Recent advances in bioelectronics and neural engineering allowed the development of brain machine interfaces and neuroprostheses, capable of facilitating or recovering functionality in people with neurological disability. To realize energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation systems for brain repair. We demonstrate here a real-time hardware neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or missing. We used in vitro modular cell cultures to mimic the mutual interaction between neuronal assemblies and created a focal lesion to functionally disconnect the two populations. Then, we employed our neuromorphic prosthesis for bidirectional bridging to artificially reconnect two disconnected neuronal modules and for hybrid bidirectional bridging to replace the activity of one module with a real-time hardware neuromorphic Spiking Neural Network. Our neuroprosthetic system opens avenues for the exploitation of neuromorphic-based devices in bioelectrical therapeutics for health care.

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that ‘case-study’, we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as ‘brain-prostheses’, capable of rewiring and/or substituting the injured nervous system.

Brain-related neuronal recordings, such as local field potential, electroencephalogram and magnetoencephalogram, offer the opportunity to study the complexity of the human brain at different spatial and temporal scales. The complex properties of neuronal signals are intrinsically related to the concept of ‘scale-free’ behavior and irregular dynamic, which cannot be fully described through standard linear methods, but can be measured by nonlinear indexes. A remarkable application of these analysis methods on electrophysiological recordings is the deep comprehension of the pathophysiology of neurodegenerative diseases, that has been shown to be associated to changes in brain activity complexity. In particular, a decrease of global complexity has been associated to Alzheimer’s disease, while a local increase of brain signals complexity characterizes Parkinson’s disease. Despite the recent proliferation of studies using fractal and entropy-based analysis, the application of these techniques is still far from clinical practice, due to the lack of an agreement about their correct estimation and a conclusive and shared interpretation. Along with the aim of helping towards the realization of a multidisciplinary audience to approach nonlinear methods based on the concepts of fractality and irregularity, this survey describes the implementation and proper employment of the mostly known and applied indexes in the context of Alzheimer’s and Parkinson’s diseases.

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.

Background: The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing‐based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN).Objectives: The aims were to systematically investigate the spectral topography, including a wide range of sub‐bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS.Methods: STN‐LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub‐bands (delta, theta, alpha, low‐beta, high‐beta, low‐gamma, high‐gamma, and fast‐gamma (FG) as well as low‐ and fast high‐frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS.Results: The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior‐superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub‐bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher‐frequency hot spots were predictive for the best rigidity response to DBS.Conclusions: The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next‐generation sensing‐based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Background: Novel commercial brain‐sense neurostimulators enable us to contextualize brain activity with symptom and medication states in real‐life ambulatory settings in Parkinson's disease (PD). Although various candidate biomarkers have been proposed for adaptive deep brain stimulation (DBS), a comprehensive comparison of their ambulatory profiles is lacking.Objectives: To systematically compare the ambulatory neurophysiological dynamics and clinical properties of three candidate biomarkers—low‐frequency, beta (β), and finely tuned γ (FTG) activity.Methods: We investigated 14 PD patients implanted with the Medtronic Percept PC, who underwent up to two 4‐week ambulatory multimodal recording periods on their regular medication and stimulation. Subthalamic nucleus local field potentials (LFPs) of low‐frequency, β, and FTG activity were recorded. Additionally, objective motor symptom states, physical activity and heart rate using wearables, as well as medication‐intake times, sleep‐awake times, and subjective symptom states using diaries were co‐registered. LFP dynamics were also compared to high‐resolution in‐hospital recordings under off/on dopaminergic medication and stimulation conditions.Results: FTG reliably indexed off to on medication states in the ambulatory setting at the group and individual levels, and these spectral dynamics could be anticipated by high‐resolution in‐hospital recordings. Both FTG and low‐frequency correlated with wearable‐based dyskinesia scores, whereas diary‐based dyskinesia events were only linked to FTG. Importantly, FTG indicated on‐medication states regardless of the presence of dyskinesia and despite potential motion and heart rate artifacts. The 24‐hour profile revealed large circadian power shifts that may overdrive medication‐intake dynamics.Conclusion: Despite the limitations of low‐temporal resolution recordings, this work provides valuable insights into the real‐life dynamics of biomarkers. Specifically, it highlights the utility of FTG as a primary and reliable indicator of medication states for adaptive DBS. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.