Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations

Cortico-striatal gamma oscillations are modulated by dopamine D3 receptors in dyskinetic rats

JOURNAL/nrgr/04.03/01300535-202504000-00031/figure1/v/2024-07-06T104127Z/r/image-tiff Long-term levodopa administration can lead to the development of levodopa-induced dyskinesia. Gamma oscillations are a widely recognized hallmark of abnormal neural electrical activity in levodopa-induced dyskinesia. Currently, studies have reported increased oscillation power in cases of levodopa-induced dyskinesia. However, little is known about how the other electrophysiological parameters of gamma oscillations are altered in levodopa-induced dyskinesia. Furthermore, the role of the dopamine D3 receptor, which is implicated in levodopa-induced dyskinesia, in movement disorder-related changes in neural oscillations is unclear. We found that the cortico-striatal functional connectivity of beta oscillations was enhanced in a model of Parkinson's disease. Furthermore, levodopa application enhanced cortical gamma oscillations in cortico-striatal projections and cortical gamma aperiodic components, as well as bidirectional primary motor cortex (M1) ↔ dorsolateral striatum gamma flow. Administration of PD128907 (a selective dopamine D3 receptor agonist) induced dyskinesia and excessive gamma oscillations with a bidirectional M1 ↔ dorsolateral striatum flow. However, administration of PG01037 (a selective dopamine D3 receptor antagonist) attenuated dyskinesia, suppressed gamma oscillations and cortical gamma aperiodic components, and decreased gamma causality in the M1 → dorsolateral striatum direction. These findings suggest that the dopamine D3 receptor plays a role in dyskinesia-related oscillatory activity, and that it has potential as a therapeutic target for levodopa-induced dyskinesia.

EEG β oscillations in aberrant data perception under cognitive load modulation

Data-driven decision making (DDDM) is becoming an indispensable component of work across various fields, and the perception of aberrant data (PAD) has emerged as an essential skill. Nonetheless, the neural processing mechanisms underpinning PAD remain incompletely elucidated. Direct evidence linking neural oscillations to PAD is currently lacking, and the impact of cognitive load remains ambiguous. We address this issue using EEG time-frequency analysis. Data were collected from 21 healthy participants. The experiment employed a 2 (low vs. high cognitive load) × 2 [PAD+ (aberrant data accurately identified as aberrant) vs. PAD- (non-aberrant data correctly recognized as normal)] within-subject laboratory design. Results indicate that upper β band oscillations (26-30 Hz) were significantly enhanced in the PAD + condition compared to PAD-, with consistent activity observed in the frontal (p < 0.001, [Formula: see text] = 0.41) and parietal lobes (p = 0.028, [Formula: see text] = 0.22) within the 300-350 ms time window. Additionally, as cognitive load increased, the time window of β oscillations for distinguishing PAD+ from PAD- shifted earlier. This study enriches our understanding of the PAD neural basis by exploring the distribution of neural oscillation frequencies, decision-making neural circuits, and the windowing effect induced by cognitive load. These findings have significant implications for elucidating the pathological mechanisms of neurodegenerative disorders, as well as in the initial screening, intervention, and treatment of diseases.

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

Objective.Can we classify movement execution and inhibition from hippocampal oscillations during arm-reaching tasks? Traditionally associated with memory encoding, spatial navigation, and motor sequence consolidation, the hippocampus has come under scrutiny for its potential role in movement processing. Stereotactic electroencephalography (SEEG) has provided a unique opportunity to study the neurophysiology of the human hippocampus during motor tasks. In this study, we assess the accuracy of discriminant functions, in combination with principal component analysis (PCA), in classifying between 'Go' and 'No-go' trials in a Go/No-go arm-reaching task.Approach.Our approach centers on capturing the modulation of beta-band (13-30 Hz) power from multiple SEEG contacts in the hippocampus and minimizing the dimensional complexity of channels and frequency bins. This study utilizes SEEG data from the human hippocampus of 10 participants diagnosed with epilepsy. Spectral power was computed during a 'center-out' Go/No-go arm-reaching task, where participants reached or withheld their hand based on a colored cue. PCA was used to reduce data dimension and isolate the highest-variance components within the beta band. The Silhouette score was employed to measure the quality of clustering between 'Go' and 'No-go' trials. The accuracy of five different discriminant functions was evaluated using cross-validation.Main results.The Diagonal-Quadratic model performed best of the 5 classification models, exhibiting the lowest error rate in all participants (median: 9.91%, average: 14.67%). PCA showed that the first two principal components collectively accounted for 54.83% of the total variance explained on average across all participants, ranging from 36.92% to 81.25% among participants.Significance.This study shows that PCA paired with a Diagonal-Quadratic model can be an effective method for classifying between Go/No-go trials from beta-band power in the hippocampus during arm-reaching responses. This emphasizes the significance of hippocampal beta-power modulation in motor control, unveiling its potential implications for brain-computer interface applications.

Beta: bursts of cognition

Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.

Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex

Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of parkinsonism. We hypothesized that decreased PT5B neuron excitability would substantially disrupt oscillatory and non-oscillatory firing patterns of neurons in layer 5 (L5) of primary motor cortex (M1). To test this hypothesis, we performed computer simulations using a previously validated computer model of mouse M1. Inclusion of the experimentally identified parkinsonism-associated decrease of PT5B excitability into our computational model produced a paradoxical increase in rest-state PT5B firing rate, as well as an increase in beta-band oscillatory power in local field potential (LFP). In the movement-state, PT5B population firing and LFP showed reduced beta and increased high-beta, low-gamma activity of 20-35 Hz in the parkinsonian, but not in control condition. The appearance of beta-band oscillations in parkinsonism would be expected to disrupt normal M1 motor output and contribute to motor activity deficits seen in patients with Parkinson's disease (PD).

Robust adaptive deep brain stimulation control of in-silico non-stationary Parkinsonian neural oscillatory dynamics

Objective. Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson's disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) Parkinsonian beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering accurate and robust control of Parkinsonian neural oscillatory dynamics.Approach. Here, we develop a new robust adaptive closed-loop DBS method for regulating the Parkinsonian beta oscillatory dynamics of the cortex-BG-thalamus network. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated Parkinsonian neural state while reducing the system's sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as an in-silico simulation testbed to generate nonlinear and non-stationary Parkinsonian neural dynamics for evaluating DBS methods.Main results. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG Parkinsonian beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms current on-off and LTI DBS methods.Significance. These results have implications for future designs of closed-loop DBS systems to treat PD.

Disruption of Electroencephalogram Coherence between Cortex/Striatum and Midbrain Dopaminergic Regions in the Knock-Out Mice with Combined Loss of Alpha, Beta, and Gamma Synucleins

The malfunctioning of the brain synucleins is associated with pathogenesis of Parkinson's disease. Synucleins' ability to modulate various pre-synaptic processes suggests their modifying effects on the electroencephalogram (EEG) recorded from different brain structures. Disturbances in interrelations between them are critical for the onset and evolution of neurodegenerative diseases. Recently, we have shown that, in mice lacking several synucleins, differences between the frequency spectra of EEG from different brain structures are correlated with specificity of synucleins' combinations. Given that EEG spectra are indirect characteristics of inter-structural relations, in this study, we analyzed a coherence of instantaneous values for EEGs recorded from different structures as a direct measure of "functional connectivity" between them.

METHODS

EEG data from seven groups of knock-out (KO) mice with combined deletions of alpha, beta, and gamma synucleins versus a group of wild-type (WT) mice were compared. EEG coherence was estimated between the cortex (MC), putamen (Pt), ventral tegmental area (VTA), and substantia nigra (SN) in all combinations.

RESULTS

EEG coherence suppression, predominantly in the beta frequency band, was observed in KO mice versus WT littermates. The suppression was minimal in MC-Pt and VTA-SN interrelations in all KO groups and in all inter-structural relations in mice lacking either all synucleins or only beta synuclein. In other combinations of deleted synucleins, significant EEG coherence suppression in KO mice was dominant in relations with VTA and SN.

CONCLUSION

Deletions of the synucleins produced significant attenuation of intra-cerebral EEG coherence depending on the imbalance of different types of synucleins.

Alpha-2a adrenergic receptor activation in genetic absence epilepsy: An absence status model?

OBJECTIVE

The objective of the study was to propose a candidate animal model of absence status epilepticus induced by specific alpha-2a adrenergic receptor (α2AR) activation. We also aim to investigate the responsiveness of this model to classical anti-status or anti-absence medications.

METHODS

An α2AR agonist, dexmedetomidine (DEX), was injected intracerebroventricularly into adult rats with genetic absence epilepsy, and their electroencephalography (EEG) was recorded. The total duration, number, and mean duration of each spike-and-wave discharges (SWDs) were evaluated. The blocks of absence status events were classified as the initial and second sets of absence statuses. Ethosuximide (ETX) was administered as a pretreatment to another group of rats and later injected with 2.5 μg DEX. In addition, ETX, valproic acid (VPA), diazepam (DIAZ), and atipamezole (ATI) were administered after induced status-like events following DEX administration. Power spectral characteristics and coherence analysis were performed on the EEG to assess the absence status events and sleep.

RESULTS

The 2.5 μg dose of DEX increased the total SWD duration and induced continuous SWDs up to 26 min. Following the initial absence status event, sleep was induced; then, the second period of absence status-like activities were initiated. ETX pretreatment blocked the occurrence of absence status-like activities. Power spectral density analyses revealed that DEX-induced post-sleep activities had higher power in delta frequency band (1-4 Hz) and attenuated power of 7 Hz harmonics (14 and 21 Hz) than the pre-injection seizure. The mean duration of SWDs were decreased in all the groups, but occasional prolonged activities were seen in ETX or VPA-injected rats but not with DIAZ or ATI.

SIGNIFICANCE

This study presents an absence status epilepticus animal model that is activated by α2AR activation to investigate the pathophysiological role of absence status. Unlike other agents ATI switched off the second set of absence statuses to normal SWDs, without sedation or lethargy, can show it may preferentially block absence status-like activity.

