in this network, several, including the posterior cingulate cortex and inferior parietal lobes, have also shown decreased metabolism early in the course of Alzheimer's disease (AD). We reasoned that default-mode network activity might therefore be abnormal in AD. To test this hypothesis, we used independent component analysis to isolate the network in a group of 13 subjects with mild AD and in a group of 13 age-matched elderly controls as they performed a simple sensory-motor processing task. Three important findings are reported. Prominent coactivation of the hippocampus, detected in all groups, suggests that the default-mode network is closely involved with episodic memory processing. The AD group showed decreased resting-state activity in the posterior cingulate and hippocampus, suggesting that disrupted connectivity between these two regions accounts for the posterior cingulate hypometabolism commonly detected in positron emission tomography studies of early AD. Finally, a goodness-of-fit analysis applied at the individual subject level suggests that activity in the default-mode network may ultimately prove a sensitive and specific biomarker for incipient AD.
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            Author and article information

            Affiliations
            1simpleDepartamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires Buenos Aires, Argentina
            2simpleDepartment of Neurology and Brain Imaging Center, Goethe-University Frankfurt Frankfurt am Main, Germany
            3simpleConsejo Nacional de Investigaciones Científicas y Tecnológicas Buenos Aires, Argentina
            4simpleDepartamento de Matemática y Ciencias, Universidad de San Andrés Buenos Aires, Argentina
            5simpleFacultad de Ciencias Médicas, Universidad Nacional de Rosario Rosario, Argentina
            6simpleDavid Geffen School of Medicine, University of California Los Angeles Los Angeles, CA, USA
            Author notes

            Edited by: Zbigniew R. Struzik, The University of Tokyo, Japan

            Reviewed by: Riccardo Barbieri, Massachusetts Institute of Technology, USA; Masanori Shimono, Indiana University, USA

            *Correspondence: Dante R. Chialvo, Department of Physiology, Northwestern University, 303 East Chicago Avenue, Chicago, IL 60611, USA. e-mail: dchialvo@ 123456ucla.edu

            This article was submitted to Frontiers in Fractal Physiology, a specialty of Frontiers in Physiology.

            Journal
            Front Physiol
            Front Physiol
            Front. Physio.
            Frontiers in Physiology
            Frontiers Research Foundation
            1664-042X
            04 January 2012
            08 February 2012
            2012
            : 3
            3274757
            22347863
            10.3389/fphys.2012.00015
            Copyright © 2012 Tagliazucchi, Balenzuela, Fraiman and Chialvo.

            This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.

            Counts
            Figures: 7, Tables: 1, Equations: 2, References: 61, Pages: 12, Words: 9236
            Categories
            Physiology
            Original Research

            Anatomy & Physiology

            criticality, point processes, fmri, brain dynamics

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