Order-Based Representation in Random Networks of Cortical Neurons \ Shahaf, Eytan, Gal, Kermany, Lyakhov, Zrenner, Marom \ PLOS Computational Biology (2008): We show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order.
Dynamics and Effective Topology Underlying Synchronization in Networks of Cortical Neurons \ Eytan, Marom \ J. Neurosci. (2006): We characterize the process underlying the timescale of synchronization, its relationship to the effective topology of connectivity within an assembly, and its impact on propagation of activity within and between assemblies. We show that the basic mode of assembly activation, “network spike,” is a threshold-governed phenomenon, following the logistics of neuronal recruitment in an effectively scale-free connected network.
Learning in Networks of Cortical Neurons \ Shahaf, Marom \ J. Neurosci. (2001): The results presented here demonstrate selective learning in a network of real cortical neurons, without the involvement of a neural rewarding entity. The connectivity can be modulated by external focal stimulation in an activity-dependent manner. Most importantly, the networks explore the space of possible responses and stabilize at configurations that remove the stimuli.
On the precarious path of reverse neuro-engineering \ Marom, Meir, Braun, Gal, Kermany, Eytan \ Frontiers in Computational Neuroscience (2009): In this perspective we demonstrate that application of reverse engineering to the study of the design principle of a functional neuro-system with a known mechanism, may result in a perfectly valid but wrong induction of the system’s design principle. If in the very simple setup we bring here it is difficult to induce a design principle, what are our chances of exposing biological design principles when more realistic conditions are examined? [robot movie and description]
Selective Adaptation in Networks of Cortical Neurons \ Eytan, Brenner, Marom \ J. Neurosci. (2003): A key property of neural systems is their ability to adapt selectively to stimuli with different features. Using multisite electrical recordings from networks of cortical neurons developing ex vivo, we show that neurons adapt selectively to different stimuli invading the network. We focus on selective adaptation to frequent and rare stimuli; networks were stimulated at two sites with two different stimulus frequencies. When both stimuli were presented within the same period, neurons in the network attenuated their responsiveness to the more frequent input, whereas their responsiveness to the rarely delivered stimuli showed a marked average increase.
Dopamine-Induced Dispersion of Correlations Between Action Potentials in Networks of Cortical Neurons \ Eytan, Minerbi, Ziv, Marom \ J. Neurophysiol. (2004): The neuro- modulatory effects of dopamine at the synaptic and cellular levels are very rich, but it is difficult to extrapolate from these elementary levels what their effect might be at the behaviorally relevant level of neuronal ensembles. Using multi-site recordings from networks of cortical neurons developing ex vivo, we studied the effects of dopa- mine on connectivity within neuronal ensembles. We found that dopamine disperses correlations between individual neuronal activities while preserving the global distribution of correlations at the network level.