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Apoorva Bhandari

@apaxon.bsky.social
54 followers 66 following 23 posts

Cognitive neuroscientist at Brown University

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Reposted by Apoorva Bhandari
Jo Etzel @joetzel.bsky.social · 05/08/2026
#introduction I'm currently a staff scientist at Washington U in St Louis (USA), but (late 2026, early 2027) looking for a new position. I'm a big fan of task #fMRI, #BIDS, #baseR #Rstats (incl. graphics) and #knitr, #QC, and papers with very extensive #supplementary materials, but not AI.
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Lucas Benjamin @lucaswbenjamin.bsky.social · 30/07/2026
This paper is now out in @pnas.org : www.pnas.org/doi/10.1073/...
pnas.org
Long-horizon associative learning as a unifying framework for statistical learning across scales | PNAS
Sensory inputs are rich with temporal patterns that unfold across multiple timescales. Uncovering these regularities is essential for anticipating ...
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Mel Andrews @bayesianboy.bsky.social · 05/06/2026
Industry is parasitic on academia for research, innovation, and training. The sweeping attacks on academia currently underway in the US are going to gut industry in the years to come. hbr.org/2026/06/the-...
hbr.org
The U.S. Research Talent Pipeline Is in Trouble
Policy shifts, funding instability, and visa uncertainty are causing a sharp decline in the willingness of young scientists trained in the United States to stay in academia—or even remain in the count...
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Tamir Eliav @tamir-eliav.bsky.social · 29/05/2026
🚨 New paper in @nature.com We asked why two hippocampal areas with very different anatomy, CA3 and CA1, often seem to code space so similarly? By recording bats flying up to 200m, we found that the difference was hidden by scale! www.nature.com/articles/s41... 🧵 1/11
nature.com
Sparse-to-dense coding transformation between hippocampal areas CA3 and CA1 - Nature
The hippocampus exhibits a CA3-to-CA1 coding transformation that combines fast learning with an efficient, compressed neural code.
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 26/05/2026
Random network structure stabilizes neural manifolds www.biorxiv.org/content/10.64898/20…
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 24/05/2026
Thalamic input drives co-timed excitation and inhibition to suppress cortical neuronal variability during movement initiation www.biorxiv.org/content/10.64898/20…
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 24/05/2026
Layer 6 corticothalamic neurons show diverse and dynamic responses that support a role in cortical gain control in noisy environments www.biorxiv.org/content/10.64898/20…
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Thomas Andrillon @thomasandrillon.bsky.social · 23/05/2026
Discover 40+ chapters on the science of consciousness: humans, babies, animals, artificial systems, etc! Experts from various disciplines and views came together under the lead of Umberto Olcese and Lucia Melloni A precious resource for anyone interested in #consciousness! www.horizon-minds.com
horizon-minds.com
Horizon Minds
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Alison Preston @aliprestonphd.bsky.social · 22/05/2026
When you're stressed, what happens to the mental links that let you connect related experiences and draw new conclusions? In our new @science.org #ScienceAdvances paper, we show that stress disrupts that linking process in the hippocampus🧵
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 18/05/2026
Task context is broadly encoded in the human brain www.biorxiv.org/content/10.64898/20…
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Randolph Helfrich @randolph-helfrich.bsky.social · 04/05/2026
Very excited to share our latest paper led by @nbinish.bsky.social in @natneuro.nature.com We demonstrate how a communication subspace channels higher-dimensional PFC dynamics into lower-D motor activity to enable efficient behavior using human iEEG. www.nature.com/articles/s41... #neuroskyence
nature.com
A communication subspace relays context-dependent actions from human prefrontal to motor cortex - Nature Neuroscience
Context-dependent behavior selects actions according to task demands. Using direct brain recordings in humans, Binish et al. uncover how coordinated population activity efficiently channels informatio...
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Kenji Lee @kenjilee.bsky.social · 27/04/2026
Super excited to (finally!) show our work on identifying cell types! Now in press www.nature.com/articles/s41.... We show how to identify cell types from ephys recordings *without* optotagging. This opens the study of not just individual cell types, but the interacting neural circuit during behavior
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Yang Teoh @yyangteoh.bsky.social · 14/04/2026
Now out in PNAS with @jaeyoungson.bsky.social, Alice Xia, @apaxon.bsky.social & @orielf.bsky.social. Medial temporal lobe encodes predictive representations of people's real-world social networks which afford them key advantages in social navigation. www.pnas.org/doi/10.1073/... 🧵
pnas.org
Medial temporal lobe encodes cognitive maps of real-world social networks | PNAS
Humans routinely solve social problems by navigating densely interconnected networks—gossiping strategically, brokering across cliques, and coordin...
