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https://github.com/patrickmineault/big-neuro-ideas

An ongoing journal club for the study of big ideas in neuro
https://github.com/patrickmineault/big-neuro-ideas

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An ongoing journal club for the study of big ideas in neuro

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# Big neuro ideas

An ongoing journal club for the study of big ideas in neuroscience.

# What are we reading right now?

We're reading [Gibson, an ecological approach to perception (1968)](https://archive.org/details/pdfy-u5hmFOvOM2Civ4Gz/mode/2up). Notes so far:

* [Week 1: Chapters 1, 2, 3](gibson/notes.md)
* [Week 2: Chapters 3, 4](gibson/notes.md#chapters-3-and-4)
* [Week 3: Chapter 5](gibson/notes.md#chapter-5)
* [Week 4: Chapter 6](gibson/notes.md#chapter-6)
* [Week 5: Chapter 7](gibson/notes.md#chapter-7)

## What's a *big idea*?

An idea that tries to unify a bunch of disparate observations about the brain, with a theoretical slant. Preferably with an explanatory bent rather than phenomenological, with an emphasis on theory. We prefer books and articles that have withstood the test of time (i.e. 10 years or older). Sometimes a big idea can just be about asking the right question, not solving it.

## On the docket

* [Rao and Ballard (1999), Predictive coding in the visual cortex](https://www.ncbi.nlm.nih.gov/pubmed/10195184)
* [McIntosh and Schenk (2009), two visual streams for perception and action](https://www.ncbi.nlm.nih.gov/pubmed/19428404)
* [23 problems in systems neuroscience (2005)](https://www.amazon.com/23-Problems-Systems-Neuroscience-Computational/dp/0195148223/ref=sr_1_1?crid=3D60KCO1WQWXV)
* [Phylogenetic refinement (2019)](https://link.springer.com/article/10.3758/s13414-019-01760-1)

## Inspiration

From [Josh Vogelstein](https://twitter.com/neuro_data/status/1208251627884498944):

1. bayes brain (rao)
2. harmonic mind (smolensky)
3. rhythyms of the brain (buzsaki)
4. free energy principle (friston)
5. memory-prediction framework (hawkins)
6. sparse distributed memory (kanerva)
7. vehicles (braitenberg)
8. phylogenic refinement (cisek)
9. Efficient coding (many)
10. Manifolds, attractor networks (many)

## Courses, teaching materials

* [How to build a brain](https://humaninformationprocessing.com/teaching/)
* [Brain inspired podcast](https://braininspired.co/)
* [Open courses and textbooks list](https://github.com/asoplata/open-computational-neuroscience-resources)

## Meta: creating an online-first journal club

* https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4597966/