Biology subjects

Sanchez-Vives, M. V.

Publications and source records attributed to Sanchez-Vives, M. V..

13 recordsLinked to original sources

bioRxiv2025

Thermodynamics of consciousness: A non-invasive perturbational framework

The quest for reliable and objective measures of consciousness is critical in basic and clinical neuroscience. Across species, the Perturbational Complexity Index (PCI) has emerged as a robust empirical marker by directly perturbing the brain, yet its underlying principles of physics are not fully understood. Here, we bridge this gap by introducing a non-invasive framework based on generative whole-brain models of non-equilibrium brain dynamics. Using these models, we identified violations of the Fluctuation-Dissipation Theorem (FDT) in humans and rodents across wakefulness, anesthesia, and disorders of consciousness. Mirroring the patterns observed with PCI, we found decreased FDT violations in unresponsive disorders of consciousness and anesthesia compared to conscious conditions. This reveals a close link between PCI and non-equilibrium dynamics in spontaneous brain signals, grounding PCI in fundamental principles of physics. Overall, this framework offers new complementary, non-invasive, model-based avenues for understanding the nature of consciousness and for developing objective tools to assess its loss and recovery in health and disease. It also provides a principled foundation for discovering novel strategies to restore consciousness.

neuroscience↗

bioRxiv2025

Slow waves generation and propagation in a model of brain lesions

Slow waves (SWs), the hallmark of non-rapid eye movement (NREM) sleep, reflect the periodic occurrence of transient silent periods in cortical neurons (Down states). During NREM, SWs and Down states physiologically disrupt large-scale network interactions. Since early EEG studies, SWs have also been observed in awake patients after brain injury. Emerging evidence indicates that these intrusions of sleep-like activity interfere with ongoing network activity and contribute to motor and cognitive deficits; yet, the mechanisms governing the generation and spread of post-lesional SWs remain unclear. Here, we extend a neural mass model of EEG to capture transitions between wake-like and sleep-like dynamics and embed it in connectome-based networks with virtual lesions. This model supports that local disfacilitation, topology-dependent propagation, and synchrony-dependent amplification throughout the connectome are sufficient to produce post-lesional SWs. These mechanisms reproduce the spatial gradients of post-lesional SWs seen in patients and identify actionable targets for neuromodulation and rehabilitation.

neuroscience↗

bioRxiv2025

Cholinergic heterogeneity facilitates synchronization and information flow in a whole-brain model

The human brain displays substantial regional variability in molecular, anatomical, and physiological organization. Yet, how this heterogeneity shapes large-scale neuronal dynamics remains poorly understood. To address this question, we employed a biologically informed whole-brain computational model capable of generating distinct brain states, from awake-like to sleep-like regimes. Our model was constrained by empirical human structural connectivity and spatial maps of cholinergic receptor gene expression, thereby embedding regional neuromodulatory variability into a macroscopic framework. We found that incorporating cholinergic heterogeneity had a significant impact on brain dynamics: it not only facilitated network synchronization but also enhanced information flow between brain regions. Furthermore, we addressed a particularly intricate dynamic regime characterized by the coexistence of localized sleep-like activity within otherwise awake-like states. We showed that the emergence of these slow waves was a byproduct of both regional levels of neuronal adaptation and structural connectivity. In summary, our findings highlight the critical role of molecular and anatomical heterogeneity in shaping global brain dynamics, suggesting new avenues for linking microscale diversity to macroscale function.

