Excessive noise explains the impaired visually-guided navigation abilities in adults with Williams syndrome: a computational approach

Recent evidence indicates our ability to recognize and navigate through places are causally dissociable: Adults with Williams syndrome (WS) – a genetic disorder – are impaired on “visually-guided navigation” (VGN) yet spared on “scene categorization”. But why? Here, we evaluated three, computationally derived mechanisms that may explain this VGN impairment: i) too little signal, ii) too much noise, or iii) an emphasis on speed (over accuracy). Twenty adults with WS and twenty mental age (MA) matched controls completed a VGN task and a scene categorization task (as a control). Then using each group of participants’ response times and accuracy for each task, we fit a hierarchical Linear Ballistic Accumulator model, an evidence accumulation model of decision-making, and operationalized the rate of information accumulation to the correct response (i.e., correct drift rate) as “signal,” the rate of information accumulation to the incorrect response (error drift rate) as “noise,” and the amount of information needed before making a decision (boundary) as “speed-accuracy trade-off.” For the VGN task, we found a significantly greater correct drift rate in WS compared to MA controls, revealing that the WS adults have more – not less – signal than controls, and thus cannot explain the VGN impairment. By contrast, we found both a significantly greater error drift rate and a significantly lower boundary in WS compared to MA controls, suggesting that the WS adults have more noise and a greater emphasis on speed than controls, consistent with their VGN impairment. Interestingly, however, the “excessive noise” effect was specific to the VGN task (i.e., it was not found in the scene categorization task), while the “speed emphasis” effect was found in both tasks. Taken together, these results reveal that the VGN impairment in WS, relative to scene categorization, is driven by high levels of noise.