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Seongmin Park @seongminpark.bsky.social · 10/07/2025
🚨 We’re hiring! The Computational Cognitive Neuroscience Lab at Virginia Tech is looking for a postdoc to join our team studying the neural + computational mechanisms of structure learning and flexible cognition: ccnvt.github.io#positions
ccnvt.github.io
CCN Lab
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hardmaru @hardmaru.bsky.social · 12/05/2025
New Paper: Continuous Thought Machines pub.sakana.ai/ctm/ Neurons in brains use timing and synchronization in the way that they compute, but this is largely ignored in modern neural nets. We believe neural timing is key for the flexibility and adaptability of biological intelligence. Thread ↓
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Lucina Uddin @lucinauddin.bsky.social · 12/05/2025
Check out our new special issue on cognitive flexibility @coolscontrol.bsky.social: authors.elsevier.com/a/1l4vl8MqMi...
authors.elsevier.com
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Datta Lab @dattalab.bsky.social · 09/05/2025
Maps are everywhere in the brain...and finally we've discovered one in the nose! Led by @davidhbrann.bsky.social, we uncovered the logic that specifies the positions of each of the 1,000 sensory neuron subtypes in the nose and aligns their projections to the brain.👇👃see more details below👃👇
biorxiv.org
A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain
Although topographical maps organize many peripheral sensory systems, it remains unclear whether olfactory sensory neurons (OSNs) choose which of the ~1100 odor receptors (ORs) to express based upon t...
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Apoorva Bhandari @apaxon.bsky.social · 28/03/2025
What a terrific idea.
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Jascha Achterberg @achterbrain.bsky.social · 23/03/2025
Looking for an exciting fellowship in AI & Neuro, with competitive salary (~£100k)? We got a new position in the lab at Oxford, working with @somnirons.bsky.social and me! 🧪 Our project: encode.pillar.vc/projects/beh... General info: encode.pillar.vc #compneuro #neuroai #neuroscience #sciencejobs
encode.pillar.vc
ARIA Opportunity Space: Scalable Neural Interfaces
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Tristan Yates @tristansyates.bsky.social · 20/03/2025
Why do we not remember being a baby? One idea is that the hippocampus, which is essential for episodic memory in adults, is too immature to form individual memories in infancy. We tested this using awake infant fMRI, new in @science.org #ScienceResearch www.science.org/doi/10.1126/...
science.org
Hippocampal encoding of memories in human infants
Humans lack memories for specific events from the first few years of life. We investigated the mechanistic basis of this infantile amnesia by scanning the brains of awake infants with functional magne...
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AntonioFR @antferrui.bsky.social · 17/03/2025
Excited to share our latest story! We found disentangled memory representations in the hippocampus that generalized across time and environments, despite the seemingly random drift and remapping of single cells. This code enabled the transfer of prior knowledge to solve new tasks
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Hayoung Song @hayoungsong.bsky.social · 13/03/2025
If you are curious about the brain🧠 on causal inference, insight💡, memory retrieval, and narrative comprehension🎬, this will be the one. work by dream team @jinke.bsky.social Rhea Madhogarhia @ycleong.bsky.social @monicarosenb.bsky.social ⭐
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Nature @nature.com · 13/03/2025
Nature research paper: Basis functions for complex social decisions in dorsomedial frontal cortex go.nature.com/3FsvUTi
go.nature.com
Basis functions for complex social decisions in dorsomedial frontal cortex - Nature
A study combining group decision-making tasks with fMRI shows that the brain’s dorsomedial prefrontal cortex uses basis functions, similar to those in the visual, motor and spatial domains, to represent patterns of social interaction.
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Riccardo Fusaroli @fusaroli.eurosky.social · 12/03/2025
How did early human symbolic behavior evolve? osf.io/preprints/ps... Can we use cultural transmission chains to explore how humans were using and producing the 40k-year of engravings from Blombos & Diepkloof? W Pagnotta Tylén @felixthehauskat.bsky.social & others. A thread:
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Nadira Faber @nadirafaber.bsky.social · 12/03/2025
Our paper in Nature (@mkwittmann.bsky.social et al.): the brain does not only process the *identity* of a person but primarily our *relationship* to them. Even on a neural level, who someone is *in relation to others* is key. www.nature.com/articles/s41... #PsychSciSky #socialpsyc #neuroskyence
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Liset M. de la Prida @lmprida.bsky.social · 26/02/2025
New from the lab!! 👉🏼 authors.elsevier.com/a/1kgT43BtfH... 📝 @cellpress.bsky.social We discovered that genetically-defined neuron types in the hippocampus form unique manifolds! Dual color imaging, chemogenetics and topological analysis all at once! With Juan Gallego @juangallego.bsky.social
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PessoaBrain @pessoabrain.bsky.social · 23/02/2025
Averaging brain responses is not a great idea... #neuroscience #neuroskyence www.nature.com/articles/s41...
