Contralesional Anodal Transcranial Direct Current Stimulation Promotes Intact Corticospinal Tract Axonal Sprouting and Functional Recovery After Traumatic Brain Injury in Mice.

BACKGROUND: Anodal transcranial direct current stimulation (AtDCS), a neuromodulatory technique, has been applied to treat traumatic brain injury (TBI) in patients and was reported to promote functional improvement. We evaluated the effect of contralesional AtDCS on axonal sprouting of the intact corticospinal tract (CST) and the underlying mechanism in a TBI mouse model to provide more preclinical evidence for the use of AtDCS to treat TBI. METHODS: TBI was induced in mice by a contusion device. Then, the mice were subjected to contralesional AtDCS 5 days per week followed by a 2-day interval for 7 weeks. After AtDCS, motor function was evaluated by the irregular ladder walking, narrow beam walking, and open field tests. CST sprouting was assessed by anterograde and retrograde labeling of corticospinal neurons (CSNs), and the effect of AtDCS was further validated by pharmacogenetic inhibition of axonal sprouting using clozapine-N-oxide (CNO). RESULTS: TBI resulted in damage to the ipsilesional cortex, while the contralesional CST remained intact. AtDCS improved the skilled motor functions of the impaired hindlimb in TBI mice by promoting CST axon sprouting, specifically from the intact hemicord to the denervated hemicord. Furthermore, electrical stimulation of CSNs significantly increased the excitability of neurons and thus activated the mechanistic target of rapamycin (mTOR) pathway. CONCLUSIONS: Contralesional AtDCS improved skilled motor following TBI, partly by promoting axonal sprouting through increased neuronal activity and thus activation of the mTOR pathway.

Adjunct Methods for Alzheimer's Disease Detection: A Review of Auditory Evoked Potentials.

The auditory afferent pathway as a clinical marker of Alzheimer's disease (AD) has sparked interest in investigating the relationship between age-related hearing loss (ARHL) and AD. Given the earlier onset of ARHL compared to cognitive impairment caused by AD, there is a growing emphasis on early diagnosis and intervention to postpone or prevent the progression from ARHL to AD. In this context, auditory evoked potentials (AEPs) have emerged as a widely used objective auditory electrophysiological technique for both the clinical diagnosis and animal experimentation in ARHL due to their non-invasive and repeatable nature. This review focuses on the application of AEPs in AD detection and the auditory nerve system corresponding to different latencies of AEPs. Our objective was to establish AEPs as a systematic and non-invasive adjunct method for enhancing the diagnostic accuracy of AD. The success of AEPs in the early detection and prediction of AD in research settings underscores the need for further clinical application and study.

Micro SleepNet: efficient deep learning model for mobile terminal real-time sleep staging.

The real-time sleep staging algorithm that can perform inference on mobile devices without burden is a prerequisite for closed-loop sleep modulation. However, current deep learning sleep staging models have poor real-time efficiency and redundant parameters. We propose a lightweight and high-performance sleep staging model named Micro SleepNet, which takes a 30-s electroencephalography (EEG) epoch as input, without relying on contextual signals. The model features a one-dimensional group convolution with a kernel size of 1 × 3 and an Efficient Channel and Spatial Attention (ECSA) module for feature extraction and adaptive recalibration. Moreover, the model efficiently performs feature fusion using dilated convolution module and replaces the conventional fully connected layer with Global Average Pooling (GAP). These design choices significantly reduce the total number of model parameters to 48,226, with only approximately 48.95 Million Floating-point Operations per Second (MFLOPs) computation. The proposed model is conducted subject-independent cross-validation on three publicly available datasets, achieving an overall accuracy of up to 83.3%, and the Cohen Kappa is 0.77. Additionally, we introduce Class Activation Mapping (CAM) to visualize the model's attention to EEG waveforms, which demonstrate the model's ability to accurately capture feature waveforms of EEG at different sleep stages. This provides a strong interpretability foundation for practical applications. Furthermore, the Micro SleepNet model occupies approximately 100 KB of memory on the Android smartphone and takes only 2.8 ms to infer one EEG epoch, meeting the real-time requirements of sleep staging tasks on mobile devices. Consequently, our proposed model has the potential to serve as a foundation for accurate closed-loop sleep modulation.

Transcranial Direct Current Stimulation Alleviates Neurovascular Unit Dysfunction in Mice With Preclinical Alzheimer's Disease.