THE PLAIN LANGUAGE SUMMARY

This study proposes a rat model for prolonged seizures, resembling absence status epilepticus. Activating the brain's alpha-2a adrenergic receptor with dexmedetomidine induced seizures lasting up to 26 minutes. Ethosuximide pretreatment and post-treatment with valproic acid, diazepam, and atipamezole decreased induced seizures. The findings suggest this model is valuable for studying absence status epilepticus. In addition, atipamezole normalized abnormal seizures without sedation, hinting at its potential for targeted treatment and further research.

Gait-related beta-gamma phase amplitude coupling in the subthalamic nucleus of parkinsonian patients

Analysis of coupling between the phases and amplitudes of neural oscillations has gained increasing attention as an important mechanism for large-scale brain network dynamics. In Parkinson's disease (PD), preliminary evidence indicates abnormal beta-phase coupling to gamma-amplitude in different brain areas, including the subthalamic nucleus (STN). We analyzed bilateral STN local field potentials (LFPs) in eight subjects with PD chronically implanted with deep brain stimulation electrodes during upright quiet standing and unperturbed walking. Phase-amplitude coupling (PAC) was computed using the Kullback-Liebler method, based on the modulation index. Neurophysiological recordings were correlated with clinical and kinematic measurements and individual molecular brain imaging studies ([123I]FP-CIT and single-photon emission computed tomography). We showed a dopamine-related increase in subthalamic beta-gamma PAC from standing to walking. Patients with poor PAC modulation and low PAC during walking spent significantly more time in the stance and double support phase of the gait cycle. Our results provide new insights into the subthalamic contribution to human gait and suggest cross-frequency coupling as a gateway mechanism to convey patient-specific information of motor control for human locomotion.

Local field potential (LFP) power and phase-amplitude coupling (PAC) changes in the striatum and motor cortex reflect neural mechanisms associated with bradykinesia and rigidity during D2R suppression in an animal model

Impairments in motor control are the primary feature of Parkinson's disease, which is caused by dopaminergic imbalance in the basal ganglia. Identification of neural biomarkers of dopamine D2 receptor (D2R) suppression would be useful for monitoring the progress of neuropathologies and effects of treatment. Male Swiss albino ICR mice were deeply anesthetized, and electrodes were implanted in the striatum and motor cortex to record local field potential (LFP). Haloperidol (HAL), a D2R antagonist, was administered to induce decreased D2R activity. Following HAL treatment, the mice showed significantly decreased movement velocity in open field test, increased latency to descend in a bar test, and decreased latency to fall in a rotarod test. LFP signals during HAL-induced immobility (open field test) and catalepsy (bar test) were analyzed. Striatal low-gamma (30.3-44.9 Hz) power decreased during immobility periods, but during catalepsy, delta power (1-4 Hz) increased, beta1(13.6-18 Hz) and low-gamma powers decreased, and high-gamma (60.5-95.7 Hz) power increased. Striatal delta-high-gamma phase-amplitude coupling (PAC) was significantly increased during catalepsy but not immobility. In the motor cortex, during HAL-induced immobility, beta1 power significantly increased and low-gamma power decreased, but during HAL-induced catalepsy, low-gamma and beta1 powers decreased and high-gamma power increased. Delta-high-gamma PAC in the motor cortex significantly increased during catalepsy but not during immobility. Altogether, the present study demonstrated changes in delta, beta1 and gamma powers and delta-high-gamma PAC in the striatum and motor cortex in association with D2R suppression. In particular, delta power in the striatum and delta-high-gamma PAC in the striatum and motor cortex appear to represent biomarkers of neural mechanisms associated with bradykinesia and rigidity.

Eltoprazine modulated gamma oscillations on ameliorating L-dopa-induced dyskinesia in rats

AIM

Parkinson's disease (PD) is a pervasive neurodegenerative disease, and levodopa (L-dopa) is its preferred treatment. The pathophysiological mechanism of levodopa-induced dyskinesia (LID), the most common complication of long-term L-dopa administration, remains obscure. Accumulated evidence suggests that the dopaminergic as well as non-dopaminergic systems contribute to LID development. As a 5-hydroxytryptamine 1A/1B receptor agonist, eltoprazine ameliorates dyskinesia, although little is known about its electrophysiological mechanism. The aim of this study was to investigate the cumulative effects of chronic L-dopa administration and the potential mechanism of eltoprazine's amelioration of dyskinesia at the electrophysiological level in rats.

METHODS

Neural electrophysiological analysis techniques were conducted on the acquired local field potential (LFP) data from primary motor cortex (M1) and dorsolateral striatum (DLS) during different pathological states to obtain the information of power spectrum density, theta-gamma phase-amplitude coupling (PAC), and functional connectivity. Behavior tests and AIMs scoring were performed to verify PD model establishment and evaluate LID severity.

