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The Journal of Neuroscience : the... Jan 2017Scientific investigation into the possible role of sleep in memory consolidation began with the early studies of Jenkins and Dallenbach (1924). Despite nearly a century...
Scientific investigation into the possible role of sleep in memory consolidation began with the early studies of Jenkins and Dallenbach (1924). Despite nearly a century of investigation with a waxing and waning of interest, the role of sleep in memory processing remains controversial and elusive. This review provides the historical background for current views and considers the relative contribution of two sleep states, rapid eye movement sleep and slow-wave sleep, to offline memory processing. The sequential hypothesis, until now largely ignored, is discussed, and recent literature supporting this view is reviewed.
Topics: Animals; Brain; Brain Waves; Humans; Memory Consolidation; Mental Recall; Sleep
PubMed: 28100730
DOI: 10.1523/JNEUROSCI.0297-16.2017 -
Current Opinion in Neurobiology Jun 2017Slow waves, the hallmark of NREM (Non Rapid Eye Movement) sleep, are not uniformly distributed across the cortical surface, but can occur locally and asynchronously... (Review)
Review
Slow waves, the hallmark of NREM (Non Rapid Eye Movement) sleep, are not uniformly distributed across the cortical surface, but can occur locally and asynchronously across brain regions. Their regional distribution and amplitude is affected by brain maturation and by time spent awake, mediated in part by experience-dependent changes in synaptic strength. Recent studies have shown that local low-frequency oscillations (<10Hz) can also occur in REM sleep and during wakefulness, leading to region-specific cognitive errors. Local decreases and increases of slow wave activity in posterior brain regions have been linked to the occurrence of dreaming and to unconscious sleep, respectively. Finally, the coexistence of local sleep-like and wake-like patterns in different brain areas is characteristic of several sleep disorders and may offer insights into these conditions.
Topics: Brain; Brain Waves; Humans; Sleep; Sleep, REM; Wakefulness
PubMed: 28575720
DOI: 10.1016/j.conb.2017.05.008 -
Nature Communications Mar 2019Traveling patterns of neuronal activity-brain waves-have been observed across a breadth of neuronal recordings, states of awareness, and species, but their emergence in...
Traveling patterns of neuronal activity-brain waves-have been observed across a breadth of neuronal recordings, states of awareness, and species, but their emergence in the human brain lacks a firm understanding. Here we analyze the complex nonlinear dynamics that emerge from modeling large-scale spontaneous neural activity on a whole-brain network derived from human tractography. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. These metastable dynamics accord with empirical data from multiple imaging modalities, including electrical waves in cortical tissue, sequential spatiotemporal patterns in resting-state MEG data, and large-scale waves in human electrocorticography. By moving the study of functional networks from a spatially static to an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena across functional neuroimaging modalities and makes specific predictions for further experimentation.
Topics: Adolescent; Adult; Brain; Brain Waves; Computer Simulation; Diffusion Tensor Imaging; Electrocorticography; Female; Healthy Volunteers; Humans; Male; Models, Neurological; Nerve Net; Neurons; Nonlinear Dynamics; Young Adult
PubMed: 30837462
DOI: 10.1038/s41467-019-08999-0 -
The European Journal of Neuroscience Jun 2022Brain waves, determined by electrical and magnetic brain recordings (e.g., EEG and MEG), and fluctuating behavioral responses, determined by response time or accuracy... (Review)
Review
Brain waves, determined by electrical and magnetic brain recordings (e.g., EEG and MEG), and fluctuating behavioral responses, determined by response time or accuracy measures, are frequently taken to support discrete perception. For example, it has been proposed that humans experience only one conscious percept per brain wave (e.g., during one alpha cycle). However, the proposed link between brain waves and discrete perception is typically rather vague. More importantly, there are many models and aspects of discrete perception and it is often not apparent in what theoretical framework brain wave findings are interpreted and to what specific aspects of discrete perception they relate. Here, we review different approaches to discrete perception and highlight issues with particular interpretations. We then discuss how certain findings on brain waves may relate to certain aspects of discrete perception. The main purpose of this meta-contribution is to give a short overview of discrete models of perception and to illustrate the need to make explicit what aspects of discrete theories are addressed by what aspects of brain wave findings.
Topics: Brain; Brain Waves; Consciousness; Humans; Perception; Reaction Time
PubMed: 34125452
DOI: 10.1111/ejn.15349 -
British Journal of Clinical Pharmacology Jan 2014To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many... (Review)
Review
To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms 'analgesics', 'electroencephalography' and 'evoked potentials' for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients.
Topics: Analgesics; Animals; Brain Waves; Electroencephalography; Evoked Potentials; Humans
PubMed: 23593934
DOI: 10.1111/bcp.12137 -
Neuron Mar 2013Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence... (Review)
Review
Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes.
Topics: Animals; Brain Waves; Hippocampus; Humans; Memory; Neural Pathways; Theta Rhythm
PubMed: 23522038
DOI: 10.1016/j.neuron.2013.03.007 -
ELife Aug 2021Sleep slow waves are studied for their role in brain plasticity, homeostatic regulation, and their changes during aging. Here, we address the possibility that two types...
