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028 – Roundtable: Neurotech vs Neuroscience
Neurotech, Neurotech Podcast

Vikash Gilja is an assistant professor at UCSD, where he researchers brain-machine interfaces. Dr. Gilja is an advisor to Paradromics. He holds a Ph.D. in computer science from Stanford University, an M.Eng and B.S. in EECS from MIT, and a B.S. in brain and cognitive sciences from MIT.

Rob Edgington is the head of AI at Paradromics. He holds a Ph.D. in brain-machine interfaces from UCL, and an M.Phys in physics from the University of Oxford.

Konrad Kording is a full professor at the University of Pennsylvania, where he works on data problems in neuroscience. He holds a Ph.D. in physics from ETH Zurich.

Top 3 Takeaways

  1. Basic neuroscience and neural engineering can and should co-evolve, much the same as physics and electrical engineering.
  2. More granular understandings from neuroscience help inform machine learning models applied in neurotechnology.
  3. Speech prostheses are a promising area for modern BMIs.

Show Notes

  • [1:10] Rob’s introduction.
  • [1:24] Konrad’s introduction.
  • [1:35] Vikash’s introduction.
  • [1:47] Avery’s introduction.
  • [2:05] Neuroscience vs. neurotechnology.
  • [2:55] Basic science and causality.
  • [3:35] Definition of causality.
  • [6:10] Closed-loops require causal models.
  • [8:15] Visual system as closing the loop.
  • [9:55] Electrical engineering is an analogy to neural engineering.
  • [12:20] Modern BMI devices.
  • [13:00] More data means more degrees of freedom.
  • [15:15] Distributed recordings.
  • [19:40] Data processing constraints in BMI.
  • [20:00] Ontology refinement.
  • [22:35] Timescale of tool development.
  • [23:45] Future-proofing a BMI.
  • [25:00] On-chip processing.
  • [26:00] Evolution of BMIs.
  • [27:15] Industry is good for integrating engineering constraints.
  • [29:30] Estimating intended speech.
  • [30:20] Neurotech for locked-in patients.
  • [32:30] Visual communication.
  • [34:00] ML vs. DL in neurotech.
  • [37:00] Better models are inspired by basic science.
  • [38:35] Hiring in neurotechnology.

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