COLLECTIVE COMPUTATION ACROSS SCALES OF BIOLOGICAL ORGANISATION

"Biological systems—from cells to tissues to individuals to societies—are hierarchically organised,

which suggests there are multiple natural scale at which these systems should be studied. Across

disciplines (e.g. neurobiology, genetics, evolutionary biology), biologists often focus on isolating a

single scale and understanding the patterns observed at this level of the hierarchy. While the task of

understanding observed patterns in nature requires revealing the mechanisms that underlie them,

these mechanisms generally operate at a different scale than the observed pattern itself. In many

cases, the patterns must be studied as emerging from interactions among a collection of smaller

units. However, in other cases, they are imposed upon the system by larger scale constraints. For

example, a compass-like representation of landmarks in the fruit fly brain is only observable at a

larger scale by coarse-graining the neural firing rates; gradient tracking in fish schools emerges from

individuals responding to local resource levels; natural selection on phenotypic traits is constrained

by the species’ evolutionary history and other environmental factors. In all examples, spatially and

temporally distributed information is captured at the system level and translated to some

behavioural output. In this thesis, I explore the link between the different scales of biological

organisation, and the idea that hierarchical organisation allows these systems to maximise

information extraction across space and time."

-extracted from the summary of Vivek's thesis.