Brain noise is task dependent and region specific.

The emerging organization of anatomical and functional connections during human brain development is thought to facilitate global integration of information. Recent empirical and computational studies have shown that this enhanced capacity for information processing enables a diversified dynamic repertoire that manifests in neural activity as irregularity and noise. However, transient functional networks unfold over multiple time, scales and the embedding of a particular region depends not only on development, but also on the manner in which sensory and cognitive systems are engaged. Here we show that noise is a facet of neural activity that is also sensitive to the task context and is highly region specific. Children (6-16 yr) and adults (20-41 yr) performed a one-back face recognition task with inverted and upright faces. Neuromagnetic activity was estimated at several hundred sources in the brain by applying a beamforming technique to the magnetoencephalogram (MEG). During development, neural activity became more variable across the whole brain, with most robust increases in medial parietal regions, such as the precuneus and posterior cingulate cortex. For young children and adults, activity evoked by upright faces was more variable and noisy compared with inverted faces, and this effect was reliable only in the right fusiform gyrus. These results are consistent with the notion that upright faces engender a variety of integrative neural computations, such as the relations among facial features and their holistic constitution. This study shows that transient changes in functional integration modulated by task demand are evident in the variability of regional neural activity.

[1]  Natasa Kovacevic,et al.  Differential Maturation of Brain Signal Complexity in the Human Auditory and Visual System , 2009, Frontiers in human neuroscience.

[2]  Kaustubh Supekar,et al.  Development of Large-Scale Functional Brain Networks in Children , 2009, NeuroImage.

[3]  O. Sporns,et al.  Key role of coupling, delay, and noise in resting brain fluctuations , 2009, Proceedings of the National Academy of Sciences.

[4]  Jonathan D. Power,et al.  Functional Brain Networks Develop from a “Local to Distributed” Organization , 2009, PLoS Comput. Biol..

[5]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[6]  Winfried Schlee,et al.  Top-Down Modulation of the Auditory Steady-State Response in a Task-Switch Paradigm , 2008, Front. Hum. Neurosci..

[7]  Viktor K. Jirsa,et al.  Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire , 2008, PLoS Comput. Biol..

[8]  O. Sporns,et al.  Mapping the Structural Core of Human Cerebral Cortex , 2008, PLoS biology.

[9]  Natasa Kovacevic,et al.  Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development , 2008, PLoS Comput. Biol..

[10]  Margot J. Taylor,et al.  Face processing in adolescents with and without epilepsy. , 2008, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[11]  Lester Melie-García,et al.  Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory , 2008, NeuroImage.

[12]  E. Hulata,et al.  Coemergence of regularity and complexity during neural network development , 2007, Developmental neurobiology.

[13]  S. Sigurdsson,et al.  Reliability of quantitative EEG features , 2007, Clinical Neurophysiology.

[14]  Elizabeth W. Pang,et al.  Event-related beamforming: A robust method for presurgical functional mapping using MEG , 2007, Clinical Neurophysiology.

[15]  Olaf Sporns,et al.  Network structure of cerebral cortex shapes functional connectivity on multiple time scales , 2007, Proceedings of the National Academy of Sciences.

[16]  Kathleen M. Thomas,et al.  Neural Bases of Cognitive Development , 2007 .

[17]  Flavio M. de Paula,et al.  Developmental differences in the neural bases of the face inversion effect show progressive tuning of face-selective regions to the upright orientation , 2007, NeuroImage.

[18]  Steven L. Bressler,et al.  The Role of Neural Context in Large-Scale Neurocognitive Network Operations , 2007 .

[19]  J. Giedd,et al.  Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging , 2006, Neuroscience & Biobehavioral Reviews.

[20]  Margot J. Taylor,et al.  Inversion and contrast-reversal effects on face processing assessed by MEG , 2006, Brain Research.

[21]  E. Bullmore,et al.  A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs , 2006, The Journal of Neuroscience.

[22]  Margot J. Taylor Neural bases of cognitive development , 2006 .

[23]  N. Kanwisher,et al.  The Neural Basis of the Behavioral Face-Inversion Effect , 2005, Current Biology.

[24]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[25]  Madalena Costa,et al.  Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Anthony Randal McIntosh,et al.  Partial least squares analysis of neuroimaging data: applications and advances , 2004, NeuroImage.

