Spikes: exploring the neural code
Spikes: exploring the neural code
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Integrate-and-fire neurons driven by correlated stochastic input
Neural Computation
Patterns of Synchrony in Neural Networks with Spike Adaptation
Neural Computation
Dynamics of Strongly Coupled Spiking Neurons
Neural Computation
Simultaneous Rate-Synchrony Codes in Populations of Spiking Neurons
Neural Computation
Stimulus Competition by Inhibitory Interference
Neural Computation
Generation of Synthetic Spike Trains with Defined Pairwise Correlations
Neural Computation
On similarity measures for spike trains
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Oscillatory synchronization model of attention to moving objects
Neural Networks
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The synchrony of neurons in extrastriate visual cortex is modulated by selective attention even when there are only small changes in firing rate (Fries, Reynolds, Rorie, & Desimone, 2001). We used Hodgkin-Huxley type models of cortical neurons to investigate the mechanism by which the degree of synchrony can be modulated independently of changes in firing rates. The synchrony of local networks of model cortical interneurons interacting through GABAA synapses was modulated on a fast timescale by selectively activating a fraction of the interneurons. The activated interneurons became rapidly synchronized and suppressed the activity of the other neurons in the network but only if the network was in a restricted range of balanced synaptic background activity. During stronger background activity, the network did not synchronize, and for weaker background activity, the network synchronized but did not return to an asynchronous state after synchronizing. The inhibitory output of the network blocked the activity of pyramidal neurons during asynchronous network activity, and during synchronous network activity, it enhanced the impact of the stimulus-related activity of pyramidal cells on receiving cortical areas (Salinas & Sejnowski, 2001). Synchrony by competition provides a mechanism for controlling synchrony with minor alterations in rate, which could be useful for information processing. Because traditional methods such as cross-correlation and the spike field coherence require several hundred milliseconds of recordings and cannot measure rapid changes in the degree of synchrony, we introduced a new method to detect rapid changes in the degree of coincidence and precision of spike timing.