Will Decker

PhD student @GeorgiaTech 🐝 and LIT Lab. Interested in how brains and machines learn + know about the world and use langauage.

[Doris Tsao @doristsao]

We show face patches implement the following code through recurrent dynamics:

Detect face
If (face found)
Discriminate face
else
Continue to detect face

IMHO, our paper conclusively resolves a debate that has raged since I was a graduate student, about whether face patches are specialized for processing faces or not. It turns out domain-general folks were right early on, domain-specific folks were right later in the response.

So proud of @Yuelin_Shi and the entire team!

[Ruimin Gao @Ruimin_G]

We’re hiring a new Lab Manager!

I’ve loved working in this lab — super supportive environment and meaningful work in AI + cognitive neuroscience

Highly recommend for anyone looking to gain research experience before grad school!

[Will Decker @jwilldecker]

Come work in LIT Lab!

[Anna Ivanova @neuranna]

Language, Intelligence & Thought lab is looking for a lab manager! This is a 2-year postbac position that will allow you to gain experience in human neuroscience, cognitive science, and AI research prior to applying to PhD programs.

Express interest here: https://t.co/HMUll9bH6q

[Anna Ivanova @neuranna]

Language, Intelligence & Thought lab is looking for a lab manager! This is a 2-year postbac position that will allow you to gain experience in human neuroscience, cognitive science, and AI research prior to applying to PhD programs.

Express interest here: https://t.co/HMUll9bH6q

[Taha Binhuraib 🦉 @NeuroTaha]

🚨 Paper alert:
To appear in the DBM Neurips Workshop

LITcoder: A General-Purpose Library for Building and Comparing Encoding Models

📄 arxiv: https://t.co/jXoYcIkpsC
🔗 project: https://t.co/UHtzfGGriY

[Will Decker @jwilldecker]

@josephfsexton https://t.co/0eeHxDB2Ls

[Will Decker @jwilldecker]

@josephfsexton Best PCA explanation: https://t.co/JRiNJ54b9P

[Will Decker @jwilldecker]

@josephfsexton 3b1b?

[Ida Momennejad @criticalneuro]

Honored that a piece I wrote made it to NYTimes. It's about how my mom's stroke changed my relationship to time, science, and nature. What a privilege to honor my mom in Modern Love.
Below is a gift link. Let me know your thoughts🙏🏼

https://t.co/DRdLEMiHzD

[Seungwook Han @seungwookh]

🧩 Why do task vectors exist in pretrained LLMs?

Our new research uncovers how transformers form internal abstractions and the mechanisms behind in-context learning(ICL).

[Apurva Ratan Murty @apurvaratan]

🚀At @NeurIPSConf tomorrow? Don't miss @nikolasmcneal and @MainakDeb19 's poster at the @unireps workshop on the adversarial sensitivity of vision encoding models of fMRI responses! A brief teaser about what they find.

[Thackery Brown @[email protected] @ThackeryBrown]

Graduate training opportunity! See thread...

The Center for Research and Education in Navigation (CRaNE) is seeking a graduate student in our Cognition & Brain Sciences (CBS) Ph.D. Program in the School of Psychology at Georgia Institute of Technology.

[Will Decker @jwilldecker]

@aniladmello @arglotfelty Congrats @arglotfelty!

[Will Decker @jwilldecker]

@josephfsexton Yeah really frustrating that institutions send it encrypted and that some applications don’t do a safety check 😑

[Will Decker @jwilldecker]

Working on a figure and google searched "MLP images" for some inspo...

[Aran Nayebi @aran_nayebi]

1/6 I usually don’t comment on these things, but @RylanSchaeffer et al.'s paper contains enough misconceptions that I thought it might be useful to address them. In short, effective dimensionality is not the whole story for model-brain linear regression, for several reasons: 🧵👇

(1) The spectral theory due to @canatar_a @jenellefeather @s_y_chung is misrepresented in this paper, and crucially relies on model alignment with brain data (this is already evident from their equations). In fact, they conclude that effective dimensionality alone doesn’t fully predict neural data.

(2) Even in this paper’s own Figure 2 (top left panel), networks with low participation ratios, like SRNN, still achieve high neural predictivity, already indicating that participation ratio is not a unilateral predictor of whether a model will match the brain via linear regression.

(3) Beyond MEC, this lack of a trend with effective dim. is also the case when looking at models in their match to macaque IT or human OTC. For example, Colin Conwell @_jacobprince_ @talia_konkle et al.’s very thorough work: https://t.co/iWSiHOrUcd shows that effective dim isn’t related to linear prediction of human OTC (cf. their Figure 5). Moreover, in macaque IT, as @apurvaratan & others have seen, if you include very predictive models of IT responses, the effective dim to linear predictivity trend also doesn’t hold. (@jenellefeather & others don’t see this trend holding up in matches to auditory cortex either.)

(4) Furthermore, the models they cite participation ratios for, were also compared against several non-fitted metrics (like RSA, score distributions, simpler-than-linear mappings, etc.), which found similar conclusions that matched linear regression results, across MEC, IT, and auditory cortex.

[Sasha Rush @srush_nlp]

Ev Fedorenko's Keynote at COLM.
https://t.co/z3pkjM9Imc

This talk is quite accessible for computer scientists interested in cognitive and neuro questions. Also touches on many of the shared themes of the two areas.

[Will Decker @jwilldecker]

Just now finding out voxel is a portmanteau from volumetric pixel...what else have I missed?!

[Ali Cohen @aliocohen]

*TWO* job searches @EmoryPsychology ‼️

Open rank Neural Mechanisms of Behavior in Small Animal Systems
https://t.co/gRll5RgWA0

Assoc/Asst Professor, Clinical Science
https://t.co/sxaUhJaBpP

And I’m recruiting a PhD student! Several opportunities to join our amazing dept ✨