Neural mechanisms underlying flexible learning and decision-making are not fully understood. Using single-cell calcium imaging, authors here found that neurons in orbitofrontal and secondary motor cortex exhibit complementary roles in reward learning, with neurons in the former exerting a sustained role in conditions of uncertainty.

Does RL teach LLMs genuinely new skills, or does it merely activate existing ones? This question lies at the core of ongoing debates about the role of RL in LLM post-training. On one side, strong empi...

Self-related processes in the default mode network (DMN) have been viewed predominantly through a cognitive lens, often overlooking the embodied dimen…

Multi-step planning is a challenge for LLMs. Here, the authors introduce a brain-inspired Modular Agentic Planner that decomposes planning into specialized LLM modules, improving performance across tasks and highlighting the value of cognitive neuroscience for LLM design.

The hypothesis that Convolutional Neural Networks (CNNs) are inherently texture-biased has shaped much of the discourse on feature use in deep learning. We revisit this hypothesis by examining limitat...

A 1,024-channel microelectrode array is delivered to the brain cortex via a minimally invasive incision in the skull and dura, and allows recording, stimulation and neural decoding across large portions of the brain in porcine models and human neurosurgical patients.

Schizophrenia - Hearing voices and other altered perceptual experiences across psychotic, mood, and anxiety disorders: from phenomenology and mechanisms to future directions

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Scientific Data - A Human EEG Dataset for Multisensory Perception and Mental Imagery

This study offers a novel approach for benchmarking complex cognitive behavior in artificial systems. Almost universally, Large Language Models (LLMs) perform best on tasks which may be included in th...

But the agency has spent nearly its entire budget for this fiscal year, which ends tomorrow.

The entire U.S. economy is being propped up by the promise of productivity gains that seem very far from materializing.