Apr 9, 2025
5:00pm - 7:00pm
Summit, Level 2, Flex Hall C
Ethan Frey1,Atharva Sahasrabudhe1,Polina Anikeeva1
Massachusetts Institute of Technology1
Ethan Frey1,Atharva Sahasrabudhe1,Polina Anikeeva1
Massachusetts Institute of Technology1
Neurotransmitters are essential for neural communication. Dysfunction in neurotransmitter signaling is the underlying cause of numerous neurological disorders, such as Parkinson’s disease, depression, and substance use disorders. Neurotransmitter sensing technology can provide deeper insights into these conditions and aid in developing effective interventions. Fast Scanning Cyclic Voltammetry (FSCV) is a translationally ready neurotransmitter sensing technology widely used in rodents and proven effective in humans. However, conventional FSCV electrodes based on glass-insulated carbon fiber lack spatial resolution, are mechanically brittle, and require manual assembly, which limits scalability.
To address these limitations, a one-step thermal drawing process is used to insulate hundreds of meters of carbon nanotube fiber (CNTF), assemble them into spatially-defined arrays, and encase them in polyvinyl alcohol (PVA), a biocompatible, water-soluble polymer. The PVA temporarily increases the fiber's stiffness to facilitate implantation into deep brain regions yet dissolves within minutes, leaving a small, low-bending stiffness probe implanted. Thermal drawing of the dissolvable shuttle allows precise control over thickness and composition, optimizing stiffness for implantation while minimizing thickness to reduce tissue damage. Our process integrates 20 µm, commercially-available CNTFs that achieve higher temporal resolution (>100 Hz) and electrochemical reversibility (I
peak,cathodic/I
peak,anodic = ~1.03) for detecting dopamine than traditional carbon fiber electrodes. Chemical modification of CNTFs is also explored to further improve their FSCV performance. This fiber design enables neurotransmitter detection with high temporal and spatial resolution. It is also compatible with cost-effective, mass manufacturing processes and is ready for translational applications.