Podcasts about theoretical neuroscience

Support the show to get full episodes and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. This is the second conversation I had while teamed up with Gaute Einevoll at a workshop on NeuroAI in Norway. In this episode, Gaute and I are joined by Cristina Savin and Tim Vogels. Cristina shares how her lab uses recurrent neural networks to study learning, while Tim talks about his long-standing research on synaptic plasticity and how AI tools are now helping to explore the vast space of possible plasticity rules. We touch on how deep learning has changed the landscape, enhancing our research but also creating challenges with the "fashion-driven" nature of science today. We also reflect on how these new tools have changed the way we think about brain function without fundamentally altering the structure of our questions. Be sure to check out Gaute's Theoretical Neuroscience podcast as well! Mikkel Lepperød Cristina Savin Tim Vogels Twitter: @TPVogels Gaute Einevoll Twitter: @GauteEinevoll Gaute's Theoretical Neuroscience podcast. Validating models: How would success in NeuroAI look like? Read the transcript, provided by The Transmitter.

Support the show to get full episodes and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. This is the first of two less usual episodes. I was recently in Norway at a NeuroAI workshop called Validating models: How would success in NeuroAI look like? What follows are a few recordings I made with my friend Gaute Einevoll. Gaute has been on this podcast before, but more importantly he started his own podcast a while back called Theoretical Neuroscience, which you should check out. Gaute and I introduce the episode, then briefly speak with Mikkel Lepperød, one of the organizers of the workshop. In this first episode, we're then joined by Ken Harris and Andreas Tolias to discuss how AI has influenced their research, thoughts about brains and minds, and progress and productivity. Validating models: How would success in NeuroAI look like? Mikkel Lepperød Andreas Tolias Twitter: @AToliasLab Ken Harris Twitter: @kennethd_harris Gaute Einevoll Twitter: @GauteEinevoll Gaute's Theoretical Neuroscience podcast. Read the transcript, provided by The Transmitter.

Support the show to get full episodes and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Check out this story: Monkeys build mental maps to navigate new tasks Sign up for “Brain Inspired” email alerts to be notified every time a new “Brain Inspired” episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. Kim Stachenfeld embodies the original core focus of this podcast, the exploration of the intersection between neuroscience and AI, now commonly known as Neuro-AI. That's because she walks both lines. Kim is a Senior Research Scientist at Google DeepMind, the AI company that sprang from neuroscience principles, and also does research at the Center for Theoretical Neuroscience at Columbia University. She's been using her expertise in modeling, and reinforcement learning, and cognitive maps, for example, to help understand brains and to help improve AI. I've been wanting to have her on for a long time to get her broad perspective on AI and neuroscience. We discuss the relative roles of industry and academia in pursuing various objectives related to understanding and building cognitive entities She's studied the hippocampus in her research on reinforcement learning and cognitive maps, so we discuss what the heck the hippocampus does since it seems to implicated in so many functions, and how she thinks of reinforcement learning these days. Most recently Kim at Deepmind has focused on more practical engineering questions, using deep learning models to predict things like chaotic turbulent flows, and even to help design things like bridges and airplanes. And we don't get into the specifics of that work, but, given that I just spoke with Damian Kelty-Stephen, who thinks of brains partially as turbulent cascades, Kim and I discuss how her work on modeling turbulence has shaped her thoughts about brains. Kim's website. Twitter: @neuro_kim. Related papers Scaling Laws for Neural Language Models. Emergent Abilities of Large Language Models. Learned simulators: Learned coarse models for efficient turbulence simulation. Physical design using differentiable learned simulators. Check out the transcript, provided by The Transmitter. 0:00 - Intro 4:31 - Deepmind's original and current vision 9:53 - AI as tools and models 12:53 - Has AI hindered neuroscience? 17:05 - Deepmind vs academic work balance 20:47 - Is industry better suited to understand brains? 24?42 - Trajectory of Deepmind 27:41 - Kim's trajectory 33:35 - Is the brain a ML entity? 36:12 - Hippocampus 44:12 - Reinforcement learning 51:32 - What does neuroscience need more and less of? 1:02:53 - Neuroscience in a weird place? 1:06:41 - How Kim's questions have changed 1:16:31 - Intelligence and LLMs 1:25:34 - Challenges

