Publications by authors named "Shouyan Wang"

87 Publications

Real-time removal of stimulation artifacts in closed-loop deep brain stimulation.

J Neural Eng 2021 Nov 24. Epub 2021 Nov 24.

Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433, CHINA.

Objective: Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters.

Approach: We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals and in vivo closed-loop DBS applications in Parkinsonian animal models.

Main Results: The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2-150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS application in vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations.

Significance: The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.
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http://dx.doi.org/10.1088/1741-2552/ac3cc5DOI Listing
November 2021

Neurophysiological characteristics in the periventricular/periaqueductal gray correlate with pain perception, sensation, and affect in neuropathic pain patients.

Neuroimage Clin 2021 Nov 10;32:102876. Epub 2021 Nov 10.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China. Electronic address:

The periventricular/periaqueductal gray (PAG/PVG) is critical for pain perception and is associated with the emotional feelings caused by pain. However, the electrophysiological characteristics of the PAG/PVG have been little investigated in humans with chronic pain. The present study analyzed the oscillatory characteristics of local field potentials (LFPs) in the PAG/PVG of eighteen neuropathic pain patients. Power spectrum analysis and neural state analysis were applied to the PAG/PVG LFPs. Neural state analysis is based on a dynamic neural state identification approach and discriminates the LFPs into different neural states, including a single neural state based on one oscillation and a combinational neural state based on two paired oscillations. The durations and occurrence rates were used to quantify the dynamic features of the neural state. The results show that the combined neural state forms three local networks based on neural oscillations that are responsible for the perceptive, sensory, and affective components of pain. The first network is formed by the interaction of the delta oscillation with other oscillations and is responsible for the coding of pain perception. The second network is responsible for the coding of sensory pain information, uses high gamma as the main node, and is widely connected with other neural oscillations. The third network is responsible for the coding of affective pain information, and beta oscillations play an important role in it. This study suggested that the combination of two neural oscillations in the PAG/PVG is essential for encoding perceptive, sensory, and affective measures of pain.
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http://dx.doi.org/10.1016/j.nicl.2021.102876DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604717PMC
November 2021

Subthalamic dynamic neural states correlate with motor symptoms in Parkinson's Disease.

Clin Neurophysiol 2021 11 25;132(11):2789-2797. Epub 2021 Aug 25.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Ministry of Education, Fudan University, Shanghai, China; Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, China; Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China. Electronic address:

Objective: This study aims to discriminate the dynamic synchronization states from the subthalamic local field potentials and investigate their correlations with the motor symptoms in Parkinson's Disease (PD).

Methods: The resting-state local field potentials of 10 patients with PD were recorded from the subthalamic nucleus. The dynamic neural states of multiple oscillations were discriminated and analyzed. The Spearman correlation was used to investigate the correlations between occurrence rate or duration of dynamic neural states and the severity of motor symptoms.

Results: The proportion of long low-beta and theta synchronized state was significantly correlated with the general motor symptom and tremor, respectively. The duration of combined low/high-beta state was significantly correlated with rigidity, and the duration of combined alpha/high-beta state was significantly correlated with bradykinesia.

Conclusions: This study provides evidence that motor symptoms are associated with the neural states coded with multiple oscillations in PD.

Significance: This study may advance the understanding of the neurophysiological mechanisms of the motor symptoms and provide potential biomarkers for closed-loop deep brain stimulation in PD.
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http://dx.doi.org/10.1016/j.clinph.2021.07.022DOI Listing
November 2021

Cerebral Hemodynamic Correlates of Transcutaneous Auricular Vagal Nerve Stimulation in Consciousness Restoration: An Open-Label Pilot Study.

Front Neurol 2021 15;12:684791. Epub 2021 Jul 15.

Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China.

This study aimed to preliminarily illustrate the cerebral hemodynamic correlates of transcutaneous auricular vagal nerve stimulation (taVNS) in consciousness restoration. Arterial spin labeling (ASL) was adopted with functional magnetic resonance imaging (fMRI) to measure cerebral blood flow (CBF) changes before and after taVNS in 10 qualified patients with disorders of consciousness (DOC). Before taVNS, five patients responded to auditory stimuli (RtAS), and five did not respond to auditory stimuli (nRtAS). The RtAS DOC patients obtained favorable prognoses after the 4-week taVNS treatment, whereas the nRtAS ones did not. Simultaneously, taVNS increased CBF of multiple brain regions in the RtAS DOC patients, but hardly in the nRtAS ones. In conclusion, the preserved auditory function might be the prior key factor of the taVNS responders in DOC patients, and taVNS might alleviate RtAS DOC by activating the salience network, the limbic system, and the interoceptive system.
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http://dx.doi.org/10.3389/fneur.2021.684791DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319239PMC
July 2021

Mindfulness practice for protecting mental health during the COVID-19 pandemic.

