Burak Güçlü

Tactile sensitivity of normal and autistic children

Many children with autistic spectrum disorders have unusual reactions to certain sensory stimuli. These reactions vary along a hyper- to hypo-responsivity continuum. For example, some children overreact to weak sensory input, but others do not respond negatively to even strong stimuli. It is typically assumed that this deviant responsivity is linked to sensitivity, although the particular stage of sensory processing affected is not known. Psychophysical vibrotactile thresholds of six male children (age: 8–12) who were diagnosed to have autistic spectrum disorders and six normal male children (age: 7–11) were measured by using a two-alternative forced-choice task. The tactile stimuli were sinusoidal displacements and they were applied on the terminal phalanx of the left middle finger of each subject. By using a forward-masking paradigm, 40- and 250-Hz thresholds of the Pacinian tactile channel and 40-Hz threshold of the Non-Pacinian I tactile channel were determined. There was no significant difference between the thresholds of autistic and normal children, and the autistic children had the same detection and masking mechanisms as the normal children. The sensory responsivity of each subject was tested by clinical questionnaires, which showed again no difference between the two subject groups. Furthermore, no significant correlations could be found between the questionnaire data and the psychophysical thresholds. However, there was a high correlation between the data from the tactile and emotional subsets of the questionnaires. These results support the hypothesis that the hyper- and hypo-responsivity to touch, which is sometimes observed in autistic spectrum disorders, is not a perceptual sensory problem, but may probably be emotional in origin.

Modeling population responses of rapidly-adapting mechanoreceptive fibers.

The population response of rapidly-adapting (RA) fibers is one component of the physiological substrate of the sense of touch. Herein, we describe a computational scheme based on the population-response model by K.O. Johnson (J. Neurophysiol. 37: 48–72, 1974) which we extended by permitting the capability to include the spatial distributions of receptors in the glabrous skin linked to RA fibers. The hypothetical cases simulated were rectangular, uniformly random and proximo-distally Gaussian distributions. Each spatial organization produced qualitatively distinct population-response profiles that also varied due to stimulus parameters. The effects of stimulus amplitude, average innervation density and contactor-probe location were studied by considering various response measures: number of active fibers, summated firing rate and the average firing rate of a subset of the modeled population. The outcome of the measures were statistically compared among simulated anatomical distributions. The response is the same for rectangular and uniformly random distributions, both of which have a homogeneous innervation density. However, the Gaussian distribution produced statistically different responses when the measure was not averaged over the subset population which represented the receptive field of a higher-order neuron. These results indicate that, as well as stimulus parameters, the anatomical organization is a significant determinant of the population response. Therefore, reconstructing population activity for testing psychophysical hypotheses must presently be done with care until the organization of the receptors within the skin has been clarified.

GABAergic/Glutamatergic–Glial/Neuronal Interaction Contributes to Rapid Adaptation in Pacinian Corpuscles

Pacinian corpuscles (PCs) are tactile receptors composed of a nerve ending (neurite) that is encapsulated by layers of lamellar cells. PCs are classified as primary mechanoreceptors because there is no synapse between the transductive membrane and the site of action-potential generation. These touch receptors respond in a rapidly adapting manner to sustained pressure (indentation or displacement), which until now was believed to be attributable solely to the mechanical properties of the capsule. However, evidence of positive immunoreactivity for GABA receptors on the neurite, as well as evidence for gene expression of synaptobrevin in the lamellar cells led to the hypothesis that GABAergic inhibition originating from the lamellar cells is involved in the rapid adaptation process of PCs. Electrophysiological data from isolated PCs demonstrates that, in the presence of either gabazine or picrotoxin (GABA receptor antagonists), many action potentials appear during the static portion of a sustained indentation stimulus (similar to slowly adapting receptors) and that these “static” spikes completely disappear in the presence of GABA. It was consequently hypothesized that glutamate, released by either the neurite itself or the lamellar cells, caused these action potentials. Indeed, the glutamate receptor blocker kynurenate either decreased or totally eliminated the static spikes. Together, these results suggest that GABA, emanating from the modified Schwann cells of the capsule, inhibits glutamatergic excitation during the static portion of sustained pressure, thus forming a “mechanochemical,” rather than purely mechanical, rapid adaptation response. This glial–neuronal interaction is a completely novel finding for the PC.

