Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis.

Peripheral nerve stimulation is an effective neuromodulation method in patients with lower extremity movement disorders caused by stroke, spinal cord injury, or other diseases. However, most current studies on rehabilitation using sciatic nerve stimulation focus solely on ankle motor regulation through stimulation of common peroneal and tibial nerves. Using the electrical nerve stimulation method, we here achieved muscle control via different sciatic nerve branches to facilitate the regulation of lower limb movements during stepping and standing. A map of relationships between muscles and nerve segments was established to artificially activate specific nerve fibers with the biomimetic stimulation waveform. Then, characteristic curves depicting the relationship between neural electrical stimulation intensity and joint control were established. Finally, by testing the selected stimulation parameters in anesthetized rats, we confirmed that single-cathode extraneural electrical stimulation could activate combined movements to promote lower limb movements. Thus, this method is effective and reliable for use in treatment for improving and rehabilitating lower limb motor dysfunction.

Liquid Metal-Based Electrode Array for Neural Signal Recording.

Neural electrodes are core devices for research in neuroscience, neurological diseases, and neural-machine interfacing. They build a bridge between the cerebral nervous system and electronic devices. Most of the neural electrodes in use are based on rigid materials that differ significantly from biological neural tissue in flexibility and tensile properties. In this study, a liquid-metal (LM) -based 20-channel neural electrode array with a platinum metal (Pt) encapsulation material was developed by microfabrication technology. The in vitro experiments demonstrated that the electrode has stable electrical properties and excellent mechanical properties such as flexibility and bending, which allows the electrode to form conformal contact with the skull. The in vivo experiments also recorded electroencephalographic signals using the LM-based electrode from a rat under low-flow or deep anesthesia, including the auditory-evoked potentials triggered by sound stimulation. The auditory-activated cortical area was analyzed using source localization technique. These results indicate that this 20-channel LM-based neural electrode array satisfies the demands of brain signal acquisition and provides high-quality-electroencephalogram (EEG) signals that support source localization analysis.

Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain.

The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes, but little was known about the functional network among the cortical areas during this process. To address the question, we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven area. Whole-brain electroencephalography signals were recorded by 32-channel implanted electrodes. Afterward, we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag index. Finally, machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of rats. We found that the functional connectivity level was higher in the preparation phase compared to the walking phase. In addition, the cortex pays more attention to the control of hind limbs with higher requirements for muscle activity. The level of functional connectivity was lower where the terrain ahead can be predicted. Functional connectivity bursts after the rat accidentally made contact with uneven terrain, while in subsequent movement, it was significantly lower than normal walking. In addition, the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during walking. These results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.

ACx-projecting cholinergic neurons in the NB influence the BLA ensembles to modulate the discrimination of auditory fear memory.

Animals need discriminating auditory fear memory (DAFM) to survive, but the related neural circuits of DAFM remain largely unknown. Our study shows that DAFM depends on acetylcholine (ACh) signal in the auditory cortex (ACx), which is projected from the nucleus basalis (NB). At the encoding stage, optogenetic inhibition of cholinergic projections of NB-ACx obfuscates distinct tone-responsive neurons of ACx recognizing from fear-paired tone to fear-unpaired tone signals, while simultaneously regulating the neuronal activity and reactivation of basal lateral amygdala (BLA) engram cells at the retrieval stage. This NBACh-ACx-BLA neural circuit for the modulation of DAFM is especially dependent on the nicotinic ACh receptor (nAChR). A nAChR antagonist reduces DAFM and diminishes the increased magnitude of ACx tone-responsive neuronal activity during the encoding stage. Our data suggest a critical role of NBACh-ACx-BLA neural circuit in DAFM: manipulation of the NB cholinergic projection to the ACx via nAChR during the encoding stage affects the activation of ACx tone-responsive neuron clusters and the BLA engram cells during the retrieval stage, thus modulating the DAFM.

Genetic and Pharmacological Inhibition of Astrocytic Mysm1 Alleviates Depressive-Like Disorders by Promoting ATP Production.

