Objectives. There is a significant correlation between EEG microstate and the neurophysiological basis of mental illness, brain state, cognitive function. Given that unclear relationship network dynamics different microstates, this paper utilized microstate, network, control theories to understand characteristics short-term memory task, aiming mechanistically explain most influential microstates regions driving abnormal changes in state transitions patients with schizophrenia. Methods. We...

Generally, an alcoholic's brain shows explicit damage. However, in cognitive tasks, the correlation between topological structural changes of networks and damage is still unclear. Scalp electrodes synchronization likelihoo

Abstract The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It important for community to realize that such open science effort must protect personal, especially facial information when raw data are shared. An ideal tool face anonymization should not disturb subsequent brain tissue extraction and further morphological measurements. Using high-resolution head images from magnetic resonance imaging (MRI) of 215 healthy Chinese, we...

With the continuous development of brain imaging technology, it has become a hot area neuroscience and information technology to research human emotion changes, cognitive status psychiatric disorders. In recent years, any smart device can be used as terminal sensor in Internet Things for interaction. It will new aspect Brain-Computer Interface(BCI) regard (the most intelligent "device") construct network based on brains (we name Brains). this paper, model wearable affective computing was...

Recognizing the emotion of text plays a key role in human-computer interaction. This paper established textual recognition model incorporating personality it. The defined series basic reasoning rules and revised it to user's on basis model. were built according OCC but simplified 22 emotional into 16 specific feature text. To include personal factor, analyzed each dimension FFM (five-factor model) modified based features dimension, then for different people. At end, using two experiments...

One aspect of difficult-to-cure neurological diseases is a lack or an anomaly the brain's overall local integration processing. When these work together, process referred to as synchronization phenomenon in neurobiological theory. By studying capabilities brain-network, we can intensively describe and characterize both state interactions between brain regions their differences people with mental illness set controls by measuring rapid changes activity patients psychiatric disorders strength...

The effective connectivity among overlapped core regions recruited by motor imagery (MI) was explored means of Granger causality and graph-theoretic method, based on Electroencephalography (EEG) data. In this paper, causal brain network (CCBN) proposed for the classification brain-Ccomputer interface applications, source analysis scalp-recorded EEGs networks. A rate about 90% achieved in human subject studied using both equivalent dipole granger analysis. present promising results suggest...

The effects of eccentricity on the attentional modulation visual discrimination have been widely studied; however, substrate this complex phenomenon is poorly understood. Here, we provided a measure three networks: alerting, orienting, and executive attention. Participants ( N = 63) were tested with modified attention network test that included an additional variation; allowed us to investigate efficiency networks at near far eccentricities. Compared targets eccentricity, generally elicited...

Policy evaluation with linear function approximation is an important problem in reinforcement learning. When facing high-dimensional feature spaces, such a becomes extremely hard considering the computation efficiency and quality of approximations. We propose new algorithm, LSTD(lambda)-RP, which leverages random projection techniques takes eligibility traces into consideration to tackle above two challenges. carry out theoretical analysis provide meaningful upper bounds estimation error,...

Abstract In this paper, the objective function is effectively optimized by improving fitness in computer algorithm. The improvement mainly focuses on adjusting weighting coefficients of completion time, load balance and execution cost. article then proceeds to optimize algorithm’s parameters based optimal parameterization criterion, designs a hybrid hill-climbing-simulated annealing optimization algorithm parameterized model. To verify safety algorithm, avalanche effect experiments were...

Embedded sensing devices that are battery-operated and resource-limited increasingly utilizing recurrent neural networks (RNNs) to attain real-time perception of the complex environment. Nevertheless, majority RNNs typically handle substantial amounts time-series data, resulting in computational intensity high energy consumption. Hence, development energy-efficient RNN models is a crucial focus. This paper introduces IS-RNN, an model featuring importance-based sparsification, aimed at...

Objective: This paper aims to prompt large language models (LLMs) for clinical temporal relation extraction (CTRE) in both few-shot and fully supervised settings. Materials Methods: study utilizes four LLMs: Encoder-based GatorTron-Base (345M)/Large (8.9B); Decoder-based LLaMA3-8B/MeLLaMA-13B. We developed full (FFT) parameter-efficient (PEFT) fine-tuning strategies evaluated these on the 2012 i2b2 CTRE task. explored GatorTron-Base: (1) Standard Fine-Tuning, (2) Hard-Prompting with Unfrozen...

Question Understanding of Chinese Question-Answering System generally includes steps such as: word segmentation, POS Tagging, keywords expansion, information retrieval etc. The extended keyword set usually has redundant messages and part the words phrases may be not relevant to question. Consequently, with bring about large numbers noise enhance difficulty answer pick-up. This paper explores use distance between vocabularies in sememe tree for reducing set. It analyzes detailed question...

Policy evaluation with linear function approximation is an important problem in reinforcement learning. When facing high-dimensional feature spaces, such a becomes extremely hard considering the computation efficiency and quality of approximations. We propose new algorithm, LSTD($\lambda$)-RP, which leverages random projection techniques takes eligibility traces into consideration to tackle above two challenges. carry out theoretical analysis provide meaningful upper bounds estimation error,...

People with schizophrenia often show deficits in recognizing facial emotions, which contributes to poor social functioning. In this experiment we directly investigated how 20 people being treated for categorized emotional faces. a control group of healthy who had no mental illness, happy faces were classified faster than sad faces, that is, there was positive classification advantage. However, phenomenon not present inverted Compared the group, more slowly, less accuracy, and without...