Neurophysiological responses of globus pallidus internus during the auditory oddball task in Parkinson's disease

Modulation of neuronal activity in human centromedian nucleus during an auditory attention and working memory task

Centromedian nucleus (CM) is one of several intralaminar nuclei of the thalamus and is thought to be involved in consciousness, arousal, and attention. CM has been suggested to play a key role in the control of attention, by regulating the flow of information to different brain regions such as the ascending reticular system, basal ganglia, and cortex. While the neurophysiology of attention in visual and auditory systems has been studied in animal models, combined single unit and LFP recordings in human have not, to our knowledge, been reported. Here, we recorded neuronal activity in the CM nucleus in 11 patients prior to insertion of deep brain stimulation electrodes for the treatment of epilepsy while subjects performed an auditory attention task. Patients were requested to attend and count the infrequent (p = 0.2) odd or "deviant" tones, ignore the frequent standard tones and report the total number of deviant tones at trial completion. Spikes were discriminated, and LFPs were band pass filtered (5-45 Hz). Average peri‑stimulus time histograms and spectra were constructed by aligning on tone onsets and statistically compared. The firing rate of CM neurons showed selective, multi-phasic responses to deviant tones in 81% of the tested neurons. Local field potential analysis showed selective beta and low gamma (13-45 Hz) modulations in response to deviant tones, also in a multi-phasic pattern. The current study demonstrates that CM neurons are under top-down control and participate in the selective processing during auditory attention and working memory. These results, taken together, implicate the CM in selective auditory attention and working memory and support a role of beta and low gamma oscillatory activity in cognitive processes. It also has potential implications for DBS therapy for epilepsy and non-motor symptoms of PD, such as apathy and other disorders of attention.

Cortical modulations before lower limb motor blocks are associated with freezing of gait in Parkinson's disease: an EEG source localization study

BACKGROUND

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) characterized by paroxysmal episodes in which patients are unable to step forward. A research priority is identifying cortical changes before freezing in PD-FOG.

METHODS

We tested 19 patients with PD who had been assessed for FOG (n=14 with FOG and 5 without FOG). While seated, patients stepped bilaterally on pedals to progress forward through a virtual hallway while 64-channel EEG was recorded. We assessed cortical activities before and during lower limb motor blocks (LLMB), defined as a break in rhythmic pedaling, and stops, defined as movement cessation following an auditory stop cue. This task was selected because LLMB correlates with FOG severity in PD and allows recording of high-quality EEG. Patients were tested after overnight withdrawal from dopaminergic medications ("off" state) and in the "on" medications state. EEG source activities were evaluated using individual MRI and standardized low resolution brain electromagnetic tomography (sLORETA). Functional connectivity was evaluated by phase lag index between seeds and pre-defined cortical regions of interest.

RESULTS

EEG source activities for LLMB vs. cued stops localized to right posterior parietal area (Brodmann area 39), lateral premotor area (Brodmann area 6), and inferior frontal gyrus (Brodmann area 47). In these areas, PD-FOG (n=14) increased alpha rhythms (8-12 Hz) before LLMB vs. typical stepping, whereas PD without FOG (n=5) decreased alpha power. Alpha rhythms were linearly correlated with LLMB severity, and the relationship became an inverted U-shape when assessing alpha rhythms as a function of percent time in LLMB in the "off" medication state. Right inferior frontal gyrus and supplementary motor area connectivity was observed before LLMB in the beta band (13-30 Hz). This same pattern of connectivity was seen before stops. Dopaminergic medication improved FOG and led to less alpha synchronization and increased functional connections between frontal and parietal areas.

CONCLUSIONS

Right inferior parietofrontal structures are implicated in PD-FOG. The predominant changes were in the alpha rhythm, which increased before LLMB and with LLMB severity. Similar connectivity was observed for LLMB and stops between the right inferior frontal gyrus and supplementary motor area, suggesting that FOG may be a form of "unintended stopping." These findings may inform approaches to neurorehabilitation of PD-FOG.

Auditory oddball responses in the human subthalamic nucleus and substantia nigra pars reticulata

The auditory oddball is a mainstay in research on attention, novelty, and sensory prediction. How this task engages subcortical structures like the subthalamic nucleus and substantia nigra pars reticulata is unclear. We administered an auditory OB task while recording single unit activity (35 units) and local field potentials (57 recordings) from the subthalamic nucleus and substantia nigra pars reticulata of 30 patients with Parkinson's disease undergoing deep brain stimulation surgery. We found tone modulated and oddball modulated units in both regions. Population activity differentiated oddball from standard trials from 200 ms to 1000 ms after the tone in both regions. In the substantia nigra, beta band activity in the local field potential was decreased following oddball tones. The oddball related activity we observe may underlie attention, sensory prediction, or surprise-induced motor suppression.

