Detection of evoked resonant neural activity in Parkinson's disease.

Objective. This study investigated a machine-learning approach to detect the presence of evoked resonant neural activity (ERNA) recorded during deep brain stimulation (DBS) of the subthalamic nucleus (STN) in people with Parkinson's disease.Approach. Seven binary classifiers were trained to distinguish ERNA from the background neural activity using eight different time-domain signal features.Main results. Nested cross-validation revealed a strong classification performance of 99.1% accuracy, with 99.6% specificity and 98.7% sensitivity to detect ERNA. Using a semi-simulated ERNA dataset, the results show that a signal-to-noise ratio of 15 dB is required to maintain a 90% classifier sensitivity. ERNA detection is feasible with an appropriate combination of signal processing, feature extraction and classifier. Future work should consider reducing the computational complexity for use in real-time applications.Significance. The presence of ERNA can be used to indicate the location of a DBS electrode array during implantation surgery. The confidence score of the detector could be useful for assisting clinicians to adjust the position of the DBS electrode array inside/outside the STN.

Can brain signals and anatomy refine contact choice for deep brain stimulation in Parkinson's disease?

INTRODUCTION: Selecting the ideal contact to apply subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson's disease is time-consuming and reliant on clinical expertise. The aim of this cohort study was to assess whether neuronal signals (beta oscillations and evoked resonant neural activity (ERNA)), and the anatomical location of electrodes, can predict the contacts selected by long-term, expert-clinician programming of STN-DBS. METHODS: We evaluated 92 hemispheres of 47 patients with Parkinson's disease receiving chronic monopolar and bipolar STN-DBS. At each contact, beta oscillations and ERNA were recorded intraoperatively, and anatomical locations were assessed. How these factors, alone and in combination, predicted the contacts clinically selected for chronic deep brain stimulation at 6 months postoperatively was evaluated using a simple-ranking method and machine learning algorithms. RESULTS: The probability that each factor individually predicted the clinician-chosen contact was as follows: ERNA 80%, anatomy 67%, beta oscillations 50%. ERNA performed significantly better than anatomy and beta oscillations. Combining neuronal signal and anatomical data did not improve predictive performance. CONCLUSION: This work supports the development of probability-based algorithms using neuronal signals and anatomical data to assist programming of deep brain stimulation.

Towards guided and automated programming of subthalamic area stimulation in Parkinson's disease.

Selecting the ideal contact to apply subthalamic nucleus deep brain stimulation in Parkinson's disease can be an arduous process, with outcomes highly dependent on clinician expertise. This study aims to assess whether neuronal signals recorded intraoperatively in awake patients, and the anatomical location of contacts, can assist programming. In a cohort of 14 patients with Parkinson's disease, implanted with subthalamic nucleus deep brain stimulation, the four contacts on each lead in the 28 hemispheres were ranked according to proximity to a nominated ideal anatomical location and power of the following neuronal signals: evoked resonant neural activity, beta oscillations and high-frequency oscillations. We assessed how these rankings predicted, on each lead: (i) the motor benefit from deep brain stimulation applied through each contact and (ii) the 'ideal' contact to apply deep brain stimulation. The ranking of contacts according to each factor predicted motor benefit from subthalamic nucleus deep brain stimulation, as follows: evoked resonant neural activity; r 2 = 0.50, Akaike information criterion 1039.9, beta; r 2 = 0.50, Akaike information criterion 1041.6, high-frequency oscillations; r 2 = 0.44, Akaike information criterion 1057.2 and anatomy; r 2 = 0.49, Akaike information criterion 1048.0. Combining evoked resonant neural activity, beta and high-frequency oscillations ranking data yielded the strongest predictive model (r 2 = 0.61, Akaike information criterion 1021.5). The 'ideal' contact (yielding maximal benefit) was ranked first according to each factor in the following proportion of hemispheres; evoked resonant neural activity 18/28, beta 17/28, anatomy 16/28, high-frequency oscillations 7/28. Across hemispheres, the maximal available deep brain stimulation benefit did not differ from that yielded by contacts chosen by clinicians for chronic therapy or contacts ranked first according to evoked resonant neural activity. Evoked resonant neural activity, beta oscillations and anatomy similarly predicted how motor benefit from subthalamic nucleus deep brain stimulation varied across contacts on each lead. This could assist programming by providing a probability ranking of contacts akin to a 'monopolar survey'. However, these factors identified the 'ideal' contact in only a proportion of hemispheres. More advanced signal processing and anatomical techniques may be needed for the full automation of contact selection.

Electrically evoked and spontaneous neural activity in the subthalamic nucleus under general anesthesia.

