Deep neural networks (DNNs) excel at extracting insights from complex data across various fields, however, their application in cognitive neuroscience remains limited, largely due to the lack of approaches with interpretability. Here, we employ two d...
This paper presents a computational model of visual working memory (VWM) that simulates the processing of spatially distributed objects and their features. The model emphasizes the prioritization of object-related information before feature-related p...
Since 3D medical imaging data is a string of sequential images, there is a strong correlation between consecutive images. Deep convolutional networks perform well in extracting spatial features, but are less capable for processing sequence data compa...
In daily life, we frequently encounter varying demands on working memory (WM), yet how the brain adapts to high WM load remains unclear. To address this question, we recorded intracranial EEG from hippocampus, entorhinal cortex (EC), and lateral temp...
Shear wave velocity (Vs) serves as a crucial petrophysical parameter for subsurface characterization, yet its acquisition remains challenging. While long short-term memory (LSTM) networks have emerged as the predominant solution for Vs prediction by ...
LSTM (Long Short-Term Memory Network) is currently extensively utilized for forecasting financial time series, primarily due to its distinct advantages in separating the long-term from the short-term memory information within a sequence. However, the...
Neural networks : the official journal of the International Neural Network Society
May 7, 2025
Motor sequence learning relies on the synergistic collaboration of multiple brain regions. However, most existing models for motor sequence learning primarily focus on functional-level analyses of sequence memory mechanisms, providing limited neuroph...
BackgroundDancing may be protective for cognitive health among adults with mild cognitive impairment, Alzheimer's disease or dementia; however, additional methods are needed to characterize motor behavior quality in studies of dance.ObjectiveTo deter...
The complexities of stock price data, characterized by its nonlinearity, non-stationarity, and intricate spatiotemporal patterns, make accurate prediction a substantial challenge. To address this, we propose the DCA-BiLSTM model, which combines dual-...
BACKGROUND: Hands-and-knees crawling is a promising rehabilitation intervention for infants with motor impairments, while research on assistive crawling devices for rehabilitation training was still in its early stages. In particular, precisely gener...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.