Biology subjects

Benjaber, M.

Publications and source records attributed to Benjaber, M..

6 recordsLinked to original sources

bioRxiv2025

A clinical grade neurostimulation implant for hierarchical control of physiological activity

Bioelectronic implants for neurostimulation aim to steer disordered neurophysiological processes back towards a healthy state. However, physiology is subject to biological rhythms, including the circadian rhythm and the sleep-wake cycle. These predictable rhythms affect disease symptomatology, biomarkers used in closed-loop therapies, and a physiological systems expected response to stimulation. Therefore, therapeutic devices should incorporate feedforward elements to align algorithm parameters with predictable changes in physiological state, as a parallel of physiological rheostatic control. Here we introduce the DyNeuMo-2c, the first clinical-grade implant capable of delivering closed-loop neurostimulation while flexibly changing its functional configuration according to time of day. The device can chronically measure brain activity and motion state to track potential biomarker patterns in natural, out-of-clinic settings, allowing identification and targeting of patient-specific chronotypes. The system implements a hierarchical control flow, with baseline therapy set by a circadian scheduler, and adaptive policies layered to take effect based on specific biomarkers indicating patient and disease state. Using a benchtop validation setup, we demonstrate that the system has the required capabilities for delivering time-contingent closed-loop therapy in two established clinical use cases: Parkinsons disease and epilepsy. Next, we deploy the system in vivo to deliver closed-loop deep brain stimulation in a healthy non-human primate model of vigilance, highlighting the importance of synchronisation between device operation and physiological state in various conditions (task performance, unconstrained behaviour, and sleep). Time-of-day-dependent adaptation of closed-loop stimulation enabled modulation of both vigilance and behaviour. Overall, the novel device architecture provides a proof-of-concept for delivering time-contingent therapy in chronic therapeutic settings where biological rhythms are of key importance.

neuroscience↗

bioRxiv2025

NeuroTest: a benchtop testbed for evaluating sensing-capable electrophysiology and neurostimulation systems

ObjectiveThe development of increasingly complex implantable neuromodulation devices requires extensive benchtop validation and testing prior to in vivo implementation. Our goal is to enable this in vitro testing by creating a benchtop system that is accessible, easy-to-use, and functions reliably across academic and industry environments, reducing discordant results that arise from discordant approaches. Furthermore, such a system paves the way for standardizing benchtop characterization of future implantable systems by establishing a repeatable and comparable methodology for validating these devices and their capabilities. ApproachWe describe the NeuroTest Board (NTB), a low-cost, open-source device that combines a low-noise current source waveform generator with a high-precision data acquisition system. We provide information on its architecture, operation, and performance as an initial benchmark of the potential capabilities of the system. Main resultsWe demonstrate the use of the NTB to assess electrophysiology systems in two separate applications. In one case, we assess a commonly used laboratory system (the RHD2132 headstage and Open Ephys data acquisition system), while the second case characterizes an investigational neuromodulation device in development for human use (the CorTec Brain InterChange). Following this initial sensing characterization, we explore stimulation-related artifacts that would hamper in vivo data collection. With the NTB, we develop and evaluate artifact mitigation strategies for each system, thus demonstrating an example application of this benchtop testbed. SignificanceThe ability to test neuromodulation devices against a common benchmark will enable faster development of novel therapeutics by increasing inter-institutional reliability and decreasing troubleshooting time.

bioengineering↗

bioRxiv2023

Bioelectronic Zeitgebers: targeted neuromodulation to re-establish circadian rhythms.

Existing neurostimulation systems implanted for the treatment of neurodegenerative disorders generally deliver invariable therapy parameters, regardless of phase of the sleep/wake cycle. However, there is considerable evidence that brain activity in these conditions varies according to this cycle, with discrete patterns of dysfunction linked to loss of circadian rhythmicity, worse clinical outcomes and impaired patient quality of life. We present a targeted concept of circadian neuromodulation using a novel device platform. This system utilises stimulation of circuits important in sleep and wake regulation, delivering bioelectronic cues (Zeitgebers) aimed at entraining rhythms to more physiological patterns in a personalised and fully configurable manner. Preliminary evidence from its first use in a clinical trial setting, with brainstem arousal circuits as a surgical target, further supports its promising impact on sleep/wake pathology. Data included in this paper highlight its versatility and effectiveness on two different patient phenotypes. In addition to exploring acute and long-term electrophysiological and behavioural effects, we also discuss current caveats and future feature improvements of our proposed system, as well as its potential applicability in modifying disease progression in future therapies.

bioengineering↗

bioRxiv2021

The sensitivity of ECG contamination to surgical implantation site in adaptive closed-loop neurostimulation systems

