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Posts by Norman Lab

Careers | Human Resources

We are hiring a research specialist, to start this summer! This position would be a great fit for individuals looking to get more experience in computational and cognitive neuroscience research before applying to graduate school. #neurojobs Apply here: research-princeton.icims.com/jobs/21503/r...

2 months ago 38 30 0 3

What if we could tell you how well you’ll remember your next visit to your local coffee shop? ☕️

In our new Nature Human Behaviour paper, we show that the 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗮 𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 can be measured with neuroimaging – and 𝘁𝗵𝗮𝘁 𝘀𝗰𝗼𝗿𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝘀 𝗵𝗼𝘄 𝘄𝗲𝗹𝗹 𝗻𝗲𝘄 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀 𝘄𝗶𝗹𝗹 𝘀𝘁𝗶𝗰𝗸.

3 months ago 72 26 3 2

Come work with us! @princetonneuro.bsky.social and the Department of Psychology at Princeton University are searching for a tenure-track Assistant Professor in the area of human cognitive neuroscience, to be hired jointly in Psychology and Neuroscience: puwebp.princeton.edu/AcadHire/app...

8 months ago 70 64 2 0

New paper led by @codydong.bsky.social now out in @cp-trendscognsci.bsky.social, exploring the relationship between memory-augmented LLMs and human episodic memory – see Cody’s post below for a short thread and a non-paywalled paper link! #NeuroAI doi.org/10.1016/j.ti...

8 months ago 21 9 1 0

New paper led by @jayneuro.bsky.social: Repetition of musical themes in Eternal Sunshine of the Spotless Mind reactivates memories of earlier scenes, and this neural reactivation correlates with subsequent memory for those scenes! Check out Jamal's thread below 👇

9 months ago 4 1 0 0

Thrilled that this collaborative project with the @maureenritchey.bsky.social lab, co-led by @gushennings.bsky.social and Paula Brooks, is out in preprint form!

11 months ago 5 1 0 0

@qlu.bsky.social is starting his lab at City U of Hong Kong! This is a truly amazing opportunity for trainees interested in computational cognitive neuroscience and neuroAI

11 months ago 17 2 1 0

Thank you to Ingrid Wickelgren and the team at Quanta for putting together this great piece, describing work by my lab and others on the neural representations of events

1 year ago 32 10 0 0
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Neural codes track prior events in a narrative and predict subsequent memory for details Communications Psychology - Context-dependent temporal structures are represented in multiple ways in parallel in the human brain during processing of temporally extended events. The neural...

Our paper on how neural codes track prior events in a narrative and predict subsequent memory for details, led by @collinsilvy.bsky.social, is now out in Communications Psychology! rdcu.be/d93Vc #neuroskyence #psychscisky

1 year ago 57 19 0 1
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Fast-timescale hippocampal processes bridge between slowly unfurling neocortical states during memory search Prior behavioral work showed that event structure plays a key role in our ability to mentally search through memories of continuous naturalistic experience. We hypothesized that, neurally, this memory...

Excited to share our preprint "Fast-timescale hippocampal processes bridge between slowly unfurling neocortical states during memory search" 🧠✨ We leverage iEEG to elucidate the fast neural mechanisms by which long multimodal narratives are unfurled in continuous memory-search tinyurl.com/wjkr3dvf

1 year ago 70 29 1 1

Training in the Method of Loci promotes the development of widespread conjunctive representations in neocortex that bind items and loci -- very excited to be part of this project led by @huangjiawen.bsky.social and @chrisbaldassano.bsky.social

1 year ago 10 0 0 0
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Large language models can segment narrative events similarly to humans - Behavior Research Methods Humans perceive discrete events such as “restaurant visits” and “train rides” in their continuous experience. One important prerequisite for studying human event perception is the ability of researche...

So happy that our paper on event segmentation in large language models is now out in Behavior Research Methods! tinyurl.com/2j76882b With @mtoneva.bsky.social, @ptoncompmemlab.bsky.social, and Manoj Kumar, we show that LLMs can segment narrative text into meaningful events similarly to humans.

1 year ago 71 19 3 1

Thrilled that this epic study led by @coralineiordan.bsky.social is now out in PNAS!

