🧠 New paper by Ishida et al who show how #neurons in the #Drosophila central complex implement vector inversion via #calcium spikes.
A single #NeuronalPopulation can flip the sign of its encoded vector by switching biophysical #spiking modes, enabling coordinate transformations through #PopulationDynamics rather than circuit switching.
Cool as it shows that computation is not imposed by the circuit, but emerges from the neuron’s own dynamics.
I wrote a blog post about a lecture introducing stability in ODE models and their numerical solution. The lecture transcript and code for figures are included.
https://nadiah.org/2025/12/04/mxb261
#mathematicalEcology #ODEs #stability #mathematics #lectureNotes #populationDynamics
I wrote a blog post about a lecture introducing stability in ODE models and their numerical solution. The lecture transcript and code for figures are included.
https://nadiah.org/2025/12/04/mxb261
#mathematicalEcology #ODEs #stability #mathematics #lectureNotes #populationDynamics
There's a great talk by Juan Gallego on how low-dimensional #NeuralManifolds arise from biological constraints, remain invariant across states and inputs, and support cross-animal alignment. Examples span #HeadDirection rings, #gridcell tori, #MotorCortex prep vs movement, striatal timing dynamics, and C. elegans #behavior loops. Cool talk as it shows how #manifold-level structure can generalize across tasks and organisms.
🧠 New preprint by Tilbury et al: Characterizing #NeuronalPopulation geometry with #AI equation discovery
The approach generates & evaluates 100s of candidate equations, finding "peaky" non-Gaussian tuning functions whose Fourier structure matches power-law dimensionality observed in real #V1 pops. Links shape of single- #neuron tuning to #PopulationLevel geometry using both data fits & analytical derivations.
🧠 New paper by Safaai et al. (2025): parietal #cortex output populations show highly structured, task-dependent population geometry. Using multi-area recordings and circuit modeling, they show that #parietal populations display organized task-related patterns rather than uniform mixed coding, and that distinct output groups shape how decisions are routed to downstream targets:
🌍 https://doi.org/10.1038/s41593-025-02095-x
#Neuroscience #NeuralCoding #ParietalCortex #PopulationDynamics #DecisionMaking
Specialized structure of neural population codes in parietal cortex outputs
🧠 New paper by Wimalasena, Pandarinath, AuYong et al: #spinal #interneuron populations form a low-dimensional #manifold that robustly organizes step cycles.
Distinct regions of the manifold mark flexion–extension transitions, and a specific “hold region” tightly controls cycle duration. Deletions emerge as failures to enter the flexor region, giving a dynamical signature of disrupted CPG function.
🌍 https://doi.org/10.1038/s41467-025-64629-y
#Neuroscience #Locomotion #SpinalCord #PopulationDynamics #CompNeuro
Spinal interneuron population dynamics underlying flexible pattern generation
🧠 New #preprint by Komi et al. (2025): Neural #manifolds that orchestrate walking and stopping. Using #Neuropixels recordings from the lumbar spinal cord of freely walking rats, they show that #locomotion arises from rotational #PopulationDynamics within a low-dimensional limit-cycle #manifold. When walking stops, the dynamics collapse into a postural manifold of stable fixed points, each encoding a distinct pose.
🧠 New preprint by Kim et al. (2025) from David Anderson’s lab: A line #attractor maintains aggressiveness during feeding in “hangry” mice 🍔🐁. Using in vivo #CalciumImaging and #rSLDS modeling, they show how moderate fasting stabilizes an aggression-related attractor in #VMHvl, while prolonged fasting collapses it, linking hunger, motivation, and aggression through #PopulationDynamics:
🌍 https://doi.org/10.1101/2025.10.16.682711
#Neuroscience #CompNeuro #Behavior #AttractorDynamics #Hypothalamus #2p #imaging
