Stochastic Ising model with plastic interactions

Eugene Pechersky, Guillem Via and Anatoly Yambartsev

We propose a new model based on the Ising model with the aim to study synaptic plasticity phenomena in neural networks. It is today well established in biology that the synapses or connections between certain types of neurons are strengthened when the neurons are co-active, a form of the so called synaptic plasticity. Such mechanism is believed to mediate the formation and maintenance of memories. The proposed model describes some features from that phenomenon. Together with the spin-flip dynamics, in our model the coupling constants are also subject to stochastic dynamics, so that they interact with each other. The evolution of the system is described by a continuous-time Markov jump process.

Snippets of the Second NeuroMat Workshop

The Research, Innovation and Dissemination Center for Neuromathematics has hosted this month its second workshop, gathering members of the three teams --research, technology transfer and scientific dissemination-- and guests. The event took place at the University of São Paulo with support from the São Paulo Research Foundation and combined short and long presentations, roundtables and working groups. This workshop provided a sense of the evolution of activities and was an opportunity to exchange interdisciplinary perspectives on ongoing and future lines of action.

Phase transitions and self-organized criticality in networks of stochastic spiking neurons

Ludmila Brochini, Ariadne de Andrade Costa, Miguel Abadi, Antônio C. Roque, Jorge Stolfi and Osame Kinouchi

Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains – a form of short-term plasticity probably located at the axon initial segment (AIS) – instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

Opening for Web-based and mobile application design Scholarship

The Research, Innovation and Dissemination Center on Neuromathematics (NeuroMat) is offering a FAPESP scholarship for information technology professionals interested in being part of a breakthrough and innovative scientific project. The recipient will interact with researchers from USP and other NeuroMat collaborating institutions in activities of development, customization, maintenance and deployment of open software related to the scientific goals of the center.

Openings for Software Developers

The Research, Innovation and Dissemination Center on Neuromathematics (RIDC NeuroMat) is offering scholarships for information technology professionals interested in being part of a breakthrough and innovative scientific project.

Pages

 

NeuroMat

The Research, Innovation and Dissemination Center for Neuromathematics is hosted by the University of São Paulo and funded by FAPESP (São Paulo Research Foundation).

 

User login

 

Contact

Address:
1010 Matão Street - Cidade Universitária - São Paulo - SP - Brasil. 05508-090. See map.

Phone:
55 11 3091-1717

General contact email:
neuromat@numec.prp.usp.br

Media inquiries email:
comunicacao@numec.prp.usp.br