1 year ago 26 3 0 0
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🔔𝐍𝐄𝐖 𝐏𝐑𝐄𝐏𝐑𝐈𝐍𝐓 𝐀𝐋𝐄𝐑𝐓🔔 Beyond excited to present our new work showcasing 𝐡𝐨𝐰 𝐰𝐞 𝐜𝐚𝐧 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐡𝐨𝐰 𝐰𝐞𝐥𝐥 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐫𝐞𝐢𝐧𝐬𝐭𝐚𝐭𝐞 𝐚 𝐧𝐞𝐰 𝐦𝐞𝐦𝐨𝐫𝐲 𝐛𝐞𝐟𝐨𝐫𝐞 𝐭𝐡𝐚𝐭 𝐦𝐞𝐦𝐨𝐫𝐲 𝐢𝐬 𝐟𝐨𝐫𝐦𝐞𝐝! Wait what? Exciting collab w/ @ptoncompmemlab.bsky.social & @chrisbaldassano.bsky.social Link: www.biorxiv.org/content/10.1... (1/11)

1 year ago 33 11 1 1

#neuroskyence #psychscisky

1 year ago 1 0 0 0

When memories are identified as targets for representational change, some of the plasticity required to implement those changes may occur later, during offline REM sleep. (9/9)

1 year ago 3 0 1 0
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Our findings support the hypothesis that REM sleep drives representational change in the hippocampus, showing one way that REM sleep may support memory consolidation… (8/9)

1 year ago 1 0 1 0

We also hypothesized that neural differentiation would be correlated with the amount the predicted item came to mind during prediction errors, more so in the REM group than the Wake and non-REM sleep-only groups. This pattern was reliable (at an uncorrected threshold) in bilateral DG. (7/9)

1 year ago 1 0 1 0

We found more differentiation in the group with REM sleep than the Wake and non-REM sleep-only groups in the right CA2/3/DG (significant at an uncorrected threshold). An exploratory analysis found that the effect was concentrated in the right DG. (6/9)

1 year ago 1 0 1 0

Using the same task as Kim et al. (2017), we measured how the representations of A and B changed across a period of consolidation with fMRI. We manipulated the presence or absence of REM sleep in a daytime nap during that consolidation period (we also included a quiet wake control group). (5/9)

1 year ago 1 0 1 0

Kim et al. found that, when an item predicted in a particular context (e.g., A predicts B) failed to appear and was later restudied in a different context, the representations of A and B became less similar in the CA2/3/DG region of the hippocampus (Kim et al., 2017). (4/9)

1 year ago 1 0 1 0

Here, we sought to test the preregistered hypothesis that learning during REM sleep helps differentiate the neural representations of related memories, by expanding on a prior fMRI study by Kim et al. (2017) showing that prediction errors lead to neural differentiation in the hippocampus… (3/9)

1 year ago 1 0 1 0

Myriad studies have contributed to our understanding of non-REM sleep and its role in memory consolidation, but the role of REM sleep largely remains a puzzle. (2/9)

1 year ago 1 0 1 0

Excited to share a new preprint with Elizabeth McDevitt, Ghootae Kim, and Nick Turk-Browne investigating the role of REM sleep in neural differentiation of memories in the hippocampus! URL: www.biorxiv.org/content/10.1101/2024.11.... (1/9)

1 year ago 36 17 3 0
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Inducing representational change in the hippocampus through real-time neurofeedback | Philosophical Transactions of the Royal Society B: Biological Sciences When you perceive or remember something, other related things come to mind, affecting how these competing items are subsequently perceived and remembered. Such behavioural consequences are believed to...

New paper led by Kailong Peng: Real-time fMRI neurofeedback that promotes coactivation of cortical representations drives integration in the hippocampus #neuroskyence #psychscisky royalsocietypublishing.org/doi/10.1098/...

1 year ago 41 15 2 0

The paper also features explainer videos! For example, this video explains why associating two scenes to the same face in Favila et al. (2016) leads to differentiation: https://www.youtube.com/watch?v=dRIW6zVp4qw
(5/5)

1 year ago 1 0 0 0
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The model predicts that, when differentiation occurs as a result of this unsupervised learning mechanism, it will be rapid and asymmetric, and it will give rise to anticorrelated representations in the region of the brain that is the source of the differentiation. (4/5)

1 year ago 2 0 1 0

We provide an unsupervised NN model that can explain these and other related findings by implementing the Nonmonotonic Plasticity Hypothesis (NMPH), whereby moderate coactivity weakens weights, leading to differentiation, and strong coactivity strengthens weights, leading to integration (3/5)

1 year ago 2 0 1 0

Classic supervised learning models posit that, when two stimuli predict similar outcomes, their representations integrate. However, these models have recently been challenged by studies showing that pairing stimuli with a shared associate can sometimes cause differentiation. (2/5)

1 year ago 1 0 1 0

Our neural network model of differentiation and integration of competing memories, developed by Victoria Ritvo and Alex Nguyen, has now been published in @elife.bsky.social:
Paper: https://tinyurl.com/4b3k95rd
Code: https://tinyurl.com/mr25rk9e
#neuroskyence #psychscisky #neuroai (1/5)

1 year ago 21 10 1 0