Networks of fast-spiking interneurons are crucial for the generation neural oscillations in brain. Here we study synchronous behavior interneuronal networks that coupled by delayed inhibitory and fast electrical synapses. We find both coupling modes play a role synchronization network. In addition, synapses affect emerging oscillatory patterns. By increasing synaptic delay, observe transition from regular to mixed patterns at critical value. also examine how unreliability influences...

Abstract Soft neural electrode arrays that are mechanically matched between tissues and electrodes offer valuable opportunities for the development of disease diagnose brain computer interface systems. Here, a thermal release transfer printing method fabrication stretchable bioelectronics, such as soft arrays, is presented. Due to large, switchable irreversible change in adhesion strength tape, low‐cost, easy‐to‐operate, temperature‐controlled process can be achieved. The mechanism this...

P300 is an important event-related potential that can be elicited by external visual, auditory, and somatosensory stimuli. Various cognition-related brain functions (i.e., attention, intelligence, working memory) multiple regions prefrontal, frontal, parietal) are reported to involved in the elicitation of P300. However, these studies do not investigate instant interactions across neural cortices from hierarchy milliseconds. Importantly, time-varying network analysis among uncover detailed...

Abstract The P3 is an important event-related potential that can be used to identify neural activity related the cognitive processes of human brain. However, relationships, especially functional correlations, between resting-state brain and have not been well established. In this study, we investigated relationships properties (i.e., amplitude latency) networks. results indicated was significantly correlated with network topology in general, larger amplitudes could evoked when more...

Absence epilepsy is believed to be associated with the abnormal interactions between cerebral cortex and thalamus. Besides direct coupling, anatomical evidence indicates that thalamus also communicate indirectly through an important intermediate bridge--basal ganglia. It has been thus postulated basal ganglia might play key roles in modulation of absence seizures, but relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here...

A new method for steady-state visual evoked potentials (SSVEPs) frequency recognition is proposed to enhance the performance of SSVEP-based brain-computer interface (BCI). Correlated component analysis (CORCA) introduced, which originally was designed find linear combinations electrodes that are consistent across subjects and maximally correlated between them. We propose a CORCA algorithm learn spatial filters with multiple blocks individual training data BCI scenario. The used remove...

Fast-spiking (FS) interneurons in the brain are self-innervated by powerful inhibitory GABAergic autaptic connections. By computational modelling, we investigate how inhibition regulates firing response of such interneurons. Our results indicate that both boosts current threshold for action potential generation and modulates input-output gain FS The transmission delay is identified as a key parameter controls patterns determines multistability regions Furthermore, observe neuronal noise...

The relationships between noise and complex dynamic behaviors of neuronal ensembles are key questions in computational neuroscience, particularly understanding some basic signal transmission mechanisms the brain. Here we systemically investigate both stochastic resonance (SR) coherence (CR) triple-neuron feed-forward-loop (FFL) network motifs by modeling. We use Izhikevich neuron model as well chemical coupling to build FFL motifs, consider all possible motif types. simulation results...

A canonical correlation analysis (CCA) is a state-of-the-art method for frequency recognition in steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) systems. Various extended methods have been developed, and among such methods, combination of CCA individual-template-based has achieved the best performance. However, requires vectors to be orthogonal, which may not reasonable assumption EEG analysis. In this paper, we propose using correlated component (CORRCA)...

Abstract The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates coupling, we here show self-innervation neurons participates the modulation irregular neuronal firing, primarily by regulating occurrence frequency burst firing. In particular, find both excitatory and electrical autapses increase thus reducing firing regularity. contrast, inhibitory suppress therefore tend to improve...

Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is fundamental importance for information processing in brain. Here we study neural systems weak envelope modulation signal, which superimposed by two periodic with different frequencies. We show that stochastic resonance occurs at beat frequency single-neuron as well population level. The performance this frequency-difference-dependent influenced both forcing...

The basal ganglia (BG), serving as an intermediate bridge between the cerebral cortex and thalamus, are believed to play crucial roles in controlling absence seizure activities generated by pathological corticothalamic system. Inspired recent experiments, here we systematically investigate contribution of a novel identified GABAergic pallido-cortical pathway, projecting from globus pallidus externa (GPe) BG cortex, control seizures. By computational modelling, find that both increasing...

Noise is an inherent part of neuronal dynamics, and thus the brain.It can be observed in activity at different spatiotemporal scales, including membrane potentials, local field electroencephalography, magnetoencephalography.A central research topic contemporary neuroscience to elucidate functional role noise information processing.Experimental studies have shown that a suitable level may enhance detection weak signals by means stochastic resonance.In response, theoretical research, based on...

The prediction of brain-computer interface (BCI) performance is a significant topic in the BCI field. Some researches have demonstrated that resting-state data are promising candidates to achieve goal. However, so far relationships between networks and steady-state visual evoked potential (SSVEP)-based not been investigated. In this paper, we investigate possible SSVEP responses, classification accuracy five stimulus frequencies closed-eye network topology.The functional connectivity...

Abstract The phenomenal finding that listening to Mozart K.448 enhances performance on spatial tasks has motivated a continuous surge in promoting music education over the past two decades. But there have been inconsistent reports previous studies of effect. Here conducted was systematic study, with and retrograde music, rhythm pitch, behaviours neurobiology tests, rats humans subjects. We show while positive cognitive effects, version negative effect rats’ Morris water maze test human...

Spiking neural networks (SNNs) mimic brain computational strategies, and exhibit substantial capabilities in spatiotemporal information processing. As an essential factor for human perception, visual attention refers to the dynamic process selecting salient regions biological vision systems. Although mechanisms have achieved great success computer applications, they are rarely introduced into SNNs. Inspired by experimental observations on predictive attentional remapping, we propose a new...

Loneliness is broadly described as a negative emotional response resulting from the differences between actual and desired social relations of an individual, which related to neural responses in connection with stimuli. Prior research has discovered that some regions play role loneliness. However, little known about among individuals loneliness relationship those networks. The current study aimed investigate individual perceived causal interactions resting-state networks (RSNs), including...

Spiking neural networks (SNNs) have demonstrated excellent capabilities in various intelligent scenarios. Most existing methods for training SNNs are based on the concept of synaptic plasticity; however, learning realistic brain also utilizes intrinsic non-synaptic mechanisms neurons. The spike threshold biological neurons is a critical neuronal feature that exhibits rich dynamics millisecond timescale and has been proposed as an underlying mechanism facilitates information processing. In...

The imaging quality of single-pixel spectral (SSI) methods is poor at a low sampling ratio (SR). To tackle this problem, new Fourier (FSSI) technique proposed. Firstly, we introduce the low-rank tensor nuclear norm (TNN) to characterize correlation between images. Compared with conventional method, TNN reconstructs image details better but brings artifacts simultaneously. Therefore, local (LTNN) constraint proposed ameliorate global ones and reduce distortion caused by SR. Secondly, make...

Abstract Over the past decade, digital twin brain (DTB) has emerged as a transformative science paradigm, integrating multimodal data to construct dynamic models closely simulating biological function. This approach advanced understanding of structure–function relationships, cognitive behaviors, and disease mechanisms, while supporting personalized therapies. Recent progress highlights DTB’s potential in capturing functional heterogeneity, information integration, predicting individual...