Deciding when to decide : time-variant sequential sampling models explain the emergence of value-based decisions in the human brain

The cognitive and neuronal mechanisms of perceptual decision making have been successfully linked to sequential sampling models. These models describe the decision process as a gradual accumulation of sensory evidence over time. The temporal evolution of economic choices, however, remains largely unexplored. We tested whether sequential sampling models help to understand the formation of value-based decisions in terms of behavior and brain responses. We used functional magnetic resonance imaging (fMRI) to measure brain activity while human participants performed a buying task in which they freely decided upon how and when to choose. Behavior was accurately predicted by a time-variant sequential sampling model that uses a decreasing rather than fixed decision threshold to estimate the time point of the decision. Presupplementary motor area, caudate nucleus, and anterior insula activation was associated with the accumulation of evidence over time. Furthermore, at the beginning of the decision process the fMRI signal in these regions accounted for trial-by-trial deviations from behavioral model predictions: relatively high activation preceded relatively early responses. The updating of value information was correlated with signals in the ventromedial prefrontal cortex, left and right orbitofrontal cortex, and ventral striatum but also in the primary motor cortex well before the response itself. Our results support a view of value-based decisions as emerging from sequential sampling of evidence and suggest a close link between the accumulation process and activity in the motor system when people are free to respond at any time

The interplay of hippocampus and ventromedial prefrontal cortex in memory-based decision making

Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making

Neural Evidence for Adaptive Strategy Selection in Value-Based Decision-Making

In everyday life, humans often encounter complex environments in which multiple sources of information can influence their decisions. We propose that in such situations, people select and apply different strategies representing different cognitive models of the decision problem. Learning advances by evaluating the success of using a strategy and eventually by switching between strategies. To test our strategy selection model, we investigated how humans solve a dynamic learning task with complex auditory and visual information, and assessed the underlying neural mechanisms with functional magnetic resonance imaging. Using the model, we were able to capture participants' choices and to successfully attribute expected values and reward prediction errors to activations in the dopaminoceptive system (e.g., ventral striatum [VS]) as well as decision conflict to signals in the anterior cingulate cortex. The model outperformed an alternative approach that did not update decision strategies, but the relevance of information itself. Activation of sensory areas depended on whether the selected strategy made use of the respective source of information. Selection of a strategy also determined how value-related information influenced effective connectivity between sensory systems and the VS. Our results suggest that humans can structure their search for and use of relevant information by adaptively selecting between decision strategie

The attraction effect modulates reward prediction errors and intertemporal choices

Classical economic theory contends that the utility of a choice option should be independent of other options. This view is challenged by the attraction effect, in which the relative preference between two options is altered by the addition of a third, asymmetrically dominated option. Here, we leveraged the attraction effect in the context of intertemporal choices to test whether both decisions and reward prediction errors (RPE)-in the absence of choice-violate the independence of irrelevant alternatives principle. We first demonstrate that intertemporal decision making is prone to the attraction effect in humans. In an independent group of participants, we then investigate how this affects the neural and behavioral valuation of outcomes, using a novel intertemporal lottery task and fMRI. Participants' behavioral responses (i.e., satisfaction ratings) were systematically modulated by the attraction effect, and this modulation was correlated across participants with the respective change of the RPE signal in the Nucleus Accumbens. Furthermore, we show that since exponential and hyperbolic discounting models are unable to account for the attraction effect, recently proposed sequential sampling models might be more appropriate to describe intertemporal choices. Our findings demonstrate for the first time that the attraction effect modulates subjective valuation even in the absence of choice. The findings also challenge the prospect of using neuroscientific methods to measure utility in a context-free manner and have important implications for theories of reinforcement learning and delay discounting.; Many theories of value-based decision making assume that people first assess the attractiveness of each option independently of each other and then pick the option with the highest subjective value. The attraction effect, however, shows that adding a new option to a choice set can change the relative value of the existing options, which is a violation of the independence principle. Using an intertemporal choice framework, we test whether such violations also occur when the brain encodes the difference between expected and received rewards (i.e., the reward prediction error). Our results suggest that both intertemporal choice and valuation without choice do not adhere to the independence principle