Subthalamic and pallidal neurons are modulated during externally cued movements in Parkinson's disease

External sensory cues can reduce freezing of gait in people with Parkinson's disease (PD), yet the role of the basal ganglia in these movements is unclear. We used microelectrode recordings to examine modulations in single unit (SU) and oscillatory local field potentials (LFP) during auditory-cued rhythmic pedaling movements of the feet. We tested five blocks of increasing cue frequencies (1 Hz, 1.5 Hz, 2 Hz, 2.5 Hz, and 3 Hz) in 24 people with PD undergoing deep brain stimulation surgery of the subthalamic nucleus (STN) or globus pallidus internus (GPi). Single unit firing and beta band LFPs (13-30 Hz) in response to movement onsets or cue onsets were examined. We found that the timing accuracy of foot pedaling decreased with faster cue frequencies. Increasing cue frequencies also attenuated firing rates in both STN and GPi neurons. Peak beta power in the GPi and STN showed different responses to the task. GPi beta power showed persistent suppression with fast cues and phasic modulation with slow cues. STN beta power showed enhanced beta synchronization following movement. STN beta power also correlated with rate of pedaling. Overall, we showed task-related responses in the GPi and STN during auditory-cued movements with differential roles in sensory and motor control. The results suggest a role for both input and output basal ganglia nuclei in auditory rhythmic pacing of gait-like movements in PD.

Aberrations in temporal dynamics of cognitive processing induced by Parkinson's disease and Levodopa

The motor symptoms of Parkinson's disease (PD) have been shown to significantly improve by Levodopa. However, despite the widespread adoption of Levodopa as a standard pharmaceutical drug for the treatment of PD, cognitive impairments linked to PD do not show visible improvement with Levodopa treatment. Furthermore, the neuronal and network mechanisms behind the PD-induced cognitive impairments are not clearly understood. In this work, we aim to explain these cognitive impairments, as well as the ones exacerbated by Levodopa, through examining the differential dynamic patterns of the phase-amplitude coupling (PAC) during cognitive functions. EEG data recorded in an auditory oddball task performed by a cohort consisting of controls and a group of PD patients during both on and off periods of Levodopa treatment were analyzed to derive the temporal dynamics of the PAC across the brain. We observed distinguishing patterns in the PAC dynamics, as an indicator of information binding, which can explain the slower cognitive processing associated with PD in the form of a latency in the PAC peak time. Thus, considering the high-level connections between the hippocampus, the posterior and prefrontal cortices established through the dorsal and ventral striatum acting as a modulatory system, we posit that the primary issue with cognitive impairments of PD, as well as Levodopa's cognitive deficit side effects, can be attributed to the changes in temporal dynamics of dopamine release influencing the modulatory function of the striatum.

Uncovering the neurophysiology of mood, motivation and behavioral symptoms in Parkinson's disease through intracranial recordings

Neuropsychiatric mood and motivation symptoms (depression, anxiety, apathy, impulse control disorders) in Parkinson's disease (PD) are highly disabling, difficult to treat and exacerbated by current medications and deep brain stimulation therapies. High-resolution intracranial recording techniques have the potential to undercover the network dysfunction and cognitive processes that drive these symptoms, towards a principled re-tuning of circuits. We highlight intracranial recording as a valuable tool for mapping and desegregating neural networks and their contribution to mood, motivation and behavioral symptoms, via the ability to dissect multiplexed overlapping spatial and temporal neural components. This technique can be powerfully combined with behavioral paradigms and emerging computational techniques to model underlying latent behavioral states. We review the literature of intracranial recording studies investigating mood, motivation and behavioral symptomatology with reference to 1) emotional processing, 2) executive control 3) subjective valuation (reward & cost evaluation) 4) motor control and 5) learning and updating. This reveals associations between different frequency specific network activities and underlying cognitive processes of reward decision making and action control. If validated, these signals represent potential computational biomarkers of motivational and behavioural states and could lead to principled therapy development for mood, motivation and behavioral symptoms in PD.

Evaluation of major depressive disorder using 7 Tesla phase sensitive neuroimaging before and after mindfulness-based cognitive therapy

OBJECTIVE

We applied 7 Tesla phase sensitive imaging to evaluate the impact of brain iron levels on depression severity and cognitive function in individuals with major depressive disorder (MDD) treated with mindfulness-based cognitive therapy (MBCT).

METHODS

Seventeen unmedicated MDD participants underwent MRI, evaluation of depression severity, and cognitive testing before and after receiving MBCT, compared to fourteen healthy controls (HC). Local field shift (LFS) values, measures of brain iron levels, were derived from phase images in the putamen, caudate, globus pallidus (GP), anterior cingulate cortex (ACC) and thalamus.

