The ability to decide and act autonomously is a distinctive feature of human cognition. From a motor neurophysiology viewpoint, these 'voluntary' actions can be distinguished by the lack of an obvious triggering sensory stimulus: the action is considered to be a product of thought, rather than a reflex result of a specific input. A reverse engineering approach shows that such actions are caused by neurons of the primary cortex, which in turn depend on medial frontal areas, and finally a combination of prefrontal cortical connections and subcortical drive from basal ganglia loops. One traditional marker of voluntary action is the EEG readiness potential (RP), recorded over the frontal cortex prior to voluntary actions. However, the interpretation of this signal remains controversial, and very few experimental studies have attempted to link the RP to the thought process that lead to voluntary action. In this talk, I will report new studies that show learning an internal model about the optimum delay at which to act influences the amplitude of the RP. More generally, a scientific understanding of voluntariness and autonomy will require new neurocognitive paradigms connecting thought and action.

Ants, bees and other insects have the ability to return to their nest or hive using a navigation strategy known as path integration. Similarly, fruit flies employ path integration to return to a previously visited food source. An important component of path integration is the ability of the insect to keep track of its heading relative to salient visual cues. A highly conserved brain region known as the central complex has been identified as being of key importance for the computations required for an insect to keep track of its heading. However, the similarities or differences of the underlying heading tracking circuit between species are not well understood. We sought to address this shortcoming by using reverse engineering techniques to derive the effective underlying neural circuits of two evolutionary distant species, the fruit fly and the locust. Our analysis revealed that regardless of the anatomical differences between the two species the essential circuit structure has not changed. Both effective neural circuits have the structural topology of a ring attractor with an eight-fold radial symmetry (Fig. 1). However, despite the strong similarities between the two ring attractors, there remain differences. Using computational modelling we found that two apparently small anatomical differences have significant functional effect on the ability of the two circuits to track fast rotational movements and to maintain a stable heading signal. In particular, the fruit fly circuit responds faster to abrupt heading changes of the animal while the locust circuit maintains a heading signal that is more robust to inhomogeneities in cell membrane properties and synaptic weights. We suggest that the effects of these differences are consistent with the behavioural ecology of the two species. On the one hand, the faster response of the ring attractor circuit in the fruit fly accommodates the fast body saccades that fruit flies are known to perform. On the other hand, the locust is a migratory species, so its behaviour demands maintenance of a defined heading for a long period of time. Our results highlight that even seemingly small differences in the distribution of dendritic fibres can have a significant effect on the dynamics of the effective ring attractor circuit with consequences for the behavioural capabilities of each species. These differences, emerging from morphologically distinct single neurons highlight the importance of a comparative approach to neuroscience.