Perisaccadic and Attentional Remapping of Receptive Fields in Lateral Intraparietal Area and Frontal Eye Fields

Kavli Affiliate: Michael Goldberg | Authors: Xiao Wang, Cong Zhang, Lin Yang, Min Jin, Michael E Goldberg, Mingsha Zhang and Ning Qian | Summary: The nature and function of perisaccadic receptive-field (RF) remapping have been controversial. We used a delayed saccade task to reduce previous confounds and examined the remapping time course in areas LIP […]


Continue.. Perisaccadic and Attentional Remapping of Receptive Fields in Lateral Intraparietal Area and Frontal Eye Fields

Automatic monitoring of whole-body neural activity in behaving Hydra

Kavli Affiliate: Rafael Yuste | Authors: Alison Hanson, Raphael Reme, Noah Telerman, Wataru Yamamoto, Jean-Christophe Olivo-Marin, Thibault Lagache and Rafael Yuste | Summary: The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with […]


Continue.. Automatic monitoring of whole-body neural activity in behaving Hydra

Predicting Long and Short Duration Beta Bursts from Subthalamic Nucleus Local Field Potential Activity in Parkinson’s Disease

Kavli Affiliate: Philip Starr | Authors: Bahman Abdi-Sargezeh, Sepehr Shirani, Abhinav Sharma, Philip Starr, Simon Little and Ashwini Oswal | Summary: Neural activities within the beta frequency range (13-30 Hz) are not stationary, but occur in transient packets known as beta bursts. Parkinson’s disease (PD) is characterized by the occurrence of beta bursts of increased […]


Continue.. Predicting Long and Short Duration Beta Bursts from Subthalamic Nucleus Local Field Potential Activity in Parkinson’s Disease

Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Hanyun Yin, Heng Huang, Wei Gao, | Summary: Fine-tuning is the most effective way of adapting pre-trained large language models (LLMs) to downstream applications. With the fast growth of LLM-enabled AI applications and democratization of open-souced LLMs, fine-tuning has become possible for non-expert individuals, but […]


Continue.. Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Hanyun Yin, Heng Huang, Wei Gao, | Summary: Fine-tuning is the most effective way of adapting pre-trained large language models (LLMs) to downstream applications. With the fast growth of LLM-enabled AI applications and democratization of open-souced LLMs, fine-tuning has become possible for non-expert individuals, but […]


Continue.. Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Deep Learning with Photonic Neural Cellular Automata

Kavli Affiliate: Alireza Marandi | First 5 Authors: Gordon H. Y. Li, Christian R. Leefmans, James Williams, Robert M. Gray, Midya Parto | Summary: Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable hardware. Photonics offers a promising solution by leveraging the unique properties of light. […]


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Exact coherent structures in two-dimensional turbulence identified with convolutional autoencoders

Kavli Affiliate: Michael P. Brenner | First 5 Authors: Jacob Page, Joe Holey, Michael P. Brenner, Rich R. Kerswell, | Summary: Convolutional autoencoders are used to deconstruct the changing dynamics of two-dimensional Kolmogorov flow as $Re$ is increased from weakly chaotic flow at $Re=40$ to a chaotic state dominated by a domain-filling vortex pair at […]


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mixed attention auto encoder for multi-class industrial anomaly detection

Kavli Affiliate: Feng Wang | First 5 Authors: Jiangqi Liu, Feng Wang, , , | Summary: Most existing methods for unsupervised industrial anomaly detection train a separate model for each object category. This kind of approach can easily capture the category-specific feature distributions, but results in high storage cost and low training efficiency. In this […]


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Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Kavli Affiliate: Mark Churchland, Liam Paninski | Authors: Yizi Zhang, Tianxiao He, Julien Boussard, Charlie Windolf, Olivier Winter, Eric Trautmann, Noam Roth, Hailey Barrell, Mark M Churchland, Nicholas A Steinmetz, The International Brain Laboratory, Erdem Varol, Cole Hurwitz and Liam Paninski | Summary: Neural decoding and its applications to brain computer interfaces (BCI) are essential […]


Continue.. Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Kavli Affiliate: Martin Lindquist | Authors: Rotem Botvinik-Nezer, Bogdan Petre, Marta Ceko, Martin A. Lindquist, Naomi P. Friedman and Tor D. Wager | Summary: Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses […]


Continue.. Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain