Abstract:The study of decision-making has mainly focused on isolated decisions where choices are associated with motor actions. However, problem-solving often involves considering a hierarchy of sub-decisions. In a recent study (Lorteije et al. 2015), we reported behavioral and neuronal evidence for hierarchical decision making in a task with a small decision tree. We observed a first phase of parallel evidence integration for multiple sub-decisions, followed by a phase in which the overall strategy formed. It has been… Show more
“…Reaction times for the 3 types of difficulty level (E: easy. I: intermediate, D:difficult) reproduce those reported in the companion paper by Zylberberg and colleagues ( Zylberberg et al, 2017 ). ( G ) Influence of L2 and L2’ difficulty onto L1 choice.…”
Section: Resultssupporting
confidence: 80%
“…Lorteije and colleagues report two behavioral and two neural effects that they argue speak unanimously in favor of the former hierarchical model against the latter non-hierarchical ‘flat model’ of decision-making. We show in contrast that all four effects can equally (and more parsimoniously) be explained by the flat model of decision-making, which is also perfectly compatible with the new effects from the same dataset described in the companion paper by Zylberberg and colleagues (Zylberberg et al, 2017). 10.7554/eLife.16650.003Figure 1.Hierarchical vs. flat models of perceptual decision during a hierarchically-structured visual task.( A ) Structure of the task.…”
Section: Introductionsupporting
confidence: 85%
“…In the companion paper ( Zylberberg et al, 2017 ), Zylberberg and colleagues question the generality of this finding, arguing that it may not be compatible with the pattern of short reaction times they provide in a new analysis for the same monkey dataset. However, our mathematical analysis (Appendix 1) shows that a clear influence of L1 difficulty onto L2 performance emerges principally when L1 difficulty strongly modulates reaction times, and thus the time of integration of L2 evidence.…”
Possible options in a decision often organize as a hierarchy of subdecisions. A recent study concluded that perceptual processes in primates mimic this hierarchical structure and perform subdecisions in parallel. We argue that a flat model that directly selects between final choices accounts more parsimoniously for the reported behavioral and neural data. Critically, a flat model is characterized by decision signals integrating evidence at different hierarchical levels, in agreement with neural recordings showing this integration in localized neural populations. Our results point to the role of experience for building integrated perceptual categories where sensory evidence is merged prior to decision.DOI:
http://dx.doi.org/10.7554/eLife.16650.001
“…Reaction times for the 3 types of difficulty level (E: easy. I: intermediate, D:difficult) reproduce those reported in the companion paper by Zylberberg and colleagues ( Zylberberg et al, 2017 ). ( G ) Influence of L2 and L2’ difficulty onto L1 choice.…”
Section: Resultssupporting
confidence: 80%
“…Lorteije and colleagues report two behavioral and two neural effects that they argue speak unanimously in favor of the former hierarchical model against the latter non-hierarchical ‘flat model’ of decision-making. We show in contrast that all four effects can equally (and more parsimoniously) be explained by the flat model of decision-making, which is also perfectly compatible with the new effects from the same dataset described in the companion paper by Zylberberg and colleagues (Zylberberg et al, 2017). 10.7554/eLife.16650.003Figure 1.Hierarchical vs. flat models of perceptual decision during a hierarchically-structured visual task.( A ) Structure of the task.…”
Section: Introductionsupporting
confidence: 85%
“…In the companion paper ( Zylberberg et al, 2017 ), Zylberberg and colleagues question the generality of this finding, arguing that it may not be compatible with the pattern of short reaction times they provide in a new analysis for the same monkey dataset. However, our mathematical analysis (Appendix 1) shows that a clear influence of L1 difficulty onto L2 performance emerges principally when L1 difficulty strongly modulates reaction times, and thus the time of integration of L2 evidence.…”
Possible options in a decision often organize as a hierarchy of subdecisions. A recent study concluded that perceptual processes in primates mimic this hierarchical structure and perform subdecisions in parallel. We argue that a flat model that directly selects between final choices accounts more parsimoniously for the reported behavioral and neural data. Critically, a flat model is characterized by decision signals integrating evidence at different hierarchical levels, in agreement with neural recordings showing this integration in localized neural populations. Our results point to the role of experience for building integrated perceptual categories where sensory evidence is merged prior to decision.DOI:
http://dx.doi.org/10.7554/eLife.16650.001
“…Models like evidence accumulation can likely be extended to show how the evidence from one decision continues to affect not just the movement enacting that decision, but also remains available and biases the next decision. [170][171][172][173] Second, social signaling appears to be significantly impacted by the results of the work reviewed. If movement is the result of competition between internally represented choice options, then our movements broadcast our evolving decision process to the world.…”
Section: Conclusion and Extensionsmentioning
confidence: 99%
“…Thus, truly sequential decision making appears to be an important next step in decision‐making theories. Models like evidence accumulation can likely be extended to show how the evidence from one decision continues to affect not just the movement enacting that decision, but also remains available and biases the next decision . Second, social signaling appears to be significantly impacted by the results of the work reviewed.…”
Decision making is a fundamental cognitive function, which not only determines our day‐to‐day choices but also shapes the trajectories of our movements, our lives, and our societies. While immense progress has been made in recent years on our understanding of the mechanisms underlying decision making, research on this topic is still largely split into two halves. Good‐based models largely state that decisions are made between representations of abstract value associated with available options; while action‐based models largely state that decisions are made at the level of action representations. These models are further divided between those that state that a decision is made before an action is specified, and those that regard decision making as an evolving process that continues until movement completion. Here, we review computational models, behavioral findings, and results from neural recordings associated with these frameworks. In synthesizing this literature, we submit that decision making is best understood as a continuous, graded, and distributed process that traverses a landscape of behaviorally relevant options, from their presentation until movement completion. Identifying and understanding the intimate links between decision making and action processing has important implications for the study of complex, goal‐directed behaviors such as social communication, and for elucidating the underlying mechanisms by which decisions are formed.
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