Emily Mackevicius is a co-founder and director of Basis, a nonprofit applied research organization focused on understanding and building intelligence while advancing society's ability to solve intractable problems.Emily is a member of the Simons Society of Fellows, and a postdoc in the Aronov lab and the Center for Theoretical Neuroscience at Columbia's Zuckerman Institute.Her research uncovers how complex cognitive behaviors are generated by networks of neurons through local interactions and learning mechanisms.Links to work mentioned in this episode: Basis, the research institute co-founded by Emily: basis.aiEmily's work with Fang et. al. relating brain computations to AI/ML algorithms: https://elifesciences.org/articles/80680Basis blog post about this work (Fang et. al.): https://www.basis.ai/blog/sr-fang2023/Stachenfeld et al. paper: https://www.nature.com/articles/nn.4650 Emily's work with Michale Fee relating Reinforcement Learning algorithms to brain areas that birds use when they learn to sing: https://www.sciencedirect.com/science/article/abs/pii/S0959438817302349Emily's work with Aronov lab colleagues on how the hippocampus forms one-shot/episodic memory 'barcodes' in food-caching birds: https://www.cell.com/cell/fulltext/S0092-8674(24)00235-6NPR story about this work: https://www.npr.org/2024/04/05/1198909635/chickadee-bird-brain-memory-brain-pattern-foodGithub collab-creatures repo for the Basis collaborative intelligent systems project: https://github.com/BasisResearch/collab-creaturesBasis's core open-source code repository for causal reasoning, ChiRho: https://basisresearch.github.io/chirho/getting_started.htmlBasis's city policy dashboard, polis: http://polis.basis.ai/

University College London/Sainsbury Wellcome Centre 博士課程の黒田澄哉さん(@_sumiyakuroda)、中野誠大さん(@_mnakano)がゲスト。UCL/SWCでのPhDコース、Tom (& Tim)  ラボでの仕事の様子、PhDアプリケーション時の話、ロンドン生活について伺いました (11/10収録) Show Notes (番組HP): 中野さん 黒田さん Optical BiologyのPhDプログラム SWCのPhDプログラム Tom Mrsic-Flogelラボ Tim Behrensラボ 1 2 Lucy (Rotten Tomatoes) 黒田さんがラマンをやっていたところ USMLE 水島研 大木研 Elective Clerkship（エレクラ）体験談いろいろ Matteo Carandini Kenneth Harris Cortex lab Isaac Bianco Florian Engert Andreas Shaefer クリック研究所のNeuroscience King's College London Jeffrey Erlich Carlos Brody Athena Akrami LabVIEW Bpod (中身はただのTeensy的なマイコン) PyBpod (全然メンテされてなくて微妙) Bonsai Harp Gonçalo Guioma Allen が引き抜いたBruno Cruz の論文とか Ivan Voitov Ivana Orsolic et al., 2021 Neuron Teensy (Arduinoの.inoスケッチで動くマイコン。CPUがArduinoに較べて謎に強力) Aruduino Maxime Rio IBL IBLのHarpによるBehavior control Champalimaud (IBLの出資元) SLM (Spatial Light Modulator) 解説 Michael Häusser Adam Packer 2015 Deisserothが使っているAll Optical Physiology用顕微鏡 Thomas Akam Mohamadyによるプレプリント Timが最初にやったNose Pokeの仕事 Cambridge Probes GPCRのInhibition PdCO 2p SLMでのGtACRを使ったinhibitionは一応あるがまだbiologyには繋がっていない 服部さんのpaAIP使った仕事 古館さん回 1 2 Sonja Hofer SWCの顕微鏡チーム Troy Margrie Rob Campbell Bruno Pichler の会社INSS COSYS のDaleさん Tiago Branco SWCのウイルスのコア SNTN (Systems and Theoretical Neuroscience) 20/21年版 Marcus Stephenson-Jones Tom Otis Angus Silver KennethのNeuroinformaticsコースClass Page Ken Harris のnonsense correlation イメージングとTranscriptomeの対応 Yoh Isogaiラボ (現Allen) Gatsy Computational Neuroscience Unit Peter Latham Maneesh Sahani John O'Keefe Tiago のSynaptic Threshold Goal/Subgoal SC Georg Keller Karl Lashley (タスクが難しすぎる&マルチモーダル過ぎたのが敗因と解釈されることが多い) Rainer Friedrich 元々DTIをやっていた Mark Walton Tolman-Eichenbaum Machineの論文 James Whittington 金森さん 2011年のHo Ko論文 Ho Ko lab Andy Murray lab デスク含め全てが波打っている SpareRoom Editorial Notes: LUCY観た人いたら連絡してください笑（中野） Georg推し人間みたいな感じになってしまいました（黒田） ２人とも今すぐポッドキャストのホストできそうな感じで面白かったです（脇） 新海は言の葉の庭(を含む)以前派です。黒田さんがPAWorks推しと認識してるのですがShirobakoの話するの忘れました（萩）

