Project description:Beta oscillations (12-30 Hz) in local field potentials are prevalent in the motor system, yet their functional role within the context of planning a movement is still debated. In this study, a human participant implanted with a multielectrode array in the hand area of primary motor cortex (MI) was instructed to plan a movement using either the second or fourth of five sequentially presented instruction cues. The beta amplitude increased from the start of the trial until the informative (second or fourth) cue, and was diminished afterwards. Moreover, the beta amplitude peaked just prior to each instruction cue and the delta frequency (0.5-1.5 Hz) entrained to the interval between the cues-but only until the informative cue. This result suggests that the beta amplitude and delta phase in MI reflect the subject's engagement with the rhythmically presented cues and work together to enhance sensitivity to predictable and task-relevant visual cues.
Project description:ObjectivesSwitching from maintenance of general anesthesia with an ether anesthetic to maintenance with high-dose (concentration >50% and total gas flow rate >4 liters per minute) nitrous oxide is a common practice used to facilitate emergence from general anesthesia. The transition from the ether anesthetic to nitrous oxide is associated with a switch in the putative mechanisms and sites of anesthetic action. We investigated whether there is an electroencephalogram (EEG) marker of this transition.MethodsWe retrospectively studied the ether anesthetic to nitrous oxide transition in 19 patients with EEG monitoring receiving general anesthesia using the ether anesthetic sevoflurane combined with oxygen and air.ResultsFollowing the transition to nitrous oxide, the alpha (8-12 Hz) oscillations associated with sevoflurane dissipated within 3-12 min (median 6 min) and were replaced by highly coherent large-amplitude slow-delta (0.1-4 Hz) oscillations that persisted for 2-12 min (median 3 min).ConclusionsAdministration of high-dose nitrous oxide is associated with transient, large amplitude slow-delta oscillations.SignificanceWe postulate that these slow-delta oscillations may result from nitrous oxide-induced blockade of major excitatory inputs (NMDA glutamate projections) from the brainstem (parabrachial nucleus and medial pontine reticular formation) to the thalamus and cortex. This EEG signature of high-dose nitrous oxide may offer new insights into brain states during general anesthesia.
Project description: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.
Project description:IntroductionSleep disturbances are common in Alzheimer's disease (AD), with estimates of prevalence as high as 65%. Recent work suggests that specific sleep stages, such as slow-wave sleep (SWS) and rapid eye movement (REM), may directly impact AD pathophysiology. A major limitation to sleep staging is the requirement for clinical polysomnography (PSG), which is often not well tolerated in patients with dementia. We have recently developed a deep learning model to reliably analyze lower quality electroencephalogram (EEG) data obtained from a simple, two-lead EEG headband. Here we assessed whether this methodology would allow for home EEG sleep staging in patients with mild-moderate AD.MethodsA total of 26 mild-moderate AD patients and 24 age-matched, healthy control participants underwent home EEG sleep recordings as well as actigraphy and subjective sleep measures through the Pittsburgh Sleep Quality Index (PSQI). Each participant wore the EEG headband for up to three nights. Sleep was staged using a deep learning model previously developed by our group, and sleep stages were correlated with actigraphy measures as well as PSQI scores.ResultsWe show that home EEG with a headband is feasible and well tolerated in patients with AD. Patients with mild-moderate AD were found to spend less time in SWS compared to healthy control participants. Other sleep stages were not different between the two groups. Actigraphy or the PSQI were not found to predict home EEG sleep stages.DiscussionOur data show that home EEG is well tolerated, and can ascertain reduced SWS in patients with mild-moderate AD. Similar findings have previously been reported, but using clinical PSG not suitable for the home environment. Home EEG will be particularly useful in future clinical trials assessing potential interventions that may target specific sleep stages to alter the pathogenesis of AD.HighlightsHome electroencephalogram (EEG) sleep assessments are important for measuring sleep in patients with dementia because polysomnography is a limited resource not well tolerated in this patient population.Simplified at-home EEG for sleep assessment is feasible in patients with mild-moderate Alzheimer's disease (AD).Patients with mild-moderate AD exhibit less time spent in slow-wave sleep in the home environment, compared to healthy control participants.Compared to healthy control participants, patients with mild-moderate AD spend more time in bed, with decreased sleep efficiency, and more awakenings as measured by actigraphy, but these measures do not correlate with EEG sleep stages.
Project description:ObjectiveSlow-wave activity (SWA) during sleep is reduced in people with amnestic mild cognitive impairment (aMCI) and is related to sleep-dependent memory consolidation. Acoustic stimulation of slow oscillations has proven effective in enhancing SWA and memory in younger and older adults. In this study we aimed to determine whether acoustic stimulation during sleep boosts SWA and improves memory performance in people with aMCI.MethodsNine adults with aMCI (72 ± 8.7 years) completed one night of acoustic stimulation (stim) and one night of sham stimulation (sham) in a blinded, randomized crossover study. Acoustic stimuli were delivered phase-locked to the upstate of the endogenous sleep slow-waves. Participants completed a declarative recall task with 44 word-pairs before and after sleep.ResultsDuring intervals of acoustic stimulation, SWA increased by >10% over sham intervals (P < 0.01), but memory recall increased in only five of the nine patients. The increase in SWA with stimulation was associated with improved morning word recall (r = 0.78, P = 0.012).InterpretationAcoustic stimulation delivered during slow-wave sleep over one night was effective for enhancing SWA in individuals with aMCI. Given established relationships between SWA and memory, a larger or more prolonged enhancement may be needed to consistently improve memory in aMCI.
