Brain Studio has been developed by the Computational Neurodynamics Lab at Imperial College London. The aim is to automate and speed-up the process of designing and testing large-scale spiking neural networks (SNNs), through a suite of new simulation tools. In particular, this suite provides (1) a framework for the compact representation of modular SNNs, suitable for large-scale brain circuits and cognitive systems, (2) a generic and powerful simulator that allows the fast implementation, visualization and real-time adjustments of SNNs, and (3) a fast optimization technique, which could be used in order to mimic the dynamical behaviour of specific neurons in the brain, using simple phenomenological models.



I have been involved in computational modelling work for the TIMESTORM project, an EU collaboration between six academic institutions around europe.

Contemporary research endeavours aim at equipping artificial systems with human-like cognitive skills, in an attempt to promote their intelligence beyond repetitive task accomplishment. However, despite the crucial role that the sense of time has in human cognition, both in perception and action, the capacity of artificial agents to experience the flow of time remains largely unexplored. The inability of existing systems to perceive time constrains their potential understanding of the inherent temporal characteristics of the dynamic world, which in turn acts as an obstacle to their symbiosis with humans. Time perception is without doubt, not an optional extra, but a necessity for the development of truly autonomous, cognitive machines.

TIMESTORM aims at bridging this fundamental gap by shifting the focus of human-machine confluence to the temporal, short- and long-term aspects of symbiotic interaction. The integrative pursuit of research and technological developments in time perception will contribute significantly to ongoing efforts in deciphering the relevant brain circuitry and will also give rise to innovative implementations of artifacts with profoundly enhanced cognitive capacities.

Equipping artificial agents with temporal cognition establishes a new framework for the investigation and integration of knowing, doing, and being in artificial systems. The proposed research will study the principles of time processing in the human brain and their replication in- silico, adopting a multidisciplinary research approach that involves developmental studies, brain imaging, computational modelling and embodied experiments. By investigating artificial temporal cognition, TIMESTORM inaugurates a novel research field in cognitive systems with the potential to contribute to the advent of next generation intelligent systems, significantly promoting the seamless integration of artificial agents in human societies.


PhD Research

I completed a PhD. in Computational Neuroscience under the supervision of Professor Murray Shanahan at Imperial College London. My PhD investigated metastable dynamics in interacting populations of spiking neurons. The investigation focused on modelling and mathematically analysing the effects of topological structure and plasticity on dynamics. The work elucidated how the combined activity of individual spiking neurons gives rise to the formation of coherent oscillating assemblies, and how the dynamics between these assemblies evolve over time. A symbiotic relationship between plasticity and structure was identified, in which spike-timing dependent plasticity acting in concert with the oscillatory interactions between neural populations causes the network to restructure so as to have a modular small-world topology akin to those found in the brain. These structures in turn enhance metastabilty. Another major finding in the thesis relating to the kinds of complex network that give rise to metastable dynamics shows that networks with a densely intra-connected set of topologically central nodes tend to promote metastability. In a nutshell this suggests that the biological brain has exactly the right sort of connectivity to generate the kind of dynamics that is believed to be central to cognition. It is my thesis that metastable phenomena permit the exploration, integration and communication of functionally related neural areas during cognitive processing.