Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease

Beta-band oscillations and spike-local field potential synchronization in the motor cortex are correlated with movement deficits in an exercise-induced fatigue mouse model

Fatigue, a complex and multifaceted symptom, profoundly influences quality of life, particularly among individuals suffering from chronic medical conditions or neurological disorders. This symptom not only exacerbates existing conditions but also hinders daily functioning, thereby perpetuating a vicious cycle of worsening symptoms and reduced physical activity. Given the pivotal role of the motor cortex (M1) in coordinating and executing voluntary movements, understanding how the cortex regulates fatigue is crucial. Despite its importance, the neural mechanisms underlying fatigue remain inadequately explored. In this study, we employed electrophysiological recordings in the M1 region of mice to investigate how excitation-inhibition dynamics and neural oscillations are regulated during exercise-induced fatigue. We observed that fatigue led to decreased voluntary physical activity and cognitive performance, manifesting as reduced running wheel distance, mean speed, exercise intensity, and exploratory behaviour. At the neural level, we detected increased firing frequencies for M1 neurons, including both pyramidal neurons and interneurons, along with heightened beta-band oscillatory activity and stronger coupling between beta-band oscillations and interneurons. These findings enhance our understanding of the mechanisms underlying fatigue, offering insights into behavioural, excitability, and oscillatory changes. The results of this study could pave the way for the development of novel intervention strategies to combat fatigue.

Differentiation with electroencephalography microstate in temporal lobe epilepsy with and without cognitive decline

OBJECTIVE

Electroencephalography (EEG) microstate analysis is widely used in the study of various neurological and psychiatric disorders. We aim to assess whether EEG microstates are altered in TLE patients with and without cognitive decline.

METHODS

This study included a total of 47 temporal lobe epilepsy (TLE) patients with or without cognitive decline and 14 healthy controls (HCs). All participants underwent 64-channel EEG monitoring. Two-minute epochs of preprocessed eye closed awake EEG data were extracted for microstate analysis. Participants were divided into groups based on intelligence quotient (IQ) scores assessed by the Wechsler Intelligence Scale: normal cognition group (n = 23, IQ ≥ 90) and abnormal cognition group (n = 24, IQ < 90). We conducted frequency spectral analysis on each frequency sub-bands (delta, 1-4 Hz; theta, 4-8 Hz; alpha, 8-12 Hz; beta, 12-30 Hz) of the three groups. Then the following microstate parameters were extracted for analysis over the full frequency band (1-30 Hz) and frequency sub-bands: duration, coverage, occurrence, and transition probability. Statistical analysis using multivariate analysis of variance (MANOVA) with Bonferroni correction (α = 0.0025).

RESULT

Microstate analysis in the beta sub-band revealed significant differences among groups. TLE patients with abnormal cognition showed increased occurrence of Map-D; significantly higher transition probabilities from Map-A, Map-B, and Map-C to Map-D; and distinct microstate characteristics compared to patients with normal cognition and HCs. In frequency spectral analysis, the power across all frequency sub-bands showed no significant differences among TLE patients with normal cognition, TLE patients with abnormal cognition, and HCs.

CONCLUSION

Beta sub-band EEG microstates, particularly Map-D characteristics, may serve as potential neurophysiological markers for cognitive decline in TLE patients.

Enhancement of Ca2+ Signal Strength in Astrocytes in the Lateral Septum Improves Cognitive Disorders in Mice After Hemorrhagic Shock and Resuscitation

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca2+ signal strength in lateral septum astrocytes following HSR.

Identification of metabolic progression and subtypes in progressive supranuclear palsy by PET molecular imaging

INTRODUCTION

Progressive supranuclear palsy (PSP) is a neurodegenerative disorder with diverse clinical presentations that are linked to tau pathology. Recently, Subtype and Stage Inference (SuStaIn) algorithm, an innovative data-driven method, has been developed to model both the spatial-temporal progression and subtypes of disease. This study explores PSP progression using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging and the SuStaIn algorithm to identify PSP metabolic progression subtypes and understand disease mechanisms.

METHODS

The study included 72 PSP patients and 70 controls, with an additional 24 PSP patients enrolled as a test set, undergoing FDG-PET, dopamine transporter (DAT) PET, and neuropsychological assessments. The SuStaIn algorithm was employed to analyze the FDG-PET data, identifying progression subtypes and sequences.

RESULTS

Two PSP subtypes were identified: the cortical subtype with early prefrontal hypometabolism and the brainstem subtype with initial midbrain alterations. The cortical subtype displayed greater cognitive impairment and DAT reduction than the brainstem subtype. The test set demonstrates the robustness and reproducibility of the findings. Pathway analysis indicated that disruptions in dopaminergic cortico-basal ganglia pathways are crucial for elucidating the mechanisms of cognitive and behavioral impairment in PSP, leading to the two metabolic progression subtypes.

