Sleep-related modifications of EEG connectivity in the sensory-motor networks in Huntington Disease: An eLORETA study and review of the literature

Repeated Transcranial Photobiomodulation with Light-Emitting Diodes Improves Psychomotor Vigilance and EEG Networks of the Human Brain

Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group's singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.

Neurophysiological correlates of non-motor symptoms in late premanifest and early-stage manifest huntington's disease

OBJECTIVE

To find sensitive neurophysiological correlates of non-motor symptoms in Huntington's disease (HD), which are essential for the development and assessment of novel treatments.

METHODS

We used resting state EEG to examine differences in oscillatory activity (analysing the isolated periodic as well as the complete EEG signal) and functional connectivity in 22 late premanifest and early stage people with HD and 20 neurotypical controls. We then assessed the correlations between these neurophysiological markers and clinical measures of apathy and processing speed.

RESULTS

Significantly lower theta and greater delta resting state power was seen in the HD group, as well as significantly greater delta connectivity. There was a significant positive correlation between theta power and processing speed, however there were no associations between the neurophysiological and apathy measures.

CONCLUSIONS

We speculate that these changes in oscillatory power and connectivity reflect ongoing, frontally concentrated degenerative and compensatory processes associated with HD.

SIGNIFICANCE

Our findings support the potential utility of quantitative EEG as a proximate marker of processing speed, but not apathy in HD.

Sleep Disorders in Patients with Choreic Syndromes

PURPOSE OF REVIEW

Patients with different types of choreic syndromes, specially those with Huntington's (HD) and Wilson's (WD) diseases, report frequent sleep complaints. This review focuses on the main findings of studies addressing the sleep features in these diseases, and other less frequent causes of chorea associated with sleep disorders, including a new syndrome described in the last decade associated with IgLON5 antibodies.

RECENT FINDINGS

Patients with HD and WD showed a bad quality of sleep and high frequency of insomnia and excessive daytime somnolence. WD patients also showed high scores on a specific scale for rapid eye movement sleep behavior disorders. HD and WD share decreased sleep efficiency and increased REM sleep latencies, percentage of sleep stage N1, and wake after sleep onset (WASO) among their polysomnographic features. Patients with HD and WD showed a high prevalence of different sleep disorders. Patients with other causes of chorea, including neuroacanthocytosis, parasomnia with sleep breathing disorder associated with antibodies to IgLON5, Sydenham's chorea, and choreic syndromes associated to certain genetic mutations show sleep disorders as well.

Medial prefrontal transcranial alternating current stimulation for apathy in Huntington's disease

We investigated the effects of transcranial alternating current stimulation (tACS) targeted to the bilateral medial prefrontal cortex (mPFC) and administered at either delta or alpha frequencies, on brain activity and apathy in people with Huntington's disease (HD) (n = 17). Given the novelty of the protocol, neurotypical controls (n = 20) were also recruited. All participants underwent three 20-min sessions of tACS; one session at alpha frequency (Individualised Alpha Frequency (IAF), or 10 Hz when an IAF was not detected); one session at delta frequency (2 Hz); and a session of sham tACS. Participants completed the Monetary Incentive Delay (MID) task with simultaneous recording of EEG immediately before and after each tACS condition. The MID task presents participants with cues signalling potential monetary gains or losses that increase activity in key regions of the cortico-basal ganglia-thalamocortical networks, with dysfunction of the latter network being implicated in the pathophysiology of apathy. We used the P300 and Contingent Negative Variation (CNV) event-related potentials elicited during the MID task as markers of mPFC engagement. HD participants' CNV amplitude significantly increased in response to alpha-tACS, but not delta-tACS or sham. Neurotypical controls' P300 and CNV were not modulated by any of the tACS conditions, but they did demonstrate a significant decrease in post-target response times following alpha-tACS. We present this as preliminary evidence of the ability of alpha-tACS to modulate brain activity associated with apathy in HD.

