Rethinking Remapping: Circuit Mechanisms of Recovery after Stroke.

Stroke is one of the most common causes of disability, and there are few treatments that can improve recovery after stroke. Therapeutic development has been hindered because of a lack of understanding of precisely how neural circuits are affected by stroke, and how these circuits change to mediate recovery. Indeed, some of the hypotheses for how the CNS changes to mediate recovery, including remapping, redundancy, and diaschisis, date to more than a century ago. Recent technological advances have enabled the interrogation of neural circuits with ever greater temporal and spatial resolution. These techniques are increasingly being applied across animal models of stroke and to human stroke survivors, and are shedding light on the molecular, structural, and functional changes that neural circuits undergo after stroke. Here we review these studies and highlight important mechanisms that underlie impairment and recovery after stroke. We begin by summarizing knowledge about changes in neural activity that occur in the peri-infarct cortex, specifically considering evidence for the functional remapping hypothesis of recovery. Next, we describe the importance of neural population dynamics, disruptions in these dynamics after stroke, and how allocation of neurons into spared circuits can restore functionality. On a more global scale, we then discuss how effects on long-range pathways, including interhemispheric interactions and corticospinal tract transmission, contribute to post-stroke impairments. Finally, we look forward and consider how a deeper understanding of neural circuit mechanisms of recovery may lead to novel treatments to reduce disability and improve recovery after stroke.

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synaptic efflux of neurochemicals in vivo, principal component regression (PCR), has been commonly used to predict the identity and concentrations of neurotransmitters. However, the sensitivity and discrimination performance of PCR have room for improvement, especially for analyzing mixtures of similar oxidizable neurochemicals. Deep learning may be able to address these challenges. To date, there have been a few studies to apply machine learning to FSCV, but no attempt to apply deep learning to neurotransmitter mixture discrimination and no comparative study have been performed between PCR and deep learning methods to demonstrate which is more accurate for FSCV analysis so far. In this study, we compared the neurochemical identification and concentration estimation performance of PCR and deep learning in an analysis of FSCV recordings of catecholamine and indolamine neurotransmitters. Both analysis methods were tested on in vitro FSCV data with a single or mixture of neurotransmitters at the desired concentration. In addition, the estimation performance of PCR and deep learning was compared in incorporation with in vivo experiments to evaluate the practical usage. Pharmacological tests were also conducted to see whether deep learning would track the increased amount of catecholamine levels in the brain. Using conventional FSCV, we used five electrodes and recorded in vitro background-subtracted cyclic voltammograms from four neurotransmitters, dopamine, epinephrine, norepinephrine, and serotonin, with five concentrations of each substance, as well as various mixtures of the four analytes. The results showed that the identification accuracy errors were reduced 5-20% by using deep learning compared to using PCR for mixture analysis, and the two methods were comparable for single analyte analysis. The applied deep-learning-based method demonstrated not only higher identification accuracy but also better discrimination performance than PCR for mixtures of neurochemicals and even for in vivo testing. Therefore, we suggest that deep learning should be chosen as a more reliable tool to analyze FSCV data compared to conventional PCR methods although further work is still needed on developing complete validation procedures prior to widespread use.

Non-human primate epidural ECoG analysis using explainable deep learning technology.

Objective.With the development in the field of neural networks,explainable AI(XAI), is being studied to ensure that artificial intelligence models can be explained. There are some attempts to apply neural networks to neuroscientific studies to explain neurophysiological information with high machine learning performances. However, most of those studies have simply visualized features extracted from XAI and seem to lack an active neuroscientific interpretation of those features. In this study, we have tried to actively explain the high-dimensional learning features contained in the neurophysiological information extracted from XAI, compared with the previously reported neuroscientific results.Approach. We designed a deep neural network classifier using 3D information (3D DNN) and a 3D class activation map (3D CAM) to visualize high-dimensional classification features. We used those tools to classify monkey electrocorticogram (ECoG) data obtained from the unimanual and bimanual movement experiment.Main results. The 3D DNN showed better classification accuracy than other machine learning techniques, such as 2D DNN. Unexpectedly, the activation weight in the 3D CAM analysis was high in the ipsilateral motor and somatosensory cortex regions, whereas the gamma-band power was activated in the contralateral areas during unimanual movement, which suggests that the brain signal acquired from the motor cortex contains information about both contralateral movement and ipsilateral movement. Moreover, the hand-movement classification system used critical temporal information at movement onset and offset when classifying bimanual movements.Significance.As far as we know, this is the first study to use high-dimensional neurophysiological information (spatial, spectral, and temporal) with the deep learning method, reconstruct those features, and explain how the neural network works. We expect that our methods can be widely applied and used in neuroscience and electrophysiology research from the point of view of the explainability of XAI as well as its performance.

