Loss of Snord116 alters cortical neuronal activity in mice: a preclinical investigation of Prader-Willi syndrome.

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder that is characterized by metabolic alteration and sleep abnormalities mostly related to rapid eye movement (REM) sleep disturbances. The disease is caused by genomic imprinting defects that are inherited through the paternal line. Among the genes located in the PWS region on chromosome 15 (15q11-q13), small nucleolar RNA 116 (Snord116) has been previously associated with intrusions of REM sleep into wakefulness in humans and mice. Here, we further explore sleep regulation of PWS by reporting a study with PWScrm+/p- mouse line, which carries a paternal deletion of Snord116. We focused our study on both macrostructural electrophysiological components of sleep, distributed among REMs and nonrapid eye movements. Of note, here, we study a novel electroencephalography (EEG) graphoelements of sleep for mouse studies, the well-known spindles. EEG biomarkers are often linked to the functional properties of cortical neurons and can be instrumental in translational studies. Thus, to better understand specific properties, we isolated and characterized the intrinsic activity of cortical neurons using in vitro microelectrode array. Our results confirm that the loss of Snord116 gene in mice influences specific properties of REM sleep, such as theta rhythms and, for the first time, the organization of REM episodes throughout sleep-wake cycles. Moreover, the analysis of sleep spindles present novel specific phenotype in PWS mice, indicating that a new catalog of sleep biomarkers can be informative in preclinical studies of PWS.

Entrainment of Network Activity by Closed-Loop Microstimulation in Healthy Ambulatory Rats.

As our understanding of volitional motor function increases, it is clear that complex movements are the result of the interactions of multiple cortical regions rather than just the output properties of primary motor cortex. However, our understanding of the interactions among these regions is limited. In this study, we used the activity-dependent stimulation (ADS) technique to determine the short/long-term effects on network activity and neuroplasticity of intracortical connections. ADS uses the intrinsic neural activity of one region to trigger stimulations in a separate region of the brain and can manipulate neuronal connectivity in vivo. Our aim was to compare single-unit neuronal activity within premotor cortex (rostral forelimb area, [RFA] in rats) in response to ADS (triggered from RFA) and randomly-generated stimulation in the somatosensory area (S1) within single sessions and across 21 consecutive days of stimulation. We examined firing rate and correlation between spikes and stimuli in chronically-implanted healthy ambulatory rats during spontaneous and evoked activity. At the end of the treatment, we evaluated changes of synaptophysin expression. Our results demonstrated the ability of ADS to modulate RFA firing properties and to promote synaptogenesis in S1, strengthening the idea that this Hebbian-inspired protocol can be used to modulate cortical connectivity.

Investigating the spectral features of the brain meso-scale structure at rest.

Recent studies provide novel insights into the meso-scale organization of the brain, highlighting the co-occurrence of different structures: classic assortative (modular), disassortative, and core-periphery. However, the spectral properties of the brain meso-scale remain mostly unexplored. To fill this knowledge gap, we investigated how the meso-scale structure is organized across the frequency domain. We analyzed the resting state activity of healthy participants with source-localized high-density electroencephalography signals. Then, we inferred the community structure using weighted stochastic block-model (WSBM) to capture the landscape of meso-scale structures across the frequency domain. We found that different meso-scale modalities co-exist and are diversely organized over the frequency spectrum. Specifically, we found a core-periphery structure dominance, but we also highlighted a selective increase of disassortativity in the low frequency bands (<8 Hz), and of assortativity in the high frequency band (30-50 Hz). We further described other features of the meso-scale organization by identifying those brain regions which, at the same time, (a) exhibited the highest degree of assortativity, disassortativity, and core-peripheriness (i.e., participation) and (b) were consistently assigned to the same community, irrespective from the granularity imposed by WSBM (i.e., granularity-invariance). In conclusion, we observed that the brain spontaneous activity shows frequency-specific meso-scale organization, which may support spatially distributed and local information processing.

Modulation of neural oscillations during working memory update, maintenance, and readout: An hdEEG study.