Transl Psychiatry 2021 05 28;11(1):329. Epub 2021 May 28.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Emerging evidence shows that the coronavirus disease 2019 (COVID-19) pandemic is negatively affecting mental health around the globe. Interventions to alleviate the psychological impact of the pandemic are urgently needed. Whether mindfulness practice may protect against the harmful emotional effects of a pandemic crisis remains hitherto unknown. We investigated the influence of mindfulness training on mental health during the COVID-19 outbreak in China. We hypothesized that mindfulness practitioners might manifest less pandemic-related distress, depression, anxiety, and stress than non-practitioners and that more frequent practice would be associated with an improvement in mental health during the pandemic. Therefore, we assessed pandemic-related distress and symptoms of depression, anxiety, and stress, as well as the frequency of meditation practice at the peak of new infections (Feb 4-5; N = 673) and three weeks later (Feb 29-30; N = 521) in mindfulness practitioners via online questionnaires. Self-reported symptoms were also collected from non-practitioners at peak time only (N = 1550). We found lower scores of pandemic-related distress in mindfulness practitioners compared to non-practitioners. In general, older participants showed fewer symptoms of depression and anxiety. In younger practitioners, pandemic-related distress decreased from peak to follow-up. Importantly, increased mindfulness training during the preceding two weeks was associated with lower scores of depression and anxiety at both assessments. Likewise, practice frequency predicted individual improvement in scores of depression, anxiety, and stress at follow-up. Our results indicate that mindfulness meditation might be a viable low-cost intervention to mitigate the psychological impact of the COVID-19 crisis and future pandemics.
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http://dx.doi.org/10.1038/s41398-021-01459-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8160402PMC
May 2021

Deep Brain Stimulation Initiative: Toward Innovative Technology, New Disease Indications, and Approaches to Current and Future Clinical Challenges in Neuromodulation Therapy.

Front Neurol 2020 28;11:597451. Epub 2021 Jan 28.

National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China.

Deep brain stimulation (DBS) is one of the most important clinical therapies for neurological disorders. DBS also has great potential to become a great tool for clinical neuroscience research. Recently, the National Engineering Laboratory for Neuromodulation at Tsinghua University held an international Deep Brain Stimulation Initiative workshop to discuss the cutting-edge technological achievements and clinical applications of DBS. We specifically addressed new clinical approaches and challenges in DBS for movement disorders (Parkinson's disease and dystonia), clinical application toward neurorehabilitation for stroke, and the progress and challenges toward DBS for neuropsychiatric disorders. This review highlighted key developments in (1) neuroimaging, with advancements in 3-Tesla magnetic resonance imaging DBS compatibility for exploration of brain network mechanisms; (2) novel DBS recording capabilities for uncovering disease pathophysiology; and (3) overcoming global healthcare burdens with online-based DBS programming technology for connecting patient communities. The successful event marks a milestone for global collaborative opportunities in clinical development of neuromodulation to treat major neurological disorders.
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http://dx.doi.org/10.3389/fneur.2020.597451DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876228PMC
January 2021

FoxO3 transcription factor promotes autophagy after oxidative stress injury in HT22 cells.

Can J Physiol Pharmacol 2021 Jun 25;99(6):627-634. Epub 2020 Nov 25.

Department of Histology and Embryology, Medical College, Nantong University, 19th Qixiu Road, 226001 Nantong, People's Republic of China.

Autophagy has been implicated in neurodegenerative diseases. Forkhead box O3 (FoxO3) transcription factors promote autophagy in heart and inhibit oxidative damage. Here we investigate the role of FoxO3 transcription factors in regulating autophagy after oxidative stress injury in immortalized mouse hippocampal cell line (HT22). The present study confirms that hydrogen peroxide (HO) injury could induce autophagy and FoxO3 activation in HT22 cells. In addition, overexpression of FoxO3 enhanced HO-induced autophagy activation and suppressed neuronal cell damage, while knockdown of FoxO3 reduced HO-induced autophagy activation and exacerbated neuronal cell injury. Inhibition of autophagy by 3-methyladenine (3-MA) resulted in reduced cell viability, increased production of reactive oxygen species (ROS), promoted nuclear condensation, and decreased expression of antiapoptotic and autophagy-related proteins, indicating that autophagy may have protective effects on HO-induced injury in HT22 cells. Moreover, overexpression of FoxO3 prevented exacerbation of brain damage induced by 3-MA. Taken together, these results show that activation of FoxO3 could induce autophagy and inhibit HO-induced damage in HT22 cells. Our study demonstrates the critical role of FoxO3 in regulating autophagy in brain.
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http://dx.doi.org/10.1139/cjpp-2020-0448DOI Listing
June 2021

A Multi-Sensor Wearable System for the Quantitative Assessment of Parkinson's Disease.

Sensors (Basel) 2020 Oct 29;20(21). Epub 2020 Oct 29.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.

