We applaud De Neys's work to define a set of domain-agnostic organizing principles that better clarify discussion on dual-process theories. This reformulation makes a welcome contribution to the field by proposing that (1) fast and intuitive response generation can activate multiple competing responses, leading to choice uncertainty, and (2) that this uncertainty drives subsequent activation of control-related deliberation. However, critical properties of these processes remain ambiguous in the current framework. Specifically, given the central role of fast and intuitive response generation processes, it is imperative to better specify how response options are generated, what determines their relative strength and time-course, and how these intuitions are compared to select a response. In this commentary, we draw on insights from the sequential sampling modeling literature to argue that even initial response generation and evaluation may not be exclusively driven by fast, automatic, and intuitive associative recall, but also modulated by controlled processes that operate rapidly from prior knowledge. In particular, we argue that deliberative control is deployed to prioritize information sampling and attribute evaluation, and thus response generation. We discuss how these forms of proactive control, in contrast to reactive control, pose a challenge to De Neys's current framework.
In De Neys's formulation, intuitive responses are the computational units that drive decisions. But these responses are themselves driven by the consideration of different cues or samples of information. Thus, the intuition generation process seems conceptually related to, if not synonymous with, the activation of relevant choice attributes in sequential sampling models. In these models, samples are drawn from noisy distributions of attribute values and accumulated as evidence for response options until the evidence passes a threshold for choice (Ratcliff & McKoon, Reference Ratcliff and McKoon2008; Shadlen & Shohamy, Reference Shadlen and Shohamy2016). The order in which attributes are considered can strongly influence decisions (Sullivan & Huettel, Reference Sullivan and Huettel2021; Sullivan, Hutcherson, Harris, & Rangel, Reference Sullivan, Hutcherson, Harris and Rangel2015). The present dual-process framework appears to use a similar probabilistic sampling process, suggesting that insights from the growing literature on sequential sampling models could prove informative.
Recent work on sequential sampling models demonstrates that people strategically prioritize gathering more valuable information, which can change both the temporal dynamics and strength of response generation. For example, in altruistic choice under time pressure, selfish people prioritize gathering information about their own, rather than others', outcomes (Teoh, Yao, Cunningham, & Hutcherson, Reference Teoh, Yao, Cunningham and Hutcherson2020). This systematically biases visual attention within the first few hundred milliseconds of choice presentation. In De Neys's terms, strategic allocation of attention changes the order of intuitive responses. Furthermore, this rapid reprioritization is context-sensitive: Changing the incentives of a social interaction (e.g., dictator vs. ultimatum game; Teoh & Hutcherson, Reference Teoh and Hutcherson2022) or the framing of a risky gamble (e.g., gain vs. loss frame; Roberts, Teoh, & Hutcherson, Reference Roberts, Teoh and Hutcherson2022) change which information is processed first, in a goal-consistent manner. Thus, prior information shapes information search patterns prior to information sampling and response generation, appearing to operate independently of the uncertainty-triggered control in De Neys's model.
Similarly, prestimulus control-related signals can also change the order or strength of information recall, proactively shaping the response generation process. For example, time-varying sequential sampling models of food choice demonstrate that instructions to focus on health-related goals – a presumably deliberative process – results in faster activation of health-related information (Maier et al., Reference Maier, Raja Beharelle, Polanía, Ruff and Hare2020). In addition to changing the temporal dynamics of information retrieval, holding health-related goals increases how much weight people place on health relative to taste in their food choices (Hare, Malmaud, & Rangel, Reference Hare, Malmaud and Rangel2011; Tusche & Hutcherson, Reference Tusche and Hutcherson2018). This suggests that retrieving and generating response options is not solely automatic. Instead, effortfully maintained goals can determine which information is most relevant, and can change the order in which response-relevant attributes are considered.
These results from both attention and memory sampling highlight an important distinction between reactive control, which are triggered by an event and strongly resembles the uncertainty-triggered deliberation of De Neys's model, and proactive control, which refers to regulatory processes that occur before encountering a stimulus (Braver, Reference Braver2012; Braver, Gray, & Burgess, Reference Braver, Gray and Burgess2007). Importantly, as we have suggested above, our own and others' work suggests that this form of control can modulate when and what intuitions are activated even in the absence of conflict, and can alter the strength or order of information processing before rather than after intuitions are retrieved.