Right Hemisphere Lateralization in Neural Connectivity Within Fronto-Parietal Networks in Non-human Primates During a Visual Reaching Task.

A fronto-parietal network, comprised of the posterior parietal cortex (PPC) and the dorsal premotor cortex (PMd) has been proposed to be involved in planning and guiding movement. However, the issue of how the network is expressed across the bilateral cortical area according to the effector's side remains unclear. In this study, we tested these questions using electrocorticographic (ECoG) recordings in non-human primates and using a simple visual guided reaching task that induced a left or right hand response based on relevant cues provided for the task. The findings indicate that right hemisphere lateralized network patterns in which the right PMd was strongly coordinated with bilateral PPC immediately after presentation of the movement cue occurred, while the coherence with the left PMd was not enhanced. No difference was found in the coherence pattern between the effector's side (left hand or right hand), but the strength of coherence was different, in that animals showed a higher coherence in the right hand response compared to the left. Our data support that right lateralization in long-range phase synchrony in the 10-20 Hz low beta band is involved in motor preparation stage, irrespective of the upcoming effector's side.

Long-term evaluation and feasibility study of the insulated screw electrode for ECoG recording.

BACKGROUND: A screw-shaped electrode can offer a compromise between signal quality and invasiveness. However, the standard screw electrode can be vulnerable to electrical noise while directly contact with the skull or skin, and the feasibility and stability for chronic implantation in primate have not been fully evaluated. NEW METHOD: We designed a novel screw electrocorticogram (ECoG) electrode composed of three parts: recording electrode, insulator, and nut. The recording electrode was made of titanium with high biocompatibility and high electrical conductivity. Zirconia is used for insulator and nut to prevent electrical noise. RESULT: In computer simulations, the screw ECoG with insulator showed a significantly higher performance in signal acquisition compared to the condition without insulator. In a non-human primate, using screw ECoG, clear visual-evoked potential (VEP) waveforms were obtained, VEP components were reliably maintained, and the electrode's impedance was stable during the whole evaluation period. Moreover, it showed higher SNR and wider frequency band compared to the electroencephalogram (EEG). We also observed the screw ECoG has a higher sensitivity that captures different responses on various stimuli than the EEG. COMPARISON: The screw ECoG showed reliable electrical characteristic and biocompatibility for three months, that shows great promise for chronic implants. These results contrasted with previous reports that general screw electrode was only applicable for acute applications. CONCLUSION: The suggested electrode can offer whole-brain monitoring with high signal quality and minimal invasiveness. The screw ECoG can be used to provide more in-depth understanding, not only relationship between functional networks and cognitive behavior, but also pathomechanisms in brain diseases.

Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates.

OBJECTIVE: In arm movement BCIs (brain-computer interfaces), unimanual research has been much more extensively studied than its bimanual counterpart. However, it is well known that the bimanual brain state is different from the unimanual one. Conventional methodology used in unimanual studies does not take the brain stage into consideration, and therefore appears to be insufficient for decoding bimanual movements. In this paper, we propose the use of a two-staged (effector-then-trajectory) decoder, which combines the classification of movement conditions and uses a hand trajectory predicting algorithm for unimanual and bimanual movements, for application in real-world BCIs. APPROACH: Two micro-electrode patches (32 channels) were inserted over the dura mater of the left and right hemispheres of two rhesus monkeys, covering the motor related cortex for epidural electrocorticograph (ECoG). Six motion sensors (inertial measurement unit) were used to record the movement signals. The monkeys performed three types of arm movement tasks: left unimanual, right unimanual, bimanual. To decode these movements, we used a two-staged decoder, which combines the effector classifier for four states (left unimanual, right unimanual, bimanual movements, and stationary state) and movement predictor using regression. MAIN RESULTS: Using this approach, we successfully decoded both arm positions using the proposed decoder. The results showed that decoding performance for bimanual movements were improved compared to the conventional method, which does not consider the effector, and the decoding performance was significant and stable over a period of four months. In addition, we also demonstrated the feasibility of epidural ECoG signals, which provided an adequate level of decoding accuracy. SIGNIFICANCE: These results provide evidence that brain signals are different depending on the movement conditions or effectors. Thus, the two-staged method could be useful if BCIs are used to generalize for both unimanual and bimanual operations in human applications and in various neuro-prosthetics fields.

Decoding Saccadic Directions Using Epidural ECoG in Non-Human Primates.