The quantitative characterization of movement disorders and their related neurophysiological signals is important for the management of Parkinson's disease (PD). The aim of this study is to develop a novel wearable system enabling the simultaneous measurement of both motion and other neurophysiological signals in PD patients. We designed a wearable system that consists of five motion sensors and three electrophysiology sensors to measure the motion signals of the body, electroencephalogram, electrocardiogram, and electromyography, respectively. The data captured by the sensors are transferred wirelessly in real time, and the outcomes are analyzed and uploaded to the cloud-based server automatically. We completed pilot studies to (1) test its validity by comparing outcomes to the commercialized systems, and (2) evaluate the deep brain stimulation (DBS) treatment effects in seven PD patients. Our results showed: (1) the motion and neurophysiological signals measured by this wearable system were strongly correlated with those measured by the commercialized systems ( > 0.94, < 0.001); and (2) by completing the clinical supination and pronation frequency test, the frequency of motion as measured by this system increased when DBS was turned on. The results demonstrated that this multi-sensor wearable system can be utilized to quantitatively characterize and monitor motion and neurophysiological PD.
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http://dx.doi.org/10.3390/s20216146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662222PMC
October 2020

Telemonitoring Parkinson's disease using machine learning by combining tremor and voice analysis.

Brain Inform 2020 Oct 22;7(1):12. Epub 2020 Oct 22.

Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh.

Background: With the growing number of the aged population, the number of Parkinson's disease (PD) affected people is also mounting. Unfortunately, due to insufficient resources and awareness in underdeveloped countries, proper and timely PD detection is highly challenged. Besides, all PD patients' symptoms are neither the same nor they all become pronounced at the same stage of the illness. Therefore, this work aims to combine more than one symptom (rest tremor and voice degradation) by collecting data remotely using smartphones and detect PD with the help of a cloud-based machine learning system for telemonitoring the PD patients in the developing countries.

Method: This proposed system receives rest tremor and vowel phonation data acquired by smartphones with built-in accelerometer and voice recorder sensors. The data are primarily collected from diagnosed PD patients and healthy people for building and optimizing machine learning models that exhibit higher performance. After that, data from newly suspected PD patients are collected, and the trained algorithms are evaluated to detect PD. Based on the majority-vote from those algorithms, PD-detected patients are connected with a nearby neurologist for consultation. Upon receiving patients' feedback after being diagnosed by the neurologist, the system may update the model by retraining using the latest data. Also, the system requests the detected patients periodically to upload new data to track their disease progress.

Result: The highest accuracy in PD detection using offline data was [Formula: see text] from voice data and [Formula: see text] from tremor data when used separately. In both cases, k-nearest neighbors (kNN) gave the highest accuracy over support vector machine (SVM) and naive Bayes (NB). The application of maximum relevance minimum redundancy (MRMR) feature selection method showed that by selecting different feature sets based on the patient's gender, we could improve the detection accuracy. This study's novelty is the application of ensemble averaging on the combined decisions generated from the analysis of voice and tremor data. The average accuracy of PD detection becomes [Formula: see text] when ensemble averaging was performed on majority-vote from kNN, SVM, and NB.

Conclusion: The proposed system can detect PD using a cloud-based system for computation, data preserving, and regular monitoring of voice and tremor samples captured by smartphones. Thus, this system can be a solution for healthcare authorities to ensure the older population's accessibility to a better medical diagnosis system in the developing countries, especially in the pandemic situation like COVID-19, when in-person monitoring is minimal.
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http://dx.doi.org/10.1186/s40708-020-00113-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579898PMC
October 2020

Association of specific biotypes in patients with Parkinson disease and disease progression.

Neurology 2020 09 14;95(11):e1445-e1460. Epub 2020 Aug 14.

From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.C., E.R., F.D, W.G., J. D., W.Z., S.W., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (L.W., W.C., J. D., W.Z., S.W., J.F.) (Fudan University), Ministry of Education, Shanghai, China; Department of Computer Science (E.R., J.F.), University of Warwick, Coventry; Oxford Centre for Computational Neuroscience (E.R.), UK; Department of Neurology and National Clinical Research Center for Aging and Medicine (F.L., J.W.), Huashan Hospital, Fudan University, Shanghai, China; and Medical Research Council Brain Network Dynamics Unit (P.B.) and Nuffield Department of Clinical Neurosciences (P.B.), University of Oxford, UK.

Objective: To identify biotypes in patients with newly diagnosed Parkinson disease (PD) and to test whether these biotypes could explain interindividual differences in longitudinal progression.

Methods: In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (n = 314, age 61.0 ± 9.5, years 34.1% female, 5 years of follow-up). Voxel-level neuroanatomic features were estimated with deformation-based morphometry (DBM) of T1-weighted MRI. Voxels with deformation values that were significantly correlated ( < 0.01) with clinical scores (Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Parts I-III and total score, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomic features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomic pattern were compared between different biotypes.

Results: Two neuroanatomic biotypes were identified: biotype 1 (n = 114) with subcortical brain volumes smaller than heathy controls and biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease durations at the initial visit and follow-up were similar between biotypes, patients with PD with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of 5 years.

Conclusion: Robust neuroanatomic biotypes exist in PD with distinct clinical and neuroanatomic patterns. These biotypes can be detected at diagnosis and predict the course of longitudinal progression, which should benefit trial design and evaluation.
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http://dx.doi.org/10.1212/WNL.0000000000010498DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116258PMC
September 2020

Covid-19 and promising solutions to combat symptoms of stress, anxiety and depression.

