Progressive Thinning of Visual Motion Area in Lower Limb Amputees

Accumulating evidence has indicated that amputation or deafferentation of a limb induces functional or structural reorganization in the visual areas. However, the extent of the visual areas involved after lower limb amputation remains uncertain. In this investigation, we studied 48 adult patients with unilateral lower limb amputation and 48 matched healthy controls using T1-weighted magnetic resonance imaging. Template-based regions of interest analysis was implemented to detect the changes of cortical thickness in the specific visual areas. Compared with normal controls, amputees exhibited significantly lower thickness in the V5/middle temporal (V5/MT+) visual area, as well as a trend of cortical thinning in the V3d. There was no significant difference in the other visual areas between the two groups. In addition, no significant difference of cortical thickness was found between patients with amputation at different levels. Across all amputees, correlation analyses revealed that the cortical thickness of the V5/MT+ was negatively correlated to the time since amputation. In conclusion, our findings indicate that the amputation of unilateral lower limb could induce changes in the motor-related visual cortex, and provide an update on the plasticity of the human brain after limb injury

Resting-state coupling between core regions within the central-executive and salience networks contributes to working memory performance

Previous studies investigated the distinct roles played by different cognitive regions and suggested that the patterns of connectivity of these regions are associated with working memory. However, the specific causal mechanism through which the neuronal circuits that involve these brain regions contribute to working memory is still unclear. Here, in a large sample of healthy young adults, we first identified the core working memory regions by linking working memory accuracy to resting-state functional connectivity with the bilateral dorsolateral prefrontal cortex (a principal region in the central-executive network). Then a spectral dynamic causal modeling analysis was performed to quantify the effective connectivity between these regions. Finally, the effective connectivity was correlated with working memory accuracy to characterize the relationship between these connections and working memory performance. We found that the functional connections between the bilateral dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex and between the right dorsolateral prefrontal cortex and the left orbital fronto-insular cortex were correlated with working memory accuracy. Furthermore, the effective connectivity from the dorsal anterior cingulate cortex to the bilateral dorsolateral prefrontal cortex and from the right dorsolateral prefrontal cortex to the left orbital fronto-insular cortex could predict individual differences in working memory. Because the dorsal anterior cingulate cortex and orbital fronto-insular cortex are core regions of the salience network, we inferred that the inter- and causal-connectivity between core regions within the central-executive and salience networks is functionally relevant for working memory performance. In summary, the current study identified the dorsolateral prefrontal cortex-related resting-state effective connectivity underlying working memory and suggests that individual differences in cognitive ability could be characterized by resting-state effective connectivity

Parcellation of the Primary Cerebral Cortices based on Local Connectivity Profiles

Primary cerebral cortices are of great importance for our understanding of the human brain. Although their functions are relatively monomodal, primary cerebral cortices have been suggested to compromise structurally and functionally distinct subregions from many evidences, for example, cytoarchitectionics, myeloarchitectonics and functional brain imaging. In recent years, structural connectivity-based parcellation using diffusion MRI has been extensively used to do parcellation of subcortical areas and association cortex. However, it has rarely been employed to primary cerebral cortices. In connectivity-based parcellation, connectivity profiles are very vital. Different researchers used different information of connectivity profiles, such as global connectivity profiles (the connectivity information from seed to the whole brain) and long connectivity profiles (the connectivity information from seed to other brain regions after excluding the seed). Given that primary cerebral cortices are rich of local hierarchical connections and possess high local functional connectivity profiles, we proposed that local connectivity profiles (the connectivity information in the seed region of interest (ROI)) might be used for parcellating primary cerebral cortices. Global, long and local connectivity profiles were compared on M1, A1, S1 and V1. We found that results using the three were all in good consistency with cytoarchitectonic results. More importantly, results using local connectivity profiles showed less inter-subject variability than results using the other two. This suggests that for parcellation of primary cerebral cortices local connectivity profiles are superior to global and long connectivity profiles. This also infers us that different connectivity profiles should be adopted according to the characteristics of the cerebral cortices

Distinct changes in functional connectivity in posteromedial cortex subregions during the progress of Alzheimer’s disease

Alzheimer’s disease is a progressive neurodegenerative disorder which causes dementia, especially in the elderly. The posteromedial cortex, which consists of several subregions involved in distinct functions, is one of the critical regions associated with the progression and severity of Alzheimer’s disease. However, previous studies always ignored the heterogeneity of the posteromedial cortex and focused on one stage of Alzheimer’s disease. Using resting-state functional magnetic resonance imaging, we studied the respective alterations of each subregion within the posteromedial cortex along the progression of Alzheimer’s disease. Our data set consisted of 21 healthy controls, 18 patients with mild cognitive impairment, 17 patients with mild Alzheimer’s disease, and 18 patients with severe Alzheimer’s disease. We investigated the functional alterations of each subregion within the posteromedial cortex in different stages of Alzheimer’s disease. We found that subregions within the posteromedial cortex have differential vulnerability in Alzheimer’s disease. Disruptions in functional connectivity began in the transition area between the precuneus and the posterior cingulate cortex and then extended to other subregions of the posteromedial cortex. In addition, each of these subregions was associated with distinct alterations in the functional networks that we were able to relate to Alzheimer’s disease. Our research demonstrated functional changes within the posteromedial cortex in the progression of Alzheimer’s disease and may elucidate potential biomarkers for clinical applications

The structural connectivity pattern of the default mode network and its association with memory and anxiety

The default mode network (DMN) is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI). Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects. Using a probabilistic fiber tractography technique based on DTI data and graph theory methods, we constructed the global structural connectivity pattern of the DMN and found that memory quotient (MQ) score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, we found the network efficiency of the DMN were related to memory and anxiety measures, which indicated that the DMN may play a role in the memory and anxiety

Scalable and DiI-compatible optical clearance of the mammalian brain

Efficient optical clearance is fundamental for whole brain imaging. In particular, clearance of the brain without membrane damage is required for the imaging of lipophilic tracer-labeled neural tracts. Relying on an ascending gradient of fructose solutions, SeeDB can achieve sufficient transparency of the mouse brain while ensuring that the plasma membrane remains intact. However, it is challenging to extend this method to larger mammalian brains due to the extremely high viscosity of the saturated fructose solution. Here we report a SeeDB-derived optical clearing method, termed FRUIT, which utilizes a cocktail of fructose and urea. As demonstrated in the adult mouse brain, combination of these two highly water-soluble clearing agents exerts a synergistic effect on clearance. More importantly, the final FRUIT solution has low viscosity so as to produce transparency of the whole adult rabbit brain via arterial perfusion, which is impossible to achieve with a saturated fructose solution. In addition to good compatibility with enhanced yellow fluorescent protein, the cocktail also preserves the fluorescence of the lipophilic tracer DiI. This work provides a volume-independent optical clearing method which retains the advantages of SeeDB, particularly compatibility with lipophilic tracers