Perceptual learning with perceptions

Abstract

In this work we present an approach to understand neuronal mechanisms underlying perceptual learning. Experimental results achieved with stimulus patterns of coherently moving dots are considered to build a simple neuronal model. The design of the model is made transparent and underlying behavioral assumptions made explicit. The key aspect of the suggested neuronal model is the learning algorithm used: We evaluated an implementation of Hebbian learning and are thus able to provide a straight-forward model capable to explain the neuronal dynamics underlying perceptual learning. Moreover, the simulation results suggest a very simple explanation for the aspect of ''sub-threshold'' learning (Watanabe et al. in Nature 413:844-884, 2001) as well as the relearning of motion discrimination after damage to primary visual cortex as recently reported (Huxlin et al. in J Neurosci 29:3981-3991, 2009) and at least indicate that perceptual learning might only occur when accompanied by conscious percepts.

Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process

“…Biological mechanisms of learning, including OL, have been studied in the context of perceptual processing, see, e.g. (Stemme et al 2011;Neiman and Loewenstein 2013). The idea of vague-to-crisp transitions found support in previous neuroimaging studies in the field of visual processing (Bar et al 2006).…”

Responses of cutaneous mechanoreceptors within fingerpad to stimulus information for tactile softness sensation of materials

“…Indeed, investigations across the human cutaneous somatosensory system have shown that the evoked responses of cutaneous mechanoreceptors to physical stimulus were consistent with the psychophysical responses (Johnson et al 2002), and then the present result indicated that the built fabric-skin-receptors model predicted the typical neural behavior of SAIs cutaneous mechanoreceptors and the typical tactile responses. Here, the comparison between sensory responses and neural responses neglected the perceptual learning (Stemme et al 2011).…”