Signal neutrality, scalar property, and collapsing boundaries as consequences of a learned multi-time scale strategy

Experiments and models in perceptual decision-making point to a key role of an integration process that accumulates sensory evidence over time. We endow a probabilistic agent comprising several such integrators with widely spread time scales and let it learn, by trial-and-error, to weight the different filtered versions of a noisy signal. The agent discovers a strategy markedly different from the literature "standard", according to which a decision made when the accumulated evidence hits a predetermined threshold. The agent instead decides during fleeting windows corresponding to the alignment of many integrators, akin to a majority vote. This strategy presents three distinguishing signatures. 1) Signal neutrality: a marked insensitivity to the signal coherence in the interval preceding the decision, as also observed in experiments. 2) Scalar property: the mean of the response times varies glaringly for different signal coherences, yet the shape of the distribution stays largely unchanged. 3) Collapsing boundaries: the agent learns to behave as if subject to a non-monotonic urgency signal, reminiscent in shape of the theoretically optimal. These three characteristics, which emerge from the interaction of a multi-scale learning agent with a highly volatile environment, are hallmarks, we argue, of an optimal decision strategy in challenging situations. As such, the present results may shed light on general information-processing principles leveraged by the brain itself.

CHaRTr: An R toolbox for modeling Choices and Response Times in decision-making tasks

Decision-making is the process of choosing and performing actions in response to sensory cues so as to achieve behavioral goals. A sophisticated research effort has led to the development of many mathematical models to describe the response time (RT) distributions and choice behavior of observers performing decision-making tasks. However, relatively few researchers use these models because it demands expertise in various numerical, statistical, and software techniques. Although some of these problems have been surmounted in existing software packages, the packages have often focused on the classical decision-making model, the diffusion decision model. Recent theoretical advances in decision-making that posit roles for “urgency”, time-varying decision thresholds, noise in various aspects of the decision-formation process or low pass filtering of sensory evidence, have proven to be challenging to incorporate in a coherent software framework that permits quantitative evaluations among these competing classes of decision-making models. Here, we present a toolbox —Choices and Response Times in R, orCHaRTr— that provides the user the ability to implement and test a wide variety of decision-making models ranging from classic through to modern versions of the diffusion decision model, to models with urgency signals, or collapsing boundaries. Earlier versions ofCHaRTrhave been instrumental in a number of recent studies of humans and monkeys performing perceptual decision-making tasks. We also provide guidance on how to extend the toolbox to incorporate future developments in decision-making models.

Expanding role boundary management theory: How volunteering highlights contextually shifting strategies and collapsing work–life role boundaries

Despite interest in expanding work–family research to focus on work–life issues, few scholars have addressed non-family life enrichment roles and their potential additional forms of and issues for boundary management. Using in-depth qualitative interviews, this study investigates the management of under-researched work–life boundaries by focusing on how volunteers communicatively manage the volunteer role in light of work and home demands. The findings suggest new boundary management processes. Specifically, in addition to the established segmenting and integrating processes, the volunteers also articulated a process of collapsing boundaries. This latter new category is manifested in two forms, named simultaneous role enactment and role value fusion. Furthermore, findings highlight how rather than only enacting one stance, individuals described contextually dependent, shifting ways of managing multiple life roles. These findings have implications for how scholars study work–life management, how practitioners seek to recruit members, and how volunteers and organizational employees make membership decisions.