- learning and memory: how does biological organisms learn and retain useful information in a dynamic world? How to model the biophysical mechanisms of learning and memory through mathematical simulations of large-scale neural systems? How do we regulate the granularity (specificity vs. generality) of what we learn?
- visual perception: how do we perceive static and moving features/objects?
- short-term memory and decision making: how is information reliably store in frontal cortical areas?
- Palma, J., and Grossberg, S., and Versace, M. (2011) Persistence and storage of activity patterns in spiking recurrent cortical networks: Modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine. Frontiers in Computational Neuroscience, 6:42. doi: 10.3389/fncom.2012.00042.
- Palma, J., Versace, M., and Grossberg, S. (2011) After-hyperpolarization currents and acetylcholine control sigmoid transfer functions in a spiking cortical model. Journal of Computational Neuroscience, DOI: 10.1007/s10827-011-0354-8.
- Leveille, J., Versace, M., and Grossberg, S. (2010) How do object reference frames and motion vector decomposition emerge in laminar cortical circuits? Attention, Perception, & Psychophysics, Vol. 73, No. 4, 1147-1170.
- Versace, M., and Zorzi, M. (2010) The role of dopamine in the maintenance of working memory in prefrontal cortex neurons: input-driven versus internally-driven networks. International Journals of Neural Systems, Aug, 20(4):249-65
- Leveille, J., Versace, M., and Grossberg, S. (2010) Running as fast as it can: How spikes form object groupings in the laminar circuits of visual cortex? Journal of Computational Neuroscience, 28(2):323-46.
- Grossberg, S., and Versace, M. (2008) Spikes, synchrony, and attentive learning by laminar thalamocortical circuits. Brain Research, 1218C, 278-312 [Authors listed alphabetically].
- Gorchetchnikov, A., Versace, M., and Hasselmo, M.E. (2005) A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay. Neural Networks 18, 458–466.
- Plastic synapses in a stable brain. Versace, M. (2010) Invited talk, Qualcomm, CA, USA.  Link to the talk. (modified Ph.D. defense talk)
- Laminar circuits for synchronous thalamocortical information processing and attentive stable learning by spiking neurons. PhD Thesis, Boston University, 2007.
- SMART networks and stimuli. Supplementary material to Brain Research, submitted in December 2007
- BA-MA thesis, Univeristy of Trieste, Italy. Come vede una rete neurale. PDF
Abstracts & Conference papers
- Gorchetchnikov, A., Versace, M., Ames, H., Chandler, B., Laveille, J., Livitz, G., Mingolla, E., Snider, G., Amerson, R., Carter, D., Abdalla, H., and Qureshi, S. (2011) A Unified Learning Framework for Memristive Neuromorphic Hardware. Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2011, San Jose, CA, USA.
- Vasilkoski , Z., Versace, M., Ames, H., Chandler, B., Leveille, J., Gorchetchnikov, A., Livitz, G., and Mingolla, E. (2011) Stability analysis of neural plasticity rules for implementation on memristive neuromorphic hardware.Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2011, San Jose, CA, USA.
- Leveille, J., Ames, H., Chandler, B., Gorchetchnikov, A., Mingolla, E., Patrick, S., and Versace, M. (2010) Learning in a distributed software architecture for large-scale neural modeling. BIONETICS10, Boston, MA, USA.
- Lorenz, S., Ames, H., and Versace, M. (2010) Consciousness and neuromorphic chips: A case for embodiment. Boston University Interdisciplinary Graduate Conference on Consciousness, Boston, MA.
- Gorchetchnikov, A., Versace, M., and Hasselmo, M.E. (2005) Spatially and temporally local spike-timing-dependent plasticity rule. Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2005, Montreal, QC, Canada. 1568, 390–396.
Tutorials and Resources
- What is a neuron, anyway? A post on neurdon.com a very basic neuron spiking neuron model and provides MATLAB code for download
- The CNS Tech Lab software repository. Provides a number of software for download, ranging from machine vision, to machine learning, to neural modeling, completed of MATLAB source code and documentation.