RESULTS

We detected exaggerated gamma activities in the dyskinetic state, with different features and impacts in distinct regions. Gamma oscillations in M1 were narrowband manner, whereas that in DLS had a broadband appearance. Striatal exaggerated theta-gamma PAC in the LID state contributed to broadband gamma oscillation, and aperiodic-corrected cortical beta power correlated robustly with aperiodic-corrected gamma power in M1. M1-DLS coherence and phase-locking values (PLVs) in the gamma band were enhanced following L-dopa administration. Eltoprazine intervention reduced gamma oscillations, theta-gamma PAC in the DLS, and coherence and PLVs in the gamma band to alleviate dyskinesia.

CONCLUSION

Excessive cortical gamma oscillation is a compelling clinical indicator of dyskinesia. The detection of enhanced PAC and functional connectivity of gamma-band oscillation can be used to guide and optimize deep brain stimulation parameters. Eltoprazine has potential clinical application for dyskinesia.

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

Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.

Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation

OBJECTIVE

Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal.

METHODS

STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated.

RESULTS

The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation).

CONCLUSIONS

Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns.

SIGNIFICANCE

A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.

Nucleus reuniens transiently synchronizes memory networks at beta frequencies

Episodic memory-based decision-making requires top-down medial prefrontal cortex and hippocampal interactions. This integrated prefrontal-hippocampal memory state is thought to be organized by synchronized network oscillations and mediated by connectivity with the thalamic nucleus reuniens (RE). Whether and how the RE synchronizes prefrontal-hippocampal networks in memory, however, remains unknown. Here, we recorded local field potentials from the prefrontal-RE-hippocampal network while rats engaged in a nonspatial sequence memory task, thereby isolating memory-related activity from running-related oscillations. We found that synchronous prefrontal-hippocampal beta bursts (15-30 Hz) dominated during memory trials, whereas synchronous theta activity (6-12 Hz) dominated during non-memory-related running. Moreover, RE beta activity appeared first, followed by prefrontal and hippocampal synchronized beta, suggesting that prefrontal-hippocampal beta could be driven by the RE. To test whether the RE is capable of driving prefrontal-hippocampal beta synchrony, we used an optogenetic approach (retroAAV-ChR2). RE activation induced prefrontal-hippocampal beta coherence and reduced theta coherence, matching the observed memory-driven network state in the sequence task. These findings are the first to demonstrate that the RE contributes to memory by driving transient synchronized beta in the prefrontal-hippocampal system, thereby facilitating interactions that underlie memory-based decision-making.

Dyrk1a Phosphorylation of α-Synuclein Mediating Apoptosis of Dopaminergic Neurons in Parkinson's Disease

Objective

To investigate the role of aberrant Dyrk1a expression in phosphorylation modification at the α-synuclein serine 129 (Ser129) site to analyze its molecular mechanism in mediating apoptosis of PD.

Methods

The protein level of P-α-synuclein (Ser129), α-synuclein, Bcl-2, Bax, active caspase 3, GSK3β, PI3K, AKT, and cyclinD1 were detected. The mRNA transcript levels of Dyrk1a and DAT and protein levels of IL-1β, IL-6, COX-2, and TNF-α were detected.

Results

P-α-synuclein (Ser129), α-synuclein, Bax, active caspase 3, GSK3β, and cyclinD1 expressions were decreased in Dyrk1a-AAV-ShRNA (P < 0.05), and Bcl-2, AKT, and PI3K expressions were increased (P < 0.05). Increased TH protein expression was shown in Dyrk1a-AAV-ShRNA (P < 0.05). Dyrk1a mRNA was decreased in the Dyrk1a-AAV-ShRNA group (P < 0.05), and DAT mRNA was increased (P < 0.05). IL-1β, IL-6, COX-2, and TNF-α protein levels were decreased in Dyrk1al-AAV-Sh-RNA (P < 0.05). Transcriptome sequencing showed that Fam220a, which was expected to activate STAT family protein binding activity and participate in the negative regulation of transcription through RNA polymerase II and protein dephosphorylation showed differentially upregulated expression. The untargeted metabolome showed that the major compounds in the Dyrk1a-AAV-ShRNA group were hormones and transmission mediators and the most metabolism-related pathways. Fam220a showed differentially upregulated expression, and differentially expressed genes were enriched for the neuroactive ligand-receptor interaction, vascular smooth muscle contraction, and melanogenesis-related pathways.

Conclusion

Abnormal Dyrk1a expression can affect α-synuclein phosphorylation modifications, and dyrk1a knockdown activates the PI3K/AKT pathway and reduces dopaminergic neuron apoptosis. It provides a theoretical basis for the group to further investigate the molecular mechanism.

Translating Pathological Brain Activity Primers in Parkinson's Disease Research

Translational experimental approaches that help us better trace Parkinson's disease (PD) pathophysiological mechanisms leading to new therapeutic targets are urgently needed. In this article, we review recent experimental and clinical studies addressing abnormal neuronal activity and pathological network oscillations, as well as their underlying mechanisms and modulation. Our aim is to enhance our knowledge about the progression of Parkinson's disease pathology and the timing of its symptom's manifestation. Here, we present mechanistic insights relevant for the generation of aberrant oscillatory activity within the cortico-basal ganglia circuits. We summarize recent achievements extrapolated from available PD animal models, discuss their advantages and limitations, debate on their differential applicability, and suggest approaches for transferring knowledge on disease pathology into future research and clinical applications.