OBJECTIVE: Deep brain stimulation (DBS) surgery is commonly performed with the patient awake to facilitate assessments of electrode positioning. However, awake neurosurgery can be a barrier to patients receiving DBS. Electrode implantation can be performed with the patient under general anesthesia (GA) using intraoperative imaging, although such techniques are not widely available. Electrophysiological features can also aid in the identification of target neural regions and provide functional evidence of electrode placement. Here we assess the presence and positional variation under GA of spontaneous beta and high-frequency oscillation (HFO) activity, and evoked resonant neural activity (ERNA), a novel evoked response localized to the subthalamic nucleus. METHODS: ERNA, beta, and HFO were intraoperatively recorded from DBS leads comprising four individual electrodes immediately after bilateral awake implantation into the subthalamic nucleus of 21 patients with Parkinson's disease (42 hemispheres) and after subsequent GA induction deep enough to perform pulse generator implantation. The main anesthetic agent was either propofol (10 patients) or sevoflurane (11 patients). RESULTS: GA reduced the amplitude of ERNA, beta, and HFO activity (p < 0.001); however, ERNA amplitudes remained large in comparison to spontaneous local field potentials. Notably, a moderately strong correlation between awake ERNA amplitude and electrode distance to an "ideal" therapeutic target within dorsal STN was preserved under GA (awake: ρ = -0.73, adjusted p value [padj] < 0.001; GA: ρ = -0.69, padj < 0.001). In contrast, correlations were diminished under GA for beta (awake: ρ = -0.45, padj < 0.001; GA: ρ = -0.13, padj = 0.12) and HFO (awake: ρ = -0.69, padj < 0.001; GA: ρ = -0.33, padj < 0.001). The largest ERNA occurred at the same electrode (awake vs GA) for 35/42 hemispheres (83.3%) and corresponded closely to the electrode selected by the clinician for chronic therapy at 12 months (awake ERNA 77.5%, GA ERNA 82.5%). The largest beta amplitude occurred at the same electrode (awake vs GA) for only 17/42 (40.5%) hemispheres and 21/42 (50%) for HFO. The electrode measuring the largest awake beta and HFO amplitudes corresponded to the electrode selected by the clinician for chronic therapy at 12 months in 60% and 70% of hemispheres, respectively. However, this correspondence diminished substantially under GA (beta 20%, HFO 35%). CONCLUSIONS: ERNA is a robust electrophysiological signal localized to the dorsal subthalamic nucleus subregion that is largely preserved under GA, indicating it could feasibly guide electrode implantation, either alone or in complementary use with existing methods.

Effect of Visual Information on Postural Control in Children with Autism Spectrum Disorder.

Visual information is crucial for postural control. Visual processing in children with autism spectrum disorder (ASD) was hypothesized to be less efficient and thus they would display a less stable standing posture than typically developing children. The present study compared the static standing responses and attentional demands of 15 children with ASD and 18 control participants in conditions of eyes open and eyes closed. The results showed that postural responses and attention invested in standing were similar between the participant groups in the two visual conditions. Both groups displayed a more stable posture when their eyes were open in comparison to eyes closed. The finding suggests that normal postural control development could occur in children with ASD.

Postural control adaptation to optic flow in children and adults with autism spectrum disorder.

BACKGROUND: Sensory reweighting is important for humans to flexibly up-weigh and down-weigh sensory information in dynamic environments. There is an element of time involved in the sensory reweighting process. A longer time spent on sensory reweighting may increase the destabilizing effect of postural control. Individuals with autism spectrum disorder (ASD) are reported to have poor postural control. It is uncertain if a different sensory reweighting process underlies the postural control deficit in children and adults with ASD. RESEARCH QUESTION: To explore the sensory reweighting capability in ASD, the present study examined whether the temporal domains of postural control differed in children and adults, with and without ASD under various optic flow conditions. METHODS: Thirty-three children (8-12 years old) and 33 adults (18-50 years old) with and without ASD underwent quiet standing in six radial optic flow conditions. Each condition lasted for 60 s and was shown twice to all participants. For each optic flow condition, changes in postural response within-trial and between-trials were measured. RESULTS: Under various optic flow illusions, both children with and without ASD took a longer time to restore their posture compared with adults with and without ASD. Nonetheless, all groups demonstrated comparable abilities to adjust their posture to one that is close to the baseline position after one exposure to the optic flow stimulation. SIGNIFICANCE: The present study showed that the temporal domains of postural control under different optic flow conditions were similar between individuals with and without ASD from the same age group. The ability to down-weigh visual information efficiently comes with the developmental progression of the sensory reweighting system. These findings suggest that the sensory reweighting process does not elucidate the postural control deficits in individuals with ASD and thus alternative explanations to determine the underlying mechanism for postural instability are needed.

