History information emerges in the cortex during learning.

We learn from our experience but the underlying neuronal mechanisms incorporating past information to facilitate learning is relatively unknown. Specifically, which cortical areas encode history-related information and how is this information modulated across learning? To study the relationship between history and learning, we continuously imaged cortex-wide calcium dynamics as mice learn to use their whiskers to discriminate between two different textures. We mainly focused on comparing the same trial type with different trial history, that is, a different preceding trial. We found trial history information in barrel cortex (BC) during stimulus presentation. Importantly, trial history in BC emerged only as the mouse learned the task. Next, we also found learning-dependent trial history information in rostrolateral (RL) association cortex that emerges before stimulus presentation, preceding activity in BC. Trial history was also encoded in other cortical areas and was not related to differences in body movements. Interestingly, a binary classifier could discriminate trial history at the single trial level just as well as current information both in BC and RL. These findings suggest that past experience emerges in the cortex around the time of learning, starting from higher-order association area RL and propagating down (i.e., top-down projection) to lower-order BC where it can be integrated with incoming sensory information. This integration between the past and present may facilitate learning.

Deep Brain Stimulation Can Differentiate Subregions of the Human Subthalamic Nucleus Area by EEG Biomarkers.

Introduction: Precise lead localization is crucial for an optimal clinical outcome of subthalamic nucleus (STN) deep brain stimulation (DBS) treatment in patients with Parkinson's disease (PD). Currently, anatomical measures, as well as invasive intraoperative electrophysiological recordings, are used to locate DBS electrodes. The objective of this study was to find an alternative electrophysiology tool for STN DBS lead localization. Methods: Sixty-one postoperative electrophysiology recording sessions were obtained from 17 DBS-treated patients with PD. An intraoperative physiological method automatically detected STN borders and subregions. Postoperative EEG cortical activity was measured, while STN low frequency stimulation (LFS) was applied to different areas inside and outside the STN. Machine learning models were used to differentiate stimulation locations, based on EEG analysis of engineered features. Results: A machine learning algorithm identified the top 25 evoked response potentials (ERPs), engineered features that can differentiate inside and outside STN stimulation locations as well as within STN stimulation locations. Evoked responses in the medial and ipsilateral fronto-central areas were found to be most significant for predicting the location of STN stimulation. Two-class linear support vector machine (SVM) predicted the inside (dorso-lateral region, DLR, and ventro-medial region, VMR) vs. outside [zona incerta, ZI, STN stimulation classification with an accuracy of 0.98 and 0.82 for ZI vs. VMR and ZI vs. DLR, respectively, and an accuracy of 0.77 for the within STN (DLR vs. VMR)]. Multiclass linear SVM predicted all areas with an accuracy of 0.82 for the outside and within STN stimulation locations (ZI vs. DLR vs. VMR). Conclusions: Electroencephalogram biomarkers can use low-frequency STN stimulation to localize STN DBS electrodes to ZI, DLR, and VMR STN subregions. These models can be used for both intraoperative electrode localization and postoperative stimulation programming sessions, and have a potential to improve STN DBS clinical outcomes.

Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients.

Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.

Independently together: subthalamic theta and beta opposite roles in predicting Parkinson's tremor.

