Martijn J. Mulder

Bias in the Brain: A Diffusion Model Analysis of Prior Probability and Potential Payoff

In perceptual decision-making, advance knowledge biases people toward choice alternatives that are more likely to be correct and more likely to be profitable. Accumulation-to-bound models provide two possible explanations for these effects: prior knowledge about the relative attractiveness of the alternatives at hand changes either the starting point of the decision process, or the rate of evidence accumulation. Here, we used model-based functional MRI to investigate whether these effects are similar for different types of prior knowledge, and whether there is a common neural substrate underlying bias in simple perceptual choices. We used two versions of the random-dot motion paradigm in which we manipulated bias by: (1) changing the prior likelihood of occurrence for two alternatives (“prior probability”) and (2) assigning a larger reward to one of two alternatives (“potential payoff”). Human subjects performed the task inside and outside a 3T MRI scanner. For each manipulation, bias was quantified by fitting the drift diffusion model to the behavioral data. Individual measurements of bias were then used in the imaging analyses to identify regions involved in biasing choice behavior. Behavioral results showed that subjects tended to make more and faster choices toward the alternative that was most probable or had the largest payoff. This effect was primarily due to a change in the starting point of the accumulation process. Imaging results showed that, at cue level, regions of the frontoparietal network are involved in changing the starting points in both manipulations, suggesting a common mechanism underlying the biasing effects of prior knowledge.

Perceptual decision neurosciences – A model-based review

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific data. The model-based approach allows capturing latent decision-making processes such as strategic adjustments of response thresholds and relate these to interindividual differences or single-trial blood-oxygenated level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) responses. The review shows that different cortico-subcortical networks are responsive to different latent decision-making processes. More concretely, we show that evidence accumulation is associated with a fronto-parietal network which is partly overlapping with choice bias in perceptual decision making. The setting of decision thresholds is associated with fronto-basal ganglia networks which are also found for choice bias. In sum, we argue that the model-based approach holds great promises to understand the neural correlates of latent cognitive processes.

Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test

In speeded two-choice tasks, optimal performance is prescribed by the drift diffusion model. In this model, prior information or advance knowledge about the correct response can manifest itself as a shift in starting point or as a shift in drift rate criterion. These two mechanisms lead to qualitatively different choice behavior. Analyses of optimal performance (i.e., Bogacz et al., 2006; Hanks et al., 2011) have suggested that bias should manifest itself in starting point when difficulty is fixed over trials, whereas bias should (additionally) manifest itself in drift rate criterion when difficulty is variable over trials. In this article, we challenge the claim that a shift in drift criterion is necessary to perform optimally in a biased decision environment with variable stimulus difficulty. This paper consists of two parts. Firstly, we demonstrate that optimal behavior for biased decision problems is prescribed by a shift in starting point, irrespective of variability in stimulus difficulty. Secondly, we present empirical data which show that decision makers do not adopt different strategies when dealing with bias in conditions of fixed or variable across-trial stimulus difficulty. We also perform a test of specific influence for drift rate variability.

The speed and accuracy of perceptual decisions in a random-tone pitch task

Research in perceptual decision making is dominated by paradigms that tap the visual system, such as the random-dot motion (RDM) paradigm. In this study, we investigated whether the behavioral signature of perceptual decisions in the auditory domain is similar to those observed in the visual domain. We developed an auditory version of the RDM task, in which tones correspond to dots and pitch corresponds to motion (the random-tone pitch task, RTP). In this task, participants have to decide quickly whether the pitch of a “sound cloud” of tones is moving up or down. Stimulus strength and speed–accuracy trade-off were manipulated. To describe the relationship between stimulus strength and performance, we fitted the proportional-rate diffusion model to the data. The results showed a close coupling between stimulus strength and the speed and accuracy of perceptual decisions in both tasks. Additionally, we fitted the full drift diffusion model (DDM) to the data and showed that three of the four participants had similar speed–accuracy trade-offs in both tasks. However, for the RTP task, drift rates were larger and nondecision times slower, suggesting that some DDM parameters might be dependent on stimulus modality (drift rate and nondecision time), whereas others might not be (decision bound). The results illustrate that the RTP task is suitable for investigating the dynamics of auditory perceptual choices. Future studies using the task might help to investigate modality-specific effects on decision making at both the behavioral and neuronal levels.