A brain-computer interface (BCI) can be used to restore some communication as an alternative interface for patients suffering from locked-in syndrome. However, most BCI systems are based on SSVEP, P300, or motor imagery, and a diversity of BCI protocols would be needed for various types of patients. In this paper, we trained the choice saccade (CS) task in 2 non-human primate monkeys and recorded the brain signal using an epidural electrocorticogram (eECoG) to predict eye movement direction. We successfully predicted the direction of the upcoming eye movement using a support vector machine (SVM) with the brain signals after the directional cue onset and before the saccade execution. The mean accuracies were 80% for 2 directions and 43% for 4 directions. We also quantified the spatial-spectro-temporal contribution ratio using SVM recursive feature elimination (RFE). The channels over the frontal eye field (FEF), supplementary eye field (SEF), and superior parietal lobule (SPL) area were dominantly used for classification. The α-band in the spectral domain and the time bins just after the directional cue onset and just before the saccadic execution were mainly useful for prediction. A saccade based BCI paradigm can be projected in the 2D space, and will hopefully provide an intuitive and convenient communication platform for users.

Rapid Detection of Glycogen Synthase Kinase-3 Activity in Mouse Sperm Using Fluorescent Gel Shift Electrophoresis.

Assaying the glycogen synthase kinase-3 (GSK3) activity in sperm is of great importance because it is closely implicated in sperm motility and male infertility. While a number of studies on GSK3 activity have relied on labor-intensive immunoblotting to identify phosphorylated GSK3, here we report the simple and rapid detection of GSK3 activity in mouse sperm using conventional agarose gel electrophoresis and a fluorescent peptide substrate. When a dye-tethered and prephosphorylated (primed) peptide substrate for GSK3 was employed, a distinct mobility shift in the fluorescent bands on the agarose was observed by GSK3-induced phosphorylation of the primed peptides. The GSK3 activity in mouse testes and sperm were quantifiable by gel shift assay with low sample consumption and were significantly correlated with the expression levels of GSK3 and p-GSK3. We suggest that our assay can be used for reliable and rapid detection of GSK3 activity in cells and tissue extracts.

Sequential phosphorylation analysis using dye-tethered peptides and microfluidic isoelectric focusing electrophoresis.

We report a simple method for analyzing sequential phosphorylation by protein kinases using fluorescent peptide substrates and microfluidic isoelectric focusing (µIEF) electrophoresis. When a dye-labeled peptide substrate was sequentially phosphorylated by two consecutive protein kinases (mitogen-activated protein kinase (MAPK) and glycogen synthase kinase 3 (GSK3)), its differently phosphorylated forms were easily separated and visualized by fluorescent focusing zones in the µIEF channel based on a change in the isoelectric point (pI) by phosphorylation. As a result, ratiometric and quantitative analysis of the fluorescent focusing regions shifted by phosphorylation enabled the analysis of phosphorylation efficiency and the relevant inhibition of protein kinases (MAPK and GSK3) with high simplicity and selectivity. Furthermore, the GSK3 activity in the cell lysates was elucidated by µIEF electrophoresis in combination with immunoprecipitation. Our results suggest that this method has great potential for analyzing the sequential phosphorylation of multiple protein kinases that are implicated in cellular signaling pathways.

A thin film polyimide mesh microelectrode for chronic epidural electrocorticography recording with enhanced contactability.

OBJECTIVE: Epidural electrocorticography (ECoG) activity may be more reliable and stable than single-unit-activity or local field potential. Invasive brain computer interface (BCI) devices are limited by mechanical mismatching and cellular reactive responses due to differences in the elastic modulus and the motion of stiff electrodes. We propose a mesh-shaped electrode to enhance the contactability between surface of dura and electrode. APPROACH: We designed a polyimide (PI) electrode with a mesh pattern for more conformal contact with a curved surface. We compared the contact capability of mesh PI electrodes with conventionally used sheet PI electrode. The electrical properties of the mesh PI electrode were evaluated for four weeks. We recorded the epidural ECoG (eECoG) activity on the surface of rhesus monkey brains while they performed a saccadic task for four months. MAIN RESULTS: The mesh PI electrode showed good contact with the agarose brain surface, as evaluated by visual inspection and signal measurement. It was about 87% accurate in predicting the direction of saccade eye movement. SIGNIFICANCE: Our results indicate that the mesh PI electrode was flexible and good contact on the curved surface and can record eECoG activity maintaining close contact to dura, which was proved by in vivo and in vitro test.

Solitary metastasis of gastric carcinoma to the cerebellopontine angle.