neuroscience↗

bioRxiv2024

Magnetoelectric Microrobots for Spinal Cord Injury Regeneration

Regenerative medicine continually seeks effective methods to address spinal cord injuries (SCI), which are known for their limited regenerative potential. Despite advances in neural progenitor cell (NPC) transplants for spinal cord injuries, challenges related to graft survival, reliable in vivo differentiation, and neural integration significantly hinder real functional recovery and limit clinical outcomes. This study introduces NPCbots, biohybrid microrobots engineered by integrating human-induced pluripotent stem cell-derived NPCs with magnetoelectric nanoparticles composed of cobalt ferrite-barium titanate. These enable magnetic navigation and neuronal stimulation, enhancing targeted therapeutic interventions. Our lab-on-a-chip system allows for the mass production of NPCbots, ensuring their differentiation and biocompatibility. Remarkably, in a zebrafish model of SCI, NPCbots stimulated by an alternating magnetic field demonstrated rapid in vivo differentiation and integration into damaged neural pathways, significantly enhancing neural regeneration. Within three days, injured zebrafish treated with NPCbots exhibited almost normal swimming behavior and significantly improved exploratory behavior, showcasing the potential of NPCbots to swiftly repair neural structures and restore the central nervous systems functionality in spinal cord injury models through non-invasive means. Additionally, precise in vitro and in vivo manipulation of NPCbots indicates their broader application in various neurodegenerative disorders, offering a promising route for effective spinal cord and neurological recovery.

neuroscience↗

bioRxiv2024

H-current modulation of cortical Up and Down states

Understanding the link between cellular processes and brain function remains a key challenge in neuroscience. One crucial aspect is the interplay between specific ion channels and network dynamics. This work reveals a role for h-current, a hyperpolarization-activated cationic current, in shaping cortical slow oscillations. Cortical slow oscillations exhibit rhythmic periods of activity (Up states) alternating with silent periods (Down states). By progressively reducing h-current in both cortical slices and in a computational model, we observed Up states transformed into prolonged plateaus of sustained firing, while Down states were also significantly extended. This transformation led to a five-fold reduction in oscillation frequency. In a biophysical recurrent network model, we identified the cellular mechanisms: an increased input resistance and membrane time constant, increasing neuronal responsiveness to even weak inputs. HCN channels, the molecular basis of h-current, are known neuromodulatory targets, suggesting potential pathways for dynamic control of brain rhythms.

neuroscience↗

bioRxiv2021

Multiscale dynamics underlying neocortical slow oscillations

Slow oscillations in the sleeping and anesthetized brain invariantly emerge as an alternation between Up (high firing) and Down (almost quiescent) states. In cortex, they occur simultaneously in cell assemblies in different layers and propagate as traveling waves, a concerted activity at multiple scales whose interplay and role is still under debate. Slow oscillations have been reported to start in deep layers, more specifically in layer 5. Here, we studied the laminar organization of slow oscillations in the anesthetized rat cortex and we found that the activity leading to Up states actually initiates in layer 6, then spreads towards upper layers. Layer 5 cell assemblies have a threshold-like activation that can persist after layer 6 inactivation, giving rise to hysteresis loops like in "flip-flop" computational units. We found that such hysteresis is finely tuned by the columnar circuitry depending on the recent history of the local ongoing activity. Furthermore, thalamic inactivation reduced infragranular excitability without affecting the columnar activation pattern. We propose a role for layer 6 acting as a hub unraveling a hierarchy of cortical loops.

neuroscience↗

bioRxiv2021

Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia

During sleep and anesthesia, large groups of neurons throughout the entire cortex activate rhythmically producing wavefronts of activity referred to as slow-wave activity (SWA). In the arousal process, the brain restores its integrative and complex activity. The network mechanisms underlying this global state transition remain however to be elucidated. Here we investigated the network features shaping the SWA under fading anesthesia. Using electrocorticographical recordings of wide cortical areas of the mouse brain, we developed a quantitative measure of the anesthesia level based on slow-wave frequency and complexity. At deep anesthesia, we document a stringent alternation of posterior-anterior-posterior modes of propagation. With fading anesthesia, SWA evolves to produce a plethora of metastable spatiotemporal patterns. A network model of spiking neurons reproduced the data using short-range connectivity, subcortical input and a local activity-dependent adaptation. The emergence from deep anesthesia does not require modifying the connectivity, but small changes in the local excitability of cortical cell assemblies, further supporting the hypothesis of a tight bound between scales in the brain.

neuroscience↗

bioRxiv2019

Modulation of cortical slow oscillatory rhythm by GABAB receptors: an experimental and computational study

