Cogan Lab

Thank you to the authors at UC Berkeley Psychology and Neuroscience for your work, and we look forward to following more of it!

cc: @ucberkeleyofficial.bsky.social

❔3️⃣: In Fig. 2C, it looks like MFG has early low-frequency activity during the approach period that dissipates about 500ms before the decision to turn around. Could this be preparatory activity that reflects participants’ plans for the trial, or predictive of how many dots they decide to eat?

[cont.] I’m curious if there is a sharp rise in beta coherence between the STN and limbic regions right before the decision to turn around, and using Granger Causality, could it be shown that the STN drives activity in limbic regions during this brief window before the decision?

❔2️⃣: The study didn’t probe the role of subcortical beta during approach-avoidance conflict, perhaps due to limitations on recording sites. I wonder if STN beta activity may play a distinct role in this circuit as well, particularly as a signal to halt and turn around. [...]

[cont.] the high-frequency activity in ACC would reflect similar patterns as those in MFG? What exactly is the role of ACC during imminent threat? Might it serve a prediction role, as it does during other types of tasks?

❔1️⃣: The ACC (and MFC more broadly) is also construed as a conflict-control region. I’m surprised it didn’t play a larger role in regulating the other regions during ghost attack trials. Perhaps, if ghost attacks occurred more randomly, instead of based on distance...

🤍3️⃣: This experiment is well-suited for the recording locations that they had access to, and nicely contrasts the roles of limbic regions and MFG under anxiety and threat.

🤍2️⃣: The anatomical summaries were quite helpful for understanding the complex analyses, and highlight the various subnetworks involved in the circuit.

🤍1️⃣: I absolutely love this task! It’s obviously engaging, but it’s also well designed. In particular, the comparison between ghost strike and ghost chase trials is a brilliant manipulation that lets the authors probe dynamic threat levels.

Circuit dynamics of approach-avoidance conflict in humans Debilitating anxiety is pervasive in the modern world. Choices to approach or avoid are common in everyday life and excessive avoidance is a cardinal feature of all anxiety disorders. Here, we used in...

This week, Jim Zhang (3rd year PhD student, @dukebrain.bsky.social) presented Brooke Staveland’s paper on circuit dynamics of approach-avoidance conflict in humans. This 🧵 explores our thoughts (🤍 & ❔)

www.biorxiv.org/content/10.1...

Thank you to the authors @nyutandon.bsky.social for your work, and we look forward to following its progress!

cc: Adeen Flinker, Daniel Friedman, Orrin Devinsky, Werner Doyle, Patricia Dugan

[cont.] converge onto a common semantic retrieval network before engaging the task-invariant pre-articulatory network and producing the response?

❔3️⃣: The paper highlights distinct pathways for auditory and visual naming, but both tasks result in the same articulated output. At what point do the auditory and visual naming networks...

❔2️⃣: How do the frontal networks for semantic retrieval and articulation interact during natural conversation where speech is more continuous and less constrained than in structured naming tasks?

❔1️⃣: Since word surprisal reflects the combined influence of lexical and syntactic information during sentence processing, what specific aspects are driving responses in the left hemisphere frontal network?

🤍3️⃣: The results from the encoding models were straightforward and the figures were clear and interpretable!

🤍2️⃣: Using data-driven methods like non-negative matrix factorization allowed the authors to find distinct brain networks without forcing anatomical constraints.

🤍1️⃣: The task is carefully designed using both auditory and visual naming tasks along with matched non-semantic controls in both modalities which allowed the authors to isolate and dissociate modality-specific processing of semantic information.

Last week, Areti Majumdar (1st year PhD student) presented Leyao Yu and colleagues’ new paper on two overlapping but distinct frontal networks for word retrieval. This 🧵 explores our thoughts (🤍 & ❔)

doi.org/10.1016/j.ce...

Thank you to the authors at Meta AI and the Adolphe de Rothschild Foundation Hospital for their work, and we look forward to following its progress!
cc: Linnea Evanson, @jeanremiking.bsky.social

❔3️⃣: For wav2vec, did you look at encoding and decoding at other regions of the architecture to see if encoding improves linearly with depth in the architecture?

❔2️⃣: What about the architecture of the Llama model do you think allows it accurately encode word information in the first layer of the model?

❔1️⃣: Do you think the encoding/decoding performance gain using the Llama weights in more developed brains is mostly due to the larger lexical space (e.g. bigger vocabulary) in these patients?

🤍3️⃣: Using weights from wav2vec and Llama to perform encoding/decoding was novel and paves the way for further research comparing LLMs to human cognition.

🤍2️⃣: Their demonstration of changes in language function (viz. being more distributed with age) was phenomenal.

🤍1️⃣: They collected one of the most fascinating datasets we have ever seen. The number of patients in the dataset across all ranges of neurodevelopment is truly a feat to behold.

Last week,
@danielsexton16.bsky.social
(7th year Neurosurgery Resident at Duke University) presented Linnea Evanson and colleagues' new paper on comparing the development of language from childhood to adulthood and how it relates to LLMs. This 🧵 explores our thoughts (🤍 & ❔)

Thank you to the authors @uottawa.ca @hhu.de for your work, and we look forward to following its progress!

cc: Yasir Çatal, Kaan Keskin, Angelika Wolman, Philipp Klar, David Smith, Georg Northoff

❔3️⃣: Does the tradeoff between resting-state INT variability and rest-task modulation develop during early brain maturation? Understanding its developmental trajectory could reveal critical periods for interventions targeting temporal imbalances.

❔2️⃣: Could abnormal INT flexibility serve as a predictive biomarker for cognitive disorders marked by inhibited temporal processing and/or behavioral adaptability?