The evolutionary history of the polyQ tract in huntingtin sheds light on its functional pro-neural activities

Huntington’s disease is caused by a pathologically long (>35) CAG repeat located in the first exon of the Huntingtin gene (HTT). While pathologically expanded CAG repeats are the focus of extensive investigations, non-pathogenic CAG tracts in protein-coding genes are less well characterized. Here, we investigated the function and evolution of the physiological CAG tract in the HTT gene. We show that the poly-glutamine (polyQ) tract encoded by CAGs in the huntingtin protein (HTT) is under purifying selection and subjected to stronger selective pressures than CAG-encoded polyQ tracts in other proteins. For natural selection to operate, the polyQ must perform a function. By combining genome-edited mouse embryonic stem cells and cell assays, we show that small variations in HTT polyQ lengths significantly correlate with cells’ neurogenic potential and with changes in the gene transcription network governing neuronal function. We conclude that during evolution natural selection promotes the conservation and purity of the CAG-encoded polyQ tract and that small increases in its physiological length influence neural functions of HTT. We propose that these changes in HTT polyQ length contribute to evolutionary fitness including potentially to the development of a more complex nervous system.

Manganese Dynamics in Mouse Brain After Systemic MnCl2 Administration for Activation-Induced Manganese-Enhanced MRI

Activation-induced manganese-enhanced MRI (AIM-MRI) is an attractive tool for non-invasively mapping whole brain activities. Manganese ions (Mn2+) enter and accumulate in active neurons via calcium channels. Mn2+ shortens the longitudinal relaxation time (T1) of H+, and the longitudinal relaxation rate R1 (1/T1) is proportional to Mn2+ concentration. Thus, AIM-MRI can map neural activities throughout the brain by assessing the R1 map. However, AIM-MRI is still not widely used, partially due to insufficient information regarding Mn2+ dynamics in the brain. To resolve this issue, we conducted a longitudinal study looking at manganese dynamics after systemic administration of MnCl2 by AIM-MRI with quantitative analysis. In the ventricle, Mn2+ increased rapidly within 1 h, remained high for 3 h, and returned to near control levels by 24 h after administration. Microdialysis showed that extracellular Mn returned to control levels by 4 h after administration, indicating a high concentration of extracellular Mn2+ lasts at least about 3 h after administration. In the brain parenchyma, Mn2+ increased slowly, peaked 24–48 h after administration, and returned to control level by 5 days after a single administration and by 2 weeks after a double administration with a 24-h interval. These time courses suggest that AIM-MRI records neural activity 1–3 h after MnCl2 administration, an appropriate timing of the MRI scan is in the range of 24–48 h following systemic administration, and at least an interval of 5 days or a couple of weeks for single or double administrations, respectively, is needed for a repeat AIM-MRI experiment.

Functional Subdivisions of the Cerebellum in Naturalistic Paradigm Functional Magnetic Resonance Imaging

Compelling evidence has suggested that the human cerebellum is engaged in a wide range of cognitive tasks besides traditional opinions of motor control, and it is organized into a set of distinct functional subregions. The existing model-driven cerebellum parcellations through resting-state functional MRI (rsfMRI) and task-fMRI are relatively coarse, introducing challenges in resolving the functions of the cerebellum especially when the brain is exposed to naturalistic environments. The current study took the advantages of the naturalistic paradigm (i.e., movie viewing) fMRI (nfMRI) to derive fine parcellations via a data-driven dual-regression-like sparse representation framework. The parcellations were quantitatively evaluated by functional homogeneity, and global and local boundary confidence. In addition, the differences of cerebellum–cerebrum functional connectivities between rsfMRI and nfMRI for some exemplar parcellations were compared to provide qualitatively functional validations. Our experimental results demonstrated that the proposed study successfully identified distinct subregions of the cerebellum. This fine parcellation may serve as a complementary solution to existing cerebellum parcellations, providing an alternative template for exploring neural activities of the cerebellum in naturalistic environments.

