Thread by @behrenstimb

Twitter-sized history of neuroscience (biased by my interests).

1760: Bayes: You should interpret what you see in the light of what you know.
1780: Galvani: Nerves have something to do with Electricity.
1850: Phineas Gauge et al: Different parts of the brain do different things.

1850: Bois-Reymond/von Helmholtz: Cells fire electrical impulses down axons.
1880: Golgi: There are beautiful things in the brain but they are all meshed together in a gloop.
1890: Ramon y Cajal: The beautiful things are all separate things called neurons.

1900: Sherington: They connect to each other with synapses.
1900: Pavlov: Brains can learn predictions.
1910: Thorndike: Predictions of reward control behaviour.
1920: Helmholtz: The Brain is a Bayesian inference machine.
1930: Lowei/Dale: Synapses are chemical.

1940: Skinner: All behaviour can be accounted for by reward prediction.
1940: Tolman: No it can’t. You need a “map”.
1940: McCulloch & Pitt: Networks of neurons can perform computations

1950: Hodgkin and Huxley: Those nerve impulses are caused by a dance of ionic currents. There are probably some ion channels.
1950: Hebb: Synapses can store memories.

1950: Lashley: Memories are represented across the whole brain equally.
1950: Penfield: Different parts of the sensorimotor cortex do different things.
1960: Milner: There are at least two forms of memory and hippocampus is only important for one of them.

1960: Sperry: Woah spooky!! The two hemispheres are actually different people.
1960: Hubel and Wiesel: Individual neurons represent real-world things in their activity.
1960: Barlow: Neurons transmit information and should do so efficiently.

1970: Marr: Cerebellar, Hippocampal and Neocortical circuits instantiate different computations.
1970-1980 Several, including Neher and Sakman: Yes there are ion channels.
1980: O’Keefe and Nadel. Hippocampal neurons form a map of space.

1980: Hinton/Senjowski/McLelland/Rumelhart:Neural networks can optimise some cool shit.
1990: Van Essen:Blimey the visual system looks complicated.
2000: Rao/Ballard/Olshausen/Fields:Those real world things that neurons represented are actually features of statistical learning

2000: Schultz, Dayan, Montague: Dopamine neurons allow reward predictions to be learnt.
2000: Kanwisher: Different parts of the higher visual cortex do different things.
2000: Haxby: No they don’t. It’s all distributed (are we still having this same argument?)

2010: Mosers: Entorhinal cells form a better map of space.
2000-2010: Deisseroth, Meisenbock, Boyden et al: Fuck me light.
2015: Hinton/LeCunn/Silver/Hassabis and many others: Neural Networks can optimise some REALLY cool shit.

2015-2020: This neural network looks just like my neurons.
2020: Jesus that’s a lot of neurons.

A couple I have since thought of:
1910: Brodmann. Cells look different in different bits of the brain.
2010: Ramirez & Tonegawa: Hebb's cell assemblies exist (Engrams)