CONCLUSION

This study identified two spatiotemporal progression subtypes of PSP based on FDG-PET imaging, revealing significant differences in metabolic patterns, striatal dopaminergic uptake, and clinical profiles, particularly cognitive impairments. The findings highlight the crucial role of dopaminergic cortico-basal ganglia pathways in PSP pathophysiology, especially in the cortical subtype, providing insights into PSP heterogeneity and potential avenues for personalized treatments.

Reduced Modulation of Theta and Beta Oscillations Mediates Empathy Impairment in Parkinson's Disease

BACKGROUND

Empathy is an inaccessible part of advanced social cognitive functions in humans. Impairment of empathy greatly affects the quality of life of patients with Parkinson's disease (PD) but the underlying neurophysiologic mechanisms have not been established.

OBJECTIVES

The dynamic process of brain oscillations in PD pain empathy was explored and the mechanism of empathy damage was studied.

METHODS

A total of 27 patients with PD and 13 healthy controls were recruited to undergo a pain judgment task, and the event-related potentials were recorded. This study compared the changes in theta and beta oscillations among two groups after the presentation of painful and neutral stimuli.

RESULTS

Time-frequency analysis results revealed that patients with PD exhibited event-related theta oscillation synchronization and beta oscillation desynchronization during pain empathy. Compared to healthy controls, patients with PD exhibited a reduced magnitude of beta oscillation desynchronization in response to painful stimuli and attenuated synchronization of theta oscillations induced by neutral stimuli. There are abnormal beta power differences between painful and neutral stimuli, while no differences were found in theta power in PD. Moreover, a positive correlation existed between the degree of beta oscillation desynchronization associated with painful stimuli and the accuracy of pain judgments.

CONCLUSION

Pain empathy deficits in PD were associated with reduced dynamic modulation of brain theta and beta oscillations.

Dysfunctional oscillatory bursting patterns underlie working memory deficits in adolescents with ADHD

Identifying neural markers of clinical symptom fluctuations is prerequisite to developing more precise brain-targeted treatments in psychiatry. We have recently shown that working memory (WM) in healthy adults is dependent on the rise and fall interplay between alpha/beta and gamma bursts within frontoparietal regions, and that deviations in these patterns lead to WM performance errors. However, it is not known whether such bursting deviations underlie clinically relevant WM-related symptoms or clinical status in individuals with WM deficits. In adolescents (n=27) with attention deficit hyperactivity disorder (ADHD), we investigated WM-related dynamics between alpha/beta and gamma bursts in relation to clinical status fluctuations. Participants repeatedly completed a visual Sternberg spatial working memory task during EEG recording as part of their participation in two research studies (n=224 person-sessions). Source localizing EEG data to each participant's structural MRI, the rate and volume of alpha, beta, and gamma bursts were examined within the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC). Alpha/beta and gamma bursts at the DLPFC and PPC displayed complimentary roles in WM processes. Alpha/beta bursting decreased during stimuli encoding and increased during the delay, while gamma bursting was elevated during encoding and decreased during the delay. Deviations in bursting patterns were associated with WM errors and clinical symptoms. We conclude that dysfunctional alpha/beta and gamma burst dynamics within the frontoparietal region underlie both intra-individual WM performance and WM symptom fluctuations in adolescents with ADHD. Such burst dynamics reflect a novel target and biomarker for WM-related treatment development.

Cortical beta oscillations map to shared brain networks modulated by dopamine

Brain rhythms can facilitate neural communication for the maintenance of brain function. Beta rhythms (13-35 Hz) have been proposed to serve multiple domains of human ability, including motor control, cognition, memory, and emotion, but the overarching organisational principles remain unknown. To uncover the circuit architecture of beta oscillations, we leverage normative brain data, analysing over 30 hr of invasive brain signals from 1772 channels from cortical areas in epilepsy patients, to demonstrate that beta is the most distributed cortical brain rhythm. Next, we identify a shared brain network from beta-dominant areas with deeper brain structures, like the basal ganglia, by mapping parametrised oscillatory peaks to whole-brain functional and structural MRI connectomes. Finally, we show that these networks share significant overlap with dopamine uptake as indicated by positron emission tomography. Our study suggests that beta oscillations emerge in cortico-subcortical brain networks that are modulated by dopamine. It provides the foundation for a unifying circuit-based conceptualisation of the functional role of beta activity beyond the motor domain and may inspire an extended investigation of beta activity as a feedback signal for closed-loop neurotherapies for dopaminergic disorders.