Patreon: https://www.patreon.com/mlst Discord: https://discord.gg/ESrGqhf5CB Twitter: https://twitter.com/MLStreetTalk Chris Eliasmith is a renowned interdisciplinary researcher, author, and professor at the University of Waterloo, where he holds the prestigious Canada Research Chair in Theoretical Neuroscience. As the Founding Director of the Centre for Theoretical Neuroscience, Eliasmith leads the Computational Neuroscience Research Group in exploring the mysteries of the brain and its complex functions. His groundbreaking work, including the Neural Engineering Framework, Neural Engineering Objects software environment, and the Semantic Pointer Architecture, has led to the development of Spaun, the most advanced functional brain simulation to date. Among his numerous achievements, Eliasmith has received the 2015 NSERC "Polany-ee" Award and authored two influential books, "How to Build a Brain" and "Neural Engineering." Chris' homepage: http://arts.uwaterloo.ca/~celiasmi/ Interviewers: Dr. Tim Scarfe and Dr. Keith Duggar TOC: Intro to Chris [00:00:00] Continuous Representation in Biologically Plausible Neural Networks [00:06:49] Legendre Memory Unit and Spatial Semantic Pointer [00:14:36] Large Contexts and Data in Language Models [00:20:30] Spatial Semantic Pointers and Continuous Representations [00:24:38] Auto Convolution [00:30:12] Abstractions and the Continuity [00:36:33] Compression, Sparsity, and Brain Representations [00:42:52] Continual Learning and Real-World Interactions [00:48:05] Robust Generalization in LLMs and Priors [00:56:11] Chip design [01:00:41] Chomsky + Computational Power of NNs and Recursion [01:04:02] Spiking Neural Networks and Applications [01:13:07] Limits of Empirical Learning [01:22:43] Philosophy of Mind, Consciousness etc [01:25:35] Future of human machine interaction [01:41:28] Future research and advice to young researchers [01:45:06] Refs: http://compneuro.uwaterloo.ca/publications/dumont2023.html  http://compneuro.uwaterloo.ca/publications/voelker2019lmu.html  http://compneuro.uwaterloo.ca/publications/voelker2018.html http://compneuro.uwaterloo.ca/publications/lu2019.html  https://www.youtube.com/watch?v=I5h-xjddzlY

A theoretical neuroscientist, Ann Kennedy, PhD, is investigating neural computation and the structure of behavior. In this episode, she talks about her recent research in the area of aggression and how it's regulated in the brains of animals. She was recently named the winner of the 2022 Eppendorf and Science Prize for Neurobiology.

Trigger warning: This podcast episode contains discussion of suicidal ideation.In Episode 76 (recorded live), Dr. Vivienne Ming, Founder, and CEO of Socos Labs, joins Melinda to discuss her new research on the neuroscience of trust in the workplace. They explore why we tend to feel an innate sense of trust in certain people over others, how we can overcome these biases to strengthen the trust on our teams, and how working remotely can shift how we build trust and psychological safety.About Dr. Vivienne Ming (she/her)Dr. Vivienne Ming explores maximizing human capacity as a theoretical neuroscientist, delusional inventor, and demented author.Over her career, she's founded 6 startups, been chief scientist at 2 others, and launched the “mad science incubator”, Socos Labs, where she explores seemingly intractable problems—from a lone child's disability to global economic inclusion—for free.Vivienne's other companies apply machine learning to lessen the corrosive health effects of chronic stress in communities, fight bias in hiring and promotion, develop neurotechnologies to treat dementia and TBI, and promote learning at home and in school. As a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, she pursued her research in cognitive neuroprosthetics.In her free time, Vivienne designs AI systems to treat her son's diabetes, predict manic episodes in bipolar sufferers, and reunite orphan refugees with extended family members. For relaxation, she writes science fiction and spends time with her wife and children.Vivienne was named one of “10 Women to Watch in Tech” by Inc. Magazine and one of the BBC's 100 Women in 2017. Find Leading With Empathy & Allyship useful? Subscribe to our podcast and like this episode!For more about Change Catalyst, and to join us for our monthly live event, visit https://ally.cc. There, you'll also find educational resources and highlights from this episode.Connect With Dr. Vivienne Ming On SocialLinkedIn https://www.linkedin.com/in/vivienneming/Twitter https://twitter.com/neuraltheoryConnect With Us On SocialYouTube: youtube.com/c/changecatalystTwitter: twitter.com/changecatalystsFacebook: facebook.com/changecatalystsInstagram: instagram.com/techinclusionLinkedIn: linkedin.com/company/changecatalystsProduction TeamCreator & Host: Melinda Briana EplerCo-Producers: Renzo Santos & Christina Swindlehurst ChanCreative Director @ Podcast Rocket: Rob ScheerbarthThis episode is sponsored by First Tech Federal Credit Union, a member-owned financial institution that is powered by a people-before-profit philosophy. Learn more at https://www.firsttechfed.com[Image description: Leading With Empathy & Allyship promo with the Change Catalyst logo and photos of Dr. Vivienne Ming, a White trans female with shoulder-length blonde hair, who is wearing a black sleeveless blouse and smiling at the camera, and host Melinda Briana Epler, a White woman with red hair, glasses, and an orange shirt holding a white mug behind a laptop.]Support the show (http://patreon.com/changecatalysts)

