Brain Inspired

Mark and I discuss his book, The Spike: An Epic Journey Through the Brain in 2.1 Seconds. It chronicles how a series of action potentials fire through the brain in a couple seconds of someone's life. Starting with light hitting the retina as a person looks at a cookie, Mark describes how that light gets translated into spikes,  how those spikes get processed in our visual system and eventually transform into motor commands to grab that cookie. Along the way, he describes some of the big ideas throughout the history of studying brains (like the mechanisms to explain how neurons seem to fire so randomly), the big mysteries we currently face (like why do so many neurons do so little?), and some of the main theories to explain those mysteries (we're prediction machines!). A fun read and discussion. This is Mark's second time on the podcast - he was on episode 4 in the early days, talking more in depth about some of the work we discuss in this episode! The Humphries Lab.Twitter: @markdhumphriesBook: The Spike: An Epic Journey Through the Brain in 2.1 Seconds.Related papersA spiral attractor network drives rhythmic locomotion. Timestamps: 0:00 - Intro 3:25 - Writing a book 15:37 - Mark's main interest 19:41 - Future explanation of brain/mind 27:00 - Stochasticity and excitation/inhibition balance 36:56 - Dendritic computation for network dynamics 39:10 - Do details matter for AI? 44:06 - Spike failure 51:12 - Dark neurons 1:07:57 - Intrinsic spontaneous activity 1:16:16 - Best scientific moment 1:23:58 - Failure 1:28:45 - Advice

Steve and I discuss his book, How to Motivate Your Students to Love Learning, which is both a memoir and a guide for teachers and students to optimize the learning experience for intrinsic motivation. Steve taught neuroscience and engineering courses while running his own lab studying the activity of live cultured neural populations (which we discuss at length in his previous episode). He relentlessly tested and tweaked his teaching methods, including constant feedback from the students, to optimize their learning experiences. He settled on real-world, project-based learning approaches, like writing wikipedia articles and helping groups of students design and carry out their own experiments. We discuss that, plus the science behind learning, principles important for motivating students and maintaining that motivation, and many of the other valuable insights he shares in the book. The first half of the episode we discuss diverse neuroscience and AI topics, like brain organoids, mind-uploading, synaptic plasticity, and more. Then we discuss many of the stories and lessons from his book, which I recommend for teachers, mentors, and life-long students who want to ensure they're optimizing their own  learning. Potter Lab.Twitter: @stevempotter.The Book: How to Motivate Your Students to Love Learning.The glial cell activity movie. 0:00 - Intro 6:38 - Brain organoids 18:48 - Glial cell plasticity 24:50 - Whole brain emulation 35:28 - Industry vs. academia 45:32 - Intro to book: How To Motivate Your Students To Love Learning 48:29 - Steve's childhood influences 57:21 - Developing one's own intrinsic motivation 1:02:30 - Real-world assignments 1:08:00 - Keys to motivation 1:11:50 - Peer pressure 1:21:16 - Autonomy 1:25:38 - Wikipedia real-world assignment 1:33:12 - Relation to running a lab

We made it to the last bit of our 100th episode celebration. These have been super fun for me, and I hope you've enjoyed the collections as well. If you're wondering where the missing 5th part is, I reserved it exclusively for Brain Inspired's magnificent Patreon supporters (thanks guys!!!!). The final question I sent to previous guests: Do we already have the right vocabulary and concepts to explain how brains and minds are related? Why or why not? Timestamps: 0:00 - Intro 5:04 - Andrew Saxe 7:04 - Thomas Naselaris 7:46 - John Krakauer 9:03 - Federico Turkheimer 11:57 - Steve Potter 13:31 - David Krakauer 17:22 - Dean Buonomano 20:28 - Konrad Kording 22:00 - Uri Hasson 23:15 - Rodrigo Quian Quiroga 24:41 - Jim DiCarlo 25:26 - Marcel van Gerven 28:02 - Mazviita Chirimuuta 29:27 - Brad Love 31:23 - Patrick Mayo 32:30 - György Buzsáki 37:07 - Pieter Roelfsema 37:26 - David Poeppel 40:22 - Paul Cisek 44:52 - Talia Konkle 47:03 - Steve Grossberg

