Tutorial: Recurrent neural networks for cognitive neuroscience @MITCBMM

Uploaded August 2021 | Updated September 2026, 1 week ago

Robert Guangyu Yang, MIT

In this hands-on tutorial, we will work together through a number of coding exercises to see how RNNs can be easily used to study cognitive neuroscience questions. We will train and analyze RNNs on various cognitive neuroscience tasks. Familiarity of Python and basic knowledge of Pytorch are assumed.

There will be a 30 minute lecture followed by a workshop utilizing Google's Collab Notebooks. Attendees are free to attend any length of the tutorial. Materials and code to complete the workshop will be made available the day of the event.

Speaker Bio:
Robert (Guangyu) Yang is an Assistant Professor in the MIT Department of Brain and Cognitive Sciences (BCS), with a joint appointment in the EECS Department in the Schwarzman College of Computing (SCC). He received his B.S. in physics from Peking University and his Ph.D. in neuroscience from New York University working with computational neuroscientist Dr. Xiao-Jing Wang. During his Ph.D., he studied how distinct types of inhibitory neurons in the brain can coordinate the information flow across brain areas. In another line of work, he studied how the same artificial neural network can accomplish many cognitive tasks. He was a postdoctoral research scientist in the Center for Theoretical Neuroscience at Columbia University’s Zuckerman Institute. Currently, he studies how artificial neural networks can become more powerful by incorporating neural architectures discovered in the brain.

Collab notebooks:

Exercises with explanations but no answers
colab.research.google.com/github/gyyang/nn-brain/blob/master/RNN_tutorial.ipynb

Exercises with explanations and answers
colab.research.google.com/drive/1UL8DkhThsepHxPTVIPg8DpzVgCge6_7q

Tutorial: Recurrent neural networks for cognitive neuroscience

$How many neurons are there in human brain? #MITTeachMeSomethingTuesday Pramod RT, Postdoctoral Associate, MIT Dept. of Brain and Cognitive Sciences Want to learn more? Check out this article and paper: • Are There Really as Many Neurons in the Human Brain as Stars in the Milky Way? https://www.nature.com/scitable/blog/brain-metrics/are_there_really_as_many/ ⁃ This is a phrase a lot of science communicators like to use because giving people a sense of scale when it comes to large numbers is so difficult. Thats why journalists report distances as number of football fields, mass as number of fully-loaded 747s, energy in terms of Hiroshima bombs, etc.Even though we cant conceive of the number of stars in the Milky Way or the number of neurons in the human brain, equating the two gives people a sense of enormity. And as conscious beings we like to find patterns, and we find equivalencies interesting, especially when the things being equated are important or epic (like neurons and stars). For a long time, neuroscientists would say that there are about 100 billion neurons in the human brain. Interestingly, no one has ever published a peer-reviewed scientific paper supporting that count. Rather its been informally interpolated from other measurements. A recent study from 2009 published by Azevedo and colleagues took a crack at a more precise estimate. Their answer?… • Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, Ferretti RE, Leite RE, Jacob Filho W, Lent R, Herculano-Houzel S. “Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain.” J Comp Neurol. 2009 Apr 10;513(5):532-41. doi: 10.1002/cne.21974. PMID: 19226510. https://pubmed.ncbi.nlm.nih.gov/19226510/ ⁃ Abstract: The human brain is often considered to be the most cognitively capable among mammalian brains and to be much larger than expected for a mammal of our body size. Although the number of neurons is generally assumed to be a determinant of computational power, and despite the widespread quotes that the human brain contains 100 billion neurons and ten times more glial cells, the absolute number of neurons and glial cells in the human brain remains unknown. Here we determine these numbers by using the isotropic fractionator and compare them with the expected values for a human-sized primate. We find that the adult male human brain contains on average 86.1 +/- 8.1 billion NeuN-positive cells (neurons) and 84.6 +/- 9.8 billion NeuN-negative (nonneuronal) cells. With only 19% of all neurons located in the cerebral cortex, greater cortical size (representing 82% of total brain mass) in humans compared with other primates does not reflect an increased relative number of cortical neurons. The ratios between glial cells and neurons in the human brain structures are similar to those found in other primates, and their numbers of cells match those expected for a primate of human proportions. These findings challenge the common view that humans stand out from other primates in their brain composition and indicate that, with regard to numbers of neuronal and nonneuronal cells, the human brain is an isometrically scaled-up primate brain. #MIT #TeachMeSomething #TeachMeSomethingTuesday #MITDepartmentofBrainandCognitiveSciences #MITBCS #teachmesomething #teachmesomethingtuesday #brain #neurons$

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