Tremor is a core feature of Parkinson's disease and the most easily recognized Parkinsonian sign. Nonetheless, its pathophysiology remains poorly understood. Here, we show that multispectral spiking activity in the posterior-dorso-lateral oscillatory (motor) region of the subthalamic nucleus distinguishes resting tremor from the other Parkinsonian motor signs and strongly correlates with its severity. We evaluated microelectrode-spiking activity from the subthalamic dorsolateral oscillatory region of 70 Parkinson's disease patients who underwent deep brain stimulation surgery (114 subthalamic nuclei, 166 electrode trajectories). We then investigated the relationship between patients' clinical Unified Parkinson's Disease Rating Scale score and their peak theta (4-7 Hz) and beta (13-30 Hz) powers. We found a positive correlation between resting tremor and theta activity (r = 0.41, P < 0.01) and a non-significant negative correlation with beta activity (r = -0.2, P = 0.5). Hypothesizing that the two neuronal frequencies mask each other's relationship with resting tremor, we created a non-linear model of their proportional spectral powers and investigated its relationship with resting tremor. As hypothesized, patients' proportional scores correlated better than either theta or beta alone (r = 0.54, P < 0.001). However, theta and beta oscillations were frequently temporally correlated (38/70 patients manifested significant positive temporal correlations and 1/70 exhibited significant negative correlation between the two frequency bands). When comparing theta and beta temporal relationship (r θ ß) to patients' resting tremor scores, we found a significant negative correlation between the two (r = -0.38, P < 0.01). Patients manifesting a positive correlation between the two bands (i.e. theta and beta were likely to appear simultaneously) were found to have lower resting tremor scores than those with near-zero correlation values (i.e. theta and beta were likely to appear separately). We therefore created a new model incorporating patients' proportional theta-beta power and r θ ßscores to obtain an improved neural correlate of resting tremor (r = 0.62, P < 0.001). We then used the Akaike and Bayesian information criteria for model selection and found the multispectral model, incorporating theta-beta proportional power and their correlation, to be the best fitting model, with 0.96 and 0.89 probabilities, respectively. Here we found that as theta increases, beta decreases and the two appear separately-resting tremor is worsened. Our results therefore show that theta and beta convey information about resting tremor in opposite ways. Furthermore, the finding that theta and beta coactivity is negatively correlated with resting tremor suggests that theta-beta non-linear scale may be a valuable biomarker for Parkinson's resting tremor in future adaptive deep brain stimulation techniques.

Movement context modulates neuronal activity in motor and limbic-associative domains of the human parkinsonian subthalamic nucleus.

The subthalamic nucleus (STN), a preferred target for treating movement disorders, has a crucial role in inhibition and execution of movement. To better understand the mechanism of movement regulation in the STN of Parkinson's disease patients, we compared the same movement with different context, facilitation vs. inhibition context. We recorded subthalamic multiunit activity intra-operatively while parkinsonian patients (off medications, n = 43 patients, 173 recording sites) performed increasingly complex oddball paradigms with frequent and deviant tones: first, passive listening to tone series with no movement ('None-Go' task, n = 7, 28 recording sites); second, pressing a button after every tone ('All-Go' task, n = 7, 26 recording sites); and third, pressing a button only for frequent tones, thus adding inhibition of movement following deviant tones ('Go-NoGo' task, n = 29, 119 recording sites). The STN responded mainly to movement-involving tasks. In the limbic-associative STN, evoked response to the deviant tone (inhibitory cue) was not significantly different between the Go-NoGo and the All-Go task. However, the evoked response to the frequent tone (go cue) in the Go-NoGo task was significantly reduced. The reduction was mainly prominent in the negative component of the evoked response amplitude aligned to the press. Successful movement inhibition was correlated with higher baseline activity. We suggest that the STN in Parkinson's disease patients adapts to movement inhibition context by selectively decreasing the amplitude of neuronal activity. Thus, the STN enables movement inhibition not by increasing responses to the inhibitory cue but by reducing responses to the release cue. The negative component of the evoked response probably facilitates movement and a higher baseline activity enables successful inhibition of movement. These discharge modulations were found in the ventromedial, non-motor domain of the STN and therefore suggest a significant role of the limbic- associative STN domains in movement planning and in global movement regulation.

Theta-alpha oscillations characterize emotional subregion in the human ventral subthalamic nucleus.

BACKGROUND: Therapeutic outcomes of STN-DBS for movement and psychiatric disorders depend on electrode location within the STN. Electrophysiological and functional mapping of the STN has progressed considerably in the past years, identifying beta-band oscillatory activity in the dorsal STN as a motor biomarker. It also has been suggested that STN theta-alpha oscillations, involved in impulse control and action inhibition, have a ventral source. However, STN local field potential mapping of motor, associative, and limbic areas is often limited by poor spatial resolution. OBJECTIVES: Providing a high-resolution electrophysiological map of the motor, associative and limbic anatomical sub-areas of the subthalamic nucleus. METHODS: We have analyzed high-spatial-resolution STN microelectrode electrophysiology recordings of PD patients (n = 303) that underwent DBS surgery. The patients' STN intraoperative recordings of spiking activity (933 electrode trajectories) were combined with their imaging data (n = 83 patients, 151 trajectories). RESULTS: We found a high theta-alpha (7-10 Hz) oscillatory area, located near the STN ventromedial border in 29% of the PD patients. Theta-alpha activity in this area has higher power and lower central frequency in comparison to theta-alpha activity in more dorsal subthalamic areas. When projected on the DISTAL functional atlas, the theta-alpha oscillatory area overlaps with the STN limbic subarea. CONCLUSIONS: We suggest that theta-alpha oscillations can serve as an electrophysiological marker for the ventral subthalamic nucleus limbic subarea. Therefore, theta-alpha oscillations can guide optimal electrode placement in neuropsychiatric STN-DBS procedures and provide a reliable biomarker input for future closed-loop DBS device. © 2019 International Parkinson and Movement Disorder Society.

Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a proven and effective therapy for the management of the motor symptoms of Parkinson's disease (PD). While accurate positioning of the stimulating electrode is critical for success of this therapy, precise identification of the STN based on imaging can be challenging. We developed a method to accurately visualize the STN on a standard clinical magnetic resonance imaging (MRI). The method incorporates a database of 7-Tesla (T) MRIs of PD patients together with machine-learning methods (hereafter 7 T-ML). OBJECTIVE: To validate the clinical application accuracy of the 7 T-ML method by comparing it with identification of the STN based on intraoperative microelectrode recordings. METHODS: Sixteen PD patients who underwent microelectrode-recordings guided STN DBS were included in this study (30 implanted leads and electrode trajectories). The length of the STN along the electrode trajectory and the position of its contacts to dorsal, inside, or ventral to the STN were compared using microelectrode-recordings and the 7 T-ML method computed based on the patient's clinical 3T MRI. RESULTS: All 30 electrode trajectories that intersected the STN based on microelectrode-recordings, also intersected it when visualized with the 7 T-ML method. STN trajectory average length was 6.2 ± 0.7 mm based on microelectrode recordings and 5.8 ± 0.9 mm for the 7 T-ML method. We observed a 93% agreement regarding contact location between the microelectrode-recordings and the 7 T-ML method. CONCLUSION: The 7 T-ML method is highly consistent with microelectrode-recordings data. This method provides a reliable and accurate patient-specific prediction for targeting the STN.

Subthalamic theta activity: a novel human subcortical biomarker for obsessive compulsive disorder.

Obsessive-compulsive disorder (OCD) is a common and serious psychiatric disorder. Although subthalamic nucleus deep brain stimulation (DBS) has been studied as a treatment for OCD patients the underlying mechanism of this treatment and the optimal method of stimulation are unknown. To study the neural basis of subthalamic nucleus DBS in OCD patients we used a novel, implantable DBS system with long-term local field potential sensing capability. We focus our analysis on two patients with OCD who experienced severe treatment-resistant symptoms and were implanted with subthalamic nucleus DBS systems. We studied them for a year at rest and during provocation of OCD symptoms (46 recording sessions) and compared them to four Parkinson's disease (PD) patients implanted with subthalamic nucleus DBS systems (69 recording sessions). We show that the dorsal (motor) area of the subthalamic nucleus in OCD patients displays a beta (25-35 Hz) oscillatory activity similar to PD patients whereas the ventral (limbic-cognitive) area of the subthalamic nucleus displays distinct theta (6.5-8 Hz) oscillatory activity only in OCD patients. The subthalamic nucleus theta oscillatory activity decreases with provocation of OCD symptoms and is inversely correlated with symptoms severity over time. We conclude that beta oscillations at the dorsal subthalamic nucleus in OCD patients challenge their pathophysiologic association with movement disorders. Furthermore, theta oscillations at the ventral subthalamic nucleus in OCD patients suggest a new physiological target for OCD therapy as well as a promising input signal for future emotional-cognitive closed-loop DBS.

Local vs. volume conductance activity of field potentials in the human subthalamic nucleus.

