Biology subjects

Battaglia, D. A.

Publications and source records attributed to Battaglia, D. A..

3 recordsLinked to original sources

bioRxiv2025

Optimal inhibitory-to-excitatory ratio governs slow and fast oscillations for enhanced neural communication

Neural oscillations at distinct frequency bands facilitate communication within and between neural populations. While single-frequency oscillations are well-characterized, the simultaneous emergence of slow (beta) and fast (gamma) oscillations within the same network remains unclear. Here, we demon-strate that multi-frequency oscillations naturally arise when the ratio of inhibitory-to-excitatory synaptic strength falls within a specific regime using a biologically plausible Izhikevich model. We show that this regime maximizes both information capacity and transmission efficiency, suggesting an optimal balance for neural communication. Deviations from this range lead to single-frequency oscillations and reduced communication efficiency, mirroring disruptions observed in neurological disorders. These findings provide mechanistic insight into how the brain leverages multiple oscillatory frequencies for efficient information processing and suggest a potential biomarker for impaired neural communication. 1. SIGNIFICANCE STATEMENTBeta (slow) and gamma (fast) oscillations often coexist in the brain, yet their origin and functional role remain unclear. Our study reveals that the inhibitory-to-excitatory synaptic strength ratio governs the emergence of this multifrequency state. Furthermore, we demonstrate that information capacity and transmission efficiency are maximized in this regime, leading to significantly enhanced neural communication. These findings provide mechanistic insight into how multiple oscillatory frequencies support efficient brain function and offer a potential framework for understanding disruptions in neural communication associated with neurological disorders.

neuroscience↗

bioRxiv2025

The Topological Architecture of Brain Identity

Accurately identifying individuals from brain activity--functional fingerprinting--is a powerful tool for understanding individual variability and detecting brain disorders. Most current approaches rely on functional connectivity (FC), which measures pairwise correlations between brain regions. However, FC is limited in capturing the higher-order, multiscale structure of brain organization. Here, we propose a novel fingerprinting method based on homological scaffolds, a topological repre-sentation derived from persistent homology of resting-state fMRI data. Using data from the Human Connectome Project (n = 100), we show that scaffold-based fingerprints achieve near-perfect identification accuracy ([~] 100%), outperforming FC-based methods (90%), and remain robust across preprocessing pipelines, atlas choices, and even with drastically shortened scan durations. Unlike FC, in which fingerprinting features localize within networks, scaffolds derive their discriminative power from inter-network connections, revealing the existence of individual mesoscale organizational signatures. Finally, we show that scaffolds bridge redundancy and synergy by balancing redundant information along high-FC border edges with synergistic interactions across the topological voids they enclose. These findings establish topological scaffolds as a powerful tool for capturing individual variability, revealing that unique signatures of brain organization are encoded in the interplay between mesoscale network integration and information dynamics.

neuroscience↗

bioRxiv2024

40 Hz light stimulation restores early brain dynamics alterations and associative memory in Alzheimer's disease model mice

Visual gamma entrainment using sensory stimuli (vGENUS) is a promising non-invasive therapeutic approach for Alzheimers disease (AD), showing efficacy in improving memory function. However, its mechanisms of action remain poorly understood. Using young AppNL-F/MAPT double knock-in (dKI) mice, a model of early AD, we examined brain dynamics alterations before amyloid plaque onset. High-density EEG recordings and novel metrics from fields outside neuroscience were used to assess brain dynamics fluidity--a measure of the brains ability to transition between activity states. We revealed that dKI mice exhibit early, awake state-specific reductions in brain dynamics fluidity associated with cognitive deficits in complex memory tasks. Daily vGENUS sessions over two weeks restored brain dynamics fluidity and rescued memory deficits in dKI mice. Importantly, these effects built up during the stimulation protocol and persisted after stimulation ended, suggesting long-term modulation of brain function. Based on these results, we propose a "brain dynamics repair" mechanism for vGENUS that goes beyond current amyloid-centric hypotheses. This dual insight - that brain dynamics are both a target for repair and a potential diagnostic tool - provides new perspectives on early Alzheimers disease pathophysiology. Significance StatementGamma ENtrainment Using Sensory stimuli (GENUS), involving 40 Hz rhythmic sensory stimulation, shows promise in improving memory function in Alzheimers disease (AD). We hypothesized that brain dynamics changes could be detected before plaque onset and modulated by vGENUS. Applying techniques from climate science to EEG recordings in young AD model mice, we found reduced brain dynamics fluidity associated with early cognitive deficits. Two weeks of vGENUS restored brain dynamics and improved memory, with effects persisting post-treatment. These findings challenge the amyloid-centric view of AD, introduce a potential early biomarker, and suggest vGENUS acts by "repairing" brain dynamics. Our approach offers new perspectives on early diagnosis and non-invasive interventions for AD and other neurological disorders with disrupted brain dynamics.

neuroscience↗