Controlling Alzheimer's disease by deep brain stimulation based on a data-driven cortical network model.

This work aims to explore the control effect of DBS on Alzheimer's disease (AD) from a neurocomputational perspective. Firstly, a data-driven cortical network model is constructed using the Diffusion Tensor Imaging data. Then, a typical electrophysiological feature of EEG slowing in AD is reproduced by reducing the synaptic connectivity parameters.

A dynamic computational model of the parallel circuit on the basal ganglia-cortex associated with Parkinson's disease dementia.

The cognitive impairment will gradually appear over time in Parkinson's patients, which is closely related to the basal ganglia-cortex network. This network contains two parallel circuits mediated by putamen and caudate nucleus, respectively. Based on the biophysical mean-field model, we construct a dynamic computational model of the parallel circuit in the basal ganglia-cortex network associated with Parkinson's disease dementia.

Characteristics and Degradation Mechanisms under High Reverse Base-Collector Bias Stress in InGaAs/InP Double HBTs.

In this paper, the reliability of InP/InGaAs DHBTs under high reverse base-collector bias stress is analyzed by experiments and simulation. The DC characteristics and S parameters of the devices under different stress times were measured, and the key parameters with high field stress were also extracted to fully understand and analyze the high-field degradation mechanism of devices. The measurements indicate that the high-field stress leads to an increase in base current, an increase in base-collector (B-C) and base-emitter (B-E) junction leakage current, and a decrease in current gain, and different degrees of degradation of key parameters over stress time.

An Aging Small-Signal Model for Degradation Prediction of Microwave Heterojunction Bipolar Transistor -Parameters Based on Prior Knowledge Neural Network.

In this paper, an aging small-signal model for degradation prediction of microwave heterojunction bipolar transistor (HBT) -parameters based on prior knowledge neural networks (PKNNs) is explored. A dual-extreme learning machine (D-ELM) structure with an adaptive genetic algorithm (AGA) optimization process is used to simulate the fresh -parameters of InP HBT devices and the degradation of -parameters after accelerated aging, respectively. In addition to the reliability parametric inputs of the original aging problem, the -parameter degradation trend obtained from the aging small-signal equivalent circuit is used as additional information to inject into the D-ELM structure.

Decreased coherence in the model of the dorsal visual pathway associated with Alzheimer's disease.

Decreased coherence in electroencephalogram (EEG) has been reported in Alzheimer's disease (AD) experimentally, which could be considered as a typical electrophysiological characteristic in AD. This work aimed to investigate the effect of AD on coherence in the dorsal visual pathway by the technique of neurocomputation. Firstly, according to the hierarchical organization of the cerebral cortex and the information flows of the dorsal visual pathway, a more physiologically plausible neural mass model including cortical areas v1, v2, and v5 was established in the dorsal visual pathway.

Effect of acetylcholine deficiency on neural oscillation in a brainstem-thalamus-cortex neurocomputational model related with Alzheimer's disease.

Previous works imply that involving brainstem in neuropathological studies of Alzheimer's disease (AD) is of clinically significant. This work constructs a comprehensive neural mass model for cholinergic neuropathogenesis that involves brainstem, thalamus and cortex, wherein how acetylcholine deficiency in AD affects neural oscillation of the model output is systematically explored from the perspective of neurocomputation. By decreasing synapse connectivity parameters in direct cholinergic pathway from brainstem to thalamus or in indirect glutamatergic synapse pathway from cortex to brainstem to mimic the pathological condition of reduced acetylcholine release in patients with AD, the property of neural oscillation in this model is numerically investigated by means of power spectrum in frequency domain and amplitude distribution in time domain.