Neural heterogeneities and stimulus properties affect burst coding in vivo

Abstract

Many neurons tend to fire clusters of action potentials called bursts followed by quiescence in response to sensory input. While the mechanisms that underlie burst firing are generally well understood in vitro, the functional role of these bursts in generating behavioral responses to sensory input in vivo are less clear. Pyramidal cells within the electrosensory lateral line lobe (ELL) of weakly electric fish offer an attractive model system for studying the coding properties of burst firing, because the anatomy and physiology of the electrosensory circuitry are well understood, and the burst mechanism of ELL pyramidal cells has been thoroughly characterized in vitro. We investigated the coding properties of bursts generated by these cells in vivo in response to mimics of behaviorally relevant sensory input. We found that heterogeneities within the pyramidal cell population had quantitative but not qualitative effects on burst coding for the low frequency components of broadband time varying input. Moreover, spatially localized stimuli mimicking, for example, prey tended to elicit more bursts than spatially global stimuli mimicking conspecific-related stimuli. We also found small but significant correlations between burst attributes such as the number of spikes per burst or the interspike interval during the burst and stimulus attributes such as stimulus amplitude or slope. These correlations were much weaker in magnitude than those observed in vitro. More surprisingly, our results show that correlations between burst and stimulus attributes actually decreased in magnitude when we used low frequency stimuli that are expected to promote burst firing. We propose that this discrepancy is attributable to differences between ELL pyramidal cell burst firing under in vivo and in vitro conditions. Keywordsweakly electric fish; neural coding; information theory; burst firing Understanding the neural code remains a central problem in neuroscience. This understanding is in part complicated by the fact that neurons in the brain are highly CIHR Author Manuscript CIHR Author Manuscript CIHR Author Manuscriptheterogeneous (Bannister and Larkman, 1995a,b;Bastian and Nguyenkim, 2001;Häusser and Mel, 2003) and are not passive input-driven devices. Instead, they are capable of rich intrinsic dynamics such as oscillations (Gray and Singer, 1989;Stopfer et al., 1997;Doiron et al., 2003a) and bursting (i.e. the firing of packets of action potentials followed by quiescence) (Lemon and Turner, 2000;Sherman, 2001;Swensen and Bean, 2003;Krahe and Gabbiani, 2004;Sabourin and Pollack, 2009). Although much is known about the intrinsic mechanisms that lead to burst firing (Wang and Rinzel, 1995;Izhikevich, 2000;Krahe and Gabbiani, 2004), the functional role of burst firing is less well understood. Studies have shown that bursts of action potentials are critical for mediating cricket escape behavior in response to threatening stimuli (Marsat and Pollack, 2006). The function of burst firing is less well understood in vertebrates: a va...

Parallel Coding of First- and Second-Order Stimulus Attributes by Midbrain Electrosensory Neurons

“…1 A). The mean baseline (i.e., no stimulus) firing rate of ELL neurons was 19.48 Ϯ 1.56 Hz, which is comparable to that obtained in previous studies using both intracellular and extracellular recordings (Bastian et al, 2002;Chacron et al, 2005b;Chacron, 2006;Krahe et al, 2008;Toporikova and Chacron, 2009;Avila-Akerberg et al, 2010) and much lower than the mean baseline firing rate of electroreceptor afferents: 199 Ϯ 8.1 Hz (Chacron et al, 2005a;Gussin et al, 2007). Further, the mean baseline firing rate of TS neurons was 5.45 Ϯ 0.71 Hz, which is comparable to that obtained from intracellular recordings in previous studies (Vonderschen and Chacron, 2011) and is furthermore significantly lower than that of ELL neurons ( p Ͻ 10 Ϫ3 , Wilcoxon rank sum test, df ϭ 190).…”

“…The mean stimulus contrast (i.e., the ratio of the SD of the AM caused by the stimulus divided by the EOD baseline amplitude) were 10 -20%, which is similar to what was used in previous studies (Bastian et al, 2002(Bastian et al, , 2004Chacron et al, 2005b;Toporikova and Chacron, 2009). The 40 -60 Hz and 0 -120 Hz noise stimuli each lasted 20 s and were each presented 5 times (Chacron, 2006;Krahe et al, 2008;Avila-Akerberg et al, 2010) to quantify response variability as described below. The 4 Hz sinusoidal AM was presented only once and lasted for at least 20 s.…”

“…Previous studies have shown that ELL neurons display large heterogeneities in their responses to sensory input that are correlated with their baseline firing rates (Bastian et al, 2002(Bastian et al, , 2004Chacron et al, 2005cChacron et al, , 2007Chacron, 2006;Toporikova and Chacron, 2009;Avila-Akerberg et al, 2010). Therefore, we next looked at whether ELL pyramidal neurons might respond differentially to first-and second-order attributes depending on their baseline firing rates.…”

Neural heterogeneities influence envelope and temporal coding at the sensory periphery

“…AMs of the animal's own EOD were delivered via two transverse electrodes in the "global" stimulation geometry (Bastian et al, 2002;Chacron, 2006;Krahe et al, 2008;Toporikova and Chacron, 2009;Avila-Akerberg et al, 2010) (Fig. 1A).…”

Neuromodulation of early electrosensory processing in gymnotiform weakly electric fish

“…Superficial pyramidal cells display the lowest spontaneous firing rates and the highest tendency to burst, whereas deep pyramidal cells display the highest spontaneous firing rates and the lowest tendency to burst in vivo (Bastian and Nguyenkim, 2001;Maler, 2009a The Journal of Experimental Biology 216 (13) presence or absence of burst firing can have significant consequences on information processing by pyramidal cells, including the gating of sensory information (Toporikova and Chacron, 2009). Further, bursts can code for specific stimulus features such as low-frequency events (Avila-Akerberg and Avila-Akerberg et al, 2010;Gabbiani et al, 1996;Krahe et al, 2002;Metzner et al, 1998;Oswald et al, 2004) as well as chirps (Marsat et al, 2009;.…”