Aneta Koseska

The paper investigates how structured connectivity in neural circuits gives rise to sequential computations by identifying circuit motifs that generate different types of neuronal selectivity.

This paper investigates the role of slow dynamics in neural computation, showing that structured transient dynamics enable temporal computation and generalization.

The paper introduces a framework called signaling homeorhesis to explain how cells interpret growth factor signals over time to produce distinct phenotypes.

The paper shows that FGF4-mediated cell-cell communication ensures stable proportions of differentiated cell types in mouse embryonic stem cells despite initial variability and perturbations.

This paper proposes a population-based dynamical framework for cellular differentiation that explains robustness and timing through symmetry breaking in growing cell populations.

This paper proposes a framework for temporal information processing in biochemical networks at criticality, showing that dynamic memory enables signal integration and balances stability with plasticity.

This paper describes a synthetic membrane system that undergoes self-organized shape changes in response to light cues through a light-inducible signaling system and microtubule dynamics.

The paper identifies how EGFR interacts with PTPs on juxtaposed membranes to create a network that senses and responds to growth factor signals.