Prof. Cristina Masoller lab:
research line on neuronal models, excitability and nonlinear dynamics
In nonlinear systems the presence of noise often
facilitates the detection and transmission of weak signals. Sensory neurons
exploit noise for encoding and transmitting external signals in sequences of
spikes. Although the statistical properties of the spike sequences have been
extensively investigated, the way in which neurons encode information remains
not fully understood. Among other mechanisms, neurons can encode information
in the spike rate (“rate coding”) or in the timing of the spikes (“temporal
coding”). We are interested in studying temporal correlations in the timing
of neuronal spikes. We use neuronal models to analyze
spike correlations when a neuron perceives a weak signal that is covered by
background noise. We are also interested in the comparison of the
statistical properties of neuronal ISI sequences and those of the
experimentally recorded optical
spikes emitted by a semiconductor laser, which resemble neuronal spikes.
Establishing a connection between these different dynamical systems can offer
new perspectives in both, photonics and neuroscience. Laser-based photonic neurons
can provide a novel, inexpensive and controllable experimental set up for
improving our understanding of neuronal activity. On the other hand,
laser-based photonic neurons can be building blocks of neuro-inspired,
ultra-fast optical computing devices. |
Neuronal spikes simulated with the FitzHugh-Nagumo model. Optical spikes recorded in the semiconductor laser
lab in Terrassa. |
Selected publications What
models and tools can contribute to a better understanding of brain activity? M. Goodfellow, R. G. Andrzejak,
C. Masoller, K. Lehnertz,
Frontiers in Network Physiology 2, 907995 (2022). Symbolic
analysis of bursting dynamical regimes of Rulkov
neural networks R. C. Budzinski,
S. R. Lopes, C. Masoller, Neurocomputing
441, 44 (2021). Arxiv: 2005.03430 Neuronal
coupling benefits the encoding of weak periodic signals in symbolic spike
patterns M. Masoliver and
C. Masoller, Commun. Nonlinear Sci. Numer. Simulat. 88, 105023
(2020). Arxiv:
1905.01933 Comparing
the dynamics of periodically forced lasers and neurons J. Tiana-Alsina, C. Quintero-Quiroz, C. Masoller,
New J. of Phys 21, 103039 (2019). Subthreshold signal
encoding in coupled FitzHugh-Nagumo neurons M. Masoliver and
C. Masoller, Scientific Reports 8, 8276 (2018). |
|
Funding ICREA ACADEMIA (2021-2025) Agencia Estatal de Investigación, PID2021-123994NB-C21
(2022-2024) |
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