In the 4th installment of our 100th episode celebration, previous guests responded to the question: What ideas, assumptions, or terms do you think is holding back neuroscience/AI, and why? As usual, the responses are varied and wonderful! Timestamps: 0:00 - Intro 6:41 - Pieter Roelfsema 7:52 - Grace Lindsay 10:23 - Marcel van Gerven 11:38 - Andrew Saxe 14:05 - Jane Wang 16:50 - Thomas Naselaris 18:14 - Steve Potter 19:18 - Kendrick Kay 22:17 - Blake Richards 27:52 - Jay McClelland 30:13 - Jim DiCarlo 31:17 - Talia Konkle 33:27 - Uri Hasson 35:37 - Wolfgang Maass 38:48 - Paul Cisek 40:41 - Patrick Mayo 41:51 - Konrad Kording 43:22 - David Poeppel 44:22 - Brad Love 46:47 - Rodrigo Quian Quiroga 47:36 - Steve Grossberg 48:47 - Mark Humphries 52:35 - John Krakauer 55:13 - György Buzsáki 59:50 - Stefan Leijnan 1:02:18 - Nathaniel Daw

Part 3 in our 100th episode celebration. Previous guests answered the question: Given the continual surprising progress in AI powered by scaling up parameters and using more compute, while using fairly generic architectures (eg. GPT-3): Do you think the current trend of scaling compute can lead to human level AGI? If not, what's missing? It likely won't surprise you that the vast majority answer "No." It also likely won't surprise you, there is differing opinion on what's missing. Timestamps: 0:00 - Intro 3:56 - Wolgang Maass 5:34 - Paul Humphreys 9:16 - Chris Eliasmith 12:52 - Andrew Saxe 16:25 - Mazviita Chirimuuta 18:11 - Steve Potter 19:21 - Blake Richards 22:33 - Paul Cisek 26:24 - Brad Love 29:12 - Jay McClelland 34:20 - Megan Peters 37:00 - Dean Buonomano 39:48 - Talia Konkle 40:36 - Steve Grossberg 42:40 - Nathaniel Daw 44:02 - Marcel van Gerven 45:28 - Kanaka Rajan 48:25 - John Krakauer 51:05 - Rodrigo Quian Quiroga 53:03 - Grace Lindsay 55:13 - Konrad Kording 57:30 - Jeff Hawkins 102:12 - Uri Hasson 1:04:08 - Jess Hamrick 1:06:20 - Thomas Naselaris

In this 2nd special 100th episode installment, many previous guests answer the question: What is currently the most important disagreement or challenge in neuroscience and/or AI, and what do you think the right answer or direction is? The variety of answers is itself revealing, and highlights how many interesting problems there are to work on. Timestamps: 0:00 - Intro 7:10 - Rodrigo Quian Quiroga 8:33 - Mazviita Chirimuuta 9:15 - Chris Eliasmith 12:50 - Jim DiCarlo 13:23 - Paul Cisek 16:42 - Nathaniel Daw 17:58 - Jessica Hamrick 19:07 - Russ Poldrack 20:47 - Pieter Roelfsema 22:21 - Konrad Kording 25:16 - Matt Smith 27:55 - Rafal Bogacz 29:17 - John Krakauer 30:47 - Marcel van Gerven 31:49 - György Buzsáki 35:38 - Thomas Naselaris 36:55 - Steve Grossberg 48:32 - David Poeppel 49:24 - Patrick Mayo 50:31 - Stefan Leijnen 54:24 - David Krakuer 58:13 - Wolfang Maass 59:13 - Uri Hasson 59:50 - Steve Potter 1:01:50 - Talia Konkle 1:04:30 - Matt Botvinick 1:06:36 - Brad Love 1:09:46 - Jon Brennan 1:19:31 - Grace Lindsay 1:22:28 - Andrew Saxe

Brain Inspired turns 100 (episodes) today! To celebrate, my patreon supporters helped me create a list of questions to ask my previous guests, many of whom contributed by answering any or all of the questions. I've collected all their responses into separate little episodes, one for each question. Starting with a light-hearted (but quite valuable) one, this episode has responses to the question, "In the last five years, what new belief, behavior, or habit has most improved your career or well being?" See below for links to each previous guest. And away we go... Timestamps: 0:00 - Intro 6:13 - David Krakauer 8:50 - David Poeppel 9:32 - Jay McClelland 11:03 - Patrick Mayo 11:45 - Marcel van Gerven 12:11 - Blake Richards 12:25 - John Krakauer 14:22 - Nicole Rust 15:26 - Megan Peters 17:03 - Andrew Saxe 18:11 - Federico Turkheimer 20:03 - Rodrigo Quian Quiroga 22:03 - Thomas Naselaris 23:09 - Steve Potter 24:37 - Brad Love 27:18 - Steve Grossberg 29:04 - Talia Konkle 29:58 - Paul Cisek 32:28 - Kanaka Rajan 34:33 - Grace Lindsay 35:40 - Konrad Kording 36:30 - Mark Humphries