Ferreira, R. F. | bioRxiv Science

bioRxiv2026

Hypothalamic asymmetry in hemisphere-specific neuroendocrine signaling

Brain lesions classically cause contralateral sensorimotor and postural deficits, attributed to the decussation of descending neural pathways. However, recent findings reveal that, beyond neural mechanisms, contralateral effects can also be mediated by the neuroendocrine system via humoral pathways. This raises the possibility that the brain regulates left- and right-sided peripheral processes through hypothalamic neurohormones released into the bloodstream. For such spatially targeted endocrine signaling to occur, hemisphere-specific neural activity must be encoded into side-specific hormonal output--requiring a lateralized organization of hypothalamic neuroendocrine systems. Here, we report molecular asymmetries in the rat hypothalamus that support this mechanism. Transcriptomic analysis revealed asymmetric expression of eleven neurohormonal genes, including Gnrh1, Cck, and Trh, along with distinct left-right side-specific gene co-expression networks. Chemogenetic stimulation of Arg-vasopressin neurons in vasopressin-hM3Dq-mCherry transgenic rats produced generalized changes in these networks--predominantly in the right hypothalamus--suggesting that hypothalamic neurohormonal circuits function as integrated, lateralized ensembles. Stereological analysis revealed asymmetric coordination of vasopressin neurons within the paraventricular nucleus, with the left rostral region decoupled from the right rostral and caudal subregions. Functionally, gonadotropin-releasing hormone, cholecystokinin-8, and thyrotropin-releasing hormone--administered intracisternally in rats with complete spinal cord transection--elicited side-specific peripheral responses, measured as hindlimb postural asymmetry in a binary left-right output model. These neurohormonal effects were therefore transmitted via the humoral route. These findings suggest that multiple hypothalamic neurohormones and their integrated networks are asymmetrically organized, and that their lateralization may be necessary for hemisphere-specific hormonal regulation of peripheral systems.

neuroscience↗

bioRxiv2024

Astrocytic Signatures in Neuronal Activity: A Machine Learning-Based Identification Approach

This study investigates the expanding role of astrocytes, the predominant glial cells, in brain function, focusing on whether and how their presence influences neuronal network activity. We focus on particular network activities identified as synchronous and asynchronous. Using computational modeling to generate synthetic data, we examine these network states and find that astrocytes significantly affect synaptic communication, mainly in synchronous states. We use different methods of extracting data from a network and compare which is best for identifying glial cells, with mean firing rate emerging with higher accuracy. To reach the aforementioned conclusions, we applied various machine learning techniques, including Decision Trees, Random Forests, Bagging, Gradient Boosting, and Feedforward Neural Networks, the latter outperforming other models. Our findings reveal that glial cells play a crucial role in modulating synaptic activity, especially in synchronous networks, highlighting potential avenues for their detection with machine learning models through experimental accessible measures.

neuroscience↗