Rani Moran

Economic irrationality is optimal during noisy decision making

Significance Healthy individuals appear to display inconsistent preferences, preferring A over B, B over C, and C over A. Inconsistent, intransitive preferences of this form are hallmark manifestations of irrational choice behavior and breach the very assumptions of economic theory. Nevertheless, the neurocognitive mechanisms that mediate the formation of intransitive preferences remain elusive. We show that intransitivity arises from a bottleneck mechanism that blocks the processing of momentarily less valuable information. Although this algorithm is by classical definitions suboptimal (permitting the loss of information), we theoretically and empirically demonstrate that it leads to better decisions when accuracy can be compromised by neural noise beyond the sensory stage. Thus, contrary to common belief, choice irrationality is a by-product of purposeful neural computations. According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a “selective integration” policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against “late” noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.

Competitive guided search : Meeting the challenge of benchmark RT distributions

Historically, visual search models were mainly evaluated based on their account of mean reaction times (RTs) and accuracy data. More recently, Wolfe, Palmer, and Horowitz (2010) have demonstrated that the shape of the entire RT distributions imposes important constraints on visual search theories and can falsify even successful models such as guided search, raising a challenge to computational theories of search. Competitive guided search is a novel model that meets this important challenge. The model is an adaptation of guided search, featuring a series of item selection and identification iterations with guidance towards targets. The main novelty of the model is its termination rule: A quit unit, which aborts the search upon selection, competes with items for selection and is inhibited by the saliency map of the visual display. As the trial proceeds, the quit unit both increases in strength and suffers less saliency-based inhibition and hence the conditional probability of quitting the trial accelerates. The model is fitted to data the data from three classical search task that have been traditionally considered to be governed by qualitatively different mechanisms, including a spatial configuration, a conjunction, and a feature search (Wolfe et al., 2010). The model is mathematically tractable and it accounts for the properties of RT distributions and for error rates in all three search tasks, providing a unifying theoretical framework for visual search.

Optimal decision making in heterogeneous and biased environments

The issue of optimal performance in speeded two-choice tasks has played a substantial role in the development and evaluation of decision making theories. For difficulty-homogeneous environments, the means to achieve optimality are prescribed by the sequential probability ratio test (SPRT), or equivalently, by the drift diffusion model (DDM). Biases in the external environments are easily accommodated into these models by adopting a prior integration bias. However, for difficulty-heterogeneous environments, the issue is more elusive. I show that in such cases, the SPRT and the DDM are no longer equivalent and both are suboptimal. Optimality is achieved by a diffusion-like accumulation of evidence while adjusting the choice thresholds during the time course of a trial. In the second part of the paper, assuming that decisions are made according to the popular DDM, I show that optimal performance in biased environments mandates incorporating a dynamic-bias component (a shift in the drift threshold) in addition to the prior bias (a shift in the starting point) into the model. These conclusions support a conjecture by Hanks, Mazurek, Kiani, Hopp, and Shadlen, (The Journal of Neuroscience, 31(17), 6339–6352, 2011) and contradict a recent attempt to refute this conjecture by arguing that optimality is achieved with the aid of prior bias alone (van Ravenzwaaij et al., 2012). The psychological plausibility of such “mathematically optimal” strategies is discussed. The current paper contributes to the ongoing effort to understand optimal behavior in biased and heterogeneous environments and corrects prior conclusions with respect to optimality in such conditions.

Search efficiency as a function of target saliency: the transition from inefficient to efficient search and beyond

Searching for an object among distracting objects is a common daily task. These searches differ in efficiency. Some are so difficult that each object must be inspected in turn, whereas others are so easy that the target object directly catches the observers eye. In 4 experiments, the difficulty of searching for an orientation-defined target was parametrically manipulated between blocks of trials via the target-distractor orientation contrast. We observed a smooth transition from inefficient to efficient search with increasing orientation contrast. When contrast was high, search slopes were flat (indicating pop-out); when contrast was low, slopes were steep (indicating serial search). At the transition from inefficient to efficient search, search slopes were flat for target-present trials and steep for target-absent trials within the same orientation-contrast block-suggesting that participants adapted their behavior on target-absent trials to the most difficult, rather than the average, target-present trials of each block. Furthermore, even when search slopes were flat, indicative of pop-out, search continued to become faster with increasing contrast. These observations provide several new constraints for models of visual search and indicate that differences between search tasks that were traditionally considered qualitative in nature might actually be due to purely quantitative differences in target discriminability. (PsycINFO Database Record

Confidence matching in group decision-making

Most important decisions in our society are made by groups, from cabinets and commissions to boards and juries. When disagreement arises, opinions expressed with higher confidence tend to carry more weight1,2. Although an individual’s degree of confidence often reflects the probability that their opinion is correct3,4, it can also vary with task-irrelevant psychological, social, cultural and demographic factors5–9. Therefore, to combine their opinions optimally, group members must adapt to each other’s individual biases and express their confidence according to a common metric10–12. However, solving this communication problem is computationally difficult. Here we show that pairs of individuals making group decisions meet this challenge by using a heuristic strategy that we call ‘confidence matching’: they match their communicated confidence so that certainty and uncertainty is stated in approximately equal measure by each party. Combining the behavioural data with computational modelling, we show that this strategy is effective when group members have similar levels of expertise, and that it is robust when group members have no insight into their relative levels of expertise. Confidence matching is, however, sub-optimal and can cause miscommunication about who is more likely to be correct. This herding behaviour is one reason why groups can fail to make good decisions10–12.

Decisions reduce sensitivity to subsequent information.

