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    News

    Neurotech Podcast

    In this podcast, we dive into Neurotech and the people working to advance the technology. We host the neurotech researchers and entrepreneurs building the technology, and hear the stories of people benefiting from neurotech advancements.

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    Latest Episodes:
    028 – Roundtable: Neurotech vs Neuroscience Dec 16, 2019
    Show notes

    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.

    Selected Links

    • Paradromics
    • The Neurotechnology Age – Matt Angle, CEO Paradromics

    Related Podcasts

    • 010 – Matt Angle
    • 026 – Gordon Wilson
    • 027 – Marc Ferro

    Disclaimer

    027 – Marc Ferro Nov 19, 2019
    Show notes

    Marc Ferro is a post-doctoral researcher at Stanford University. Marc holds a Ph.D. from École des Mines de Saint-Étienne and an undergraduate degree from École nationale supérieure des Mines de Saint-Étienne.

    Top 3 Takeaways

    1. Small neural interfaces improve signal quality.
    2. Small neural interfaces avoid biological damage.
    3. Researchers and entrepreneurs have many commonalities.

    Show Notes

    • [0:59] Marc’s background.
    • [2:22] Biggest materials science challenges in neural interfaces.
    • [4:30] Respecting brain tissue.
    • [5:30] Initial insult vs. chronic injury.
    • [7:30] Constraints on neural interfaces.
    • [9:30] NeuroRoots.
    • [11:00] Status of NeuroRoots.
    • [12:15] NeuroRoots vs. other cutting-edge interfaces.
    • [17:08] Researchers as entrepreneurs.
    • [19:48] What kind of skillsets do neural interfaces teams need to have?

    Selected Links

    • NeuroRoots
    • BrainMind talks
    • Zen and Art of Motorcycle Maintenance

    Related Podcasts

    • 010 – Matt Angle
    • 020 – Mary Beth Henderson
    • 024 – Brian Pepin

    Disclaimer

    026 – Gordon Wilson Nov 03, 2019
    Show notes

    Gordon Wilson is the CEO of Rain Neuromorphics, a company developing neuromorphic computer chips to enable brain-like artificial intelligence. Gordon holds a B.S. in Statistics and Mathematics from the University of Florida.

    Top 3 Takeaways

    1. Training deep learning algorithms is expensive.
    2. To understand the brain, you need to build one.
    3. Modern computing hardware doesn’t have the parallelism and energy efficiency of the brain.

    Show Notes

    • [1:12] Building a processor for brain math.
    • [2:40] The cost of artificial neural networks.
    • [3:36] What is “brain-inspired hardware”?
    • [4:50] Nanowires and memristors.
    • [6:25] Cross-disciplinary chip design.
    • [7:30] Size of the brain vs. size of artificial neural networks.
    • [9:05] Research vs. development.
    • [12:00] Bridging brain science and AI.
    • [13:54] Neuromorphics vs. GPUs.
    • [18:00] Chips on the market.
    • [20:40] Go-to-market: matrix multiplication.
    • [22:22] Cost and energy of Rain’s hardware.
    • [23:33] Does chip design impact software development?
    • [24:08] Fusing training and inference.
    • [26:26] Wide learning vs. deep learning.
    • [29:30] Sparse learning.
    • [32:10] Gordon’s book recommendations.

    Selected Links

    • A talk by Gordon
    • An article about Rain’s technology
    • OpenAI’s blog
    • On Intelligence, by Jeff Hawkins
    • WaitButWhy, a blog by Tim Urban

    Related Podcasts

    • 002 – Jeff Hawkins
    • 020 – Mary Beth Henderson
    • 024 – Brian Pepin

    Disclaimer

    025 – Alik Widge Oct 04, 2019
    Show notes

    Dr. Alik Widge is an Assistant Professor at the University of Minnesota, where he is a practicing psychiatrist and conducts research in applying neurotechnology to psychiatric disorders. Alik holds a B.A. in computer science and cognitive science from Dartmouth College, a Ph.D. in robotics from Carnegie Mellon University, and an M.D. from the University of Pittsburgh School of Medicine.

    Top 3 Takeaways

    1. Alik’s work pursues the idea of nudging brain networks underlying psychiatric disorders.
    2. Nudges are about reinstating normal emotional dynamics, rather than moving emotion to a particular regime.
    3. Cross-training scientists and clinicians can lead to novel perspectives on psychiatric treatments.

    Show Notes

    • [1:22] Alik’s background & overview of his current work.
    • [2:55] Synthesizing fields impacts Alik’s approach.
    • [3:28] Networks and nudges.
    • [5:03] Regions vs. networks in neurotechnology.
    • [6:00] History of depression interventions.
    • [9:00] Biology vs. historical neurology.
    • [10:00] Networks of different scales.
    • [12:15] What does a “nudge” look like?
    • [15:55] Behavioral therapy & neuromodulation nudges.
    • [19:00] Neuroscience vs. psychiatry.
    • [21:00] New language in psychiatry.
    • [23:35] Needed changes in industry.
    • [26:00] Specialized chips in neural implants.
    • [27:20] Alik’s recent paper.