Neurons, glial cells and blood vessels are collectively referred to as the neurovascular unit (NVU). In the Alzheimer's disease (AD) brain, the main components of the NVU undergo pathological changes. Transcranial direct current stimulation (tDCS) can protect neurons, induce changes in glial cells, regulate cerebral blood flow, and exert long-term neuroprotection. However, the mechanism by which tDCS improves NVU function is unclear. In this study, we explored the effect of tDCS on the NVU in mice with preclinical AD and the related mechanisms. 10 sessions of tDCS were given to six-month-old male APP/PS1 mice in the preclinical stage. The model group, sham stimulation group, and control group were made up of APP/PS1 mice and C57 mice of the same age. All mice were histologically evaluated two months after receiving tDCS. Protein content was measured using Western blotting and an enzyme-linked immunosorbent assay (ELISA). The link between glial cells and blood vessels was studied using immunofluorescence staining and lectin staining. The results showed that tDCS affected the metabolism of Aß; the levels of Aß, amyloid precursor protein (APP) and BACE1 were significantly reduced, and the levels of ADAM10 were significantly increased in the frontal cortex and hippocampus in the stimulation group. In the stimulation group, tDCS reduced the protein levels of Iba1 and GFAP and increased the protein levels of NeuN, LRP1 and PDGRFß. This suggests that tDCS can improve NVU function in APP/PS1 mice in the preclinical stage. Increased blood vessel density and blood vessel length, decreased IgG extravasation, and increased the protein levels of occludin and coverage of astrocyte foot processes with blood vessels suggested that tDCS had a protective effect on the blood-brain barrier. Furthermore, the increased numbers of Vimentin, S100 expression and blood vessels (lectin-positive) around Aß indicated that the effect of tDCS was mediated by astrocytes and blood vessels. There was no significant difference in these parameters between the model group and the sham stimulation group. In conclusion, our results show that tDCS can improve NVU function in APP/PS1 mice in the preclinical stage, providing further support for the use of tDCS as a treatment for AD.

Anodal transcranial direct current stimulation alleviates cognitive impairment in an APP/PS1 model of Alzheimer's disease in the preclinical stage.

Anodal transcranial direct current stimulation (AtDCS) has been shown to alleviate cognitive impairment in an APP/PS1 model of Alzheimer's disease in the preclinical stage. However, this enhancement was only observed immediately after AtDCS, and the long-term effect of AtDCS remains unknown. In this study, we treated 26-week-old mouse models of Alzheimer's disease in the preclinical stage with 10 AtDCS sessions or sham stimulation. The Morris water maze, novel object recognition task, and novel object location test were implemented to evaluate spatial learning memory and recognition memory of mice. Western blotting was used to detect the relevant protein content. Morphological changes were observed using immunohistochemistry and immunofluorescence staining. Six weeks after treatment, the mice subjected to AtDCS sessions had a shorter escape latency, a shorter path length, more platform area crossings, and spent more time in the target quadrant than sham-stimulated mice. The mice subjected to AtDCS sessions also performed better in the novel object recognition and novel object location tests than sham-stimulated mice. Furthermore, AtDCS reduced the levels of amyloid-ß42 and glial fibrillary acidic protein, a marker of astrocyte activation, and increased the level of neuronal marker NeuN in hippocampal tissue. These findings suggest that AtDCS can improve the spatial learning and memory abilities and pathological state of an APP/PS1 mouse model of Alzheimer's disease in the preclinical stage, with improvements that last for at least 6 weeks.

Benefits in Alzheimer's Disease of Sensory and Multisensory Stimulation.

Alzheimer's disease (AD) is a serious neurodegenerative disease, which seriously affects the behavior, cognition, and memory of patients. Studies have shown that sensory stimulation can effectively improve the cognition and memory of AD patients, and its role in brain plasticity and neural regulation is initially revealed. This paper aims to review the effect of various sensory stimulation and multisensory stimulation for AD, and to explain the possible mechanism, so as to provide some new ideas for further research in this field. We searched the Web of Science and PubMed databases (from 2000 to October 27, 2020) for literature on the treatment of AD with sensory and multisensory stimulation, including music therapy, aromatherapy, rhythmic (e.g., visual or acoustic) stimulation, light therapy, multisensory stimulation, and virtual reality assisted therapy, then conducted a systematic analysis. Results show these sensory and multisensory stimulations can effectively ameliorate the pathology of AD, arouse memory, and improve cognition and behaviors. What's more, it can cause brain nerve oscillation, enhance brain plasticity, and regulate regional cerebral blood flow. Sensory and multisensory stimulation are very promising therapeutic methods, and they play an important role in the improvement and treatment of AD, but their potential mechanism and stimulation parameters need to be explored and improved.

