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Proceedings of the National Academy of... Apr 2023Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure...
Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure of the waves-their shapes and patterns over finite timescales. Here, we study brain wave patterning in different physiological contexts using two independent approaches: The first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses "orderliness" of the waves' features. The corresponding measures capture the waves' characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns' dynamics and the animal's location, speed, and acceleration. Specifically, we studied patterns of , , and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave's cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Taken together, our results offer a complementary-mesoscale-perspective on brain wave structure, dynamics, and functionality.
Topics: Animals; Mice; Hippocampus; Brain; Brain Waves; Periodicity; Theta Rhythm
PubMed: 36976768
DOI: 10.1073/pnas.2218245120 -
Neuroscience Letters Oct 2019Cross frequency coupling is used to study the cross talk between brain oscillations. In this paper we focus on a special type of frequency coupling between brain and...
Cross frequency coupling is used to study the cross talk between brain oscillations. In this paper we focus on a special type of frequency coupling between brain and body oscillations, which is reflected by the numerical ratio (r) between two frequencies (m and n; n > m). This approach is motivated by theoretical considerations, indicating that during alert wakefulness brain-body oscillations form a coupled hierarchy of frequencies with integer relationships that are binary multiples (r = n:m = 1:2, 1:4, 1:8…..). During sleep we expect an irrational relationship (r = n/m = irrational number) between brain and body oscillations that reflects decoupling. We analyzed alpha frequency, heart rate, breathing frequency during performance of a memory tasks and in addition spindle frequency from data collected by the SIESTA sleep research group. As predicted, our results show a binary multiple frequency relationship between alpha, heart rate and breathing frequency during task performance but an irrational relationship between spindle frequency, heart rate and breathing frequency during sleep.
Topics: Adult; Aged; Aged, 80 and over; Brain; Brain Waves; Cardiovascular Physiological Phenomena; Electroencephalography; Female; Humans; Male; Middle Aged; Sleep; Wakefulness; Young Adult
PubMed: 31349018
DOI: 10.1016/j.neulet.2019.134401 -
Epilepsia Open Aug 2022Drug-resistant epilepsy (DRE) affects approximately one-third of the patients with epilepsy. Based on experimental findings from animal models and brain tissue from... (Review)
Review
Drug-resistant epilepsy (DRE) affects approximately one-third of the patients with epilepsy. Based on experimental findings from animal models and brain tissue from patients with DRE, different hypotheses have been proposed to explain the cause(s) of drug resistance. One is the intrinsic severity hypothesis that posits that drug resistance is an inherent property of epilepsy related to disease severity. Seizure frequency is one measure of epilepsy severity, but frequency alone is an incomplete measure of severity and does not fully explain basic research and clinical studies on drug resistance; thus, other measures of epilepsy severity are needed. One such measure could be pathological high-frequency oscillations (HFOs), which are believed to reflect the neuronal disturbances responsible for the development of epilepsy and the generation of spontaneous seizures. In this manuscript, we will briefly review the intrinsic severity hypothesis, describe basic and clinical research on HFOs in the epileptic brain, and based on this evidence discuss whether HFOs could be a clinical measure of epilepsy severity. Understanding the mechanisms of DRE is critical for producing breakthroughs in the development and testing of novel strategies for treatment.
Topics: Animals; Brain Waves; Drug Resistant Epilepsy; Electroencephalography; Epilepsy; Seizures
PubMed: 34861102
DOI: 10.1002/epi4.12565 -
Neural Plasticity 2016Spindle oscillations have been described during early brain development and in the adult brain. Besides similarities in temporal patterns and involved brain areas,... (Review)
Review
Spindle oscillations have been described during early brain development and in the adult brain. Besides similarities in temporal patterns and involved brain areas, neonatal spindle bursts (NSBs) and adult sleep spindles (ASSs) show differences in their occurrence, spatial distribution, and underlying mechanisms. While NSBs have been proposed to coordinate the refinement of the maturating neuronal network, ASSs are associated with the implementation of acquired information within existing networks. Along with these functional differences, separate synaptic plasticity mechanisms seem to be recruited. Here, we review the generation of spindle oscillations in the developing and adult brain and discuss possible implications of their differences for synaptic plasticity. The first part of the review is dedicated to the generation and function of ASSs with a particular focus on their role in healthy and impaired neuronal networks. The second part overviews the present knowledge of spindle activity during development and the ability of NSBs to organize immature circuits. Studies linking abnormal maturation of brain wiring with neurological and neuropsychiatric disorders highlight the importance to better elucidate neonatal plasticity rules in future research.
