Losing the error related negativity (ERN): an indicator for willed action

When people make errors in a discrimination task, a negative-going waveform can be observed in scalp-recorded EEG that has been coined the error-related negativity (ERN). We hypothesized that the ERN only occurs with slips, that is unwilled action errors, but not if an error is committed willingly and intentionally. We investigated the occurrence of the ERN in a choice reaction time task that has been shown to produce an ERN and in an error simulation task where subjects had to fake errors while the EEG was recorded. We observed a loss of the ERN when errors were committed in willed actions but not in unwilled actions thus supporting the idea that the production of the ERN is tied to slips in unwilled actions but not mistakes in willed actions

Track, then Decide: Category-Agnostic Vision-based Multi-Object Tracking

The most common paradigm for vision-based multi-object tracking is tracking-by-detection, due to the availability of reliable detectors for several important object categories such as cars and pedestrians. However, future mobile systems will need a capability to cope with rich human-made environments, in which obtaining detectors for every possible object category would be infeasible. In this paper, we propose a model-free multi-object tracking approach that uses a category-agnostic image segmentation method to track objects. We present an efficient segmentation mask-based tracker which associates pixel-precise masks reported by the segmentation. Our approach can utilize semantic information whenever it is available for classifying objects at the track level, while retaining the capability to track generic unknown objects in the absence of such information. We demonstrate experimentally that our approach achieves performance comparable to state-of-the-art tracking-by-detection methods for popular object categories such as cars and pedestrians. Additionally, we show that the proposed method can discover and robustly track a large variety of other objects.Comment: ICRA'18 submissio