Sebastian Gluth

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.

Cortical thickness is linked to executive functioning in adulthood and aging

Executive functions that are dependent upon the frontal‐parietal network decline considerably during the course of normal aging. To delineate neuroanatomical correlates of age‐related executive impairment, we investigated the relation between cortical thickness and executive functioning in 73 younger (20–32 years) and 56 older (60–71 years) healthy adults. Executive functioning was assessed using the Wisconsin Card Sorting Test (WCST). Cortical thickness was measured at each location of the cortical mantle using surface‐based segmentation procedures on high‐resolution T1‐weighted magnetic resonance images. For regions involved in WCST performance, such as the lateral prefrontal and parietal cortices, we found that thicker cortex was related to higher accuracy. Follow‐up ROI‐based analyses revealed that these associations were stronger in older than in younger adults. Moreover, among older adults, high and low performers differed in cortical thickness within regions generally linked to WCST performance. Our results indicate that the structural cortical correlates of executive functioning largely overlap with previously identified functional patterns. We conclude that structural preservation of relevant brain regions is associated with higher levels of executive performance in old age, and underscore the need to consider the heterogeneity of brain aging in relation to cognitive functioning. Hum Brain Mapp, 2011.

Don’t Look Back in Anger! Responsiveness to Missed Chances in Successful and Nonsuccessful Aging

Emotionally healthy older adults show a reduced responsiveness to regret when performing a sequential decision task. No Regrets As people grow older, the possibility to think about “missed chances” increases. When we are young, thinking about missed opportunities may help to optimize future behavior. However, the older we get the probability of “second chances” decreases and thus the benefit of ruminating upon them disappears. Brassen et al. (p. 612, published online 19 April) studied the behavioral and neural response to missed chances in young adults, the healthy elderly subjects and late-life depressed volunteers. Compared with young and depressed subjects, the healthy elderly subjects showed a reduced sensitivity to missed opportunities. The findings suggest a potential mechanism for preserved emotional health in older age. Life-span theories explain successful aging with an adaptive management of emotional experiences like regret. As opportunities to undo regrettable situations decline with age, a reduced engagement into these situations represents a potentially protective strategy to maintain well-being in older age. Yet, little is known about the underlying neurobiological mechanisms supporting this claim. We used a multimodal psychophysiological approach in combination with a sequential risk-taking task that induces the feeling of regret and investigated young as well as emotionally successfully and unsuccessfully (i.e., late-life depressed) aged participants. Responsiveness to regret was specifically reduced in successful aging paralleled by autonomic and frontostriatal characteristics indicating adaptive shifts in emotion regulation. Our results suggest that disengagement from regret reflects a critical resilience factor for emotional health in older age.

Separate amygdala subregions signal surprise and predictiveness during associative fear learning in humans.

It has recently been suggested that learning signals in the amygdala might be best characterized by attentional theories of associative learning [such as Pearce–Hall (PH)] and more recent hybrid variants that combine Rescorla–Wagner and PH learning models. In these models, unsigned prediction errors (PEs) determine the associability of a cue, which is used in turn to control learning of outcome expectations dynamically and reflects a function of the reliability of prior outcome predictions. Here, we employed an aversive Pavlovian reversal‐learning task to investigate computational signals derived from such a hybrid model. Unlike previous accounts, our paradigm allowed for the separate assessment of associability at the time of cue presentation and PEs at the time of outcome. We combined this approach with high‐resolution functional magnetic resonance imaging to understand how different subregions of the human amygdala contribute to associative learning. Signal changes in the corticomedial amygdala and in the midbrain represented unsigned PEs at the time of outcome showing increased responses irrespective of whether a shock was unexpectedly administered or omitted. In contrast, activity in basolateral amygdala regions correlated negatively with associability at the time of cue presentation. Thus, whereas the corticomedial amygdala and the midbrain reflected immediate surprise, the basolateral amygdala represented predictiveness and displayed increased responses when outcome predictions became more reliable. These results extend previous findings on PH‐like mechanisms in the amygdala and provide unique insights into human amygdala circuits during associative learning.

