Brain Structure & Function最新文献

This mini-review explores sexual dimorphism in the ventral midline thalamus, focusing on the reuniens nucleus and its role in behavioral functions. Traditionally linked to tasks such as working memory, cognitive flexibility, fear generalization, and memory consolidation, most studies have been conducted in male rodents. Research comparing the effects of ventral midline thalamus manipulations between female and male rodents is limited. Emerging evidence suggests sex-specific differences, particularly in response to stress, pharmacological manipulations, and memory processes. Studies reveal distinct c-Fos expression patterns in the reuniens nucleus between females and males, especially under stress, with females often showing different neural activation. Additionally, females exhibit different recruitment of the reuniens nucleus in object recognition tasks, indicating possible sex-dependent cognitive strategies. While evidence suggests functional differences between sexes in the reuniens nucleus, current data are limited. Further research is needed to understand how sex influences brain function and cognition, particularly in the ventral midline thalamus, which is crucial for various cognitive processes.

The dual task cost of gait (DTC) is an accessible and cost-effective test that can help identify individuals with cognitive decline and dementia. However, its neural substrate has not been widely described. This study aims to investigate the neural substrate of the high DTC in older adults across the spectrum of cognitive decline. A total of 336 individuals from the GAIT study cohort were analyzed, including cognitively healthy (N = 122, 71 ± 3.6 years), those with mild cognitive impairment (N = 168, 71 ± 5.3 years), and those with dementia (N = 46, 80 ± 5.7 years). A DTC of 20% or greater was considered to indicate a high level of slowing down while performing successively two verbal tasks (counting backwards task by ones and naming animals). Voxel-based morphometry was employed to investigate differences in gray matter volume (GMV) between groups, which were dichotomized according to the DTC. A high DTC in the whole population (N = 336) was associated with a smaller GMV in the bilateral temporal lobe across both dual-task conditions. A moderation analysis was employed to compare the neural substrate between cognitive status groups. This revealed that the dementia group exhibited an additional cluster located in the left precentral gyrus with GMV loss associated with a high naming animals DTC, in contrast to the other cognitive groups. These results provide new evidence on why dual-task gait capabilities deteriorate in normal and pathological cognitive aging. A more precise understanding of the neural substrate associated with high DTC and cognitive status would help elucidate its use in clinical and research settings.

The default mode network (DMN) is a singular pattern of synchronization between brain regions, usually observed using resting-state functional magnetic resonance imaging (rs-fMRI) and functional connectivity analyses. In comparison to other brain networks that are primarily involved in attentional-demanding tasks (such as the frontoparietal network), the DMN is linked with self-referential activities, and alterations in its pattern of connectivity have been related to a wide range of disorders. Structural connectivity analyses have highlighted the vital role of the posterior cingulate cortex and the precuneus as integrative hubs, and advanced parcellation methods have further contributed to elucidate the DMN's regions, enriching its explanatory potential across cognitive functions and dysfunctions. Interestingly, the study of its temporal characteristics - the specific frequency spectrum of BOLD signal oscillations -, its developmental trajectory over the course of life, and its interaction with other networks, provides new insight into the DMN's defining features. In this context, this review aims to synthesize the state of the art in the study of the DMN to provide the most updated findings to anyone interested in its research. Finally, some weaknesses in the current state of knowledge and some interesting lines of work for further progress in the study of the DMN are presented.

This editorial celebrates the 80th birthday of Distinguished Professor Laszlo Zaborszky, co-founder of Brain Structure and Function, and reflects on his monumental contributions to neuroscience, particularly his pioneering work on the cholinergic basal forebrain. Professor Zaborszky's research has reshaped our understanding of this brain region's organization and function, uncovering its critical role in cognitive processes such as learning, memory, and attention. His findings have challenged longstanding assumptions, demonstrating that the cholinergic projections to the cortex are highly organized, with implications for neurodegenerative diseases like Alzheimer's. Beyond his scientific achievements, Professor Zaborszky has made lasting contributions through his mentorship, shaping the careers of many neuroscientists, including the author. This editorial pays tribute to his remarkable legacy, both as a researcher and mentor and highlights his enduring impact on the field of neuroscience.

Acute cerebral ischemia alters brain network connectivity, leading to notable increases in both anatomical and functional connectivity while observing a reduction in metabolic connectivity. However, alterations of the cerebral blood flow (CBF) based functional connectivity remain unclear. We collected continuous CBF images using laser speckle contrast imaging (LSCI) technology to monitor ischemic occlusion-reperfusion progression through occlusion of the left carotid artery. We also used a dense cortical grid atlas to construct CBF-based functional connectivity networks for hyperacute ischemic rodents. Graph theoretical analysis was used to measure network topological characteristics and construct topological connection graphs. Coactivation pattern (CAP) analysis was utilized to examine the spatiotemporal characteristics of the global network. Additionally, we measured evoked functional hyperemia and correlated it with network topologies. Network analysis indicated a significant increase in functional connectivity, global efficiency, local efficiency, small-worldness, clustering coefficient, and regional degree centrality primarily within the left ischemic intra-hemisphere, accompanied by weaker changes in the right intra-hemisphere. Inter-hemisphere networks exhibited reduced homologous connections, global efficiency, and small-worldness. CAP analysis revealed increased strength of the left negative activation brain network's state fraction of time and transition probability from equilibrium-to-imbalance states. Left network metrics declined following blood flow reperfusion. Furthermore, positive/negative correlations between barrel-evoked intensity and regional network topologies were reversed as negative/positive correlations after cerebral ischemia. These findings suggest a damaged CBF functional network mechanism following acute cerebral ischemia and a disrupted association between resting state and evoked hyperemia.