Working memory (WM) performance is very often measured using the n-back task, in which the participant is presented with a sequence of stimuli, and required to indicate whether the current stimulus matches the one presented n steps earlier. In this study, we used high-density electroencephalography (hdEEG) coupled to source localization to obtain information on spatial distribution and temporal dynamics of neural oscillations associated with WM update, maintenance and readout. Specifically, we a priori selected regions from a large fronto-parietal network, including also the insula and the cerebellum, and we analyzed modulation of neural oscillations by event-related desynchronization and synchronization (ERD/ERS). During update and readout, we found larger θ ERS and smaller ß ERS respect to maintenance in all the selected areas. γLOW and γHIGH bands oscillations decreased in the frontal and insular cortices of the left hemisphere. In the maintenance phase we observed decreased θ oscillations and increased ß oscillations (ERS) in most of the selected posterior areas and focally increased oscillations in γLOW and γHIGH bands in the frontal and insular cortices of the left hemisphere. Finally, during WM readout, we also found a focal modulation of the γLOW band in the left fusiform cortex and cerebellum, depending on the response trial type (true positive vs. true negative). Overall, our study demonstrated specific spectral signatures associated with updating of memory information, WM maintenance, and readout, with relatively high spatial resolution.

Differential Effects of Open- and Closed-Loop Intracortical Microstimulation on Firing Patterns of Neurons in Distant Cortical Areas.

Intracortical microstimulation can be used successfully to modulate neuronal activity. Activity-dependent stimulation (ADS), in which action potentials recorded extracellularly from a single neuron are used to trigger stimulation at another cortical location (closed-loop), is an effective treatment for behavioral recovery after brain lesion, but the related neurophysiological changes are still not clear. Here, we investigated the ability of ADS and random stimulation (RS) to alter firing patterns of distant cortical locations. We recorded 591 neuronal units from 23 Long-Evan healthy anesthetized rats. Stimulation was delivered to either forelimb or barrel field somatosensory cortex, using either RS or ADS triggered from spikes recorded in the rostral forelimb area (RFA). Both RS and ADS stimulation protocols rapidly altered spike firing within RFA compared with no stimulation. We observed increase in firing rates and change of spike patterns. ADS was more effective than RS in increasing evoked spikes during the stimulation periods, by producing a reliable, progressive increase in stimulus-related activity over time and an increased coupling of the trigger channel with the network. These results are critical for understanding the efficacy of closed-loop electrical microstimulation protocols in altering activity patterns in interconnected brain networks, thus modulating cortical state and functional connectivity.

Investigating the impact of electrical stimulation temporal distribution on cortical network responses.

BACKGROUND: The brain is continuously targeted by a wealth of stimuli with complex spatio-temporal patterns and has presumably evolved in order to cope with those inputs in an optimal way. Previous studies investigating the response capabilities of either single neurons or intact sensory systems to external stimulation demonstrated that stimuli temporal distribution is an important, if often overlooked, parameter. RESULTS: In this study we investigated how cortical networks plated over micro-electrode arrays respond to different stimulation sequences in which inter-pulse intervals followed a 1/f ß distribution, for different values of ß ranging from 0 to ∞. Cross-correlation analysis revealed that network activity preferentially synchronizes with external input sequences featuring ß closer to 1 and, in any case, never for regular (i.e. fixed-frequency) stimulation sequences. We then tested the interplay between different average stimulation frequencies (based on the intrinsic firing/bursting frequency of the network) for two selected values of ß, i.e. 1 (scale free) and ∞ (regular). In general, we observed no preference for stimulation frequencies matching the endogenous rhythms of the network. Moreover, we found that in case of regular stimulation the capability of the network to follow the stimulation sequence was negatively correlated to the absolute stimulation frequency, whereas using scale-free stimulation cross-correlation between input and output sequences was independent from average input frequency. CONCLUSIONS: Our results point out that the preference for a scale-free distribution of the stimuli is observed also at network level and should be taken into account in designing more efficient protocols for neuromodulation purposes.

Modulation of Neural Network Activity through Single Cell Ablation: An in Vitro Model of Minimally Invasive Neurosurgery.

The technological advancement of optical approaches, and the growth of their applications in neuroscience, has allowed investigations of the physio-pathology of neural networks at a single cell level. Therefore, better understanding the role of single neurons in the onset and progression of neurodegenerative conditions has resulted in a strong demand for surgical tools operating with single cell resolution. Optical systems already provide subcellular resolution to monitor and manipulate living tissues, and thus allow understanding the potentiality of surgery actuated at single cell level. In the present work, we report an in vitro experimental model of minimally invasive surgery applied on neuronal cultures expressing a genetically encoded calcium sensor. The experimental protocol entails the continuous monitoring of the network activity before and after the ablation of a single neuron, to provide a robust evaluation of the induced changes in the network activity. We report that in subpopulations of about 1000 neurons, even the ablation of a single unit produces a reduction of the overall network activity. The reported protocol represents a simple and cost effective model to study the efficacy of single-cell surgery, and it could represent a test-bed to study surgical procedures circumventing the abrupt and complete tissue removal in pathological conditions.

