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Progress in Brain Research 2010Mechanism is at the heart of understanding, and this chapter addresses underlying brain mechanisms and pathways of cognition and the impact of sleep on these processes,... (Review)
Review
Mechanism is at the heart of understanding, and this chapter addresses underlying brain mechanisms and pathways of cognition and the impact of sleep on these processes, especially those serving learning and memory. This chapter reviews the current understanding of the relationship between sleep/waking states and cognition from the perspective afforded by basic neurophysiological investigations. The extensive overlap between sleep mechanisms and the neurophysiology of learning and memory processes provide a foundation for theories of a functional link between the sleep and learning systems. Each of the sleep states, with its attendant alterations in neurophysiology, is associated with facilitation of important functional learning and memory processes. For rapid eye movement (REM) sleep, salient features such as PGO waves, theta synchrony, increased acetylcholine, reduced levels of monoamines and, within the neuron, increased transcription of plasticity-related genes, cumulatively allow for freely occurring bidirectional plasticity, long-term potentiation (LTP) and its reversal, depotentiation. Thus, REM sleep provides a novel neural environment in which the synaptic remodelling essential to learning and cognition can occur, at least within the hippocampal complex. During non-REM sleep Stage 2 spindles, the cessation and subsequent strong bursting of noradrenergic cells and coincident reactivation of hippocampal and cortical targets would also increase synaptic plasticity, allowing targeted bidirectional plasticity in the neocortex as well. In delta non-REM sleep, orderly neuronal reactivation events in phase with slow wave delta activity, together with high protein synthesis levels, would facilitate the events that convert early LTP to long-lasting LTP. Conversely, delta sleep does not activate immediate early genes associated with de novo LTP. This non-REM sleep-unique genetic environment combined with low acetylcholine levels may serve to reduce the strength of cortical circuits that activate in the ~50% of delta-coincident reactivation events that do not appear in their waking firing sequence. The chapter reviews the results of manipulation studies, typically total sleep or REM sleep deprivation, that serve to underscore the functional significance of the phenomenological associations. Finally, the implications of sleep neurophysiology for learning and memory will be considered from a larger perspective in which the association of specific sleep states with both potentiation or depotentiation is integrated into mechanistic models of cognition.
Topics: Brain; Brain Waves; Humans; Long-Term Potentiation; Neurons; Sleep
PubMed: 21075230
DOI: 10.1016/B978-0-444-53702-7.00001-4 -
BMC Bioinformatics Jun 2021Brain wave signal recognition has gained increased attention in neuro-rehabilitation applications. This has driven the development of brain-computer interface (BCI)...
BACKGROUND
Brain wave signal recognition has gained increased attention in neuro-rehabilitation applications. This has driven the development of brain-computer interface (BCI) systems. Brain wave signals are acquired using electroencephalography (EEG) sensors, processed and decoded to identify the category to which the signal belongs. Once the signal category is determined, it can be used to control external devices. However, the success of such a system essentially relies on significant feature extraction and classification algorithms. One of the commonly used feature extraction technique for BCI systems is common spatial pattern (CSP).
RESULTS
The performance of the proposed spatial-frequency-temporal feature extraction (SPECTRA) predictor is analysed using three public benchmark datasets. Our proposed predictor outperformed other competing methods achieving lowest average error rates of 8.55%, 17.90% and 20.26%, and highest average kappa coefficient values of 0.829, 0.643 and 0.595 for BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, respectively.
CONCLUSIONS
Our proposed SPECTRA predictor effectively finds features that are more separable and shows improvement in brain wave signal recognition that can be instrumental in developing improved real-time BCI systems that are computationally efficient.
Topics: Algorithms; Brain; Brain Waves; Brain-Computer Interfaces; Electroencephalography; Imagination; Signal Processing, Computer-Assisted
PubMed: 34078274
DOI: 10.1186/s12859-021-04091-x -
Dialogues in Clinical Neuroscience Sep 2013Neural oscillations at low- and high-frequency ranges are a fundamental feature of large-scale networks. Recent evidence has indicated that schizophrenia is associated... (Review)
Review
Neural oscillations at low- and high-frequency ranges are a fundamental feature of large-scale networks. Recent evidence has indicated that schizophrenia is associated with abnormal amplitude and synchrony of oscillatory activity, in particular, at high (beta/gamma) frequencies. These abnormalities are observed during task-related and spontaneous neuronal activity which may be important for understanding the pathophysiology of the syndrome. In this paper, we shall review the current evidence for impaired beta/gamma-band oscillations and their involvement in cognitive functions and certain symptoms of the disorder. In the first part, we will provide an update on neural oscillations during normal brain functions and discuss underlying mechanisms. This will be followed by a review of studies that have examined high-frequency oscillatory activity in schizophrenia and discuss evidence that relates abnormalities of oscillatory activity to disturbed excitatory/inhibitory (E/I) balance. Finally, we shall identify critical issues for future research in this area.
Topics: Animals; Brain; Brain Waves; Electroencephalography; Humans; Nerve Net; Periodicity; Schizophrenia
PubMed: 24174902
DOI: 10.31887/DCNS.2013.15.3/puhlhaas -
Journal of Neurophysiology Jun 2016The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the...
