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In neuroimaging experiments, motor sequence learning has been extensively studied, mainly using the serial reaction time task (SRTT), and randomly ordered, less complex, already practiced or known sequences as the control condition. Here, starting from an initial sample of 48 neuroimaging experiments testing 640 healthy non-elderly adult human participants, we performed activation likelihood estimation (ALE) coordinate-based meta-analyses on baseline- and task-specific subsets of the sample. Baseline-specific analyses indicated that the choice of the control condition can, through the properties of the sequence used, favor detection of brain areas reported to sustain some motor sequence learning relevant cognitive processes over others. Relevant to the task choice, we failed to replicate the findings of previous meta-analyses that focused on the SRTT with slightly different inclusion criteria. These findings should urge the neuroimaging community in general and the motor sequence learning community in particular to carefully consider the experimental design and the inclusion criteria of future studies. They can also, as we propose, further inform the existing neurobiological models of motor sequence learning.

Insight problem solving requires overcoming an initial incorrect problem representation and finding an alternative and correct solution. Hattori et al. (2013) demonstrated that clue images for an insight problem-solving task using visual masking so that the participants were not aware that they were seeing them (hereafter referred to as subliminal clues) can facilitate solving the task. Recent studies, however, have reported that a subliminal clue can hamper the performance of insight problem-solving, which we call a negative clue effect (e.g., Nishida et al., 2018; Orita & Hattori, 2023). In one case, Nishida et al. (2018) reported that participants with stronger levels of cognitive inhibition performed less well in insight problem-solving when presented with a subliminal clue. Orita and Hattori (2023) also showed that subliminal clues hindered solving insight problems when a participant was in a state of arousal. These cases suggest that the negative clue effect occurs when a participant has a high level of cognitive control. In other words, a subliminal clue can be helpful with a low level of cognitive control. However, evidence supporting this hypothesis is limited to a few cases. Therefore, we will experiment to clarify the relationship between the effects of a subliminal clue and cognitive control in insight problem solving. We assume that subliminal clues hamper insight problem solving when cognitive control is high (i.e., a negative clue effect). In contrast, subliminal clues facilitate solving the problem when cognitive control is low (i.e., a positive clue effect). To strengthen and enhance cognitive control, we will provide participants with instructions to encourage the generation of new ideas during problem solving and boost participants’ efforts to solve the problem. To reduce cognitive control, we will require participants to concurrently perform memory tasks during problem solving to consume cognitive resources for problem solving.

Insight problem solving requires overcoming an initial incorrect problem representation and finding an alternative and correct solution. Hattori et al. (2013) demonstrated that clue images for an insight problem-solving task using visual masking so that the participants were not aware that they were seeing them (hereafter referred to as subliminal clues) can facilitate solving the task. Recent studies, however, have reported that a subliminal clue can hamper the performance of insight problem-solving, which we call a negative clue effect (e.g., Nishida et al., 2018; Orita & Hattori, 2023). In one case, Nishida et al. (2018) reported that participants with stronger levels of cognitive inhibition performed less well in insight problem-solving when presented with a subliminal clue. Orita and Hattori (2023) also showed that subliminal clues hindered solving insight problems when a participant was in a state of arousal. These cases suggest that the negative clue effect occurs when a participant has a high level of cognitive control. In other words, a subliminal clue can be helpful with a low level of cognitive control. However, evidence supporting this hypothesis is limited to a few cases. Therefore, we will experiment to clarify the relationship between the effects of a subliminal clue and cognitive control in insight problem solving. We assume that subliminal clues hamper insight problem solving when cognitive control is high (i.e., a negative clue effect). In contrast, subliminal clues facilitate solving the problem when cognitive control is low (i.e., a positive clue effect). To strengthen and enhance cognitive control, we will provide participants with instructions to encourage the generation of new ideas during problem solving and boost participants’ efforts to solve the problem. To reduce cognitive control, we will require participants to concurrently perform memory tasks during problem solving to consume cognitive resources for problem solving.

