Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains

Experimental studies have observed Long Term synaptic Potentiation (LTP) when a presynaptic neuron fires shortly before a postsynaptic neuron, and Long Term Depression (LTD) when the presynaptic neuron fires shortly after, a phenomenon known as Spike Timing Dependant Plasticity (STDP). When a neuron is presented successively with discrete volleys of input spikes STDP has been shown to learn ‘early spike patterns’, that is to concentrate synaptic weights on afferents that consistently fire early, with the result that the postsynaptic spike latency decreases, until it reaches a minimal and stable value. Here, we show that these results still stand in a continuous regime where afferents fire continuously with a constant population rate. As such, STDP is able to solve a very difficult computational problem: to localize a repeating spatio-temporal spike pattern embedded in equally dense ‘distractor’ spike trains. STDP thus enables some form of temporal coding, even in the absence of an explicit time reference. Given that the mechanism exposed here is simple and cheap it is hard to believe that the brain did not evolve to use it

Codage par latence et STDP : des clés pour comprendre le traitement visuel rapide

In the rapid visual processing theory, visual information is encoded in the firing latency of the cells, a scheme that readily explains its speed. In the present thesis, we show that, within this theory, spike timing-dependent plasticity (STDP) can explain the development of neural selectivities that will produce fast and selective responses. A neuron will indeed systematically tune to the earliest spikes through STDP, when the firing patterns elicited by a stimulus yield some form of temporal structure. This law leads, at the population level, to the emergence of representations inspired by the ventral stream, when the system is presented with natural images. Besides we also show, through a psychophysical experiment, that rapid visual processing not only is accurate but that it also yields a quasi-invariance to stimulus rotation.La théorie du traitement visuel rapide se base sur un codage par latence de l'information visuelle, et explique ainsi sa rapidité. Nous démontrons dans cette thèse qu'un mécanisme de plasticité synaptique dépendant des temps de décharges, la STDP, permet, au sein de cette théorie, d'expliquer la formation de sélectivités neuronales à même de produire des réponses rapides et sélectives. Par STDP, un neurone va concentrer ses poids synaptiques sur les entrées les plus précoces, une loi qui se traduit au niveau des populations par l'émergence de représentations inspirées de la voie ventrale, lorsque le système est exposé à des images naturelles.Nous montrons de plus, par une expérience de psychophysique, que le traitement visuel rapide est non seulement précis mais qu'il présente aussi une quasi-invariance à la rotation des images

Codage par latence et STDP (des stratégies temporelles pour expliquer le traitement visuel rapide)

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Spike times make sense

Many behavioral responses are completed too quickly for the underlying sensory processes to rely on estimation of neural firing rates over extended time windows. Theoretically, first-spike times could underlie such rapid responses, but direct evidence has been lacking. Such evidence has now been uncovered in the human somatosensory system. We discuss these findings and their potential generalization to other sensory modalities, and we consider some future challenges for the neuroscientific community

Animals roll around the clock: the rotation invariance of ultrarapid visual processing.

International audienceThe processing required to categorize faces and animals is not only rapid but also remarkably resistant to inversion. It has been suggested that this sort of categorization performance could be achieved using the global distribution of orientations within the image, which interestingly is unchanged by inversion. Here, we presented subjects with two natural scenes at 16 different orientations that were simultaneously flashed in the left and right hemifield and we asked them to make a saccade to the side containing an animal. We report that human performance is surprisingly rotation invariant as reaction times were similar and accuracy remarkably stable across orientations. The results imply that this form of rapid object detection could not depend on the global distribution of orientations within the image. One alternative is that subjects are instead using local combinations of features that are diagnostic for the presence of an animal

Spatio-temporal spike pattern.

<p>Here we show in red a repeating 50 ms long pattern that concerns 50 afferents among 100. The bottom panel plots the population-averaged firing rates over 10 ms time bins (we chose 10 ms because it is the membrane time constant of the neuron used later in the simulations), and demonstrates that nothing characterizes the periods when the pattern is present. The right panel plots the individual firing rates averaged over the whole period. Neurons involved in the pattern are shown in red. Again, nothing characterizes them in terms of firing rates. Detecting the pattern thus requires taking the spike times into account.</p

Resistance to degradations (100 trials).

<p>(a) Percentage of successful trials as a function of the pattern frequency (pattern duration/the total duration, given a fixed pattern length of 50 ms). The pattern needs to be consistently present, at least at the beginning, for the STDP to start the learning process. (b) Percentage of successful trials as a function of jitter. For jitter greater than 3 ms spike coincidences are lost and the STDP weight updates are inaccurate, so the learning is impaired (c) Percentage of successful trials as a function of the proportion of afferents involved in the pattern. Performance is good if this proportion is above 1/3 (d) Percentage of successful trials as a function of the initial weights. With a high value the neuron can handle more discharges outside the pattern. (e) Percentage of successful trials as a function of the proportion of spikes deleted. With a 10% deletion the pattern was correctly learnt in 82% of the cases.</p

Neurons tune to the earliest spikes through STDP.

International audienceSpike timing-dependent plasticity (STDP) is a learning rule that modifies the strength of a neuron's synapses as a function of the precise temporal relations between input and output spikes. In many brains areas, temporal aspects of spike trains have been found to be highly reproducible. How will STDP affect a neuron's behavior when it is repeatedly presented with the same input spike pattern? We show in this theoretical study that repeated inputs systematically lead to a shaping of the neuron's selectivity, emphasizing its very first input spikes, while steadily decreasing the postsynaptic response latency. This was obtained under various conditions of background noise, and even under conditions where spiking latencies and firing rates, or synchrony, provided conflicting informations. The key role of first spikes demonstrated here provides further support for models using a single wave of spikes to implement rapid neural processing