Spatio-temporal dynamics of resting-state brain networks are associated with migraine disability

OBJECTIVE

The changes in resting-state functional networks and their correlations with clinical traits remain to be clarified in migraine. Here we aim to investigate the brain spatio-temporal dynamics of resting-state networks and their possible correlations with the clinical traits in migraine.

METHODS

Twenty Four migraine patients without aura and 26 healthy controls (HC) were enrolled. Each included subject underwent a resting-state EEG and echo planar imaging examination. The disability of migraine patients was evaluated by Migraine Disability Assessment (MIDAS). After data acquisition, EEG microstates (Ms) combining functional connectivity (FC) analysis based on Schafer 400-seven network atlas were performed. Then, the correlation between obtained parameters and clinical traits was investigated.

RESULTS

Compared with HC group, the brain temporal dynamics depicted by microstates showed significantly increased activity in functional networks involving MsB and decreased activity in functional networks involving MsD; The spatial dynamics were featured by decreased intra-network FC within the executive control network( ECN) and inter-network FC between dorsal attention network (DAN) and ECN (P < 0.05); Moreover, correlation analysis showed that the MIDAS score was positively correlated with the coverage and duration of MsC, and negatively correlated with the occurrence of MsA; The FC within default mode network (DMN), and the inter-FC of ECN- visual network (VN), ECN- limbic network, VN-limbic network was negatively correlated with MIDAS. However, the FC of DMN-ECN was positively correlated with MIDAS; Furthermore, significant interactions between the temporal and spatial dynamics were also obtained.

CONCLUSIONS

Our study confirmed the notion that altered spatio-temporal dynamics exist in migraine patients during resting-state. And the temporal dynamics, the spatial changes and the clinical traits such as migraine disability interact with each other. The spatio-temporal dynamics obtained from EEG microstate and fMRI FC analyses may be potential biomarkers for migraine and with a huge potential to change future clinical practice in migraine.

Sleep and Circadian Rhythm Dysfunction in Animal Models of Huntington's Disease

Sleep and circadian disruption affects most individuals with Huntington's disease (HD) at some stage in their lives. Sleep and circadian dysregulation are also present in many mouse and the sheep models of HD. Here I review evidence for sleep and/or circadian dysfunction in HD transgenic animal models and discuss two key questions: 1) How relevant are such findings to people with HD, and 2) Whether or not therapeutic interventions that ameliorate deficits in animal models of HD might translate to meaningful therapies for people with HD.

Sleep, Circadian Rhythms, and Cognitive Dysfunction in Huntington's Disease

BACKGROUND

In healthy people, sleep and circadian disruption are linked to cognitive deficits. People with Huntington's disease (HD), who have compromised brain function and sleep and circadian disturbances, may be even more susceptible to these cognitive effects.

OBJECTIVE

To conduct a comprehensive review and synthesis of the literature in HD on the associations of cognitive dysfunction with disturbed sleep and circadian rhythms.

METHODS

We searched MEDLINE via OVID, CINAHL Plus, EMBASE via OVID, and PubMed in May 2023. The first author then screened by title and abstract and conducted a full review of remaining articles.

RESULTS

Eight studies investigating the influence of sleep and/or circadian rhythms on cognitive function in HD were found. In manifest HD, poorer sleep was associated with worse cognitive function. For behavioral 24-hour (circadian) rhythms, two studies indicated that later wake times correlated with poorer cognitive function. No reported studies in HD examined altered physiological 24-hour (circadian) rhythms and cognitive impairment.

CONCLUSION

Some associations exist between poor sleep and cognitive dysfunction in manifest HD, yet whether these associations are present before clinical diagnosis is unknown. Whether circadian disturbances relate to cognitive impairment in HD also remains undetermined. To inform sleep and circadian interventions aimed at improving cognitive symptoms in HD, future research should include a range of disease stages, control for external factors, and utilize robust cognitive batteries targeted to the aspects of cognitive function known to be adversely affected in HD.

Sleep Alterations in a Mouse Model of Spinocerebellar Ataxia Type 3

Spinocerebellar ataxia type 3 (SCA3) is a neurodegenerative disorder showing progressive neuronal loss in several brain areas and a broad spectrum of motor and non-motor symptoms, including ataxia and altered sleep. While sleep disturbances are known to play pathophysiologic roles in other neurodegenerative disorders, their impact on SCA3 is unknown. Using spectrographic measurements, we sought to quantitatively characterize sleep electroencephalography (EEG) in SCA3 transgenic mice with confirmed disease phenotype. We first measured motor phenotypes in 18-31-week-old homozygous SCA3 YACMJD84.2 mice and non-transgenic wild-type littermate mice during lights-on and lights-off periods. We next implanted electrodes to obtain 12-h (zeitgeber time 0-12) EEG recordings for three consecutive days when the mice were 26-36 weeks old. EEG-based spectroscopy showed that compared to wild-type littermates, SCA3 homozygous mice display: (i) increased duration of rapid-eye movement sleep (REM) and fragmentation in all sleep and wake states; (ii) higher beta power oscillations during REM and non-REM (NREM); and (iii) additional spectral power band alterations during REM and wake. Our data show that sleep architecture and EEG spectral power are dysregulated in homozygous SCA3 mice, indicating that common sleep-related etiologic factors may underlie mouse and human SCA3 phenotypes.

Electroencephalogram microstates and functional connectivity of cybersickness

Virtual reality (VR) is a rapidly developing technology that simulates the real world. However, for some cybersickness-susceptible people, VR still has an unanswered problem-cybersickness-which becomes the main obstacle for users and content makers. Sensory conflict theory is a widely accepted theory for cybersickness. It proposes that conflict between afferent signals and internal models can cause cybersickness. This study analyzes the brain states that determine cybersickness occurrence and related uncomfortable feelings. Furthermore, we use the electroencephalogram (EEG) microstates and functional connectivity approach based on the sensory conflict theory. The microstate approach is a time-space analysis method that allows signals to be divided into several temporarily stable states, simultaneously allowing for the exploration of short- and long-range signals. These temporal dynamics can show the disturbances in mental processes associated with neurological and psychiatric conditions of cybersickness. Furthermore, the functional connectivity approach gives us in-depth insight and relationships between the sources related to cybersickness. We recruited 40 males (24.1 ± 2.3 years), and they watched a VR video on a curved computer monitor for 10 min to experience cybersickness. We recorded the 5-min resting state EEG (baseline condition) and 10-min EEG while watching the VR video (task condition). Then, we performed a microstate analysis, focusing on two temporal parameters: mean duration and global explained variance (GEV). Finally, we obtained the functional connectivity data using eLoreta and lagged phase synchronization (LPS). We discovered five sets of microstates (A-E), including four widely reported canonical microstates (A-D), during baseline and task conditions. The average duration increased in microstates A and B, which is related to the visual and auditory networks. The GEV and duration decreased in microstate C, whereas those in microstate D increased. Microstate C is related to the default mode network (DMN) and D to the attention network. The temporal dynamics of the microstate parameters are from cybersickness disturbing the sensory, DMN, and attention networks. In the functional connectivity part, the LPS between the left and right parietal operculum (OP) significantly decreased (p < 0.05) compared with the baseline condition. Furthermore, the connectivity between the right OP and V5 significantly decreased (p < 0.05). These results also support the disturbance of the sensory network because a conflict between the visual (V5) and vestibular system (OP) causes cybersickness. Changes in the microstates and functional connectivity support the sensory conflict theory. These results may provide additional information in understanding brain dynamics during cybersickness.

Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation

Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm². In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.

