Regional slow waves and spindles in human sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.     

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring

Background

Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) time series.

Methods & Results

In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD) images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep.

Conclusions

In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.     

Multisensory integration: methodological approaches and emerging principles in the human brain.

Understanding the conditions under which the brain integrates the different sensory streams and the mechanisms supporting this phenomenon is now a question at the forefront of neuroscience. In this paper, we discuss the opportunities for investigating these multisensory processes using modern imaging techniques, the nature of the information obtainable from each method and their benefits and limitations. Despite considerable variability in terms of paradigm design and analysis, some consistent findings are beginning to emerge. The detection of brain activity in human neuroimaging studies that resembles multisensory integration responses at the cellular level in other species, suggests similar crossmodal binding mechanisms may be operational in the human brain. These mechanisms appear to be distributed across distinct neuronal networks that vary depending on the nature of the shared information between different sensory cues. For example, differing extents of correspondence in time, space or content seem to reliably bias the involvement of different integrative networks which code for these cues. A combination of data obtained from haemodynamic and electromagnetic methods, which offer high spatial or temporal resolution respectively, are providing converging evidence of multisensory interactions at both "early" and "late" stages of processing--suggesting a cascade of synergistic processes operating in parallel at different levels of the cortex.     

Spectral fingerprints of large-scale neuronal interactions

Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.     

Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.     

Decreased Resting Functional Connectivity after Traumatic Brain Injury in the Rat

Traumatic brain injury (TBI) contributes to about 10% of acquired epilepsy. Even though the mechanisms of post-traumatic epileptogenesis are poorly known, a disruption of neuronal networks predisposing to altered neuronal synchrony remains a viable candidate mechanism. We tested a hypothesis that resting state BOLD-fMRI functional connectivity can reveal network abnormalities in brain regions that are connected to the lesioned cortex, and that these changes associate with functional impairment, particularly epileptogenesis. TBI was induced using lateral fluid-percussion injury in seven adult male Sprague-Dawley rats followed by functional imaging at 9.4T 4 months later. As controls we used six sham-operated animals that underwent all surgical operations but were not injured. Electroencephalogram (EEG)-functional magnetic resonance imaging (fMRI) was performed to measure resting functional connectivity. A week after functional imaging, rats were implanted with bipolar skull electrodes. After recovery, rats underwent pentyleneterazol (PTZ) seizure-susceptibility test under EEG. For image analysis, four pairs of regions of interests were analyzed in each hemisphere: ipsilateral and contralateral frontal and parietal cortex, hippocampus, and thalamus. High-pass and low-pass filters were applied to functional imaging data. Group statistics comparing injured and sham-operated rats and correlations over time between each region were calculated. In the end, rats were perfused for histology. None of the rats had epileptiform discharges during functional imaging. PTZ-test, however revealed increased seizure susceptibility in injured rats as compared to controls. Group statistics revealed decreased connectivity between the ipsilateral and contralateral parietal cortex and between the parietal cortex and hippocampus on the side of injury as compared to sham-operated animals. Injured animals also had abnormal negative connectivity between the ipsilateral and contralateral parietal cortex and other regions. Our data provide the first evidence on abnormal functional connectivity after experimental TBI assessed with resting state BOLD-fMRI.     

Modeling the effect of sleep regulation on a neural mass model

In mammals, sleep is categorized by two main sleep stages, rapid eye movement (REM) and non-REM (NREM) sleep that are known to fulfill different functional roles, the most notable being the consolidation of memory. While REM sleep is characterized by brain activity similar to wakefulness, the EEG activity changes drastically with the emergence of K-complexes, sleep spindles and slow oscillations during NREM sleep. These changes are regulated by circadian and ultradian rhythms, which emerge from an intricate interplay between multiple neuronal populations in the brainstem, forebrain and hypothalamus and the resulting varying levels of neuromodulators. Recently, there has been progress in the understanding of those rhythms both from a physiological as well as theoretical perspective. However, how these neuromodulators affect the generation of the different EEG patterns and their temporal dynamics is poorly understood. Here, we build upon previous work on a neural mass model of the sleeping cortex and investigate the effect of those neuromodulators on the dynamics of the cortex and the corresponding transition between wakefulness and the different sleep stages. We show that our simplified model is sufficient to generate the essential features of human EEG over a full day. This approach builds a bridge between sleep regulatory networks and EEG generating neural mass models and provides a valuable tool for model validation.     