Subthalamic nucleus field potentials have attracted growing research and clinical interest over the last few decades. However, it is unclear whether subthalamic field potentials represent locally generated neuronal subthreshold activity or volume conductance of the organized neuronal activity generated in the cortex. This study aimed at understanding of the physiological origin of subthalamic field potentials and determining the most accurate method for recording them. We compared different methods of recordings in the human subthalamic nucleus: spikes (300-9,000 Hz) and field potentials (3-100 Hz) recorded by monopolar micro- and macroelectrodes, as well as by differential-bipolar macroelectrodes. The recordings were done outside and inside the subthalamic nucleus during electrophysiological navigation for deep brain stimulation procedures (150 electrode trajectories) in 41 Parkinson's disease patients. We modeled the signal and estimated the contribution of nearby/independent vs. remote/common activity in each recording configuration and area. Monopolar micro- and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity. However, bipolar macroelectrode recordings inside the subthalamic nucleus can detect locally generated potentials. These results are confirmed by high correspondence between the model predictions and actual correlation of neuronal activity recorded by electrode pairs. Differential bipolar macroelectrode subthalamic field potentials can overcome volume conductance effects and reflect locally generated neuronal activity. Bipolar macroelectrode local field potential recordings might be used as a biological marker of normal and pathological brain functions for future electrophysiological studies and navigation systems as well as for closed-loop deep brain stimulation paradigms.NEW & NOTEWORTHY Our results integrate a new method for human subthalamic recordings with a development of an advanced mathematical model. We found that while monopolar microelectrode and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity, bipolar macroelectrode recordings inside the subthalamic nucleus (STN) detect locally generated potentials that are significantly different than those recorded outside the STN. Differential bipolar subthalamic field potentials can be used in navigation and closed-loop deep brain stimulation paradigms.

Anesthesia reduces discharge rates in the human pallidum without changing the discharge rate ratio between pallidal segments.

Classical rate models of basal ganglia circuitry associate discharge rate of the globus pallidus external and internal segments (GPe, GPi respectively) solely with dopaminergic state and predict an inverse ratio between the discharge rates of the two pallidal segments. In contrast, the effects of other rate modulators such as general anesthesia (GA) on this ratio have been ignored. To respond to this need, we recorded the neuronal activity in the GPe and GPi in awake and anesthetized human patients with dystonia (57 and 53 trajectories respectively) and in awake patients with Parkinson's disease (PD, 16 trajectories) undergoing deep brain stimulation procedures. This triad enabled us to dissociate pallidal discharge ratio from general discharge modulation. An automatic offline spike detection and isolation quality system was used to select 1560 highly isolated units for analysis. The mean discharge rate in the GPi of awake PD patients was dramatically higher than in awake dystonia patients although the firing rate in the GPe was similar. Firing rates in dystonic patients under anesthesia were lower in both nuclei. Surprisingly, in all three groups, GPe firing rates were correlated with firing rates in the ipsilateral GPi. Thus, the firing rate ratio of ipsilateral GPi/GPe pairs was similar in awake and anesthetized patients with dystonia and significantly higher in PD. We suggest that pallidal activity is modulated by at least two independent processes: dopaminergic state which changes the GPi/GPe firing rate ratio, and anesthesia which modulates firing rates in both pallidal nuclei without changing the ratio between their firing rates.

Constant Current versus Constant Voltage Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease.

Background: Subthalamic nucleus (STN) deep brain stimulation (DBS) is an established therapy for advanced Parkinson's disease (PD). Motor efficacy and safety have been established for constant voltage (CV) devices and more recently for constant current (CC) devices. CC devices adjust output voltage to provide CC stimulation irrespective of impedance fluctuation, while the current applied by CV stimulation depends on the impedance that may change over time. No study has directly compared the clinical effects of these two stimulation modalities. Objective: To compare the safety and clinical impact of CC STN DBS to CV STN DBS in patients with advanced PD 2 years after surgery. Methods: Patients were eligible for inclusion if they had undergone STN DBS surgery for idiopathic PD, had been implanted with a Medtronic Activa PC and if their stimulation program and medication had been stable for at least 1 year. This single-center trial was designed as a double-blind, randomized, prospective study with crossover after 2 weeks. Motor equivalence of the 2 modalities was confirmed utilizing part III of the Unified Parkinson's Disease Rating Scale (UPDRS). PD diaries and multiple subjective and objective evaluations of quality of life, depression, cognition and emotional processing were evaluated on both CV and on CC stimulation. Analysis using the paired t test with Bonferroni correction for multiple comparisons was performed to identify any significant difference between the stimulation modalities. Results: 8 patients were recruited (6 men, 2 women); 1 patient did not complete the study. The average age at surgery was 56.7 years (range 47-63). Disease duration at the time of surgery was 7.5 years (range 3-12). Patients were recruited 23.8 months (range 22.5-24) after surgery. At the postoperative study baseline, this patient group showed an average motor improvement of 69% (range 51-97) as measured by the change in UPDRS part III with stimulation alone. Levodopa equivalent medication was reduced on average by 67% (range 15-88). Patients were poorly compliant with PD diaries, and these did not yield useful information. The minor deterioration in quality-of-life scores (Parkinson's Disease Questionnaire-39, Quality of Life Enjoyment and Satisfaction Questionnaire) with CC stimulation were not statistically significant. Two measures of depression (Hamilton Rating Scale D17, Quick Inventory of Depressive Symptomatology - Self-Report) showed a nonsignificant lower score (less depression) with CC stimulation, but a third (Beck Depression Inventory) showed equivalence. Cognitive testing (Mini Mental State Examination) and emotional processing (Montreal Affective Voices) were equivalent for CC and CV. Conclusion: CC STN DBS is safe. For equivalent motor efficacy, no significant difference could be identified between CC and CV stimulation for nonmotor evaluations in PD patients 2 years after surgery. © 2015 S. Karger AG, Basel.