Episode 19, Segment 3 of 3 – Dr. Vivienne Ming – Inventing Superpowers Trident Room Host Mike Wish sits down and has a conversation with philanthropic mad scientist Dr. Vivienne Ming. This episode was recorded on August 24, 2021. Dr. Vivienne Ming explores maximizing human capacity as a theoretical neuroscientist, delusional inventor, and demented author. Over her career she's founded 6 startups, been chief scientist at 2 others, and launched the “mad science incubator", Soco's Labs, where she explores seemingly intractable problems—from a lone child's disability to global economic inclusion—for free. Vivienne's other companies apply machine learning to lessen the corrosive health effects of chronic stress in communities, fight bias in hiring and promotion, develop Neurotechnologies to treat dementia and TBI, and promote learning at home and in school. As a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, she pursued her research in researching neuroprosthetics. In her free time, Vivienne designs AI systems to treat her son's diabetes, predict manic episodes in bipolar sufferers, and reunite orphan refugees with extended family members. For relaxation, she writes science fiction and spends time with her wife and children. Vivienne was named “10 Women to Watch in Tech” by Inc. Magazine and one of the BBC's 100 Women in 2017. She is featured frequently for her research and inventions in The Financial Times, The Atlantic, Quartz Magazine and the New York Times. Twitter: @neuraltheory LinkedIn: www.linkedin.com/in/vivienneming/ The Trident Room Podcast is brought to you by the Naval Postgraduate School Alumni Association and the Naval Postgraduate School Foundation. npsfoundation.org/ For comments, suggestions, and critiques, please email us at TridentRoomPodcastHost@nps.edu, and find us online at nps.edu/tridentroompodcast. Thank you! The views expressed in this interview are those of the individuals and do not reflect the official policy or position of the U.S. Government, the Department of Defense, the US Navy, or the Naval Postgraduate School.

Episode 19, Segment 1 of 3 – Dr. Vivienne Ming – A Shared Purpose Trident Room Host Mike Wish sits down and has a conversation with philanthropica mad scientist Dr. Vivienne Ming. This episode was recorded on August 24, 2021. Dr. Vivienne Ming explores maximizing human capacity as a theoretical neuroscientist, delusional inventor, and demented author. Over her career she's founded 6 startups, been chief scientist at 2 others, and launched the “mad science incubator", Soco's Labs, where she explores seemingly intractable problems—from a lone child's disability to global economic inclusion—for free. Vivienne's other companies apply machine learning to lessen the corrosive health effects of chronic stress in communities, fight bias in hiring and promotion, develop Neurotechnologies to treat dementia and TBI, and promote learning at home and in school. As a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, she pursued her research in researching neuroprosthetics. In her free time, Vivienne designs AI systems to treat her son's diabetes, predict manic episodes in bipolar sufferers, and reunite orphan refugees with extended family members. For relaxation, she writes science fiction and spends time with her wife and children. Vivienne was named “10 Women to Watch in Tech” by Inc. Magazine and one of the BBC's 100 Women in 2017. She is featured frequently for her research and inventions in The Financial Times, The Atlantic, Quartz Magazine and the New York Times. Twitter: @neuraltheory LinkedIn: www.linkedin.com/in/vivienneming/ The Trident Room Podcast is brought to you by the Naval Postgraduate School Alumni Association and the Naval Postgraduate School Foundation. npsfoundation.org/ For comments, suggestions, and critiques, please email us at TridentRoomPodcastHost@nps.edu, and find us online at nps.edu/tridentroompodcast. Thank you! The views expressed in this interview are those of the individuals and do not reflect the official policy or position of the U.S. Government, the Department of Defense, the US Navy, or the Naval Postgraduate School.

Episode 19, Segment 2 of 3 – Dr. Vivienne Ming – MAD SCIENCE Trident Room Host Mike Wish sits down and has a conversation with philanthropic mad scientist Dr. Vivienne Ming. This episode was recorded on August 24, 2021. Dr. Vivienne Ming explores maximizing human capacity as a theoretical neuroscientist, delusional inventor, and demented author. Over her career she's founded 6 startups, been chief scientist at 2 others, and launched the “mad science incubator", Soco's Labs, where she explores seemingly intractable problems—from a lone child's disability to global economic inclusion—for free. Vivienne's other companies apply machine learning to lessen the corrosive health effects of chronic stress in communities, fight bias in hiring and promotion, develop Neurotechnologies to treat dementia and TBI, and promote learning at home and in school. As a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, she pursued her research in researching neuroprosthetics. In her free time, Vivienne designs AI systems to treat her son's diabetes, predict manic episodes in bipolar sufferers, and reunite orphan refugees with extended family members. For relaxation, she writes science fiction and spends time with her wife and children. Vivienne was named “10 Women to Watch in Tech” by Inc. Magazine and one of the BBC's 100 Women in 2017. She is featured frequently for her research and inventions in The Financial Times, The Atlantic, Quartz Magazine and the New York Times. Twitter: @neuraltheory LinkedIn: www.linkedin.com/in/vivienneming/ The Trident Room Podcast is brought to you by the Naval Postgraduate School Alumni Association and the Naval Postgraduate School Foundation. npsfoundation.org/ For comments, suggestions, and critiques, please email us at TridentRoomPodcastHost@nps.edu, and find us online at nps.edu/tridentroompodcast. Thank you! The views expressed in this interview are those of the individuals and do not reflect the official policy or position of the U.S. Government, the Department of Defense, the US Navy, or the Naval Postgraduate School.

