Faculty Opinions recommendation of Coherent neural oscillations predict future motor and language improvement after stroke.

Author(s):  
Paul Verschure
Keyword(s):  
Author(s):  
Brittany K. Taylor ◽  
Jacob A. Eastman ◽  
Michaela R. Frenzel ◽  
Christine M. Embury ◽  
Yu-Ping Wang ◽  
...  

Author(s):  
Marcus O. Harrington ◽  
Scott A. Cairney

Abstract Purpose of Review Auditory stimulation is a technique that can enhance neural oscillations linked to overnight memory consolidation. In this review, we evaluate the impacts of auditory stimulation on the neural oscillations of sleep and associated memory processes in a variety of populations. Recent Findings Cortical EEG recordings of slow-wave sleep (SWS) are characterised by two cardinal oscillations: slow oscillations (SOs) and sleep spindles. Auditory stimulation delivered in SWS enhances SOs and phase-coupled spindle activity in healthy children and adults, children with ADHD, adults with mild cognitive impairment and patients with major depression. Under certain conditions, auditory stimulation bolsters the benefits of SWS for memory consolidation, although further work is required to fully understand the factors affecting stimulation-related memory gains. Recent work has turned to rapid eye movement (REM) sleep, demonstrating that auditory stimulation can be used to manipulate REM sleep theta oscillations. Summary Auditory stimulation enhances oscillations linked to overnight memory processing and shows promise as a technique for enhancing the memory benefits of sleep.


NeuroImage ◽  
2016 ◽  
Vol 136 ◽  
pp. 139-148 ◽  
Author(s):  
Kai Hwang ◽  
Avniel S. Ghuman ◽  
Dara S. Manoach ◽  
Stephanie R. Jones ◽  
Beatriz Luna

Neuroforum ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Maryam Ghorbani ◽  
Lisa Marshall

AbstractSleep contributes actively to the consolidation of many forms of memory. This review describes the neural oscillations of non-rapid eye movement (NREM) sleep, the structures underlying these oscillations and their relation to hippocampus-dependent memory consolidation. A main focus lies on the relation between inter- and intraregional interactions and their electrophysiological representation. Methods for modulating neural oscillations with the intent of affecting memory consolidation are presented.


2008 ◽  
Vol 78 (2) ◽  
Author(s):  
Axel Hutt ◽  
Connie Sutherland ◽  
André Longtin
Keyword(s):  

2015 ◽  
Vol 113 (5) ◽  
pp. 1556-1563 ◽  
Author(s):  
Freek van Ede ◽  
Stan van Pelt ◽  
Pascal Fries ◽  
Eric Maris

Neural oscillations have emerged as one of the major electrophysiological phenomena investigated in cognitive and systems neuroscience. These oscillations are typically studied with regard to their amplitude, phase, and/or phase coupling. Here we demonstrate the existence of another property that is intrinsic to neural oscillations but has hitherto remained largely unexplored in cognitive and systems neuroscience. This pertains to the notion that these oscillations show reliable diversity in their phase-relations between neighboring recording sites (phase-relation diversity). In contrast to most previous work, we demonstrate that this diversity is restricted neither to low-frequency oscillations nor to periods outside of sensory stimulation. On the basis of magnetoencephalographic (MEG) recordings in humans, we show that this diversity is prominent not only for ongoing alpha oscillations (8–12 Hz) but also for gamma oscillations (50–70 Hz) that are induced by sustained visual stimulation. We further show that this diversity provides a dimension within electrophysiological data that, provided a sufficiently high signal-to-noise ratio, does not covary with changes in amplitude. These observations place phase-relation diversity on the map as a prominent and general property of neural oscillations that, moreover, can be studied with noninvasive methods in healthy human volunteers. This opens important new avenues for investigating how neural oscillations contribute to the neural implementation of cognition and behavior.


NeuroImage ◽  
2010 ◽  
Vol 53 (2) ◽  
pp. 757-768 ◽  
Author(s):  
Yan Mu ◽  
Shihui Han

NeuroImage ◽  
2010 ◽  
Vol 51 (4) ◽  
pp. 1319-1333 ◽  
Author(s):  
Alexander J. Shackman ◽  
Brenton W. McMenamin ◽  
Jeffrey S. Maxwell ◽  
Lawrence L. Greischar ◽  
Richard J. Davidson

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