Relationship between maximal bite force and tooth wear in bruxist and non-bruxist individuals

OBJECTIVE (i) To compare individuals with self-reported bruxism and non-bruxist individuals in terms of maximal bite force (MBF) and temporomandibular joint (TMJ) primary assessment parameters and (ii) to examine the relationship between MBF and tooth wear in these subjects. MATERIALS AND METHODS Twenty-nine bruxist subjects and 29 healthy controls were enrolled. MBF measurements were carried out by the use of bite force recorder. Tooth wear indices, maximal mouth opening, maximal lateral excursions and maximal protrusions were measured for every subject. RESULTS MBF and tooth wear index scores were significantly higher in bruxists (p values <0.05) compared to non-bruxists. MBF and tooth wear index scores were found to be significantly correlated in the bruxist group (r=0.79, p=0.00). Less significant correlation was observed in the non-bruxist group (r=0.38, p=0.04). No differences in masticatory clinical examination parameters were identified between the groups. CONCLUSION This study is the first to show that MBF can increase in bruxist individuals and that the increase in MBF are correlated with tooth wear in bruxist subjects. Further studies regarding the possible role of MBF in bruxism are to be done.

Vibrotactile thresholds of the Non-Pacinian I channel: I. Methodological issues.

Thresholds of the Non-Pacinian I (NP I) channel were measured using a two-interval forced-choice paradigm, a technique independent of the subjects criterion. The studies were performed using the terminal phalanx of the human middle finger with a 40-Hz vibratory stimulus. Unlike most of the previous experiments performed in our laboratory, a contactor surround was not used. This was done to enable comparison with population models of mechanoreceptive fibers in the literature. Since the Pacinian (P) channel and NP I channel have similar vibrotactile thresholds at 40 Hz, a forward-masking procedure was used to elevate the thresholds of the P channel with respect to the NP I channel. While it has been established that the Pacinian fibers are entrained at high stimulus levels, the P channel can be perceptually masked using a 250-Hz stimulus presented prior to the 40-Hz test stimulus. The masking functions were found to be approximately linear on log-log axes and the threshold shifts were found to increase as the masking-stimulus levels increased. The results are discussed in relation to previous studies that were performed at various stimulation sites by using a contactor surround or not. A companion paper presents the variation of NP I-channel thresholds, measured using the methods described herein, and addresses the effects of stimulation along the proximo-distal axis of the phalanx. The companion paper also discusses the predictions of a computational model, recently proposed, in light of the empirical results presented.

Vibrotactile thresholds of the Non-Pacinian I channel: II. Predicting the effects of contactor location on the phalanx

The firing-rate-based population model for rapidly-adapting (RA) mechanoreceptive fibers by Güçlü and Bolanowski (Güçlü B, Bolanowski SJ. 2002. Modeling population responses of rapidly-adapting mechanoreceptive fibers. Journal of Computational Neuroscience 12:201–218.) is extended by including temporal-response properties of RA fibers. This representation allows for the generation of action-potential (spike) times for each fiber when a sinusoidal, steady-state stimulus is applied onto the skin. Signal detection theory was used to predict human psychophysical thresholds. Specifically, the effects of sensorineural innervation pattern, stimulus-contactor location and selected decision rules on the model predictions were studied. The predicted thresholds were lowest when the decision rule was one spike and highest when many active fibers were required for detection. These predictions were empirically tested by measuring vibrotactile thresholds of the Non-Pacinian I (NP I) channel, which required the special techniques discussed in the preceding article. Although the model predicted thresholds to decrease distally due to the known innervation density which is higher distally, the thresholds of the NP I psychophysical channel were found to be approximately constant (20–25 dB re 1 µm peak amplitude) from the proximal site on the terminal phalanx to the most distal portion. Interestingly, the mechanical impedance of the skin was found not to be constant along the proximo-distal axis. This latter result implies that the space-invariant mechanical attenuation function used in the model may not be valid at every location on the fingertip. Because of this, the discrepancy between the models predictions and the psychophysical results may be reconciled.

Spatial summation in the tactile sensory system: Probability summation and neural integration

Psychophysical thresholds for the detection of a 300-Hz burst of vibration applied to the thenar eminence were measured for stimuli applied to the skin through 1.5 cm2 and through 0.05 cm2 contactors. Thresholds were approximately 13 dB lower when the area of the contactor was 1.5 cm2 than when it was 0.05 cm2. The difference between the thresholds measured with the large and small contactors was significantly reduced when only the lowest thresholds obtained in the testing sessions were considered. This result supports the hypothesis that one component of spatial summation in the P channel is probability summation. In addition, threshold measurements within a session were less variable when measured with the 1.5 cm2 contactor. We conclude that spatial summation in the P channel is a joint function of two processes that occur as the areal extent of the stimulus increases: probability summation in which the probability of exceeding the psychophysical detection threshold increases as the number of receptors of varying sensitivities increases, and neural integration in which neural activity originating from separate receptors is combined within the central nervous system rendering the channel more sensitive to the stimulus.

