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One may easily implement this more computationally in terms of S/N ratios in a Bayesian or MLE framework. Modern neural computation models indicate that the brain is associative (Dayan and Abbott, 2001), using synaptic weighting to correlate related properties among neurons that ��recognize�� objects (Quiroga et al., 2005). The association of lines that are oriented at different angles but have constant length could be based on this type of neural processing. The enhanced learning due to head tilt (and retained in no-head-tilt trials) is consistent with neural network behavior using supervised learning. In supervised learning, a neural network improves at classification as more training images and correct answer pairs are presented (Dayan and Abbott, 2001). In length constancy training, with no-head-tilt in each trial, the number of trials is equal to the number of unique training images presented to the neural network. But when the participant uses head tilt, the number of unique training stimuli presented increases by a significant factor because each head position provides a unique training stimulus. Each head position presents different parameters to calculate length, thereby effectively increasing the number of training stimuli presented during supervised learning greatly and making classification more accurate (Changizi et al., 2008). The use of sensorimotor integration has been shown in this study to be important to learning with the vOICe device (Epstein et al., 1989; Segond et al., 2005; Poirier et al., 2006; Proulx et al., 2008; Siegle and Warren, 2010; Levy-Tzedek et al., 2012; Haigh et al., 2013). It is important for further device design and use to discuss how broadly this finding applies to different SS devices with tactile or auditory interfaces. Despite variations in visual-to-auditory or tactile encodings most SS devices have a head mounted camera for dynamically ��viewing�� the environment. The head-tilt based learning improvement would click here likely work for all of the SS devices with a head-mounted camera. While the vOICe has a dramatically different encoding of line length vertically (frequency range) vs. horizontally (sound duration), this is not a critical feature to improvement with head-tilt. Given our analyses, it is most likely that head-tilt is not a method to view the line at the easiest angle to interpret it with vOICe (especially since improvement was maintained even when head-tilt was prohibited in the final training sessions), but rather a sensory-motor engagement that would be useful even if the encoding is same in all directions (such as with the tactile devices). Therefore, our result of sensorimotor learning with length constancy is likely moderately generalizable to other SS devices. In summary, critical perceptual properties such as constancy and externalization can be achieved to some degree with current SS devices.