Neurocognitive Correlates of Learning in a Visual Object Recognition Task

Abstract

Abstract. Preliminary results of a longitudinal study aimed at understanding the neurocognitive correlates of learning in a visual object recognition task are reported. The experimental task used real-world novel stimuli, whereas the control task used real-world familiar stimuli. Participants practiced the tasks over 10 weeks and reached a high level of accuracy. Brain imaging data was acquired in weeks 2, 6, and 10 and eye-tracking data was acquired in the other seven weeks. Quantitative and qualitative changes in brain activity were observed over the course of learning and skill acquisition. Generally, in the experimental task, brain activity increased at week 6 and decreased at week 10, whereas in the control task, brain activity decreased at week 6 and further decreased at week 10 compared to week 2. New clusters of brain activity emerged at week 6 in the experimental task. Eye-fixation and pupil-dilation data showed that fast learners tend to inspect the stimuli more thoroughly even after a response was given. These results are used to inform the development of computational cognitive models of visual object recognition tasks.

Foundations of Augmented Cognition

“…This is reflected in the fact that only after around 16-20 rounds, does the learning curve starts to plateau. The fMRI results (Juvina, et al, 2015) further confirms our finding that proceduralization of the aircraft starts to occur only after 20 training rounds (approximately 2 h of training). However, we could reasonably start manipulating the aircraft presentation stimuli after about 16 rounds (i.e., show only incorrect aircraft tracked in the past 4 consecutive rounds) without significant loss of performance (Fig.…”

“…The eye tracking results from the behavior study shows that slow learners spent very less time looking at the aircraft (both before response and after they receive feedback) (Juvina, et al, 2015). In general, the behavior profile shows that slow learners are low on motivation compared to fast learners.…”

“…The training sessions in the study where set up a week apart. However, no significant degrading of performance was observed when participants played the first round of a new week's session (Juvina, et al, 2015). As a result, there was no decay introduced in the model also to account for gaps in actual training sessions.…”

“…The data collection protocol and analysis of results is presented in Juvina et al (Juvina, et al, 2015).…”