Response properties of mouse trigeminal ganglion neurons

Kwegyir-Afful, Ernest E.; Marella, Sashi; Simons, Daniel J.

doi:10.1080/08990220802467612

Cited by 20 publications

(40 citation statements)

References 42 publications

(77 reference statements)

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“…1B and noting that, in these neurons, the onset of responses becomes progressively earlier as velocity increases. This phenomenon has been reported in several studies in rodents and humans (to name but a few, Johansson and Birznieks 2004;Kwegyir-Afful et al 2008;Shoykhet et al 2000). The same applies also to the first interspike interval, which becomes progressively shorter.…”

Section: Resultsmentioning

confidence: 77%

Parallel coding schemes of whisker velocity in the rat's somatosensory system

Lottem

Gugig

Azouz

2015

Journal of Neurophysiology

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The function of rodents' whisker somatosensory system is to transform tactile cues, in the form of vibrissa vibrations, into neuronal responses. It is well established that rodents can detect numerous tactile stimuli and tell them apart. However, the transformation of tactile stimuli obtained through whisker movements to neuronal responses is not well-understood. Here we examine the role of whisker velocity in tactile information transmission and its coding mechanisms. We show that in anaesthetized rats, whisker velocity is related to the radial distance of the object contacted and its own velocity. Whisker velocity is accurately and reliably coded in first-order neurons in parallel, by both the relative time interval between velocity-independent first spike latency of rapidly adapting neurons and velocity-dependent first spike latency of slowly adapting neurons. At the same time, whisker velocity is also coded, although less robustly, by the firing rates of slowly adapting neurons. Comparing first- and second-order neurons, we find similar decoding efficiencies for whisker velocity using either temporal or rate-based methods. Both coding schemes are sufficiently robust and hardly affected by neuronal noise. Our results suggest that whisker kinematic variables are coded by two parallel coding schemes and are disseminated in a similar way through various brain stem nuclei to multiple brain areas.

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Section: Resultsmentioning

confidence: 77%

Parallel coding schemes of whisker velocity in the rat's somatosensory system

Lottem

Gugig

Azouz

2015

Journal of Neurophysiology

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“…It is unlikely that the greater overall responsiveness of mouse TCUs simply reflects inputs from primary afferent neurons that fire more robustly than those in rats. Percentages of slowly adapting trigeminal ganglion cells are equivalent between the two species as are response magnitudes of slowly adapting cells (Kwegyir-Afful et al 2008). Responses of rapidly adapting cells are smaller and shorter in duration than those in rats; this could account for the slightly smaller initial response of mouse VPm neurons to deflection onset ( Fig.…”

Section: Discussionmentioning

confidence: 99%

“…For comparable ranges of deflection velocity, firing rates of trigeminal ganglion neurons vary over a narrower range in mouse vs. rat. This difference likely reflects mechanical properties of the whiskers and facial tissue (Kwegyir-Afful et al 2008). For example, in mice both the whisker hairs themselves, which are considerably thinner than those in rats, and mystacial-pad facial tissues may be more compliant and less able to transfer small differences in force to sensory receptors within the follicle.…”

Section: Discussionmentioning

confidence: 99%

“…For example, even casual inspection of whiskers in mice and rats reveals that they differ substantially in length and especially thickness. A recent study of whisker-evoked responses in mouse trigeminal ganglion neurons (Kwegyir-Afful et al 2008) revealed substantial similarities with the rat, but also some subtle differences that could potentially affect information transfer in the whisker-tobarrel pathway.Here we examine information processing in mouse barrels by recording responses of thalamic "barreloid" and cortical Present address of E. E. Kwegyir-Afful: US Food and Drug Administration, …”

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confidence: 99%

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Weaker feedforward inhibition accounts for less pronounced thalamocortical response transformation in mouse vs. rat barrels

