Study of EEG characteristics while solving scientific problems with different mental effort

Studying the mental effort in problem-solving is important to the understanding of how the brain allocates cognitive resources to process information. The electroencephalogram is a promising physiological approach to assessing the online mental effort. In this study, we investigate the EEG indicators of mental effort while solving scientific problems. By manipulating the complexity of the scientific problem, the level of mental effort also changes. With the increase of mental effort, theta synchronization in the frontal region and lower alpha desynchronization in the parietal and occipital regions significantly increase. Also, upper alpha desynchronization demonstrates a widespread enhancement across the whole brain. According to the functional topography of brain activity in the theta and alpha frequency, our results suggest that the mental effort while solving scientific problems is related to working memory, visuospatial processing, semantic processing and magnitude manipulation. This study suggests the reliability of EEG to evaluate the mental effort in an educational context and provides valuable insights into improving the problem-solving abilities of students in educational practice.

A functional topography within the cholinergic basal forebrain for encoding sensory cues and behavioral reinforcement outcomes

Basal forebrain cholinergic neurons (BFCNs) project throughout the cortex to regulate arousal, stimulus salience, plasticity, and learning. Although often treated as a monolithic structure, the basal forebrain features distinct connectivity along its rostrocaudal axis that could impart regional differences in BFCN processing. Here, we performed simultaneous bulk calcium imaging from rostral and caudal BFCNs over a one-month period of variable reinforcement learning in mice. BFCNs in both regions showed equivalently weak responses to unconditioned visual stimuli and anticipated rewards. Rostral BFCNs in the horizontal limb of the diagonal band were more responsive to reward omission, more accurately classified behavioral outcomes, and more closely tracked fluctuations in pupil-indexed global brain state. Caudal tail BFCNs in globus pallidus and substantia innominata were more responsive to unconditioned auditory stimuli, orofacial movements, aversive reinforcement, and showed robust associative plasticity for punishment-predicting cues. These results identify a functional topography that diversifies cholinergic modulatory signals broadcast to downstream brain regions.

Functional Orderly Topography of Brain Networks Associated with Gene Expression Heterogeneity

The human cerebral cortex expanded much more relative to non-human primates and rodent in evolution, leading to a functional orderly topography of the brain networks. Here, we show that functional topography may be associated with gene expression heterogeneity in various brain structures. The neocortex exhibits greater gene expression heterogeneity, with lower housekeeping gene proportion, a longer mean path length, less clusters, and a lower degree of ordering of networks, compared to archicortical and subcortical area in human, rhesus macaque, and mouse brains consistently. In particular, the cerebellar cortex displays greater gene expression heterogeneity than cerebellar deep nuclei in the human brain, but not in the mouse brain, corresponding to the emergence of novel functions in the human cerebellar cortex. Moreover, the cortical areas with greater gene expression heterogeneity, primarily located in multimodal association cortex, tend to express genes with higher evolutionary rates and exhibit higher functional connectivity degree measured by resting-state fMRI, implying that such spatial pattern of cortical gene expression may be shaped by evolution and favorable for the specialization of higher cognitive functions. Together, the cross-species imaging genetic findings may provide convergent evidence to support the association between the orderly topography of brain function networks and gene expression.

Unique spatiotemporal fMRI dynamics in the awake mouse brain

Resting state fMRI (rsfMRI) mapping in the mouse is typically performed under light anesthesia, preventing a full characterization of how the ensuing network architecture reconfigures under wakeful, conscious states. Leveraging a robust protocol for rsfMRI mapping in non-anesthetized, head-fixed mice, we provide a comprehensive description of the functional topography and dynamic structure of rsfMRI activity in awake mice. We find that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation states encompassing functional anti-coordination between visual-auditory and default mode network areas, and a prominent participation of arousal-related forebrain nuclei. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation states are configured as leading network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems, and document that its dynamic structure recapitulates distinctive, evolutionarily-relevant principles that are predictive of conscious states in higher mammalian species.

Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in association cortex that has been implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth. Capitalizing on a large sample with 27-minutes of high-quality functional MRI data (n=790, ages 8-23 years) and advances in machine learning, we examined associations between functional topography and four correlated dimensions of psychopathology (fear, psychosis, externalizing, anxious-misery) as well as an overall psychopathology factor. We found that functional topography significantly predicted individual differences in dimensions of psychopathology, driven mainly by robust associations between topography and overall psychopathology. Reduced cortical representations of association networks were among the most important features of the model. Our results emphasize the value of considering systematic differences in functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.

Sex Differences in Functional Topography of Association Networks

Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8-23 years) who underwent functional magnetic resonance imaging as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 83% accuracy (p<0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention and default mode networks. Mass-univariate analyses using generalized additive models with penalized splines provided convergent results. Comparative analysis using transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography correlated with the expression of genes on the X-chromosome. These results identify normative developmental sex differences in the functional topography of association networks and highlight the role of sex as a biological variable in shaping brain development in youth.