Better specifying how prestimulus control influences response generation may not only better link the current model to the self-regulation literature, but also extend it to more general models of information processing. The iterative reprocessing framework (Cunningham, Zelazo, Packer, & Van Bavel, Reference Cunningham, Zelazo, Packer and Van Bavel2007) is one such model which allows both stimulus-driven, bottom-up processes to inform goal-based, top-down processes, and vice versa. This echoes findings in attention (Asplund, Todd, Snyder, & Marois, Reference Asplund, Todd, Snyder and Marois2010; Corbetta & Shulman, Reference Corbetta and Shulman2002) and memory (Burianová, Ciaramelli, Grady, & Moscovitch, Reference Burianová, Ciaramelli, Grady and Moscovitch2012; Ciaramelli, Grady, & Moscovitch, Reference Ciaramelli, Grady and Moscovitch2008) which propose that there are distinct but related top-down and bottom-up processes which mutually inform each other. Under this framework, organizational, top-down processes are always informing what is considered most relevant by stimulus-driven processes. This top-down influence could become more effortful or directed with reflective control (Cunningham & Zelazo, Reference Cunningham and Zelazo2007), but pre-existing knowledge plays an important causal role in determining the relevance of automatically retrieved information.
As uncertainty-triggered deliberative processes remain to be fully specified in De Neys's model, it is unclear whether proactive control processes should be considered a separate process, or whether it might use the same architecture. Regardless, considering when and how proactive deliberative processes are activated represents a fruitful area of inquiry. For example, dieters are often highly motivated to engage in healthy eating, yet may fail to spontaneously engage in proactive control (Cosme, Zeithamova, Stice, & Berkman, Reference Cosme, Zeithamova, Stice and Berkman2020). Although learning can automatize these priorities, as De Neys discusses, the effortful engagement of proactive control is not well incorporated into the current automatic-deliberative division. This case study thus highlights the need for a better articulation of how both intuitive and deliberative processes shape the initial response generation process, and points to the benefits of marrying dual-process models with the richness of recent computational models of information sampling and choice.
We applaud De Neys's work to define a set of domain-agnostic organizing principles that better clarify discussion on dual-process theories. This reformulation makes a welcome contribution to the field by proposing that (1) fast and intuitive response generation can activate multiple competing responses, leading to choice uncertainty, and (2) that this uncertainty drives subsequent activation of control-related deliberation. However, critical properties of these processes remain ambiguous in the current framework. Specifically, given the central role of fast and intuitive response generation processes, it is imperative to better specify how response options are generated, what determines their relative strength and time-course, and how these intuitions are compared to select a response. In this commentary, we draw on insights from the sequential sampling modeling literature to argue that even initial response generation and evaluation may not be exclusively driven by fast, automatic, and intuitive associative recall, but also modulated by controlled processes that operate rapidly from prior knowledge. In particular, we argue that deliberative control is deployed to prioritize information sampling and attribute evaluation, and thus response generation. We discuss how these forms of proactive control, in contrast to reactive control, pose a challenge to De Neys's current framework.
In De Neys's formulation, intuitive responses are the computational units that drive decisions. But these responses are themselves driven by the consideration of different cues or samples of information. Thus, the intuition generation process seems conceptually related to, if not synonymous with, the activation of relevant choice attributes in sequential sampling models. In these models, samples are drawn from noisy distributions of attribute values and accumulated as evidence for response options until the evidence passes a threshold for choice (Ratcliff & McKoon, Reference Ratcliff and McKoon2008; Shadlen & Shohamy, Reference Shadlen and Shohamy2016). The order in which attributes are considered can strongly influence decisions (Sullivan & Huettel, Reference Sullivan and Huettel2021; Sullivan, Hutcherson, Harris, & Rangel, Reference Sullivan, Hutcherson, Harris and Rangel2015). The present dual-process framework appears to use a similar probabilistic sampling process, suggesting that insights from the growing literature on sequential sampling models could prove informative.
Recent work on sequential sampling models demonstrates that people strategically prioritize gathering more valuable information, which can change both the temporal dynamics and strength of response generation. For example, in altruistic choice under time pressure, selfish people prioritize gathering information about their own, rather than others', outcomes (Teoh, Yao, Cunningham, & Hutcherson, Reference Teoh, Yao, Cunningham and Hutcherson2020). This systematically biases visual attention within the first few hundred milliseconds of choice presentation. In De Neys's terms, strategic allocation of attention changes the order of intuitive responses. Furthermore, this rapid reprioritization is context-sensitive: Changing the incentives of a social interaction (e.g., dictator vs. ultimatum game; Teoh & Hutcherson, Reference Teoh and Hutcherson2022) or the framing of a risky gamble (e.g., gain vs. loss frame; Roberts, Teoh, & Hutcherson, Reference Roberts, Teoh and Hutcherson2022) change which information is processed first, in a goal-consistent manner. Thus, prior information shapes information search patterns prior to information sampling and response generation, appearing to operate independently of the uncertainty-triggered control in De Neys's model.