Kwegyir-Afful

Kyriazi

Simons

2013

Journal of Neurophysiology

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Kwegyir-Afful EE, Kyriazi HT, Simons DJ. Weaker feedforward inhibition accounts for less pronounced thalamocortical response transformation in mouse vs. rat barrels. J Neurophysiol 110: 2378 -2392, 2013. First published August 21, 2013 doi:10.1152/jn.00574.2012.-Feedforward inhibition is a common motif of thalamocortical circuits. Strong engagement of inhibitory neurons by thalamic inputs enhances response differentials between preferred and nonpreferred stimuli. In rat whisker-barrel cortex, robustly driven inhibitory barrel neurons establish a brief epoch during which synchronous or nearsynchronous thalamic firing produces larger responses to preferred stimuli, such as high-velocity deflections of the principal whisker in a preferred direction. Present experiments in mice show that barrel neuron responses to preferred vs. nonpreferred stimuli differ less than in rats. In addition, fast-spike units, thought to be inhibitory barrel neurons, fire less robustly to whisker stimuli in mice than in rats. Analyses of real and simulated data indicate that mouse barrel circuitry integrates thalamic inputs over a broad temporal window, and that, as a consequence, responses of barrel neurons are largely similar to those of thalamic neurons. Results are consistent with weaker feedforward inhibition in mouse barrels. Differences in thalamocortical circuitry between mice and rats may reflect mechanical properties of the whiskers themselves. cortical circuits; thalamus; whiskers SENSORY AREAS OF THE CEREBRAL cortex are strongly driven by thalamic inputs. Studies of visual and somatosensory systems offer compelling evidence for such feedforward models. Accumulating evidence suggests a common circuit motif of thalamocortical input to both excitatory and inhibitory neurons whose interactions alter or transform incoming sensory signals (Alonso and Swadlow 2005; Bruno 2011). Feedforward inputs establish initial cortical response tuning, whereas engagement of inhibitory neurons by thalamocortical inputs acts in conjunction with neuronal and circuit nonlinearities (Pesavento et al. 2010) to enhance response differentials between preferred and nonpreferred stimuli (Miller 2003;Miller et al. 2001). Thalamic inputs evoke short-latency excitation followed by inhibition, creating a limited temporal window for afferent signals to produce cortical spiking (Gabernet et al. 2005;Wehr and Zador 2003). Indeed, diverse evidence indicates that response tuning in thalamocortical circuits is strongly affected by thalamic response timing and firing synchrony (Blomquist et al. 2009; Bruno and Sakmann 2006;Cardin et al. 2010). It is likely that, within this overall operational framework, details of local circuitry reflect evolutionary differences in brain structure and function, as well as constraints imposed by the nature of afferent signals arising from different sensory systems in different species.Thalamocortical processing in the rat whisker/barrel system is highly sensitive to thalamic population input timing Wang et al. 2010). Strong feedforw...

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“…Over the years, a great deal of effort has been invested in the anatomical examination of FSC innervation (Chambers et al, 1972;Gottschaldt et al, 1973;Rice et al, 1986;Waite and Jacquin, 1992;Waite and Tracey, 1995;Ebara et al, 2002) and in the study of response properties of first-order neurons (Zucker and Welker, 1969;Hahn, 1971;Gottschaldt et al, 1972Gottschaldt et al, , 1973Dykes, 1975;Gottschaldt and Vahle-Hinz, 1981;Gibson and Welker 1983a,b;Lichtenstein et al, 1990;Shoykhet et al, 2000;Szwed et al, 2003;Arabzadeh et al, 2005;Moxon, 2006, 2007;Stüttgen et al, 2006;Kwegyir-Afful et al, 2008). These efforts have been motivated by the realization of how critical it is to understand responses during the transduction stages, since these responses shape all subsequent somatosensory processing.…”

Section: Introductionmentioning

confidence: 99%

A Unifying Framework Underlying Mechanotransduction in the Somatosensory System

Lottem

Azouz²

2011

Journal of Neuroscience

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Rodents use their whiskers to sense their surroundings. As most of the information available to the somatosensory system originates in whiskers' primary afferents, it is essential to understand the transformation of whisker motion into neuronal activity. Here, we combined in vivo recordings in anesthetized rats with mathematical modeling to ascertain the mechanical and electrical characteristics of mechanotransduction. We found that only two synergistic processes, which reflect the dynamic interactions between (1) receptor and whisker and (2) receptor and surrounding tissue, are needed to describe mechanotransduction during passive whiskers deflection. Interactions between these processes may account for stimulus-dependent changes in the magnitude and temporal pattern of tactile responses on multiple scales. Thus, we are able to explain complex electromechanical processes underlying sensory transduction using a simple model, which captures the responses of a wide range of mechanoreceptor types to diverse sensory stimuli. This compact and precise model allows for a ubiquitous description of how mechanoreceptors encode tactile stimulus.

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Response properties of mouse trigeminal ganglion neurons

Cited by 20 publications

References 42 publications

Parallel coding schemes of whisker velocity in the rat's somatosensory system

Parallel coding schemes of whisker velocity in the rat's somatosensory system

Weaker feedforward inhibition accounts for less pronounced thalamocortical response transformation in mouse vs. rat barrels

A Unifying Framework Underlying Mechanotransduction in the Somatosensory System

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