    Selected Links

    • Alik’s paper.

    Related Podcasts

    • 021 – Cory Inman
    • 020 – Mary Beth Henderson
    • 024 – Brian Pepin

    Disclaimer

    024 – Brian Pepin Sep 17, 2019
    Show notes

    Brian Pepin is the CEO and founder of Rune Labs. Brian holds an MSEE in electrical engineering from UC Berkeley and a BSEE from the University of Washington. Prior to starting Rune, Brian spent nearly five years at Verily Life Sciences.

    Top 3 Takeaways

    1. It makes sense to use neuromodulation therapies for neurological and psychiatric disorders that inherently fluctuate over time.
    2. Neuromodulation data is siloed and that slows down research and translation.
    3. Closed-loop DBS can enable novel, more efficacious therapies.

    Show Notes

    • [0:47] Brian’s background.
    • [1:50] The Google phase.
    • [3:10] Brian’s transition into Rune Labs.
    • [3:30] Rune in a nutshell.
    • [4:32] Unmet needs for brain diseases.
    • [5:58] Why neuromodulation instead of drugs.
    • [7:30] Need for adaptive therapies.
    • [8:53] Impact of neuromodulation in Parkinson’s Disorder.
    • [10:54] Who fits the bill for DBS.
    • [13:30] Siloed data in neuromodulation.
    • [15:15] Competition in DBS.
    • [16:45] Initial application of closed-loop DBS is auto-tune.
    • [17:30] Closed-loop can enable therapies.
    • [19:03] Software development in DBS devices.
    • [20:10] Partnerships between medical device companies and AI companies.
    • [21:27] Long-term vision for Rune.

    Selected Links

    • Strive PD patient-facing application

    Related Podcasts

    • 021 – Cory Inman
    • 020 – Mary Beth Henderson
    • 016 – Jim Cavuoto

    Disclaimer

    023 – Jeff June Aug 27, 2019
    Show notes

    Jeff June is the founder and CEO of IschemiaCare. Jeff comes from a background in venture capital and private equity, and held the Forsythe Chair in Entrepreneurship at Miami University of Ohio.

    Top 3 Takeaways

    1. In 40% of stroke cases, the specific cause is unknown.
    2. Stroke care can benefit from greater diagnostic personalization.
    3. Having the right people in your life and on your team is an outsized advantage.

    Show Notes

    • [1:00] Jeff’s background.
    • [2:45] Origin of IschemiaCare.
    • [5:52] What IschemiaCare does.
    • [8:05] A-fib stroke.
    • [10:20] How IschemiaCare gains usage.
    • [13:30] IschemiaCare’s business model.
    • [15:20] Growth plan.
    • [16:00] IschemiaCare’s product and how it fits into stroke care pipeline.
    • [17:50] The RNA data play.
    • [19:40] Extrapolating data insights.
    • [23:40] Key lessons about healthtech.
    • [27:30] Reminding people of your mission.
    • [30:00] Doug’s meme on the Loup website.

    Selected Links

    • IschemiaCare
    • Stroke care guidelines

    Related Podcasts

    • 020 – Mary Beth Henderson
    • 017 – Ana Maiques
    • 013 – Ladan Jiracek, Manfred Franke, and Doug Clinton

    Disclaimer

    022 – Tom Hughes Jun 05, 2019
    Show notes

    Tom Hughes is the Senior Principal Advisor in Healthcare Economics and Reimbursement at Regulatory and Clinical Research Institute, Inc. He holds a J.D. from William Mitchell College of Law, and an undergraduate degree from the University of Minnesota-Twin Cities.

    Top 3 Takeaways

    1. The three legs of the reimbursement stool are coding, coverage, and payment.
    2. When figuring out reimbursement, it’s important to consider details like the site of care.
    3. Obtaining reimbursement requires showing evidence that your device is medically necessary.

    Show Notes

    • [1:20] Tom’s winding background.
    • [3:00] What is reimbursement?
    • [5:10] Tom’s process for introducing a company to reimbursement consulting.
    • [7:40] What happens if there isn’t a code for a new device?
    • [9:00] Evidence development.
    • [9:47] Reimbursement evidence vs. clinical trial evidence.
    • [11:10] How to demonstrate medical necessity.
    • [12:15] Where are startups weakest regarding reimbursement?
    • [14:00] The integration of regulatory and reimbursement.
    • [15:20] When to begin thinking about reimbursement.
    • [16:45] Payment vs. coding.
    • [19:30] Cash pay.
    • [20:50] Biggest reimbursement mistakes companies make.
    • [21:10] You should figure out what payor think.