Neuropsychopharmacology 2021 01;46(1):217-218

Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, PR China.

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http://dx.doi.org/10.1038/s41386-020-00791-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425273PMC
January 2021

Pain-Induced Beta Activity in the Subthalamic Nucleus of Parkinson's Disease.

Stereotact Funct Neurosurg 2020;98(3):193-199. Epub 2020 Apr 29.

National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.

Background: The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) in Parkinson's disease (PD) and is believed to serve a role in sensorimotor integration. In addition to therapeutic neuromodulation, DBS facilitates the recording of local-field potentials (LFPs) in order to further understand the neurophysiological basis of disease. The capacity to wirelessly transmit these signals in real time has overcome the obstacle of externalization of electrodes during LFP recordings.

Objective: Using the G102RS device (PINS Medical, China), we investigated the LFP changes in response to mechanical pain stimulation to further elucidate the representation of pain sensation in the basal ganglia.

Methods: LFPs from 2 patients who had undergone bilateral STN-DBS were wirelessly recorded during no stimulation, low-frequency stimulation (60 and 90 Hz), and high-frequency stimulation (130 and 150 Hz) while introducing painful and nonpainful stimuli. Power spectral analysis was conducted to compare the changes in β frequency (13-30 Hz) during each stimulus.

Results: During painful stimuli, STN power spectra (n = 4) revealed a significant increase in β activity compared to non-painful and no-stimulus epochs. Both low- and high-frequency stimulation produced a significant decrease in pain-related β activity.

Conclusion: These 2 cases have demonstrated the potential for acute noxious stimuli to exacerbate pathologic β oscillatory activity in the STN. Our findings represent novel evidence of the neurophysiologic representation of pain in the STN of PD patients.
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http://dx.doi.org/10.1159/000507032DOI Listing
May 2021

Dynamic changes in rhythmic and arrhythmic neural signatures in the subthalamic nucleus induced by anaesthesia and tracheal intubation.

Br J Anaesth 2020 07 24;125(1):67-76. Epub 2020 Apr 24.

Center of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address:

Background: Subcortical structures, including the basal ganglia, have been proposed to be crucial for arousal, consciousness, and behavioural responsiveness. How the basal ganglia contribute to the loss and recovery of consciousness during anaesthesia has, however, not yet been well characterised.

Methods: Twelve patients with advanced Parkinson's disease, who were undergoing deep brain stimulation (DBS) electrode implantation in the subthalamic nucleus (STN), were included in this study. Local field potentials (LFPs) were recorded from the DBS electrodes and EEG was recorded from the scalp during induction of general anaesthesia (with propofol and sufentanil) and during tracheal intubation. Neural signatures of loss of consciousness and of the expected arousal during intubation were sought in the STN and EEG recordings.

Results: Propofol-sufentanil anaesthesia resulted in power increases in delta, theta, and alpha frequencies, and broadband power decreases in higher frequencies in both STN and frontal cortical areas. This was accompanied by increased STN-frontal cortical coherence only in the alpha frequency band (119 [68]%; P=0.0049). We observed temporal activity changes in STN after tracheal intubation, including power increases in high-beta (22-40 Hz) frequency (98 [123]%; P=0.0064) and changes in the power-law exponent in the power spectra at lower frequencies (2-80 Hz), which were not observed in the frontal cortex. During anaesthesia, the dynamic changes in the high-gamma power in STN LFPs correlated with the power-law exponent in the power spectra at lower frequencies (2-80 Hz).

Conclusions: Apart from similar activity changes in both STN and cortex associated with anaesthesia-induced unresponsiveness, we observed specific neuronal activity changes in the STN in response to the anaesthesia and tracheal intubation. We also show that the power-law exponent in the power spectra in the STN was modulated by tracheal intubation in anaesthesia. Our results support the hypothesis that subcortical nuclei may play an important role in the loss and return of responsiveness.
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http://dx.doi.org/10.1016/j.bja.2020.03.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347416PMC
July 2020

Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson's Disease by Wearable Sensors: Controlled Study.

JMIR Mhealth Uhealth 2020 03 20;8(3):e16650. Epub 2020 Mar 20.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Background: Gait impairments including shuffling gait and hesitation are common in people with Parkinson's disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD.

Objective: This study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS).

Methods: A total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated.

Results: The results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F=69.75, P<.001, partial eta-square=0.59), initial step angle (F=15.56, P<.001, partial eta-square=0.25), and last step angle (F=61.99, P<.001, partial eta-square=0.56). Within the PD cohort, both the ALCT and DBS induced greater mean step angles (ACLT: F=5.77, P=.02, partial eta-square=0.13; DBS: F=8.53, P=.005, partial eta-square=0.14) and last step angles (ACLT: F=10, P=.003, partial eta-square=0.21; DBS: F=4.96, P=.003, partial eta-square=0.09), but no significant changes were observed in step time and number after the treatments. Additionally, these step angles were correlated with the Unified Parkinson's Disease Rating Scale, Part III score: mean step angle (single task: r=-0.60, P<.001; dual task: r=-0.52, P<.001), initial step angle (single task: r=-0.35, P=.006; dual task: r=-0.35, P=.01), and last step angle (single task: r=-0.43, P=.001; dual task: r=-0.41, P=.002).

