Synaptic adaptation stabilizes sequential stimulus representations

Throughout our everyday experience, we are continuously exposed to dynamic and highly complexstreams of multimodal sensory information, which we tend to perceive as a series of discrete andcoherently bounded sub-sequences [1]. While these 'perceptual events' [2] are unfolding, activerepresentations of the relevant stimulus features (such as identity, duration, intensity, etc.) aremaintained and ought to be sufficiently discernible by the distributed responses of specifically tunedneuronal populations, transiently associated into coherent ensembles [3]. Achieving suchdiscriminable responses constitutes a fundamental, primary function of neocortical circuits,necessary for specialized information processing to take place and must rely on their ability to selforganize,resorting to a complex interaction of various activity-dependent modifications of synapticand intrinsic neuronal properties.Such modifications ought to be robust and reliable enough to endow neuronal circuits with theability to dynamically adopt relevant representations of time-varying, sequential events in astimulus- and state-dependent manner, while maintaining the necessary sensitivity to allow globalshifts in representational space when necessary and to learn from and operate upon relevantspatiotemporal dependencies between events. The current state of the circuit, which largelyinfluences the dynamical properties of such representations, is primarily determined by the ongoing,internally generated activity, which sets the ground state from which input-specific transformationsemerge.In this work, we study the properties of biologically realistic networks of LIF neurons, withdifferentially modulated, dynamic excitation and inhibition, combining well established as well asmore recent phenomenological models of synaptic plasticity [4, 5]. We begin by demonstrating thattiming-dependent synaptic plasticity mechanisms have an important role to play in the activemaintenance of an ongoing dynamics characterized by asynchronous and irregular firing, closelyresembling cortical activity in vivo. Incoming stimuli, acting as perturbations of the local balance ofexcitation and inhibition, require fast adaptive responses to prevent the development of unstableactivity regimes, which we objectively link between to a reduced generic computational capacity.Additionally, we demonstrate that the action of plasticity shapes and stabilizes the transient networkstates exhibited in the presence of sequentially presented stimulus events, allowing the developmentof adequate and discernible stimulus representations. The main feature responsible for the increaseddiscriminability of stimulus-driven population responses in plastic networks is shown to be thedecorrelating action of inhibitory plasticity and the consequent maintenance of the asynchronousirregular dynamic regime both for ongoing activity and stimulus-driven responses, whereasexcitatory plasticity is shown to play only a marginal role.References:[1] Schapiro, A. C., Rogers, T. T., Cordova, N. I., Turk-Browne, N. B., and Botvinick, M. M.(2013), Neural representations of events arise from temporal community structure., NatureNeuroscience, 16, 4, 486 92, doi:10.1038/nn.3331[2] Zacks, J. M., Speer, N. K., Swallow, K. M., Braver, T. S., and Reynolds, J. R. (2007), Eventperception: a mind-brain perspective., Psychological Bulletin, 133, 2, 273–93, doi:10.1037/0033-2909.133.2.273[3] Singer, W. (2013), Cortical dynamics revisited., Trends in Cognitive Sciences, 17, 12, 616–26,doi:10.1016/j.tics.2013.09.006[4] Vogels, T. P., Sprekeler, H., Zenke, F., Clopath, C., and Gerstner, W. (2011), Inhibitory plasticitybalances excitation and inhibition in sensory pathways and memory networks., Science, 334, 6062,569–73, doi:10.1126/science.1211095[5] Morrison, A., Diesmann, M., and Gerstner, W. (2008), Phenomenological models of synapticplasticity based on spike timing, Biological Cybernetics, 98, 459–478, doi:10.1007/s00422-008-0233-