Major depressive disorder (MDD) is a leading cause of disability worldwide. A comprehensive understanding of the molecular mechanisms of this disorder is critical for the therapy of MDD. In this study, it is observed that deubiquitinase Mysm1 is induced in the brain tissues from patients with major depression and from mice with depressive behaviors. The genetic silencing of astrocytic Mysm1 induced an antidepressant-like effect and alleviated the osteoporosis of depressive mice. Furthermore, it is found that Mysm1 knockdown led to increased ATP production and the activation of p53 and AMP-activated protein kinase (AMPK). Pifithrin α (PFT α) and Compound C, antagonists of p53 and AMPK, respectively, repressed ATP production and reversed the antidepressant effect of Mysm1 knockdown. Moreover, the pharmacological inhibition of astrocytic Mysm1 by aspirin relieved depressive-like behaviors in mice. The study reveals, for the first time, the important function of Mysm1 in the brain, highlighting astrocytic Mysm1 as a potential risk factor for depression and as a valuable target for drug discovery to treat depression.

Effect of neuromorphic transcutaneous electrical nerve stimulation (nTENS) of cortical functional networks on tactile perceptions: an event-related electroencephalogram study.

Background.Transcutaneous electrical nerve stimulation (TENS) is generally applied for tactile feedback in the field of prosthetics. The distinct mechanisms of evoked tactile perception between stimulus patterns in conventional TENS (cTENS) and neuromorphic TENS (nTENS) are relatively unknown. This is the first study to investigate the neurobiological effect of nTENS for cortical functional mechanism in evoked tactile perception.Methods.Twenty-one healthy participants were recruited in this study. Electroencephalogram (EEG) was recorded while the participants underwent a tactile discrimination task. One cTENS pattern (square pattern) and two nTENS patterns (electromyography and single motor unit patterns) were applied to evoke tactile perception in four fingers, including the right and left index and little fingers. EEG was preprocessed and somatosensory-evoked potentials (SEPs) were determined. Then, source-level functional networks based on graph theory were evaluated, including clustering coefficient, path length, global efficiency, and local efficiency in six frequency bands.Main results.Behavioral results suggested that the single motor units (SMUs) pattern of nTENS was the most natural tactile perception. SEPs results revealed that SMU pattern exhibited significant shorter latency in P1 and N1 components than the other patterns, while nTENS patterns have significantly longer latency in P3 component than cTENS pattern. Cortical functional networks showed that the SMU pattern had the lowest short path and highest efficiency in beta and gamma bands.Conclusion.This study highlighted that distinct TENS patterns could affect brain activities. The new characteristics in tactile manifestation of nTENS would provide insights for the application of tactile perception restoration.

Multisite Simultaneous Neural Recording of Motor Pathway in Free-Moving Rats.

Neural interfaces typically focus on one or two sites in the motoneuron system simultaneously due to the limitation of the recording technique, which restricts the scope of observation and discovery of this system. Herein, we built a system with various electrodes capable of recording a large spectrum of electrophysiological signals from the cortex, spinal cord, peripheral nerves, and muscles of freely moving animals. The system integrates adjustable microarrays, floating microarrays, and microwires to a commercial connector and cuff electrode on a wireless transmitter. To illustrate the versatility of the system, we investigated its performance for the behavior of rodents during tethered treadmill walking, untethered wheel running, and open field exploration. The results indicate that the system is stable and applicable for multiple behavior conditions and can provide data to support previously inaccessible research of neural injury, rehabilitation, brain-inspired computing, and fundamental neuroscience.

Different Modes of Low-Frequency Focused Ultrasound-Mediated Attenuation of Epilepsy Based on the Topological Theory.