The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the seizure onset zone (SOZ), is functionally isolated from surrounding brain regions in focal neocortical epilepsy. The modulatory effect of behavioral state on the spatial and spectral scales over which the reduced functional connectivity occurs, however, is unclear. Here we use simultaneous sleep staging from scalp EEG with intracranial EEG recordings from medial temporal lobe to investigate how behavioral state modulates the spatial and spectral scales of local field potential synchrony in focal epileptic hippocampus. The local field spectral power and linear correlation between adjacent electrodes provide measures of neuronal population synchrony at different spatial scales, ∼1 and 10 mm, respectively. Our results show increased connectivity inside the SOZ and low connectivity between electrodes in SOZ and outside the SOZ. During slow-wave sleep, we observed decreased connectivity for ripple and fast ripple frequency bands within the SOZ at the 10 mm spatial scale, while the local synchrony remained high at the 1 mm spatial scale. Further study of these phenomena may prove useful for SOZ localization and help understand seizure generation, and the functional deficits seen in epileptic eloquent cortex.
Topics: Adult; Brain Mapping; Brain Waves; Electroencephalography; Epilepsy, Temporal Lobe; Female; Hippocampus; Humans; Male; Middle Aged; Sleep; Spectrum Analysis; Young Adult
PubMed: 27030735
DOI: 10.1152/jn.00089.2016 -
IEEE Transactions on Bio-medical... May 2014Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI... (Review)
Review
Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI systems extract specific features of brain activity and translate them into control signals that drive an output. Recently, a category of BCIs that are built on the rhythmic activity recorded over the sensorimotor cortex, i.e., the sensorimotor rhythm (SMR), has attracted considerable attention among the BCIs that use noninvasive neural recordings, e.g., electroencephalography (EEG), and have demonstrated the capability of multidimensional prosthesis control. This paper reviews the current state and future perspectives of SMR-based BCI and its clinical applications, in particular focusing on the EEG SMR. The characteristic features of SMR from the human brain are described and their underlying neural sources are discussed. The functional components of SMR-based BCI, together with its current clinical applications, are reviewed. Finally, limitations of SMR-BCIs and future outlooks are also discussed.
Topics: Brain Waves; Brain-Computer Interfaces; Electrodes, Implanted; Electroencephalography; Feedback, Physiological; Humans; Signal Processing, Computer-Assisted; Spinal Cord Diseases
PubMed: 24759276
DOI: 10.1109/TBME.2014.2312397 -
Neuroscience and Biobehavioral Reviews Sep 2023Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have... (Review)
Review
Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.
Topics: Animals; Humans; Brain Waves; Brain; Respiration; Mental Disorders; Mammals
PubMed: 37271298
DOI: 10.1016/j.neubiorev.2023.105262 -
Nature Neuroscience Aug 2022Studying the natural wanderings of the living brain is extremely challenging. Bolt et al. describe a new framework to consider the brain’s intrinsic activity based on...
Studying the natural wanderings of the living brain is extremely challenging. Bolt et al. describe a new framework to consider the brain’s intrinsic activity based on the geophysical concepts of standing and traveling waves.
Topics: Brain; Brain Waves
PubMed: 35902650
DOI: 10.1038/s41593-022-01119-0 -
Frontiers in Neural Circuits 2022
Topics: Brain; Brain Waves
PubMed: 35860210
DOI: 10.3389/fncir.2022.960157 -
Cognitive, Affective & Behavioral... Jun 2019Exercising self-control can be phenomenologically aversive. Insofar as individuals strive to maintain a positive emotional state, one consequence of exercising... (Review)
Review
Exercising self-control can be phenomenologically aversive. Insofar as individuals strive to maintain a positive emotional state, one consequence of exercising self-control may thus be a temporarily tuning toward or amplification of reward-related impulses (perhaps arising to countermand the aversive feelings that stem from self-control). Reward-relevant after-effects are relatively underappreciated in self-control research. In the current paper, we review theory and research pertaining to the idea that exercising self-control increases reward responsivity. First, we review theoretical models of self-control focusing on the relationship between control systems and reward systems. Second, we review behavioral studies regarding the effects of exercising self-control on subsequent reactivity to food, money, drugs, and positive emotional images. Third, we review findings from functional neuroimaging and electroencephalographic research pertaining to the reward responsivity hypothesis. We then call for additional research to integrate how, when, and under what circumstances self-control exertion influences reward processing. Such an endeavor will help to advance research and theory on self-control by offering a more precise characterization of the dynamic interactions between control systems and reward systems.
Topics: Brain; Brain Waves; Decision Making; Evoked Potentials; Humans; Reward; Self-Control
PubMed: 30673962
DOI: 10.3758/s13415-019-00694-3 -
The Neuroscientist : a Review Journal... Feb 2020Brain oscillations are regarded as important for perception as they open and close time windows for neural spiking to enable the effective communication within and... (Review)
Review
Brain oscillations are regarded as important for perception as they open and close time windows for neural spiking to enable the effective communication within and across brain regions. In the past, studies on perception primarily relied on the use of electrophysiological techniques for probing a correlative link between brain oscillations and perception. The emergence of noninvasive brain stimulation techniques such as transcranial alternating current stimulation (tACS) provides the possibility to study the causal contribution of specific oscillatory frequencies to perception. Here, we review the studies on visual, auditory, and somatosensory perception that employed tACS to probe the causality of brain oscillations for perception. The current literature is consistent with a causal role of alpha and gamma oscillations in parieto-occipital regions for visual perception and theta and gamma oscillations in auditory cortices for auditory perception. In addition, the sensory gating by alpha oscillations applies not only to the visual but also to the somatosensory domain. We conclude that albeit more refined perceptual paradigms and individualized stimulation practices remain to be systematically adopted, tACS is a promising tool for establishing a causal link between neural oscillations and perception.
Topics: Auditory Perception; Brain; Brain Waves; Humans; Nerve Net; Transcranial Direct Current Stimulation; Visual Perception
PubMed: 30730265
DOI: 10.1177/1073858419828646