2.3k citations
- University of California San DiegoUS25 papers
- Center for Theoretical Biological PhysicsUS6 papers
- Tel Aviv UniversityIL6 papers
- Stanford UniversityUS5 papers
- Harvard UniversityUS4 papers
- Institut national de recherche en sciences et technologies du numériqueFR4 papers
- Northeastern UniversityUS4 papers
- Baylor College of MedicineUS3 papers
- Columbia UniversityUS3 papers
- Georgia Institute of TechnologyUS3 papers
- Imperial College LondonGB3 papers
- Lawrence Berkeley National LaboratoryUS3 papers
57 papers
MIMIC-MJX: Neuromechanical Emulation of Animal Behavior
Charles Y. Zhang, Yuanjia Yang, Aidan Sirbu +25
The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavior, kinematic trajectories alone provi…
Fast Wide-field Light Sheet Electro-optic FLIM
V. Rose Knight, Nils Bode, Dara P. Dowlatshahi +5
We demonstrate volumetric fluorescence lifetime microscopy (FLIM) using the electro-optic FLIM technique. Images acquired in a selective plane illumination microscope are gated usi…
Community recommendations on cryoEM data archiving and validation
Gerard J. Kleywegt, Paul D. Adams, Sarah J. Butcher +44
In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle anal…
The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions
Gal Haspel, Ben Baker, Isabel Beets +34
Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand…
Optimizing Attention and Cognitive Control Costs Using Temporally-Layered Architectures
Devdhar Patel, Terrence Sejnowski, Hava Siegelmann
The current reinforcement learning framework focuses exclusively on performance, often at the expense of efficiency. In contrast, biological control achieves remarkable performance…
Large Language Models and the Reverse Turing Test
Terrence Sejnowski
Large Language Models (LLMs) have been transformative. They are pre-trained foundational models that are self-supervised and can be adapted with fine tuning to a wide range of natu…