Probability of stimulus detection in a model population of rapidly adapting fibers

The goal of this study is to establish a link between somatosensory physiology and psychophysics at the probabilistic level. The model for a population of monkey rapidly adapting (RA) mechanoreceptive fibers by Gl and Bolanowski (2002) was used to study the probability of stimulus detection when a 40 Hz sinusoidal stimulation is applied with a constant contactor size (2 mm radius) on the terminal phalanx. In the model, the detection was assumed to be mediated by one or more active fibers. Two hypothetical receptive field organizations (uniformly random and gaussian) with varying average innervation densities were considered. At a given stimulus-contactor location, changing the stimulus amplitude generates sigmoid probability-of-detection curves for both receptive field organizations. The psychophysical results superimposed on these probability curves suggest that 5 to 10 active fibers may be required for detection. The effects of the contactor location on the probability of detection reflect the pattern of innervation in the model. However, the psychophysical data do not match with the predictions from the populations with uniform or gaussian distributed receptive field centers. This result may be due to some unknown mechanical factors along the terminal phalanx, or simply because a different receptive field organization is present. It has been reported that human observers can detect one single spike in an RA fiber. By considering the probability of stimulus detection across subjects and RA populations, this article proves that more than one active fiber is indeed required for detection.

Tristate markov model for the firing statistics of rapidly-adapting mechanoreceptive fibers.

Rapidly-adapting (RA) mechanoreceptive fibers, which are associated with Meissner corpuscles, mediate one component of the neural information that contributes to the sense of touch. Responses of cat RA fibers subject to 40-Hz sinusoidal stimulation were modeled as a Markov process. Since an RA fiber generates one, two or no spikes in each cycle of the stimulus, the fibers activity was considered to exist in one of these three possible states. By analyzing empirically generated spike trains, the probability of each state and the probabilities of transitions between the three states were found as a function of the average firing rate of the fiber. The average firing rate depends on the stimulus amplitude. In addition, the phase of each spike with respect to the stimulus cycle was represented by a Laplace distribution. Based on empirical data, the mean and the standard deviation of this distribution decrease as the stimulus amplitude is increased. The entire stochastic model was implemented on a computer to simulate the responses of RA fibers. The post-stimulus time, inter-spike interval and period histograms generated from the simulations match the histograms obtained from the empirical data well as quantified by relative errors. This temporal model can be combined with a population model for average rate to derive a spatio-temporal description of the responses of somatosensory afferents. The effects of changing the stimulation frequency are discussed.

Frequency responses of cat rapidly adapting mechanoreceptive fibers.

The frequency responses of 11 rapidly adapting (RA) fibers in cat were studied by representing the average firing rate as a function of sinusoidal stimulus amplitude and stimulus frequency. Specifically, rate-intensity functions at different stimulation frequencies were fitted by four-parameter (a0, a1, a2, a3), piece-wise linear functions using nonlinear regression (n = 59; R2 > 0.877). Rate-intensity functions at intermediate frequencies were found by linear interpolation. The result of this analysis is rate–amplitude–frequency functions plotted as two-dimensional surfaces. The surfaces consist of five regions separated and sufficiently defined by four space curves. At 14 different frequencies, the statistical distribution of each rate-intensity-function parameter could be approximated by a particular lognormal distribution (n = 56; R2 > 0.796). The Kolmogorov–Smirnov test fails to reject this hypothesis for each combination of frequency and parameter (56 tests; p > 0.39). Therefore, at a given frequency, the variation of the parameters can be represented by lognormal distributions with specific means and standard deviations. Responses of six RA fibers, which are different from the data-set used for modeling, were compared with the stochastic model at different frequencies. The parameters of those fibers were tested against the null hypotheses that they were sampled from the particular parameter distributions dictated by the model. The Kolmogorov–Smirnov test fails to reject all the hypotheses at the α = 0.05 level (44 tests). At the α = 0.10 level, only a few test parameters were found to be departing from the model (a0 and a1 at 5 Hz; a2 at 20 Hz; a2 and a3 at 50 Hz). The remaining test parameters could be accurately described by the model. Having confirmed the validity of the model, the logarithmic means and the logarithmic standard deviations of the lognormally distributed rate-intensity-function parameters were estimated in the frequency range of 4–200 Hz. The rate–amplitude–frequency surfaces sampled from the established stochastic model completely characterize the rate responses of RA fibers to sinusoidal stimuli and are superior to tuning curves which require selecting criterion responses. The current rate-response model is promising for future computational work, especially on population modeling.