Are the spikes emitted by a semiconductor laser with feedback similar to neuronal spikes?

In semiconductor lasers optical feedback induces a wide range of dynamical regimes. In this talk I will focus on the low frequency fluctuations (LFFs) regime, in which the laser emits optical spikes that resemble the spikes of biological neurons. In this regime, semiconductor lasers have potential to act as ultra-fast photonic neurons, which can be building blocks of novel information processing systems [1], inspired in the way biological neurons process information. In order to use the laser as a basic, neuro-inspired information processing unit, we first need to understand how an input signal can be encoded in the output sequence of optical spikes [2-4], and then compare with neuronal encoding. Single biological neurons may encode information in the spike rate (“rate coding”) or in the relative timing of the spikes (“temporal coding”). In a recent work [5] we have analyzed the well-known FitzHugh-Nagumo (FHN) single-neuron model and we have shown that the interplay of noise and a weak (subthreshold) periodic input signal induced temporal ordering in the timing of the spikes (i.e., induced temporal correlations among several inter-spike-intervals, ISIs), in the form of more/less frequently expressed patterns, which depend of the period of the input signal. Our results suggested that single neurons in noisy environments encode information about the period of a subthreshold periodic input in the relative timing of the spikes.

In this talk I will present an experimental study of the laser dynamics in the LFF regime under weak pump current sinusoidal modulation and I will compare the statistical properties of optical spikes with those of synthetic neuronal spikes [5]. In spite of the fact that the laser with feedback is a high dimensional system (due to the feedback delay time) while the FHN model is a low dimensional system, in general a good qualitative agreement is found; however some relevant differences will also be discussed.

[1] P. R. Prucnal, B. J. Shastri, T. F. de Lima, M. A. Nahmias, and A. N. Tait, “Recent progress in semiconductor excitable lasers for photonic spike processing”, Advances in Optics and Photonics 8, 228 (2016).

[2] T. Sorrentino, C. Quintero-Quiroz, A. Aragoneses, M. C. Torrent, and C. Masoller, “The effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback”, Optics Express 23, 5571 (2015).

[3] C. Quintero-Quiroz, J. Tiana-Alsina, J. Roma, M. C. Torrent, and C. Masoller, “Characterizing how complex optical signals emerge from noisy intensity fluctuations”, Sci. Rep. 6 37510 (2016).

[4] A. Aragoneses, S. Perrone, T. Sorrentino, M. C. Torrent and C. Masoller, "Unveiling the complex organization of recurrent patterns in spiking dynamical systems", Sci. Rep. 4, 4696 (2014).

[5] J. A. Reinoso, M. C. Torrent and C. Masoller, “Emergence of spike correlations in periodically forced excitable systems”, Phys. Rev. E. 94, 032218 (2016).