Conclusions: This pilot study demonstrated that the gait angular characteristics, as quantified by the step angles, were sensitive to the disease severity of PD and, more importantly, can capture the effects of treatments on the gait, while the traditional metrics cannot. This indicates that these metrics may serve as novel markers to help the assessment of gait in those with PD as well as the rehabilitation of this vulnerable cohort.
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http://dx.doi.org/10.2196/16650DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125438PMC
March 2020

Deep brain stimulation in the globus pallidus modulates pallidal and subthalamic neural oscillations.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:5204-5207

Deep brain stimulation (DBS) in the basal ganglia has been introduced to treat movement disorders. The effects of pallidal DBS on the neural oscillations in the globus pallidus interna (GPi) and the subthalamic nucleus (STN) of the same subject remains unclear. In this study, the DBS electrodes were bilaterally implanted in the GPi and STN in patients with Tourette's syndrome (TS). The local field potentials were simultaneously recorded from the GPi and STN during pallidal DBS with 130 Hz, 60 microseconds, and 1V/2V/2.5V voltages. The time-frequency characteristics were analyzed across the conditions of resting, stimulation and post-stimulation. The results showed that alpha and beta oscillation existed in the basal ganglia and the beta oscillation was attenuated by pallidal stimulation. The attenuations are significantly different among 1V/2V/2.5V voltages. The results suggest that beta oscillations may have physiological function in resisting tics in TS. Thus, the oscillation- and symptom-guided intelligent DBS needs to be investigated.
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http://dx.doi.org/10.1109/EMBC.2019.8856535DOI Listing
July 2019

Quantifying the influence of DBS surgery in patients with Parkinson's disease during perioperative period by wearable sensors.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:3311-3314

It is a significant but ignored issue to quantify the influence of Deep Brain Stimulation (DBS) surgery in patients with Parkinson's disease during the whole perioperative period. In this paper, wearable sensors were utilized to record patients' motor changes in the time before surgery, after surgery with stimulation off and stimulation on. The results showed that the DBS surgery is effective and safe in the perioperative period.
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http://dx.doi.org/10.1109/EMBC.2019.8856618DOI Listing
July 2019

Epileptic States Recognition Using Transfer Learning.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:2539-2542

Automatic recognition of electroencephalogram (EEG) signals plays a major role in epilepsy diagnosis and assessment. However, the recognition accuracy of conventional methods is usually not satisfactory because of the inconsistent distribution of training and testing data in practical applications. To overcome this problem, we used cross-domain mean joint approximation embedding (CMJAE) transductive transfer learning method to realize the knowledge transfer from the training data to the testing data by measuring the distribution difference between them. We combined the subspace learning and joint distribution to adapt the marginal and conditional distribution discrepancy. Our method was able to effectively learn a model for the testing data from training data with different distribution at a low computational complexity cost. On a public dataset, an ad-hoc cross-validation scheme of the proposed method exhibited that the average recognition accuracy, sensitivity, specificity of different states was 97.5%, 94.3%, 92.7% respectively, much better than conventional machine learning or deep learning methods, which may serve as a promising strategy for epileptic states recognition algorithms.
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http://dx.doi.org/10.1109/EMBC.2019.8857265DOI Listing
July 2019

Cardiovascular autonomic responses in patients with Parkinson disease to pedunculopontine deep brain stimulation.

Clin Auton Res 2019 12 6;29(6):615-624. Epub 2019 Sep 6.

Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.

Purpose: Dysautonomia can be a debilitating feature of Parkinson disease (PD). Pedunculopontine nucleus (PPN) stimulation may improve gait disorders in PD, and may also result in changes in autonomic performance.

Methods: To determine whether pedunculopontine nucleus stimulation improves cardiovascular responses to autonomic challenges of postural tilt and Valsalva manoeuver, eight patients with pedunculopontine nucleus deep brain stimulation were recruited to the study; two were excluded for technical reasons during testing. Participants underwent head up tilt and Valsalva manoeuver with stimulation turned ON and OFF. Continuous blood pressure and ECG waveforms were recorded during these tests. In a single patient, local field potential activity was recorded from the implanted electrode during tilt.

Results: The fall in systolic blood pressure after tilt was significantly smaller with stimulation ON (mean - 8.3% versus - 17.2%, p = 0.044). Valsalva ratio increased with stimulation from median 1.15 OFF to 1.20 ON (p = 0.028). Baroreflex sensitivity increased during Valsalva compared to rest with stimulation ON versus OFF (p = 0.028). The increase in baroreflex sensitivity correlated significantly with the mean depth of PPN stimulating electrode contacts. This accounted for 89% of its variance (r = 0.943, p = 0.005).