Epilepsy is common brain dysfunction, where abnormal synchronized activities can be observed across multiple brain regions. Low-frequency focused pulsed ultrasound has been proven to modulate the epileptic brain network. In this study, we used two modes of low-intensity focused ultrasound (pulsed-wave and continuous-wave) to sonicate the brains of KA-induced epileptic rats, analyzed the EEG functional brain connections to explore their respective effect on the epileptic brain network, and discuss the mechanism of ultrasound neuromodulation. By comparing the brain network characteristics before and after sonication, we found that two modes of ultrasound both significantly affected the functional brain network, especially in the low-frequency band below 12 Hz. After two modes of sonication, the power spectral density of the EEG signals and the connection strength of the brain network were significantly reduced, but there was no significant difference between the two modes. Our results indicated that the ultrasound neuromodulation could effectively regulate the epileptic brain connections. The ultrasound-mediated attenuation of epilepsy was independent of modes of ultrasound.

Low-Intensity Focused Ultrasound-Mediated Attenuation of Acute Seizure Activity Based on EEG Brain Functional Connectivity.

(1) Background: Ultrasound has been used for noninvasive stimulation and is a promising technique for treating neurological diseases. Epilepsy is a common neurological disorder, that is attributed to uncontrollable abnormal neuronal hyperexcitability. Abnormal synchronized activities can be observed across multiple brain regions during a seizure. (2) Methods: we used low-intensity focused ultrasound (LIFU) to sonicate the brains of epileptic rats, analyzed the EEG functional brain network to explore the effect of LIFU on the epileptic brain network, and continued to explore the mechanism of ultrasound neuromodulation. LIFU was used in the hippocampus of epileptic rats in which a seizure was induced by kainic acid. (3) Results: By comparing the brain network characteristics before and after sonication, we found that LIFU significantly impacted the functional brain network, especially in the low-frequency band. The brain network connection strength across multiple brain regions significantly decreased after sonication compared to the connection strength in the control group. The brain network indicators (the path length, clustering coefficient, small-worldness, local efficiency and global efficiency) all changed significantly in the low-frequency. (4) Conclusions: These results revealed that LIFU could reduce the network connections of epilepsy circuits and change the structure of the brain network at the whole-brain level.

Association between cortical thickness and distinct vascular cognitive impairment and dementia in patients with white matter lesions.

NEW FINDINGS: What is the central question of this study? White matter lesions (WMLs) are a brain disease characterized by altered brain structural and functional connectivity, but findings have shown an inconsistent pattern: are there distinct cortical thickness changes in patients with WMLs subtypes? What is the main finding and its importance? Patients with WMLs with non-dementia vascular cognitive impairment and WMLs with vascular dementia showed distinct pathophysiology in cortical thickness. These neural correlates of WMLs should be considered in future treatment. ABSTRACT: The effect of cortical thickness on white matter lesions (WMLs) in patients with distinct vascular cognitive impairments is relatively unknown. This study investigated the correlation between cortical thickness and vascular cognitive manifestations. WML patients and healthy controls from Beijing Tiantan Hospital between 2014 and 2018 were included. The patients were further divided into two subgroups, namely WMLs with non-dementia vascular cognitive impairment (WML-VCIND) and WMLs with vascular dementia (WML-VaD) according to the Clinical Dementia Rating (CDR) scale and the Beijing version of the Montreal Cognitive Assessment (MoCA). Changes in cortical thickness were calculated using FreeSurfer. Pearson's correlation analysis was performed to explore the relationship between cognitive manifestations and cortical thickness in WML patients. Forty-five WML patients and 23 healthy controls were recruited. The WML group exhibited significant difference in cortical thickness compared to the control group. Significantly decreased cortical thickness in the middle and superior frontal gyri, middle temporal gyrus, angular gyrus and insula was found in the WML-VaD versus WML-VCIND subgroup. Cortical thickness deficits of the left caudal middle frontal gyrus (r = 0.451, P = 0.002), left rostral middle frontal gyrus (r = 0.514, P < 0.001), left superior frontal gyrus (r = 0.410, P = 0.006), right middle temporal gyrus (r = 0.440, P = 0.003), right pars triangularis (r = 0.462, P = 0.002), right superior frontal gyrus (r = 0.434, P = 0.004) and right insula (r = 0.499, P = 0.001) were positively correlated with the MoCA score in WML patients. The specific pattern of cortical thickness deficits in the WML-VaD subgroup revealed the pathophysiology of WMLs, which should be considered in future treatment of WMLs.

