TTX-sensitive dendritic sodium channels underlie oscillatory discharge in a vertebrate sensory neuron

Turner, Ray W.; Maler, Leonard; Deerinck, Tom; Levinson, S. R.; Ellisman, MH

doi:10.1523/jneurosci.14-11-06453.1994

Cited by 131 publications

(221 citation statements)

References 76 publications

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“…ELL tissue slices of 300-400 μm were then prepared as described previously (Turner et al 1994;Ellis et al 2007b;Mehaffey et al 2008b) and were maintained by constant perfusion (2-3 mL/min) of artificial cerebrospinal fluid (ACSF, composition in mM: 126 NaCl, 2.5 KCl, 1.2 NaH 2 PO 4 , 1.2 MgCl 2 , 18 NaHCO 3 , 2.4 CaCl 2 , and 11 D-glucose) as well as superfusion with carbogen (5% CO 2 /95% O 2 ).…”

Section: In Vitro Electrophysiologymentioning

confidence: 99%

“…Indeed, bursting in ELL pyramidal neurons is intrinsic and relies on a somatodendritic interaction (Turner et al 1994;Lemon and Turner 2000). Somatic action potentials back-propagate into the proximal apical dendrites where they trigger a dendritic spike that propagates back to the soma, leading to a depolarizing afterpotential (DAP) and promotes the firing of another somatic action potential.…”

Section: Modeling Differences In Burst Coding Seen In Vitro and In Vivomentioning

confidence: 99%

“…Pyramidal cells display the tendency to fire bursts of action potentials both in vitro (Turner et al 1994) and in vivo (Bastian and Nguyenkim 2001) through a well-characterized stimulus amplitude and slope ). However, a recent study performed in vivo found weak if at all significant correlations between the burst interval and either of stimulus amplitude or slope (Avila Akerberg et al 2010).…”

Section: Introductionmentioning

confidence: 99%

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In vivo conditions influence the coding of stimulus features by bursts of action potentials

Akerberg

Chacron

2011

J Comput Neurosci

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The functional role of burst firing (i.e. the firing of packets of action potentials followed by quiescence) in sensory processing is still under debate. Should bursts be considered as unitary events that signal the presence of a particular feature in the sensory environment or is information about stimulus attributes contained within their temporal structure? We compared the coding of stimulus attributes by bursts in vivo and in vitro of electrosensory pyramidal neurons in weakly electric fish by computing correlations between burst and stimulus attributes. Our results show that, while these correlations were strong in magnitude and significant in vitro, they were actually much weaker in magnitude if at all significant in vivo. We used a mathematical model of pyramidal neuron activity in vivo and showed that such a model could reproduce the correlations seen in vitro, thereby suggesting that differences in burst coding were not due to differences in bursting seen in vivo and in vitro. We next tested whether variability in the baseline (i.e. without stimulation) activity of ELL pyramidal neurons could account for these differences. To do so, we injected noise into our model whose intensity was calibrated to mimic baseline activity variability as quantified by the coefficient of variation. We found that this noise caused significant decreases in the magnitude of correlations between burst and stimulus attributes and could account for differences between in vitro and in vivo conditions. We then tested this prediction experimentally by directly injecting noise in vitro through the recording electrode. Our results show that this caused a lowering in magnitude of the correlations between burst and stimulus attributes in vitro and gave rise to values that were quantitatively similar to those seen under in vivo conditions.While it is expected that noise in the form of baseline activity variability will lower correlations between burst and stimulus attributes, our results show that such variability can account for differences seen in vivo. Thus, the high variability seen under in vivo conditions has profound consequences on the coding of information by bursts in ELL pyramidal neurons. In particular, our results support the viewpoint that bursts serve as a detector of particular stimulus features but do not carry detailed information about such features in their structure.