Abnormal patterns of sleep and EEG power distribution during non-rapid eye movement sleep in the sheep model of Huntington's disease

Sleep disruption is a common invisible symptom of neurological dysfunction in Huntington's disease (HD) that takes an insidious toll on well-being of patients. Here we used electroencephalography (EEG) to examine sleep in 6 year old OVT73 transgenic sheep (Ovis aries) that we used as a presymptomatic model of HD. We hypothesized that despite the lack of overt symptoms of HD at this age, early alterations of the sleep-wake pattern and EEG powers may already be present. We recorded EEG from female transgenic and normal sheep (5/group) during two undisturbed 'baseline' nights with different lighting conditions. We then recorded continuously through a night of sleep disruption and the following 24 h (recovery day and night). On baseline nights, regardless of whether the lights were on or off, transgenic sheep spent more time awake than normal sheep particularly at the beginning of the night. Furthermore, there were significant differences between transgenic and normal sheep in both EEG power and its pattern of distribution during non-rapid eye movement (NREM) sleep. In particular, there was a significant decrease in delta (0.5-4 Hz) power across the night in transgenic compared to normal sheep, and the distributions of delta, theta and alpha oscillations that typically dominate the EEG in the first half of the night of normal sheep were skewed so they were predominant in the second, rather than the first half of the night in transgenic sheep. Interestingly, the effect of sleep disruption on normal sheep was also to skew the pattern of distribution of EEG powers so they looked more like that of transgenic sheep under baseline conditions. Thus it is possible that transgenic sheep exist in a state that resemble a chronic state of physiological sleep deprivation. During the sleep recovery period, normal sheep showed a significant 'rebound' increase in delta power with frontal dominance. A similar rebound was not seen in transgenic sheep, suggesting that their homeostatic response to sleep deprivation is abnormal. Although sleep abnormalities in early stage HD patients are subtle, with patients often unaware of their existence, they may contribute to impairment of neurological function that herald the onset of disease. A better understanding of the mechanisms underlying EEG abnormalities in early stage HD would give insight into how, and when, they progress into the sleep disorder. The transgenic sheep model is ideally positioned for studies of the earliest phase of disease when sleep abnormalities first emerge.

EEG Functional Connectivity and Cognitive Variables in Premanifest and Manifest Huntington's Disease: EEG Low-Resolution Brain Electromagnetic Tomography (LORETA) Study

Background

Scientific literature does not offer sufficient data on electroencephalography (EEG) functional connectivity and its correlations with clinical and cognitive features in premanifest and manifest HD.

Aim

This study tries to identify abnormal EEG patterns of functional connectivity, in conditions of “brain resting state” and correlations with motor decline and cognitive variable in Huntington’s disease (HD), in premanifest and manifest phase, looking for a reliable marker measuring disease progression.

Method

This was an observational cross-sectional study; 105 subjects with age ≥18 years submitted to HD genetic test. Each subject underwent a neurological, psychiatric, and cognitive assessment, EEG recording and genetic investigation for detecting the expansion of the CAG trait. EEG connectivity analysis was performed by means of exact Low Resolution Electric Tomography (eLORETA) in 18 premanifest HD (pHD), 49 manifest HD (mHD), and 38 control (C) subjects.

Results

HD patients showed a Power Spectral Density reduced in the alpha range and increased in delta band compared to controls; no difference was detectable between pHD and mHD; the Global Connectivity in pHD revealed no significant differences if compared to mHD. The Current Source Density was similar among groups. No statistically significant results when comparing pHD with C group, even in comparison of mHD with Controls, and pHD with mHD. mHD compared to Controls showed a significant increase in delta, alpha1, alpha2, beta2, and beta3. Lagged Phase Synchronization in delta, alpha1, alpha2, beta2, and beta3 bands was increased in HD compared to controls (t = −3.921, p < 0.05). A significant correlation was found in Regression Analysis: statistically significant results in pHD for the “Symbol Digit Modality Test and lagged phase synchronization” in the Beta1 (r = −0.806, p < 0.05) in the prefrontal regions. The same correlation was found in mHD for the Stroop Word Reading Test (SWRT) in the Alpha2 band (r = −0.759, p < 0.05).

