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Discriminative Power of Handwriting and Drawing Features in Depression
This study contributes knowledge on the detection of depression through handwriting/drawing features, to identify quantitative and noninvasive indicators of the disorder for implementing algorithms for its automatic detection. For this purpose, an original online approach was adopted to provide a dynamic evaluation of handwriting/drawing performance of healthy participants with no history of any psychiatric disorders ([Formula: see text]), and patients with a clinical diagnosis of depression ([Formula: see text]). Both groups were asked to complete seven tasks requiring either the writing or drawing on a paper while five h...
Source: International Journal of Neural Systems - November 27, 2023 Category: Neurology Authors: Claudia Greco Gennaro Raimo Terry Amorese Marialucia Cuciniello Gavin Mcconvey Gennaro Cordasco Marcos Faundez-Zanuy Alessandro Vinciarelli Zoraida Callejas-Carrion Anna Esposito Source Type: research

Author Index: Volume 33 (2023)
Int J Neural Syst. 2023 Dec;33(12):2399001. doi: 10.1142/S0129065723990010.NO ABSTRACTPMID:37990997 | DOI:10.1142/S0129065723990010 (Source: International Journal of Neural Systems)
Source: International Journal of Neural Systems - November 22, 2023 Category: Neurology Source Type: research

Self-Supervised EEG Representation Learning with Contrastive Predictive Coding for Post-Stroke Patients
Int J Neural Syst. 2023 Dec;33(12):2350066. doi: 10.1142/S0129065723500661.ABSTRACTStroke patients are prone to fatigue during the EEG acquisition procedure, and experiments have high requirements on cognition and physical limitations of subjects. Therefore, how to learn effective feature representation is very important. Deep learning networks have been widely used in motor imagery (MI) based brain-computer interface (BCI). This paper proposes a contrast predictive coding (CPC) framework based on the modified s-transform (MST) to generate MST-CPC feature representations. MST is used to acquire the temporal-frequency featu...
Source: International Journal of Neural Systems - November 22, 2023 Category: Neurology Authors: Fangzhou Xu Yihao Yan Jianqun Zhu Xinyi Chen Licai Gao Yanbing Liu Weiyou Shi Yitai Lou Wei Wang Jiancai Leng Yang Zhang Source Type: research

Neonatal White Matter Damage Analysis Using DTI Super-Resolution and Multi-Modality Image Registration
Int J Neural Syst. 2023 Nov 17:2450001. doi: 10.1142/S0129065724500011. Online ahead of print.ABSTRACTPunctate White Matter Damage (PWMD) is a common neonatal brain disease, which can easily cause neurological disorder and strongly affect life quality in terms of neuromotor and cognitive performance. Especially, at the neonatal stage, the best cure time can be easily missed because PWMD is not conducive to the diagnosis based on current existing methods. The lesion of PWMD is relatively straightforward on T1-weighted Magnetic Resonance Imaging (T1 MRI), showing semi-oval, cluster or linear high signals. Diffusion Tensor Ma...
Source: International Journal of Neural Systems - November 20, 2023 Category: Neurology Authors: Yi Wang Yuan Zhang Chi Ma Rui Wang Zhe Guo Yu Shen Miaomiao Wang Hongying Meng Source Type: research