Rat Locomotion Detection Based on Brain Functional Directed Connectivity from Implanted Electroencephalography Signals.

Previous findings have suggested that the cortex involved in walking control in freely locomotion rats. Moreover, the spectral characteristics of cortical activity showed significant differences in different walking conditions. However, whether brain connectivity presents a significant difference during rats walking under different behavior conditions has yet to be verified. Similarly, whether brain connectivity can be used in locomotion detection remains unknown. To address those concerns, we recorded locomotion and implanted electroencephalography signals in freely moving rats performing two kinds of task conditions (upslope and downslope walking). The Granger causality method was used to determine brain functional directed connectivity in rats during these processes. Machine learning algorithms were then used to categorize the two walking states, based on functional directed connectivity. We found significant differences in brain functional directed connectivity varied between upslope and downslope walking. Moreover, locomotion detection based on brain connectivity achieved the highest accuracy (91.45%), sensitivity (90.93%), specificity (91.3%), and F1-score (91.43%). Specifically, the classification results indicated that connectivity features in the high gamma band contained the most discriminative information with respect to locomotion detection in rats, with the support vector machine classifier exhibiting the most efficient performance. Our study not only suggests that brain functional directed connectivity in rats showed significant differences in various behavioral contexts but also proposed a method for classifying the locomotion states of rat walking, based on brain functional directed connectivity. These findings elucidate the characteristics of neural information interaction between various cortical areas in freely walking rats.

Electrocortical activity in freely walking rats varies with environmental conditions.

Longstanding theories in the field of neurophysiology have held that walking in rats is an unconscious, rhythmic locomotion that does not require cortical involvement. However, recent studies have suggested that the extent of cortical involvement during walking actually varies depending on the environmental conditions. To determine the impact of environmental conditions on cortical engagement in freely walking rats, we recorded limb kinematics and signals from implanted electroencephalography arrays in rats performing a series of natural behaviors. We found that rat gaits were significantly different across various locomotion terrains (e.g. walking on an upslope vs. downslope). Further, rat forelimbs and hindlimbs showed similar patterns of motion. The results also suggested that rat cortical engagement during walking varied across environmental conditions. Specifically, α band power significantly increased during 30° downslope walking in the posterior parietal, left secondary motor, and left somatosensory clusters. Additionally, during 30° upslope walking, the ß band power was greater in the left primary motor and left and right secondary motor sources. Further, rats walking on up- or downslopes of varying steepness were found to have different cortical activities. Compared with 10° downslope walking, α band power was greater during 30° downslope locomotion in the left primary motor and somatosensory sources. These findings support the hypothesis that cortical contribution during walking in rats is influenced by environmental conditions, underlining the importance of goal-directed behaviors for motor function rehabilitation and neuro-prosthetic control in brain-machine interfaces.

Unexpected Terrain Induced Changes in Cortical Activity in Bipedal-Walking Rats.

Humans and other animals can quickly respond to unexpected terrains during walking, but little is known about the cortical dynamics in this process. To study the impact of unexpected terrains on brain activity, we allowed rats with blocked vision to walk on a treadmill in a bipedal posture and then walk on an uneven area at a random position on the treadmill belt. Whole brain EEG signals and hind limb kinematics of bipedal-walking rats were recorded. After encountering unexpected terrain, the θ band power of the bilateral M1, the γ band power of the left S1, and the θ to γ band power of the RSP significantly decreased compared with normal walking. Furthermore, when the rats left uneven terrain, the ß band power of the bilateral M1 and the α band power of the right M1 decreased, while the γ band power of the left M1 significantly increased compared with normal walking. Compared with the flat terrain, the θ to low ß (3-20 Hz) band power of the bilateral S1 increased after the rats contacted the uneven terrain and then decreased in the single- or double- support phase. These results support the hypothesis that unexpected terrains induced changes in cortical activity.

The lateralization of left hippocampal CA3 during the retrieval of spatial working memory.

