A compact solution for vibrotactile proprioceptive feedback of wrist rotation and hand aperture.

BACKGROUND: Closing the control loop between users and their prostheses by providing artificial sensory feedback is a fundamental step toward the full restoration of lost sensory-motor functions. METHODS: We propose a novel approach to provide artificial proprioceptive feedback about two degrees of freedom using a single array of 8 vibration motors (compact solution). The performance afforded by the novel method during an online closed-loop control task was compared to that achieved using the conventional approach, in which the same information was conveyed using two arrays of 8 and 4 vibromotors (one array per degree of freedom), respectively. The new method employed Gaussian interpolation to modulate the intensity profile across a single array of vibration motors (compact feedback) to convey wrist rotation and hand aperture by adjusting the mean and standard deviation of the Gaussian, respectively. Ten able-bodied participants and four transradial amputees performed a target achievement control test by utilizing pattern recognition with compact and conventional vibrotactile feedback to control the Hannes prosthetic hand (test conditions). A second group of ten able-bodied participants performed the same experiment in control conditions with visual and auditory feedback as well as no-feedback. RESULTS: Conventional and compact approaches resulted in similar positioning accuracy, time and path efficiency, and total trial time. The comparison with control condition revealed that vibrational feedback was intuitive and useful, but also underlined the power of incidental feedback sources. Notably, amputee participants achieved similar performance to that of able-bodied participants. CONCLUSIONS: The study therefore shows that the novel feedback strategy conveys useful information about prosthesis movements while reducing the number of motors without compromising performance. This is an important step toward the full integration of such an interface into a prosthesis socket for clinical use.

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.

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.

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.

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.

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.

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.

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.

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.

Neural oscillations modulation during working memory in pre-manifest and early Huntington's disease.

INTRODUCTION: We recently demonstrated specific spectral signatures associated with updating of memory information, working memory (WM) maintenance and readout, with relatively high spatial resolution by means of high-density electroencephalography (hdEEG). WM is impaired already in early symptomatic HD (early-HD) and in pre-manifest HD (pre-HD). The aim of this study was to test whether hdEEG coupled to source localization allows for the identification of neuronal oscillations in specific frequency bands in 16 pre-HD and early-HD during different phases of a WM task. METHODS: We examined modulation of neural oscillations by event-related synchronization and desynchronization (ERS/ERD) of θ, ß, gamma low, γLOW and γHIGH EEG bands in a-priori selected large fronto-parietal network, including the insula and the cerebellum. RESULTS: We found: (i) Reduced θ oscillations in HD with respect to controls in almost all the areas of the WM network during the update and readout phases; (ii) Modulation of ß oscillations, which increased during the maintenance phase of the WM task in both groups; (iii) correlation of γHIGH oscillations during WM task with disease burden score in HD patients. CONCLUSIONS: Our data show reduced phase-specific modulation of oscillations in pre-HD and early-HD, even in the presence of preserved dynamic of modulation. Particularly, reduced synchronization in the θ band in the areas of the WM network, consistent with abnormal long-range coordination of neuronal activity within this network, was found in update and readout phases in HD groups.

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.

A Novel Method for Vibrotactile Proprioceptive Feedback Using Spatial Encoding and Gaussian Interpolation.

OBJECTIVE: The bidirectional communication between the user and the prosthesis is an important requirement when developing prosthetic hands. Proprioceptive feedback is fundamental to perceiving prosthesis movement without the need for constant visual attention. We propose a novel solution to encode wrist rotation using a vibromotor array and Gaussian interpolation of vibration intensity. The approach generates tactile sensation that smoothly rotates around the forearm congruently with prosthetic wrist rotation. The performance of this scheme was systematically assessed for a range of parameter values (number of motors and Gaussian standard deviation). METHODS: Fifteen non-disabled subjects and one individual with congenital limb deficiency used vibrational feedback to control a virtual hand in the target-achievement control test. Performance was assessed by end-point error and efficiency as well as subjective impressions. RESULTS: The results showed a preference for smooth feedback and a higher number of motors (8 and 6 versus 4). With 8 and 6 motors, the standard deviation, determining the sensation spread and continuity, could be modulated through a broad range of values (0.1 - 2) without a significant performance loss. The overall average error and efficiency across these feedback configurations were ∼ 10% and ∼ 30%, respectively. For low values of standard deviation (0.1-0.5), the number of motors could be reduced to 4 without a significant performance decrease. CONCLUSION: The study demonstrated that the developed strategy provided meaningful rotation feedback. Moreover, the results indicate that the Gaussian standard deviation could be used as an independent parameter to encode an additional feedback variable. SIGNIFICANCE: The proposed method is a flexible and effective approach to provide proprioceptive feedback while adjusting the trade-off between sensation quality and the number of vibromotors.