Communication through Resonance in Spiking Neuronal Networks

The cortex processes stimuli through a distributed network of specialized brain areas. This processing requires mechanisms that can route neuronal activity across weakly connected cortical regions. Routing models proposed thus far are either limited to propagation of spiking activity across strongly connected networks or require distinct mechanisms that create local oscillations and establish their coherence between distant cortical areas. Here, we propose a novel mechanism which explains how synchronous spiking activity propagates across weakly connected brain areas supported by oscillations. In our model, oscillatory activity unleashes network resonance that amplifies feeble synchronous signals and promotes their propagation along weak connections (“communication through resonance”). The emergence of coherent oscillations is a natural consequence of synchronous activity propagation and therefore the assumption of different mechanisms that create oscillations and provide coherence is not necessary. Moreover, the phase-locking of oscillations is a side effect of communication rather than its requirement. Finally, we show how the state of ongoing activity could affect the communication through resonance and propose that modulations of the ongoing activity state could influence information processing in distributed cortical networks.     

Early network activity propagates bidirectionally between hippocampus and cortex

Spontaneous activity in the developing brain helps refine neuronal connections before the arrival of sensory‐driven neuronal activity. In mouse neocortex during the first postnatal week, waves of spontaneous activity originating from pacemaker regions in the septal nucleus and piriform cortex propagate through the neocortex. Using high‐speed Ca²⁺ imaging to resolve the spatiotemporal dynamics of wave propagation in parasagittal mouse brain slices, we show that the hippocampus can act as an additional source of neocortical waves. Some waves that originate in the hippocampus remain restricted to that structure, while others pause at the hippocampus‐neocortex boundary and then propagate into the neocortex. Blocking GABAergic neurotransmission decreases the likelihood of wave propagation into neocortex, whereas blocking glutamatergic neurotransmission eliminates spontaneous and evoked hippocampal waves. A subset of hippocampal and cortical waves trigger Ca²⁺ waves in astrocytic networks after a brief delay. Hippocampal waves accompanied by Ca²⁺ elevation in astrocytes are more likely to propagate into the neocortex. Finally, we show that two structures in our preparation that initiate waves—the hippocampus and the piriform cortex—can be electrically stimulated to initiate propagating waves at lower thresholds than the neocortex, indicating that the intrinsic circuit properties of those regions are responsible for their pacemaker function. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 76: 661–672, 2016     

Changes in P3b Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task

Learning is not a unitary phenomenon. Rather, learning progresses through stages, with the stages reflecting different challenges that require the support of specific cognitive processes that reflect the functions of different brain networks. A theory of general learning proposes that learning can be divided into early and late stages controlled by corticolimbic networks located in frontal and posterior brain regions, respectively. Recent human studies using dense-array EEG (dEEG) support these results by showing progressive increases in P3b amplitude (an Event Related Potential with estimated sources in posterior cingulate cortex and hippocampus) as participants acquire a new visuomotor skill. In the present study, the P3b was used to track the learning and performance of participants as they identify defensive football formations and make an appropriate response. Participants acquired the task over three days, and P3b latency and amplitude significantly changed when participants learned the task. As participants demonstrated further proficiency with extensive training, amplitude and latency changes in the P3b continued to closely mirror performance improvements. Source localization results across all days suggest that an important source generator of the P3b is located in the posterior cingulate cortex. Results from the study support prior findings and further suggest that the careful analysis of covert learning mechanisms and their underlying electrical signatures are a robust index of task competency.     

