Which physical parameter of vibrissa deflections is extracted by the rodent tactile system for discrimination? Particularly, it remains unclear whether perception has access to instantaneous kinematic parameters (i.e., the details of the trajectory) or relies on temporally integration of the movement trajectory such as frequency (e.g., spectral information) and intensity (e.g., mean speed). Here, we use a novel detection of change paradigm in head-fixed rats, which presents pulsatile vibrissa stimuli in seamless sequence for discrimination. This procedure ensures that processes of decision making can directly tap into sensory signals (no memory functions involved). We find that discrimination performance based on instantaneous kinematic cues far exceeds the ones provided by frequency and intensity. Neuronal modeling based on barrel cortex single units shows that small populations of sensitive neurons provide a transient signal that optimally fits the characteristic of the subject's perception. The present study is the first to show that perceptual read-out is superior in situations allowing the subject to base perception on detailed trajectory cues, that is, instantaneous kinematic variables. A possible impact of this finding on tactile systems of other species is suggested by evidence for instantaneous coding also in primates.

Rodents use active whisker movements to explore their environment. The “slip hypothesis” of whisker-related tactile perception entails that short-lived kinematic events (abrupt whisker movements, called “slips”, due to bioelastic whisker properties that occur during active touch of textures) carry the decisive texture information. Supporting this hypothesis, previous studies have shown that slip amplitude and frequency occur in a texture-dependent way. Further, experiments employing passive pulsatile whisker deflections revealed that perceptual performance based on pulse kinematics (i.e., signatures that resemble slips) is far superior to the one based on time-integrated variables like frequency and intensity. So far, pulsatile stimuli were employed in a noise free environment. However, the realistic scenario involves background noise (e.g., evoked by rubbing across the texture). Therefore, if slips are used for tactile perception, the tactile neuronal system would need to differentiate slip-evoked spikes from those evoked by noise. To test the animals under these more realistic conditions, we presented passive whisker-deflections to head-fixed trained rats, consisting of “slip-like” events (waveforms mimicking slips occurring with touch of real textures) embedded into background noise. Varying the (i) shapes (ramp or pulse); (ii) kinematics (amplitude, velocity, etc.); and (iii) the probabilities of occurrence of slip-like events, we observed that rats could readily detect slip-like events of different shapes against noisy background. Psychophysical curves revealed that the difference of slip event and noise amplitude determined perception, while increased probability of occurrence (frequency) had barely any effect. These results strongly support the notion that encoding of kinematics dominantly determines whisker-related tactile perception while the computation of frequency or intensity plays a minor role.

Kohonen's self-organizing map (SOM) is a popular neural network architecture for solving problems in the field of explorative data analysis, clustering, and data visualization. One of the major drawbacks of the SOM algorithm is the difficulty for nonexpert users to interpret the information contained in a trained SOM. In this paper, this problem is addressed by introducing an enhanced version of the Clusot algorithm. This algorithm consists of two main steps: 1) the computation of the Clusot surface utilizing the information contained in a trained SOM and 2) the automatic detection of clusters in this surface. In the Clusot surface, clusters present in the underlying SOM are indicated by the local maxima of the surface. For SOMs with 2-D topology, the Clusot surface can, therefore, be considered as a convenient visualization technique. Yet, the presented approach is not restricted to a certain type of 2-D SOM topology and it is also applicable for SOMs having an n-dimensional grid topology.

Classical conditioning that involves mnemonic processing, that is, a "trace" period between conditioned and unconditioned stimulus, requires awareness of the association to be formed and is considered a simple model paradigm for declarative learning. Barrel cortex, the whisker representation of primary somatosensory cortex, is required for the learning of a tactile variant of trace eyeblink conditioning (TTEBC) and undergoes distinct map plasticity during learning. To investigate the cellular mechanism underpinning TTEBC and concurrent map plasticity, we used two-photon imaging of dendritic spines in barrel cortex of awake mice while being conditioned. Monitoring layer 5 neurons' apical dendrites in layer 1, we show that one cellular expression of barrel cortex plasticity is a substantial spine count reduction of ϳ15% of the dendritic spines present before learning. The number of eliminated spines and their time of elimination are tightly related to the learning success. Moreover, spine plasticity is highly specific for the principal barrel column receiving the main signals from the stimulated vibrissa. Spines located in other columns, even those directly adjacent to the principal column, are unaffected. Because layer 1 spines integrate signals from associative thalamocortical circuits, their column-specific elimination suggests that this spine plasticity may be the result of an association of top-down signals relevant for declarative learning and spatially precise ascending tactile signals.