User-centered design and development of TWIN-Acta: A novel control suite of the TWIN lower limb exoskeleton for the rehabilitation of persons post-stroke.

Introduction: Difficulties faced while walking are common symptoms after stroke, significantly reducing the quality of life. Walking recovery is therefore one of the main priorities of rehabilitation. Wearable powered exoskeletons have been developed to provide lower limb assistance and enable training for persons with gait impairments by using typical physiological movement patterns. Exoskeletons were originally designed for individuals without any walking capacities, such as subjects with complete spinal cord injuries. Recent systematic reviews suggested that lower limb exoskeletons could be valid tools to restore independent walking in subjects with residual motor function, such as persons post-stroke. To ensure that devices meet end-user needs, it is important to understand and incorporate their perspectives. However, only a limited number of studies have followed such an approach in the post-stroke population. Methods: The aim of the study was to identify the end-users needs and to develop a user-centered-based control system for the TWIN lower limb exoskeleton to provide post-stroke rehabilitation. We thus describe the development and validation, by clinical experts, of TWIN-Acta: a novel control suite for TWIN, specifically designed for persons post-stroke. We detailed the conceived control strategy and developmental phases, and reported evaluation sessions performed on healthy clinical experts and people post-stroke to evaluate TWIN-Acta usability, acceptability, and barriers to usage. At each developmental stage, the clinical experts received a one-day training on the TWIN exoskeleton equipped with the TWIN-Acta control suite. Data on usability, acceptability, and limitations to system usage were collected through questionnaires and semi-structured interviews. Results: The system received overall good usability and acceptability ratings and resulted in a well-conceived and safe approach. All experts gave excellent ratings regarding the possibility of modulating the assistance provided by the exoskeleton during the movement execution and concluded that the TWIN-Acta would be useful in gait rehabilitation for persons post-stroke. The main limit was the low level of system learnability, attributable to the short-time of usage. This issue can be minimized with prolonged training and must be taken into consideration when planning rehabilitation. Discussion: This study showed the potential of the novel control suite TWIN-Acta for gait rehabilitation and efficacy studies are the next step in its evaluation process.

Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.

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.

LFP Analysis of Brain Injured Anesthetized Animals Undergoing Closed-Loop Intracortical Stimulation.

Activity dependent stimulation (ADS) is a closed loop stimulation technique whose neurophysiological effects have not been deeply investigated. Here we explored how Local field Potentials (LFP) are impacted by a focal ischemic lesion and, subsequently, by ADS treatment. Intracortical microelectrode arrays were implanted in the rostral forelimb area (RFA) and in the primary somatosensory area (S1) of anaesthetized rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. The lesion induced an acute depressive trend in LFP power in RFA (evaluated in 6 bands of interest: Delta (1-4Hz), Theta (4-8Hz), Alpha (8-11Hz), Beta (11-30Hz), LowGamma (30-55Hz) and HighGamma (55-80)) followed by a noticeable significant rebound in both areas. Applying ADS induced an overall decrease of power. The lesion impacted the connectivity in a frequency specific manner, resulting in widespread increase in connectivity in Delta both between and within areas. Two hours after the lesion, without stimulation, correlated activity between areas increased in Beta and Gamma. After stimulation, inter-area connectivity increased in Delta, Theta and Alpha, while considerably dropping within RFA in highGamma. By computing phase-amplitude coupling, we found that the lesion produced an incremental increase in the coupling between (Theta) Alpha phase and (lowGamma) highGamma amplitude within RFA, while S1 had a more generalized increase. Likewise, coupling between Theta phase and lowGamma/highGamma amplitudes increased between areas after lesion. ADS induced a similar increase, but greater in magnitude both within and between RFA and S1. These results have important implications on the emerging field of closed-loop adaptive stimulation promoting ADS as an innovative tool for the treatment of neurological disorders.

Using robots to advance clinical translation in neurorehabilitation.

A preclinical robotic platform aids rehabilitation, therapy development, and assessment of recovery for upper limb impairments.