Exploring the Phase-Locking Mechanisms Yielding Delayed and Anticipated Synchronization in Neuronal Circuits

Synchronization is one of the brain mechanisms allowing the coordination of neuronal activity required in many cognitive tasks. Anticipated Synchronization (AS) is a specific type of out-of-phase synchronization that occurs when two systems are unidirectionally coupled and, consequently, the information is transmitted from the sender to the receiver, but the receiver leads the sender in time. It has been shown that the primate cortex could operate in a regime of AS as part of normal neurocognitive function. However it is still unclear what is the mechanism that gives rise to anticipated synchronization in neuronal motifs. Here, we investigate the synchronization properties of cortical motifs on multiple scales and show that the internal dynamics of the receiver, which is related to its free running frequency in the uncoupled situation, is the main ingredient for AS to occur. For biologically plausible parameters, including excitation/inhibition balance, we found that the phase difference between the sender and the receiver decreases when the free running frequency of the receiver increases. As a consequence, the system switches from the usual delayed synchronization (DS) regime to an AS regime. We show that at three different scales, neuronal microcircuits, spiking neuronal populations and neural mass models, both the inhibitory loop and the external current acting on the receiver mediate the DS-AS transition for the sender-receiver configuration by changing the free running frequency of the receiver. Therefore, we propose that a faster internal dynamics of the receiver system is the main mechanism underlying anticipated synchronization in brain circuits.

[1]  Xin Wang,et al.  Statistical Wiring of Thalamic Receptive Fields Optimizes Spatial Sampling of the Retinal Image , 2014, Neuron.

[2]  Olaf Sporns,et al.  Mechanisms of Zero-Lag Synchronization in Cortical Motifs , 2013, PLoS Comput. Biol..

[3]  Ned J Corron,et al.  Lag and anticipating synchronization without time-delay coupling. , 2005, Chaos.

[4]  Rodrigo F. Salazar,et al.  Content-Specific Fronto-Parietal Synchronization During Visual Working Memory , 2012, Science.

[5]  Henning U. Voss,et al.  Erratum: Anticipating chaotic synchronization [Phys. Rev. E 61, 5115 (2000)] , 2001 .

[6]  Claudio R Mirasso,et al.  Anticipation via canards in excitable systems. , 2019, Chaos.

[7]  Raúl Toral,et al.  Predict-prevent control method for perturbed excitable systems. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Alessandro Barardi,et al.  Phase-Coherence Transitions and Communication in the Gamma Range between Delay-Coupled Neuronal Populations , 2014, PLoS Comput. Biol..

[9]  D. Zanette,et al.  Anticipated synchronization in coupled chaotic maps with delays , 2001, nlin/0104061.

[10]  K. Pyragas,et al.  Anticipating spike synchronization in nonidentical chaotic neurons , 2013, Nonlinear Dynamics.

[11]  Peter Hänggi,et al.  Anticipated synchronization in coupled inertial ratchets with time-delayed feedback: a numerical study. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Albert Compte,et al.  Integrated Mechanisms of Anticipation and Rate-of-Change Computations in Cortical Circuits , 2007, PLoS Comput. Biol..

[13]  G. Orban,et al.  Velocity selectivity in the cat visual system. I. Responses of LGN cells to moving bar stimuli: a comparison with cortical areas 17 and 18. , 1985, Journal of neurophysiology.

[14]  Gregor Schöner,et al.  Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex , 2004, The Journal of physiology.

[15]  J. Bullier,et al.  Visual latencies in areas V1 and V2 of the macaque monkey , 1995, Visual Neuroscience.

[16]  K. Pyragas,et al.  Anticipating chaotic synchronization via act-and-wait coupling , 2015 .

[17]  Henning U Voss,et al.  Signal prediction by anticipatory relaxation dynamics. , 2015, Physical review. E.

[18]  Voss,et al.  Anticipating chaotic synchronization , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[19]  Emilio Hernández-García,et al.  Anticipating the dynamics of chaotic maps , 2001, nlin/0111011.

[20]  Renormalized time scale for anticipating and lagging synchronization. , 2016, Physical review. E.

[21]  Michael T. Turvey,et al.  On strong anticipation , 2010, Cognitive Systems Research.

[22]  H U Voss,et al.  Dynamic long-term anticipation of chaotic states. , 2001, Physical review letters.

[23]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[24]  E. Conway,et al.  Potassium accumulation in muscle and associated changes 1 , 1941 .

[25]  Eugene M. Izhikevich,et al.  Simple model of spiking neurons , 2003, IEEE Trans. Neural Networks.

[26]  E. M. Shahverdiev,et al.  Experimental demonstration of anticipating synchronization in chaotic semiconductor lasers with optical feedback. , 2001, Physical review letters.

[27]  Jean Daunizeau,et al.  The Social Bayesian Brain: Does Mentalizing Make a Difference When We Learn? , 2014, PLoS Comput. Biol..

[28]  H. Voss A delayed-feedback filter with negative group delay. , 2018, Chaos.

[29]  Claudio R. Mirasso,et al.  Anticipated synchronization in neuronal circuits unveiled by a phase-response-curve analysis. , 2017, Physical review. E.

[30]  Claudio R Mirasso,et al.  Anticipated synchronization in a biologically plausible model of neuronal motifs. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  Alexander N. Pisarchik,et al.  Synchronization with an arbitrary phase shift in a pair of synaptically coupled neural oscillators , 2014 .

[32]  A. Pérez-Villalba Rhythms of the Brain, G. Buzsáki. Oxford University Press, Madison Avenue, New York (2006), Price: GB £42.00, p. 448, ISBN: 0-19-530106-4 , 2008 .

[33]  Nigel Stepp,et al.  Anticipation in Manual Tracking With Multiple Delays , 2017, Journal of experimental psychology. Human perception and performance.

[34]  Albert Compte,et al.  Selective detection of abrupt input changes by integration of spike-frequency adaptation and synaptic depression in a computational network model , 2006, Journal of Physiology-Paris.

[35]  Gabriel B. Mindlin,et al.  Anticipated Synchronization and Zero-Lag Phases in Population Neural Models , 2018, Int. J. Bifurc. Chaos.

[36]  Leonardo L. Gollo,et al.  Modeling positive Granger causality and negative phase lag between cortical areas , 2014, NeuroImage.

[37]  J. M. Sausedo-Solorio,et al.  Synchronization of map-based neurons with memory and synaptic delay , 2014 .

[38]  P. Fries A mechanism for cognitive dynamics: neuronal communication through neuronal coherence , 2005, Trends in Cognitive Sciences.

[39]  S. Bressler,et al.  Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[40]  K. Gegenfurtner,et al.  Neuronal Processing Delays Are Compensated in the Sensorimotor Branch of the Visual System , 2003, Current Biology.

[41]  Claudio R Mirasso,et al.  Anticipating the response of excitable systems driven by random forcing. , 2002, Physical review letters.

[42]  J M Liu,et al.  Experimental verification of anticipated and retarded synchronization in chaotic semiconductor lasers. , 2003, Physical review letters.

[43]  Kestutis Pyragas,et al.  Anticipatory synchronization via low-dimensional filters , 2017 .