Slow wave oscillations (SWO) dominate cortical activity during deep sleep, anesthesia and in some brain lesions. SWO consist of Up states or periods of activity interspersed with Down states or periods of silence. The rhythmicity expressed during SWO integrates neuronal and connectivity properties of the network and it is often altered in neurological pathological conditions. Different mechanisms have been proposed to drive the transitions between Up and Down states, in particular, adaptation mechanisms have been proposed to contribute to the Up-to-Down transition. Synaptic inhibition, and specially GABAB receptors, have also been proposed to have a role in the termination of Up states. The interplay between these two potential mechanisms, adaptation and inhibition, is not well understood and the role of slow inhibition is not yet clear regarding the full cycle of the slow oscillatory rhythm. Here we contribute to its understanding by combining experimental and computational techniques. GABAB receptors-blockade not only elongated Up states, but also affected the subsequent Down states, and thus the whole cycle of the oscillations. Furthermore, while adaptation tends to yield a rather regular behavior, GABAB receptors-blockade decreased the variability of the sequence of Up and Down states. Interestingly, variability changes could be accomplished in two different ways: either accompanied by a shortening or by a lengthening of the duration of the Down state. Even when the most common observation is the lengthening of the Down states, both changes are expressed experimentally and also in numerical simulations. Our simulations suggest that the sluggishness of GABAB receptors to follow the excitatory fluctuations of the cortical network can explain these different network dynamics modulated by GABAB receptors.

neuroscience↗

bioRxiv2019

Control of brain state transitions with light

Behavior is driven by specific neuronal activity and can be directly associated with characteristic brain states. The oscillatory activity of neurons contains information about the mental state of an individual, and the transition between physiological brain states is largely controlled by neuromodulators. Manipulating neural activity, brain rhythms or synchronization is of significant therapeutic interest in several neurological disorders and can be achieved by different means such as transcranial current and magnetic stimulation techniques, and by light through optogenetics, although the clinical translation of the latter is hampered by the need of gene therapy. Here, we directly modulate brain rhythms with light using a novel photoswitchable muscarinic agonist. Synchronous slow wave activity is transformed into a higher frequency pattern in the cerebral cortex both in slices in vitro and in anesthetized mice. These results open the way to the study of the neuromodulation and control of spatiotemporal patterns of activity and pharmacology of brain states, their transitions, and their links to cognition and behavior, in different organisms without requiring any genetic manipulation.

neuroscience↗

bioRxiv2019

Agency and responsibility over virtual movements controlled through different paradigms of brain-computer interface

Agency is the attribution of an action to the self and is a prerequisite for experiencing responsibility over its consequences. Here we investigated agency and responsibility by studying the control of movements of an embodied avatar, via brain computer interface (BCI) technology, in immersive virtual reality. After induction of virtual body ownership by visuomotor correlations, healthy participants performed a motor task with their virtual body. We compared the passive observation of the subjects own virtual arm performing the task with (1) the control of the movement through activation of sensorimotor areas (motor imagery) and (2) the control of the movement through activation of visual areas (steady-state visually evoked potentials). The latter two conditions were carried out using a brain-computer interface (BCI) and both shared the intention and the resulting action. We found that BCI-control of movements engenders the sense of agency, which is strongest for sensorimotor areas activation. Furthermore, increased activity of sensorimotor areas, as measured using EEG, correlates with levels of agency and responsibility. We discuss the implications of these results for the neural bases of agency, but also in the context of novel therapies involving BCI and the ethics of neurotechnology.\n\nKey points summaryO_LIWe induced embodiment of a virtual body and its movements were controlled by two different BCI paradigms - one based on signals from sensorimotor versus one from visual cortical areas.\nC_LIO_LIBCI-control of movements engenders agency, but not equally for all paradigms.\nC_LIO_LICortical sensorimotor activation correlates with agency and responsibility.\nC_LIO_LIThis has significant implications for neurological rehabilitation and neuroethics.\nC_LI

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bioRxiv2019

Attractor competition enriches cortical dynamics during awakening from anesthesia

