Biology subjects

Gutierrez-Barragan, D.

Publications and source records attributed to Gutierrez-Barragan, D..

9 recordsLinked to original sources

bioRxiv2026

Endogenous oxytocin reconfigures brainwide network dynamics toward salience-related states

Oxytocin (OXT) can exert diverse effects across social, affective and motivational domains, yet its impact on brain function at the systems level remains unclear. Here, we combine chemogenetics with fMRI and electrophysiology in mice to investigate how endogenous OXT reshapes intrinsic large-scale brain network dynamics. Using mice constitutively expressing hM3Dq DREADD receptors in OXT-releasing hypothalamic neurons, we show that chemogenetic stimulation of OXT neurons elicits widespread increases in cerebral blood volume, with prominent effects in fronto-striatal regions and dorsal hippocampal areas. This broad functional response is accompanied by a network-specific reconfiguration of brain-wide functional connectivity, characterized by increased coupling between key components of the rodent social brain, and negative functional coupling between hippocampal and fronto-cortical regions. In vivo electrophysiology under matched conditions shows concordant changes in slow (<1 Hz) and delta-band coherence across frontalthalamic and fronto-hippocampal circuits, revealing a plausible neural correlate of the observed connectivity effects. Notably, these changes are accompanied by a marked reconfiguration of the temporal architecture of fMRI network activity, with increased occupancy of co-activation states engaging saliencerelated regions and a concomitant suppression of sensory-dominated states. Together, these findings identify dynamic network-state reconfiguration as a systems-level mechanism through which endogenous OXT can tune functional communication across social-affective circuits.

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bioRxiv2024

Competitive interactions shape brain dynamics and computation across species

Adaptive cognition relies on cooperation across anatomically distributed brain circuits. However, specialised neural systems are also in constant competition for limited processing resources. How does the brains network architecture enable it to balance these cooperative and competitive tendencies? Here we use computational whole-brain modelling to examine the dynamical and computational relevance of cooperative and competitive interactions in the mammalian connectome. Across human, macaque, and mouse we show that the architecture of the models that most faithfully reproduce brain activity, consistently combines modular cooperative interactions with diffuse, long-range competitive interactions. The model with competitive interactions consistently outperforms the cooperative-only model, with excellent fit to both spatial and dynamical properties of the living brain, which were not explicitly optimised but rather emerge spontaneously. Competitive interactions in the effective connectivity produce greater levels of synergistic information and local-global hierarchy, and lead to superior computational capacity when used for neuromorphic computing. Altogether, this work provides a mechanistic link between network architecture, dynamical properties, and computation in the mammalian brain.

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bioRxiv2023

Evolutionarily conserved fMRI network dynamics in the mouse, macaque, and human brain

Evolutionarily relevant networks have been previously described in several mammalian species using time-averaged analyses of fMRI time-series. However, fMRI network activity is highly dynamic and continually evolves over timescales of seconds. Whether the dynamic organization of resting-state fMRI network activity is conserved across mammalian species remains unclear. Using frame-wise clustering of fMRI time-series, we find that intrinsic fMRI network dynamics in awake macaques and humans is characterized by recurrent transitions between a set of 4 dominant, neuroanatomically homologous fMRI coactivation modes (C-modes), three of which are also plausibly represented in the rodent brain. Importantly, in all species C-modes exhibit species-invariant dynamic features, including preferred occurrence at specific phases of fMRI global signal fluctuations, and a state transition structure compatible with infraslow coupled oscillator dynamics. Moreover, dominant C-mode occurrence reconstitutes the static organization of the fMRI connectome in all species, and is predictive of ranking of corresponding fMRI connectivity gradients. These results reveal a set of species-invariant principles underlying the dynamic organization of fMRI networks in mammalian species, and offer novel opportunities to relate fMRI network findings across the phylogenetic tree.

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bioRxiv2022

The evolution of information transmission in mammalian brain networks

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brains computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapted across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.

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bioRxiv2022

A model of the mouse cortex with attractor dynamics explains the structure and emergence of rsfMRI co-activation patterns

