Topic: neuronal dynamics

Artificial neural networks simplify complex biological circuits into tractable models for computational exploration and experimentation. However, the simplification of artificial models also undermines their applicability to real brain dynamics. Typical efforts to address this mismatch add complexity to increasingly unwieldy models. Here, we take a different approach; by reducing the complexity of a biological cortical culture, we aim to distil the essential factors of neuronal dynamics and plasticity. We leverage recent advances in growing neurons from human induced pluripotent stem cells (hi

Distinct synapses influence one another when they undergo changes, with unclear consequences for neuronal dynamics and function. Here we show that synapses can interact such that excitatory currents are naturally normalised and balanced by inhibitory inputs. This happens when classical spike-timing dependent synaptic plasticity rules are extended by additional mechanisms that incorporate the influence of neighbouring synaptic currents and regulate the amplitude of efficacy changes accordingly. The resulting control of excitatory plasticity by inhibitory activation, and vice versa, gives rise t

In a complex and mutable environment, animals continuously face scenarios where behavioral decisions determine their survival. These rely primarily on sensory input and the associated cognitive process is known as perceptual decision-making. The decision-making is typically preceded by the gathering of information across time in a process called evidence accumulation. This has been widely studied on various animals; however, in flies, the emphasis has primarily been centered on the subcellular integration mechanisms, overlooking the behavioral impacts and whole-brain neuronal dynamics.Here, we