In this study, we used a word search puzzle paradigm to investigate age differences in the rate of information gain and the cues used to make patch-departure decisions in information foraging. The likelihood of patch departure increased as the profitability of the patch decreased generally. Both younger and older adults persisted past the point of optimality as defined by the marginal value theorem, which assumes perfect knowledge of the foraging ecology. Nevertheless, there was evidence that adults were rational in terms (...) of being sensitive to the change in RG for making the patch-departure decisions. However, given the limitations in cognitive resources and knowledge about the ecology, the estimation of RG may not be accurate. Younger adults were more likely to leave the puzzle as the long-term RG incrementally decreased, whereas older adults were more likely to leave the puzzle as the local RG decreased. However, older adults with better executive control were more likely to adjust their likelihood of patch-departure decisions to the long-term change in RG. Thus, age-dependent reliance on the long-term or local change in RG to make patch-departure decisions might be due to individual differences in executive control. (shrink)

As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as (...) potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures’ unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists’ cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems. (shrink)