The Reflection Effect in Memory-Based Decisions

Previous research has indicated a bias in memory-based decision-making, with people preferring options that they remember better. However, the cognitive mechanisms underlying this memory bias remain elusive. Here, we propose that choosing poorly remembered options is conceptually similar to choosing options with uncertain outcomes. We predicted that the memory bias would be reduced when options had negative subjective value, analogous to the reflection effect, according to which uncertainty aversion is stronger in gains than in losses. In two preregistered experiments ( N = 36 each), participants made memory-based decisions between appetitive and aversive stimuli. People preferred better-remembered options in the gain domain, but this behavioral pattern reversed in the loss domain. This effect was not related to participants' ambiguity or risk attitudes, as measured in a separate task. Our results increase the understanding of memory-based decision-making and connect this emerging field to well-established research on decisions under uncertainty

Leave-One-Trial-Out, LOTO, a general approach to link single-trial parameters of cognitive models to neural data

A key goal of model-based cognitive neuroscience is to estimate the trial-by-trial fluctuations of cognitive model parameters in order to link these fluctuations to brain signals. However, previously developed methods are limited by being difficult to implement, time-consuming, or model-specific. Here, we propose an easy, efficient and general approach to estimating trial-wise changes in parameters: Leave-One-Trial-Out (LOTO). The rationale behind LOTO is that the difference between parameter estimates for the complete dataset and for the dataset with one omitted trial reflects the parameter value in the omitted trial. We show that LOTO is superior to estimating parameter values from single trials and compare it to previously proposed approaches. Furthermore, the method makes it possible to distinguish true variability in a parameter from noise and from other sources of variability. In our view, the practicability and generality of LOTO will advance research on tracking fluctuations in latent cognitive variables and linking them to neural data

A reinforcement learning diffusion decision model for value-based decisions

Psychological models of value-based decision-making describe how subjective values are formed and mapped to single choices. Recently, additional efforts have been made to describe the temporal dynamics of these processes by adopting sequential sampling models from the perceptual decision-making tradition, such as the diffusion decision model (DDM). These models, when applied to value-based decision-making, allow mapping of subjective values not only to choices but also to response times. However, very few attempts have been made to adapt these models to situations in which decisions are followed by rewards, thereby producing learning effects. In this study, we propose a new combined reinforcement learning diffusion decision model (RLDDM) and test it on a learning task in which pairs of options differ with respect to both value difference and overall value. We found that participants became more accurate and faster with learning, responded faster and more accurately when options had more dissimilar values, and decided faster when confronted with more attractive (i.e., overall more valuable) pairs of options. We demonstrate that the suggested RLDDM can accommodate these effects and does so better than previously proposed models. To gain a better understanding of the model dynamics, we also compare it to standard DDMs and reinforcement learning models. Our work is a step forward towards bridging the gap between two traditions of decision-making research

Structure, acid-resistance and high-temperature behavior of silica-based one-part geopolymers and geopolymer-zeolite composites