Resting state fMRI activity in mammals exhibits rich dynamics on a fast, frame-by-frame timescale of seconds, including the robust emergence of recurring fMRI co-activation patterns (CAPs). To understand how such dynamics emerges from the underlying anatomical cortico-cortical connectivity, we developed a whole-cortex model of resting-state fMRI activity in the mouse. Our model implemented neural input-output nonlinearities and excitatory-inhibitory interactions within cortical regions, as well as directed anatomical connectivity between regions inferred from the Allen mouse brain atlas. We found that, even if the model parameters were fitted to explain static properties of fMRI activity on the timescale of minutes, the model generated rich frame-by-frame attractor dynamics, with multiple stationary and oscillatory attractors. Guided by these theoretical predictions, we found that empirical mouse fMRI time series exhibited analogous signatures of attractor dynamics, and that model attractors recapitulated the topographical organization of empirical fMRI CAPs. The model established key relationships between attractor dynamics, CAPs and features of the directed cortico-cortical intra- and inter-hemispheric anatomical connectivity. Specifically, we found that neglecting fiber directionality severely affected the number of models attractors and their ability to explain CAPs. Furthermore, modifying inter-hemispheric anatomical connectivity strength by decreasing or increasing it from the value of real mouse anatomical data, resulted in fewer attractors generated by cortico-cortical interactions and reduced non-homotopic features of the attractors generated by the model, which were important for better predicting empirical CAPs. These results offer novel theoretical insight into the dynamic organization of resting state fMRI in the mouse brain and suggest that the frame-wise BOLD activity captured by CAPs reflects an emerging property of cortical dynamics resulting from directed cortico-cortical interactions. Author summaryWhole-brain activity at rest transitions on a timescale of seconds between stereotyped co-activation patterns (CAPs), each with a distinct spatial profile of co-activation across different brain regions. CAPs have been robustly reported across datasets and mammalian species, including humans and mice. However, the significance and origin of these patterns remain unknown. Here we studied the origin of CAPs using a computational model of the whole cortex based on real-world directed measurements of mouse cortical anatomical connectivity. We found that we could explain the formation and topography of CAPs in terms of attractors (that is, states the network tends to converge to) that reflect the information in the anatomical connections between cortical regions. Attractors and CAPs are significantly influenced by the directionality of connectivity (available in mice but not in humans) and the strength of inter-hemispheric coupling. Together, our findings provide a novel possible explanation of the mechanisms of CAP generation which relates to cortico-cortical connectivity, and suggest that CAPs are at least in part an emergent property of cortico-cortical interactions which can be generated also in absence of the action of arousing modulatory nuclei.

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bioRxiv2021

Unique spatiotemporal fMRI dynamics in the awake mouse brain

Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species, remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei, and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems, and document that its dynamic structure recapitulates distinctive, evolutionarily-relevant principles that are predictive of conscious states in higher mammalian species.

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bioRxiv2021

Microglia complement signaling promotes neuronal elimination and normal brain functional connectivity

Complement signaling is thought to serve as an opsonization signal to promote the phagocytosis of synapses by microglia. However, while its role in synaptic remodeling has been demonstrated in the retino-thalamic system, it remains unclear whether complement signaling mediates synaptic pruning in the brain more generally. Here we show that mice lacking the complement 3 receptor (C3r), the major microglia complement receptor, fail to show a deficit in either synaptic pruning or axon elimination in the developing mouse cortex. Instead, mice lacking C3r show a deficit in the perinatal elimination of neurons, both in the retina as well as in the cortex, a deficit that is associated with increased cortical thickness and enhanced functional connectivity in these regions in adulthood. These data demonstrate a preferential role for complement in promoting neuronal elimination in the developing brain and argue for a reconsideration of the role of complement in synaptic pruning.

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bioRxiv2020

Cortical silencing results in paradoxical fMRI overconnectivity

fMRI-based measurements of functional connectivity are commonly interpreted as an index of anatomical coupling and direct interareal communication. However, causal testing of this hypothesis has been lacking. Here we combine neural silencing, resting-state fMRI and in vivo electrophysiology to causally probe how inactivation of a cortical region affects brain-wide functional coupling. We find that chronic silencing of the prefrontal cortex (PFC) via overexpression of a potassium channel paradoxically increases rsfMRI connectivity between the silenced area and its thalamo-cortical terminals. Acute chemogenetic silencing of the PFC reproduces analogous patterns of overconnectivity, an effect associated with over-synchronous fMRI coupling between polymodal thalamic regions and widespread cortical districts. Notably, multielectrode recordings revealed that chemogenetic inactivation of the PFC attenuates gamma activity and increases delta power in the silenced area, resulting in robustly increased delta band coherence between functionally overconnected regions. The observation of enhanced rsfMRI coupling between chemogenetically silenced areas challenges prevailing interpretations of functional connectivity as a monotonic index of direct axonal communication, and points at a critical contribution of slow rhythm generators to the establishment of brain-wide functional coupling.

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bioRxiv2018

Oscillatory brain states govern spontaneous fMRI network dynamics

Spontaneous brain activity as assessed with resting-state fMRI exhibits rich spatiotemporal structure. However, the principles by which brain-wide patterns of spontaneous fMRI activity reconfigure and interact with each other, remain unclear. We devised a frame-wise clustering approach to map spatiotemporal dynamics of spontaneous fMRI activity with voxel resolution in the resting mouse brain. We show that brain-wide patterns of fMRI co-activation can be reliably mapped at the group and subject level, defining a restricted set of recurring brain states characterized by rich network structure. We document that these functional states are characterized by contrasting patterns of spontaneous fMRI activity and exhibit coupled oscillatory dynamics, with each state occurring at specific phases of global fMRI signal fluctuations. Finally, we show that autism-associated genetic alterations result in the engagement of non-canonical brain states and altered coupled oscillatory dynamics. Our approach reveals a new set of fundamental principles guiding the spatiotemporal organization of resting state fMRI activity, and its disruption in brain disorders.

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