Project description:During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.
Project description:Slow oscillations are a pattern of synchronized network activity generated by the cerebral cortex. They consist of Up and Down states, which are periods of activity interspersed with periods of silence, respectively. However, even when this is a unique dynamic regime of transitions between Up and Down states, this pattern is not constant: there is a range of oscillatory frequencies (0.1-4 Hz), and the duration of Up vs. Down states during the cycles is variable. This opens many questions. Is there a constant relationship between the duration of Up and Down states? How much do they vary across conditions and oscillatory frequencies? Are there different sub regimes within the slow oscillations? To answer these questions, we aimed to explore a concrete aspect of slow oscillations, Up and Down state durations, across three conditions: deep anesthesia, light anesthesia, and slow-wave sleep (SWS), in the same chronically implanted rats. We found that light anesthesia and SWS have rather similar properties, occupying a small area of the Up and Down state duration space. Deeper levels of anesthesia occupy a larger region of this space, revealing that a large variety of Up and Down state durations can emerge within the slow oscillatory regime. In a network model, we investigated the network parameters that can explain the different points within our bifurcation diagram in which slow oscillations are expressed.
Project description:Spatial memory, among many other brain processes, shows hemispheric lateralization. Most of the published evidence suggests that the right hippocampus plays a leading role in the manipulation of spatial information. Concurrently in the hippocampus, memory consolidation during sleep periods is one of the key steps in the formation of newly acquired spatial memory traces. One of the most characteristic oscillatory patterns in the hippocampus are sharp-wave ripple (SWR) complexes. Within this complex, fast-field oscillations or ripples have been demonstrated to be instrumental in the memory consolidation process. Since these ripples are relevant for the consolidation of memory traces associated with spatial navigation, and this process appears to be lateralized, we hypothesize that ripple events between both hippocampi would exhibit different temporal dynamics. We tested this idea by using a modified "split-hyperdrive" that allows us to record simultaneous LFPs from both right and left hippocampi of Sprague-Dawley rats during sleep. We detected individual events and found that during sleep periods these ripples exhibited a different occurrence patterns between hemispheres. Most ripple events were synchronous between intra- rather than inter-hemispherical recordings, suggesting that ripples in the hippocampus are independently generated and locally propagated within a specific hemisphere. In this study, we propose the ripples' lack of synchrony between left and right hippocampi as the putative physiological mechanism underlying lateralization of spatial memory.
Project description:Sleep has been implicated in both memory consolidation and forgetting of experiences. However, it is unclear what governs the balance between consolidation and forgetting. Here, we tested how activity-dependent processing during sleep might differentially regulate these two processes. We specifically examined how neural reactivations during non-rapid eye movement (NREM) sleep were causally linked to consolidation versus weakening of the neural correlates of neuroprosthetic skill. Strikingly, we found that slow oscillations (SOs) and delta (δ) waves have dissociable and competing roles in consolidation versus forgetting. By modulating cortical spiking linked to SOs or δ waves using closed-loop optogenetic methods, we could, respectively, weaken or strengthen consolidation and thereby bidirectionally modulate sleep-dependent performance gains. We further found that changes in the temporal coupling of spindles to SOs relative to δ waves could account for such effects. Thus, our results indicate that neural activity driven by SOs and δ waves have competing roles in sleep-dependent memory consolidation.
Project description:Accumulating evidence points to neurophysiological abnormalities of the motor cortex in Schizophrenia (SCZ). However, whether these abnormalities represent a core biological feature of psychosis rather than a superimposed neurodegenerative process is yet to be defined, as it is their putative relationship with clinical symptoms. in this study, we used Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) to probe the intrinsic oscillatory properties of motor (Brodmann Area 4, BA4) and non-motor (posterior parietal, BA7) cortical areas in twenty-three first-episode psychosis (FEP) patients and thirteen age and gender-matched healthy comparison (HC) subjects. Patients underwent clinical evaluation at baseline and six-months after the TMS-EEG session. We found that FEP patients had reduced EEG activity evoked by TMS of the motor cortex in the beta-2 (25-34 Hz) frequency band in a cluster of electrodes overlying BA4, relative to HC participants. Beta-2 deficits in the TMS-evoked EEG response correlated with worse positive psychotic symptoms at baseline and also predicted positive symptoms severity at six-month follow-up assessments. Altogether, these findings indicate that reduced TMS-evoked fast oscillatory activity in the motor cortex is an early neural abnormality that: 1) is present at illness onset; 2) may represent a state marker of psychosis; and 3) could play a role in the development of new tools of outcome prediction in psychotic patients.