Deep Brain Stimulation for Alzheimer's Disease: Stimulation Parameters and Potential Mechanisms of Action.

Deep brain stimulation (DBS) is a neurosurgical technique that regulates neuron activity by using internal pulse generators to electrodes in specific target areas of the brain. As a blind treatment, DBS is widely used in the field of mental and neurological diseases, although its mechanism of action is still unclear. In the past 10 years, DBS has shown a certain positive effect in animal models and patients with Alzheimer's disease (AD), but there are also different results that may be related to the stimulation parameters of DBS. Based on this, determining the optimal stimulation parameters for DBS in AD and understanding its mechanism of action are essential to promote the clinical application of DBS in AD. This review aims to explore the therapeutic effect of DBS in AD, and to analyze its stimulation parameters and potential mechanism of action. The keywords "Deep brain stimulation" and "Alzheimer's Disease" were used for systematic searches in the literature databases of Web of Science and PubMed (from 1900 to September 29, 2020). All human clinical studies and animal studies were reported in English, including individual case studies and long-term follow-up studies, were included. These studies described the therapeutic effects of DBS in AD. The results included 16 human clinical studies and 14 animal studies, of which 28 studies clearly demonstrated the positive effect of DBS in AD. We analyzed the current stimulation parameters of DBS in AD from stimulation target, stimulation frequency, stimulation start time, stimulation duration, unilateral/bilateral treatment and current intensity, etc., and we also discussed its potential mechanism of action from multiple aspects, including regulating related neural networks, promoting nerve oscillation, reducing ß-amyloid and tau levels, reducing neuroinflammation, regulating the cholinergic system, inducing the synthesis of nerve growth factor.

Anodal Transcranial Direct Current Stimulation Can Improve Spatial Learning and Memory and Attenuate Aß42 Burden at the Early Stage of Alzheimer's Disease in APP/PS1 Transgenic Mice.

Alzheimer's disease (AD) is an irreversible progressive neurodegenerative disease. Intervention in the early stage of AD is a new path for AD treatment that is being explored. The behavioral and pathological effects of anodal transcranial direct current stimulation (AtDCS) at the early stage of AD in the mouse model, amyloid precursor protein (APP)/presenilin-1 (PS1) transgenic mice, were investigated based on our previous studies. Thirty-three 6-month-old male APP/PS1 mice were randomly divided into the model group (AD group), model + sham stimulation group (ADST group) and stimulation group (ADT group). Eleven 6-month-old male C57 wild-type mice were randomly selected as a control group (CTL group). The ADT group received 10 AtDCS sessions. The Morris water maze (MWM) task and novel object recognition (NOR) task were used to test mouse memory. Nissl staining, Western blot (WB), immunohistochemistry and immunofluorescence staining of ß-amyloid (Aß42), glial fibrillary acidic protein (GFAP) and NF200 were conducted for pathological analysis. The ADT group and the CTL group had a shorter escape latency and more platform-region crossings than the AD group and ADST group in the MWM. There was no significant difference in the discrimination index among the groups in the NOR task. Pathological analysis showed visible differences between the AD group and ADT group. This study revealed that early-stage APP/PS1 transgenic mice did not show recognition memory impairment. AtDCS effectively improved spatial learning and memory in the early-stage APP/PS1 transgenic mouse model of AD, alleviating Aß burden and having a protective effect on neurons. AtDCS could improve AD-related symptoms by activating many glial cells to promote the degradation and clearance of Aß or directly affecting production and degradation of Aß to reduce glial activation. AtDCS is an effective means of early intervention in the early stage of AD.

After-effects of repetitive anodal transcranial direct current stimulation on learning and memory in a rat model of Alzheimer's disease.

Repetitive anodal transcranial direct current stimulation (tDCS) in a rat model of Alzheimer's disease (AD) has been shown to have distinct neuroprotective effects. Moreover, the effects of anodal tDCS not only occur during the stimulation but also persist after the stimulation has ended (after-effects). Here, the duration of the after-effects induced by repetitive anodal tDCS was investigated based on our previous studies. Adult male Sprague-Dawley rats were divided into three groups: a sham group, a ß-amyloid (Aß) group (AD group) and a stimulation group (ATD group). Aß was injected into the bilateral hippocampi of the rats in the AD and ATD groups to produce the AD model. Rats in the ATD group underwent 10 sessions of anodal tDCS, and the after-effects of repetitive anodal tDCS were evaluated by behavioral and histological analyses. A Morris water maze (MWM) was utilized on a monthly basis to assess spatial learning and memory abilities. The ATD group showed shorter escape latencies and more platform region crossings than the AD group. Hippocampal choline acetyltransferase (ChAT) and glial fibrillary acidic protein (GFAP) immunohistochemical analyses were carried out after the last MWM assessment. The immunohistochemistry results showed notable differences among the groups, particularly between the AD and ATD groups. This study reveals that repetitive anodal tDCS can not only improve cognitive function and memory performance but also has long-term after-effects that persist for 2 months.