Effective Connectivity between Hippocampus and Ventromedial Prefrontal Cortex Controls Preferential Choices from Memory

Although many preferential choices in everyday life require remembering relevant information, the interplay of neural systems mediating decisions and memory has rarely been studied. We addressed this question by combining a task, in which choice options had to be retrieved from memory, with cognitive modeling and fMRI. We found that memory-guided decisions are captured by established process models of choice (sequential sampling models) but constrained by forgetting. People are biased toward remembered options and reject them only if they are very unattractive. Using a Bayesian modeling approach, we determined the posterior probability that options were remembered given the observed choices. This probability correlated with hippocampal activation during encoding. During decision making, the bias toward remembered options was linked to increased connectivity between hippocampus and ventromedial prefrontal cortex. Our results provide insights into the dependency of decisions on memory constraints and show that memory-related activation can be inferred from decisions.

Attitudes toward younger and older adults: The German Aging Semantic Differential

The present study used the German Aging Semantic Differential (ASD) to assess attitudes toward younger and older adults in a heterogeneous sample of n = 151 younger and n = 143 older adults. The questionnaire was administered in two versions, one referring to the evaluation of younger adults, the other to the evaluation of older adults. Multiple-group confirmatory factor analysis replicated the four-factor solution reported in the literature. Younger compared to older adults were rated as higher in terms of instrumentality (i.e., more active, adaptive to change) and integrity (i.e., more personally satisfied, at peace with oneself), whereas older adults were described as more autonomous and self-sufficient than younger adults. Younger participants reported more negative attitudes toward younger and older adults in some of the factors than did older participants. Structural equation modeling furthermore showed that attitudes correlated with personality characteristics and positive and negative affect, in that more agreeable, extraverted, and positively tempered participants reported less negative attitudes toward younger and older adults. Results are discussed in the context of multidimensional assessment of age stereotypes.

Classic EEG motor potentials track the emergence of value-based decisions

Making a value-based decision is a cognitively complex phenomenon and divisible into several sub-processes, such as the perception, evaluation, and final selection of choice options. Although previous research has attempted to dissociate these processes in the brain, there is emerging evidence that late action selection mechanisms are influenced continuously throughout the entire decision act. We used electroencephalography (EEG) and an established sequential decision making paradigm to investigate the extent to which the readiness potential (RP) and the lateralized readiness potential (LRP), two classic preparatory EEG motor components, reflect the ongoing evaluation process in value-based choices. During the task, human participants sequentially sampled probabilistic information to buy or reject offers of unknown value (using both hands) and were allowed to respond at any time. The pressure to respond was manipulated by charging low or high costs for collecting information. We modeled how and when decisions were made and found that participants adaptively lowered their threshold for required evidence with information costs and elapsed time. These shifts were accompanied by an increased RP-like signal during the decision process. The RP was further influenced by the amount of accumulated evidence. In addition, an LRP could be measured from the start of the decision process, well in advance and independent of the final decision. Our results are consistent with a continuous involvement of the brains motor system in emerging value-based decisions and advocate using classic EEG motor potentials for studying neurocognitive theories of decision making.

Medial prefrontal cortex activity when thinking about others depends on their age

This functional magnetic resonance imaging study examined medial prefrontal cortex (mPFC) activity as young and older participants rated an unknown young and older person, and themselves, on personality characteristics. For both young and older participants, there was greater activation in ventral mPFC (anterior cingulate) when they made judgments about own-age than other-age individuals. Additionally, across target age and participant age, there was greater activity in a more anterior region of ventral mPFC (largely medial frontal gyrus, anterior cingulate) when participants rated others than when they rated themselves. We discuss potential interpretations of these findings in the context of previous results suggesting functional specificity of subregions of ventral mPFC.

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.

Wiring the altruistic brain

Communication between brain regions uncovers hidden motives for generous behavior [Also see Report by Hein et al.] Contrary to classical economic supposition (1), understanding peoples preferences and decisions is not as simple as observing their actions. Indeed, there are many reasons for behaving altruistically, such as being moved by someones suffering (empathy) or feeling obliged to return a favor (reciprocity) (2, 3). One of the major challenges for social psychologists and neuroscientists is to characterize the different motives underlying our interactions with other people. On page 1074 in this issue, Hein et al. (4) show that knowing how distinct areas in the human brain communicate with each other can tell us why someone behaves altruistically.