Successful training of filtering mechanisms in multiple object tracking does not transfer to filtering mechanisms in a visual working memory task: Behavioral and electrophysiological evidence

In this training study, we aimed to selectively train participants' filtering mechanisms to enhance visual working memory (WM) efficiency. The highly restricted nature of visual WM capacity renders efficient filtering mechanisms crucial for its successful functioning. Filtering efficiency in visual WM can be measured via the lateralized change detection task with distractors. From an array of items, only a subsample must be memorized (targets), whereas distractors must be filtered out. From the EEG recorded while items are maintained in memory, slow potentials over posterior recording sides can be extracted. In addition, the contralateral delay activity (CDA) can be calculated as the difference wave between contralateral and ipsilateral slow potentials. As the amplitudes of contralateral slow potentials and CDA reflect the number of remembered items, one can infer if distractors were filtered out. Efficient filtering mechanisms are also highly important in multiple object tracking (MOT). We trained participants' filtering ability with the aid of this latter task. Filtering in both tasks is assumed to happen via allocation of selective attention. We observed large training-induced improvements in MOT. However, these improvements did not transfer to improved filtering mechanisms in the change detection task. Instead, we obtained suggestive evidence for an overall improvement in filtering mechanisms in the change detection task for both the training and control group. Apparently, there exist differences in the exact nature of filtering mechanisms that operate in change detection and MOT.

► Training study that investigated plasticity of filter ability in visual WM via EEG.
► Filtering is important for WM efficiency as measured in a change detection task.
► MOT and change detection might demand common filter mechanism (selective attention).
► Large training gains in filter ability in MOT, no transfer to change detection task.
► Behavioral and ERP evidence for plasticity of filter ability in change detection task.