    Selected Links

    • Overview of CPT coding
    • HCPCS codes

    Related Podcasts

    • 020 – Mary Beth Henderson
    • 017 – Ana Maiques
    • 013 – Ladan Jiracek, Manfred Franke, and Doug Clinton

    Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

    021 – Cory Inman Apr 03, 2019
    Show notes

    Cory Inman is a Post Doctoral Fellow at Emory University’s Department of Neurosurgery, where he studies human memory and emotion. Cory holds a B.A. in Experimental Psychology from Georgia State University, and a Ph.D. in Psychology and M.A. in Psychology and Cognitive Neuroscience from Emory University.

    Top 3 Takeaways

    1. Emotion neurostimulation needs to be very precise.
    2. Different depression treatments are better suited to different patients; this is a major challenge of the field.
    3. Stimulating specific brain regions can improve memory retention.

    Show Notes

    • [0:50] Cory’s path into neurotechnology.
    • [2:55] Cory’s research in emotion modulation.
    • [5:20] Some results on human emotion.
    • [6:50] Neurostimulation of the amygdala.
    • [10:05] Pros and cons of DBS and pharmaceuticals for depression.
    • [12:40] Non-invasive neurostimulation for depression treatment.
    • [15:50] Cory’s work with memory enhancement.
    • [19:30] Amygdala-mediated memory enhancement in humans.
    • [22:20] Ethics of memory and emotion enhancement.
    • [25:15] Cory’s favorite neuroscience books

    Selected Links

    • Principles of Neuroscience, by Eric Kandel
    • Brain on Fire, by Susannah Cahalan
    • FDA approval of Esketamine for depression

    Related Podcasts

    • 017 – Ana Maiques
    • 014 – AJ Keller
    • 010 – Matt Angle

    Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

    020 – Mary Beth Henderson Mar 26, 2019
    Show notes

    Mary Beth Henderson is the VP of Regulatory Affairs and Quality Systems at Regulatory and Clinical Research Institute, Inc. She holds a B.A. in Chemistry from Gustavus Adolphus College, an M.S. and Ph.D. in Chemistry from Northwestern University, and an MBA from the University of Massachusetts at Lowell.

    Top 3 Takeaways

    1. Mary Beth’s diverse medical device background gives her an advantage in bringing products through the FDA.
    2. FDA regulatory plans are intricate.
    3. Different classes of medical device have different post-approval requirements.

    Show Notes

    • [1:22] Mary Beth’s background.
    • [5:36] When should companies start to think about regulatory strategy?
    • [8:30] Basic components for developing a regulatory strategy.
    • [13:57] Early-stage medical device companies and use-cases.
    • [16:00] The differences between classes of medical device classes.
    • [19:55] RCRI’s expertise and offering.
    • [21:22] What happens after approval/clearance?
    • [23:25] Changes to Class II products.
    • [24:55] Changes to Class III products.
    • [26:30] The FDA’s attitude toward innovation.
    • [31:50] Reading on regulation.

    Selected Links

    • Overview of FDA medical device regulation
    • Overview of EU medical device regulation

    Related Podcasts

    • 017 – Ana Maiques
    • 014 – AJ Keller
    • 013 – Ladan Jiracek, Manfred Franke, and Doug Clinton

    Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

    019 – Iris Coates McCall Mar 19, 2019
    Show notes

    Iris Coates McCall is a Neurotechnology Researcher at Neuroethics Canada, University of British Columbia. Iris holds a Bachelors of Arts and Science in Cognitive Science from McGill University, and a Masters of Bioethics from Johns Hopkins.

    Top 3 Takeaways

    1. There are three ways to apply ethical guidance to an organization.
    2. Scientific evidence can change people’s beliefs in the credibility of a claim.
    3. The ethics of augmentative neurosurgery are unclear.

    Show Notes

    • [1:00] How does Iris spend her time researching?
    • [2:00] How Iris became involved in neuroethics
    • [4:00] Neuroethics in the workplace
    • [5:05] The ethicist’s practical toolkit
    • [6:10] What kind of regulation governs consumer neurotechnology?
    • [8:50] Enforcement of regulation
    • [10:00] Impact of scientific evidence on what people believe
    • [12:45] What’s the process for translating ethics research into policy/enforcement?
    • [15:20] Do profitability and social good go hand in hand?
    • [18:00] How can ethics be adjudicated?
    • [20:00] Pragmatic neuroethics
    • [22:00] Ethics of augmentative neurosurgery
    • [25:20] Iris’s book recommendation

    Selected Links

    • Portraits of the Mind
    • Neuroethics Canada, UBC

    Related Podcasts

    • 017 – Ana Maiques
    • 014 – AJ Keller
    • 013 – Ladan Jiracek, Manfred Franke, and Doug Clinton

    Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

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