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 09/02/2025
Computation-through-Dynamics Benchmark: Simulated datasets and quality metrics for dynamical models of neural activity www.biorxiv.org/content/10.1101/202…
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Dorsa Amir @dorsaamir.bsky.social · 25/01/2025
Does the culture you grow up in shape the way you see the world? In a new Psych Review paper, @chazfirestone.bsky.social & I tackle this centuries-old question using the Müller-Lyer illusion as a case study. Come think through one of history's mysteries with us🧵(1/13):
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Jae-Young Son @jaeyoungson.bsky.social · 02/08/2024
Cool new work from my labmate Alice!
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Apoorva Bhandari @apaxon.bsky.social · 03/08/2024
New paper with Alice Xia, Yang Teoh and Oriel FeldmanHall.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Please do share your feedback and thoughts, and repost!
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
This is the hardest project I've worked on: extensive methods development, painstaking piloting, writing two grants, intensive data collection, and a LOT of thinking. It needed a huge dose of patience as we carried its burden over many years. A bit like Frodo carrying the ring.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Collectively, studying representations of two different task structures in the same subjects revealed generalizable principles by which lPFC tailors representations to different tasks.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
The flat task showed local high-dim structure and orthogonality across clusters that were unrelated to the structure of the task. These may have been vestiges of an expressive, task-agnostic representation. Such a process has been observed in monkey lPFC www.biorxiv.org/content/10.1...
biorxiv.org
Learning shapes neural geometry in the prefrontal cortex
bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
However, there were clues in the data suggesting lPFC may have started with a task-agnostic, high-dim representation with learning-driven dimensionality reduction helping reshape it to fit the task structure.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Therefore, at least in highly trained subjects, lPFC learned task-tailored representations that recapitulated the structure of the task, showing that lPFC representations are shaped by representation learning.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
On the other hand, in the flat task, a global axis encoded the response-relevant, XOR categories abstractly. Category-specific local geometries were high-dimensional, retaining stimulus information that was not strictly required for readout.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
In the hierarchy task, the global axis abstractly encoded higher-level context, while low-dimensional, context-specific local geometries compressed context-irrelevant information & abstractly encoded context-relevant response-relevant category.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Using a series of decoding analyses, we comprehensively worked out the detailed local structure within each cluster in both tasks.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Nevertheless, lPFC representational geometry for each task was highly tailored to its structure. In each task, clustering created subspaces along a global axis - context subspaces in the hierarchy task, and response category subspaces in the flat task.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Across both tasks, inputs were encoded on manifolds of intermediate dimensionality, with at least some non-linear mixing of inputs. These representations did not differ in their overall separability, or degree of non-linear mixing.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
With decoding analyses, across both task structures, we found lPFC coding diverse task-relevant information. On the other hand, primary auditory cortex showed obligatory coding of only auditory information, whether or not it was task-relevant.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
As we have previously shown, lPFC representations are hard to study with fMRI, with poor pattern reliability and small effects. Haley tackled this head-on with deep sampling, heroically collecting 200+ minutes of fMRI data on each task from 20 subjects.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
One task used a categorization rule for mapping inputs to outputs. The other used a flat, XOR structure. We yoked & counterbalanced inputs and output across the two tasks, focusing the comparison on the structure of input-output mappings.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
To really tease these two accounts apart, one needs to characterize lPFC representations in 2 very different tasks in the same subject. We focused on characterizing content, separability & generalizability of lPFC representations as people did two different categorization tasks.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Another account is that lPFC flexibility is a consequence of representation learning. lPFC just learns specialized, task-tailored representations suited to each task, coding them in orthogonal subspaces.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
One account, popularized by Mattia Rigotti & Stefano Fusi, is that lPFC non-linearly mixes inputs, projecting them on a high-dim, task-agnostic manifold from which any task mapping can be read out without any representation learning.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
Dozens of studies show that lPFC neurons are highly flexible, coding whatever task is being performed. How lPFC accommodates different tasks of varying structures at the population level remains unsettled.
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Apoorva Bhandari @apaxon.bsky.social · 09/03/2024
New preprint w/ Haley Keglovits & David Badre. lPFC flexibly codes tasks of diff structure. How? We test 2 prevalant ideas 1) it uses a high dim, expressive geometry, agnostic to structure 2) it learns tailored geometries for each structure. tldr - Its 1* www.biorxiv.org/content/10.1...
biorxiv.org
Task structure tailors the geometry of neural representations in human lateral prefrontal cortex
bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution
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