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Questions about measurement of individual differences in implicit attitudes, which have been the focus so far in this exchange, should be distinguished from more general questions about whether implicit attitudes exist and operate in our minds. Theorists frequently move too quickly from pessimistic results regarding the first set of questions to pessimistic conclusions about the second. That is, they take evidence that indirect measures such as the implicit association test (IAT) disappoint as individual difference measures and use it to (mistakenly) suggest that people do not in fact have implicit attitudes directed at stigmatized groups. In this commentary, I dissect this mistake in detail, drawing key lessons from a parallel debate that has unfolded in cognitive science about "conflict tasks" such as the Stroop task. I argue that the evidence overall supports a nuanced conclusion: Indirect measures such as the IAT measure individual differences in implicit attitudes poorly, but they-via distinct lines of evidence-still support the view that implicit attitudes exist. This article is categorized under: PsychologyTheory and Methods.

General cognitive ability (GCA) refers to a trait‐like ability that contributes to performance across diverse cognitive tasks. Identifying brain‐based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole‐brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N‐back working memory task as well as six other tasks in the Human Connectome Project dataset (n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2‐back versus 0‐back contrast achieved a 0.50 correlation with GCA scores in 10‐fold cross‐validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation—a brain activation pattern associated with executive processing and higher cognitive demand—are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain‐based prediction of GCA., We investigated prediction of general cognitive ability (GCA) based on fMRI task activation patterns with 15 task contrasts in the Human Connectome Project dataset. The 2‐back versus 0‐back contrast achieved a 0.50 correlation with GCA scores in ten10‐fold cross‐validation analysis. Additionally, we found that task contrasts that produce greater fronto‐parietal activation and default mode network deactivation—a brain activation pattern associated with executive processing and higher cognitive demand—are more effective in GCA prediction.

Background Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders of childhood. Neuroimaging investigations of ADHD have traditionally sought to detect localized abnormalities in discrete brain regions. Recent years, however, have seen the emergence of complementary lines of investigation into distributed connectivity disturbances in ADHD. Current models emphasize abnormal relationships between default network—involved in internally directed mentation and lapses of attention—and task positive networks, especially ventral attention network. However, studies that comprehensively investigate interrelationships between large-scale networks in ADHD remain relatively rare. Methods Resting state functional magnetic resonance imaging scans were obtained from 757 participants at seven sites in the ADHD-200 multisite sample. Functional connectomes were generated for each subject, and interrelationships between seven large-scale brain networks were examined with network contingency analysis. Results ADHD brains exhibited altered resting state connectivity between default network and ventral attention network [P

The exercise of willpower is puzzling because it seems to require that a person both most wants to act on a wayward desire, and most wants to resist this desire, and this seems impossible. There are two accounts that try to resolve this puzzle of synchronic self-control, Jeanette Kennett and Michael Smith’s ‘non-actional’ account and Alfred Mele’s ‘ancillary action’ account. I criticize these accounts because they set too strong constraints on what kinds of synchronic self-control are possible, and thus what willpower could turn out to be. I then propose a ‘divided mind’ account that helps make sense of particularly strong forms of willpower that cannot be accommodated on the alternative accounts. On the divided mind account, motivational architecture is divided between a deliberative motivational system and an emotional motivational system, and willpower is a proprietary action exclusively available to the deliberative system. I address potential objections to the divided mind account. One objection says that it is not in fact possible for a weaker desire to defeat a stronger one. A second objection says that actions that arise exclusively from parts of a mind cannot be said to belong to the whole agent.

Incompatibilists and compatibilists (mostly) agree that there is a strong intuition that a manipulated agent, i.e., an agent who is the victim of methods such as indoctrination or brainwashing, is unfree. They differ however on why exactly this intuition arises. Incompatibilists claim our intuitions in these cases are sensitive to the manipulated agent’s lack of ultimate control over her actions, while many compatibilists argue that our intuitions respond to damage inflicted by manipulation on the agent’s psychological and volitional capacities. Much hangs on this issue because manipulation-based arguments are among the most important for defending incompatibilist views of free will. In this paper, I investigate this issue from a experimental perspective, using a set of statistical methods well suited for identifying the features of hypothetical cases people’s intuitions are responding to. Results strongly support the compatibilist view—subjects’ tendency to judge that a manipulated agent is unfree was found to depend on their judgments that the agent suffers impairments to certain psychological/volitional capacities that compatibilists say are the basis for free will. I discuss the significance of these results for the use of manipulation cases in the philosophical debate about free will.

Recently, a number of philosophers have advanced a surprising conclusion: people's judgments about whether an agent brought about an outcome intentionally are pervasively influenced by normative considerations. In this paper, we investigate the 'Chairman case', an influential case from this literature and disagree with this conclusion. Using a statistical method called structural path modeling, we show that people's attributions of intentional action to an agent are driven not by normative assessments, but rather by attributions of underlying values and characterological dispositions to the agent. In a second study, we examined people's judgments about what they think drives asymmetric intuitions in the Chairman case and found that people are highly inaccurate in identifying which features of the case their intuitions track. In the final part of the paper, we discuss how the statistical methods used in this study can help philosophers with the critical features problem, the problem of figuring out which among the myriad features present in hypothetical cases are the critical ones that our intuitions are responsive to. We show how the methods used in this study have some advantages over both armchair methods used by traditional philosophers and survey methods used by experimental philosophers.

Making choices between payoffs available at different points in time reliably engages a decision-making brain circuit that includes medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and ventral striatum (VS). Previous neuroimaging studies produced differing accounts of the functions of these regions, including that these regions: (1) are sensitive to the value of rewards discounted by a function of delay ('subjective value'); (2) are differentially sensitive to the availability of an immediate reward; and (3) are implicated in impulsive decision-making. In this event-related fMRI study of 20 volunteers, these hypotheses were investigated simultaneously using a delay discounting task in which magnitude of rewards and stimulus type, i.e., the presence or absence of an immediate option, were independently varied, and in which participants' trait impulsivity was assessed with the Barratt Impulsiveness Scale. Results showed that mPFC, PCC, and VS are sensitive to the subjective value of rewards, whereas mPFC and PCC, but not VS, are sensitive to the presence of an immediate reward in the choice option. Moderation by individual differences in trait impulsivity was specific to the mPFC. Conjunction analysis showed significant overlap in mPFC and PCC for the main effects of subjective value and stimulus type, indicating these regions may serve multiple distinct roles during intertemporal decision-making. These findings significantly advance our understanding of the specificity and overlap of functions subserved by different regions involved in intertemporal decision-making, and help to reconcile conflicting accounts in the literature.

In this article, I survey four key questions about willpower: How is willpower possible? Why does willpower fail? How does willpower relate to other self-regulatory processes? and What are the connections between willpower and weakness of will? Empirical research into willpower is growing rapidly and yielding some fascinating new findings. This survey emphasizes areas in which empirical progress in understanding willpower helps to advance traditional philosophical debates.