Conclusion: PPN stimulation can modulate the cardiovascular system in patients with PD. In this study, it reduced the postural fall in systolic blood pressure during head-up tilt and improved the cardiovascular response during Valsalva, presumably by altering the neural control of baroreflex activation.
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http://dx.doi.org/10.1007/s10286-019-00634-8DOI Listing
December 2019

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

Eur J Neurosci 2020 01 23;51(2):628-640. Epub 2019 Sep 23.

Neural and Intelligence Engineering Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

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.
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http://dx.doi.org/10.1111/ejn.14569DOI Listing
January 2020

The pedunculopontine region and breathing in Parkinson's disease.

Ann Clin Transl Neurol 2019 May 1;6(5):837-847. Epub 2019 May 1.

Department of Physiology, Anatomy & Genetics University of Oxford Oxford UK.

Objective: Respiratory abnormalities such as upper airway obstruction are common in Parkinson's disease (PD) and are an important cause of mortality and morbidity. We tested the effect of pedunculopontine region (PPNr) stimulation on respiratory maneuvers in human participants with PD, and separately recorded PPNr neural activity reflected in the local field potential (LFP) during these maneuvers.

Methods: Nine patients with deep brain stimulation electrodes in PPNr, and seven in globus pallidus interna (GPi) were studied during trials of maximal inspiration followed by forced expiration with stimulation OFF and ON. Local field potentials (LFPs) were recorded in the unstimulated condition.

Results: PEFR increased from 6.41 ± 0.63 L/sec in the OFF stimulation state to 7.5 L ± 0.65 L/sec in the ON stimulation state ( = -2.666, df = 8,  = 0.024). Percentage improvement in PEFR was strongly correlated with proximity of the stimulated electrode contact to the mesencephalic locomotor region in the rostral PPN ( = 0.814,  = 9,  = 0.008). Mean PPNr LFP power increased within the alpha band (7-11 Hz) during forced respiratory maneuvers (1.63 ± 0.16 V/Hz) compared to resting breathing (0.77 ± 0.16 V/Hz;  = -2.197, df = 6,  = 0.028). No changes in alpha activity or spirometric indices were seen with GPi recording or stimulation. Percentage improvement in PEFR was strongly positively correlated with increase in alpha power ( = 0.653,  = 14 (7 PPNr patients recorded bilaterally),  = 0.0096).

Interpretation: PPNr stimulation in PD improves indices of upper airway function. Increased alpha-band activity is seen within the PPNr during forced respiratory maneuvers. Our findings suggest a link between the PPNr and respiratory performance in PD.
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http://dx.doi.org/10.1002/acn3.752DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529926PMC
May 2019

Decoding voluntary movements and postural tremor based on thalamic LFPs as a basis for closed-loop stimulation for essential tremor.

Brain Stimul 2019 Jul - Aug;12(4):858-867. Epub 2019 Feb 21.

Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom. Electronic address:

Background: High frequency Deep brain stimulation (DBS) targeting motor thalamus is an effective therapy for essential tremor (ET). However, conventional continuous stimulation may deliver unnecessary current to the brain since tremor mainly affects voluntary movements and sustained postures in ET.

Objective: We aim to decode both voluntary movements and the presence of postural tremor from the Local field potentials (LFPs) recorded from the electrode implanted in motor thalamus for stimulation, in order to close the loop for DBS so that stimulation could be delivered on demand, without the need for peripheral sensors or additional invasive electrodes.

Methods: LFPs from the motor thalamus, surface electromyographic (EMG) signals and/or behavioural measurements were simultaneously recorded in seven ET patients during temporary lead externalisation 3-5 days after the first surgery for DBS when they performed different voluntary upper limb movements. Nine different patients were recorded during the surgery, when they were asked to lift their arms to trigger postural tremor. A machine learning based binary classifier was used to detect voluntary movements and postural tremor based on features extracted from thalamic LFPs.

Results: Cross-validation demonstrated that both voluntary movements and postural tremor can be decoded with an average sensitivity of 0.8 and false detection rate of 0.2. Oscillatory activities in the beta frequency bands (13-23 Hz) and the theta frequency bands (4-7 Hz) contributed most to the decoding of movements and postural tremor, respectively, though incorporating features in different frequency bands using a machine learning approach increased the accuracy of decoding.
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http://dx.doi.org/10.1016/j.brs.2019.02.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6600875PMC
December 2019

FoxO3 transcription factor promotes autophagy after transient cerebral ischemia/reperfusion.

Int J Neurosci 2019 Aug 15;129(8):738-745. Epub 2019 Feb 15.

b Basic Medical Research Centre, Medical School , Nantong University , Nantong , People's Republic of China.

