On biophysics of computation – with Christof Koch - #2

Theoretical Neuroscience Podcast

#Science #Biology #Physics #Gaute Einevoll

41:05

When negative feedback shakes your confidence, it can be difficult to get back to feeling like yourself at work. In this episode, Anne and Frances help a struggling listener who has spent years toning herself down in the workplace after being told that she was too assertive — now, she feels that her modest approach is holding her back. Together, they use Anne and Frances’s “trust triangle” framework to explore how empathy, authenticity, and logic can help you rebuild confidence and trust with your colleagues, and share helpful confidence hacks for getting comfy with discomfort. What problems are you dealing with at work? Text or call 234-FIXABLE or email fixable@ted.com to be featured on the show. For the full text transcript, visit ted.com/podcasts/fixable-transcripts Want to help shape TED’s shows going forward? Fill out our survey ! Hosted on Acast. See acast.com/privacy for more information.…

2 years ago 1:20:10

MP3•Episode home

Starting from the pioneering work of Hodgkin, Huxley and Rall in the 1950s and 60s, we have a well-founded biophysics-based mathematical understanding of how neurons integrate signals from other neurons and generate action potentials.

Today’s guest wrote the classic book “Biophysics of Computation” on the subject in 1998.

We discuss its contents, what has changed in the last 25 years, and also touch on his other main research interest: consciousness research.

28 episodes

On biophysics of computation – with Christof Koch - #2

Theoretical Neuroscience Podcast

14 subscribers

published 2 years ago

MP3•Episode home

Today’s guest wrote the classic book “Biophysics of Computation” on the subject in 1998.

We discuss its contents, what has changed in the last 25 years, and also touch on his other main research interest: consciousness research.

28 episodes

#Science #Biology #Physics #Gaute Einevoll

All episodes

Theoretical Neuroscience Podcast

1
On whole-cell modeling of bacteria - with Markus Covert - #28 2:04:23

25 days ago2:04:23

2:04:23

A future computational neuroscience project could be to model not only the signal processing properties of neurons, but also all processes that keep a neuron alive for, say, a 100-year life span. In 2012 the group of the guest published the first such whole-cell model for a very simple bacterium (M. genitalia). In 2020 a model of the larger E. coli bacterium comprising 10.000 equations and 19.000 model parameters was presented. How are such models built, and what can they do?…

Theoretical Neuroscience Podcast

1
On construction and clinical use of multipurpose neuron models - with Etay Hay - #27 1:13:21

8 weeks ago1:13:21

1:13:21

Numerous neuron models have been made, but most of them are "single-purpose" in that they are made to address a single scientific question. In contrast, multipurpose neuron models are made to be used to address many scientific questions. In 2011, the guest published a multipurpose rodent pyramidal-cell model which has been actively used by the community ever since. We talk about how such models are made, and how his group later built human neuron models to explore network dynamics in brains of depressed patients.…

Theoretical Neuroscience Podcast

1
On the population code in visual cortex - with Kenneth Harris - #26 1:24:49

12 weeks ago1:24:49

1:24:49

With modern electrical and optical measurement techniques, we can now measure neural activity in hundreds or thousands of neurons simultaneously. This allows for the investigation of population codes, that is, of how groups of neurons together encode information. In 2019 today’s guest published a seminal paper with collaborators at UCL in London where analysis of optophysiological data from 10.000 neurons in mouse visual cortex revealed an intriguing population code balancing the needs for efficient and robust coding. We discuss the paper and (towards the end) also how new AI tools may be a game-changer for neuroscience data analysis.…

Theoretical Neuroscience Podcast

1
On growing synthetic dendrites – with Hermann Cuntz - #25 1:34:34

16 weeks ago1:34:34

1:34:34

The observed variety of dendritic structures in the brains is striking. Why are they so different, and what determine the branching patterns? Following the dictum “if you understand it, you can build it”, the lab of the guest builds dendritic structures in a computer and explore the underlying principles. Two key principles seem to be to minimize (i) the overall length of dendrites and (ii) the path length from the synapses to the soma.…

Theoretical Neuroscience Podcast

1
On neuroscience foundation models - with Andreas Tolias - #24 1:31:43

20 weeks ago1:31:43

1:31:43

The term “foundation model” refers to machine learning models that are trained on vast datasets and can be applied to a wide range of situations. The large language model GPT-4 is an example. The group of the guest has recently presented a foundation model for optophysiological responses in mouse visual cortex trained on recordings from 135.000 neurons in mice watching movies. We discuss the design, validation, use of this and future neuroscience foundation models.…

Theoretical Neuroscience Podcast

1
On human whole-brain models - with Viktor Jirsa - #23 1:55:21

24 weeks ago1:55:21

1:55:21

A holy grail of the multiscale approach for physical brain modelling is to link the different scales from molecules, via cells and local neural networks, up to whole-brain models. The goal of the Virtual Brain Twin project, lead by today’s guest, is to use personalized human whole-brain models to aid clinicians in treating brain ailments. The podcast discusses how such models are presently made using neural field models, starting with neuron population dynamics rather than molecular dynamics.…