The hippocampal CA3 contributes to spatial working memory (SWM), but which stage of SWM the CA3 neurons act on and whether the lateralization of CA3 function occurs in SWM is also unknown. Here, we reveal increased neural activity in both sample and choice phases of SWM. Left CA3 (LCA3) neurons show higher sensitivity in the choice phase during the correct versus error trials compared with right CA3 (RCA3) neurons. LCA3 initiates firing prior to RCA3 in the choice phase. Optogenetic suppression of pyramidal neurons in LCA3 disrupts SWM only in the choice phase. Furthermore, we discover that parvalbumin (PV) neurons, rather than cholinergic neurons in the medial septum (DB were cholinergic neurons), can project directly to unilateral CA3. Selective suppression of PV neurons in the MS projecting to LCA3 impairs SWM. The findings suggest that MSPV-LCA3 projection plays a crucial role in manipulating the lateralization of LCA3 in the retrieval of SWM.

A Robust Real-Time Detecting and Tracking Framework for Multiple Kinds of Unmarked Object.

A rodent real-time tracking framework is proposed to automatically detect and track multi-objects in real time and output the coordinates of each object, which combines deep learning (YOLO v3: You Only Look Once, v3), the Kalman Filter, improved Hungarian algorithm, and the nine-point position correction algorithm. A model of a Rat-YOLO is trained in our experiment. The Kalman Filter model is established in an acceleration model to predict the position of the rat in the next frame. The predicted data is used to fill the losing position of rats if the Rat-YOLO doesn't work in the current frame, and to associate the ID between the last frame and current frame. The Hungarian assigned algorithm is used to show the relationship between the objects of the last frame and the objects of the current frame and match the ID of the objects. The nine-point position correction algorithm is presented to adjust the correctness of the Rat-YOLO result and the predicted results. As the training of deep learning needs more datasets than our experiment, and it is time-consuming to process manual marking, automatic software for generating labeled datasets is proposed under a fixed scene and the labeled datasets are manually verified in term of their correctness. Besides this, in an off-line experiment, a mask is presented to remove the highlight. In this experiment, we select the 500 frames of the data as the training datasets and label these images with the automatic label generating software. A video (of 2892 frames) is tested by the trained Rat model and the accuracy of detecting all the three rats is around 72.545%, however, the Rat-YOLO combining the Kalman Filter and nine-point position correction arithmetic improved the accuracy to 95.194%.

Activation of the primary motor cortex using fully-implanted electrical sciatic nerve stimulation.

Functional degradation of the motor cortex usually results from brain injury, stroke, limb amputation, aging or other diseases. Currently, there are no ideal means of treatment, other than medication and sports rehabilitation. The present study investigated whether electrical stimulation of the sciatic nerve can activate the motor-related area of the brain. The study is based on a self-developed fully implantable nerve electrical stimulator and a self-developed multi-channel electroencephalogram (EEG) electrode array. The sciatic nerves of Sprague-Dawley rats (sorted into old and young groups) were stimulated by the electrical stimulator under anesthesia, and the EEG signal was recorded simultaneously. The relationship between sciatic nerve stimulation and brain activity was analyzed. The results showed that when the sciatic nerve was stimulated by the implanted electrical stimulator, motor-related channels were activated, causing contraction of the left leg. It was found that at the frequency band of 8-16 Hz, the EEG signal in the right motor area was higher than at other frequency bands. This phenomenon was identical in both young and old rats. The results indicated that electrical stimulation of the sciatic nerve can activate the motor region of the rat brain, and provided evidence that stimulation of the sciatic nerve could be a method of preventing motor cortex degeneration.

Tactile priming accelerates conscious access to continuous flash-suppressed characters.

