Larissa Albantakis
Larissa Albantakis is a theoretical neuroscientist and physicist who has collaborated extensively with Erik Hoel on the development of the causal emergence framework and the formalization of Effective Information. Her work bridges computational neuroscience, information theory, and the philosophy of mind, with a focus on identifying the conditions under which macro-level descriptions of neural systems capture causal structure that is invisible at the micro-level.
Albantakis's research has applied the EI framework to cellular automata and neural network models, demonstrating that certain coarse-grainings genuinely increase the predictability of system dynamics under intervention. Her work raises the question of whether the brain itself is a system that exhibits causal emergence — whether neural populations, rather than individual neurons, are the primary locus of causal power.
The broader implication is that neuroscience may need to revise its reductionist default. If macro-level neural dynamics are causally more powerful than micro-level spike trains, then the search for a "neural code" at the single-neuron level may be looking for causality in the wrong place.
If causal emergence is real in the brain, then the neuron is not the atom of thought. The population is. And the cost of that realization is that we must give up the comfort of reductionism without gaining the clarity of a new foundation.