Spike recorded by multi-channel microelectrode array is very weak and susceptible to interference, whose noisy characteristic affects the accuracy of spike detection. Aiming at the independent white noise, correlation noise and colored noise in the process of spike detection, combining principal component analysis (PCA), wavelet analysis and adaptive time-frequency analysis, a new denoising method (PCWE) that combines PCA-wavelet (PCAW) and ensemble empirical mode decomposition is proposed. Firstly, the principal component was extracted and removed as correlation noise using PCA. Then the wavelet-threshold method was used to remove the independent white noise. Finally, EEMD was used to decompose the noise into the intrinsic modal function of each layer and remove the colored noise. The simulation results showed that PCWE can increase the signal-to-noise ratio by about 2.67 dB and decrease the standard deviation by about 0.4 μV, which apparently improved the accuracy of spike detection. The results of measured data showed that PCWE can increase the signal-to-noise ratio by about 1.33 dB and reduce the standard deviation by about 18.33 μV, which showed its good denoising performance. The results of this study suggests that PCWE can improve the reliability of spike signal and provide an accurate and effective spike denoising new method for the encoding and decoding of neural signal.
ObjectiveTo analyze the risk factors for electrical status epilepticus during sleep (ESES) in patients with self-limited epilepsy with centrotemporal spikes (SeLECTs) and to construct a nomogram model. MethodsThis study selected 174 children with SeLECTs who visited the Third Affiliated Hospital of Zhengzhou University from March 2017 to March 2024 and had complete case data as the research subjects. According to the results of video electroencephalogram monitoring during the course of the disease, the children were divided into non-ESES group (88 cases) and ESES group (86 cases). Multivariate logistic regression analysis was used to identify the risk factors for the occurrence of ESES in SeLECTs patients. ResultsThe multifactor Logistic regression analysis demonstrated that the EEG discharges in bilateral cerebral areas,types of seizure, epileptic seizures after initial treatment were the independent risk factors for the occurrence of ESES in SeLECTs. ConclusionBilateral distribution of electroencephalogram discharges before treatment, emergence of new seizure forms, and epileptic seizures after initial treatment are risk factors for the ESES in SeLECTs patients. The nomogram model constructed based on the above risk factors has a high degree of accuracy.
Transcranial magneto-acoustical stimulation (TMAS), utilizing focused ultrasound and a magnetostatic field to generate an electric current in tissue fluid to regulate the activities of neurons, has high spatial resolution and penetration depth. The neuronal spike-frequency adaptation plays an important role in the treatment of neural information. In this paper, we study the effects of ultrasonic intensity, magnetostatic field intensity and ultrasonic frequency on the neuronal spike-frequency adaptation based on the Ermentrout neuron model. The simulation results show that, the peak time interval becomes smaller, the interspike interval becomes shorter and the time of the firing of the neuron is shortened with the increasing of the magnetostatic field intensity. With the increase of the adaptive variables, the initial spike-frequency is shifted to the right with the magnetostatic field intensity, and the spike-frequency is linearly related to the increase of the magnetostatic field intensity in steady state. The simulation effect with change of the ultrasonic intensity is consistent with the change of magnetostatic field intensity. The change of the ultrasonic frequency has no effect on the neuronal spike-frequency adaptation. Under the different adaptive variables, with the increase of the adaptive variables, the initial spike-frequency amplitude decreased with the increasing of the ultrasonic frequency, and the spike-frequency is linearly related to the increase of the ultrasonic frequency in steady state. These results of the study can help us to reveal the mechanism of transcranial magneto-acoustical stimulation on the neuronal spike-frequency adaptation, and provide a theoretical basis for its application in the treatment of neurological disorders.
The rapid development of artificial intelligence put forward higher requirements for the computational speed, resource consumption and the biological interpretation of computational neuroscience. Spiking neuron networks can carry a large amount of information, and realize the imitation of brain information processing. However, its hardware is an important way to realize its powerful computing ability, and it is also a challenging technical problem. The memristor currently is the electronic devices that functions closest to the neuron synapse, and able to respond to spike voltage in a highly similar spike timing dependent plasticity (STDP) mechanism with a biological brain, and has become a research hotspot to construct spiking neuron networks hardware circuit in recent years. Through consulting the relevant literature at home and abroad, this paper has made a thorough understanding and introduction to the research work of the spiking neuron networks based on the memristor in recent years.
The phase-locking relationship between the firings of neuronal action potentials (i.e., spikes) and the oscillations of local field potentials (LFP) reflects important neural coding information. However, the present analysis methods can only determine whether there has phase-locking, but not the different strengths among various types of phase-locking. In the present paper, we used spike-triggered average (STA) signals and the percentage ratio (named φ) of the STA power to the power of original LFP as an index to evaluate the strengths of phase-locking. Experimental recordings obtained from rat hippocampal CA1 region as well as simulation data were used to evaluate the method. The results showed that the index φ changed monotonically as a function of the strength of phase-locking, and it could provide an effective critical value to divide phase-locking from non-phase-locking. Because the calculation of the index does not need pre-filtering, it can avoid the unwanted influences caused by intentionally limiting the frequencies of LFP oscillations such as in the traditional bin statistical method. Therefore, the index φ provides a novel method to investigate the mechanisms underlying neuronal coding in brain.