Electrical Pacing of Cardiac Tissue Including Potassium Inward Rectification

In this study cardiac tissue is stimulated electrically through a small unipolar electrode. Numerical simulations predict that around an electrode are adjacent regions of depolarization and hyperpolarization. Experiments have shown that during pacing of resting cardiac tissue the hyperpolarization is often inhibited. Our goal is to determine if the inward rectifying potassium current (I_K1) causes the inhibition of hyperpolarization. Numerical simulations were carried out using the bidomain model with potassium dynamics specified to be inward rectifying. In the simulations, adjacent regions of depolarization and hyperpolarization were observed surrounding the electrode. For cathodal currents the virtual anode produces a hyperpolarization that decreases over time. For long duration pulses the current-voltage curve is non-linear, with very small hyperpolarization compared to depolarization. For short pulses, the hyperpolarization is more prominent. Without the inward potassium rectification, the current voltage curve is linear and the hyperpolarization is evident for both long and short pulses. In conclusion, the inward rectification of the potassium current explains the inhibition of hyperpolarization for long duration stimulus pulses, but not for short duration pulses.     

Mapping the structural core of human cerebral cortex

Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.     

Stochastic resonance modulates neural synchronization within and between cortical sources

Neural synchronization is a mechanism whereby functionally specific brain regions establish transient networks for perception, cognition, and action. Direct addition of weak noise (fast random fluctuations) to various neural systems enhances synchronization through the mechanism of stochastic resonance (SR). Moreover, SR also occurs in human perception, cognition, and action. Perception, cognition, and action are closely correlated with, and may depend upon, synchronized oscillations within specialized brain networks. We tested the hypothesis that SR-mediated neural synchronization occurs within and between functionally relevant brain areas and thus could be responsible for behavioral SR. We measured the 40-Hz transient response of the human auditory cortex to brief pure tones. This response arises when the ongoing, random-phase, 40-Hz activity of a group of tuned neurons in the auditory cortex becomes synchronized in response to the onset of an above-threshold sound at its "preferred" frequency. We presented a stream of near-threshold standard sounds in various levels of added broadband noise and measured subjects' 40-Hz response to the standards in a deviant-detection paradigm using high-density EEG. We used independent component analysis and dipole fitting to locate neural sources of the 40-Hz response in bilateral auditory cortex, left posterior cingulate cortex and left superior frontal gyrus. We found that added noise enhanced the 40-Hz response in all these areas. Moreover, added noise also increased the synchronization between these regions in alpha and gamma frequency bands both during and after the 40-Hz response. Our results demonstrate neural SR in several functionally specific brain regions, including areas not traditionally thought to contribute to the auditory 40-Hz transient response. In addition, we demonstrated SR in the synchronization between these brain regions. Thus, both intra- and inter-regional synchronization of neural activity are facilitated by the addition of moderate amounts of random noise. Because the noise levels in the brain fluctuate with arousal system activity, particularly across sleep-wake cycles, optimal neural noise levels, and thus SR, could be involved in optimizing the formation of task-relevant brain networks at several scales under normal conditions.     

Human cortical traveling waves: dynamical properties and correlations with responses

The spatiotemporal behavior of human EEG oscillations is investigated. Traveling waves in the alpha and theta ranges are found to be common in both prestimulus and poststimulus EEG activity. The dynamical properties of these waves, including their speeds, directions, and durations, are systematically characterized for the first time, and the results show that there are significant changes of prestimulus spontaneous waves in the presence of an external stimulus. Furthermore, the functional relevance of these waves is examined by studying how they are correlated with reaction times on a single trial basis; prestimulus alpha waves traveling in the frontal-to-occipital direction are found to be most correlated to reaction speeds. These findings suggest that propagating waves of brain oscillations might be involved in mediating long-range interactions between widely distributed parts of human cortex.     

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model.     

