🧠 New preprint by Hacker et al.: A systematic comparison of population representations in spikes vs high-gamma #LFP activity.
Using pseudopopulations, representational similarity analyses, and categorical decoders, the study shows that both spikes and #HGA carry robust category information, but with distinct statistical structure and effect sizes. A data-driven look at what different neural signals actually encode at the #PopulationLevel.
🧠 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.
📙#Fertility #projections are vital for anticipating demand for #maternity, #childcare & other services 🫄👨👦
The innovative #Bayesian model reported in this new journal article by Joanne Ellison, Ann Berrington, Eren Dodd, and Jonathan Forster, incorporates individual-level #UnderstandingSociety #data to generate plausible #forecasts by individual-level variables - including #educational #qualification - despite their absence in the #populationlevel data. Read more 👇👇
https://academic.oup.com/jrsssc/advance-article/doi/10.1093/jrsssc/qlad095/7343209?login=true
Charles Micou & Timothy O'Leary discover that representational drift in #neuralactivity and physiological changes, observed over extended periods, suggests the continuous application of a #learningrule at the #cellular and #populationlevel. This phenomenon serves as a measurable signal to uncover system-level properties of biological #plasticity mechanisms, such as precision and effective #learningrates.
Fabrizio Musacchio
Fabrizio Musacchio
Centre for Population Change