Computational implications of biophysical diversity and multiple timescales in neurons and synapses for circuit performance

Abstract

Despite advances in experimental and theoretical neuroscience, we are still trying to identify key biophysical details that are important for characterizing the operation of brain circuits. Biological mechanisms at the level of single neurons and synapses can be combined as ‘building blocks’ to generate circuit function. We focus on the importance of capturing multiple timescales when describing these intrinsic and synaptic components. Whether inherent in the ionic currents, the neuron’s complex morphology, or the neurotransmitter composition of synapses, these multiple timescales prove crucial for capturing the variability and richness of circuit output and enhancing the information-carrying capacity observed across nervous systems.

Degeneracy in hippocampal physiology and plasticity

“…Even with reference to individual neurons, the literature has defined several forms of homeostasis, with popular measures involving neuronal firing rate, cytosolic calcium or excitation-inhibition balance (Gjorgjieva et al, 2016;Hengen et al, 2016;Honnuraiah and Narayanan, 2013;Nelson and Turrigiano, 2008;Siegel et al, 1994;Srikanth and Narayanan, 2015;Turrigiano, 2011;Turrigiano, 1999Turrigiano, , 2008Turrigiano and Nelson, 2004;Yizhar et al, 2011). In addition, despite perpetual changes in afferent activity under in vivo conditions (Buzsaki, 1986(Buzsaki, , 1989(Buzsaki, , 2002(Buzsaki, , 2006Buzsaki et al, 1992;Csicsvari et al, 1999;English et al, 2014;Grosmark et al, 2012;Louie and Wilson, 2001;Mizuseki et al, 2011;Montgomery et al, 2008;Srikanth and Narayanan, 2015;Tononi and Cirelli, 2006;Wilson and McNaughton, 1994;Ylinen et al, 1995a), specific neuronal subtypes maintain distinct functional signatures, say in terms of their excitability or oscillatory or frequency selectivity measurements, that are different from other neuronal subtypes even in the same brain region Shepherd, 2002, 2005;Johnston, 2007, 2008;Pike et al, 2000;Spruston, 2008;Zemankovics et al, 2010).…”

“…Specifically, owing to inherent variability in different constitutive components, the channel conductance values or neuronal intrinsic properties or synaptic strengths could be very different across different neurons despite maintenance of precise calcium homeostasis in neurons or their network (Gjorgjieva et al, 2016;Srikanth and Narayanan, 2015). Finally, calcium and firing rate homeostasis have been shown to be significantly dissociated whereby tremendous variability in channel conductance values, firing rate and pattern of firing have been observed despite efficacious maintenance of calcium homeostasis (O'Leary et al, 2013;Srikanth and Narayanan, 2015).…”

“…2-3). First, there is significant degeneracy in the emergence of neurophysiological properties, where disparate combinations of channels could come together to elicit similar functional properties Narayanan, 2014, 2015;Drion et al, 2015;Foster et al, 1993;Gjorgjieva et al, 2016;Goldman et al, 2001;Grashow et al, 2010;Marder, 2011;Marder and Goaillard, 2006;Marder and Taylor, 2011;Mishra and Narayanan, 2015;Rathour et al, 2016;Narayanan, 2012a, b, 2014;Taylor et al, 2009). Second, the dependence of different physiological properties on distinct peer-reviewed) is the author/funder.…”

“…The advantages of biological variability, degeneracy and complexity have been widely studied and recognized in simple nervous systems (Edelman and Gally, 2001;Foster et al, 1993;Gjorgjieva et al, 2016;Goldman et al, 2001;Katz, 2016;Marder, 2011;Marder and Goaillard, 2006;Marder et al, 2015;Marder and Taylor, 2011;Prinz et al, 2004;Taylor et al, 2009). However, this recognition has been very limited in the mammalian neuroscience literature, where the focus is predominantly on explicitly assigning (or implicitly assuming) unique causal mechanistic relationships between constituent components and emergent functions.…”

“…1B) through interactions among disparate parametric combinations in a lower scale (Edelman and Gally, 2001;Foster et al, 1993;Gjorgjieva et al, 2016;Goldman et al, 2001;Marder, 2011;Marder and Goaillard, 2006;Marder et al, 2015;Marder and Taylor, 2011; parameters (at the molecular scale) to achieve activity homeostasis (Gjorgjieva et al, 2016;Hengen et al, 2016;Nelson and Turrigiano, 2008;Turrigiano, 2011;Turrigiano, 1999Turrigiano, , 2008Turrigiano and Nelson, 2004). Thus, under the degeneracy framework, different uncorrelated clusters in the lower-scale parametric space could result in similar, if not identical, functional outcomes in the higher-scale measurement space, thereby suggesting a many-to-one relationship between the lower-and higher-scale manifolds (Edelman and Gally, 2001;Jazayeri and Afraz, 2017;Krakauer et al, 2017).…”