A palm-worn device to quantify rigidity in Parkinson's disease.

BACKGROUND: Parkinsonian rigidity is identified on clinical examination as resistance to passive movement. Measurement of rigidity commonly relies on ordinal rating scales (MDS-UPDRS), however instrumented objective measures may provide greater mechanistic insight. NEW METHOD: We present a palm-worn instrument to objectively quantify rigidity on a continuous scale. The device employs a miniature motor to flex the third digit of the hand about the metacarpophalangeal joint whilst transducers record flexion/extension forces. We aim to determine congruence with the MDS-UPDRS, investigate sensitivity to the impact of deep brain stimulation (DBS) and contralateral movement, and make comparisons with healthy individuals. Eight participants with Parkinson's disease underwent evaluation during conditions: on and off DBS, and with and without contralateral limb movement to activate rigidity. During each DBS condition, wash-in/out effects were tracked using both our instrument and two blinded clinical raters. Sixteen healthy volunteers (age-matched/young) served as controls. RESULTS: Rigidity measured using our instrument had moderate agreement with the MDS-UPDRS and showed differences between therapeutic state, activation conditions, and disease/healthy cohorts. Rigidity gradually worsened over a one-hour period after DBS cessation, but improved more rapidly with DBS resumption. COMPARISON WITH EXISTING METHODS: Previous attempts to quantify rigidity include manual approaches where a clinician is required to manipulate limbs while sensors passively gather information, or large automated instruments to move the wrist or elbow. CONCLUSION: Given its ability to track changes in rigidity due to therapeutic intervention, our technique could have applications where continuous measurement is required or where a suitably qualified rater is absent.

Objective evaluation of bradykinesia in Parkinson's disease using an inexpensive marker-less motion tracking system.

OBJECTIVE: Quantification of bradykinesia (slowness of movement) is crucial for the treatment and monitoring of Parkinson's disease. Subjective observational techniques are the de-facto 'gold standard', but such clinical rating scales suffer from poor sensitivity and inter-rater variability. Although various technologies have been developed for assessing bradykinesia in recent years, most still require considerable expertise and effort to operate. Here we present a novel method to utilize an inexpensive off-the-shelf hand-tracker (Leap Motion) to quantify bradykinesia. APPROACH: Eight participants with Parkinson's disease receiving benefit from deep brain stimulation were recruited for the study. Participants were assessed 'on' and 'off' stimulation, with the 'on' condition repeated to evaluate reliability. Participants performed wrist pronation/supination, hand open/close, and finger-tapping tasks during each condition. Tasks were simultaneously captured by our software and rated by three clinicians. A linear regression model was developed to predict clinical scores and its performance was assessed with leave-one-subject-out cross validation. MAIN RESULTS: Aggregate bradykinesia scores predicted by our method were in strong agreement (R = 0.86) with clinical scores. The model was able to differentiate therapeutic states and comparison between the test-retest conditions yielded no significant difference (p  = 0.50). SIGNIFICANCE: These findings demonstrate that our method can objectively quantify bradykinesia in agreement with clinical observation and provide reliable measurements over time. The hardware is readily accessible, requiring only a modest computer and our software to perform assessments, thus making it suitable for both clinic- and home-based symptom tracking.

Effect of Visual Information on Postural Control in Adults with Autism Spectrum Disorder.

Sensory processing difficulties affect the development of sensorimotor skills in individuals with autism spectrum disorder (ASD). However, the effect of sensory information on postural control is unclear in the ASD adult population. The present study examined the effect of visual information on postural control as well as the attentional demands associated with postural control in fourteen adults with ASD and seventeen typically developed adults. The results showed that postural sway and attention demands of postural control were larger in adults with ASD than in typically developed adults. These findings indicate that visual processing used for postural control may be different in adults with ASD. Further research in visual field processing and visual motion processing may elucidate these sensorimotor differences.

Validation of a precision tremor measurement system for multiple sclerosis.