Topics: Adult; Brain; Brain Waves; Humans; Neuronal Plasticity; Sleep; Sleep Stages
PubMed: 27293903
DOI: 10.1155/2016/5787423 -
Current Opinion in Neurobiology Dec 2015Waking and sleeping states are privileged periods for distinct mnemonic processes. In waking behavior, rapid retrieval of previous experience aids memory-guided decision... (Review)
Review
Waking and sleeping states are privileged periods for distinct mnemonic processes. In waking behavior, rapid retrieval of previous experience aids memory-guided decision making. In sleep, a gradual series of reactivated associations supports consolidation of episodes into memory networks. Synchronized bursts of hippocampal place cells during events called sharp-wave ripples communicate associated neural patterns across distributed circuits in both waking and sleeping states. Differences between sleep and awake sharp-wave ripples, and in particular the accuracy of recapitulated experience, highlight their state-dependent roles in memory processes.
Topics: Animals; Brain Waves; Hippocampus; Humans; Memory; Sleep; Wakefulness
PubMed: 26011627
DOI: 10.1016/j.conb.2015.05.001 -
Neural Plasticity 2016Since the advent of EEG recordings, sleep spindles have been identified as hallmarks of non-REM sleep. Despite a broad general understanding of mechanisms of spindle... (Review)
Review
Since the advent of EEG recordings, sleep spindles have been identified as hallmarks of non-REM sleep. Despite a broad general understanding of mechanisms of spindle generation gleaned from animal studies, the mechanisms underlying certain features of spindles in the human brain, such as "global" versus "local" spindles, are largely unknown. Neither the topography nor the morphology of sleep spindles remains constant throughout the lifespan. It is likely that changes in spindle phenomenology during development and aging are the result of dramatic changes in brain structure and function. Across various developmental windows, spindle activity is correlated with general cognitive aptitude, learning, and memory; however, these correlations vary in strength, and even direction, depending on age and metrics used. Understanding these differences across the lifespan should further clarify how these oscillations are generated and their function under a variety of circumstances. We discuss these issues, and their translational implications for human cognitive function. Because sleep spindles are similarly affected in disorders of neurodevelopment (such as schizophrenia) and during aging (such as neurodegenerative conditions), both types of disorders may benefit from therapies based on a better understanding of spindle function.
Topics: Aging; Brain; Brain Waves; Electroencephalography; Humans; Sleep; Sleep Stages
PubMed: 27190654
DOI: 10.1155/2016/6936381 -
BMC Anesthesiology Mar 2019The oculocardiac reflex (OCR), bradycardia that occurs during strabismus surgery is a type of trigemino-cardiac reflex (TCR) is blocked by anticholinergics and enhanced...
BACKGROUND
The oculocardiac reflex (OCR), bradycardia that occurs during strabismus surgery is a type of trigemino-cardiac reflex (TCR) is blocked by anticholinergics and enhanced by opioids and dexmedetomidine. Two recent studies suggest that deeper inhalational anesthesia monitored by BIS protects against OCR; we wondered if our data correlated similarly.
METHODS
In an ongoing, prospective study of OCR/TCR elicited by 10-s, 200 g square-wave traction on extraocular muscles (EOM) from 2009 to 2013, anesthetic depth was estimated in cohorts using either BIS or Narcotrend monitors. The depth of anesthesia was deliberately varied between first and second EOM tested.
