Precise Temporal Responses in Whisker Trigeminal Neurons

Jones, Lauren M.; Lee, Soo-Hyun; Trageser, Jason C.; Simons, Daniel J.; Keller, Asaf

doi:10.1152/jn.00031.2004

Cited by 78 publications

(85 citation statements)

References 17 publications

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“…This resulted in broader ISI distributions that were not statistically distinguishable, but nevertheless had medians that correspond to the stimulus temporal frequency. We previously found similar variability in spike timing elicited in response to low frequency (<25 Hz) white-noise stimuli ( Jones et al 2004a( Jones et al , 2004b. Shoykhet et al (2000) also demonstrated that response latencies are more variable for low velocity whisker deflections.…”

Section: More Variable Responses At Low Frequenciessupporting

confidence: 75%

“…Previous studies have demonstrated that firing patterns of trigeminal ganglion neurons can phase-lock to high frequency stimuli (Gottschaldt and Vahle-Hinz 1981;Welker 1983a, 1983b;Lichtenstein et al 1990;Shoykhet et al 2000;Deschênes et al 2003;Jones et al 2004aJones et al , 2004bTimofeeva et al 2004). In these studies, individual whiskers were attached to a stimulating device and stimulated in isolation with precisely reproducible movements.…”

Section: Discussionmentioning

confidence: 99%

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Whisker primary afferents encode temporal frequency of moving gratings

Jones

Kwegyir-Afful

Keller

2006

Somatosensory & Motor Research

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To investigate the encoding of behaviorally relevant stimuli in the rodent whisker-somatosensory system, we recorded responses to moving gratings from trigeminal ganglion neurons. This allowed us to quantify how spike patterns in these neurons encode behaviorally distinguishable tactile stimuli presented with the variability inherent in a freely moving whisker paradigm. Our stimulus set consisted of three grating plates with raised bars of the same thickness (275 μm) having different spatial periods (1.0, 1.1, and 1.5 mm) swept rostro-caudally past the whiskers at velocities ranging from 50 to 330 mm/s. This resulted in 20 presentations each of nine different temporal frequencies (ranging from 50 to 220 Hz) for every grating plate. We found that despite the additional degrees of freedom introduced in this freely moving whisker paradigm, firing patterns from the majority (83%) of trigeminal ganglion neurons were statistically distinguishable, and corresponded to the temporal frequency of stimulation. The range of velocities (100-160 mm/s) that resulted in the most accurate and least variable representation of stimulus temporal frequency by trigeminal firing patterns closely corresponds to the whisking velocities employed by trained rats performing similar discrimination tasks. This suggests that, during naturally occurring whisking, individual primary afferents faithfully encode temporal frequency evoked by whisker contacts.

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Section: More Variable Responses At Low Frequenciessupporting

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Whisker primary afferents encode temporal frequency of moving gratings

Jones

Kwegyir-Afful

Keller

2006

Somatosensory & Motor Research

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“…As a consequence, Oswald et al (2007) showed that an ideal observer could distinguish different stimulus amplitudes using the amount of time between two consecutive spikes within a burst. As the value of the burst ISI was typically <10 ms and the time scales associated with the stimulus were in that study were greater than 16 ms, they showed that information about the stimulus is contained in the structure of the burst at time scales that are smaller than those contained in the stimulus, which constitutes a temporal code by definition (Theunissen and Miller 1995;Dayan and Abbott 2001;Jones et al 2004;Sadeghi et al 2007). Our previous results obtained in vivo did not find such strong correlations between burst and stimulus attributes (Avila Akerberg et al 2010).…”

Section: Do Bursts Contain Information About Sensory Stimuli In Theirmentioning

confidence: 90%

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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“…When rats sweep their whiskers across objects or textures, the spatial pattern is converted into a high-speed whisker vibration (the "vibrotactile signal"), whose dynamics are represented faithfully by first-order neurons in the trigeminal ganglion (Jones et al, 2004). Since the vibrotactile signal varies over time, it seems necessary to perform some sort of temporal integration of signals to extract features that carry information about the spatial configurations being palpated.…”

Section: Introductionmentioning

confidence: 99%

Integration of Vibrotactile Signals for Whisker-Related Perception in Rats Is Governed by Short Time Constants: Comparison of Neurometric and Psychometric Detection Performance

Stüttgen¹,

Schwarz²

2010

J. Neurosci.

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Rats explore environments by sweeping their whiskers across objects and surfaces. Both sensor movement and repetitive sweeping typical for this behavior require that vibrotactile signals are integrated over time. While temporal integration properties of neurons along the whisker somatosensory pathway have been studied extensively, the consequences for behavior are unknown. Here, we investigate the ability of headfixed rats to integrate information over time for the detection of near-threshold pulsatile deflection sequences applied to a single whisker. Psychometric detection performance was assessed with whisker stimuli composed of different numbers of pulses (1-31) delivered at varying frequencies (10, 20, 100 Hz). Detection performance indeed improved with increasing number and frequency of pulses, albeit this improvement was much lower than predicted by probabilistic combination, suggesting highly sublinear integration of pulses. This behavioral observation was reflected in the firing properties of concomitantly recorded barrel cortex neurons, which showed substantial response adaptation to repetitive whisker deflection. To estimate the integration time with which barrel cortex neuronal activity must be read out to match behavior, we constructed a model monitoring spiking activity of simulated neuronal pools, where spike trains were channeled through a leaky integrator with exponential decay. Detection was accomplished by simple threshold crossings. This simple model gave an excellent match of neurometric and psychometric data at surprisingly small time constants of 5-8 ms, thus limiting integration largely to Ͻ25 ms. This result carries important implications regarding sensory processing for whisker-mediated perception.

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Precise Temporal Responses in Whisker Trigeminal Neurons

Cited by 78 publications

References 17 publications

Whisker primary afferents encode temporal frequency of moving gratings

Whisker primary afferents encode temporal frequency of moving gratings

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

Integration of Vibrotactile Signals for Whisker-Related Perception in Rats Is Governed by Short Time Constants: Comparison of Neurometric and Psychometric Detection Performance

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