Aging alters regional multichemical profile of the human brain: an in vivo 1H-MRS study of young versus middle-aged subjects

Age-related differences in the multichemical proton magnetic resonance spectroscopy (1H-MRS) profile of the human brain have been reported for several age groups, and most consistently for ages from neonates to 16-year-olds. Our recent 1H-MRS study demonstrated a significant age-related increase of total chemical concentration (relative to creatine) in the prefrontal and sensorimotor cortices within young adulthood (19-31-year-olds). In the present study we test the hypothesis that the level of brain chemicals in the same cortices, which show increased chemical levels during normal development, are reduced with normal aging after young adulthood. The multichemical 1H-MRS profile of the brain was compared between 19 young and 16 middle-aged normal subjects across multiple brain regions for all chemicals of 1H-MRS spectra. Chemical concentrations were measured relative to creatine. Over all age groups the total relative chemical concentration was highest in the prefrontal cortex. Middle-aged subjects demonstrated a significant decrease of total relative chemical concentration in the dorsolateral prefrontal (F = 54.8, p < 10(-7), ANOVA), orbital frontal (F = 3.7, p < 0.05) and sensorimotor (F = 15.1, p < 0.0001) cortices, as compared with younger age. Other brain regions showed no age-dependent differences. The results indicate that normal aging alters multichemical 1H-MRS profile of the human brain and that these changes are region-specific, with the largest changes occuring in the dorsolateral prefrontal cortex. These findings provide evidence that the processes of neuronal maturation of the human brain, and neurotransmitters and other chemical changes as the marker of these neuronal changes are almost finished by young adulthood and then reduced during normal aging toward middle age period of life. The present data also support the notion of heterochronic regressive changes of the aging human brain, where the multichemical brain regional profile seems to inversely recapitulate cortical chemical maturation within normal development.     

A review of EEG and MEG for brainnetome research

The majority of brain activities are performed by functionally integrating separate regions of the brain. Therefore, the synchronous operation of the brain’s multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links. Because of the complexity of brain interactions and their varying effects at different levels of complexity, one of the corresponding authors of this paper recently proposed the brainnetome as a new –ome to explore and integrate the brain network at different scales. Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics of neuronal connections, they lend themselves to the analysis of the neural networks comprising the brainnetome. Because of EEG/MEG’s applicability to brainnetome analyses, the aim of this review is to identify the procedures that can be used to form a network using EEG/MEG data in sensor or source space and to promote EEG/MEG network analysis for either neuroscience or clinical applications. To accomplish this aim, we show the relationship of the brainnetome to brain networks at the macroscale and provide a systematic review of network construction using EEG and MEG. Some potential applications of the EEG/MEG brainnetome are to use newly developed methods to associate the properties of a brainnetome with indices of cognition or disease conditions. Associations based on EEG/MEG brainnetome analysis may improve the comprehension of the functioning of the brain in neuroscience research or the recognition of abnormal patterns in neurological disease.     

Mapping human brain networks with cortico-cortical evoked potentials

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex.     

Bilaterally propagating waves of spontaneous activity arising from discrete pacemakers in the neonatal mouse cerebral cortex

Spontaneous electrical activity that moves in synchronized waves across large populations of neurons plays widespread and important roles in nervous system development. The propagation patterns of such waves can encode the spatial location of neurons to their downstream targets and strengthen synaptic connections in coherent spatial patterns. Such waves can arise as an emergent property of mutually excitatory neural networks, or can be driven by a discrete pacemaker. In the mouse cerebral cortex, spontaneous synchronized activity occurs for approximately 72 h of development centered on the day of birth. It is not known whether this activity is driven by a discrete pacemaker or occurs as an emergent network property. Here we show that this activity propagates as a wave that is initiated at either of two homologous pacemakers in the temporal region, and then propagates rapidly across both sides of the brain. When these regions of origin are surgically isolated, waves do not occur. Therefore, this cortical spontaneous activity is a bilateral wave that originates from a discrete subset of pacemaker neurons. © 2009 Wiley Periodicals, Inc. Develop Neurobiol, 2009