ObjectivesTo explore the characteristics of cognitive deficits of Benign epilepsy of childhood with centrotemporal spikes (BECTS).MethodsA total of 61 BECTS patients who visited Neurology Clinic of Xuanwu Hospital Capital Medical University between September 2010 to December 2019 and 60 healthy controls were enrolled in our study. All patients and healthy controls performed a series of neuropsychological tests to assess their cognitive function in the "Multi-dimensional psychology" of Beijing Normal University, including attention; memory; arithmetic calculation; language processing; executive function; visuospatial processing; visual perception; psychomotor speed. Lastly, independent sample t-test and friedman test were performed on the scores of BECTS group and controls using SPSS 20.0 and we conducted a multi-factor comprehensive analysis of correlation between clinical criteria and cognitive dysfunction in BECTS.ResultsCompared with 60 healthy controls, the as group got an average score of 19.56±2.91 in Paired Association Learning Test (P<0.001), (23.67±9.50) in Word Discrimination Test (P=0.017), (61.45±13.14) in Object Quantity Perception Task (P=0.040), (6.54±1.47) in Digit Span Test (P<0.001), (5.79±5.90) in Vocal Perception Test (P<0.001), (35.10±2.33) in Taylor Complex Figure Test (P<0.001) and (700.34±493.053) (P=0.008) in Choice Reaction Time Test. The results of these tests are inferior to the control group and the remaining 10 tests are of no statistical significance. There were 36 children with onset of seizure before 8 years of age. Compared with the patients experienced onset of illness at a later age, the 36 patients exhibited lower scores in most of the neuropsychological tests including Visual Tracking Task, Spatial Memory Task, Simple Subtraction Task, Number Comparison Test, Language Rhyme Test, Word Discrimination Testand Visual Perception Task (P<0.05). 34 patients received monotherapy, and 27 received a combination of 2 or 3 anti-epileptic drugs. The scores of attention, memory, visual perception and reaction tests in the multi drug treatment group were lower than those in the single drug treatment group (P<0.05).ConclusionsChildren with BECTS have impairment in attention, vocal perception, visual perception, memory and psychomotor speed. The younger the age of onset, the more severe the cognitive impairments. The degree of cognitive deficitsinchildren treated with multi drugs was more serious than that of children treated with single drugs.
Anti-seizure medications (ASMs) are the most important and basic treatment for epilepsy, and are also the first choice for epilepsy treatment, but about one-third of patients have drug resistance. Perampanel (PER), as a novel third generation ASMs, inhibits the α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor (AMPAR) through non-competitive inhibition. AMPA plays an anti-seizure role. Since its approval in China in 2021, it has been mainly used in the treatment of focal epilepsy (with or without general seizure) as a single drug or addition, and has good safety, effectiveness and tolerability. Self-limited epilepsy with centrotemporal spikes (SeLECTS) is a common childhood focal epilepsy syndrome, accounting for 15% ~ 25% of various childhood epilepsies, PER has important advantages in clinical studies and has shown certain curative effect. At the same time, the overall effect of PER on cognition was neutral, with no systemic cognitive deterioration or improvement. In view of the relatively short application time of PER, which is still a new drug, this article will review the mechanism of action, dose, add-on (single drug) treatment, adverse events and, in order to provide clinicians with more drug choices and facilitate the individualized diagnosis and treatment of epilepsy.
The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.
Recently a COVID-19 pneumonia pandemic caused by a novel coronavirus 2019-nCoV has broken out over the world. In order to better control the spread of the pandemic, there’s an urgent need to extensively study the virus’ origin and the mechanisms for its infectivity and pathogenicity. Spike protein is a special structural protein on the surface of coronavirus. It contains important information about the evolution of the virus and plays critical roles in the processes of cellular recognition and entry. In the past decades, spike protein has always been one of the most important objects in research works on coronaviruses closely related to human life. In this review we introduce these research works related to spike proteins, hoping it will provide reasonable ideas for the control of the current pandemic, as well as for the diagnosis and treatment of COVID-19.
Both spike and local field potential (LFP) signals are two of the most important candidate signals for neural decoding. At present there are numerous studies on their decoding performance in mammals, but the decoding performance in birds is still not clear. We analyzed the decoding performance of both signals recorded from nidopallium caudolaterale area in six pigeons during the goal-directed decision-making task using the decoding algorithm combining leave-one-out and k-nearest neighbor (LOO-kNN). And the influence of the parameters, include the number of channels, the position and size of decoding window, and the nearest neighbor k value, on the decoding performance was also studied. The results in this study have shown that the two signals can effectively decode the movement intention of pigeons during the this task, but in contrast, the decoding performance of LFP signal is higher than that of spike signal and it is less affected by the number of channels. The best decoding window is in the second half of the goal-directed decision-making process, and the optimal decoding window size of LFP signal (0.3 s) is shorter than that of spike signal (1 s). For the LOO-kNN algorithm, the accuracy is inversely proportional to the k value. The smaller the k value is, the larger the accuracy of decoding is. The results in this study will help to parse the neural information processing mechanism of brain and also have reference value for brain-computer interface.