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Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

ABSTRACT: Whether measured by MRI or direct cortical physiology, infraslow rhythms have defined state invariant cortical networks. The time scales of this functional architecture, however, are unlikely to be able to accommodate the more rapid cortical dynamics necessary for an active cognitive task. Using invasively monitored epileptic patients as a research model, we tested the hypothesis that faster frequencies would spectrally bind regions of cortex as a transient mechanism to enable fast network interactions during the performance of a simple hear-and-repeat speech task. We term these short-lived spectrally covariant networks functional spectral networks (FSNs). We evaluated whether spectrally covariant regions of cortex, which were unique in their spectral signatures, provided a higher degree of task-related information than any single site showing more classic physiologic responses (i.e., single-site amplitude modulation). Taken together, our results showing that FSNs are a more sensitive measure of task-related brain activation and are better able to discern phonemic content strongly support the concept of spectrally encoded interactions in cortex. Moreover, these findings that specific linguistic information is represented in FSNs that have broad anatomic topographies support a more distributed model of cortical processing.

SUBMITTER: Freudenburg ZV

PROVIDER: S-EPMC3970528 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

Freudenburg Zachary V ZV Gaona Charles M CM Sharma Mohit M Bundy David T DT Breshears Jonathan D JD Pless Robert B RB Leuthardt Eric C EC

Proceedings of the National Academy of Sciences of the United States of America 20140310 12

Whether measured by MRI or direct cortical physiology, infraslow rhythms have defined state invariant cortical networks. The time scales of this functional architecture, however, are unlikely to be able to accommodate the more rapid cortical dynamics necessary for an active cognitive task. Using invasively monitored epileptic patients as a research model, we tested the hypothesis that faster frequencies would spectrally bind regions of cortex as a transient mechanism to enable fast network inter ...[more]

PMID: 24616527

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Project description:Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.

Project description:Multiple color-selective areas have been described in visual cortex, in both humans and non-human primates. In macaques, hue-selective columns have been reported in several areas. In V2, it has been proposed that such hue-selective columns are mapped so as to mirror the order of wavelength through the visible spectrum, within thin-type stripes. Other studies have suggested a neural segregation of mid-spectral vs. end-spectral hue preferences (e.g. red and blue vs. green and yellow), within thin- and thick-type stripes, respectively. This latter segregation could reduce the spatial 'blur' due to chromatic aberration in the encoding of fine spatial details in the thick-type stripes. To distinguish between these and related models, we tested the organization of hue preferences in human visual cortex using fMRI at high spatial resolution. We used a high field (7T) scanner in humans (n = 7), measuring responses to four independent hues, including end-spectral (i.e. red-gray and blue-gray) and mid-spectral (i.e. green-gray and yellow-gray) isoluminant gratings, and also relative to achromatic luminance-varying (control) stimuli. In each subject, thin- and thick-type columns in V2 and V3 were localized using an independent set of stimuli and scans. We found distinct hue-selective differences along the dimension of mid-vs. end-spectral hues, in striate and early extrastriate visual cortex. First, as reported previously in macaques, V1 responded more strongly to end-spectral hues, compared to mid-spectral hues. Second, the color-selective thin-type stripes in V2 and V3 showed a greater response to end- and mid-spectral hues, relative to luminance-varying gratings. Third, thick-type stripes in V2/V3 showed a significantly stronger response to mid-spectral (compared to end-spectral) hues. Fourth, in the higher-tier color-selective area in occipital temporal cortex (n = 4), responses to all four hues were statistically equivalent to each other. These results suggest that early visual cortex segregates the processing of mid-vs. end-spectral hues, perhaps to counter the challenging optical constraint of chromatic aberration.

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Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

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Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

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