Publications by authors named "E J Chichilnisky"
Objective: Neural interfaces are designed to evoke specific patterns of electrical activity in populations of neurons by stimulating with many electrodes. However, currents passed simultaneously through multiple electrodes often combine nonlinearly to drive neural responses, making evoked responses difficult to predict and control. This response nonlinearity could arise from the interaction of many excitable sites in each cell, any of which can produce a spike.
View Article and Find Full Text PDFSilicon-based microelectronics can scalably record and modulate neural activity at high spatiotemporal resolution, but their planar form factor poses challenges in targeting 3D neural structures. A method for fabricating tissue-penetrating 3D microelectrodes directly onto planar microelectronics using high-resolution 3D printing via 2-photon polymerization and scalable microfabrication technologies are presented. This approach enables customizable electrode shape, height, and positioning for precise targeting of neuron populations distributed in 3D.
View Article and Find Full Text PDFArticle Synopsis
- The study challenges the traditional view of retinal ganglion cells (RGCs) in the retina functioning mainly through simple center-surround spatial filtering, revealing instead a much higher functional diversity in primate RGC types, particularly in macaques and humans.
- Researchers identified 18-27 functional RGC types in primates, along with surprising non-classical receptive field structures and distinct responses to visual stimuli like natural movies.
- These findings suggest that these diverse RGC types have specialized roles in vision rather than just proportioning visual information at varying spatial scales.
Neural implants have the potential to restore lost sensory function by electrically evoking the complex naturalistic activity patterns of neural populations. However, it can be difficult to predict and control evoked neural responses to simultaneous multi-electrode stimulation due to nonlinearity of the responses. We present a solution to this problem and demonstrate its utility in the context of a bidirectional retinal implant for restoring vision.
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- - This paper introduces a neural recording integrated circuit (IC) designed for brain-computer interfaces, allowing for high-bandwidth and single-cell resolution data compression during digitization to manage large amounts of data more efficiently.
- - The IC reduces the output data rate by 146× by eliminating unnecessary baseline samples while still enabling the reconstruction of important neural signals, using a low-power design and an effective routing system.
- - Fabricated in a compact 28-nm CMOS process, the IC features a 32 x 32 array with 1024 channels, achieving high energy efficiency and low noise levels, making it suitable for integration with high-density microelectrode arrays.