In this episode of Intel on AI host Amir Khosrowshahi and Bruno Olshausen talk about neuroscience and the future of computing. Bruno is a professor at Berkeley with appointments in the Helen Wills Neuroscience Institute and School of Optometry. He is also the director of the Redwood center for Theoretical Neuroscience, which brings the fields of physics, mathematics, engineering, and neuroscience together to study how networks of neurons in the brain process information. In the episode, Bruno and Amir discuss research about recording large populations of neurons, hyperdimensional computing, and discovering new types of engineering principles. Bruno talks about how in order to understand intelligence and its underpinnings, we have to understand the origins of intelligence and perceptual psychology outside of mammalian brains. He points to the sophisticated visual system of jumping spiders as inspiration for developing systems that use low energy in a small form factor. By better understanding the origins of perception and other biophysical structures, Bruno theorizes the artificial intelligence field may evolve beyond image recognition tasks of current neural networks. Bruno and Amir close the episode by talking about the elementary units of computation, the idea of “listening to silicon” as proposed by Carver Mead, neuromorphic computing, and what the future of research might hold. Academic research discussed in the podcast episode: Spatially Distributed Local Fields in the Hippocampus Encode Rat Position Beyond inspiration: Three lessons from biology on building intelligent machines The Chinese Room Argument Digital tissue and what it may reveal about the brain Principles of Neural Design (Bruno calls this a “must read”) Experiencing and Perceiving Visual Surfaces Analog VLSI Implementation of Neural Systems OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems

Jeffrey Hawkins speaks exclusively to Indian Genes, he is the American founder of Palm Computing and Handspring where he invented the PalmPilot and Treo, respectively. He has since turned to work on neuroscience full-time, founding the Redwood Center for Theoretical Neuroscience (formerly the Redwood Neuroscience Institute) in 2002 and Numenta in 2005. Hawkins is currently Chief Scientist at Numenta, where he leads a team in efforts to reverse-engineer the neocortex and enable machine intelligence technology based on brain theory. Hawkins is the author of On Intelligence which explains his memory-prediction framework theory of the brain. In March 2021, he released his second book, A Thousand Brains: A New Theory of Intelligence, which details the discoveries he and the Numenta team made that led to the Thousand Brains Theory of Intelligence.

Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. His previous book, On Intelligence, was an impressive scientific journey into intelligence as a memory-prediction system for experiences and therefore vastly different than a computer. He compared a human brain’s neuron to two machine neurons: a traditional neural network neuron and his version of a more sophisticated one in the form of hierarchical temporal memory (HTM) cells. Almost 20 years later, he takes this earlier HTM concept to a higher plane and has truly established himself as both a formidable teacher and an ardent student of intelligence. His latest book, A Thousand Brains: A New Theory of Intelligence, is framed in the construct of how the neocortex represents object compositionally, object behaviors, and higher level concepts. The main premise is that every part of the neocortex learns complete models of objects and concepts, and that there are many such models of each object distributed throughout the neocortex that have long range connections (hence the title of the book). https://numenta.com https://twitter.com/numenta https://www.youtube.com/watch?v=-EVqrDlAqYo https://www.ted.com/speakers/jeff_hawkins https://ai-med.io/analysis/a-thousand-brains-jeff-hawkins/ HELP ME CROWDFUND MY GAMESTOP BOOK. Go to https://wen-moon.com or join the crowdfunding campaign and pre-order my next book If you haven’t already and you enjoyed this episode, please subscribe to this podcast and our mailing list, and don’t forget, my book, Brexit: The Establishment Civil War, is now out, you’ll find the links in the description below. Express VPN 12 Months 35% off!! - https://www.xvinlink.com/?a_fid=chatter​ NameCheap - https://namecheap.pxf.io/WD4Xrn Spreaker - https://spreaker.pxf.io/0JmQoL Watch Us On Odysee.com - https://odysee.com/$/invite/@TheJist:4 Sign up and watch videos to earn crypto-currency! Buy Brexit: The Establishment Civil War - https://amzn.to/39XXVjq Mailing List - https://www.getrevue.co/profile/thejist Twitter - https://twitter.com/Give_Me_TheJist Website -