One-part geopolymers (OPGs) are a sort of alkali-activated materials (AAMs) which production avoids the use of highly-alkaline activator-solutions and contributes to a better acceptance of alternative mineral binders in terms of safety-related and economic aspects. In the present contribution OPGs were synthesized by blending silica sources (two industrial silicas and two biogenic silicas) with sodium aluminate and only water must be added to initiate the hardening, i.e. mixing is performed in the same way as for conventional Portland cements. The OPGs were characterized by XRD, and SEM and the degrees of reaction of the silicas were determined by a chemical dissolution method. The industrial silicas led to the formation of geopolymer-zeolite composites, that contained, besides geopolymeric gel, crystalline tectosilicates (e.g. zeolite A and hydrosodalite) and depending on the starting composition also unreacted silica. The biogenic silicas provided a higher reactivity and avoided the formation of crystallite by-products. The differences in the microstructures caused differences in the mechanical strength of the specimens [1, 2]. The treatment of the OPG composites at moderate elevated temperatures revealed promising behavior on thermal dehydration in terms of shrinkage and residual strength up to 700 °C. Above 700 °C sintering and partial melting occurred, and new phase formation commenced. After exposure to 1000 °C the specimens appeared virtually amorphous or formed stuffed silica structures of nepheline- or carnegieite-type type [3]. The investigations of the OPG based mortars on their resistance against sulfuric acid in accordance with DIN 19573 (Appendix A) revealed very high residual strengths up to 78 % after treatment with H2SO4 (pH 1) for 70d. A mechanism of dissolution of the primary aluminosilicate reaction products of the pastes and the precipitation of a silica gel that protects the remaining aluminosilicates and decelerates further corrosion was found to be the main reason for the good performance under acidic conditions. The addition of CaO-containing feedstocks enhanced hardening, but at a certain content the resistance against sulfuric acid decreased, due to the formation of gypsum on exposure to sulfate. In addition, the mortars exhibited excellent shrinkage behavior as well as good bond to concrete substrates with pull-off strength up to \u3e 3 MPa. The workability of the fresh mortars provided very good manual applicability; automatic applications such as sprayed and spun mortars will require further optimization regarding rheological properties. In summary, the studied OPG are promising materials for the construction and the repair of concrete structures, such as sewers, that are affected by biogenic sulfuric acid corrosion. [1] Sturm, P., Greiser, S., Gluth, G. J. G., Jäger, C. & Brouwers, H. J. H. Degree of reaction and phase content of silica-based one-part geopolymers investigated using chemical and NMR spectroscopic methods. J. Mater. Sci. 50, 6768–6778 (2015). [2] Sturm, P., Gluth, G. J. G., Brouwers, H. J. H. & Kühne, H.-C. Synthesizing one-part geopolymers from rice husk ash. Constr. Build. Mater. 124, 961–966 (2016). [3] Sturm, P., Gluth, G. J. G., Simon, S., Brouwers, H. J. H. & Kühne, H.-C. The effect of heat treatment on the mechanical and structural properties of one-part geopolymer-zeolite composites. Thermochim. Acta 635, 41–58 (2016)

Semantic Incongruency Interferes With Endogenous Attention in Cross-Modal Integration of Semantically Congruent Objects

Efficient multisensory integration is often influenced by other cognitive processes including, but not limited to, semantic congruency and focused endogenous attention. Semantic congruency can re-allocate processing resources to the location of a congruent stimulus, while attention can prioritize the integration of multi-sensory stimuli under focus. Here, we explore the robustness of this phenomenon in the context of three stimuli, two of which are in the focus of endogenous attention. Participants completed an endogenous attention task with a stimulus compound consisting of 3 different objects: (1) a visual object (V) in the foreground, (2) an auditory object (A), and (3) a visual background scene object (B). Three groups of participants focused their attention on either the visual object and auditory sound (Group VA,; n; = 30), the visual object and the background (VB,; n; = 27), or the auditory sound and the background (AB,; n; = 30), and judged the semantic congruency of the objects under focus. Congruency varied systematically across all 3 stimuli: All stimuli could be semantically incongruent (e.g., V, ambulance; A, church bell; and B, swimming-pool) or all could be congruent (e.g., V, lion; A, roar; and B, savannah), or two objects could be congruent with the remaining one incongruent to the other two (e.g., V, duck; A, quack; and B, phone booth). Participants exhibited a distinct pattern of errors: when participants attended two congruent objects (e.g., group VA: V, lion; A, roar), in the presence of an unattended, incongruent third object (e.g., B, bath room) they tended to make more errors than in any other stimulus combination. Drift diffusion modeling of the behavioral data revealed a significantly smaller drift rate in two-congruent-attended condition, indicating slower evidence accumulation, which was likely due to interference from the unattended, incongruent object. Interference with evidence accumulation occurred independently of which pair of objects was in the focus of attention, which suggests that the vulnerability of congruency judgments to incongruent unattended distractors is not affected by sensory modalities. A control analysis ruled out the simple explanation of a negative response bias. These findings implicate that our perceptual system is highly sensitive to semantic incongruencies even when they are not endogenously attended