Microglia play important roles in maintaining homeostasis and immunoreactive defense in the central nervous system including retina. To accomplish such a wide range of functions, microglia are highly heterogeneous. Dark microglia (DM) were recently identified by electron microscopy (EM). However, the specific correlation between microglial morphological phenotypes, including DM, and physiological or pathological conditions remains poorly understood. We established acute and chronic neuroinflammatory models by Lipopolysaccharide (LPS) and light-induced photoreceptor neurodegeneration model to explore these questions in the mouse retina. Immunofluorescence and EM were used to detect microglia in these models. Our light microscopy (LM) results reveal that the withdrawal phenotype is predominant in acute neuroinflammation models, both in vitro and in vivo, while the dystrophic microglia are the major phenotype in chronic neuroinflammation and neurodegeneration models in vivo. Ultrastructurally, acute models exhibit high electron dense processes, but not somas, while chronic models show high electron dense somas and processes. Given the consistency between LM and EM, we propose that DM-like somas and processes likely indicate a dystrophic population. It's important to note, however, that DM may not represent a single specific microglia phenotype, but rather a dynamic transformation of gradually activated microglia. Finally, we provide evidence for the presence of DM in mouse retinas in the neuroinflammatory model and the neurodegenerative model. This research provides valuable insights into investigating microglia phenotypes through both LM and EM.

Co-activation of distinct brain areas provides a valuable measure of functional interaction, or connectivity, between them. One well-validated way to investigate the co-activation patterns of a precise area is meta-analytic connectivity modeling (MACM), which performs a seed-based meta-analysis on task-based functional magnetic resonance imaging (task-fMRI) data. While MACM stands as a powerful automated tool for constructing robust models of whole-brain human functional connectivity, its inherent limitation lies in its inability to capture the distinct interrelationships among multiple brain regions. Consequently, the connectivity patterns highlighted through MACM capture the direct relationship of the seed region with third brain regions, but also a (less informative) residual relationship between the third regions themselves. As a consequence of this, this technique does not allow to evaluate to what extent the observed connectivity pattern is really associated with the fact that the seed region is activated, or it just reflects spurious co-activations unrelated with it. In order to overcome this methodological gap, we introduce a meta-analytic Bayesian-based method, called meta-analytic connectivity perturbation analysis (MACPA), that allows to identify the unique contribution of a seed region in shaping whole-brain connectivity. We validate our method by analyzing one of the most complex and dynamic structures of the human brain, the amygdala, indicating that MACPA may be especially useful for delineating region-wise co-activation networks.

Aim: To describe the cortical brain development and full-IQ performance in middle school age children after extremely preterm (EPT) birth considering discrete white matter abnormalities (WMA). In addition, to assess possible early motor predictors of cortical brain development and full-IQ in children born EPT with and without discrete WMA diagnosed at 10 years.

Methods: T1-weighted MRI images from fifty-one children born before 27 weeks' gestation and 40 full-term born controls (M_age=10.09 years; SD_age=0.77) were scored for discrete WMA and analyzed with Freesurfer (v7.2.0). The assessments included motor assessments (i.e., fine- and gross motor function) of Bayley Scales of Infant and Toddler Development - Third Edition (BSID-III) at a mean age of 2½ years. Full-IQ was also assessed with Wechsler Intelligence Scale for Children - Fifth Edition (WISC-V) at 12 years.

Results: No differences were displayed in motor function or full-IQ score between children born EPT with and without discrete WMA at 10 years. Moreover, no global differences were found in cortex volume. However, bilateral mean cortical thicknesses (CTh) were exhibited to be thicker in children born EPT with discrete WMA. Children born EPT with discrete WMA exhibited regional increases mainly in the frontal and temporal lobes apart from left caudal anterior cingulate gyrus (mean difference = -0.11 (-0.22, -0.01), p = 0.026). Full-IQ was predicted by impairments in fine motor skills in children born EPT with discrete WMA, explaining 42.9% of the variance.

Conclusions: Bilateral mean and regional CTh were found to be greater in children born EPT with discrete WMA at 10 years compared to those without. Fine motor function at 2½ years was a strong predictor of full-IQ dependent in children with discrete WMA.