Grace Lindsay is a computational neuroscientist currently based at University College London. She completed her PhD at the Centre for Theoretical Neuroscience at Columbia University, where her research focused on building mathematical models of how the brain controls its own sensory processing. Before that, she earned a bachelor's degree in Neuroscience from the University of Pittsburgh and received a research fellowship to study at the Bernstein Center for Computational Neuroscience in Freiburg, Germany. She was awarded a Google PhD Fellowship in Computational Neuroscience in 2016. To find out more about Grace, her book and her work click on the following link:tinyurl.com/h9dn4bw7 To find out more about me, my books and my work go to:www.fionamurden.com  

Episode 4 – A Glimpse into the Neural Code: Theoretical Neuroscience with Dr. Larry Abbott Our guest is Dr. Larry Abbott, a pioneer in the field of theoretical neuroscience and also the co-director of the Center of Theoretical Neuroscience at Columbia University. We enjoyed learning about theoretical neuroscience as it relates to the broader neuroscience […]

In this episode, we talk with Jeff Hawkins—an entrepreneur and scientist, known for inventing some of the earliest handheld computers, the Palm and the Treo, who then turned his career to neuroscience and founded the Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005—about a new theory about how the cells in our brain work to create intelligence. What exactly is happening in the neocortex as our brains process and interpret information and sensory input—like sight, smell, touch, or language, or math—to create a perception of and to navigate through the world around us?  a16z General Partner Vijay Pande and I talk to Jeff about the basic principles in this new idea of the brain’s learning methodology for creating not just human intelligence, but animal intelligence, artificial intelligence, even alien intelligence, which he lays out in his newly just released book, A Thousand Brains: A New Theory of Intelligence. The conversation covers how the neocortex builds models of the world around us, and what this could mean for how we design the next generation of truly intelligent machines. This episode goes all the way from tiny neurons and how they speak to each other to what’s happening in optical illusions to the future of humanity and beyond.

Dr. Simon Stringer. Obtained his Ph.D in mathematical state space control theory and has been a Senior Research Fellow at Oxford University for over 27 years. Simon is the director of the the Oxford Centre for Theoretical Neuroscience and Artificial Intelligence, which is based within the Oxford University Department of Experimental Psychology. His department covers vision, spatial processing, motor function, language and consciousness -- in particular -- how the primate visual system learns to make sense of complex natural scenes. Dr. Stringers laboratory houses a team of theoreticians, who are developing computer models of a range of different aspects of brain function. Simon's lab is investigating the neural and synaptic dynamics that underpin brain function. An important matter here is the The feature-binding problem which concerns how the visual system represents the hierarchical relationships between features. the visual system must represent hierarchical binding relations across the entire visual field at every spatial scale and level in the hierarchy of visual primitives. We discuss the emergence of self-organised behaviour, complex information processing, invariant sensory representations and hierarchical feature binding which emerges when you build biologically plausible neural networks with temporal spiking dynamics. 00:00:09 Tim Intro 00:09:31 Show kickoff 00:14:37 Hierarchical Feature binding and timing of action potentials 00:30:16 Hebb to Spike-timing-dependent plasticity (STDP) 00:35:27 Encoding of shape primitives 00:38:50 Is imagination working in the same place in the brain 00:41:12 Compare to supervised CNNs 00:45:59 Speech recognition, motor system, learning mazes 00:49:28 How practical are these spiking NNs 00:50:19 Why simulate the human brain 00:52:46 How much computational power do you gain from differential timings 00:55:08 Adversarial inputs 00:59:41 Generative / causal component needed? 01:01:46 Modalities of processing i.e. language 01:03:42 Understanding 01:04:37 Human hardware 01:06:19 Roadmap of NNs? 01:10:36 Intepretability methods for these new models 01:13:03 Won't GPT just scale and do this anyway? 01:15:51 What about trace learning and transformation learning 01:18:50 Categories of invariance 01:19:47 Biological plausibility https://www.youtube.com/watch?v=aisgNLypUKs

