Why the whole is more than the sum of its parts: salience-driven overestimation in aggregated tactile sensations

Experimental psychology often studies perception analytically, reducing its focus to minimal sensory units, such as thresholds or just noticeable differences in a single stimulus. Here, in contrast, we examine a synthetic aspect: how multiple inputs to a sensory system are aggregated into an overall percept. Participants in three experiments judged the total stimulus intensity for simultaneous electrical shocks to two digits. We tested whether the integration of component somatosensory stimuli into a total percept occurs automatically, or rather depends on the ability to consciously perceive discrepancy among components (Experiment 1), whether the discrepancy among these components influences sensitivity or/and perceptual bias in judging totals (Experiment 2), and whether the salience of each individual component stimulus affects perception of total intensity (Experiment 3). Perceptual aggregation of two simultaneous component events occurred both when participants could perceptually discriminate the two intensities, and also when they could not. Further, the actual discrepancy between the stimuli modulated both participants’ sensitivity and perceptual bias: increasing discrepancies produced a systematic and progressive overestimation of total intensity. The degree of this bias depended primarily on the salience of the stronger stimulus in the pair. Overall, our results suggest that important nonlinear mechanisms contribute to sensory aggregation. The mind aggregates component inputs into a coherent and synthetic perceptual experience in a salience-weighted fashion that is not based on simple summation of inputs

What is the limit of redundancy reduction with divisive normalization?

Divisive normalization has been proposed as a nonlinear redundancy reduction mechanism capturing contrast correlations. Its basic function is a radial rescaling of the population response. Because of the saturation of divisive normalization, however, it is impossible to achieve a fully independent representation. In this letter, we derive an analytical upper bound on the inevitable residual redundancy of any saturating radial rescaling mechanism