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pro vyhledávání: '"Sejnowski Terrence"'
There is now substantial evidence for traveling waves and other structured spatiotemporal recurrent neural dynamics in cortical structures; but these observations have typically been difficult to reconcile with notions of topographically organized se
Externí odkaz:
http://arxiv.org/abs/2409.13669
Traveling waves are a fundamental phenomenon in the brain, playing a crucial role in short-term information storage. In this study, we leverage the concept of traveling wave dynamics within a neural lattice to formulate a theoretical model of neural
Externí odkaz:
http://arxiv.org/abs/2402.10163
The capabilities of transformer networks such as ChatGPT and other Large Language Models (LLMs) have captured the world's attention. The crucial computational mechanism underlying their performance relies on transforming a complete input sequence - f
Externí odkaz:
http://arxiv.org/abs/2401.14267
Traveling waves of neural activity have been observed throughout the brain at a diversity of regions and scales; however, their precise computational role is still debated. One physically inspired hypothesis suggests that the cortical sheet may act l
Externí odkaz:
http://arxiv.org/abs/2309.08045
Publikováno v:
Neural Computation, 1-30 (2024)
The current reinforcement learning framework focuses exclusively on performance, often at the expense of efficiency. In contrast, biological control achieves remarkable performance while also optimizing computational energy expenditure and decision f
Externí odkaz:
http://arxiv.org/abs/2305.18701
Autor:
Patel, Devdhar, Russell, Joshua, Walsh, Francesca, Rahman, Tauhidur, Sejnowski, Terrence, Siegelmann, Hava
We present temporally layered architecture (TLA), a biologically inspired system for temporally adaptive distributed control. TLA layers a fast and a slow controller together to achieve temporal abstraction that allows each layer to focus on a differ
Externí odkaz:
http://arxiv.org/abs/2301.00723
Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional pe
Externí odkaz:
http://arxiv.org/abs/2211.05922
Autor:
Zador, Anthony, Escola, Sean, Richards, Blake, Ölveczky, Bence, Bengio, Yoshua, Boahen, Kwabena, Botvinick, Matthew, Chklovskii, Dmitri, Churchland, Anne, Clopath, Claudia, DiCarlo, James, Ganguli, Surya, Hawkins, Jeff, Koerding, Konrad, Koulakov, Alexei, LeCun, Yann, Lillicrap, Timothy, Marblestone, Adam, Olshausen, Bruno, Pouget, Alexandre, Savin, Cristina, Sejnowski, Terrence, Simoncelli, Eero, Solla, Sara, Sussillo, David, Tolias, Andreas S., Tsao, Doris
Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which c
Externí odkaz:
http://arxiv.org/abs/2210.08340
Autor:
Sejnowski, Terrence
Publikováno v:
Neural Computation, 35, 309-342 (2023)
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 natural language tasks, each of which previously would have required a sep
Externí odkaz:
http://arxiv.org/abs/2207.14382
Autor:
Budzinski, Roberto C., Nguyen, Tung T., Benigno, Gabriel B., Doàn, Jacqueline, Mináč, Ján, Sejnowski, Terrence J., Muller, Lyle E.
We introduce an analytical approach that allows predictions and mechanistic insights into the dynamics of nonlinear oscillator networks with heterogeneous time delays. We demonstrate that time delays shape the spectrum of a matrix associated to the s
Externí odkaz:
http://arxiv.org/abs/2207.13785