Measuring complex behaviors of local oscillatory networks in deep brain local field potentials

Balance between pallidal neural oscillations correlated with dystonic activity and severity

BACKGROUND AND OBJECTIVE

The balance between neural oscillations provides valuable insights into the organisation of neural oscillations related to brain states, which may play important roles in dystonia. We aim to investigate the relationship of the balance in the globus pallidus internus (GPi) with the dystonic severity under different muscular contraction conditions.

METHODS

Twenty-one patients with dystonia were recruited. All of them underwent bilateral GPi implantation, and local field potentials (LFPs) from the GPi were recorded via simultaneous surface electromyography. The power spectral ratio between neural oscillations was computed as the measure of neural balance. This ratio was calculated under high and low dystonic muscular contraction conditions, and its correlation with the dystonic severity was assessed using clinical scores.

RESULTS

The power spectral of the pallidal LFPs peaked in the theta and alpha bands. Within participant comparison showed that the power spectral of the theta oscillations significantly increased during high muscle contraction compared with that during low contraction. The power spectral ratios between the theta and alpha, theta and low beta, and theta and high gamma oscillations were significantly higher during high contraction than during low contraction. The total score and motor score were associated with the power spectral ratio between the low and high beta oscillations, which was correlated with the dystonic severity both during high and low contractions. The power spectral ratios between the low beta and low gamma and between the low beta and high gamma oscillations showed a significantly positive correlation with the total score during both high and low contractions; a correlation with the motor scale score was found only during high contraction. Meanwhile, the power spectral ratio between the theta and alpha oscillations during low contraction showed a significantly negative correlation with the total score. The power spectral ratios between the alpha and high beta, alpha and low gamma, and alpha and high gamma oscillations were significantly correlated with the dystonic severity only during low contraction.

CONCLUSION

The balance between neural oscillations, as quantified by the power ratio between specific frequency bands, differed between the high and low muscular contraction conditions and was correlated with the dystonic severity. The balance between the low and high beta oscillations was correlated with the dystonic severity during both conditions, making this parameter a new possible biomarker for closed-loop deep brain stimulation in patients with dystonia.

Functional dynamics of thalamic local field potentials correlate with modulation of neuropathic pain

Understanding the functional dynamics of neural oscillations in the sensory thalamus is essential for elucidating the perception and modulation of neuropathic pain. Local field potentials were recorded from the sensory thalamus of twelve neuropathic pain patients. Single and combinational neural states were defined by the activity state of a single or paired oscillations. Relationships between the duration or occurrence rate of neural state and pre-operative pain level or pain relief induced by deep brain stimulation were evaluated. Results showed that the occurrence rate of the single neural state of low-beta oscillation was significantly correlated with pain relief. The duration and occurrence rate of combinational neural states of the paired low-beta with delta, theta, alpha, high-beta or low-gamma oscillations were more significantly correlated with pain relief than the single neural states. Moreover, these significant combinational neural states formed a local oscillatory network with low-beta oscillation as a key node. The results also showed correlations between measures of combinational neural states and subjective pain level as well. The duration of combinational neural states of paired alpha with delta or theta oscillations and the occurrence rate of neural states of the paired delta with low-beta or low-gamma oscillations were significantly correlated with pre-operative pain level. In conclusion, this study revealed that the integration of oscillations and the functional dynamics of neural states were differentially involved in modulation and perception of neuropathic pain. The functional dynamics could be biomarkers for developing neural state-dependent deep brain stimulation for neuropathic pain.

Characteristics of Globus Pallidus Internus Local Field Potentials in Hyperkinetic Disease

Background: Dystonia and Huntington's disease (HD) are both hyperkinetic movement disorders but exhibit distinct clinical characteristics. Aberrant output from the globus pallidus internus (GPi) is involved in the pathophysiology of both HD and dystonia, and deep brain stimulation (DBS) of the GPi shows good clinical efficacy in both disorders. The electrode externalized period provides an opportunity to record local field potentials (LFPs) from the GPi to examine if activity patterns differ between hyperkinetic disorders and are associated with specific clinical characteristics.

Methods: LFPs were recorded from 7 chorea-dominant HD and nine cervical dystonia patients. Differences in oscillatory activities were compared by power spectrum and Lempel-Ziv complexity (LZC). The discrepancy band power ratio was used to control for the influence of absolute power differences between groups. We further identified discrepant frequency bands and frequency band ratios for each subject and examined the correlations with clinical scores.

Results: Dystonia patients exhibited greater low frequency power (6–14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26–43 Hz) (p < 0.0298, corrected). United Huntington Disease Rating Scale chorea sub-score was positively correlated with 26–43 Hz frequency band power and negatively correlated with the 6–14 Hz/26–43 Hz band power ratio.

Conclusion: Dystonia and HD are characterized by distinct oscillatory activity patterns, which may relate to distinct clinical characteristics. Specifically, chorea may be related to elevated high-beta and low-gamma band power, while dystonia may be related to elevated low frequency band power. These LFPs may be useful biomarkers for adaptive DBS to treat hyperkinetic diseases.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation

OBJECTIVE

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations.

APPROACH

Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model.

MAIN RESULTS

This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief.

SIGNIFICANCE

The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations.

Human centromedian-parafascicular complex signals sensory cues for goal-oriented behavior selection

Experimental research has shown that the centromedian-parafascicular complex (CM-Pf) of the intralaminar thalamus is activated in attentional orienting and processing of behaviorally relevant stimuli. These observations resulted in the hypothesis that the CM-Pf plays a pivotal role in goal-oriented behavior selection. We here set out to test this hypothesis with electrophysiological recordings from patients with electrodes implanted in CM-Pf for deep brain stimulation (DBS) treatment of chronic neuropathic pain. Six patients participated in (1) an auditory three-class oddball experiment, which required a button press to target tones, but not to standard and deviant tones and in (2) a multi-speaker experiment with a target word that required attention selection and a target image that required response selection. Subjects showed transient neural responses (8-15Hz) to the target tone and the target word. Two subjects additionally showed transient neural responses (15-25Hz) to the target image. All sensory target stimuli were related to an internal goal and required a behavior selection (attention selection, response selection). In group analyses, neural responses were greater to target tones than deviant and standard tones and to target words than other task-relevant words that did not require attention selection. The transient neural responses occurred after the target stimuli but prior to the overt behavioral response. Our results demonstrate that in human subjects the CM-Pf is involved in signaling sensory inputs related to goal-oriented selection of behavior.