Similarly, prestimulus control-related signals can also change the order or strength of information recall, proactively shaping the response generation process. For example, time-varying sequential sampling models of food choice demonstrate that instructions to focus on health-related goals – a presumably deliberative process – results in faster activation of health-related information (Maier et al., Reference Maier, Raja Beharelle, Polanía, Ruff and Hare2020). In addition to changing the temporal dynamics of information retrieval, holding health-related goals increases how much weight people place on health relative to taste in their food choices (Hare, Malmaud, & Rangel, Reference Hare, Malmaud and Rangel2011; Tusche & Hutcherson, Reference Tusche and Hutcherson2018). This suggests that retrieving and generating response options is not solely automatic. Instead, effortfully maintained goals can determine which information is most relevant, and can change the order in which response-relevant attributes are considered.
These results from both attention and memory sampling highlight an important distinction between reactive control, which are triggered by an event and strongly resembles the uncertainty-triggered deliberation of De Neys's model, and proactive control, which refers to regulatory processes that occur before encountering a stimulus (Braver, Reference Braver2012; Braver, Gray, & Burgess, Reference Braver, Gray and Burgess2007). Importantly, as we have suggested above, our own and others' work suggests that this form of control can modulate when and what intuitions are activated even in the absence of conflict, and can alter the strength or order of information processing before rather than after intuitions are retrieved.
Better specifying how prestimulus control influences response generation may not only better link the current model to the self-regulation literature, but also extend it to more general models of information processing. The iterative reprocessing framework (Cunningham, Zelazo, Packer, & Van Bavel, Reference Cunningham, Zelazo, Packer and Van Bavel2007) is one such model which allows both stimulus-driven, bottom-up processes to inform goal-based, top-down processes, and vice versa. This echoes findings in attention (Asplund, Todd, Snyder, & Marois, Reference Asplund, Todd, Snyder and Marois2010; Corbetta & Shulman, Reference Corbetta and Shulman2002) and memory (Burianová, Ciaramelli, Grady, & Moscovitch, Reference Burianová, Ciaramelli, Grady and Moscovitch2012; Ciaramelli, Grady, & Moscovitch, Reference Ciaramelli, Grady and Moscovitch2008) which propose that there are distinct but related top-down and bottom-up processes which mutually inform each other. Under this framework, organizational, top-down processes are always informing what is considered most relevant by stimulus-driven processes. This top-down influence could become more effortful or directed with reflective control (Cunningham & Zelazo, Reference Cunningham and Zelazo2007), but pre-existing knowledge plays an important causal role in determining the relevance of automatically retrieved information.
As uncertainty-triggered deliberative processes remain to be fully specified in De Neys's model, it is unclear whether proactive control processes should be considered a separate process, or whether it might use the same architecture. Regardless, considering when and how proactive deliberative processes are activated represents a fruitful area of inquiry. For example, dieters are often highly motivated to engage in healthy eating, yet may fail to spontaneously engage in proactive control (Cosme, Zeithamova, Stice, & Berkman, Reference Cosme, Zeithamova, Stice and Berkman2020). Although learning can automatize these priorities, as De Neys discusses, the effortful engagement of proactive control is not well incorporated into the current automatic-deliberative division. This case study thus highlights the need for a better articulation of how both intuitive and deliberative processes shape the initial response generation process, and points to the benefits of marrying dual-process models with the richness of recent computational models of information sampling and choice.
Acknowledgments
H.C. would like to thank the members of the Toronto Decision Neuroscience Lab and the 2020 enrollee cohort of graduate students at the University of Toronto, Department of Psychology for their continued support.
Financial support
Funding from the Canada Research Chairs program (to C.A.H.), the Natural Science and Engineering Research Council (to W.A.C.), and an Ontario Graduate Scholarship (to Y.Y.T.) is gratefully acknowledged. All views expressed in this article represent the views of the authors, and not of the funding bodies.
Competing interest
None.