Unraveling the Complexity of Parkinson's Disease: Insights into Pathogenesis and Precision Interventions

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss, leading to motor and non-motor symptoms. Early detection before symptom onset is crucial but challenging. This study presents a framework integrating circuit modeling, non-equilibrium dynamics, and optimization to understand PD pathogenesis and enable precision interventions. Neuronal firing patterns, particularly oscillatory activity, play a critical role in PD pathology. The basal ganglia network, specifically the subthalamic nucleus-external globus pallidus (STN-GPe) circuitry, exhibits abnormal activity associated with motor dysfunction. The framework leverages the non-equilibrium landscape and flux theory to identify key connections generating pathological activity, providing insights into disease progression and potential intervention points. The intricate STN-GPe interplay is highlighted, shedding light on compensatory mechanisms within this circuitry may initially counteract changes but later contribute to pathological alterations as disease progresses. The framework addresses the need for comprehensive evaluation methods to assess intervention outcomes. Cross-correlations between state variables provide superior early warning signals compared to traditional indicators relying on critical slowing down. By elucidating compensatory mechanisms and circuit dynamics, the framework contributes to improved management, early detection, risk assessment, and potential prevention/delay of PD development. This pioneering research paves the way for precision medicine in neurodegenerative disorders.

Distinct functions for beta and alpha bursts in gating of human working memory

Multiple neural mechanisms underlying gating to working memory have been proposed with divergent results obtained in human and animal studies. Previous findings from non-human primates suggest prefrontal beta frequency bursts as a correlate of transient inhibition during selective encoding. Human studies instead suggest a similar role for sensory alpha power fluctuations. To cast light on these discrepancies we employed a sequential working memory task with distractors for human participants. In particular, we examined their whole-brain electrophysiological activity in both alpha and beta bands with the same single-trial burst analysis earlier performed on non-human primates. Our results reconcile earlier findings by demonstrating that both alpha and beta bursts in humans correlate with the filtering and control of memory items, but with region and task-specific differences between the two rhythms. Occipital beta burst patterns were selectively modulated during the transition from sensory processing to memory retention whereas prefrontal and parietal beta bursts tracked sequence order and were proactively upregulated prior to upcoming target encoding. Occipital alpha bursts instead increased during the actual presentation of unwanted sensory stimuli. Source reconstruction additionally suggested the involvement of striatal and thalamic alpha and beta. Thus, specific whole-brain burst patterns correlate with different aspects of working memory control.

A Knowledge-Driven Framework Discovers Brain ACtivation-Transition-Spectrum (ACTS) Features for Parkinson's Disease

Dopaminergic treatment has proved effective to Parkinson's disease (PD), but the conventional treatment assessment is human-administered and prone to intra- and inter-assessor variability. In this paper, we propose a knowledge-driven framework and discover that brain ACtivation-Transition-Spectrum (ACTS) features achieve effective quantified assessments of dopaminergic therapy in PD. Firstly, brain activities of fifty-one PD patients during clinical walking tests under the OFF and ON states (without and with dopaminergic medication) were measured with functional near-infrared spectroscopy (fNIRS). Then, brain ACTS features were formulated based on the medication-induced variations in temporal features of brain regional activation, transition features of brain hemodynamic states, and graph spectrum of brain functional connectivity. Afterwards, a prior selection algorithm was constructed based on recursive feature elimination and graph spectrum analysis for the selection of principal discriminative features. Further, linear discriminant analysis was conducted to predict the treatment-induced improvements. The results demonstrated that the proposed method decreased the misclassification probability from 42% to 16% in the evaluations of dopaminergic treatment and outperformed existing fNIRS-based methods. Therefore, the proposed method promises a quantified and objective approach for dopaminergic treatment assessment, and our brain ACTS features may serve as promising functional biomarkers for treatment evaluation.

Beta and theta oscillations track effort and previous reward in the human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we report an exploratory investigation into this with chronic intracranial recordings from the prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson's disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12 to 20 Hz) oscillations tracking effort on a single-trial basis and PFC theta (4 to 7 Hz) signaling previous trial reward, with no effects of net subjective value. Stimulation of PFC increased overall acceptance of offers and sensitivity to reward while decreasing the impact of effort on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, supports a causal role of PFC for such choices, and seeds hypotheses for future studies.