NEW FINDINGS: What is the central question of this study? Research has reported that some sensory input, such as auditory and olfactory input, can affect subliminal visual processing. However, it is important to address whether tactile input, another form of elementary sensory input, could influence the interocular rivalry process. What is the main finding and its importance? We present several pieces of evidence regarding the influences of familiar tactile shapes and temperature on continuous flash suppression. Our findings provide support for the hypothesis that there is a cross-modal effect on subconscious visual semantic processing of Chinese characters. More specifically, tactile sensations affect subliminal processing of visual information. ABSTRACT: Tactile and visual sensations are the most vital human functions for obtaining environmental information. However, whether tactile information influences visual processing remains unclear. In this study, a breaking continuous flash suppression (b-CFS) protocol was used to measure the extent to which tactile sensations facilitate visual processing subconsciously. In experiment 1, finger stimulation with cold and hot temperatures served as primers for the words 'cold' and 'hot', which were in turn suppressed by CFS. In experiment 2, subjects viewed the upright or inverted word 'cell phone', with or without tactile priming of holding a cell phone in their hand. Results demonstrated that the tactile primer significantly shortened the reaction time in the touch group compared with the control group in both experiments. Thus, the tactile sensation of a familiar article and/or temperature appears to facilitate corresponding visual semantic recognition to break CFS earlier.

Decomposing single-channel intramuscular electromyography signal sampled at a low frequency into its motor unit action potential trains with a generative adversarial network.

Conventional methods decompose single-channel intramuscular electromyography (iEMG) signals into their constituent motor unit action potential trains (MUAPTs) by detecting and clustering individual motor unit action potentials (MUAPs). However, these methods are not applicable for iEMG signals recorded by electrodes with a large sensing areas or iEMG signals sampled at a low frequency, in which detecting and clustering individual MUAPs are difficult due to superimpositions of the MUAPs and the loss of MUAP morphological characteristics. In this study, we propose an approach based on a generative adversarial network to decompose iEMG signals, which does not depend on detecting and clustering individual MUAPs from the iEMG signal. The proposed approach decomposes the iEMG signal into its MUAPTs based on Bayes' law and a Wasserstein generative adversarial network with gradient penalty (WGAN-GP). MUAPTs generated by the WGAN-GP were used to decompose the iEMG signal to maximize the posterior probability of the generated MUAPTs given the iEMG signal. The accuracy of the proposed approach is analysed directly by decomposing the simulated iEMG signal with seven gold-standard motor units. The results showed that the proposed approach achieved a 53% accuracy in capturing the firing regularities of the MUs, while the conventional method achieved a 37% accuracy on the same task.

The effect of acute glutamate treatment on the functional connectivity and network topology of cortical cultures.

Microelectrode arrays (MEAs) allow the investigation of the pharmacological and toxicological effects of chemicals on cultured neuronal networks. Understanding the functional connections between neurons and the resulting neuronal networks is important for evaluating drugs that affect synaptic transmission. Therefore, we acutely treated a mature cultured neuronal network on MEAs with accumulating amounts of glutamate and recorded their altered electrophysiology. Subsequently, a cross-covariance analysis was applied to process the spiking activity in the network and to evaluate the connections between neurons. Finally, graph theory was used to assess the functional network properties under acute glutamate treatment. Our data demonstrated that glutamate increased the similarity, connectivity weight, density, and largest-component size of the functional network. In addition, the small-world network topology was altered after glutamate treatment. Our results indicate that the graph theory can advance our understanding of the pharmacological significance of neurotransmitters on neuronal networks.

sEMG-Based Hand-Gesture Classification Using a Generative Flow Model.

Conventional pattern-recognition algorithms for surface electromyography (sEMG)-based hand-gesture classification have difficulties in capturing the complexity and variability of sEMG. The deep structures of deep learning enable the method to learn high-level features of data to improve both accuracy and robustness of a classification. However, the features learned through deep learning are incomprehensible, and this issue has precluded the use of deep learning in clinical applications where model comprehension is required. In this paper, a generative flow model (GFM), which is a recent flourishing branch of deep learning, is used with a SoftMax classifier for hand-gesture classification. The proposed approach achieves 63.86 ± 5.12 % accuracy in classifying 53 different hand gestures from the NinaPro database 5. The distribution of all 53 hand gestures is modelled by the GFM, and each dimension of the feature learned by the GFM is comprehensible using the reverse flow of the GFM. Moreover, the feature appears to be related to muscle synergy to some extent.