BACKGROUND: Tremor is a debilitating symptom of Multiple Sclerosis (MS). Little is known about its pathophysiology and treatments are limited. Clinical trials investigating new interventions often rely on subjective clinical rating scales to provide supporting evidence of efficacy. NEW METHOD: We present a novel instrument (TREMBAL) which uses electromagnetic motion capture technology to quantify MS tremor. We aim to validate TREMBAL by comparison to clinical ratings using regression modelling with 310 samples of tremor captured from 13 MS participants who performed five different hand exercises during several follow-up visits. Minimum detectable change (MDC) and test-retest reliability were calculated and comparisons were made between MS tremor and data from 12 healthy volunteers. RESULTS: Velocity of the index finger was most congruent with clinical observation. Regression modelling combining different features, sensor configurations, and labelling exercises did not improve results. TREMBAL MDC was 84% of its initial measurement compared to 91% for the clinical rating. Intra-class correlations for test-retest reliability were 0.781 for TREMBAL and 0.703 for clinical ratings. Tremor was lower (p = 0.002) in healthy subjects. COMPARISON WITH EXISTING METHODS: Subjective scales have low sensitivity, suffer from ceiling effects, and mitigation against inter-rater variability is challenging. Inertial sensors are ubiquitous, however, their output is nonlinearly related to tremor frequency, compensation is required for gravitational artefacts, and their raw data cannot be intuitively comprehended. CONCLUSIONS: TREMBAL, compared with clinical ratings, gave measures in agreement with clinical observation, had marginally lower MDC, and similar test-retest reliability.

Effect of Optic Flow on Postural Control in Children and Adults with Autism Spectrum Disorder.

Individuals with autism spectrum disorder (ASD) have been associated with sensorimotor difficulties, commonly presented by poor postural control. Postural control is necessary for all motor behaviors. However, findings concerning the effect of visual motion on postural control and the age progression of postural control in individuals with ASD are inconsistent. The aims of the present study were to examine postural responses to optic flow in children and adults with and without ASD, postural responses to optic flow in the central and peripheral visual fields, and the changes in postural responses between the child and adult groups. Thirty-three children (8-12 years old) and 33 adults (18-50 years old) with and without ASD were assessed on quiet standing for 60 seconds under conditions of varying optic flow illusions, consisting of different combinations of optic flow directions and visual field display. The results showed that postural responses to most optic flow conditions were comparable between children with and without ASD and between adults with and without ASD. However, adults with ASD appeared more responsive to forward-moving optic flow in the peripheral visual field compared with typically developed adults. The findings suggest that children and adults with ASD may not display maladaptive postural responses all the time. In addition, adults in the ASD group may have difficulties prioritizing visual information in the central visual field over visual information in the peripheral visual field when in unfamiliar environments, which may have implications in understanding their motor behaviors in new surroundings.

Postural and cortical responses following visual occlusion in standing and sitting tasks.

Perturbation-evoked responses (PERs) to a physical perturbation of postural stability have been detected using electroencephalography (EEG). Components of these responses are hypothesized to demonstrate the detection (P1) and evaluation (N1) of postural instability. Despite the important contribution of the visual system to postural control, PERs to a visual perturbation of posture have yet to be reported. Ten healthy young adults were exposed to unpredictable visual occlusion mediated through liquid crystal glasses under two conditions of postural demand: quiet standing and quiet sitting. The participants' PERs and postural responses were recorded and differences between conditions assessed using Wilcoxon signed-rank tests. In response to unpredictable visual occlusion, both P1 and N1 components of the PER were observed in both postural conditions. The amplitude of the P1 response remained consistent between postural conditions ([Formula: see text], [Formula: see text]), whereas N1 amplitude and postural responses were significantly smaller in the sitting condition ([Formula: see text], [Formula: see text]). This is the first study to demonstrate cortical responses to visual perturbation of posture. The responses to postural perturbation by sudden visual occlusion are similar in nature to that seen in relation to a physical perturbation. In addition, the amplitude of the N1 response is not only consistent with the relative magnitude of the perturbation, but also the underlying postural set, with a larger N1 seen in standing relative to sitting. The study informs the relative importance of vision to postural stability, postural set and provides a protocol to objectively assess sensory-based postural disorders.

Single-trial event-related potential extraction through one-unit ICA-with-reference.

OBJECTIVE: In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. APPROACH: In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. MAIN RESULTS: Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. SIGNIFICANCE: In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application.

An improved P300 extraction using ICA-R for P300-BCI speller.

In this study, a new P300 extraction method is investigated by using a form of constrained independent component analysis (cICA) algorithm called one-unit ICA-with-reference (ICA-R) which extracts the P300 signal based on its temporal information. The main advantage of this method compared to the existing ICA-based method is that the desired P300 signal is extracted directly without requiring partial or full signal decomposition and any post-processing on the outcome of the ICA before the P300 signal can be obtained. Since only one IC is extracted, the method is computationally more efficient for real-time P300 BCI applications. In our study, when tested on the BCI competition 2003 dataset IIb, the current state-of-the-art performance is maintained by using the one-unit ICA-R. Besides that, the ability of the method to visualize P300 signals at the single-trial level also suggests it has potential applications in other types of ERP studies.