Systematic modeling of Air Traffic Control (ATC) cognitive structures and control strategies in today's system is needed as a basis for evaluating the cognitive effects of increased automation in future modernization phases of the National Airspace System (NAS). To develop an effective method for identifying cognitive structures and strategies, methods and measures were reviewed that have been applied to ATC and other complex domains. Candidate methods and measures identified during the literature review were evaluated against five criteria: (1) non-disruption of operations; (2) demonstrated in other domains; (3) relevance and meaningfulness as an index of cognitive processes; (4) efficiency of data analysis; and (5) direct evidence of cognitive structures and decision-making strategies. A combined set of appropriate methods and measures was developed for use in data collection, which took place at Jacksonville, Florida. The qualitative model developed by this research can contribute to Federal Aviation Administration (FAA) decision making in several crucial areas of ATC: selection and training, decision-aiding, operational test and evaluation (OT and E), display interface configuration, controller workload, and sector design. Cognitive Structures ATC Strategies Real-Time Effects of Automation ATC Simulation Decision Making.

Air traffic controller decision making is a key contributor to safety in the National Airspace System (NAS). Little systematic attention has been paid, however, to investigating the parameters of controller decision making or the factors that affect decision making in the air traffic control (ATC) environment. Because controller decision making takes place within the context of controlled airspace, it is necessary to understand the elements of that context as potential influences on decision-making outcomes. Previous research was conducted on sector complexity in the Great Lakes Region. The research documented in this report was designed to further investigate the elements of en route sector complexity in the Southeast Region and to examine the effects of those elements on controller decision making. Nineteen candidate factors were generated through the use of direct and indirect methods. Of these 19 factors, II had significant product-moment correlations, with overall ratings of sector complexity. The results suggested that the use of indirect approaches for knowledge elicitation did not prove to have any distinct advantage in terms of information yield over directly asking controllers for candidate complexity factors.

Cognitive control (also referred to as executive control or executive function) can be broadly understood as the prioritisation of information for goal-driven decision-making (Mackie et al., 2013). More specifically, it encompasses a set of processes that support creating and preserving relevant task goals while suppressing irrelevant task goals, as well as using goal representations to adjust attentional biases and enhance performance (Gratton et al., 2018). Cognitive control processes such as inhibitory control, working memory, and cognitive flexibility are crucial during physical exercise for regulating behaviour, managing physical demands, and optimising performance (Janelle, 1999). Similarly, music can influence exercise performance, decrease perceived exertion, and enhance positive affective states (Terry et al., 2020). While both music and exercise have been shown independently to initiate and impact cognitive control processes (e.g., Eskin, et al., 2020) recent studies have begun to explore their combination (e.g., Park, et al., 2023; Bigliassi, et al., 2018). As this intersection has not been systematically summarised yet, the present review aims to provide an overview of the cognitive control processes that underlie music listening during physical exercise. For the purpose of this review, we aim to focus on those which might be especially relevant in the realm of physical exercise and music listening, that is, inhibitory control, working memory, cognitive flexibility, task switching, attentional control, motivation, emotion regulation, and overall cognitive performance. Specifically, we focus on distinct yet interrelated cognitive control processes—inhibitory control, working memory, cognitive flexibility, task switching, attentional control, motivation, and emotion regulation—each serving specific functions during exercise and music interventions. Inhibitory control involves suppressing irrelevant stimuli and responses to maintain task focus (Diamond, 2013), while working memory is responsible for temporarily holding and manipulating information to guide ongoing actions (Baddeley & Hitch, 1974). Cognitive flexibility refers to the ability to adapt to new information and switch between mental tasks (Diamond, 2013), distinguished from task switching, which specifically measures the cognitive cost of shifting between tasks (Monsell, 2003). Attentional control is the ability to focus on relevant stimuli while ignoring distractions (Posner & Petersen, 1990), a more focused aspect of cognitive regulation compared to the broader adaptive nature of cognitive flexibility. Beyond these core cognitive processes, motivation and emotion regulation influence cognitive control by driving goal-directed behaviour and managing stress during demanding tasks (Ryan & Deci, 2000; Gross, 2014). Music’s influence on these processes—through mechanisms like arousal and mood modulation—provides the conceptual foundation for assessing its impact on overall cognitive performance during exercise (Terry et al., 2020; Bigliassi et al., 2018).

Risk of death by suicide is especially high in the months after discharge from inpatient psychiatric treatment, and particularly for people hospitalized due to suicidal thoughts or behaviors (STB). Processes examined here have been validated as STB correlates, but little work has examined how dynamic short-term changes at the within-person level contribute to STB. This study will examine short-term, proximal STB risk factors using ambulatory self-report, cognitive, and actigraphy assessment among adults (N = 130) recently discharged from inpatient psychiatric care.