Neural Oscillations and Networks in Processes Specific to Auditory Imagery

Auditory imagery is a cognitive process for generating sound in our mind. Despite the absence of external stimuli, neuroimaging studies have found overlapping neural activities within perception and imagery. While neuroimaging studies have revealed activities unique to auditory imagery, namely memory retrieval and mental manipulation, little is known about the functional oscillatory networks associated with these processes. Therefore, in this study, we aimed to distinguish between neural oscillations for memory retrieval and mental manipulation processes by building a novel experimental paradigm containing multiple imagery conditions with the goal of enabling the effective investigation of different oscillatory processes. We found that frontal and temporal gamma power was associated with mental manipulation, while frontotemporal delta phase coupling and delta-gamma phase-amplitude coupling were each associated with memory retrieval during auditory imagery. Moreover, we found that oscillations reflecting auditory-motor communication were associated with memory retrieval. Our results suggest the critical role of neural oscillations associated with imagery-specific processes and present evidence supporting the long-debated role of motor functions in auditory imagery. Our work thus adds dimension to the state of knowledge regarding functional networks within auditory imagery.

Multiple-Timescale Neural Networks: Generation of History-Dependent Sequences and Inference Through Autonomous Bifurcations

Sequential transitions between metastable states are ubiquitously observed in the neural system and underlying various cognitive functions such as perception and decision making. Although a number of studies with asymmetric Hebbian connectivity have investigated how such sequences are generated, the focused sequences are simple Markov ones. On the other hand, fine recurrent neural networks trained with supervised machine learning methods can generate complex non-Markov sequences, but these sequences are vulnerable against perturbations and such learning methods are biologically implausible. How stable and complex sequences are generated in the neural system still remains unclear. We have developed a neural network with fast and slow dynamics, which are inspired by the hierarchy of timescales on neural activities in the cortex. The slow dynamics store the history of inputs and outputs and affect the fast dynamics depending on the stored history. We show that the learning rule that requires only local information can form the network generating the complex and robust sequences in the fast dynamics. The slow dynamics work as bifurcation parameters for the fast one, wherein they stabilize the next pattern of the sequence before the current pattern is destabilized depending on the previous patterns. This co-existence period leads to the stable transition between the current and the next pattern in the non-Markov sequence. We further find that timescale balance is critical to the co-existence period. Our study provides a novel mechanism generating robust complex sequences with multiple timescales. Considering the multiple timescales are widely observed, the mechanism advances our understanding of temporal processing in the neural system.

Ultrasonic thalamic stimulation modulates neural activity of thalamus and motor cortex in the mouse

Objective. Previous studies have demonstrated that ultrasound thalamic stimulation (UTS) can treat disorders of consciousness. However, it is still unclear how UTS modulates neural activity in the thalamus and cortex. Approach. In this study, we performed UTS in mice and recorded the neural activities including spike and local field potential (LFP) of the thalamus and motor cortex. We analyzed the firing rate of spikes and the power spectrum of LFPs and evaluated the coupling relationship between LFPs from the thalamus and motor cortex with Granger causality. Main results. Our results clearly indicate that UTS can directly induce neural activity in the thalamus and indirectly induce neural activity in the motor cortex. We also found that there is a strong connection relationship of neural activity between thalamus and motor cortex under UTS. Significance. These results demonstrate that UTS can modulate the neural activity of the thalamus and motor cortex in mice. It has the potential to provide guidance for the ultrasound treatment of thalamus-related diseases.

Overlapping Representation of Basic Tastes in the Human Gustatory Cortex

The topological representation is a fundamental property of human primary sensory cortices. The human gustatory cortex (GC) responds to the five basic tastes: bitter, salty, sweet, umami, and sour. However, the topological representation of the human gustatory cortex remains controversial. Through functional magnetic resonance imaging(fMRI) measurements of human responses to the five basic tastes, the current study aimed to delineate the taste representations within the GC. During the scanning, the volunteers tasted solutions of the five basic tastes, then washed their mouths with the tasteless solution. The solutions were then sucked from the volunteers' mouths, eliminating the action of swallowing. The results showed that the bilateral mid-insula activated most during the taste task, and the active areas were mainly in the precentral and central insular sulcus. However, the regions responding to the five basic tastes are substantially overlapped, and the analysis of contrasts between each taste response and the averaged response to the remaining tastes does not report any significant results. Furthermore, in the gustatory insular cortex, the multivariate pattern analysis (MVPA) was unable to distinguish the activation patterns of the basic tastes, suggesting the possibility of weakly clustered distribution of the taste-preference neural activities in the human insular cortex. In conclusion, the presented results suggest overlapping representations of the basic tastes in the human gustatory insular cortex.