Ährlund-Richter, S. | bioRxiv Science

bioRxiv2026

Decomposing the modulation of interactions between neuronal populations

Identifying subpopulations of neurons that interact with each other from simultaneous recordings of populations of many neurons is key for understanding across-brain communication with cellular resolution. Recent work identified communication subspaces, which capture additive interactions between pairs of high-dimensional neural populations through a small number of source and target activity patterns. However, no current method captures how a third, potentially multivariate variable - such as behavioral state or the activity of a third population - modulates these interactions. Here we extend the communication subspace framework by parameterizing modulation as a low-rank tensor. This identifies multiplicative interaction channels (MICs), defined as triplets of source, target, and modulator activity patterns, in which the modulator pattern gates the source-target interaction. We derive MICs as a bilinear perturbation of reduced-rank regression. We develop a hierarchical fitting pipeline and provide a closed-form decomposition that quantifies whether modulation reshapes the modulator-averaged baseline interaction, recruits private dimensions of one population, or opens new interactions. In simulations, MICs reliably recover the presence and geometry of ground-truth modulation even in the high-dimensional, low-sample regime. Applying MICs to simultaneous calcium imaging of prefrontal axons and interneurons in the visual cortex revealed that behavioral state asymmetrically modulates top-down interactions, reconfiguring the patterns of prefrontal projections that interact with a stable set of visual interneuron activity patterns. By providing an efficient and compact characterization of modulatory interactions, MICs enable asking new questions about how potentially high-dimensional variables shape interactions between neural populations.

neuroscience↗

bioRxiv2025

Persistent Disruptions in Prefrontal Connectivity Despite Behavioral Rescue by Environmental Enrichment in a Mouse Model of Rett Syndrome

Rett Syndrome, a neurodevelopmental disorder caused by loss-of-function mutations in the MECP2 gene, is characterized by severe motor, cognitive and emotional impairments. Some of the deficits may result from changes in cortical connections, especially downstream projections of the prefrontal cortex, which may also be targets of restoration following rearing conditions such as environmental enrichment that alleviate specific symptoms. Here, using a heterozygous Mecp2+/- female mouse model closely analogous to human Rett Syndrome, we investigated the impact of early environmental enrichment on behavioral deficits and prefrontal cortex connectivity. Behavioral analyses revealed that enriched housing rescued fine motor deficits and reduced anxiety, with enrichment-housed Mecp2+/- mice performing comparably to wild-type (WT) controls in rotarod and open field assays. Anatomical mapping of top-down anterior cingulate cortex (ACA) projections demonstrated altered prefrontal cortex connectivity in Mecp2+/- mice, with increased axonal density in the somatosensory cortex and decreased density in the motor cortex compared to WT controls. ACA axons revealed shifts in hemispheric distribution, particularly in the medial network regions, with Mecp2+/-mice exhibiting reduced ipsilateral dominance. These changes were unaffected by enriched housing, suggesting that structural abnormalities in prefrontal cortex connectivity persist despite behavioral improvements. Enriched housing rescued brain-derived neurotrophic factor (BDNF) levels in the hippocampus but failed to restore BDNF levels in the prefrontal cortex, consistent with the persistent deficits observed in prefrontal axonal projections. These findings highlight the focal nature of changes induced by reduction of MeCP2 and by exposure to environmental enrichment, and suggest that environmental enrichment starting in adolescence can alleviate behavioral deficits without reversing abnormalities in large-scale cortical connectivity.

neuroscience↗