Sleep slow waves are studied for their role in brain plasticity, homeostatic regulation, and their changes during aging. Here, we address the possibility that two types of slow waves co-exist in humans. Thirty young and 29 older adults underwent a night of polysomnographic recordings. Using the slow waves with a slow transition (slow switchers) and those with a fast transition (fast switchers) were discovered. Slow switchers had a high electroencephalography (EEG) connectivity along their depolarization transition while fast switchers had a lower connectivity dynamics and dissipated faster during the night. Aging was associated with lower temporal dissipation of sleep pressure in slow and fast switchers and lower EEG connectivity at the microscale of the oscillations, suggesting a decreased flexibility in the connectivity network of older individuals. Our findings show that two different types of slow waves with possible distinct underlying functions coexist in the slow wave spectrum.
Topics: Adult; Age Factors; Aged; Brain; Brain Waves; Electroencephalography; Female; Humans; Male; Middle Aged; Neuronal Plasticity; Polysomnography; Sleep, Slow-Wave; Time Factors; Young Adult
PubMed: 34448453
DOI: 10.7554/eLife.64337 -
Neuron May 2015The term spreading depolarization (SD) refers to waves of abrupt, sustained mass depolarization in gray matter of the CNS. SD, which spreads from neuron to neuron in... (Review)
Review
The term spreading depolarization (SD) refers to waves of abrupt, sustained mass depolarization in gray matter of the CNS. SD, which spreads from neuron to neuron in affected tissue, is characterized by a rapid near-breakdown of the neuronal transmembrane ion gradients. SD can be induced by hypoxic conditions--such as from ischemia--and facilitates neuronal death in energy-compromised tissue. SD has also been implicated in migraine aura, where SD is assumed to ascend in well-nourished tissue and is typically benign. In addition to these two ends of the "SD continuum," an SD wave can propagate from an energy-depleted tissue into surrounding, well-nourished tissue, as is often the case in stroke and brain trauma. This review presents the neurobiology of SD--its triggers and propagation mechanisms--as well as clinical manifestations of SD, including overlaps and differences between migraine aura and stroke, and recent developments in neuromonitoring aimed at better diagnosis and more targeted treatments.
Topics: Animals; Brain; Brain Waves; Cortical Spreading Depression; Humans; Migraine Disorders; Neurons; Stroke
PubMed: 25996134
DOI: 10.1016/j.neuron.2015.04.004 -
Neuroscience and Biobehavioral Reviews May 2020It is increasingly being recognized that active control of breathing - a key aspect of ancient Vedic meditative practices, can relieve stress and anxiety and improve... (Review)
Review
It is increasingly being recognized that active control of breathing - a key aspect of ancient Vedic meditative practices, can relieve stress and anxiety and improve cognition. However, the underlying mechanisms of respiratory modulation of neurophysiology are just beginning to be elucidated. Research shows that brainstem circuits involved in the motor control of respiration receive input from and can directly modulate activity in subcortical circuits, affecting emotion and arousal. Meanwhile, brain regions involved in the sensory aspects of respiration, such as the olfactory bulb, are like-wise linked with wide-spread brain oscillations; and perturbing olfactory bulb activity can significantly affect both mood and cognition. Thus, via both motor and sensory pathways, there are clear mechanisms by which brain activity is entrained to the respiratory cycle. Here, we review evidence gathered across multiple species demonstrating the links between respiration, entrainment of brain activity and functional relevance for affecting mood and cognition. We also discuss further linkages with cardiac rhythms, and the potential translational implications for biorhythm monitoring and regulation in neuropsychiatric disorders.
Topics: Animals; Brain Stem; Brain Waves; Heart Rate; Humans; Olfactory Bulb; Respiratory Physiological Phenomena
PubMed: 32027875
DOI: 10.1016/j.neubiorev.2020.02.001 -
Journal of Neurophysiology Feb 2020The Wilson-Cowan population model of neural activity has greatly influenced our understanding of the mechanisms for the generation of brain rhythms and the emergence of... (Review)
Review
The Wilson-Cowan population model of neural activity has greatly influenced our understanding of the mechanisms for the generation of brain rhythms and the emergence of structured brain activity. As well as the many insights that have been obtained from its mathematical analysis, it is now widely used in the computational neuroscience community for building large-scale in silico brain networks that can incorporate the increasing amount of knowledge from the Human Connectome Project. Here, we consider a neural population model in the spirit of that originally developed by Wilson and Cowan, albeit with the added advantage that it can account for the phenomena of event-related synchronization and desynchronization. This derived mean-field model provides a dynamic description for the evolution of synchrony, as measured by the Kuramoto order parameter, in a large population of quadratic integrate-and-fire model neurons. As in the original Wilson-Cowan framework, the population firing rate is at the heart of our new model; however, in a significant departure from the sigmoidal firing rate function approach, the population firing rate is now obtained as a real-valued function of the complex-valued population synchrony measure. To highlight the usefulness of this next-generation Wilson-Cowan style model, we deploy it in a number of neurobiological contexts, providing understanding of the changes in power spectra observed in electro- and magnetoencephalography neuroimaging studies of motor cortex during movement, insights into patterns of functional connectivity observed during rest and their disruption by transcranial magnetic stimulation, and to describe wave propagation across cortex.
Topics: Brain Waves; Cerebral Cortex; Connectome; Cortical Synchronization; Humans; Magnetoencephalography; Models, Biological; Transcranial Magnetic Stimulation
PubMed: 31774370
DOI: 10.1152/jn.00406.2019