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Learning Neural Connectivity from Firing Activity: Scalable Algorithms with Provable Guarantees

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Definitive Consensus for Distributed Data Inference

Leonidas Georgopoulos

Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...

EPFL2011

Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer

Michael Lee Hines, Sameer Kumar

For neural network simulations on parallel machines, Interprocessor spike communication can be a significant portion of the total simulation time. The performance of several spike exchange methods using a Blue Gene/P (BG/P) supercomputer has been tested wi ...

2011

Adaptation reduces variability of the neuronal population code

Eilif Benjamin Muller

Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calculate the interval and count statistics ...

2011

Network community-detection enhancement by proper weighting

Martin Hasler, Ali Ajdari Rad, Alireza Khadivi

In this article, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general ...

American Physical Society2011

Effective Stimuli for Constructing Reliable Neuron Models

Henry Markram, Sean Lewis Hill, Thomas Berger, Idan Segev

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for ...

Public Library of Science2011

Organizing neural networks

Henry Markram, Rodrigo de Campos Perin, Thomas Berger

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by betwe ...

2011

Estimating small-world topology of neural networks from multi-electrode recordings

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

Since the seminal work of Watts in the late 90s [1], graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures [2]. Most studies have focused on functional connectivity defined between whole brain regions, us ...

2010

Decoding of attention deployment

Michael Herzog, Gijs Plomp, Yvonne Evelina Thunell

Attending to an object can strongly modulate the neural processing of this object. Using average EEG, it was shown that small differences in the focus of attention yield large and long lasting changes in brain dynamics (Plomp et al, 2009). Here, we show th ...

2010

Code-specific policy gradient rules for spiking neurons

Wulfram Gerstner, Guillaume Hennequin

Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning r ...

Massachusetts Institute of Technology Press2009

Early consensus in complex networks under variable graph topology

Martin Hasler, Leonidas Georgopoulos

Analysis of the linear algorithm for consensus on complex networks shows the existence of two distinct phases, the asymptotic and the transient. The network reaches the asymptotic when the components corresponding to the spectral gap eigenvalue of the weig ...

IEEE2009