Applying some of Karl Popper's and David Deutsch's ideas to analyze and evaluate Elon Musk's recent Neuralink presentation and the Q&A afterward. Throwing some of my own ideas into the mix as well. Errors mine. If you enjoyed this episode, follow me on Twitter: https://twitter.com/dchackethal References - The original presentation and Q&A: https://www.youtube.com/watch?v=DVvmgjBL74w - The neo-Darwinian theory of the mind (written article): https://medium.com/conjecture-magazine/the-neo-darwinian-theory-of-the-mind-d84c0bcc6485 - The neo-Darwinian theory of the mind (read out loud): https://soundcloud.com/dchacke/16-the-neo-darwinian-theory-of-the-mind - David Deutsch’s interview on CBC radio: https://www.cbc.ca/radio/tapestry/the-new-human-1.4696724/oxford-physicist-predicts-ai-will-be-human-in-all-but-name-1.4696754 - David Deutsch’s second interview with Sam Harris: https://samharris.org/podcasts/finding-our-way-in-the-cosmos/ - Article about fluid buildup replacing much of man’s brain: https://www.newscientist.com/article/dn12301-man-with-tiny-brain-shocks-doctors/ - David Deutsch, “The Beginning of Infinity,” chapters 5 (levels of emergence and abstractions), 12 (bad philosophy), 13 (Balinksi’s and Young’s no-go theorem regarding “deriving” the will of the group from the will of each individual) - Karl Popper, “Objective Knowledge,” appendix “The Bucket and the Searchlight” - Karl Popper, “Alle Menschen sind Philosophen,” Kapitel “Zweites Präludium: Die Zukunft ist offen” (the conversation with Konrad Lorenz) - Redwood Center for Theoretical Neuroscience ("Our Goal" section): https://redwood.berkeley.edu/ - https://en.wikipedia.org/wiki/Hard_problem_of_consciousness - https://en.wikipedia.org/wiki/Telepathy Additional source - Twitter thread by Dennis containing tweets made live during the event: https://twitter.com/dchackethal/status/1299500744287031296 Correction: at 15:00, I say that memories are always based on self-replicating ideas *that have high longevity*. That's not true. A memory could be a self-replicating idea with low longevity but high fecundity and high copying fidelity.

Dr. Vivienne Ming is a theoretical neuroscientist, entrepreneur, and author frequently featured for her research and inventions in The Financial Times, The Atlantic, Quartz and the New York Times,. She co-founded Socos Labs, her fifth company, a mad science incubator. Previously, Vivienne was a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, pursuing her research in cognitive neuroprosthetics. In her free time, Vivienne has invented AI systems to help treat her diabetic son, predict manic episodes in bipolar sufferers weeks in advance, and reunited orphan refugees with extended family members. She sits on the boards of numerous companies and nonprofits.

Dr. Vivienne Ming is a theoretical neuroscientist, entrepreneur, and author frequently featured for her research and inventions in The Financial Times, The Atlantic, Quartz and the New York Times,. She co-founded Socos Labs, her fifth company, a mad science incubator. Previously, Vivienne was a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, pursuing her research in cognitive neuroprosthetics. In her free time, Vivienne has invented AI systems to help treat her diabetic son, predict manic episodes in bipolar sufferers weeks in advance, and reunited orphan refugees with extended family members. She sits on the boards of numerous companies and nonprofits.

Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where

Thursday, February 7, 2019 This episode is a panel discussion recorded as the conclusion of a two part series showcasing Present & Future Frameworks in Theoretical Neuroscience, an international workshop hosted by Horacio Rotstein (NJIT) & Fidel Santamaria (UTSA) through support of NSF's Brain Initiative (see episode 194 for Part I). Part II is a round table with a new group that recaps the themes of the workshop and reports on the main themes of the discussions that occurred in each of the five workgroups. Many trainees were involved in the workshop, and two of them join the panel to highlight the value and necessity of fresh voices to any discussion about the future of theoretical neuroscience. Workshop co-organizer Fidel Santamaria leads the panel. Duration: 34 minutes Panel:(in alphabetical order, pictured left to right) Habiba Azab, PhD student, Ben Hayden lab, UMN - Student perspective on Organizing Theories Workgroup Carmen Canavier, Professor & Vice Chair, LSU Health Krešimir Josić, Professor, Univ of Houston; Chair, Gulf Coast Consortium for Theoretical & Computational Neuroscience Farzan Nadim, Professor, NJIT-Rutgers Newark. Organizing Theories Workgroup Horacio Rotstein, Professor, NJIT, Workshop organizer and Co-chair Matthew Singh, PhD student, Braver lab & Ching lab, WUStL Fidel Santamaria, Professor, UTSA, Workshop organizer and Co-chair Recorded at the Emily Morgan Hotel, San Antonio TX. acknowledgement: JM Tepper for original music.

This episode is a panel discussion recorded as the conclusion of a two part series showcasing Present & Future Frameworks in Theoretical Neuroscience, an international workshop hosted by Horacio Rotstein (NJIT) & Fidel Santamaria (UTSA) through support of NSF’s Brain Initiative (see episode 194 for Part I). Part II is a round table with a new group that recaps the themes of the workshop and reports on the main themes of the discussions that occurred in each of the five workgroups. Many trainees were involved in the workshop, and two of them join the panel to highlight the value and necessity of fresh voices to any discussion about the future of theoretical neuroscience. Workshop co-organizer Fidel Santamaria leads the panel. Duration: 34 minutesPanel:(in alphabetical order, pictured left to right)Habiba Azab, PhD student, Ben Hayden lab, UMN - Student perspective on Organizing Theories WorkgroupCarmen Canavier, Professor & Vice Chair, LSU HealthKrešimir Josić, Professor, Univ of Houston; Chair, Gulf Coast Consortium for Theoretical & Computational NeuroscienceFarzan Nadim, Professor, NJIT-Rutgers Newark. Organizing Theories WorkgroupHoracio Rotstein, Professor, NJIT, Workshop organizer and Co-chairMatthew Singh, PhD student, Braver lab & Ching lab, WUStLFidel Santamaria, Professor, UTSA, Workshop organizer and Co-chairRecorded at the Emily Morgan Hotel, San Antonio TX.acknowledgement: JM Tepper for original music.

