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Check out the newest work from our, from Fabricio Nicola @fabricionicola.bsky.social on mouse jumping and spinal cell types. Excellent collab with @vulcnethologist.bsky.social www.biorxiv.org/content/10.6...

Cool new work from @dudman.bsky.social and @fluketc.bsky.social Reward magnitude determines reinforcement learning efficiency: www.science.org/doi/10.1126/...

Hot off the presses, this study is now out in the Journal of Neuroscience! A quick write-up: www.jneurosci.org/content/46/2... And the full paper: www.jneurosci.org/content/46/2...

Standard animal learning studies minimize individual reward magnitudes to maximize the repetitions of reinforced behaviors. We investigated how reward magnitude influences initial learning across five...

Come work with us! We're looking for a new lab manager to help us develop new motion capture methods, new biosensors, and to hopefully learn something cool about the brain. Bonus: you get to do all this in the ATL and, in my humble opinion, we're nice people to work with! markolab.org/careers/

Toward Improving Brain–Computer Interfaces Ryan A. Canfield, Tomohiro Ouchi, Hao Fang, Beatrice Macagno, Lydia I. Smith et al. (see article e1965252026) Researchers are working on improving motor ...

🚨Pre-print alert! 🚨https://www.biorxiv.org/content/10.1101/2025.10.17.683171v1 Our new study tackles the question: do all neurons in motor cortices (MC) encode movement & coordinate as we move? Answering this question will be key for effectively targeting motor representations in BCIs.

Intracortical brain-computer interfaces (BCI) leverage knowledge about neural representations to translate movement-related neural activity into actions. BCI implants have targeted broad cortical regi...

Natural behavior unfolds as coordinated sequences of body movements. This organization suggests that behavior may be built from discrete motor patterns, yet how such arrangements are implemented by neural circuits remains unknown. Here, we combined kinematic analysis, muscle recordings, genetically identified cell types, and closed-loop optogenetic perturbations to examine the organizational logic of natural gap-crossing jumps in mice. Jumping was characterized by a series of precisely defined phases and their associated modular motor patterns. The core phases, propulsion and flight, exhibited distinct signatures of neural control, including unique bursts of coordinated hindlimb muscle activity, differential tuning strategies for jump distance, and active requirements for spinal neural drive. Mapping activity across lumbar interneuron populations and functionally screening candidate cell types for their ability to drive coordinated movement revealed that a population of dorsal excitatory dILB6 neurons can autonomously evoke coordinated multi-joint hindlimb flexion characteristic of the jumping flight phase, across behavioral contexts. These findings provide a specific cellular substrate for the long-standing concept of spinal modular motor control: a flexible, preconfigured motor template that the mammalian CNS can recruit and modulate to meet the demands of natural behavior. ### Competing Interest Statement The authors have declared no competing interest. Intramural Research Program of the National Institutes of Health (NIH)

Mammals have hundreds of joints and muscles. Controlling them individually would be nearly impossible. How does the nervous system organize such complexity into coherent actions? Our new study explores this question through a natural behavior: jumping.