RESULTS
From 1992 through 2013, 2833 cases of OCR during strabismus surgery were monitored. Excluding re-operations and cases with anticholinergic, OCR from first EOM traction averaged - 20.2 ± 21.8% (S.D.) with a range from - 95 to + 25% in patients aged 0.2 to 90 (median 6.5) years. We did not find correlation between %OCR and brain wave for 97 patients with BIS monitoring and 91 with Narcotrend. With intra-patient controls between first and second muscle, the difference in brain wave did not correlate with difference in %OCR for BIS (r = 0.0002, 95% C. I -0.0002, 0.002, p = 0.30) or for Narcotrend (r = - 0.001, 95% C. I -0.004, 0.001, p = 0.32). Secondary multi-variable analysis demonstrated significant association on %OCR particularly with BIS monitor, opioid, propofol and nitrous oxide concentration in the second EOM tensioned. Sevoflurane concentration correlated better with BIS monitor in second and third EOM tension. %OCR correlated with younger age (p < 0.01). OCR with rapid onset was more profound than those with gradual onset (difference in means 18, 95% C. I 10, 26%).
CONCLUSIONS
We were unable to confirm a direct correlation between brain wave monitor and OCR when using multifactorial anesthetic agents. The discrepency with other studies probably reflects direct impact of inhalational agent concentration and less deliberate quantification of EOM tension. We found no level of BIS or Entropy EEG monitoring that uniformly prevents OCR.
TRIAL REGISTRY
NCT03663413.
DATA
http://www.abcd-vision.org/OCR/OCR%20Brainwave%20de-identified.pdf .
Topics: Adolescent; Adult; Aged; Aged, 80 and over; Anesthetics, Inhalation; Bradycardia; Brain Waves; Child; Child, Preschool; Consciousness Monitors; Female; Humans; Infant; Male; Middle Aged; Oculomotor Muscles; Prospective Studies; Reflex, Oculocardiac; Sevoflurane; Strabismus; Young Adult
PubMed: 30871507
DOI: 10.1186/s12871-019-0712-z -
NeuroImage Jul 2023Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and...
STUDY OBJECTIVES
Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood.
METHODS
We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N = 21, 10.3 ± 1.5 years old) and young healthy adults (N = 18, 31.1 ± 4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p = 0.05.
RESULTS
The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms.
CONCLUSIONS
Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.
Topics: Adult; Humans; Child; Electroencephalography; Sleep; Neocortex; Brain Waves
PubMed: 37094626
DOI: 10.1016/j.neuroimage.2023.120133 -
International Journal of... Aug 2014This paper presents an overview of historical advances and the current state of genetic psychophysiology, a rapidly developing interdisciplinary research linking... (Review)
Review
This paper presents an overview of historical advances and the current state of genetic psychophysiology, a rapidly developing interdisciplinary research linking genetics, brain, and human behavior, discusses methodological problems, and outlines future directions of research. The main goals of genetic psychophysiology are to elucidate the neural pathways and mechanisms mediating genetic influences on cognition and emotion, identify intermediate brain-based phenotypes for psychopathology, and provide a functional characterization of genes being discovered by large association studies of behavioral phenotypes. Since the initiation of this neurogenetic approach to human individual differences in the 1970s, numerous twin and family studies have provided strong evidence for heritability of diverse aspects of brain function including resting-state brain oscillations, functional connectivity, and event-related neural activity in a variety of cognitive and emotion processing tasks, as well as peripheral psychophysiological responses. These data indicate large differences in the presence and strength of genetic influences across measures and domains, permitting the selection of heritable characteristics for gene finding studies. More recently, candidate gene association studies began to implicate specific genetic variants in different aspects of neurocognition. However, great caution is needed in pursuing this line of research due to its demonstrated proneness to generate false-positive findings. Recent developments in methods for physiological signal analysis, hemodynamic imaging, and genomic technologies offer new exciting opportunities for the investigation of the interplay between genetic and environmental factors in the development of individual differences in behavior, both normal and abnormal.
Topics: Brain; Brain Waves; Genetic Linkage; Genetics; Humans; Psychophysiology; Twin Studies as Topic
PubMed: 24739435
DOI: 10.1016/j.ijpsycho.2014.04.003 -
Frontiers in Neural Circuits 2015Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level,...
Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.
Topics: Adult; Brain Waves; Cerebral Cortex; Female; Humans; Male; Nerve Net; Neuronal Plasticity; Sleep; Young Adult
PubMed: 26578891
DOI: 10.3389/fncir.2015.00062