BackgroundBrain sensing devices are approved today for Parkinsons, essential tremor, and epilepsy therapies. Clinical decisions for implants are often influenced by the premise that patients will benefit from using sensing technology. However, artifacts, such as ECG contamination, can render such treatments unreliable. Therefore, clinicians need to understand how surgical decisions may affect artifact probability. ObjectivesInvestigate neural signal contamination with ECG activity in sensing enabled neurostimulation systems, and in particular clinical choices such as implant location that impact signal fidelity. MethodsElectric field modelling and empirical signals from 85 patients were used to investigate the relationship between implant location and ECG contamination.a ResultsThe impact on neural recordings depends on the difference between ECG signal and noise floor of the electrophysiological recording. Empirically, we demonstrate that severe ECG contamination was more than 3.2x higher in left-sided subclavicular implants (48.3%), when compared to right-sided implants (15.3%). Cranial implants did not show ECG contamination. ConclusionsGiven the relative frequency of corrupted neural signals, we conclude that implant location will impact the ability of brain sensing devices to be used for "closed-loop" algorithms. Clinical adjustments such as implant location can significantly affect signal integrity and need consideration. HighlightsO_LIChronic embedded brain sensing promises algorithm-based neurostimulation C_LIO_LIAlgorithms for closed-loop stimulation can be impaired by artifacts C_LIO_LIThe relationship of implant location to cardiac dipole has relevant impact on neural signal fidelity; simple models can provide guidance on the sensitivity C_LIO_LIECG artifacts are present in up to 50% of neural signals from left subclavicular DBS systems C_LIO_LIImplanting DBS in a right subclavicular location significantly reduces frequency of ECG artifacts C_LIO_LICranial-mounted implants are relatively immune to artifacts C_LI

neuroscience↗

bioRxiv2020

DyNeuMo Mk-1: A Fully-Implantable, Motion-Adaptive Neurostimulator with Configurable Response Algorithms

There is growing interest in using adaptive neuro-modulation to provide a more personalized therapy experience that might improve patient outcomes. Current implant technology, however, can be limited in its adaptive algorithm capability. To enable exploration of adaptive algorithms with chronic implants, we designed and validated the Picostim DyNeuMo Mk-1 (DyNeuMo Mk-1 for short), a fully-implantable, adaptive research stimulator that titrates stimulation based on circadian rhythms (e.g. sleep, wake) and the patients movement state (e.g. posture, activity, shock, free-fall). The design leverages off-the-shelf consumer technology that provides inertial sensing with low-power, high reliability, and relatively modest cost. The DyNeuMo Mk-1 system was designed, manufactured and verified using ISO 13485 design controls, including ISO 14971 risk management techniques to ensure patient safety, while enabling novel algorithms. The system was validated for an intended use case in movement disorders under an emergency-device authorization from the Medicines and Healthcare Products Regulatory Agency (MHRA). The algorithm configurability and expanded stimulation parameter space allows for a number of applications to be explored in both central and peripheral applications. Intended applications include adaptive stimulation for movement disorders, synchronizing stimulation with circadian patterns, and reacting to transient inertial events such as posture changes, general activity, and walking. With appropriate design controls in place, first-in-human research trials are now being prepared to explore the utility of automated motion-adaptive algorithms.

bioengineering↗

bioRxiv2020

Physiological Artifacts and the Implications for Brain-Machine-Interface Design

The accurate measurement of brain activity by Brain-Machine-Interfaces (BMI) and closed-loop Deep Brain Stimulators (DBS) is one of the most important steps in communicating between the brain and subsequent processing blocks. In conventional chest-mounted systems, frequently used in DBS, a significant amount of artifact can be induced in the sensing interface, often as a common-mode signal applied between the case and the sensing electrodes. Attenuating this common-mode signal can be a serious challenge in these systems due to finite commonmode-rejection-ratio (CMRR) capability in the interface. Emerging BMI and DBS devices are being developed which can mount on the skull. Mounting the system on the cranial region can potentially suppress these induced physiological signals by limiting the artifact amplitude. In this study, we model the effect of artifacts by focusing on cardiac activity, using a current-source dipole model in a torso-shaped volume conductor. Performing finite element simulation with the different DBS architectures, we estimate the ECG common mode artifacts for several device architectures. Using this model helps define the overall requirements for the total system CMRR to maintain resolution of brain activity. The results of the simulations estimate that the cardiac artifacts for skull-mounted systems will have a significantly lower effect than non-cranial systems that include the pectoral region. It is expected that with a pectoral mounted device, a minimum of 60-80 dB CMRR is required to suppress the ECG artifact, while in cranially-mounted devices, a 20 dB CMRR is sufficient, in the worst-case scenario. The methods used for estimating cardiac artifacts can be extended to other sources such as motion/muscle sources. The susceptibility of the device to artifacts has significant implications for the practical translation of closed-loop DBS and BMI, including the choice of biomarkers and the design requirements for insulators and lead systems.

bioengineering↗