Conclusion

Increased phase synchronization in main bands characterized EEG in HD patients, as compared to controls. pHD were not dissimilar from mHD as regard to this EEG pattern. Increased phase synchronization correlated to cognitive decline in HD patients, with a similar trend in pHD, suggesting that it would be a potential biomarker of early phenotypical expression.

EEG Resting-State Networks Responsible for Gait Disturbance Features in Idiopathic Normal Pressure Hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric disease characterized by gait disturbance, cognitive dysfunction, and urinary incontinence that affects a large population of elderly people. These symptoms, especially gait disturbance, can potentially be improved by cerebrospinal fluid (CSF) drainage, which is more effective if performed at an early stage of the disease. However, the neurophysiological mechanisms of these symptoms and their recovery by CSF drainage are poorly understood. In this study, using exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) with electroencephalography (EEG) data, we assessed activities of five EEG resting-state networks (EEG-RSNs) in 58 iNPH patients before and after drainage of CSF by lumbar puncture (CSF tapping). In addition, we assessed correlations of changes in these five EEG-RSNs activities with CSF tapping-induced changes in iNPH symptoms. The results reveal that compared with 80 healthy controls, iNPH patients had significantly decreased activities in the occipital alpha rhythm, visual perception network, and self-referential network before CSF tapping. Furthermore, CSF tapping-induced changes in occipital alpha activity correlated with changes in postural sway and frontal lobe function. Changes in visual perception network activity correlated with changes in gait speed. In addition, changes in memory perception network activity correlated with changes in Parkinsonian gait features. These results indicate a recruitment of cognitive networks in gait control, and involvement of the occipital alpha activity in cognitive dysfunction in iNPH patients. Based on these findings, eLORETA-ICA with EEG data can be considered a noninvasive, useful tool for detection of EEG-RSN activities and for understanding the neurophysiological mechanisms underlying this disease.

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

BACKGROUND

Dementia with Lewy bodies (DLB) is characterized by progressive cognitive decline, fluctuating cognition, visual hallucinations, rapid eye movement sleep behavior disorder, and parkinsonism. DLB is the second most common type of degenerative dementia of all dementia cases. However, DLB, particularly in the early stage, is underdiagnosed and sometimes misdiagnosed with other types of dementia. Thus, it is of great interest investigating neurophysiological markers of DLB.

METHOD

We introduced exact low-resolution brain electromagnetic tomography (eLORETA)-independent component analysis (ICA) to assess activities of 5 electroencephalography (EEG) resting-state networks (RSNs) in 41 drug-free DLB patients.

RESULTS

Compared to 80 healthy controls, DLB patients had significantly decreased activities in occipital visual and sensorimotor networks, where DLB patients and healthy controls showed no age dependences in all EEG-RSN activities. Also, we found correlations between all EEG-RSN activities and DLB symptoms. Specifically, decreased occipital α activity showed correlations with worse brain functions related to attention/concentration, visuospatial discrimination, and global cognition. Enhanced visual perception network activity correlated with milder levels of depression and anxiety. Enhanced self-referential network activity correlated with milder levels of depression. Enhanced memory perception network activity correlated with better semantic memory, visuospatial discrimination function, and global cognitive function as well as with severer visual hallucination. In addition, decreased sensorimotor network activity correlated with a better semantic memory.

CONCLUSION

These results indicate that eLORETA-ICA can detect EEG-RSN activity alterations in DLB related to symptoms. Therefore, eLORETA-ICA with EEG data can be a useful noninvasive tool for sensitive detection of EEG-RSN activity changes characteristic of DLB and for understanding the neurophysiological mechanisms underlying this disease.