Interactions between network synchrony and the dynamics of neuronal threshold

Abstract

Wallach A, Marom S. Interactions between network synchrony and the dynamics of neuronal threshold. J Neurophysiol 107: 2926 -2936, 2012. First published March 7, 2012 doi:10.1152/jn.00876.2011.-Synchronous activity impacts on a range of functional brain capacities in health and disease. To address the interrelations between cellular level activity and network-wide synchronous events, we implemented in vitro a recently introduced technique, the response clamp, which enables online monitoring of single neuron threshold dynamics while ongoing network synchronous activity continues uninterrupted. We show that the occurrence of a synchronous network event causes a significant biphasic change in the single neuron threshold. These threshold dynamics are correlated across the neurons constituting the network and are entailed by the input to the neurons rather than by their own spiking (i.e., output) activity. The magnitude of network activity during a synchronous event is correlated with the threshold state of individual neurons at the event's onset. Recovery from the impact of a given synchronous event on the neuronal threshold lasts several seconds and seems to be a key determinant of the time to the next spontaneously occurring synchronous event. Moreover, the neuronal threshold is shown to be correlated with the excitability dynamics of the entire network. We conclude that the relations between the two levels (network activity and the single neuron threshold) should be thought of in terms that emphasize their interactive nature. neuron; response clamp; burst SYNCHRONY IS A MOST BASIC mode of activity in the cortex, believed to be critical for a range of functional brain capacities (Singer 1999). In most cases, regardless of the complex topology of connectivity (e.g., Eytan and Marom 2006;Bonifazi et al. 2009), the cortical synchronous event is considered a collective population phenomenon, emerging from interactions among the elements comprising the network (e.g., Abeles 1991; Beggs and Plenz 2003;Eckmann et al. 2010), rather than being driven by a uniquely identified class of pacing neurons. To address the generation of network-wide synchronous events, as well as the factors constraining the frequency of their occurrence, simultaneous monitoring of relevant state variables at both the network and cellular levels is wanted.While an ultimate design aiming at such multilevel monitoring would involve measurement and stimulation in the intact brain, obvious issues of experimental stability and control make the choice of large-scale networks of cortical neurons developing in vitro an attractive alternative in this context (Marom and Shahaf 2002). These networks are readily accessible to well-controlled long-term experiments and exhibit the dynamics of synchrony that is comparable in some key features to synchrony observed in vivo Ham et al. 2008;Jimbo et al. 1993;Maeda et al. 1995;Stegenga et al. 2008;Van Pelt et al. 2004;Wagenaar et al. 2006).Previous experiments that attempted simultaneous monitoring of both single ne...

Quantitative examination of stimulus-response relations in cortical networks in vitro

“…Furthermore, compared with cellular excitability modulation, a model of activity-dependent synaptic depression better replicated the dynamics of oscillatory discharges and increasing response lengths with longer duration of preceding inactivity in the chick spinal cord (Tabak et al 2000(Tabak et al , 2001. A close link between single-neuron threshold dynamics and magnitude of synchronized network activity has been demonstrated recently in cortical neuronal networks in vitro too (Wallach and Marom 2012). In addition, spikefrequency adaptation in single neurons during high bursting activity could further affect stimulus-response dynamics.…”

Synaptic dynamics contribute to long-term single neuron response fluctuations

“…Hence, they might interfere with our capacity to interpret the impacts of stimulation on response dynamics (Wallach and Marom, 2012; Weihberger et al, 2013). Network spikes may be suppressed by pharmacological blockage of NMDA channels in cultured cortical networks (Robinson et al, 1993; Jimbo et al, 2000; Bonzano et al, 2006).…”

Adaptation to prolonged neuromodulation in cortical cultures: an invariable return to network synchrony

“…The system we used for this purpose was based on the 'neuronal response clamp' developed by Marom and colleagues [76][77][78][79]. This system was composed of a 'bare-bones' personal computer running a real time application ( Figure 1a (Figure 4a).…”