RESULTS

Compared to the HC group, the MDD group had significantly lower baseline LFS (indicative of higher iron) in the left GP and left putamen and had a higher number of subjects with impairment in a test of information processing speed. In the MDD group, lower LFS values in the left and right ACC, right putamen, right GP, and right thalamus were significantly associated with depression severity; and lower LFS in the right GP was correlated with worse performance on measures of attention. All MBCT participants experienced depression relief. MBCT treatment also significantly improved executive function and attention. MBCT participants with lower baseline LFS values in the right caudate experienced significantly greater improvement in depression severity with treatment; and those with lower LFS values in the right ACC, right caudate, and right GB at baseline performed better on measures of verbal learning and memory after MBCT.

CONCLUSIONS

Our study highlights the potential contribution of subtle differences in brain iron to MDD symptoms and their successful treatment.

Landscape and future directions of machine learning applications in closed-loop brain stimulation

Brain stimulation (BStim) encompasses multiple modalities (e.g., deep brain stimulation, responsive neurostimulation) that utilize electrodes implanted in deep brain structures to treat neurological disorders. Currently, BStim is primarily used to treat movement disorders such as Parkinson's, though indications are expanding to include neuropsychiatric disorders like depression and schizophrenia. Traditional BStim systems are "open-loop" and deliver constant electrical stimulation based on manually-determined parameters. Advancements in BStim have enabled development of "closed-loop" systems that analyze neural biomarkers (e.g., local field potentials in the sub-thalamic nucleus) and adjust electrical modulation in a dynamic, patient-specific, and energy efficient manner. These closed-loop systems enable real-time, context-specific stimulation adjustment to reduce symptom burden. Machine learning (ML) has emerged as a vital component in designing these closed-loop systems as ML models can predict / identify presence of disease symptoms based on neural activity and adaptively learn to modulate stimulation. We queried the US National Library of Medicine PubMed database to understand the role of ML in developing closed-loop BStim systems to treat epilepsy, movement disorders, and neuropsychiatric disorders. Both neural and non-neural network ML algorithms have successfully been leveraged to create closed-loop systems that perform comparably to open-loop systems. For disorders in which the underlying neural pathophysiology is relatively well understood (e.g., Parkinson's, essential tremor), most work has involved refining ML models that can classify neural signals as aberrant or normal. The same is seen for epilepsy, where most current research has focused on identifying optimal ML model design and integrating closed-loop systems into existing devices. For neuropsychiatric disorders, where the underlying pathologic neural circuitry is still being investigated, research is focused on identifying biomarkers (e.g., local field potentials from brain nuclei) that ML models can use to identify onset of symptoms and stratify severity of disease.

Top-down control of human motor thalamic neuronal activity during the auditory oddball task

The neurophysiology of selective attention in visual and auditory systems has been studied in animal models but not with single unit recordings in human. Here, we recorded neuronal activity in the ventral intermediate nucleus as well as the ventral oral anterior, and posterior nuclei of the motor thalamus in 25 patients with parkinsonian (n = 6) and non-parkinsonian tremors (n = 19) prior to insertion of deep brain stimulation electrodes while they performed an auditory oddball task. In this task, patients were requested to attend and count the randomly occurring odd or "deviant" tones, ignore the frequent standard tones and report the number of deviant tones at trial completion. The neuronal firing rate decreased compared to baseline during the oddball task. Inhibition was specific to auditory attention as incorrect counting or wrist flicking to the deviant tones did not produce such inhibition. Local field potential analysis showed beta (13-35 Hz) desynchronization in response to deviant tones. Parkinson's disease patients off medications had more beta power than the essential tremor group but less neuronal modulation of beta power to the attended tones, suggesting that dopamine modulates thalamic beta oscillations for selective attention. The current study demonstrated that ascending information to the motor thalamus can be suppressed during auditory attending tasks, providing indirect evidence for the searchlight hypothesis in humans. These results taken together implicate the ventral intermediate nucleus in non-motor cognitive functions, which has implications for the brain circuitry for attention and the pathophysiology of Parkinson's disease.

Clinical neurophysiology of Parkinson's disease and parkinsonism

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This review is part of the series on the clinical neurophysiology of movement disorders and focuses on Parkinson’s disease and parkinsonism.

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The pathophysiology of cardinal parkinsonian motor symptoms and myoclonus are reviewed.

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The recordings from microelectrode and deep brain stimulation electrodes are reported in detail.

This review is part of the series on the clinical neurophysiology of movement disorders. It focuses on Parkinson’s disease and parkinsonism. The topics covered include the pathophysiology of tremor, rigidity and bradykinesia, balance and gait disturbance and myoclonus in Parkinson’s disease. The use of electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies of cortical excitability with single and paired transcranial magnetic stimulation, studies of plasticity, intraoperative microelectrode recordings and recording of local field potentials from deep brain stimulation, and electrocorticography are also reviewed. In addition to advancing knowledge of pathophysiology, neurophysiological studies can be useful in refining the diagnosis, localization of surgical targets, and help to develop novel therapies for Parkinson’s disease.