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Brain signal variability relates to stability of behavior after recovery from diffuse brain injury.

ABSTRACT: Variability or noise is an unmistakable feature of neural signals; however such fluctuations have been regarded as not carrying meaningful information or as detrimental for neural processes. Recent empirical and computational work has shown that neural systems with a greater capacity for information processing are able to explore a more varied dynamic repertoire, and the hallmark of this is increased irregularity or variability in the neural signal. How this variability in neural dynamics affects behavior remains unclear. Here, we investigated the role of variability of magnetoencephalography signals in supporting healthy cognitive functioning, measured by performance on an attention task, in healthy adults and in patients with traumatic brain injury. As an index of variability, we calculated multiscale entropy, which quantifies the temporal predictability of a time series across progressively more coarse time scales. We found lower variability in traumatic brain injury patients compared to controls, arguing against the idea that greater variability reflects dysfunctional neural processing. Furthermore, higher brain signal variability indicated improved behavioral performance for all participants. This relationship was statistically stronger for people with brain injury, demonstrating that those with higher brain signal variability were also those who had recovered the most cognitive ability. Rather than impede neural processing, cortical signal variability within an optimal range enables the exploration of diverse functional configurations, and may therefore play a vital role in healthy brain function.

SUBMITTER: Raja Beharelle A

PROVIDER: S-EPMC3303989 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Brain signal variability relates to stability of behavior after recovery from diffuse brain injury.

Raja Beharelle Anjali A Kovačević Natasa N McIntosh Anthony R AR Levine Brian B

NeuroImage 20120111 2

Variability or noise is an unmistakable feature of neural signals; however such fluctuations have been regarded as not carrying meaningful information or as detrimental for neural processes. Recent empirical and computational work has shown that neural systems with a greater capacity for information processing are able to explore a more varied dynamic repertoire, and the hallmark of this is increased irregularity or variability in the neural signal. How this variability in neural dynamics affect ...[more]

PMID: 22261371

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Project description:BACKGROUND:Diffuse traumatic brain injury (TBI) is known to lead to microstructural changes within both white and grey matter detected in vivo with diffusion tensor imaging (DTI). Numerous studies have shown alterations in fractional anisotropy (FA) and mean diffusivity (MD) within prominent white matter tracts, but few have linked these to changes within the grey matter with confirmation via histological assessment. This is especially important as alterations in the grey matter may be predictive of long-term functional deficits. METHODS:A total of 33 male Sprague Dawley rats underwent severe closed-head TBI. Eight animals underwent tensor-based morphometry (TBM) and DTI at baseline (pre-TBI), 24 hours (24 h), 7, 14, and 30 days post-TBI. Immunohistochemical analysis for the detection of ionised calcium-binding adaptor molecule 1 (IBA1) to assess microglia number and percentage of activated cells, ?-amyloid precursor protein (APP) as a marker of axonal injury, and myelin basic protein (MBP) to investigate myelination was performed at each time-point. RESULTS:DTI showed significant alterations in FA and RD in numerous white matter tracts including the corpus callosum, internal and external capsule, and optic tract and in the grey-matter in the cortex, thalamus, and hippocampus, with the most significant effects observed at 14 D post-TBI. TBM confirmed volumetric changes within the hippocampus and thalamus. Changes in DTI were in line with significant axonal injury noted at 24 h post-injury via immunohistochemical analysis of APP, with widespread microglial activation seen within prominent white matter tracts and the grey matter, which persisted to 30 D within the hippocampus and thalamus. Microstructural alterations in MBP+ve fibres were also noted within the hippocampus and thalamus, as well as the cortex. CONCLUSION:This study confirms the widespread effects of diffuse TBI on white matter tracts which could be detected via DTI and extends these findings to key grey matter regions, with a comprehensive investigation of the whole brain. In particular, the hippocampus and thalamus appear to be vulnerable to ongoing pathology post-TBI, with DTI able to detect these alterations supporting the clinical utility in evaluating these regions post-TBI.

Project description:Despite sharing the same genes, identical twins demonstrate substantial variability in behavioral traits and in their risk for disease. Epigenetic factors-DNA and chromatin modifications that affect levels of gene expression without affecting the DNA sequence-are thought to be important in establishing this variability. Epigenetically-mediated differences in the levels of gene expression that are associated with individual variability traditionally are thought to occur only in a gene-specific manner. We challenge this idea by exploring the large-scale organizational patterns of gene expression in an epigenetic model of behavioral variability.To study the effects of epigenetic influences on behavioral variability, we examine gene expression in genetically identical mice. Using a novel approach to microarray analysis, we show that variability in the large-scale organization of gene expression levels, rather than differences in the expression levels of specific genes, is associated with individual differences in behavior. Specifically, increased activity in the open field is associated with increased variance of log-transformed measures of gene expression in the hippocampus, a brain region involved in open field activity. Early life experience that increases adult activity in the open field also similarly modifies the variance of gene expression levels. The same association of the variance of gene expression levels with behavioral variability is found with levels of gene expression in the hippocampus of genetically heterogeneous outbred populations of mice, suggesting that variation in the large-scale organization of gene expression levels may also be relevant to phenotypic differences in outbred populations such as humans. We find that the increased variance in gene expression levels is attributable to an increasing separation of several large, log-normally distributed families of gene expression levels. We also show that the presence of these multiple log-normal distributions of gene expression levels is a universal characteristic of gene expression in eurkaryotes. We use data from the MicroArray Quality Control Project (MAQC) to demonstrate that our method is robust and that it reliably detects biological differences in the large-scale organization of gene expression levels.Our results contrast with the traditional belief that epigenetic effects on gene expression occur only at the level of specific genes and suggest instead that the large-scale organization of gene expression levels provides important insights into the relationship of gene expression with behavioral variability. Understanding the epigenetic, genetic, and environmental factors that regulate the large-scale organization of gene expression levels, and how changes in this large-scale organization influences brain development and behavior will be a major future challenge in the field of behavioral genomics.

Dataset Information

Brain signal variability relates to stability of behavior after recovery from diffuse brain injury.

Publications

Brain signal variability relates to stability of behavior after recovery from diffuse brain injury.

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