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Section: In Vitro Electrophysiologymentioning

confidence: 99%

Section: Modeling Differences In Burst Coding Seen In Vitro and In Vivomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In vivo conditions influence the coding of stimulus features by bursts of action potentials

Akerberg

Chacron

2011

J Comput Neurosci

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“…All chemicals were obtained from SIGMA (St. Louis, MO) unless otherwise noted. Animals were anaesthetized in 0.05% phenoxyethanol, and ELL tissue slices of 300-400 μm thickness were prepared, and recorded from, as previously described (Turner et al, 1994). For analysis of coherence or frequency content, RAMs were created as current injection protocols lasting 100 s, with frequency content between 0 and 60 Hz, as these frequencies are accurately represented in the pyramidal cell membrane voltage (Chacron et al, 2003a;Middleton et al, 2006).…”

Section: In Vitro Electrophysiologymentioning

confidence: 99%

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Mehaffey

Ellis

Krahe

et al. 2008

Journal of Physiology-Paris

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Sensory neurons encode natural stimuli by changes in firing rate or by generating specific firing patterns, such as bursts. Many neural computations rely on the fact that neurons can be tuned to specific stimulus frequencies. It is thus important to understand the mechanisms underlying frequency tuning. In the electrosensory system of the weakly electric fish, Apteronotus leptorhynchus, the primary processing of behaviourally relevant sensory signals occurs in pyramidal neurons of the electrosensory lateral line lobe (ELL). These cells encode low frequency prey stimuli with bursts of spikes and high frequency communication signals with single spikes. We describe here how bursting in pyramidal neurons can be regulated by intrinsic conductances in a cell subtype specific fashion across the sensory maps found within the ELL, thereby regulating their frequency tuning. Further, the neuromodulatory regulation of such conductances within individual cells and the consequences to frequency tuning are highlighted. Such alterations in the tuning of the pyramidal neurons may allow weakly electric fish to preferentially select for certain stimuli under various behaviourally relevant circumstances.

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“…It is known that some neurons can display both bursting and tonic firing modes (Turner et al, 1994;Wang and Rinzel, 1995;Sherman, 2001) depending on the particular input. Moreover, neurons at the same stage of processing can often be subdivided into bursting and tonically firing subgroups (Goldberg, 2000;Bastian and Nguyenkim, 2001).…”

Section: Introductionmentioning

confidence: 99%

To Burst or Not to Burst?

2004

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It is well known that some neurons tend to fire packets of action potentials followed by periods of quiescence (bursts) while others within the same stage of sensory processing fire in a tonic manner. However, the respective computational advantages of bursting and tonic neurons for encoding time varying signals largely remain a mystery. Weakly electric fish use cutaneous electroreceptors to convey information about sensory stimuli and it has been shown that some electroreceptors exhibit bursting dynamics while others do not. In this study, we compare the neural coding capabilities of tonically firing and bursting electroreceptor model neurons using information theoretic measures. We find that both bursting and tonically firing model neurons efficiently transmit information about the stimulus. However, the decoding mechanisms that must be used for each differ greatly: a non-linear decoder would be required to extract all the available information transmitted by the bursting model neuron whereas a linear one might suffice for the tonically firing model neuron. Further investigations using stimulus reconstruction techniques reveal that, unlike the tonically firing model neuron, the bursting model neuron does not encode the detailed time course of the stimulus. A novel measure of feature detection reveals that the bursting neuron signals certain stimulus features. Finally, we show that feature extraction and stimulus estimation are mutually exclusive computations occurring in bursting and tonically firing model neurons, respectively. Our results therefore suggest that stimulus estimation and feature extraction might be parallel computations in certain sensory systems rather than being sequential as has been previously proposed.

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TTX-sensitive dendritic sodium channels underlie oscillatory discharge in a vertebrate sensory neuron

Cited by 131 publications

References 76 publications

In vivo conditions influence the coding of stimulus features by bursts of action potentials

In vivo conditions influence the coding of stimulus features by bursts of action potentials

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

To Burst or Not to Burst?

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