Parameter Optimization Analysis of Prolonged Analgesia Effect of tDCS on Neuropathic Pain Rats.

Background: Transcranial direct current stimulation (tDCS) is widely used to treat human nerve disorders and neuropathic pain by modulating the excitability of cortex. The effectiveness of tDCS is influenced by its stimulation parameters, but there have been no systematic studies to help guide the selection of different parameters. Objective: This study aims to assess the effects of tDCS of primary motor cortex (M1) on chronic neuropathic pain in rats and to test for the optimal parameter combinations for analgesia. Methods: Using the chronic neuropathic pain models of chronic constriction injury (CCI), we measured pain thresholds before and after anodal-tDCS (A-tDCS) using different parameter conditions, including stimulation intensity, stimulation time, intervention time and electrode located (ipsilateral or contralateral M1 of the ligated paw on male/female CCI models). Results: Following the application of A-tDCS over M1, we observed that the antinociceptive effects were depended on different parameters. First, we found that repetitive A-tDCS had a longer analgesic effect than single stimulus, and both ipsilateral-tDCS (ip-tDCS) and contralateral-tDCS (con-tDCS) produce a long-lasting analgesic effect on neuropathic pain. Second, the antinociceptive effects were intensity-dependent and time-dependent, high intensities worked better than low intensities and long stimulus durations worked better than short stimulus durations. Third, timing of the intervention after injury affected the stimulation outcome, early use of tDCS was an effective method to prevent the development of pain, and more frequent intervention induced more analgesia in CCI rats, finally, similar antinociceptive effects of con- and ip-tDCS were observed in both sexes of CCI rats. Conclusion: Optimized protocols of tDCS for treating antinociceptive effects were developed. These findings should be taken into consideration when using tDCS to produce analgesic effects in clinical applications.

Intensity-dependent effects of repetitive anodal transcranial direct current stimulation on learning and memory in a rat model of Alzheimer's disease.

Single-session anodal transcranial direct current stimulation (tDCS) can improve the learning-memory function of patients with Alzheimer's disease (AD). After-effects of tDCS can be more significant if the stimulation is repeated regularly in a period. Here the behavioral and the histologic effects of the repetitive anodal tDCS on a rat model of AD were investigated. Sprague-Dawley rats were divided into 6 groups, the sham group, the ß-amyloid (Aß) group, the Aß+20µA tDCS group, the Aß+60µA tDCS group, the Aß+100µA tDCS group and the Aß+200µA tDCS group. Bilateral hippocampus of the rats in the Aß group and the Aß+tDCS groups were lesioned by Aß1-40 to produce AD models. One day after drug injection, repetitive anodal tDCS (10 sessions in two weeks, 20min per session) was applied to the frontal cortex of the rats in the tDCS groups, while sham stimulation was applied to the Aß group and the sham group. The spatial learning and memory capability of the rats were tested by Morris water maze. Bielschowsky's silver staining, Nissl's staining, choline acetyltransferase (ChAT) and glial-fibrillary-acidic protein (GFAP) immunohistochemistry of the hippocampus were conducted for histologic analysis. Results show in the Morris water maze task, rats in the Aß+100µA and the Aß+200µA tDCS groups had shorter escape latency and larger number of crossings on the platform. Significant histologic differences were observed in the Aß+100µA and the Aß+200µA tDCS groups compared to the Aß group. The behavioral and the histological experiments indicate that the proposed repetitive anodal tDCS treatment can protect spatial learning and memory dysfunction of Aß1-40-lesioned AD rats.

[A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

[Design of low-intermediate frequency electrotherapy and pain assessment system].

Aiming at the single treatment and the design separation between treatment and assessment in electrotherapy equipment, a kind of system including low-intermediate frequency treatment and efficacy evaluation was developed. With C8051F020 single-chip microcomputer as the core and the circuit design and software programming used, the system realized the random switch of therapeutic parameters, the collection, display and data storage of pressure pain threshold in the assessment. Experiment results showed that the stimulus waveform, current intensity, frequency, duty ratio of the system output were adjustable, accurate and reliable. The obtained pressure pain threshold had a higher accuracy (< 0.3 N) and better stability, guiding the parameter choice in the precise electrical stimulation. It, therefore, provides a reliable technical support for the treatment and curative effect assessment.