Cortical slow oscillations ([lsim] 1 Hz) are a hallmark of slow-wave sleep and deep anesthesia across animal species. They arise from spatiotemporal patterns of activity with low degree of complexity, eventually increasing as wakefulness is approached and cognitive functions emerge. The arousal process is then an open window on the widely unknown mechanisms underlying the emergence of the dynamical richness of awake cortical networks. Here, we investigated the changes in the network dynamics as anesthesia fades out and wakefulness is approached in layer 5 neuronal assemblies of the rat visual cortex. Far from being a continuum, this transition displays both gradual and abrupt activity changes. Starting from deep anesthesia, slow oscillations increase their frequency eventually expressing maximum regularity. This stage is followed by the abrupt onset of an infra-slow (~ 0.2 Hz) alternation between sleep-like oscillations and activated states. A population rate model reproduces this transition driven by an increased excitability that brings it to periodically cross a critical point. We conclude that dynamical richness emerges as a competition between two metastable attractor states whose existence is here experimentally confirmed.

neuroscience↗

bioRxiv2018

First person experience of threat modulates cortical network encoding human peripersonal space

Peripersonal space is the area directly surrounding the body, which supports object manipulation and social interaction, but is also critical for threat detection. In the monkey, ventral premotor and intraparietal cortex support initiation of defensive behavior. However, the brain network that underlies threat detection in human peripersonal space still awaits investigation. We combined fMRI measurements with a preceding virtual reality training from either first or third person perspective to manipulate whether approaching human threat was perceived as directed to oneself or another. We found that first person perspective increased body ownership and identification with the virtual victim. When threat was perceived as directed towards oneself, synchronization of brain activity in the human peripersonal brain network was enhanced and connectivity increased from premotor and intraparietal cortex towards superior parietal lobe. When this threat was nearby, synchronization also occurred in emotion-processing regions. Priming with third person perspective reduced synchronization of brain activity in the peripersonal space network and increased top-down modulation of visual areas. In conclusion, our results showed that after first person perspective training peripersonal space is remapped to the virtual victim, thereby causing the fronto-parietal network to predict intrusive actions towards the body and emotion-processing regions to signal nearby threat.

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bioRxiv2018

Modulation of slow and fast oscillations by direct current stimulation in the cerebral cortex in vitro

Non-invasive brain stimulation techniques, such as transcranial direct current stimulation (tDCS), play a growing role in the treatment of neurological disorders. However, the mechanisms by which electric fields modulate cortical network activity are only partially understood. To explore the spatiotemporal modulation of cortical activity by electric fields (DC fields), we exposed neocortical slices to constant fields of varying intensity and direction and we measured their effect on the low (<1 Hz) and high frequencies (beta 15-30 Hz and gamma 30-90 Hz) of spontaneously generated cortical oscillations. Slow oscillations consist of Up (active) and Down (silent) states. We found that DC fields ranging from -6 to +6 V/m induced an exponential increase in the frequency of slow oscillations through the regulation of the excitability and duration of Down states, while hardly affecting Up states duration. A computational model based on the mean-field theory of attractor dynamics provided a mechanistic and quantitative description of the network dynamics underlying such precise modulation of slow oscillatory frequency. The modulation of high frequencies by DC fields was less consistent, the high frequency power varying with the intensity of the fields only in a fraction of slices. Interestingly, negative DC fields of increasing intensities progressively and effectively reversed the increase in high frequency power induced by kainate application. Our findings have implications for the understanding of cortical oscillations and the mechanisms by which they are modulated by DC fields and may contribute to the future development of tools with an accurate spatiotemporal control of cortical activity.\n\nSignificance statementActing on the brain through electrical stimulation in order to correct dysfunctions or to induce functional recovery is a relatively common technique nowadays used in the clinical realm. In spite of the existence of previous studies on the effect of electric fields on neuronal and network physiology, questions regarding the mechanisms underlying exogenous electrical modulation of cortical dynamics still remain open. We demonstrate that continuous electric fields between -6 and +6 V/m induce a precise modulation of slow and fast cortical rhythms. Based on both experimental evidence and theoretical analysis, we describe some of the mechanistic underpinnings at play and provide useful information for the development of tools with better spatiotemporal control of cortical activity.

neuroscience↗