Monday, February 4, 2019 This episode is a panel discussion recorded as Part I of a two part series on the recent Present & Future Frameworks in Theoretical Neuroscience, an international workshop hosted by Horacio Rotstein (NJIT) & Fidel Santamaria (UTSA) with support from the NSF's Brain Initiative. Part I is a preamble recorded on day one of the meeting, in which some friends of the podcast (see below) define the need for the workshop and identify their objectives as they undertake their workgroups. Hosted by Salma Quraishi. Stay tuned for Part II, which was recorded at the close of the workshop. Part II will be posted separately as a follow up to summarize some of the critical discussions that transpired in the workgroups. Duration: 33 minutes Panel:(in alphabetical order, pictured left to right) Veronica Alvarez, Senior Investigator, IRP NIAAA Alain Destexhe, Research Director, CNRS Paris Tatiana Engel, Assistant Professor, CSHL Horacio Rotstein, Professor, NJIT David Redish, Distinguished McKnight Professor, University of Minnesota Fidel Santamaria, Professor, UTSA Recorded at the Emily Morgan Hotel, San Antonio TX. acknowledgement: JM Tepper for original music.

This episode is a panel discussion recorded as Part I of a two part series on the recent Present & Future Frameworks in Theoretical Neuroscience, an international workshop hosted by Horacio Rotstein (NJIT) & Fidel Santamaria (UTSA) with support from the NSF’s Brain Initiative. Part I is a preamble recorded on day one of the meeting, in which some friends of the podcast (see below) define the need for the workshop and identify their objectives as they undertake their workgroups. Hosted by Salma Quraishi.Stay tuned for Part II, which was recorded at the close of the workshop. Part II will be posted separately as a follow up to summarize some of the critical discussions that transpired in the workgroups. Duration: 33 minutesPanel:(in alphabetical order, pictured left to right)Veronica Alvarez, Senior Investigator, IRP NIAAAAlain Destexhe, Research Director, CNRS ParisTatiana Engel, Assistant Professor, CSHLHoracio Rotstein, Professor, NJITDavid Redish, Distinguished McKnight Professor, University of MinnesotaFidel Santamaria, Professor, UTSARecorded at the Emily Morgan Hotel, San Antonio TX.acknowledgement: JM Tepper for original music.

My guest today is a theoretical neuroscientist, technologist and entrepreneur who was named one of Inc. Magazine's top 10 women to watch in tech in 2013. She co-founded Socos, a cutting-edge startup which applies cognitive modeling to create adaptive, personalized educational technology. She is also a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience pursuing her research in neuroprosthetics. Previously, she was a junior fellow at Standford's Mind, Brain & Computation Center and earned her Ph.D. from Carnegie Mellon. Her work and research has received a ton of media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and The Atlantic. In this interview, we discuss her INCREDIBLE STORY, how technology will be used to predict our learning and performance, how we can change life outcomes, how prosthetic devices will be used to alter and repair or brains and bodies, and the very realistic possibility of a hyper-intelligent superhuman race… and that's just in the first 30 minutes.

Holger Lyre (Magdeburg) gives a talk at the MCMP Colloquium (6 May, 2015) titled "Structures, Mechanisms and Dynamics in Theoretical Neuroscience". Abstract: Proponents of mechanistic explanations have recently proclaimed that all explanations in the neurosciences appeal to mechanisms – including computational and dynamical explanations. The purpose of the talk is to critically assess these statements. I shall defend an understanding of both dynamical and computational explanations according to which they focus on the explanatorily relevant spatiotemporal-cum-causal structures in the target domain. This has impact on at least three important issues: reductionism, multi-realizability, and explanatory relevance. A variety of examples from the theoretical neurosciences shall be used to show that very often the explanatory relevance, burden, and advantage in view of law-like generalizability lies in picking out the relevant structure rather than characterizing mechanisms in all details.

Prof. Chris Eliasmith is currently the director of the Centre for Theoretical Neuroscience at University of Waterloo and the team-leader behind SPAUN – the brain simulation project that recently made news around the world. So, when I discovered that Eliasmith’s lab is just over an hour worth of driving from my place, I decided that I […]