Theoretical Neuroscience Podcast

1
On 40 years with the Hopfield network model - with Wulfram Gerstner - #22 1:27:49

28 weeks ago1:27:49

1:27:49

In 1982 John Hopfield published the paper "Neural networks and physical systems with emergent collective computational abilities" describing a simple network model functioning as an associative and content-addressable memory. The paper started a new subfield in computational neuroscience and led to the influx of numerous theoretical scientists, in particular physicists, to the field. The podcast guest wrote his PhD thesis on the model in the early 1990s, and we talk about the history and present impact of the model.…

Theoretical Neuroscience Podcast

1
On models for short-term memory - with Pawel Herman - #21 1:47:42

32 weeks ago1:47:42

1:47:42

The leading theory for learning and memorization in the brain is that learning is provided by synaptic learning rules and memories stored in synaptic weights between neurons. But this is for long-term memory. What about short-term, or working, memory where objects are kept in memory for only a few seconds? The traditional theory held that here the mechanism is different, namely persistent firing of select neurons in areas such as prefrontal cortex. But this view is challenged by recent synapse-based models explored by today’s guest and others.…

Theoretical Neuroscience Podcast

1
On neuro-AI on the boat - part 2 of 2 - with Cristina Savin, Tim Vogels, Mikkel Lepperød, Paul Middlebrooks - #20 1:21:03

36 weeks ago1:21:03

1:21:03

In September Paul Middlebrooks, the producer of the podcast BrainInspired, and I were both on a neuro-AI workshop on a coast liner cruising the Norwegian fjords. We decided to make two joint podcasts with some of the participants where we discuss the role of AI in neuroscience. In this second part we discuss the topic with Cristina Savin and Tim Vogels and round off with a brief discussion with Mikkel Lepperød, the main organizer of the workshop, about what he learned from the workshop.…

Theoretical Neuroscience Podcast

1
On neuro-AI on the boat - part 1 of 2 - with Ken Harris, Andreas Tolias, Mikkel Lepperød, Paul Middlebrooks - #19 1:19:26

36 weeks ago1:19:26

1:19:26

In September Paul Middlebrooks, the producer of the podcast BrainInspired, and I were both on a neuro-AI workshop on a coast liner cruising the Norwegian fjords. We decided to make two joint podcasts with some of the participants where we discuss the role of AI in neuroscience. In this first part we talk with Mikkel Lepperod, the main organizer about the goal of the workshop, and with Ken Harris and Andreas Tolias about how AI has affected their research neuroscientists and their thoughts about the future of neuro-AI.…

Theoretical Neuroscience Podcast

1
On electric brain signals - solo episode - #18 1:48:22

39 weeks ago1:48:22

1:48:22

Most of what we have learned about the functioning of the living brain has come from extracellular electrical recordings, like the measurement of spikes, LFP, ECoG and EEG signals. And most analysis of these recordings has been statistical, looking for correlations between the recorded signals and what the animal/human is doing or being exposed to. However, starting with the neuron rather than the data, these electrical brain signals can also be computed from biophysics-based forward models, and this is topic of this podcast.…

Theoretical Neuroscience Podcast

1
On dendritic function - with Yiota Poirazi - #17 1:27:39

44 weeks ago1:27:39

1:27:39

The most prominent visual characteristic of neurons is their dendrites. Even more than 100 years after their first observation by Cajal, their function is not fully understood. Biophysical modeling based on cable theory is a key research tool for exploring putative functions, and today’s guest is one the leading researchers in this field. We talk about of passive and active dendrites, the kind of filtering of synaptic inputs they support, the key role of synapse placements, and how the inclusion of dendrites may facilitate AI.…

Theoretical Neuroscience Podcast

1
On consciousness - with Christof Koch - #16 2:04:59

46 weeks ago2:04:59

2:04:59

The greatest mystery of all is why a group of atoms, like the ones constituting me, can feel anything. The mind-brain problem has puzzled philosophers for millennia. Thanks to pioneers like Christof Koch, consciousness studies have recently become a legitimate field of scientific inquiry. In this vintage episode, recorded in February 2021, we discuss many aspects of the phenomenon, including an intriguing candidate theory: Integrated Information Theory.…

Theoretical Neuroscience Podcast

1
On the simulation tool NEURON - with Michael Hines - #15 1:26:35

48 weeks ago1:26:35

1:26:35

Computational neuroscientists use many software tools, and NEURON has become the leading tool for biophysical modeling of neurons and neural network. Today’s guest has been the leading developer of NEURON since the infancy almost 50 years ago. We talk about how the tool got started and the development up until today’s modern version of the software, including CoreNEURON optimized for parallel execution of large-scale network models on multicore supercomputers.…

Theoretical Neuroscience Podcast

1
On the molecular memory code - with Sam Gershman - #14 1:20:44

52 weeks ago1:20:44