Biology subjects

Cauwenberghs, G.

Publications and source records attributed to Cauwenberghs, G..

3 recordsLinked to original sources

bioRxiv2025

Rapid-Response, High-Gain Inkjet-Printed Organic Electrochemical Transistors with Geometry-Optimized Design for Neural Recording and Biosensing

Organic Electrochemical Transistors (OECTs) are witnessing rapid growth in biomedical applications and are increasingly becoming an integral part of bio-electronic interfaces. High-performing OECTs are typically fabricated using multistep photolithography and conventional spin-coating and lift-off processes, and while printing techniques have emerged as promising alternatives, they still face challenges in achieving comparable resolutions, reproducibility and performance metrics. Several groups have demonstrated printed OECTs using PEDOT:PSS as the channel material, highlighting the promise of additive manufacturing for scalable bioelectronics. In this work, we build upon these advances and develop an optimized inkjet-printed OECT platform that achieves transconductance values up to 15 mS and sub-millisecond response times as low as 0.31 ms. Our approach systematically optimizes OECT geometrical parameters--channel width, length, and thickness--through precise patterning and oxygen plasma surface modification to overcome longstanding limitations in inkjet printing resolution and reproducibility. The resulting devices exhibit outstanding electrical stability, high amplification, and fast dynamic response. Using a configuration optimized for biosensing, we demonstrate the detection of the heart failure biomarker NT-proBNP within a clinically relevant range of 10-400 pg/mL, with a sensitivity of 0.038% {Delta}IDS/pg/mL. In a separate configuration on a flexible substrate tailored for in vivo biopotential recording, we showcase the devices capabilities by effectively capturing epileptic seizure progression in a rat model with high signal fidelity. This work demonstrates how careful process and geometry optimization can close the performance gap between printed and conventionally fabricated OECTs, enabling scalable, reproducible, and substrate-flexible bioelectronic platforms.

bioengineering↗

bioRxiv2020

Towards Biophysically-Based Neuromorphic Computing at Scale: Markov Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission

Progress in computational neuroscience towards understanding brain function is challenged both by the complexity of molecular-scale electrochemical interactions at the level of individual neurons and synapses and the dimensionality of network dynamics across the brain covering a vast range of spatial and temporal scales. Our work abstracts an existing highly detailed, biophysically realistic 3D reaction-diffusion model of a chemical synapse to a compact internal state space representation that maps onto parallel neuromorphic hardware for efficient emulation at a very large scale and offers near-equivalence in input-output dynamics while preserving biologically interpretable tunable parameters.

neuroscience↗

bioRxiv2018

Can the presence of neural probes be neglected in computational modeling of extracellular potentials?

AbstractO_ST_ABSObjectiveC_ST_ABSMechanistic modeling of neurons is an essential component of computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach to simulation of extracellular neural recordings first computes transmembrane currents using the cable equation and then sums their contribution to model the extracellular potential. This two-step approach relies on the assumption that the extracellular space is an infinite and homogeneous conductive medium, while measurements are performed using neural probes. The main purpose of this paper is to assess to what extent the presence of the neural probes of varying shape and size impacts the extracellular field and how to correct for them.\n\nApproachWe apply a detailed modeling framework allowing explicit representation of the neuron and the probe to study the effect of the probes and thereby estimate the effect of ignoring it. We use meshes with simplified neurons and different types of probe and compare the extracellular action potentials with and without the probe in the extracellular space. We then compare various solutions to account for the probes presence and introduce an efficient probe correction method to include the probe effect in modeling of extracellular potentials.\n\nMain resultsOur computations show that microwires hardly influence the extracellular electric field and their effect can therefore be ignored. In contrast, Multi-Electrode Arrays (MEAs) significantly affect the extracellular field by magnifying the recorded potential. While MEAs behave similarly to infinite insulated planes, we find that their effect strongly depends on the neuron-probe alignment and probe orientation.\n\nSignificanceIgnoring the probe effect might be deleterious in some applications, such as neural localization and parameterization of neural models from extracellular recordings. Moreover, the presence of the probe can improve the interpretation of extracellular recordings, by providing a more accurate estimation of the extracellular potential generated by neuronal models.

bioengineering↗