benvenuti to the personal website of massimiliano versace

I received my MA in Experimental Psychology from the University of Trieste, Italy and my PhD from the Department of Cognitive and Neural Systems at Boston University, where I am currently a Postdoc and Assistant Director of the CNS Technology Lab. My research interests are focused on neural networks - in particular applied to cortical models of learning and memory. I am also involved in the development and testing of a software package for advanced neurosimulations, KInNeSS. Most of my activity is carried out at CNS at Boston University.
Massimiliano Versace
In January 2006 I co-founded Neurala LLC with the target of developing a technology platform that enables programmers to write brain-based algorithms that exploit emerging, low-cost parallel hardware components. Other research interests include the application of machine learning algorithms to financial forecasting. [read more]

RESEARCH Highlights

The Synchonous Matching Adaptive Resonance Theory (SMART) model

SMART was jointly developed with Prof. Stephen Grossberg at Boston University to answer a fundamental question in neuroscience and brain-inspired technologies: how do spiking laminar cortical circuits self-organize and stably learn relevant information? How can these circuits be embedded in low-power, hybrid CMOS chip and used to solve challenging pattern recognition problems?

 

neurons The SMART model of Synchronous Matching Adaptive Resonance Theory clarifies how multiple levels of brain organization, from spikes, to brain local field potentials, inter-areal synchronous oscillations, and spike-timing dependent plasticity are coordinated to regulate stable category learning and attention during cognitive information processing. This achievement was facilitated by the concurrent development of the KDE Integrated NeuroSimulation Software (KInNeSS), which is a software for large-scale neural models of cortical and subcortical areas unique in its kind in that it simultaneously allows the researcher to evaluate the spiknig dynamics of the individual cells in the network and the behavior of the entire system.  [read more]

IN THE WORKS....

- How to reliably control the spiking transfer function of biophysically realistic neurons?

- Explaining motion reference frames in laminar cortical circuits


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