The MANDA lab

The Memory and Neurodynamics (MANDA) lab is part of the CogSci lab at the Kohli Center on Intelligent Systems at IIIT Hyderabad. PI: Vishnu Sreekumar

[Nick Steinmetz @SteinmetzNeuro]

Have you wondered whether fast spatiotemporal brain dynamics like traveling waves are local, confined to just one region, or whether they are shared across many regions simultaneously? The latest work from @ZhiwenNeuron in my lab has the answer! Thread-
https://t.co/0TR4rzM1SI

[bioRxiv Neuroscience @biorxiv_neursci]

Neuronal Avalanches in Naturalistic Speech and Music Listening https://t.co/uTmoJuNEkV #biorxiv_neursci

[CLaE @leafs_s]

Markov Spatial Flows in BOLD fMRI: a Novel Lens on the BOLD Signal Reveals Attracting Patterns of Signal Intensity https://t.co/Jta9qg4Jf3

[DeepLabCut 🦄 @DeepLabCut]

🐁💜#deeplabcut+🦓🖤#cebra = 🔥

@mwmathislab show you can use @CEBRAai with only neural data, only behavior data (#CEBRA supports loading your @DeepLabCut data 👀), and powerfully combine data for rich metrics & insights into neural population dynamics

https://t.co/sbkVpPeDDO

[David Quiroga🧠👂🎵 🇨🇴 @dquiroga.bsky.social @dariquima]

Happy to announce I just got a @Carlsbergfondet
fellowship to study musical imagination with single neuron recordings in humans at @UCPH_Research @Rigshospitalet in Copenhagen.

Exciting times!

See project here:
https://t.co/6IufwPE9lZ

[Elizabeth Siefert @lizsiefert]

New preprint! We use real-time Targeted Memory Reactivation to show that sleep reactivation transforms object memories, enhancing certain features at the expense of others. W/ Sindhuja Uppuluri, Jianing Mu, @MarlieTandoc, @JamesWardAntony, @AnnaSchapiro
https://t.co/0y7liOVzPb

[The Brains Blog (fediscience.org/@Brains) @philofbrains]

What makes #neuroscience models explanatory?

Today we premiered Dr. Mazviita Chirimuuta’s four mini-lectures about explanations, mechanisms, models, and simplifications.

This is a fantastic closer to our 26-video Beginner’s Guide To @NeuralMech-anisms: https://t.co/HkuYhZKbIS

[Matthew Larkum @mattlark]

Congratulations to Tim Zolnik who made a superhuman effort for this paper (https://t.co/u8mEXaxGOP)! Thanks to the rest of the team including @BrittaEickholt and our Visiting Einstein Fellow @ZoltanMolnar64.

[MaxPlanck-Psycholinguistics @MPI_NL]

Interdependence of “what” and “when” in the brain. New paper by @TenOever_Sanne & @andrea_e_martin
https://t.co/y6Aw1zh9ny
paper: https://t.co/ct2wPNUHMN

[Richard McElreath 🐈‍⬛ @rlmcelreath]

I've frozen registration for Statistical Rethinking 2024. There are 342 ppl on the wait list. As attendance falls, I will invite from the list. But all of the lectures and homework and my boundless love for data rebellion remain open to all. BE EMBRACED: https://t.co/w014wsghxd

[CLaE @leafs_s]

Nature Communications

CA3 hippocampal synaptic plasticity supports ripple physiology during memory consolidation
https://t.co/6aiRxekYXE

[CLaE @leafs_s]

Nature Aging

The Information Theory of Aging
https://t.co/boC1SiZ6x0

[Earl K. Miller @MillerLabMIT]

Theta-alpha connectivity in the hippocampal-entorhinal circuit predicts working memory load
https://t.co/wVRz3TjMsJ
#neuroscience

[Alexander Huth @alex_ander]

At NeurIPS this week, @RichardAntone13 is presenting his work on scaling fMRI encoding models. We've also shared code, extracted features, and estimated model weights for some of our best models: https://t.co/wpBUSWupIF

Tweeprint: https://t.co/5Jf8gRZIgd

[Sam Nastase @samnastase]

Our experiments in using real-time fMRI neurofeedback to alter the interpretation of an ambiguous, naturalistic narrative—a colossal amount of work by @acmennen with @ptoncompmemlab—now published in NeuroImage: Reports https://t.co/VQlucCKlgP

[David Liu @davidliuneuro]

Standard neural coding approaches (think GLM) model how firing rates depend on stimuli. But how do we capture the widely observed phenomenon that the variability of spike trains is also stimulus-dependent? Our new #NeurIPS2023 paper has the solution: https://t.co/wVxRzWf5e1
1/10

[Imaging Neuroscience @ImagingNeurosci]

New paper in Imaging Neuroscience @mitpress by Janine D. Bijsterbosch, Stephen M. Smith, et al:

Evaluating functional brain organization in individuals and identifying contributions to network overlap

https://t.co/VeOkbYX2bZ

[Michael W. Cole @TheColeLab]

Lab's latest: "Neural representation dynamics reveal computational principles of cognitive task learning", wherein we tracked dynamic changes in cortical-subcortical cognitive representations over practice, revealing computational principles underlying task learning: 1/n

[CLaE @leafs_s]

Nature Communications

Mental search of concepts is supported by egocentric vector representations and restructured grid maps
https://t.co/uJTUGTTAzu

[postlelab @postlelab]

Just submitted by psychophysics/neuroscience powerhouse @ChunyueTeng : model-based analysis of a WM+visual-discrimination dual task, applying RL model of cognitive control from
@jfjiang. Don't be that person who hasn't yet read it https://t.co/zcN6vbs1m3