Cortico-subthalamic connection predicts individual differences in value-driven choice bias

It has been suggested that a connection between the STN and value-sensitive areas of the prefrontal cortex might mediate value-based actions in perceptual decision making. In this study, we first seek to quantify a structural connection between the STN and a cortical region that was associated with mechanisms underlying bias in choice behavior (vmPFC). Next, we tested whether individual differences in the probabilistic tract-strength of this connection were predictive for individual differences in the magnitude of bias in a perceptual decision-making task. Probabilistic tractography was used to measure the tract-strength between the STN and the vmPFC. Bias was quantified using an accumulation-to-bound model where a shift in the starting point of the accumulation of sensory evidence causes faster and more choices for an alternative that is more likely or more valuable. Results show that vmPFC is structurally connected with the STN and that the strength of this connection is predictive for choice bias towards an alternative that is more valuable, but not for choice bias towards an alternative that is more likely. These findings confirm the involvement of the cortico-subthalamic circuit in mechanisms underlying value-based actions in perceptual decision making.

Are accuracy and reaction time affected via different processes

A recent study by van Ede et al. (2012) shows that the accuracy and reaction time in humans of tactile perceptual decisions are affected by an attentional cue via distinct cognitive and neural processes. These results are controversial as they undermine the notion that accuracy and reaction time are influenced by the same latent process that underlie the decision process. Typically, accumulation-to-bound models (like the drift diffusion model) can explain variability in both accuracy and reaction time by a change of a single parameter. To elaborate the findings of van Ede et al., we fitted the drift diffusion model to their behavioral data. Results show that both changes in accuracy and reaction time can be partly explained by an increase in the accumulation of sensory evidence (drift rate). In addition, a change in non-decision time is necessary to account for reaction time changes as well. These results provide a subtle explanation of how the underlying dynamics of the decision process might give rise to differences in both the speed and accuracy of perceptual tactile decisions. Furthermore, our analyses highlight the importance of applying a model-based approach, as the observed changes in the model parameters might be ecologically more valid, since they have an intuitive relationship with the neuronal processes underlying perceptual decision making.

A New Synthetic Strategy for Magnetic Metal Bis(dithiolene) Based Conductors

The combination of the [Co-III(Cl-2-bpy)(3)](3+) complex with the [Ni(dmit)(2)](-) anion is a one-step reaction, which results in the partially oxidised Ni(dmit)(2)-based material [Co-II(C;(2)-bpy)(3)][Ni(dmit)(2)](5) with a paramagnetic Con cation, as proven by Raman, EPR and XAS, exemplifying a, for M(dithiolene)(2) compounds new, synthetic strategy that may give access to a large variety of new [Co-II(N,N-imine)(3)][M(dithiolene)(2)] (n > 2, M = Ni, Pd) type magnetic conductors.

Paradoxes of optimal decision making: a response to Moran (2014)

The optimality of human decision making is a topic of enduring fascination and intense scrutiny. The article by Moran adds fuel to the fire by proving several paradoxical phenomena. First, models that have long been upheld as prototypes of optimality (e.g., the Sequential Probability Ratio Test and the diffusion model) appear to lose this desirable characteristic in environments with heterogeneous difficulty. In such environments, optimal responding requires response criteria that change during stimulus processing. The extent to which people are actually able or willing to execute such optimal adjustments of response criteria is not yet fully clear and requires a systematic set of experiments and model comparisons. Second, Moran revisits our work (van Ravenzwaaij et al. 2012) in which we challenged the conjecture by Hanks et al. (2011). The conjecture holds that in biased environments with heterogeneous difficulty, decision makers should incorporate prior information by adjusting both the starting point of processing and the evidence evaluation process itself (i.e., by adding a bias to drift rate). As Moran demonstrates, Hanks’ conjecture is correct as long as the decision

The temporal dynamics of evidence accumulation in the brain.

People organize the world in perceptual categorizations, which helps them to navigate through and interact with their environment. Often, this requires a perceptual decision: e.g., is this a snake or a water hose? How the brain processes sensory information into a perceptual choice is a central