Biology subjects

Moradi Chameh, H.

Publications and source records attributed to Moradi Chameh, H..

4 recordsLinked to original sources

bioRxiv2026

Laser-integrated nanophotonic neural probes with on-chip sensors for addressable photostimulation

Studying the role of individual neurons in behavior and disease requires tools for controlling neural activity with high spatiotemporal resolution. Implantable nanophotonic neural probes are capable of delivering targeted photostimulation to enable genetically distinct neurons to be selectively controlled, yet face barriers to achieving scalable emitter densities and lack sensors for monitoring feedback signals relevant to device operation. To address this, we developed laser-integrated nanophotonic neural probes, which feature hybrid-integrated laser diodes (LD) and thermo-optic photonics switches for scalable emitter addressing and on-chip sensors for monitoring optical power and temperature during photo-stimulation. Devices were fabricated at a commercial silicon photonics foundry on 200-mm diameter silicon-on-insulator (SOI) wafers in an active visible-light platform and were controlled using a custom-developed electronic circuit board. Each device features a hybrid-integrated InGaN LD which couples 450-nm light into a reconfigurable photonic switching tree for delivering spatially resolved photostimulation through 16 emitters along a 3-mm implantable shank. Using the on-chip photodetectors, we demonstrate how devices can enable switching tree calibration as well as output power monitoring during photostimulation. Furthermore, using the on-chip temperature sensors, we show how device temperature perturbations resulting from LD and thermo-optic switch activation can be directly monitored during photostimulation to ensure temperature fluctuations remain below 1 {degrees}C. We validate our design by delivering high spatiotemporal photostimulation during an in vivo optogenetic experiment with simultaneous Neuropixels recording to monitor evoked responses. Overall, these scalable integrated devices offer a pathway for neuroscientists to conduct fiberless optogenetic experiments with greater control and precision.

neuroscience↗

bioRxiv2022

OpenMEA: Open-Source Microelectrode Array Platform for Bioelectronic Interfacing

Bioelectronic interfaces have the potential to revolutionize the treatment of medical disorders and augment physiology. Implantable devices such as pacemakers and deep brain stimulators have already been deployed to control activity in diseases including Parkinsons disease and epilepsy. These devices typically operate by delivering electrical stimulation at pre-programmed intervals (known as open-loop stimulation). Recent advances in machine learning and low-power integrated circuits have led to the emergence of personalized medical devices that monitor the users state and stimulate in response to measured biological activity (known as closed-loop stimulation). There are two key questions that require fundamental research to achieve breakthroughs in personalized devices: 1) What biomarkers and algorithms are best suited to detecting biological states (e.g. seizures in epilepsy)? and 2) What types of electrical stimuli are optimal for controlling these states? The answer to these questions can be explored in vitro using multielectrode array (MEA) systems that interface with biological tissue with reduced experimental complexity, better reproducibility, and fewer confounding variables present in whole organisms. However, existing MEA systems have functional limitations and closed-source designs that prevent researchers from developing improvements. This paper introduces OpenMEA, an open-source platform for closed-loop bioelectronics research. OpenMEA includes designs for the components necessary to build a benchtop in vitro laboratory, including electrophysiological recording and stimulation electronics, a microfluidic perfusion system, and physical designs for multielectrode arrays. The system is demonstrated with the electrical recording and stimulation of epileptogenic human and rodent brain slices. The aim of OpenMEA is to democratize bioelectronic research tools to accelerate the deployment of devices for the treatment of disorders and beyond.

bioengineering↗

bioRxiv2021

Resilience through diversity: Loss of neuronal heterogeneity in epileptogenic human tissue renders neural networks more susceptible to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a unique bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

neuroscience↗

bioRxiv2021

Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits

Cortical processing depends on finely-tuned excitatory and inhibitory connections in neuronal microcircuits. Reduced inhibition by somatostatin-expressing interneurons is a key component of altered inhibition associated with treatment-resistant major depressive disorder (depression), which is implicated in cognitive deficits and rumination, but the link remains to be better established mechanistically in humans. Here, we tested the impact of reduced somatostatin interneuron mediated inhibition on cortical processing in human neuronal microcircuits using a data-driven computational approach. We integrated human cellular, circuit and gene-expression data to generate detailed models of human cortical microcircuits in health and depression. We simulated microcircuit baseline and response activity and found reduced signal-to-noise ratio and increased false/failed detection of stimuli due to a higher baseline activity in depression. Our results thus applied novel models of human cortical microcircuits to demonstrate mechanistically how reduced inhibition impairs cortical processing in depression, providing quantitative links between altered inhibition and cognitive deficits.

neuroscience↗