Neurons in both pallidal segments change their firing properties similarly prior to closure of the eyes.

Current anatomical models of the cortico-basal ganglia (BG) network predict reciprocal discharge patterns between the external and internal segments of the globus pallidus (GPe and GPi, respectively), as well as cortical driving of BG activity. However, physiological studies revealing similarity in the transient responses of GPe and GPi neurons cast doubts on these predictions. Here, we studied the discharge properties of GPe, GPi, and primary motor cortex neurons of two monkeys in two distinct states: when eyes are open versus when they are closed. Both pallidal populations exhibited decreased discharge rates in the "eye closed" state accompanied by elevated values of the coefficient of variation (CV) of their interspike interval (ISI) distributions. The pallidal modulations in discharge patterns were partially attributable to larger fractions of longer ISIs in the "eye closed" state. In addition, the pallidal discharge modulations were gradual, starting prior to closing of the eyes. Cortical neurons, as opposed to pallidal neurons, increased their discharge rates steeply on closure of the eyes. Surprisingly, the cortical rate modulations occurred after pallidal modulations. However, as in the pallidum, the CV values of cortical ISI distributions increased in the "eye closed" state, indicating a more bursty discharge pattern in that state. Thus changes in GPe and GPi discharge properties were positively correlated, suggesting that the subthalamic nucleus and/or the striatum constitute the main common driving force for both pallidal segments. Furthermore, the early, unexpected changes in the pallidum are better explained by a subcortical rather than a cortical loop through the BG.

Low-pass filter properties of basal ganglia cortical muscle loops in the normal and MPTP primate model of parkinsonism.

Oscillatory bursting activity is commonly found in the basal ganglia (BG) and the thalamus of the parkinsonian brain. The frequency of these oscillations is often similar to or higher than that of the parkinsonian tremor, but their relationship to the tremor and other parkinsonian symptoms is still under debate. We studied the frequency dependency of information transmission in the cortex-BG and cortex-periphery loops by recording simultaneously from multiple electrodes located in the arm-related primary motor cortex (MI) and in the globus pallidus (GP) of two vervet monkeys before and after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment and induction of parkinsonian symptoms. We mimicked the parkinsonian bursting oscillations by stimulating with 35 ms bursts given at different frequencies through microelectrodes located in MI or GP while recording the evoked neuronal and motor responses. In the normal state, microstimulation of MI or GP does not modulate the discharge rate in the other structure. However, the functional-connectivity between MI and GP is greatly enhanced after MPTP treatment. In the frequency domain, GP neurons usually responded equally to 1-15 Hz stimulation bursts in both states. In contrast, MI neurons demonstrated low-pass filter properties, with a cutoff frequency above 5 Hz for the MI stimulations, and below 5 Hz for the GP stimulations. Finally, muscle activation evoked by MI microstimulation was markedly attenuated at frequencies higher than 5 Hz. The low-pass properties of the pathways connecting GP to MI to muscles suggest that parkinsonian tremor is not directly driven by the BG 5-10 Hz burst oscillations despite their similar frequencies.

Basal ganglia oscillations and pathophysiology of movement disorders.

Low frequency rest tremor is one of the cardinal signs of Parkinson's disease and some of its animal models. Current physiological studies and models of the basal ganglia differ as to which aspects of neuronal activity are crucial to the pathophysiology of Parkinson's disease. There is evidence that neural oscillations and synchronization play a central role in the generation of the disease. However, parkinsonian tremor is not strictly correlated with the synchronous oscillations in the basal ganglia networks. Rather, abnormal basal ganglia output enforces abnormal thalamo-cortical processing leading to akinesia, the main negative symptom of Parkinson's disease. Parkinsonian tremor has probably evolved as a downstream compensatory mechanism.