Average power and burst analysis revealed complementary information on drug-related changes of motor performance in Parkinson's disease

In patients with Parkinson's disease (PD), suppression of beta and increase in gamma oscillations in the subthalamic nucleus (STN) have been associated with both levodopa treatment and motor functions. Recent results suggest that modulation of the temporal dynamics of theses oscillations (bursting activity) might contain more information about pathological states and behaviour than their average power. Here we directly compared the information provided by power and burst analyses about the drug-related changes in STN activities and their impact on motor performance within PD patients. STN local field potential (LFP) signals were recorded from externalized patients performing self-paced movements ON and OFF levodopa. When normalised across medication states, both power and burst analyses showed an increase in low-beta oscillations in the dopamine-depleted state during rest. When normalised within-medication state, both analyses revealed that levodopa increased movement-related modulation in the alpha and low-gamma bands, with higher gamma activity around movement predicting faster reaches. Finally, burst analyses helped to reveal opposite drug-related changes in low- and high-beta frequency bands, and identified additional within-patient relationships between high-beta bursting and movement performance. Our findings suggest that although power and burst analyses share a lot in common they also provide complementary information on how STN-LFP activity is associated with motor performance, and how levodopa treatment may modify these relationships in a way that helps explain drug-related changes in motor performance. Different ways of normalisation in the power analysis can reveal different information. Similarly, the burst analysis is sensitive to how the threshold is defined - either for separate medication conditions separately, or across pooled conditions. In addition, the burst interpretation has far-reaching implications about the nature of neural oscillations - whether the oscillations happen as isolated burst-events or are they sustained phenomena with dynamic amplitude variations? This can be different for different frequency bands, and different for different medication states even for the same frequency band.

Case report: Bilateral double beta peak activity is influenced by stimulation, levodopa concentrations, and motor tasks, in a Parkinson's disease patient on chronic deep brain stimulation

Introduction

Subthalamic (STN) local field potentials (LFPs) in the beta band are considered potential biomarkers for closed-loop deep brain stimulation (DBS) in Parkinson's disease (PD). The beta band is further dissected into low-and high-frequency components with somewhat different functions, although their concomitance and association in the single patient is far to be defined. We present a 56-year-old male PD patient undergoing DBS showing a double-beta peak activity on both sides. The aim of the study was to investigate how low-and high-beta peaks were influenced by plasma levodopa (L-dopa) levels, stimulation, and motor performances.

Methods

A systematic evaluation of raw LFPs, plasma L-dopa levels, and motor tasks was performed in the following four conditions: OFF medications/ON stimulation, OFF medications/OFF stimulation, ON medications/OFF stimulation, and ON medications/ON stimulation.

Results

The analysis of the LFP spectra suggests the following results: (1) the high-beta peak was suppressed by stimulation, while the low-beta peak showed a partial and not consistent response to stimulation; (2) the high-beta peak is also influenced by plasma L-dopa concentration, showing a progressive amplitude increment concordant with plasma L-dopa levels, while the low-beta peak shows a different behavir; and (3) motor performances seem to impact beta peaks behavior.

Conclusion

This single exploratory case study illustrates a complex behavior of low-and high-beta peaks in a PD patient, in response to stimulation, L-dopa plasma levels, and motor performances. Our results suggest the importance to investigate patient-specific individual LFP patterns in view of upcoming closed-loop stimulation.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

Dopamine depletion leads to pathological synchronization of distinct basal ganglia loops in the beta band

Motor symptoms of Parkinson's Disease (PD) are associated with dopamine deficits and pathological oscillation of basal ganglia (BG) neurons in the β range ([12-30] Hz). However, how dopamine depletion affects the oscillation dynamics of BG nuclei is still unclear. With a spiking neurons model, we here capture the features of BG nuclei interactions leading to oscillations in dopamine-depleted condition. We highlight that both the loop between subthalamic nucleus (STN) and Globus Pallidus pars externa (GPe) and the loop between striatal fast spiking and medium spiny neurons and GPe display resonances in the β range, and synchronize to a common β frequency through interaction. Crucially, the synchronization depends on dopamine depletion: the two loops are largely independent for high levels of dopamine, but progressively synchronize as dopamine is depleted due to the increased strength of the striatal loop. The model is validated against recent experimental reports on the role of cortical inputs, STN and GPe activity in the generation of β oscillations. Our results highlight the role of the interplay between the GPe-STN and the GPe-striatum loop in generating sustained β oscillations in PD subjects, and explain how this interplay depends on the level of dopamine. This paves the way to the design of therapies specifically addressing the onset of pathological β oscillations.

