Biology subjects

Mirasso, C. R.

Publications and source records attributed to Mirasso, C. R..

6 recordsLinked to original sources

bioRxiv2026

Structure-Constrained Intrinsic Timescales Across Tasks

Intrinsic neural timescale (INT) quantifies the persistence of spontaneous neural dynamics and offers a principled metric for characterizing brain-wide temporal organization. Although a hierarchy of INTs has been established during rest, how task engagement reconfigures this organization and how it is constrained by the structural connectome (SC) remain poorly understood. Here, we systematically mapped whole-brain INT using high-resolution fMRI data from the Human Connectome Project during rest and seven tasks spanning working memory, gambling, motor, language, social, relational, and emotion domains. Task engagement induced robust, regionally heterogeneous changes in INT while largely preserving the brain-wide temporal hierarchy across cognitive states. SC-INT coupling remained strong but consistently decreased during tasks, indicating that anatomical architecture continues to constrain INT, although its influence is attenuated under task demands. To investigate these findings mechanistically, we employed a multiscale, whole-brain neuronal-network model, which revealed that INT increase and peak within a broad critical-like regime. Strong SC-INT coupling, as observed empirically, emerged in the subcritical regime, weakened progressively with increasing network excitability, and reversed in the supercritical regime. These results demonstrate that task engagement reconfigures INTs while maintaining their hierarchical organization, suggesting that both resting and task states operate largely within a common subcritical dynamical regime.

neuroscience↗

bioRxiv2026

Deep-learning-assisted simulation of a cortical circuit: integrating anatomy, physiology and function

Mechanistic understanding of the brain requires models constrained by anatomy, physiology, and functional activity. We present a differentiable simulator and a ~67,000-neuron model of mouse primary visual cortex that integrates multimodal data, including electron-microscopy connectomics, multipatch synaptic physiology, cell-type-resolved intrinsic electrophysiology, and large-scale Neuropixels recordings from diverse cell types. End-to-end training completes on a single GPU in ~6.5 hours while preserving biological constraints. Networks trained only on brief drifting-grating responses reproduce cell-type-specific benchmarks and generalize to new contrasts and natural scenes. We uncover heterogeneous cell-type- and tuning-dependent synaptic organization and show that training preferentially sculpts inhibitory connectivity into distinct cohorts that exert outsized control over network activity. Targeted ablations show that removing biological priors on synaptic weight distributions can preserve functional activity yet disrupt emergent wiring rules. The freely shared models and code facilitate differentiable simulations as a computationally practical framework for studying brain circuit function and mechanisms under biological constraints.

neuroscience↗

bioRxiv2025

The Role of Feedforward and Feedback Inhibition in Modulating Theta-Gamma Cross-Frequency Interactions

Interactions among brain rhythms play a crucial role in organizing neuronal firing sequences during specific cognitive functions. In memory formation, the coupling between the phase of the theta rhythm and the amplitude of gamma oscillations has been extensively studied in the hippocampus. Prevailing perspectives suggest that the phase of the slower oscillation modulates the fast activity. However, recent metrics, such as Cross-Frequency Directionality (CFD), indicate that these electrophysiological interactions can be bidirectional. Using a computational model, we demonstrate that feedforward inhibition modeled by a theta-modulated ING (Interneuron Network Gamma) mechanism induces fast-to-slow interactions, while feedback inhibition through a PING (Pyramidal Interneuron Network Gamma) model drives slow-to-fast interactions. Importantly, in circuits combining both feedforward and feedback motifs, as commonly found experimentally, directionality is flexibly modulated by synaptic strength within biologically realistic ranges. A signature of this interaction is that fast-to-slow dominance in feedforward motifs is associated with gamma oscillations of higher frequency, and vice versa. Using previously acquired electrophysiological data from the hippocampus of rats freely navigating in a familiar environment or in a novel one, we show that CFD is dynamically regulated and linked to the frequency of the gamma band, as predicted by the model. Finally, the model attributes each theta-gamma interaction scheme, determined by the balance between feedforward and feedback inhibition, to distinct modes of information transmission and integration, adding computational flexibility. Our results offer a plausible neurobiological interpretation for cross-frequency directionality measurements associated with the activation of different underlying motifs that serve distinct computational needs. Author SummaryThis study investigates the interaction between various types of brain oscillations and their potential relationship with the connectivity of underlying neural networks. Brain activity encompasses slow oscillations, such as theta, alpha, and delta, as well as faster oscillations, including gamma. These oscillations interact through Cross-Frequency Coupling (CFC), a mechanism essential for cognitive processes like memory, learning, and attention. Given the higher spectral power and broader spatial propagation of slow oscillations, it has been proposed that CFC arises when slow oscillations modulate faster activity. However, recent evidence suggests that gamma oscillations can also predict the phase of slower oscillations, indicating a bidirectional and more intricate relationship. To explore this complexity, we developed a computational model that reproduces both forms of interaction observed experimentally. Our results demonstrate that while slow oscillations originating from distant regions can induce gamma activity, local connectivity and specific cell-type dynamics allow gamma oscillations to anticipate slow oscillations in certain conditions. The balance of inhibitory circuits modulates fast-slow oscillation interactions, creating distinct dynamical modes with varying computational properties and enhancing system flexibility. This work integrates competing hypotheses on oscillation interactions and offers a conceptual framework for linking these dynamics to the structural organization of neural circuits.

