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White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson's disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Decoding brain cognitive states from neuroimaging signals is an important topic in neuroscience. In recent years, deep neural networks (DNNs) have been recruited for multiple brain state decoding and achieved good performance. However, the open question of how to interpret the DNN black box remains unanswered. Capitalizing on advances in machine learning, we integrated attention modules into brain decoders to facilitate an in-depth interpretation of DNN channels. A four-dimensional (4D) convolution operation was also included to extract temporo-spatial interaction within the fMRI signal. The experiments showed that the proposed model obtains a very high accuracy (97.4%) and outperforms previous researches on the seven different task benchmarks from the Human Connectome Project (HCP) dataset. The visualization analysis further illustrated the hierarchical emergence of task-specific masks with depth. Finally, the model was retrained to regress individual traits within the HCP and to classify viewing images from the BOLD5000 dataset, respectively. Transfer learning also achieves good performance. Further visualization analysis shows that, after transfer learning, low-level attention masks remained similar to the source domain, whereas high-level attention masks changed adaptively. In conclusion, the proposed 4D model with attention module performed well and facilitated interpretation of DNNs, which is helpful for subsequent research., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

White matter hyperintensities (WMH) are common in elderly individuals and cause brain network deficits. However, it is still unclear how the global brain network is affected by the focal WMH. We aimed to investigate the diffusion of WMH‐related deficits along the connecting white matters (WM). Brain magnetic resonance imaging data and neuropsychological evaluations of 174 participants (aged 74 ± 5 years) were collected and analyzed. For each participant, WMH lesions were segmented using a deep learning method, and 18 major WM tracts were reconstructed using automated quantitative tractography. The diffusion characteristics of distal WM tracts (with the WMH penumbra excluded) were calculated. Multivariable linear regression analysis was performed. We found that a high burden of tract‐specific WMH was related to worse diffusion characteristics of distal WM tracts in a wide range of WM tracts, including the forceps major (FMA), forceps minor (FMI), anterior thalamic radiation (ATR), cingulum cingulate gyrus (CCG), corticospinal tract (CST), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus‐parietal (SLFP), superior longitudinal fasciculus‐temporal (SLFT), and uncinate fasciculus (UNC). Furthermore, a higher mean diffusivity (MD) of distal tracts was linked to worse attention and executive function in the FMI, right CCG, left ILF, SLFP, SLFT, and UNC. The effect of WMH on the microstructural integrity of WM tracts may propagate along tracts to distal regions beyond the penumbra and might eventually affect attention and executive function. [ABSTRACT FROM AUTHOR]

Background. Clinical and experimental data suggest that ultrasound stimulation (US) at acupoints can produce similar effective treatment compared to manual acupuncture (MA). Although the brain activation to MA at acupoints is investigated by numerous studies, the brain activation to US at acupoints remains unclear. Methods. In the present work, we employed task state functional magnetic resonance imaging (fMRI) to explore the human brain's activation to US and MA at ST 36 (Zusanli) which is one of the most commonly used acupoints in acupuncture-related studies. 16 healthy subjects underwent US and MA procedures in an interval of more than one week. On-off block design stimulation was used for the recording of fMRI-related brain patterns. Results. Both US and MA at ST 36 produced activations in somatosensory and limbic/paralimbic regions (postcentral gyrus, insula, middle prefrontal cortex, and anterior cingulate cortex). Only US at ST 36 produced a significant signal increase in the inferior parietal lobule and decrease in the posterior cingulate cortex, whereas MA at ST 36 produced a significant signal increase in the lentiform nucleus and cerebellum. Conclusions. Our results indicate that US may be a possible noninvasive alternative method to MA due to its similar activation patterns. [ABSTRACT FROM AUTHOR]