Internal auditory canal (IAC) and cerebellopontine metastases are very rare lesions and their diagnosis is very difficult due to their similarity to vestibular schwannoma in clinical characteristics and radiologic findings. Our case is peculiar and differs from previously reported cases of malignant metastasis to the IAC in two aspects: 1) solitary IAC metastasis occurred without distant metastasis and 2) symptoms due to IAC metastasis preceded outbreak of primary lesion symptoms or diagnosis of primary lesion. In our literature search, no correlating cases have been reported. In this peculiar case, rapid progression of otologic symptoms, short duration of onset from hearing impairment to facial palsy, and laterally eccentric contrast enhancement in gadolinium-enhanced T1-weighted magnetic resonance imaging may have been clues for metastatic lesion.

Huge middle ear adenoma with delayed facial nerve paralysis.

Middle ear adenoma is a rare disease that arises from the mucosa of the middle ear. Only a few cases of associated facial nerve paralysis have been reported. Facial nerve involvement is most likely related to nerve compression rather than tumor invasion of the nerve. We describe a case of a huge middle ear adenoma in a 63-year-old man. He presented with a 1-month history of right-sided otalgia, otorrhea, and facial palsy; he also had a 10-year history of right-sided hearing loss. A tympanomastoidectomy was performed. Intraoperatively, the tumor was found to fill the middle ear cavity as well as the entire diameter of the external auditory canal. The tumor had eroded the wall of the facial canal at the second genu, and it was tightly adherent to the epineurium. Focal inflammation around the tumor was observed at the exposed facial nerve. The tumor was removed and the facial nerve was decompressed. Immediately after surgery, the patient's aural symptoms resolved. The final pathology evaluation established the diagnosis of a middle ear adenoma. At the 3-year follow-up, the ear cavity was completely healed and facial nerve function was improved.

Benign paroxysmal positional vertigo is not a prognostic factor in sudden sensorineural hearing loss.

OBJECTIVE: Little is known concerning the role of benign paroxysmal positional vertigo (BPPV) as a prognostic factor for sudden sensorineural hearing loss (SSNHL). The purpose of this study is to analyze the hearing recovery in patients who have SSNHL with BPPV compared with those who have SSNHL without BPPV. The study also documented the relative incidence of each semicircular canal involvement. STUDY DESIGN: Case-control study. SETTING: Academic tertiary otologic practice. SUBJECTS AND METHODS: Ninety patients diagnosed with SSNHL with vertigo were enrolled. Clinical characteristics such as gender, age, and pure tone audiogram threshold were compared between group A (SSNHL with BPPV, n = 17) and group B (SSNHL without BPPV, n = 73). The frequency of each canal involvement was compared between group A and another 111 patients with BPPV only (group C). The proportion of patients with hearing recovery was compared between patients with or without BPPV, and between those with or without canal paresis. RESULTS: Patients in group A did not display significant differences in the sex ratio, mean age, or initial results of pure tone audiogram threshold compared with those in group B. Most patients with SSNHL with BPPV had lateral canal canalithiasis (64.7%). The presence of BPPV had no influence on the recovery of hearing. CONCLUSIONS: The clinical characteristics of patients with SSNHL with BPPV were not different from those with SSNHL without BPPV. The lateral canal was the most frequently involved, and the presence or absence of BPPV had no dramatic impact on the outcome of SSNHL.

Recurrence of vertigo in patients with vestibular neuritis.

UNLABELLED: CONCLUSION. The recurrence rate of vertigo due to any cause in patients with vestibular neuritis (VN) was about 26.0% in our study. No clinical characteristics were significantly associated with recurrences. OBJECTIVE: We aimed to: 1) determine the prevalence of recurrent VN; 2) compare the clinical characteristics and epidemiologic factors of patients with non-recurrent and recurrent VN; and 3) determine the prevalence of benign paroxysmal positional vertigo (BPPV) in patients with VN. METHODS: In 131 patients diagnosed as having VN (68 males, aged 49.8 ± 14.9 years and 63 females, aged 57.5 ± 12.5 years), a retrospective chart review and telephone survey about the recurrent vertigo were performed. Vestibular function testing, inner ear magnetic resonance imaging (MRI), and pure tone audiograms were performed on every patient. Vestibular function testing was repeated in patients with recurrences. RESULTS: Fourteen of 131 patients (10.7%) had recurrent VN. The subjective intensity of recurrent VN was less than the first attack. There were no significant differences in clinical characteristics such as accompanying headache or preceding respiratory infection and in epidemiologic risk factors between patients with recurrent and non-recurrent VN. Twenty of 131 patients (15.3%) experienced BPPV during the follow-up period.