neuroscience↗

bioRxiv2025

NAc-DBS selectively enhances memory updating without effect on retrieval

Deep brain stimulation (DBS) has emerged as a widely used therapeutic option when pharmacological treatments prove ineffective or refractory for psychiatric patients. The nucleus accumbens (NAc) represents a frequently targeted site in DBS interventions due to its demonstrated safety profile and therapeutic efficacy in obsessive-compulsive disorder, major depression, and anorexia nervosa. However, limited mechanistic understanding hampers its broader clinical applicability. This study sought to delineate the distinct behavioural dimensions modulated by NAc-DBS, its impact on distinct facets of memory, and to elucidate the underlying brain-network mechanism of action. We developed a novel spatial navigation task for rats and employed a high-dimensional behavioural analysis complemented by fMRI to dissect the cognitive, behavioural and neurobiological effects of NAc-DBS. Active NAc-DBS produced a selective enhancement of long-term memory encoding without affecting memory recall or working memory. We found no effect of NAc-DBS on motor, appetitive or stress-related behaviours. Sustained neuronal activation in the NAc, septum, entorhinal and insular cortex demonstrated no desensitization to chronic NAc-DBS, which triggered a functional reorganization among dopaminergic-related structures. These findings suggest that NAc-DBS induces a functional reorganization in the mesocorticolimbic system, potentially mimicking a dopaminergic novelty signal to enhance memory updating. This provides a mechanistic basis for the therapeutic use of NAc-DBS, particularly in improving cognitive flexibility in psychiatric disorders.

neuroscience↗

bioRxiv2023

Competition between bottom-up visual input and internal inhibition generates error neurons in a model of the mouse primary visual cortex

The predictive coding theory, although attractive, is far from being proven. Supporters of this theory agree that bottom-up sensory inputs and top-down predictions of these inputs must be compared in certain types of neurons called error neurons. Excitatory neurons in layer 2/3 (E2/3) of the primary visual cortex (V1) are ideal candidates to act as error neurons, although how these error neurons are generated is poorly understood. In this study, we aimed to gain insight into how the genetically encoded structure of canonical microcircuits in the neocortex implements the emergence of error neurons. To this end, we used a biologically realistic computational model of V1, developed by the Allen Institute, to study the effect that sudden changes in bottom-up input had on the dynamics of E2/3 neurons. We found that the responses of these neurons can be divided into two main classes: one that depolarized (reporting positive errors; dVf neurons) and one that hyperpolarized (reporting negative errors; hVf neurons). Detailed analysis of both network and effective connectivity allowed us to uncover the mechanism that led to the dynamic segregation of these neurons. This mechanism was found to be the competition between the external visual input, originating in the thalamus, and the recurrent inhibition, originating mainly in layers 2/3 and 4. In contrast, we found no evidence of similar division and responses in excitatory infragranular neurons of layers 5 and 6. Our results are in agreement with recent experimental findings and shed light on the mechanisms responsible for the emergence of error neurons.

neuroscience↗

bioRxiv2018

Gamma oscillations coordinate different theta rhythms in the hippocampus

Hippocampal firing is organized in theta sequences controlled by internal memory-related processing and by external sensory cues. How these computations are segregated or integrated, depending on the cognitive needs, is not fully understood. Although theta activity in the hippocampus is most commonly studied as a unique coherent oscillation, it is the result of a complex interaction between different rhythm generators. Here we investigated the coordination between theta generators as a possible mechanism to couple or decouple internally and externally driven computations. We separated and quantified three different theta current generators from the hippocampus of freely behaving rats, one originating in CA3 with current sinks in CA1 str. radiatum and two with current sinks in CA1 str. lacunosum-moleculare and dentate molecular layer, mainly driven by entorhinal cortex (EC) layers 3 and 2, respectively. These theta generators followed non fully coherent dynamics and presented epochs of higher and lower phase coupling, suggesting a flexible interaction between them. Selective optogenetic inhibition in CA3 depressed the str. radiatum generator without affecting the EC-driven theta oscillations, indicating that theta rhythm generators can be modulated independently. In addition, band-specific gamma interactions with theta oscillations selectively occurred with the corresponding pathway-specific theta current generator, supporting the existence of different theta-gamma coding frameworks to organize neuronal firing in the hippocampus. Importantly, we found that epochs of highly synchronized theta rhythmicity across generators preferentially occurred during memory-guided exploration and mismatch novelty detection in familiar environments, two conditions in which internally generated memory representations need to be coordinated with the incoming sensory information about external cues. We propose a mechanism for segregating and integrating hippocampal computations based on the coexistence of different theta-gamma frameworks that flexibly couple or decouple accommodating the cognitive needs.

neuroscience↗