[27]  Margot J. Taylor,et al.  The Faces of Development: A Review of Early Face Processing over Childhood , 2004, Journal of Cognitive Neuroscience.

[28]  Margot J. Taylor,et al.  Face Recognition Memory and Configural Processing: A Developmental ERP Study using Upright, Inverted, and Contrast-Reversed Faces , 2004, Journal of Cognitive Neuroscience.

[29]  D. Maurer,et al.  The many faces of configural processing , 2002, Trends in Cognitive Sciences.

[30]  D. Maurer,et al.  Configural Face Processing Develops more Slowly than Featural Face Processing , 2002, Perception.

[31]  Margot J. Taylor,et al.  Inversion and Contrast Polarity Reversal Affect both Encoding and Recognition Processes of Unfamiliar Faces: A Repetition Study Using ERPs , 2002, NeuroImage.

[32]  A. Freire,et al.  Face recognition in 4- to 7-year-olds: processing of configural, featural, and paraphernalia information. , 2001, Journal of experimental child psychology.

[33]  David Poeppel,et al.  Reconstructing spatio-temporal activities of neural sources using an MEG vector beamformer technique , 2001, IEEE Transactions on Biomedical Engineering.

[34]  Mark H. Johnson Functional brain development in humans , 2001, Nature Reviews Neuroscience.

[35]  Margot J. Taylor,et al.  Eyes first! Eye processing develops before face processing in children , 2001, Neuroreport.

[36]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[37]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[38]  N Birbaumer,et al.  Complexity of electrocortical dynamics in children: developmental aspects. , 2000, Developmental psychobiology.

[39]  A. McIntosh,et al.  Mapping cognition to the brain through neural interactions. , 1999, Memory.

[40]  V. Goffaux,et al.  Spatio-temporal localization of the face inversion effect: an event-related potentials study , 1999, Biological Psychology.

[41]  Alan C. Evans,et al.  Structural maturation of neural pathways in children and adolescents: in vivo study. , 1999, Science.

[42]  Leslie G. Ungerleider,et al.  The Effect of Face Inversion on Activity in Human Neural Systems for Face and Object Perception , 1999, Neuron.

[43]  Se Robinson,et al.  Functional neuroimaging by Synthetic Aperture Magnetometry (SAM) , 1999 .

[44]  E. Halgren,et al.  Location of human face‐selective cortex with respect to retinotopic areas , 1999, Human brain mapping.

[45]  James W. Tanaka,et al.  Face recognition in young children : When the whole is greater than the sum of its parts , 1998 .

[46]  E. Gibson Linguistic complexity: locality of syntactic dependencies , 1998, Cognition.

[47]  K. Nakayama,et al.  The effect of face inversion on the human fusiform face area , 1998, Cognition.

[48]  T. Allison,et al.  Face-Specific Processing in the Human Fusiform Gyrus , 1997, Journal of Cognitive Neuroscience.

[49]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[50]  A. Meyer-Lindenberg,et al.  The evolution of complexity in human brain development: an EEG study. , 1996, Electroencephalography and clinical neurophysiology.

[51]  T. Allison,et al.  Electrophysiological Studies of Face Perception in Humans , 1996, Journal of Cognitive Neuroscience.

[52]  T. Allison,et al.  Face-sensitive regions in human extrastriate cortex studied by functional MRI. , 1995, Journal of neurophysiology.

[53]  M. Farah,et al.  What causes the face inversion effect? , 1995, Journal of experimental psychology. Human perception and performance.

[54]  G. Edelman,et al.  A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[55]  S. Carey,et al.  Are faces perceived as configurations more by adults than by children , 1994 .

[56]  G. Rhodes,et al.  What's lost in inverted faces? , 1993, Cognition.

[57]  M. Farah,et al.  Parts and Wholes in Face Recognition , 1993, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[58]  T. Gasser,et al.  Development of the EEG of school-age children and adolescents. I. Analysis of band power. , 1988, Electroencephalography and clinical neurophysiology.

[59]  Robert Tibshirani,et al.  Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy , 1986 .

[60]  R. Yin Looking at Upside-down Faces , 1969 .