In vitro studies of neuronal networks and synaptic plasticity in invertebrates and in mammals using multielectrode arrays.

Brain functions are strictly dependent on neural connections formed during development and modified during life. The cellular and molecular mechanisms underlying synaptogenesis and plastic changes involved in learning and memory have been analyzed in detail in simple animals such as invertebrates and in circuits of mammalian brains mainly by intracellular recordings of neuronal activity. In the last decades, the evolution of techniques such as microelectrode arrays (MEAs) that allow simultaneous, long-lasting, noninvasive, extracellular recordings from a large number of neurons has proven very useful to study long-term processes in neuronal networks in vivo and in vitro. In this work, we start off by briefly reviewing the microelectrode array technology and the optimization of the coupling between neurons and microtransducers to detect subthreshold synaptic signals. Then, we report MEA studies of circuit formation and activity in invertebrate models such as Lymnaea, Aplysia, and Helix. In the following sections, we analyze plasticity and connectivity in cultures of mammalian dissociated neurons, focusing on spontaneous activity and electrical stimulation. We conclude by discussing plasticity in closed-loop experiments.

A transparent organic transistor structure for bidirectional stimulation and recording of primary neurons.

Real-time stimulation and recording of neural cell bioelectrical activity could provide an unprecedented insight in understanding the functions of the nervous system, and it is crucial for developing advanced in vitro drug screening approaches. Among organic materials, suitable candidates for cell interfacing can be found that combine long-term biocompatibility and mechanical flexibility. Here, we report on transparent organic cell stimulating and sensing transistors (O-CSTs), which provide bidirectional stimulation and recording of primary neurons. We demonstrate that the device enables depolarization and hyperpolarization of the primary neuron membrane potential. The transparency of the device also allows the optical imaging of the modulation of the neuron bioelectrical activity. The maximal amplitude-to-noise ratio of the extracellular recording achieved by the O-CST device exceeds that of a microelectrode array system on the same neuronal preparation by a factor of 16. Our organic cell stimulating and sensing device paves the way to a new generation of devices for stimulation, manipulation and recording of cell bioelectrical activity in vitro and in vivo.

Connectivity, excitability and activity patterns in neuronal networks.

Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFPi,j) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFPi,j with the autocorrelation of i (i.e. CFPi,i), to obtain the single pulse response (SPRi,j)-the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression.

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function.

Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.

Electrical and chemical modulation of homogeneous and heterogeneous human-iPSCs-derived neuronal networks on high density arrays.

The delicate "Excitatory/Inhibitory balance" between neurons holds significance in neurodegenerative and neurodevelopmental diseases. With the ultimate goal of creating a faithful in vitro model of the human brain, in this study, we investigated the critical factor of heterogeneity, focusing on the interplay between excitatory glutamatergic (E) and inhibitory GABAergic (I) neurons in neural networks. We used high-density Micro-Electrode Arrays (MEA) with 2304 recording electrodes to investigate two neuronal culture configurations: 100% glutamatergic (100E) and 75% glutamatergic / 25% GABAergic (75E25I) neurons. This allowed us to comprehensively characterize the spontaneous electrophysiological activity exhibited by mature cultures at 56 Days in vitro, a time point in which the GABA shift has already occurred. We explored the impact of heterogeneity also through electrical stimulation, revealing that the 100E configuration responded reliably, while the 75E25I required more parameter tuning for improved responses. Chemical stimulation with BIC showed an increase in terms of firing and bursting activity only in the 75E25I condition, while APV and CNQX induced significant alterations on both dynamics and functional connectivity. Our findings advance understanding of diverse neuron interactions and their role in network activity, offering insights for potential therapeutic interventions in neurological conditions. Overall, this work contributes to the development of a valuable human-based in vitro system for studying physiological and pathological conditions, emphasizing the pivotal role of neuron diversity in neural network dynamics.

Electrophysiological and morphological modulation of neuronal-glial network by breast cancer and nontumorigenic mammary cell conditioned medium.