Behavioural studies over half a century indicate that making categorical choices alters beliefs about the state of the world. People seem biased to confirm previous choices, and to suppress contradicting information. These choice-dependent biases imply a fundamental bound of human rationality. However, it remains unclear whether these effects extend to lower level decisions, and only little is known about the computational mechanisms underlying them. Building on the framework of sequential-sampling models of decision-making, we developed novel psychophysical protocols that enable us to dissect quantitatively how choices affect the way decision-makers accumulate additional noisy evidence. We find robust choice-induced biases in the accumulation of abstract numerical (experiment 1) and low-level perceptual (experiment 2) evidence. These biases deteriorate estimations of the mean value of the numerical sequence (experiment 1) and reduce the likelihood to revise decisions (experiment 2). Computational modelling reveals that choices trigger a reduction of sensitivity to subsequent evidence via multiplicative gain modulation, rather than shifting the decision variable towards the chosen alternative in an additive fashion. Our results thus show that categorical choices alter the evidence accumulation mechanism itself, rather than just its outcome, rendering the decision-maker less sensitive to new information.

When items 'pop into mind': variability in temporal-context reinstatement in free-recall

It is well established that performance in free-recall is mediated by an individual’s ability to reinstate the study-context during retrieval. This notion is supported by an abundance of evidence and is reflected in prominent models of memory. Introspectively, however, we often feel that a memory just ‘pops into mind’ and its recall is not accompanied by contextual detail. Here we ask whether this introspection is honored by the cognitive system. Namely, do items one recalls vary in the extent to which their contexts are reinstated? Previous research has provided evidence that indeed recall of some items relies on only little, if any, contextual reinstatement. This evidence pertains to one aspect of context: the concurrent, static encoding context of items, as tapped by the source-memory paradigm. However, because real-life events are strongly embedded in time, it is crucial to also investigate the dynamic, temporal aspects of context. To do so, we capitalized on one of the seminal findings linking recall with temporal-context: the temporal-contiguity effect, whereby the closer two items at study, the higher the probability that they will be retrieved one after the other during test. Using the Remember/Know paradigm, we show that in free-recall, ‘Remember’ retrievals, which are supposedly accompanied by contextual reinstatement, produce a larger temporal-contiguity effect as compared to ‘Know’ retrievals. Furthermore, ‘Know’ retrievals are more likely to be followed by retrieval errors (e.g., intrusions) than ‘Remember’ retrievals. These findings provide evidence that recalled items vary in the degree to which their temporal-context is reinstated.

Absolutely relative or relatively absolute: violations of value invariance in human decision making

Making decisions based on relative rather than absolute information processing is tied to choice optimality via the accumulation of evidence differences and to canonical neural processing via accumulation of evidence ratios. These theoretical frameworks predict invariance of decision latencies to absolute intensities that maintain differences and ratios, respectively. While information about the absolute values of the choice alternatives is not necessary for choosing the best alternative, it may nevertheless hold valuable information about the context of the decision. To test the sensitivity of human decision making to absolute values, we manipulated the intensities of brightness stimuli pairs while preserving either their differences or their ratios. Although asked to choose the brighter alternative relative to the other, participants responded faster to higher absolute values. Thus, our results provide empirical evidence for human sensitivity to task irrelevant absolute values indicating a hard-wired mechanism that precedes executive control. Computational investigations of several modelling architectures reveal two alternative accounts for this phenomenon, which combine absolute and relative processing. One account involves accumulation of differences with activation dependent processing noise and the other emerges from accumulation of absolute values subject to the temporal dynamics of lateral inhibition. The potential adaptive role of such choice mechanisms is discussed.

Exploring metacognitive components of confidence and control in individuals with obsessive-compulsive tendencies.

BACKGROUND AND OBJECTIVES Obsessive-compulsive (OC) patients typically display reduced metacognitive confidence, but findings regarding the scope of this phenomenon and factors that mediate it have been inconsistent. This study aimed to further the understanding of reduced metacognitive confidence in obsessive-compulsive disorder (OCD) by exploring the relationship between metacognitive processes and OC tendencies. METHODS High and low OC participants answered a general-knowledge questionnaire, rated their confidence in each answer, and decided whether or not to report each answer. RESULTS High and low OC participants did not differ either in their performance (general knowledge) or in their subjective estimations or confidence regarding their performance. The two groups also did not differ in the effectiveness of their metacognitive monitoring or in the relationship between monitoring and report-control decisions (control sensitivity). However, the two groups did differ in response criterion, with high OC participants less willing to report answers held with low-to-medium levels of subjective confidence. LIMITATIONS The study was conducted with non-clinical participants, which limits generalization to OCD. CONCLUSIONS These results suggest that conservative response criterion among OC individuals might be the critical factor underlying feelings of doubt and uncertainty endemic in OCD.

Reply to Davis-Stober et al.: Violations of rationality in a psychophysical task are not aggregation artifacts.

Humans deviate from rational choice theory if their estimates of the attribute values for one alternative change as a function of the attribute values of competing alternatives (1). In our paper (2), we report such “context-dependent” (CD) deviations from rationality in the form of a frequent winner (FW) effect and the corresponding weak stochastic transitivity (WST) violations. Davis-Stober et al. (3) claim that this observation is an artifact of aggregating over different trial types, and suggest that a context-independent (CI) decision model might explain our data. We thank Davis-Stober et al. (3) for drawing attention to a potentially important issue. However, we find their analysis to be misleading. Below, we comprehensively rebut their claims and present evidence that corroborates our original findings.