Autophagy was activated after cerebral ischemia reperfusion (I/R) injury. However, the molecular mechanisms underlying regulation of autophagy in cerebral I/R injury were not completely understood. Studies reported that Forked-box class O (FoxO) transcription factors involved in autophagy and might be the regulator of autophagy in multiple cells. In this study, we investigated the effects of FoxO3 on regulating autophagy after cerebral I/R injury. Rats were subjected to MCAO for 2 h and reperfusion for different times, western blot was used to examine the expression of p-FoxO3, FoxO3 and the autophagic marker LC3 and Beclin-1 in penumbral region. Then rats were injected with WT-FoxO3 or TM-FoxO3 adenovirus by lateral cerebral ventricle to increase the function of FoxO3, western blot was used to examine the expression of LC3 and Beclin-1 in penumbral region. TTC and HE staining were used to evaluate the effects of increased FoxO3 activation on I/R induced brain damage. Our studies showed that I/R injury resulted in induction of autophagy in penumbral brain tissue with concomitant dephosphorylation of FoxO3, consistent with increased activity of nuclear FoxO3 transcription factor. Increased FoxO3 activation led to autophagy significantly increased and had a protective effects on I/R injury. These data revealed an important role of FoxO3 in regulating autophagy in brain, and provided a new approach for further prevention and treatment of cerebral ischemia.
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http://dx.doi.org/10.1080/00207454.2018.1564290DOI Listing
August 2019

Enhancer RNAs: a missing regulatory layer in gene transcription.

Sci China Life Sci 2019 Jul 26;62(7):905-912. Epub 2018 Dec 26.

Basic Medical Research Center, School of Medicine, Nantong University, Nantong, 226019, China.

Enhancers and super-enhancers exert indispensable roles in maintaining cell identity through spatiotemporally regulating gene transcription. Meanwhile, active enhancers and super-enhancers also produce transcripts termed enhancer RNAs (eRNAs) from their DNA elements. Although enhancers have been identified for more than 30 years, widespread transcription from enhancers are just discovered by genome-wide sequencing and considered as the key to understand longstanding questions in gene transcription. RNA-transcribed enhancers are marked by histone modifications such as H3K4m1/2 and H3K27Ac, and enriched with transcription regulatory factors such as LDTFs, P300, CBP, BRD4 and MED1. Those regulatory factors might constitute a Mega-Trans-like complex to potently activate enhancers. Compared to mRNAs, eRNAs are quite unstable and play roles at local. Functionally, it has been shown that eRNAs promote formation of enhancer-promoter loops. Several studies also demonstrated that eRNAs help the binding of RNA polymerase II (RNAPII) or transition of paused RNAPII by de-association of the negative elongation factor (NELF) complex. Nevertheless, these proposed mechanisms are not universally accepted and still under controversy. Here, we comprehensively summarize the reported findings and make perspectives for future exploration. We also believe that super-enhancer derived RNAs (seRNAs) might be informative to understand the nature of super-enhancers.
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http://dx.doi.org/10.1007/s11427-017-9370-9DOI Listing
July 2019

Characteristics of Globus Pallidus Internus Local Field Potentials in Hyperkinetic Disease.

Front Neurol 2018 5;9:934. Epub 2018 Nov 5.

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

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. 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. Dystonia patients exhibited greater low frequency power (6-14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26-43 Hz) ( < 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. 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.
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http://dx.doi.org/10.3389/fneur.2018.00934DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6230660PMC
November 2018

A super-enhancer maintains homeostatic expression of Regnase-1.

Gene 2018 Aug 16;669:35-41. Epub 2018 May 16.

Basic Medical Research Center, School of Medicine, Nantong University, China; Department of Immunology, School of Medicine, Nantong University, China. Electronic address:

Regnase-1 is not only a key component in maintaining intracellular homeostasis but also a critical negative regulator in preventing autoimmune diseases and cancer development. To keep homeostatic state, Regnase-1 has to be maintained at a desired level in multiple cell types. However, the molecular mechanism of keeping a certain transcriptional level of Reganase-1 is largely unknown. In this study, we found a super-enhancer (Reg-1-SE) around Regnase-1 gene is able to control the homeostatic expression of Regnase-1. Functional inhibition of super-enhancers through BRD4 inhibitors or genetic silence of key components such as BRD4 and MED1 significantly downregulates Regnase-1 expression at multiple cell types. Consistently, treatment of JQ1 or I-BET-762 dramatically decreases the protein level of Regnase-1. By analyzing Regnase-1 gene, the distribution of H3K27Ac is highly enriched at a 8 kb DNA region around the second intron. Several DNA elements at the second intron are highly conserved between different species. Deletion of the second intron by CRISPR-Cas9 technology significantly reduces the expression of Regnase-1. JQ1 or I-BET-762 failed to further downregulate the expression of Regnase-1 in cells without the second intron. Our result reveals a novel molecular mechanism by which a super-enhancer around the second intron regulates the expression of Regnase-1, and in turn maintains a desired level of Regnase-1.
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http://dx.doi.org/10.1016/j.gene.2018.05.052DOI Listing
August 2018

[Quantitative assessment of motor function in patients with Parkinson's disease using wearable sensors].