Breast cancer is a significant global health concern, with the overexpression of human epidermal growth factor receptor 2 (HER2/ERBB2) being a driver oncogene in 20%-30% of cases. Indeed, HER2/ERBB2 plays a crucial role in regulating cell growth, differentiation, and survival via a complex signaling network. Overexpression of HER2/ERBB2 is associated with more aggressive behavior and increased risk of brain metastases, which remains a significant clinical challenge for treatment. Recent research has highlighted the role of breast cancer secretomes in promoting tumor progression, including excessive proliferation, immune invasion, and resistance to anti-cancer therapy, and their potential as cancer biomarkers. In this study, we investigated the impact of ERBB2+ breast cancer SKBR-3 cell line compared with MCF10-A mammary non-tumorigenic cell conditioned medium on the electrophysiological activity and morphology of neural networks derived from neurons differentiated from human induced pluripotent stem cells. Our findings provide evidence of active modulation of neuronal-glial networks by SKBR-3 and MCF10-A conditioned medium. These results provide insights into the complex interactions between breast cancer cells and the surrounding microenvironment. Further research is necessary to identify the specific factors within breast cancer conditioned medium that mediate these effects and to develop targeted therapies that disrupt this interaction.

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies.

Objective.We analyze and interpret arm and forearm muscle activity in relation with the kinematics of hand pre-shaping during reaching and grasping from the perspective of human synergistic motor control.Approach.Ten subjects performed six tasks involving reaching, grasping and object manipulation. We recorded electromyographic (EMG) signals from arm and forearm muscles with a mix of bipolar electrodes and high-density grids of electrodes. Motion capture was concurrently recorded to estimate hand kinematics. Muscle synergies were extracted separately for arm and forearm muscles, and postural synergies were extracted from hand joint angles. We assessed whether activation coefficients of postural synergies positively correlate with and can be regressed from activation coefficients of muscle synergies. Each type of synergies was clustered across subjects.Main results.We found consistency of the identified synergies across subjects, and we functionally evaluated synergy clusters computed across subjects to identify synergies representative of all subjects. We found a positive correlation between pairs of activation coefficients of muscle and postural synergies with important functional implications. We demonstrated a significant positive contribution in the combination between arm and forearm muscle synergies in estimating hand postural synergies with respect to estimation based on muscle synergies of only one body segment, either arm or forearm (p< 0.01). We found that dimensionality reduction of multi-muscle EMG root mean square (RMS) signals did not significantly affect hand posture estimation, as demonstrated by comparable results with regression of hand angles from EMG RMS signals.Significance.We demonstrated that hand posture prediction improves by combining activity of arm and forearm muscles and we evaluate, for the first time, correlation and regression between activation coefficients of arm muscle and hand postural synergies. Our findings can be beneficial for myoelectric control of hand prosthesis and upper-limb exoskeletons, and for biomarker evaluation during neurorehabilitation.

BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network.

Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.

Heterogeneous subpopulations of GABAAR-responding neurons coexist across neuronal network scales and developmental stages in health and disease.

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in adults. Depolarizing GABA responses have been well characterized at neuronal-population average level during typical neurodevelopment and partially in brain disorders. However, no investigation has specifically assessed whether a mosaicism of cells with either depolarizing or hyperpolarizing/inhibitory GABAergic responses exists in animals in health/disease at diverse developmental stages, including adulthood. Here, we showed that such mosaicism is present in wild-type (WT) and down syndrome (DS) neuronal networks, as assessed at increasing scales of complexity (cultures, brain slices, behaving mice). Nevertheless, WT mice presented a much lower percentage of cells with depolarizing GABA than DS mice. Restoring the mosaicism of hyperpolarizing and depolarizing GABA-responding neurons to WT levels rescued anxiety behavior in DS mice. Moreover, we found heterogeneous GABAergic responses in developed control and trisomic human induced-pluripotent-stem-cells-derived neurons. Thus, a heterogeneous subpopulation of GABA-responding cells exists in physiological/pathological conditions in mouse and human neurons, possibly contributing to disease-associated behaviors.

Investigating the reliability of the evoked response in human iPSCs-derived neuronal networks coupled to micro-electrode arrays.

In vitro models of neuronal networks have emerged as a potent instrument for gaining deeper insights into the intricate mechanisms governing the human brain. Notably, the integration of human-induced pluripotent stem cells (hiPSCs) with micro-electrode arrays offers a means to replicate and dissect both the structural and functional elements of the human brain within a controlled in vitro environment. Given that neuronal communication relies on the emission of electrical (and chemical) stimuli, the employment of electrical stimulation stands as a mean to comprehensively interrogate neuronal assemblies, to better understand their inherent electrophysiological dynamics. However, the establishment of standardized stimulation protocols for cultures derived from hiPSCs is still lacking, thereby hindering the precise delineation of efficacious parameters to elicit responses. To fill this gap, the primary objective of this study resides in delineating effective parameters for the electrical stimulation of hiPSCs-derived neuronal networks, encompassing the determination of voltage amplitude and stimulation frequency able to evoke reliable and stable responses. This study represents a stepping-stone in the exploration of efficacious stimulation parameters, thus broadening the electrophysiological activity profiling of neural networks sourced from human-induced pluripotent stem cells.

