In this task, examining free interaction with a stimulus mouse, α-CaMKII hKO mice generally showed periods of investigatory behavior during the first 2 min of the 5-min test, but exhibited decreased interaction thereafter with only sporadic encounters.
Video summarization, which is the task examined in this work, addresses the problem of providing a short summary of a full-length video, including mainly information required for context understanding; however, without sacrificing the initial informativeness and enjoyability of the original material.
Nolan et al. attempted to capture the basics of the model, however, the task examined in that study likely confounded cognitive control with cognitive flexibility.
This review describes those characteristics of miRs that make them particularly amenable to this task, and examines the influences of both the sex chromosome complement as well as gonadal hormones on their regulation.
Furthermore, the ANT-I task examines three attentional networks and their interaction in a single task.
Using this task to examine the balance between goal-directed behavior and habit formation, BED compared to non-BED obese subjects had impairment in model-based, goal-directed behavior with a shift toward model-free habitual behaviors.
Although some recent studies have attempted to use this task to examine shift and disengagement biases (e.g., Koster et al., 2004; Salemink, van den Hout, & Kindt, 2007), this approach is susceptible to the same problems as noted earlier for the spatial cueing task.
To solve this task, we examined different hypotheses for model combination and performed a number of qualitative and quantitative benchmark simulations to compare the hybrid model with the established ODE model, to test whether the combined models are compatible and to check whether the new hybrid model has potential to explain a broader range of scenarios.
A new word definition task examined word comprehension across grammatical categories, i.e. nouns, verbs and adjectives, and was designed to overcome the ceiling effect.
QUANNs are also more powerful than CLANNs, again for some of the tasks examined, in terms of what the network can learn.
