Temporal organization of naturalistic behavior

Naturalistic animal behavior exhibits a striking amount of variability in the temporal domain, and be decomposed across at least three axes: hierarchical, contextual, and stochastic. A large hierarchy of simultaneous timescales at which behavior unfolds, ranging from milliseconds to minutes; contextual modulations affecting the expression of behavior at each level of this hierarchy; and stochasticity in the variability of the same behavioral unit across repetition in the same context. These three axes may or may not interact depending on the scenarios and the species. We explore an emergent mechanistic theory of temporal variability based on attractor neural networks and metastable dynamics, arising from the coordinated interactions between mesoscopic neural circuits. A crucial role is played by structural heterogeneities and by noise arising in mesoscopic circuits.

Metastable attractors explain the variable timing of stable behavioral action sequences
S. Recanatesi*, U. Pereira*, M. Murakami, Z. Mainen*, L. Mazzucato*.
2022, Neuron 110, 1–15. Open Access link.
[code] [biorxiv]

Neural mechanisms underlying the temporal organization of naturalistic animal behavior
L. Mazzucato. [arXiv]

State-dependent control of cortical processing speed via gain modulation
David Wyrick, L. Mazzucato.
Journal of Neuroscience 41 (18), 3988-4005. [pdf]
[biorxiv][simulation code][data analysis code]

A reservoir of timescales in random neuronal networks
Merav Stern, Nicu Istrate, Luca Mazzucato, biorxiv.

Expectation-induced modulation of metastable activity underlies faster coding of sensory stimuli
​​​L. Mazzucato, G. La Camera*, A. Fontanini*. 
Nature Neuroscience 2019, https://doi.org/10.1038/s41593-019-0364-9 
[article] [biorxiv] [code] [pdf] [suppl]

Cortical computations via metastable activity
G. La Camera, A. Fontanini, L. Mazzucato.
Current Opinion in Neurobiology 58, 37-45, https://doi.org/10.1016/j.conb.2019.06.007
[article] [arxiv] [pdf]