Deepening the role of excitation/inhibition balance in human iPSCs-derived neuronal networks coupled to MEAs during long-term development.

Objective.The purpose of this study is to investigate whether and how the balance between excitation and inhibition ('E/I balance') influences the spontaneous development of human-derived neuronal networksin vitro. To achieve that goal, we performed a long-term (98 d) characterization of both homogeneous (only excitatory or inhibitory neurons) and heterogeneous (mixed neuronal types) cultures with controlled E/I ratios (i.e. E:I 0:100, 25:75, 50:50, 75:25, 100:0) by recording their electrophysiological activity using micro-electrode arrays.Approach.Excitatory and inhibitory neurons were derived from human induced pluripotent stem cells (hiPSCs). We realized five different configurations by systematically varying the glutamatergic and GABAergic percentages.Main results.We successfully built both homogeneous and heterogeneous neuronal cultures from hiPSCs finely controlling the E/I ratios; we were able to maintain them for up to 3 months. Homogeneity differentially impacted purely inhibitory (no bursts) and purely excitatory (few bursts) networks, deviating from the typical traits of heterogeneous cultures (burst dominated). Increased inhibition in heterogeneous cultures strongly affected the duration and organization of bursting and network bursting activity. Spike-based functional connectivity and image-based deep learning analysis further confirmed all the above.Significance.Healthy neuronal activity is controlled by a well-defined E/I balance whose alteration could lead to the onset of neurodevelopmental disorders like schizophrenia or epilepsy. Most of the commonly usedin vitromodels are animal-derived or too simplified and thus far from thein vivohuman condition. In this work, by performing a long-term study of hiPSCs-derived neuronal networks obtained from healthy human subjects, we demonstrated the feasibility of a robustin vitromodel which can be further exploited for investigating pathological conditions where the E/I balance is impaired.

An efficient deep learning approach to identify dynamics in in vitro neural networks.

Understanding and discriminating the spatiotemporal patterns of activity generated by in vitro and in vivo neuronal networks is a fundamental task in neuroscience and neuroengineering. The state-of-the-art algorithms to describe the neuronal activity mostly rely on global and local well-established spike and burst-related parameters. However, they are not able to capture slight differences in the activity patterns. In this work, we introduce a deep-learning-based algorithm to automatically infer the dynamics exhibited by different neuronal populations. Specifically, we demonstrate that our algorithm is able to discriminate with high accuracy the dynamics of five different populations of in vitro human-derived neural networks with an increasing inhibitory to excitatory neurons ratio.

Biohybrid restoration of the hippocampal loop re-establishes the non-seizing state in anin vitromodel of limbic seizures.

Objective. The compromise of the hippocampal loop is a hallmark of mesial temporal lobe epilepsy (MTLE), the most frequent epileptic syndrome in the adult population and the most often refractory to medical therapy. Hippocampal sclerosis is found in >50% of drug-refractory MTLE patients and primarily involves the CA1, consequently disrupting the hippocampal output to the entorhinal cortex (EC). Closed-loop deep brain stimulation is the latest frontier to improve drug-refractory MTLE; however, current approaches do not restore the functional connectivity of the hippocampal loop, they are designed by trial-and-error and heavily rely on seizure detection or prediction algorithms. The objective of this study is to evaluate the anti-ictogenic efficacy and robustness of an artificial bridge restoring the dialog between hippocampus and EC.Approach. In mouse hippocampus-EC slices treated with 4-aminopyridine and in which the Schaffer Collaterals are severed, we established an artificial bridge between hippocampus and EC wherein interictal discharges originating in the CA3 triggered stimulation of the subiculum so to entrain EC networks. Combining quantification of ictal activity with tools from information theory, we addressed the efficacy of the bridge in controlling ictogenesis and in restoring the functional connectivity of the hippocampal loop.Main results. The bridge significantly decreased or even prevented ictal activity and proved robust to failure; when operating at 100% of its efficiency (i.e., delivering a pulse upon each interictal event), it recovered the functional connectivity of the hippocampal loop to a degree similar to what measured in the intact circuitry. The efficacy and robustness of the bridge stem in mirroring the adaptive properties of the CA3, which acts as biological neuromodulator.Significance. This work is the first stepping stone toward a paradigm shift in the conceptual design of stimulation devices for epilepsy treatment, from function control to functional restoration of the salient brain circuits.