Pharmacology of currents underlying the different firing patterns of spinal sensory neurons and interneurons identified in vivo using multivariate analysis

Abstract

The operation of neuronal networks depends on the firing patterns of the network's neurons. When sustained current is injected, some neurons in the central nervous system fire a single action potential and others fire repetitively. For example, in Xenopus laevis tadpoles, primary-sensory Rohon-Beard (RB) neurons fired a single action potential in response to 300-ms rheobase current injections, whereas dorsolateral (DL) interneurons fired repetitively at 10-20 Hz. To investigate the basis for these differences in vivo, we examined drug-induced changes in the firing patterns of Xenopus spinal neurons using whole cell current-clamp recordings. Neuron types were initially separated through cluster analysis, and we compared results produced using different clustering algorithms. We used these results to develop a predictive function to classify subsequently recorded neurons. The potassium channel blocker tetraethylammonium (TEA) converted single-firing RB neurons to low-frequency repetitive firing but reduced the firing frequency of repetitive-firing DL interneurons. Firing frequency in DL interneurons was also reduced by the potassium channel blockers 4-aminopyridine (4-AP), catechol, and margatoxin; 4-AP had the greatest effect. The calcium channel blockers amiloride and nimodipine had few effects on firing in either neuron type but reduced action potential duration in DL interneurons. Muscarine, which blocks M-currents, did not affect RB neurons but reduced firing frequency in DL interneurons. These results suggest that potassium currents may control neuron firing patterns: a TEA-sensitive current prevents repetitive firing in RB neurons, whereas a 4-AP-sensitive current underlies repetitive firing in DL interneurons. The cluster and discriminant analysis described could help to classify neurons in other systems.

The firing patterns of spinal neurons: in situ patch‐clamp recordings reveal a key role for potassium currents

“…, 2006). We found no evidence of such currents: no persistent inward currents were evoked by depolarising RB neurons ( n = 4) or DL neurons ( n = 3) from −80 mV to potentials between −70 and −40 mV for durations of 100–5000 ms. As reported previously (Winlove & Roberts, 2011), input resistance was unaffected by holding neurons at potentials between −100 and −40 mV.…”

“…Currents evoked by at least three such voltage steps were averaged, and the cellular input resistance was calculated by using Ohm’s law. Input resistances were unaltered by holding neurons at potentials between −50 and −100 mV, and were unaffected by the drugs used in this study (Winlove & Roberts, 2011).…”

“…We previously reported changes in the firing patterns of RB and DL neurons caused by the potassium current blockers TEA and 4‐AP (Winlove & Roberts, 2011). Do these effects result from changes in the properties of I Kf and I Ks ?…”

“…The rheobase of DL neurons was significantly higher: 1866 pA vs. RB, t 64 = −11.558, P < 0.0001, and vs. RB‐2, t 42 = −8.044, P < 0.0001. The duration of action potentials was measured at the potential midpoint between action potential peak and action potential threshold (Winlove & Roberts, 2011); in RB‐2 neurons, the duration of action potentials was between that of RB and DL neurons (Fig. 9B; RB‐2, n = 6, action potential duration = 1.21 ± 0.18 ms).…”

Modeling human neurodevelopmental disorders in theXenopustadpole: from mechanisms to therapeutic targets

“…Because of the relatively high permeability of the tadpole blood-brain barrier, pharmacological manipulations of the nervous system are usually achieved by simply adding the pharmacological agent to the tadpole rearing solution. Electrophysiological techniques have been successfully employed in Xenopus to quantify network connectivity (Pratt and Aizenman, 2007; Li et al, 2009; Pratt and Aizenman, 2009; Straka and Simmers, 2012), synaptic maturation (Wu et al, 1996; Akerman and Cline, 2006; Aizenman and Cline, 2007; Deeg et al, 2009; Khakhalin and Aizenman, 2012), synaptic plasticity (Engert et al, 2002; Mu and Poo, 2006; Pratt et al, 2008; Tsui et al, 2010) and cell intrinsic properties (Aizenman et al, 2003; Pratt and Aizenman, 2007; Winlove and Roberts, 2011). The behaviors controlled by corresponding neural circuits, including several types of escape behaviors (Roberts et al, 2000; Wassersug and Yamashita, 2002; Dong et al, 2009; Sillar and Robertson, 2009), orienting reflexes (Pronych et al, 1996; Simmons et al, 2004; Straka, 2010) and social behaviors (Katz et al, 1981; Villinger and Waldman, 2012), have been well described, and can be experimentally manipulated (Lum et al, 1982; Jamieson and Roberts, 2000; Wassersug and Yamashita, 2002; Simmons et al, 2004; Dong et al, 2009; Straka, 2010).…”