Neuromodulation of Neural Oscillations in Health and Disease

Using EEG and local field potentials (LFPs) as an index of large-scale neural activities, research has been able to associate neural oscillations in different frequency bands with markers of cognitive functions, goal-directed behavior, and various neurological disorders. While this gives us a glimpse into how neurons communicate throughout the brain, the causality of these synchronized network activities remains poorly understood. Moreover, the effect of the major neuromodulatory systems (e.g., noradrenergic, cholinergic, and dopaminergic) on brain oscillations has drawn much attention. More recent studies have suggested that cross-frequency coupling (CFC) is heavily responsible for mediating network-wide communication across subcortical and cortical brain structures, implicating the importance of neurotransmitters in shaping coordinated actions. By bringing to light the role each neuromodulatory system plays in regulating brain-wide neural oscillations, we hope to paint a clearer picture of the pivotal role neural oscillations play in a variety of cognitive functions and neurological disorders, and how neuromodulation techniques can be optimized as a means of controlling neural network dynamics. The aim of this review is to showcase the important role that neuromodulatory systems play in large-scale neural network dynamics, informing future studies to pay close attention to their involvement in specific features of neural oscillations and associated behaviors.

Mechanisms of Sleep/Wake Regulation under Hypodopaminergic State: Insights from MitoPark Mouse Model of Parkinson's Disease

Sleep/wake alterations are predominant in neurological and neuropsychiatric disorders involving dopamine dysfunction. Unfortunately, specific, mechanisms-based therapies for these debilitating sleep problems are currently lacking. The pathophysiological mechanisms of sleep/wake alterations within a hypodopaminergic MitoPark mouse model of Parkinson's disease (PD) are investigated. MitoPark mice replicate most PD-related sleep alterations, including sleep fragmentation, hypersomnia, and daytime sleepiness. Surprisingly, these alterations are not accounted for by a dysfunction in the circadian or homeostatic regulatory processes of sleep, nor by acute masking effects of light or darkness. Rather, the sleep phenotype is linked with the impairment of instrumental arousal and sleep modulation by behavioral valence. These alterations correlate with changes in high-theta (8-11.5 Hz) electroencephalogram power density during motivationally-charged wakefulness. These results demonstrate that sleep/wake alterations induced by dopamine dysfunction are mediated by impaired modulation of sleep by motivational valence and provide translational insights into sleep problems associated with disorders linked to dopamine dysfunction.

Alterations of resting-state networks of Parkinson's disease patients after subthalamic DBS surgery

The implantation of deep brain stimulation (DBS) electrodes in Parkinson's disease (PD) patients can lead to a temporary improvement in motor symptoms, known as the stun effect. However, the network alterations induced by the stun effect are not well characterized. As therapeutic DBS is known to alter resting-state networks (RSN) and subsequent motor symptoms in patients with PD, we aimed to investigate whether the DBS-related stun effect also modulated RSNs. Therefore, we analyzed RSNs of 27 PD patients (8 females, 59.0 +- 8.7 years) using magnetoencephalography and compared them to RSNs of 24 age-matched healthy controls (8 females, 62.8 +- 5.1 years). We recorded 30 min of resting-state activity two days before and one day after implantation of the electrodes with and without dopaminergic medication. RSNs were determined by use of phase-amplitude coupling between a low frequency phase and a high gamma amplitude and examined for differences between conditions (i.e., pre vs post surgery). We identified four RSNs across all conditions: sensory-motor, visual, fronto-occipital, and frontal. Each RSN was altered due to electrode implantation. Importantly, these changes were not restricted to spatially close areas to the electrode trajectory. Interestingly, pre-operative RSNs corresponded better with healthy control RSNs regarding the spatial overlap, although the stun effect is associated with motor improvement. Our findings reveal that the stun effect induced by implantation of electrodes exerts brain wide changes in different functional RSNs.

Stable, interactive modulation of neuronal oscillations produced through brain-machine equilibrium

Closed-loop interaction has the potential to regulate ongoing brain activity by continuously binding an external stimulation to specific dynamics of a neural circuit. Achieving interactive modulation requires a stable brain-machine feedback loop. Here, we demonstrate that it is possible to maintain oscillatory brain activity in a desired state by delivering stimulation accurately aligned with the timing of each cycle. We develop a fast algorithm that responds on a cycle-by-cycle basis to stimulate basal ganglia nuclei at predetermined phases of successive cortical beta cycles in parkinsonian rats. Using this approach, an equilibrium emerges between the modified brain signal and feedback-dependent stimulation pattern, leading to sustained amplification or suppression of the oscillation depending on the phase targeted. Beta amplification slows movement speed by biasing the animal's mode of locomotion. Together, these findings show that highly responsive, phase-dependent stimulation can achieve a stable brain-machine interaction that leads to robust modulation of ongoing behavior.