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2018 04;35(2):206-213

Suzhou Institute of Biomedical Engineering, Chinese Academy of Sciences, Suzhou, Jiangsu 215163,

Motor dysfunction is the main clinical symptom and diagnosis basis of patients with Parkinson's disease (PD). A total of 30 subjects were recruited in this study, including 15 PD patients (PD group) and 15 healthy subjects (control group). Then 5 wearable inertial sensor nodes were worn on the bilateral upper limbs, lower limbs and waist of subjects. When completing the 6 paradigm tasks, the acceleration and angular velocity signals from different parts of the body were acquired and analyzed to obtain 20 quantitative parameters which contain information about the amplitude, frequency, and fatigue degree of movements to assess the motor function. The clinical data of the two groups were statistically analyzed and compared, and then Back Propagation (BP) Neural Network was used to classify the two groups and predict the clinical score. The final results showed that most of the parameters had significant difference between the two groups, ten times of 5-fold cross validation showed that the classification accuracy of the BP Neural Network for the two groups was 90%, and the predictive accuracy of Hoehn-Yahr (H-Y) staging and unified PD rating scale (UPDRS) Ⅲ score of the patients were 72.80% and 68.64%, respectively. This study shows the feasibility of quantitative assessment of motor function in PD patients using wearable sensors, and the quantitative parameters obtained in this paper may have reference value for future related research.
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http://dx.doi.org/10.7507/1001-5515.201704037DOI Listing
April 2018

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

Front Neurosci 2018 11;12:237. Epub 2018 Apr 11.

Neural and Intelligence Engineering Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

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.
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http://dx.doi.org/10.3389/fnins.2018.00237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904287PMC
April 2018

Oscillatory local field potentials of the nucleus accumbens and the anterior limb of the internal capsule in heroin addicts.

Clin Neurophysiol 2018 06 30;129(6):1242-1253. Epub 2018 Mar 30.

Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an 710038, China. Electronic address:

Objectives: The nucleus accumbens (NAc) is known to regulate the motivation and underlie addictive behaviors, and the anterior limb of the internal capsule (ALIC) is involved in several psychiatric disorders. Our study aimed to explore the functions of NAc and ALIC electrophysiologically.

Methods: The local field potentials (LFPs) of the NAc and ALIC were recorded from 7 heroin addicts treated with deep brain stimulation. Correlation analysis was made between LFP powers in various frequency bands and the subjects' neuropsychological test scores; coherence was calculated for the LFPs in NAc and ALIC.

Results: Both the NAc and ALIC exhibited prominent theta and alpha frequency band activity in the LFP power spectra. Additionally, a distinct beta band peak was detected in the power spectra of ALIC LFPs, which may represent the activity of striatal bridge cells. There was a significant negative correlation between the power of the theta frequency band of ALIC LFPs and visual analogue scale (VAS) scores indicative of cravings (Spearman's ρ = -0.758, P = 0.002), and a significant positive correlation was found between the power of the alpha frequency band of NAc LFPs and subjects' scores on the Hamilton depression inventory (ρ = 0.727, P = 0.005). LFPs of the NAc and ALIC exhibited higher coherence values in the theta and alpha frequency bands.

Conclusions: The results suggest that theta power in the ALIC/dorsal striatum and alpha power in the NAc may be associated with drug cravings and depressive symptoms, respectively, in heroin addicts. For these subjects, the neural activities in the dorsal and ventral striatum were mainly coordinated within the low-frequency band.

Significance: The study illustrates the neurophysiologic characteristics of heroin addiction and its comorbidities, providing a potential theoretical basis for optimizing deep brain stimulation (DBS) therapy.
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http://dx.doi.org/10.1016/j.clinph.2018.03.008DOI Listing
June 2018

Intra-operative characterisation of subthalamic oscillations in Parkinson's disease.

Clin Neurophysiol 2018 05 27;129(5):1001-1010. Epub 2018 Feb 27.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. Electronic address:

Objective: This study aims to use the activities recorded directly from the deep brain stimulation (DBS) electrode to address the focality and distinct nature of the local field potential (LFP) activities of different frequency.

Methods: Pre-operative and intra-operative magnetic resonance imaging (MRI) were acquired from patients with Parkinson's disease (PD) who underwent DBS in the subthalamic nucleus and intra-operative LFP recording at rest and during cued movements. Images were reconstructed and 3-D visualized using Lead-DBS® toolbox to determine the coordinates of contact. The resting spectral power and movement-related power modulation of LFP oscillations were estimated.

Results: Both subthalamic LFP activity recorded at rest and its modulation by movement had focal maxima in the alpha, beta and gamma bands. The spatial distribution of alpha band activity and its modulation was significantly different to that in the beta band. Moreover, there were significant differences in the scale and timing of movement related modulation across the frequency bands.

Conclusion: Subthalamic LFP activities within specific frequency bands can be distinguished by spatial topography and pattern of movement related modulation.

Significance: Assessment of the frequency, focality and pattern of movement related modulation of subthalamic LFPs reveals a heterogeneity of neural population activity in this region. This could potentially be leveraged to finesse intra-operative targeting and post-operative contact selection.
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http://dx.doi.org/10.1016/j.clinph.2018.01.075DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884428PMC
May 2018

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

Neurobiol Dis 2018 Jan 13;109(Pt A):117-126. Epub 2017 Oct 13.

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai 200433, China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.nbd.2017.10.009DOI Listing
January 2018
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