Biology subjects

Buccelli, S.

Publications and source records attributed to Buccelli, S..

7 recordsLinked to original sources

bioRxiv2023

The impact of gravity on functional movements: kinematic insights and features selection

Exploring the impact of gravity on daily upper-limb movements is crucial for comprehending the complexities of upper-limb impairments. The present study delves into the relationship between the gravitational force and the functional aspects of upper-limb mobility. Starting from 9 pick-and-place tasks, hand trajectories of 24 healthy subjects were acquired using a motion capture system. Five in-use and two novel kinematic metrics were calculated by such trends and tested across conditions. Results suggest movements performed against and propelled by gravity lead to statistically significant changes in motor behaviour in terms of planning, smoothness, efficiency, and accuracy of the movement, underlining the need of differentiating the study of such movements in impaired subjects.

neuroscience↗

bioRxiv2023

Enabling Model-based Design for closed-loop applications in neuroengineering

This study addresses the inherent difficulties in the creation of neuroengineering devices for closed-loop stimulation, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. To overcome these obstacles, we adopted an alternative strategy centered on Model-based Design (MBD) as a means to simplify the creation of closed-loop systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the development workflow and facilitating the implementation of intricate systems. In this study, we applied MBD techniques to implement a spike detection algorithm on a Field-Programmable Gate Array (FPGA) using commercially available hardware that combines neural probe electronics with programmable FPGA-based hardware. The entire process of data handling and data processing was designed within the Simulink(R) environment, with subsequent generation of HDL code tailored to the FPGA hardware. The validation of our approach was conducted through in vivo experiments involving six animals. We have made all project code files open-source, thereby providing free access to fellow scientists interested in the development of closed-loop systems.

bioengineering↗

bioRxiv2023

Biohybrid restoration of the hippocampal loop re-establishes the non-seizing state in an in vitro model of limbic seizures

ObjectiveThe 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 (DBS) 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. ApproachIn 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 resultsThe 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.

neuroscience↗

bioRxiv2023

The intrinsic clock of the hippocampal subfield CA3 rescues limbic seizures in a biohybrid graft-host interaction in vitro

Hippocampal dysfunction is the hallmark of mesial temporal lobe epilepsy (MTLE), the most common epileptic syndrome in adults and the most often refractory to medical therapy. Deep brain stimulation (DBS) may ameliorate drug-refractory MTLE, but it still cannot guarantee a seizure-free life. One major drawback is that the stimulation policy is informed by trial-and-error rather than by the operating mode of the brain. Thus, optimizing DBS parameters is still an unmet clinical need. Here, we propose the deployment of hippocampal interictal activity in a biohybrid approach to control limbic ictogenesis. Specifically, an electronic bridge establishes a graft-host interaction between the hippocampal subfield CA3 (graft) and the parahippocampal cortex (CTX - host) of distinct rodent brain slices, both treated with 4-aminopyridine; the electronic bridge relays the graft interictal events to the host via electrical pulses. We show that interictal activity generated by the graft CA3 controls limbic ictogenesis in the host CTX even in the absence of feedback from it, thus likely reflecting an intrinsic anti-ictogenic clock of this brain region. This work opens a translational perspective for MTLE treatment via biohybrid neuroprostheses relying on the intrinsic clock of incorporated hippocampal cells.

neuroscience↗

bioRxiv2020

Frequency-specific meso-scale structure of spontaneous oscillatory activity in the human brain

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-modelling to capture the landscape of meso-scale structures across the frequency domain. We found that meso-scale modalities were mixed over the frequency spectrum, with a core-periphery structure predominance. Nevertheless, we also highlighted a selective increase of disassortativity in the delta and theta bands, and of assortativity in the low gamma band (30-50 Hz). We further described other features of the meso-scale organization by identifying those brain regions which, at the same time, i) exhibited the highest degree of assortativity, disassortativity and core-peripheriness (i.e. participation), ii) were consistently assigned to the same community, irrespective from the granularity imposed by WSBM (i.e. granularity-invariance). We defined those brain areas as Participation and Granularity Invariant. In conclusion, we observed that the brain spontaneous activity shows frequency-specific meso-scale organization which may support spatially distributed and local information processing.

neuroscience↗

bioRxiv2020

Real-time detection of bursts in neuronal cultures using a Neuromorphic Auditory Sensor and Spiking Neural Networks

The correct identification of burst events is crucial in many scenarios, ranging from basic neuroscience to biomedical applications. However, none of the burst detection methods that can be found in the literature have been widely adopted for this task. As an alternative to conventional techniques, a novel neuromorphic approach for real-time burst detection is proposed and tested on acquisitions from in vitro cultures. The system consists of a Neuromorphic Auditory Sensor, which converts the input signal obtained from electrophysiological recordings into spikes and decomposes them into different frequency bands. The output of the sensor is sent to a trained spiking neural network implemented on a SpiNNaker board that discerns between bursting and non-bursting activity. This data-driven approach was compared with 8 different conventional spike-based methods, addressing some of their drawbacks, such as being able to detect both high and low frequency events and working in an online manner. Similar results in terms of number of detected events, mean burst duration and correlation as current state-of-the-art approaches were obtained with the proposed system, also benefiting from its lower power consumption and computational latency. Therefore, our neuromorphic-based burst detection paves the road to future implementations for neuroprosthetic applications.

neuroscience↗

bioRxiv2019

A neuroprosthetic system to restore neuronal communication in modular networks

Recent advances in neurotechnology allow neurological impairments to be treated or reduced by brain machine interfaces and neuroprostheses. To develop energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation neurobiohybrid systems for brain repair. We demonstrate here the first exploitation of a neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or completely 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 two specific applications with future clinical implications: bidirectional bridging to artificially reconnect two disconnected neuronal modules and hybrid bidirectional bridging to replace the activity of one module with a neuromorphic spiking neural network. Our neuroprosthetic system opens up new avenues for the development of novel bioelectrical therapeutics for human applications.

bioengineering↗