Dynamics of Excitability over Extended Timescales in Cultured Cortical Neurons

Gal, A.; Eytan, Danny; Wallach, Avner; Sandler, Maya; Schiller, Jackie; Marom, Shimon

doi:10.1523/jneurosci.4859-10.2010

Cited by 98 publications

(238 citation statements)

References 81 publications

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“…The hippocampal cultures were kept in growth medium that was slowly circulated by an ultraslow perfusion system to improve the longterm preparation vitality (Minerbi et al, 2009). Images were collected at a rate of one image every 5 min for durations of Ն3 h. To minimize the effects of spontaneous activity, the glutamate receptor blockers AP-5 (50 M) and CNQX (10 M) were added to the external solution (Wagenaar et al, 2006;Gal et al, 2010).…”

Section: Following Long-term Changes In the Sv Content Of Individual mentioning

confidence: 99%

Use Dependence of Presynaptic Tenacity

Fisher-Lavie

Zeidan²,

Stern³

et al. 2011

J. Neurosci.

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Recent studies indicate that synaptic vesicles (SVs) are continuously interchanged among nearby synapses at very significant rates. These dynamics and the lack of obvious barriers confining synaptic vesicles to specific synapses would seem to challenge the ability of synapses to maintain a constant amount of synaptic vesicles over prolonged time scales. Moreover, the extensive mobilization of synaptic vesicles associated with presynaptic activity might be expected to intensify this challenge. Here we examined the ability of individual presynaptic boutons of rat hippocampal neurons to maintain their synaptic vesicle content, and the degree to which this ability is affected by continuous activity. We found that the synaptic vesicle content of individual boutons belonging to the same axons gradually changed over several hours, and that these changes occurred independently of activity. Intermittent stimulation for 1 h accelerated rates of vesicle pool size change. Interestingly, however, following stimulation cessation, vesicle pool size change rates gradually converged with basal change rates. Over similar time scales, active zones (AZs) exhibited substantial remodeling; yet, unlike synaptic vesicles, AZ remodeling was not affected by the stimulation paradigms used here. These findings indicate that enhanced activity levels can increase synaptic vesicle redistribution among nearby synapses, but also highlight the presence of forces that act to restore particular set points in terms of SV contents, and support a role for active zones in preserving such set points. These findings also indicate, however, that neither AZ size nor SV content set points are particularly stable, questioning the long-term tenacity of presynaptic specializations.

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Section: Following Long-term Changes In the Sv Content Of Individual mentioning

confidence: 99%

Use Dependence of Presynaptic Tenacity

Fisher-Lavie

Zeidan²,

Stern³

et al. 2011

J. Neurosci.

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“…Whereas the reproducible responses of directly stimulated individual neurons consist of precisely timed single action potentials (APs) or trains of APs under specific conditions (Bryant and Segundo 1976;Mainen and Sejnowski 1995; but see Gal et al 2010), stimulation in recurrent networks elicits multiphasic responses. These typically consist of: 1) a fast excitatory component of precise and reliable firing by antidromic or monosynaptic activation of local neurons with delays between 2 and 20 ms, 2) a transition phase with low activity thought to be mediated by inhibitory neurons, and 3) a delayed excitatory component driven by recurrent polysynaptic activation (Butovas and Schwarz 2003;Eccles et al 1974;Fanselow and Nicolelis 1999;Rowland and Jaeger 2008;Wagenaar et al 2004).…”

mentioning

confidence: 99%

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

Weihberger

Okujeni

Mikkonen

et al. 2013

Journal of Neurophysiology

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Variable responses of neuronal networks to repeated sensory or electrical stimuli reflect the interaction of the stimulus' response with ongoing activity in the brain and its modulation by adaptive mechanisms, such as cognitive context, network state, or cellular excitability and synaptic transmission capability. Here, we focus on reliability, length, delays, and variability of evoked responses with respect to their spatial distribution, interaction with spontaneous activity in the networks, and the contribution of GABAergic inhibition. We identified network-intrinsic principles that underlie the formation and modulation of spontaneous activity and stimulus-response relations with the use of state-dependent stimulation in generic neuronal networks in vitro. The duration of spontaneously recurring network-wide bursts of spikes was best predicted by the length of the preceding interval. Length, delay, and structure of responses to identical stimuli systematically depended on stimulus timing and distance to the stimulation site, which were described by a set of simple functions of spontaneous activity. Response length at proximal recording sites increased with the duration of prestimulus inactivity and was best described by a saturation function y(t) ϭ A(1 Ϫ e Ϫ␣t ). Concomitantly, the delays of polysynaptic late responses at distant sites followed an exponential decay y(t) ϭ Be Ϫ␤t ϩ C. In addition, the speed of propagation was determined by the overall state of the network at the moment of stimulation. Disinhibition increased the number of spikes/network burst and interburst interval length at unchanged gross firing rate, whereas the response modulation by the duration of prestimulus inactivity was preserved. Our data suggest a process of network depression during bursts and subsequent recovery that limit evoked responses following distinct rules. We discuss shortterm synaptic depression due to depletion of neurotransmitter vesicles as an underlying mechanism. The seemingly unreliable patterns of spontaneous activity and stimulus-response relations thus follow a predictable structure determined by the interdependencies of network structures and activity states.

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“…This baseline latency was shown to be a highly reliable, intrinsic measure which is unaffected by synaptic blockade (see Fig. 1 in Gal et al 2010). The time window encompasses the dynamic range of evoked response latency in these neurons.…”

Section: Response Clampmentioning

confidence: 94%

“…This procedure also minimizes the risk of detecting spikes from multiple neurons. To verify this, spikes shapes were observed throughout the experiment (for further discussion on single cell isolation in these cultures, see Gal et al 2010).…”

Section: Response Clampmentioning

confidence: 99%

Interactions between network synchrony and the dynamics of neuronal threshold

Wallach

Marom

2012

Journal of Neurophysiology

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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...

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Dynamics of Excitability over Extended Timescales in Cultured Cortical Neurons

Cited by 98 publications

References 81 publications

Use Dependence of Presynaptic Tenacity

Use Dependence of Presynaptic Tenacity

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

Interactions between network synchrony and the dynamics of neuronal threshold

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