Subthreshold Membrane-Potential Resonances Shape Spike-Train Patterns in the Entorhinal Cortex

Abstract

Many neurons exhibit subthreshold membrane-potential resonances, such that the largest voltage responses occur at preferred stimulation frequencies. Because subthreshold resonances are known to influence the rhythmic activity at the network level, it is vital to understand how they affect spike generation on the single-cell level. We therefore investigated both resonant and nonresonant neurons of rat entorhinal cortex. A minimal resonate-and-fire type model based on measured physiological parameters captures fundamental properties of neuronal firing statistics surprisingly well and helps to shed light on the mechanisms that shape spike patterns: 1) subthreshold resonance together with a spike-induced reset of subthreshold oscillations leads to spike clustering and 2) spike-induced dynamics influence the fine structure of interspike interval (ISI) distributions and are responsible for ISI correlations appearing at higher firing rates (> or =3 Hz). Both mechanisms are likely to account for the specific discharge characteristics of various cell types.

Nonrenewal spike train statistics: causes and functional consequences on neural coding

“…The oldest report that is known to the authors is in the activity of motoneurons in humans (Hagiwara 1949). Subsequent studies have found nonrenewal spiking statistics in retinal cat retinal ganglion cells (Kuffler et al 1957;Rodieck 1967;Levine 1980), cat superior olivary neurons (Goldberg et al 1964;Tsuchitani and Johnson 1985), cat peripheral auditory fibers (Lowen and Teich 1992), cat cochlear nuclear neurons (Goldberg and Greenwood 1966), cat medullary sympathetic neurons (Lewis et al 2001), cat sympathetic efferent fibers (Floyd et al 1982), pigeon vestibular afferents (Correia and Landolt 1977), weakly electric fish electroreceptor neurons (Longtin and Racicot 1997;Chacron et al 2000;Ratnam and Nelson 2000;Chacron et al 2001b;Chacron et al 2005b;Gussin et al 2007), paddlefish electroreceptors (Bahar et al 2001;Neiman and Russell 2001;Neiman and Russell 2004), catfish electroreceptors (Schäfer et al 1995), weakly electric fish electrosensory pyramidal neurons (Doiron et al 2003;Chacron et al 2007), honeybee mushroom body neurons (Farkhooi et al 2009), grasshopper auditory neurons (Schwalger et al 2010), primate spinothalamic neurons (Surmeier et al 1989), rat mesencephalic reticular neurons (Lansky and Radil 1987), primate somatosensory cortical neurons (Yamamoto and Nakahama 1983;Lebedev and Nelson 1996;Nawrot et al 2007), as well as rat entorhinal cortical pyramidal and interneurons (Engel et al 2008). We note that the last five studies challenge the notion that cortical neurons can be described by a renewal process such as the Poisson process and shall return to this point later.…”

“…Several investigators have reported nonrenewal spike train statistics in the form of a negative ISI serial correlation coefficient at lag 1 that is significantly different from zero (Kuffler et al 1957;Goldberg et al 1964;Yamamoto and Nakahama 1983;Tsuchitani and Johnson 1985;Schäfer et al 1995;Chacron et al 2000;Chacron et al 2007;Nawrot et al 2007;Engel et al 2008;Farkhooi et al 2009). As mentioned above, this implies that ISIs that are shorter than average tend to be followed by ISIs that are longer than average and vice versa, thus giving rise to patterning in the spike train.…”

“…While peripheral sensory neurons such as auditory fibers or electroreceptors displaying non-renewal spike trains might not be coupled, this is certainly not the case for central neurons. Indeed, cortical neurons (Engel et al 2008), cochlear nuclear neurons (Goldberg and Greenwood 1966) as well as electrosensory pyramidal cells (Chacron and Bastian 2008) all receive thousands of synaptic input and display nonrenewal spike train statistics. Such input most likely contributes to experimentally observed correlations between the activities of neighboring neurons across sensory systems (Meister et al 1995;Averbeck and Lee 2006).…”

“…While it is frequently assumed that cortical neurons can be modeled by Poisson processes with a refractory period (Shadlen and Newsome 1998;Kara et al 2000) due to their high variability (Softky and Koch 1993), this view is being challenged more and more (Engel et al 2008;Farkhooi et al 2009;Maimon and Assad 2009). In particular, recent studies have found that cortical neurons could display nonrenewal spike train statistics in vivo (Engel et al 2008).…”

“…In particular, recent studies have found that cortical neurons could display nonrenewal spike train statistics in vivo (Engel et al 2008). A more recent paper has argued that it is possible that nonrenewal spike train statistics are far more prevalent in cortical neurons than was originally thought and might have been missed in extracellular recordings due to missed spikes (Farkhooi et al 2009).…”