Plasticity, Learning, and Complexity in Spiking Networks

Abstract

Complexity is widespread in neuronal spike trains and propagation of spike activity, in that variations in measurements of neural activity are irregular, heterogeneous, non-stationary, transient, and scale-free. There are numerous possible reasons for this complexity, and numerous possible consequences for neural and behavioral function. The present review is focused on relationships among neural plasticity, learning, and complex spike dynamics in animal nervous systems, including those of humans. The literature on complex spike dynamics and mechanisms of synaptic plasticity are reviewed for the purpose of considering the roles that each might play for the other. That is, the roles of complex spike dynamics in learning and regulatory functions are considered, as well as the roles of learning and regulatory functions in generating complex spike dynamics. Experimental and computational studies from a range of disciplines and perspectives are discussed, and it is concluded that cognitive science and neuroscience have much to gain from investigating the adaptive aspects of complex spike dynamics for neural and cognitive function.

Identification and Assessment of Systematic Measurement Error on Electrophysiological Recordings of Neural Cell Cultures

“…4) Create PCA representations (similar to Figure 4) towards identifying more subtle patterns of electrode defectiveness. This review process is critical prior to applying data analysis algorithms [27]- [31]. However, we go beyond the identification of two forms of electrode defectiveness; we also demonstrate possibilities for post-analytic review.…”

“…This review process is critical prior to applying data analysis algorithms [27]–[31]. However, we go beyond the identification of two forms of electrode defectiveness; we also demonstrate possibilities for post-analytic review.…”

“…To quote the first sentence of Kello et al: Complexity is widespread in neuronal spike trains and propagation of spike activity [31]. We presented a protocol towards ensuring that this complexity is not further muddled by systematic measurement error.…”

Van Orden Dynamics

“…In this essay, I trace my arc to its first connection with Guy and the shared path we took for some time thereafter. I end with a connectionist-like model of complex dynamics that grew from our time together and is beginning to come full circle (Kello, 2013;Kello, Rodny, Warlaumont, & Noelle, 2012).…”

“…Now, when I think about the model, I think about bringing this arc full circle. I'm working to integrate a simple mechanism of reinforcement learning with critical branching so that branching dynamics may be selectively reinforced (Kello et al, 2012). One envisioned outcome of this work is a connectionist-like modeling framework that enables researchers to simulate the soft assembly of specific sensorimotor and cognitive functions.…”