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Sebastian Frank, Mark Greenlee, Peter Tse; Long time no see: enduring behavioral and neuronal changes in feature conjunction learning 3 years after training. Journal of Vision 2018;18(10):289. doi: https://doi.org/10.1167/18.10.289.
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Successful learning should lead to enduring improvements that outlast the period of training and that ideally persist for a life-time. Here, we show that for a certain class of visual stimuli, conjunctions of simple motion features, learning leads to changes that endure for years beyond the period of training. Moreover, we show that these enduring behavioral learning effects are associated with lasting changes in brain activity. A group of participants was trained on a visual search task for motion trajectories. Specifically, participants were trained to detect the presence of a "v"-shaped target trajectory among inverted "v"-shaped distractor trajectories. Participants performed twelve training sessions (about 15 min each) on separate days. Over the course of training performance improved dramatically. The first and last of these training sessions were carried out during functional MRI. The MRI-results suggested that the representation of the target improved over the representation of the distractor stimulus in early visual cortex (V1-V3) after training. In order to test the long-term stability of these training-induced behavioral and neuronal changes, participants were recruited for a retest on the trained task three years after the end of their original training. We observed that performance improvements were highly stable over time. Participants performed as if no time had passed between the end of training and the retest after three years. A similar long-lasting effect of training was observed for the neuronal representation of the stimuli in early visual cortex. Together, these results suggest that feature conjunction learning may lead to changes in performance and brain activity that last for years beyond the period of training and that potentially endure for a life-time (see Frank, Greenlee, & Tse, 2017, Cerebral Cortex, doi: 10.1093/cercor/bhx039).
Meeting abstract presented at VSS 2018
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