Synaptic determinants of cholinergic interneurons hyperactivity during parkinsonism

Parkinson’s disease is a neurodegenerative ailment generated by the loss of dopamine in the basal ganglia, mainly in the striatum. The disease courses with increased striatal levels of acetylcholine, disrupting the balance among these modulatory transmitters. These modifications disturb the excitatory and inhibitory balance in the striatal circuitry, as reflected in the activity of projection striatal neurons. In addition, changes in the firing pattern of striatal tonically active interneurons during the disease, including cholinergic interneurons (CINs), are being searched. Dopamine-depleted striatal circuits exhibit pathological hyperactivity as compared to controls. One aim of this study was to show how striatal CINs contribute to this hyperactivity. A second aim was to show the contribution of extrinsic synaptic inputs to striatal CINs hyperactivity. Electrophysiological and calcium imaging recordings in Cre-mice allowed us to evaluate the activity of dozens of identified CINs with single-cell resolution in ex vivo brain slices. CINs show hyperactivity with bursts and silences in the dopamine-depleted striatum. We confirmed that the intrinsic differences between the activity of control and dopamine-depleted CINs are one source of their hyperactivity. We also show that a great part of this hyperactivity and firing pattern change is a product of extrinsic synaptic inputs, targeting CINs. Both glutamatergic and GABAergic inputs are essential to sustain hyperactivity. In addition, cholinergic transmission through nicotinic receptors also participates, suggesting that the joint activity of CINs drives the phenomenon; since striatal CINs express nicotinic receptors, not expressed in striatal projection neurons. Therefore, CINs hyperactivity is the result of changes in intrinsic properties and excitatory and inhibitory inputs, in addition to the modification of local circuitry due to cholinergic nicotinic transmission. We conclude that CINs are the main drivers of the pathological hyperactivity present in the striatum that is depleted of dopamine, and this is, in part, a result of extrinsic synaptic inputs. These results show that CINs may be a main therapeutic target to treat Parkinson’s disease by intervening in their synaptic inputs.

Single-neuron bursts encode pathological oscillations in subcortical nuclei of patients with Parkinson's disease and essential tremor

Deep brain stimulation procedures offer an invaluable opportunity to study disease through intracranial recordings from awake patients. Here, we address the relationship between single-neuron and aggregate-level (local field potential; LFP) activities in the subthalamic nucleus (STN) and thalamic ventral intermediate nucleus (Vim) of patients with Parkinson's disease (n = 19) and essential tremor (n = 16), respectively. Both disorders have been characterized by pathologically elevated LFP oscillations, as well as an increased tendency for neuronal bursting. Our findings suggest that periodic single-neuron bursts encode both pathophysiological beta (13 to 33 Hz; STN) and tremor (4 to 10 Hz; Vim) LFP oscillations, evidenced by strong time-frequency and phase-coupling relationships between the bursting and LFP signals. Spiking activity occurring outside of bursts had no relationship to the LFP. In STN, bursting activity most commonly preceded the LFP oscillation, suggesting that neuronal bursting generated within STN may give rise to an aggregate-level LFP oscillation. In Vim, LFP oscillations most commonly preceded bursting activity, suggesting that neuronal firing may be entrained by periodic afferent inputs. In both STN and Vim, the phase-coupling relationship between LFP and high-frequency oscillation (HFO) signals closely resembled the relationships between the LFP and single-neuron bursting. This suggests that periodic single-neuron bursting is likely representative of a higher spatial and temporal resolution readout of periodic increases in the amplitude of HFOs, which themselves may be a higher resolution readout of aggregate-level LFP oscillations. Overall, our results may reconcile "rate" and "oscillation" models of Parkinson's disease and shed light on the single-neuron basis and origin of pathophysiological oscillations in movement disorders.

The genesis and functional consequences of cortico-subthalamic beta augmentation and excessive subthalamic burst discharges after dopaminergic deprivation

The cardinal electrophysiological signs in Parkinson's disease (PD) include augmented beta oscillations in the motor cortex-subthalamic nucleus (MC-STN) axis and excessive burst discharges in STN. We have shown that excessive STN burst discharges have a direct causal relation with the locomotor deficits in PD. To investigate the correlation between the two cardinal signs, we characterized the courses of development of the electrophysiological abnormalities in the hemiparkinsonian rat model. The loss of dopaminergic neurons develops fast, and is histologically completed within 4-7 days of the lesion. The increase in STN burst discharges is limited to the lesioned side, and follows a very similar course. In contrast, beta augmentation has a bilateral presentation, and requires 14-21 days for full development. Behaviorally, the gross locomotor deficits in open field test and limb akinesia in stepping test match the foregoing fast and slow time courses, respectively. A further look into the spike entrainment shows that the oscillations in local field potential (LFP) of the MC effectively entrain the multi-unit (MU) spikes of MC, STN and entopeduncular nucleus (EPN), a rat homolog of human globus pallidus interna (GPi), whereas the LFP of STN or EPN (GPi) cannot entrain the spikes in MC. We conclude that excessive STN burst discharges are a direct consequence, whereas beta augmentation is probably a secondary or adaptive changes in the cortico-subcortical re-entrant loops, to dopaminergic deprivation. Beta augmentation is therefore not so consistently present as excessive STN burst discharges, but could signal more delicate derangements at the level of cortical programming in PD.

Spontaneous pauses in firing of external pallidum neurons are associated with exploratory behavior

Spontaneous pauses in firing are the hallmark of external pallidum (GPe) neurons. However, the role of GPe pauses in the basal ganglia network remains unknown. Pupil size and saccadic eye movements have been linked to attention and exploration. Here, we recorded GPe spiking activity and the corresponding pupil sizes and eye positions in non-human primates. We show that pauses, rather than the GPe discharge rate per se, were associated with dilated pupils. In addition, following pause initiation there was a considerable increase in the rate of spontaneous saccades. These results suggest that pauses are a powerful mechanism by which the GPe may influence basal ganglia downstream structures and play a role in exploratory behavior.