[Design of an embedded stroke rehabilitation apparatus system based on Linux computer engineering].

A realizaton project of electrical stimulator aimed at motor dysfunction of stroke is proposed in this paper. Based on neurophysiological biofeedback, this system, using an ARM9 S3C2440 as the core processor, integrates collection and display of surface electromyography (sEMG) signal, as well as neuromuscular electrical stimulation (NMES) into one system. By embedding Linux system, the project is able to use Qt/Embedded as a graphical interface design tool to accomplish the design of stroke rehabilitation apparatus. Experiments showed that this system worked well.

[Effects of fastigial nucleus stimulation on crucial cardiovascular physiological parameters].

OBJECTIVE: In order to study the effect of fastigial nucleus stimulation (FNS) on human cardiovascular system, the photo plethysmogram (PPG) affected by FNS were recorded and analyzed. METHODS: Thirty volunteers' pulse signals were recorded before, during and after the FNS, and 5 PPG characteristics, such as H, Slope, and K were extracted. Changes of each characteristic in three stages were analyzed contrastive and based on which physiological changes caused by FNS were described. RESULTS: The pulse wave showed sensitive on-going short-term changes during the FNS. CONCLUSION: Changes of characteristics indicates that FNS results in ongoing short-term changes of some physiological parameters such as peripheral blood flow and peripheral resistance.

[Development of the stroke rehabilitation apparatus based on EMG-biofeedback].

This Stroke Rehabilitation Apparatus uses the electromyography triggered neuromuscular electrical stimulation as the means of the major therapeutics, and the fastigial nucleus stimulation as the means of the assistant therapeutics. This paper introduces the overall structure of the apparatus, the principle of its component, the EMG processing based on local nonlinear projective filtering algorithm and the alternating treatment modes. The therapeutic apparatus has the features of non-invasiveness, safety, convenience and strong alternating capability.

[R-wave detection of ECG signal by using wavelet transform].

The detection of R-wave of ECG is essential to the analysis of the heart rate variability (HRV). In this paper, an R-wave detection method using wavelet transform(WT) is presented in line with the principle of discrete wavelet transform(DWT) and multi-resolution technique (MRT). We made use of the special properties of dbl wavelet in time-domain, decomposed the original ECG signals into 3-level detailed signals on different frequency bands by using DWT with Mallat algorithm, and got appropriate threshold values in different high frequency bands to distinguish R-wave. It is concluded that the algorithm had significant effects on it, which is verified by MIT/BIH (Massachusetts Institute of Technology/Boston's Beth Israel Hospital) ECG Database. The results show that R-wave could be detected accurately and localized precisely by this method, even when the patient was seriously sick or the signal was disturbed by noise. Consequently the method has a quite high locating precision (its error is not more than two sampled points and about 85 percent of the points of R-wave in ECG signal are localized precisely) and the correct detection rate of R-wave is 99.8% by using wavelet transform, so this method is quite feasible.

[Application of Ris/PACS in the prevention and treatment of SARS at the hospital radiology].

This paper introduces the difficulties ever facing the hospital radiology during the earlier prevention and treatment times of SARS and a RIS/ PACS system based on the DICOM standard and its actual functions in that condition is described, and a typical system project and its related analysis and explanation are put forward.

[Exercise ECG signal de-noising using unbiased risk estimate and wavelet transform].

In this paper a filtering method for EECG (Exercise ECG) signal is proposed which is based on wavelet transform (WT) and Stein's unbiased risk estimate (SURE). This algorithm was used to decompose original EECG signals into detail signals on different frequency bands by using WT and get different thresholds with SURE. According to EECG signal features and by using the above thresholds, the method amended several detail signals so that the main interferences in EECG signal can be removed efficiently. The authors also put forward two indexes to estimate the validity of such algorithms. Our experimental results demonstrate that this is an efficient de-noising method for EECG.

[The research advance of analytical methodology for detecting bovine spongiform encephalopathy].

Bovine spongiform encephalopathy (BSE) is an infectious disease which can threaten animal husbandry and human health seriously. The disease mainly violates the central neural system. This article selectively reviewed current researches on the analytical detection of BSE and transmissible spongiform encephalopathy (TSE).