Biology subjects

Battaglia, D. A.

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

6 recordsLinked to original sources

bioRxiv2026

Inhibitory Gain and Hub Architecture Confer Dynamic Resilience to Microcircuit Degeneration

Neurodegeneration progressively removes synapses and neurons, yet neural circuits can retain stable collective dynamics despite substantial structural loss. Which structural principles confer this resilience remained unclear. Using large-scale spiking networks spanning empirical and synthetic microcircuit architectures, we systematically compared synaptic and neuronal modes of degeneration under controlled pruning strategies. We found that resilience was not determined by connectivity loss alone, but by how inhibitory gain was embedded within circuit architecture. Networks in which inhibitory neurons occupied structurally central positions robustly maintained health-like firing rates, levels of synchrony, and informational bandwidth across degeneration stages, whereas architectures lacking such embedding exhibited amplified dynamical disruption. Across regimes, the evolution of activity was organized by a compact set of weight-aware structural descriptors that generalized across network sizes and classes, with total effective synaptic coupling providing a dominant organizing axis. These results identified inhibitory architecture as a mechanistic determinant of circuit resilience and provided a predictive framework linking structural degeneration to collective dynamics.

neuroscience↗

bioRxiv2026

Time-structured communication through cross-frequency bursts

Adaptive brain function requires communication that is selective in both space and time, yet the circuit mechanisms that transiently favor specific routes of information transfer remain unclear. Here we show that, when coupled, spiking populations with distinct inhibitory timescales can reprogram one anothers intrinsic burst preferences, generating irregular multi-frequency bursts that self-organize into Multi-Frequency Oscillatory Patterns (MFOPs). State-resolved transfer entropy revealed that different MFOPs were associated with distinct Information Routing Patterns (IRPs), defining transient windows of enhanced directed transfer with specific delays and directions. At the microscopic level, the same oscillatory states selectively increased or decreased delayed spike transmission across monosynaptic pathways, yielding transmission barcodes that significantly resembled the corresponding IRPs. This repertoire was markedly reduced when inhibitory diversity was removed. These results identify coordinated multi-frequency bursting as a mechanism by which recurrent circuits can dynamically filter inputs according to source and latency.

neuroscience↗

bioRxiv2025

The critical roaming hypothesis: arousal-driven transitions across critical lines reproduce human functional connectivity dynamics

Ongoing brain activity displays rich temporal variability associated with efficient cognition, with functional connectivity (FC) continually reconfiguring over time. The resulting functional connectivity dynamics (FCD) specifically show complex, fat-tailed statistics that alternate between persistent epochs and faster reconfiguration transients. While nonlinear whole-brain models tuned nearby a critical point have reproduced some aspects of FCD, they fall short of capturing its full temporal complexity. We propose that slow fluctuations in arousal offer a biologically plausible mechanism for exploring critical regimes in large-scale brain dynamics and thus enrich FCD. Using a connectome-based model of coupled cortical populations, we identified phase boundaries where system dynamics transition between regimes of faster or slower FCD. We then phenomenologically incorporated arousal changes, modeling them as stochastic fluctuations in key parameters such as cortical excitability, input gain, and noise amplitude. This non-autonomous formulation enables the system to roam dynamically across regime boundaries, flexibly tuning its distance from critical transition lines and producing intermittent transitions that mirror the stochastic evolution observed in empirical FCD. Fitting these models to human resting-state fMRI and performing model comparison, we find that arousal-driven models more accurately reproduce the distinctive quantitative features of FCD with the greatest improvements coming from the previously poorly accounted fat-tailed portions of the distributions. Together, these results suggest that arousal fluctuations -likely mediated by changes in neuromodulatory tone - shape the brains attractor landscape over time, expanding the repertoire of accessible functional network states and providing a mechanistic basis for the complexity of spontaneous functional dynamics.

neuroscience↗

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↗