Integrated analysis of external pallidum (GPe) neuronal firing, pupil size, and saccadic movements in non-human primates reveals that pauses in GPe firing are associated with pupil dilation. These results suggest that pauses in GPe activity might influence downstream structures in the basal ganglia network and influence exploratory behavior.

A translational perspective on pathophysiological changes of oscillatory activity in dystonia and parkinsonism

Intracerebral recordings from movement disorders patients undergoing deep brain stimulation have allowed the identification of pathophysiological patterns in oscillatory activity that correlate with symptom severity. Changes in oscillatory synchrony occur within and across brain areas, matching the classification of movement disorders as network disorders. However, the underlying mechanisms of oscillatory changes are difficult to assess in patients, as experimental interventions are technically limited and ethically problematic. This is why animal models play an important role in neurophysiological research of movement disorders. In this review, we highlight the contributions of translational research to the mechanistic understanding of pathological changes in oscillatory activity, with a focus on parkinsonism and dystonia, while addressing the limitations of current findings and proposing possible future directions.

Designing and Validating a Robust Adaptive Neuromodulation Algorithm for Closed-Loop Control of Brain States

OBJECTIVE

Neuromodulation systems that use closed-loop brain stimulation to control brain states can provide new therapies for brain disorders. To date, closed-loop brain stimulation has largely used linear time-invariant controllers. However, nonlinear time-varying brain network dynamics and external disturbances can appear during real-time stimulation, collectively leading to real-time model uncertainty. Real-time model uncertainty can degrade the performance or even cause instability of time-invariant controllers. Three problems need to be resolved to enable accurate and stable control under model uncertainty. First, an adaptive controller is needed to track the model uncertainty. Second, the adaptive controller additionally needs to be robust to noise and disturbances. Third, theoretical analyses of stability and robustness are needed as prerequisites for stable operation of the controller in practical applications.

APPROACH

We develop a robust adaptive neuromodulation algorithm that solves the above three problems. First, we develop a state-space brain network model that explicitly includes nonlinear terms of real-time model uncertainty and design an adaptive controller to track and cancel the model uncertainty. Second, to improve the robustness of the adaptive controller, we design two linear filters to increase steady-state control accuracy and reduce sensitivity to high-frequency noise and disturbances. Third, we conduct theoretical analyses to prove the stability of the neuromodulation algorithm and establish a trade-off between stability and robustness, which we further use to optimize the algorithm design. Finally, we validate the algorithm using comprehensive Monte Carlo simulations that span a broad range of model nonlinearity, uncertainty, and complexity.

MAIN RESULTS

The robust adaptive neuromodulation algorithm accurately tracks various types of target brain state trajectories, enables stable and robust control, and significantly outperforms state-of-the-art neuromodulation algorithms.

SIGNIFICANCE

Our algorithm has implications for future designs of precise, stable, and robust closed-loop brain stimulation systems to treat brain disorders and facilitate brain functions.

Consistent Changes in Cortico-Subthalamic Directed Connectivity Are Associated With the Induction of Parkinsonism in a Chronically Recorded Non-human Primate Model

Parkinson’s disease is a neurological disease with cardinal motor signs including bradykinesia and tremor. Although beta-band hypersynchrony in the cortico-basal ganglia network is thought to contribute to disease manifestation, the resulting effects on network connectivity are unclear. We examined local field potentials from a non-human primate across the naïve, mild, and moderate disease states (model was asymmetric, left-hemispheric dominant) and probed power spectral density as well as cortico-cortical and cortico-subthalamic connectivity using both coherence and Granger causality, which measure undirected and directed effective connectivity, respectively. Our network included the left subthalamic nucleus (L-STN), bilateral primary motor cortices (L-M1, R-M1), and bilateral premotor cortices (L-PMC, R-PMC). Results showed two distinct peaks (Peak A at 5–20 Hz, Peak B at 25–45 Hz) across all analyses. Power and coherence analyses showed widespread increases in power and connectivity in both the Peak A and Peak B bands with disease progression. For Granger causality, increases in Peak B connectivity and decreases in Peak A connectivity were associated with the disease. Induction of mild disease was associated with several changes in connectivity: (1) the cortico-subthalamic connectivity in the descending direction (L-PMC to L-STN) decreased in the Peak A range while the reciprocal, ascending connectivity (L-STN to L-PMC) increased in the Peak B range; this may play a role in generating beta-band hypersynchrony in the cortex, (2) both L-M1 to L-PMC and R-M1 to R-PMC causalities increased, which may either be compensatory or a pathologic effect of disease, and (3) a decrease in connectivity occurred from the R-PMC to R-M1. The only significant change seen between mild and moderate disease was increased right cortical connectivity, which may reflect compensation for the left-hemispheric dominant moderate disease state.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.