MesoNet: nonlinear dynamics and useful variability

interesting squiggles ≠ automatically chaos. same input spikes, almost-identical initial states... save that comparison for later

study topic: chaotic attractors and the relation between nonlinear network dynamics, robustness and computation. The notebook explores configurations with different weight scales and activity behavior.

Lyapunov heatmap

Dynamical-systems conjecture

reference distinction: variability, oscillation and chaos are not interchangeable descriptions. A visually irregular trace is not by itself a demonstrated chaotic attractor.

review questions: what state variables and timescale define the trajectory? Are the dynamics driven by stochastic input, deterministic recurrence or changing weights? Freeze learning when isolating state dynamics, and preserve the input/seed when comparing perturbations. These are suggested checks for the research question, not additional historical experiments.

References saved in this journal section

• https://brian2.readthedocs.io/en/latest/resources/tutorials/2-intro-to-brian-synapses.html
• https://journals.aps.org/pre/abstract/10.1103/PhysRevE.51.738
• https://eclass.uoa.gr/modules/document/file.php/MATH626/Morris%20W.%20Hirsch%2C%20Stephen%20Smale%20and%20Robert%20L.%20Devaney%20%28Auth.%29%20-%20Differential%20Equations%2C%20Dynamical%20Systems%2C%20and%20an%20Introduction%20to%20Chaos-Academic%20Press%20%282012%29.pdf
• https://www.jmlr.org/papers/volume22/20-1031/20-1031.pdf