Neural encoding schemes of tactile information in afferent activity of the vibrissal system

Comparative study of extracellular recording methods for analysis of afferent sensory information: Empirical modeling, data analysis and interpretation

BACKGROUND

Physiological studies of sensorial systems often require the acquisition and processing of data extracted from their multiple components to evaluate how the neural information changes in relation to the environment changes. In this work, a comparative study about methodological aspects of two electrophysiological approaches is described.

NEW METHOD

Extracellular recordings from deep vibrissal nerves were obtained by using a customized microelectrode Utah array during passive mechanical stimulation of rat´s whiskers. These recordings were compared with those obtained with bipolar electrodes. We also propose here a simplified empirical model of the electrophysiological activity obtained from a bundle of myelinated nerve fibers.

RESULTS

The peripheral activity of the vibrissal system was characterized through the temporal and spectral features obtained with both recording methods. The empirical model not only allows the correlation between anatomical structures and functional features, but also allows to predict changes in the CAPs morphology when the arrangement and the geometry of the electrodes changes.

COMPARISON WITH EXISTING METHOD(S)

This study compares two extracellular recording methods based on analysis techniques, empirical modeling and data processing of vibrissal sensory information.

CONCLUSIONS

This comparative study reveals a close relationship between the electrophysiological techniques and the processing methods necessary to extract sensory information. This relationship is the result of maximizing the extraction of information from recordings of sensory activity.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition

BACKGROUND

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches.

NEW METHOD

In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution.

RESULTS

The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis.

COMPARISON WITH EXISTING METHODS

Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity.

CONCLUSIONS

Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods.

Functional specificity of rat vibrissal primary afferents

In this study, we propose to analyze the peripheral vibrissal system specificity through its neuronal responses. Receiver operating characteristics (ROC) curve analyses were used, which required the implementation of a binary classifier (artificial neural network) trained to identify the applied stimulus. The training phase consisted of the observation of a predetermined amount of vibrissal sweeps on two surfaces of different texture and similar roughness. Our results suggest that the specificity of the peripheral vibrissal system easily permits the discrimination between perceived stimuli, quantified through neuronal responses, and that it can be evaluated through an ROC curve analysis. We found that such specificity makes a linear binary classifier capable of detecting differences between stimuli with five sweeps at most.

Study of the cortical representation of whisker frequency selectivity using voltage-sensitive dye optical imaging

The facial whiskers of rodents act as a high-resolution tactile apparatus that allow the animal to detect the finest details of its environment. Previously it was shown that whisker-sensitive neurons in the somatosensory cortex show frequency selectivity to small amplitude stimuli, An intravital voltage-sensitive dye optical imaging (VSDi) method in combination with the different frequency whisker stimulation was used in order to visualize neural activity in the mice somatosensory cortex in response to the stimulation of a single whisker by different frequencies. Using the intravital voltage-sensitive dye optical imaging (VSDi) method in combination with the different frequency whisker stimulation we visualized neural activity in the mice somatosensory cortex in response to the stimulation of a single whisker by different frequencies. We found that whisker stimuli with different frequencies led to different optical signals in the barrel field. Our results provide evidence that different neurons of the barrel cortex have different frequency preferences. This supports prior research that whisker deflections cause responses in cortical neurons within the barrel field according to the frequency of the stimulation. Many studies of the whisker frequency selectivity were performed using unit recording but to map spatial organization, imaging methods are essential. In the work described in the present paper, we take a serious step toward detailed functional mapping of the somatosensory cortex using VSDi. To our knowledge, this is the first demonstration of whisker frequency sensitivity and selectivity of barrel cortex neurons with optical imaging methods.