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Do the dynamics, discussed earlier in the context of spontaneous activity, play an active role in neural computations? We should note that fluctuations appear when the network system is in a transitional regime: the perceptual system is sensitive to small fluctuations and thus is flexible; at the same time, the system preserves a memory of the past stimuli in the long time correlation tails.
In order to test this hypothesis, we measured the model's response characteristics to localized input modulations, and to spatial frequency (sinusoidal gratings) modulations , which were applied transiently to the network. Despite the fact that the amplitude of the modulation was small relative to the background we find that the network has a strong amplifying response with a relatively fast onset and a slow decay. The former is due to the rearranging of the activity pattern in relation to the stimuli, while the slow decay is due to the slow diffusion. In particular we find that the regime accomplishes a trade-off between signal amplification and memory; very fluid activity patterns (low inhibition) have fast and strong amplification response but no memory, and the opposite occurs at very rigid activity patterns (high inhibition). Moreover, when stimulating with spatial gratings, we find that the stronger and longer lasting response occurs at a specific spatial frequency (determined by the intra-cluster distance). We also find that a more complex stimulation (at two localized spots), has a similar effect: a stronger and longer-lasting effect when the inter-stimulus distance is compatible with the preferred characteristic frequency of the network. Thus the network response depends not only on the stimuli but also on spatial relationships between stimuli (Fig. 15).
Figure 15: The stimulus consists of raising the external input rate by 12 % of over a circular region of radius 3. The response shown above is the mean spike count per msec within a region of radius 5, averaged over trials. The three traces represent different strengths of inhibition (, respectively). The inset displays the response to two successive stimuli at the same location.
Finally, we find that a succession of two stimuli separated by 100 msec at the same location results in a `priming effect' due to the memory inherent in the system: the second stimulus elicits a faster and stronger response. Using signals for neural computation is an intriguing and promising possibility deserving further research .