I am hiring a post doc at UAlberta, affiliated with Amii! We study language processing in the brain using LLMs and neuroimaging. Looking for someone with experience with ideally both neuroimaging and LLMs, or a willingness to learn. Email me with Qs
apps.ualberta.ca/careers/post...

Alona Fyshe @alonaf.bsky.social on the BabyLM Challenge, a competition that trains language models (LMs) on smaller datasets, more akin to how a baby learns, in search of solutions to some of the major challenges of today’s LLMs.

#NeuroAI #neuroskyence

www.thetransmitter.org/neuroai/the-...

Did you know the famous man -> woman king -> queen analogy geometry in Mikolov et al (2013) was actually described in a 1973 paper by Rumelhart and Abrahamson? Thanks to the @jurafsky.bsky.social and Martin book for the reference!

Every year at the end of the semester, I ask the students in my Psych of Language class to create memes about what they've learned. They then vote for their favorites.
Here's the winner about how the idea of a universal grammar is no longer as compelling as it once seemed.
1/5

That is pretty crazy - thanks for flagging it for me.

Oh my goodness I forgot to link to the actual paper! Here it is!

openreview.net/forum?id=L07...

We loved looking through these results so much that we made a viewer to share all of them with the community: fyshelab.github.io/brain-viewer/

Have a look!

Another cluster emphasized hands instead of legs. Positive images show people with their hands clearly visible, while the negative images are exclusively non-primate animals without hands. Thus, the brain's “body” area may be made up of multiple more refined concepts (i.e. legs and hands).

Our method also identified several body-related clusters (EBA in the figure). The positive representative images for one cluster showed people and animals outside with an emphasis on legs and active movement. The negative images typically depict people sitting with their legs obscured by tables.

However, we also observed many vibrant and colorful positive images that contained no food. Strikingly, the negative representative images are entirely gray-scale! This provided very strong evidence that this brain area may be responding to color, not food.

Our method identified a large possibly food-related cluster with many positive food-related images, and the area aligned with a recently previously food area (i.e. the colored brain areas in the figure overlap with the reported food area).

The positive and negative images provide additional evidence for the possible function of brain areas, helping us to refine hypotheses about the associated brain areas.

These clusters allowed us to identify stimulus images that most drive neural activity in the voxels of a cluster (positive images), but also the images which are most associated with below-average voxel response (negative images).

This clustering is done via our new variant of the DBSCAN algorithm, with adaptations to consider only clusters that contain voxels from more than 2 participants.

We first trained a model to map fMRI to CLIP representations. We then clustered the *parameters* of that model to identify voxels that are driven by certain CLIP concepts. Because we cluster in model parameter space, we can look for concept representations across participants.

Still, only a few broad semantic categories have been identified, and they typically cover large areas of the brain. So… there may be other semantic categories localized in the brain (or a way to refine existing categories)!

There have been multiple attempts to identify new functionally localized regions of the brain with some converging evidence; for example, a possible “food area” was recently reported.

Neuroimaging has revealed a lot about how the brain processes and organizes visual information. For example, there is evidence that certain areas of the brain activate in response to images depicting specific semantic concepts like faces, places, bodies, and words.

Our ICLR poster is Saturday Morning (Hall 3 + Hall 2B #63)! We (myself with Cory Efird, Alex Murphy and Joel Zylberberg) are excited to share our work searching for Shared Decodable Concepts in the human brain. We used the Natural Scenes Dataset to find the concepts that most drive brain activity…

Wonderful to see this recognition of Rich's contribution to AI and computing! Rich maintains the strong founding connections between cognition and AI, showing that studying intelligence can help us build intelligence.
www.amii.ca/updates-insi...

Nice! Thanks for sharing! Do the colors of post it notes mean anything?

Friday 12th January is the deadline to apply for our Assistant Professor in AI + Biological Cognition. Details below:

careers.ualberta.ca/Competition/...

We are hiring at UAlberta: Assistant professor in AI + Biological Cognition.  We are looking for a candidate who can play equally well in the AI and Neurosci fields, and contribute to our knowledge of how AI and neuroscience relate! www.careers.ualberta.ca/Competition/...
Happy to field Qs by email

I took a comp. ling. class in grad school and the (Polish) prof said two words in Polish that were indistinguishable to me but he swore they had phonemes that he could differentiate but I couldn't. Then he told us we learn to speak without really being taught how to use our mouths to make phonemes