Transcranial direct current stimulation and cognitive changes in Parkinson's disease, a systematic review with meta-analysis and meta-regression

Parkinson's disease is the second most common neurodegenerative disease, but therapeutic options such as neuromodulation continue to show variable effects, making clinical management of the disease difficult. This systematic review with meta-analysis and meta-regression aimed to analyze the isolated effect of cortical modulation with transcranial direct current stimulation (tDCS) compared to sham stimulation on cognitive changes in people with Parkinson's disease. The databases used were: Web of Science, Scopus, PsycINFO, PubMed, and Cochrane. The results showed that tDCS can influence the improvement of cognition in PD (Inverse Variance:0.24 [95% Confidence Interval: 0.09 to -0.40], p < 0.00). The meta-analysis showed that active tDCS can influence cognitive function by improving aspects related to memory (Inverse Variance:0.34 [95% Confidence Interval: 0.07 to 0.61], p < 0.01) and reducing reaction time in cognitive tasks (Inverse Variance:0.42 [95% Confidence Interval: 0.07 to 0.76], p < 0.02). Innovative meta-regression analyses showed that variables such as age (Q = 2.54, df = 1, p < 0.11), education level (Q = 2.62, df = 1, p < 0.10), disease duration (Q = 0.01, df = 1, p < 0.92), and Unified PD Rating Scale stage (Q = 0.01, df = 1, p < 0.92) did not influence the results. Thus, tDCS may be a therapeutic option for cognitive changes in people with PD, and we suggest further studies to identify protocols that can be replicated.

A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease

Objective.Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.Approach.This paper proposed a dynamic brain network decomposition method and discovered brain hemodynamic sub-networks that well characterized the efficacy of dopaminergic treatment in PD. Firstly, a clinical walking procedure with functional near-infrared spectroscopy was developed, and brain activations during the procedure from fifty PD patients under the OFF and ON states (without and with dopaminergic medication) were captured. Then, dynamic brain networks were constructed with sliding-window analysis of phase lag index and integrated time-varying functional networks across all patients. Afterwards, an aggregated network decomposition algorithm was formulated based on aggregated effectiveness optimization of functional networks in spanning network topology and cross-validation network variations, and utilized to unveil effective brain hemodynamic sub-networks for PD patients. Further, dynamic sub-network features were constructed to characterize the brain flexibility and dynamics according to the temporal switching and activation variations of discovered sub-networks, and their correlations with differential treatment-induced gait alterations were analyzed.Results.The results demonstrated that PD patients exhibited significantly enhanced flexibility after dopaminergic therapy within a sub-network related to the improvement of motor functions. Other sub-networks were significantly correlated with trunk-related axial symptoms and exhibited no significant treatment-induced dynamic interactions.Significance.The proposed method promises a quantified and objective approach for dopaminergic treatment evaluation. Moreover, the findings suggest that the gait of PD patients comprises distinct motor domains, and the corresponding neural controls are selectively responsive to dopaminergic treatment.

Transcranial Ultrasound Stimulation Improves Memory Performance of Parkinsonian Mice

Cognitive impairment is one of the most common non-motor symptoms of Parkinson's disease (PD). Previous studies have demonstrated that low-intensity transcranial ultrasound stimulation can significantly suppress the motor symptoms of PD. However, whether ultrasound stimulation can improve cognitive ability in PD and the related neural oscillation mechanism remain unclear to date. To evaluate the effect of ultrasound stimulation on memory ability in PD and explore its neural oscillation mechanism. Ultrasonography was used for 7-day stimulation of the CA1 in transgenic mice with PD. The working memory ability of the PD mice was then tested using novel object discrimination, and the local field potential and spikes in the mice CA1 were recorded at the same time as in the behavioral test. We found that ultrasound stimulation of the PD mice CA1 for 4 days: 1) significantly increased their learning and memory ability, although the learning and memory ability on the 7th day after the stimulation stopped was not significantly different from that before stimulation (P>0.05); 2) significantly increased the relative power of theta, low gamma, and high gamma frequency bands of the local field potential, and the phase amplitude coupling strength between theta and low gamma and between theta and high gamma; and 3) modulated the phase-locking angle between the spike of interneuron and theta wave to a 180°-360° rise cycle. Transcranial ultrasound stimulation can improve the learning and memory abilities of PD mice, and evoking neural oscillations in the CA1 is the potential mechanism.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

Beta and theta oscillations track effort and previous reward in human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we investigate this with chronic intracranial recordings from prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson's disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12-20 Hz) oscillations tracking subjective effort on a single trial basis and PFC theta (4-7 Hz) signaling previous trial reward. Stimulation of PFC increased overall acceptance of offers in addition to increasing the impact of reward on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, as well as supporting a causal role of PFC for such choices.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes.

METHODS

We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD.

RESULTS

149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis.

CONCLUSIONS

These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.