Copertina

How much neuroscience does a neuroscientist need to know?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Whittington, James C. R., Dorrell, William
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Neurons and Cognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

If Grid Cells are the Answer, What is the Question? A Review of Normative Grid Cell Theory
di: Dorrell, William, et al.
Pubblicazione: (2026)

Convex Efficient Coding
di: Dorrell, William, et al.
Pubblicazione: (2026)

Actionable Neural Representations: Grid Cells from Minimal Constraints
di: Dorrell, William, et al.
Pubblicazione: (2022)

Reduced rank regression for neural communication: a tutorial for neuroscientists
di: Wu, Bichan, et al.
Pubblicazione: (2025)

Mapping Connectomic Structure to Function(s) in Cerebellar-like Networks using Kernel Regression
di: Dorrell, William, et al.
Pubblicazione: (2026)

Clarifying the conceptual dimensions of representation in neuroscience
di: Pohl, Stephan, et al.
Pubblicazione: (2024)

How to optimize neuroscience data utilization and experiment design for advancing brain models of visual and linguistic cognition?
di: Tuckute, Greta, et al.
Pubblicazione: (2024)

The tardigrade as an emerging model organism for systems neuroscience
di: Lyons, Ana M., et al.
Pubblicazione: (2025)

Separating minimal from radical embodied cognitive neuroscience
di: de Wit, Matthieu M.
Pubblicazione: (2024)

Rethinking scale in network neuroscience: Contributions and opportunities at the nanoscale
di: Betzel, Richard, et al.
Pubblicazione: (2025)

A perspective on neuroscience data standardization with Neurodata Without Borders
di: Pierré, Andrea, et al.
Pubblicazione: (2023)

Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation
di: Taylor, Paul A., et al.
Pubblicazione: (2025)

TRACE: Contrastive learning for multi-trial time-series data in neuroscience
di: Schmors, Lisa, et al.
Pubblicazione: (2025)

Decoding Alignment without Encoding Alignment: A critique of similarity analysis in neuroscience
di: Bertram, Johannes, et al.
Pubblicazione: (2026)

Unifying equivalences across unsupervised learning, network science, and imaging/network neuroscience
di: Rubinov, Mika
Pubblicazione: (2025)

An introduction to reinforcement learning for neuroscience
di: Jensen, Kristopher T.
Pubblicazione: (2023)

How does the inner retinal network shape the ganglion cells receptive field : a computational study
di: Kartsaki, Evgenia, et al.
Pubblicazione: (2024)

Why does time feel the way it does? Towards a principled account of temporal experience
di: Comolatti, Renzo, et al.
Pubblicazione: (2024)

Integrative neurocybernetic modeling in the era of large-scale neuroscience
di: Park, Il Memming, et al.
Pubblicazione: (2026)

Biological detail and graph structure in network neuroscience
di: Papo, David, et al.
Pubblicazione: (2025)

Dynamical properties and mechanisms of metastability: a perspective in neuroscience
di: Rossi, Kalel L., et al.
Pubblicazione: (2023)

Large language models surpass human experts in predicting neuroscience results
di: Luo, Xiaoliang, et al.
Pubblicazione: (2024)

A foundation model of vision, audition, and language for in-silico neuroscience
di: d'Ascoli, Stéphane, et al.
Pubblicazione: (2026)

The Integrated Information Theory needs Attention
di: Lopez, Azenet, et al.
Pubblicazione: (2024)

Generative causal testing to bridge data-driven models and scientific theories in language neuroscience
di: Antonello, Richard, et al.
Pubblicazione: (2024)

Efficient coding with chaotic neural networks: A journey from neuroscience to physics and back
di: Kadmon, Jonathan
Pubblicazione: (2024)

Why does tinnitus vary with naps? A polysomnographic prospective study exploring the somatosensory hypothesis
di: Guillard, Robin, et al.
Pubblicazione: (2025)

Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation
di: Azizpour, Sahel, et al.
Pubblicazione: (2024)

How 'Neural' is a Neural Foundation Model?
di: Bertram, Johannes, et al.
Pubblicazione: (2026)

Some things to know about achieving artificial general intelligence
di: Roitblat, Herbert
Pubblicazione: (2025)

How to set up a psychedelic study: Unique considerations for research involving human participants
di: Glennon, Marcus J., et al.
Pubblicazione: (2025)

From task structures to world models: What do LLMs know?
di: Yildirim, Ilker, et al.
Pubblicazione: (2023)

The mouth speaks as much as the eyes: Free-ranging dogs depend on inner facial features for human recognition
di: Sarkar, Rohan, et al.
Pubblicazione: (2024)

How Easterners and Westerners perceive ADHD differently
di: Lin, Xing-Chan
Pubblicazione: (2025)

How EEG preprocessing shapes decoding performance
di: Kessler, Roman, et al.
Pubblicazione: (2024)

How constraints on editing affects cultural evolution
di: Tchernichovski, Ofer, et al.
Pubblicazione: (2025)

From Thought to Action: How a Hierarchy of Neural Dynamics Supports Language Production
di: Zhang, Mingfang, et al.
Pubblicazione: (2025)

How memories are stored in the brain: the declarative memory model
di: Zhang, Jie
Pubblicazione: (2024)

Microbes in the Moonlight: How the Gut Microbiota Influences Sleep
di: Alegre, Enso Onill Torres
Pubblicazione: (2025)

How brains build higher order representations of uncertainty
di: Peters, Megan A. K., et al.
Pubblicazione: (2025)