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      Energy features in spontaneous up and down oscillations

      , ,
      Cognitive Neurodynamics
      Springer Science and Business Media LLC

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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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            Neuronal oscillations in cortical networks.

            G Buzsáki (2004)
            Clocks tick, bridges and skyscrapers vibrate, neuronal networks oscillate. Are neuronal oscillations an inevitable by-product, similar to bridge vibrations, or an essential part of the brain's design? Mammalian cortical neurons form behavior-dependent oscillating networks of various sizes, which span five orders of magnitude in frequency. These oscillations are phylogenetically preserved, suggesting that they are functionally relevant. Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
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              Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest.

              We assessed the relation between hemodynamic and electrical indices of brain function by performing simultaneous functional MRI (fMRI) and electroencephalography (EEG) in awake subjects at rest with eyes closed. Spontaneous power fluctuations of electrical rhythms were determined for multiple discrete frequency bands, and associated fMRI signal modulations were mapped on a voxel-by-voxel basis. There was little positive correlation of localized brain activity with alpha power (8-12 Hz), but strong and widespread negative correlation in lateral frontal and parietal cortices that are known to support attentional processes. Power in a 17-23 Hz range of beta activity was positively correlated with activity in retrosplenial, temporo-parietal, and dorsomedial prefrontal cortices. This set of areas has previously been characterized by high but coupled metabolism and blood flow at rest that decrease whenever subjects engage in explicit perception or action. The distributed patterns of fMRI activity that were correlated with power in different EEG bands overlapped strongly with those of functional connectivity, i.e., intrinsic covariations of regional activity at rest. This result indicates that, during resting wakefulness, and hence the absence of a task, these areas constitute separable and dynamic functional networks, and that activity in these networks is associated with distinct EEG signatures. Taken together with studies that have explicitly characterized the response properties of these distributed cortical systems, our findings may suggest that alpha oscillations signal a neural baseline with "inattention" whereas beta rhythms index spontaneous cognitive operations during conscious rest.
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                Author and article information

                Journal
                Cognitive Neurodynamics
                Cogn Neurodyn
                Springer Science and Business Media LLC
                1871-4080
                1871-4099
                February 2021
                May 29 2020
                February 2021
                : 15
                : 1
                : 65-75
                Article
                10.1007/s11571-020-09597-3
                876d21c3-f364-4223-803d-aa7db4cf5397
                © 2021

                https://www.springer.com/tdm

                https://www.springer.com/tdm

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