Computational modeling reveals strategic and developmental differences in the behavioral impact of reward across adolescence.

Studies of reward effects on behavior in adolescence typically rely on performance metrics that confound myriad cognitive and non-cognitive processes, making it challenging to determine which process is impacted by reward. The present longitudinal study applied the diffusion decision model to a reward task to isolate the influence of reward on response caution from influences of processing and motor speed. Participants completed three annual assessments from early to middle adolescence (N = 387, 55% female, Mage  = 12.1 at Wave 1; Mage  = 13.1 at Wave 2, Mage  = 14.1 at Wave 3) and three annual assessments in late adolescence (Mages  = 17.8, 18.9, 19.9). At each assessment, participants completed a two-choice reaction time task under conditions of no-reward and a block in which points were awarded for speeded accuracy. Reward reduced response caution at all waves, as expected, but had a greater impact as teens moved from early to middle adolescence. Simulations to identify optimal response caution showed that teens were overly cautious in early adolescence but became too focused on speed over accuracy by middle adolescence. By late adolescence, participants adopted response styles that maximized reward. Further, response style was associated with both internalizing and externalizing symptoms in early-to-middle adolescence, providing evidence for the construct validity of a diffusion model approach in this developmental period.

Effects of Acute Aerobic Exercise on Cognition and Constructs of Decision-Making in Adults With and Without Hypertension.

Hypertension accelerates brain aging, resulting in cognitive dysfunction with advancing age. Exercise is widely recommended for adults with hypertension to attenuate cognitive dysfunction. Whether acute exercise benefits cognitive function in this at-risk population is unknown. The purpose of this study was to compare the effects of acute aerobic exercise on cognitive function in 30 middle-aged hypertensive (HTN) and 30 age, sex, and body mass index (BMI)-matched non-HTN adults (56 ± 6 years, BMI 28.2 ± 2.9 kg/m2; 32 men). Subjects underwent cognitive testing pre/post 30-min cycling (≈55% peak oxygen consumption). Cognition was assessed using standard metrics of accuracy and reaction time (RT) across memory recognition, 2-back, and Flanker tasks. Behavioral data was further analyzed using drift-diffusion modeling to examine underlying components of decision-making (strength of evidence, caution, bias) and RT (non-decision time). Exercise elicited similar changes in cognitive function in both HTN and non-HTN groups (p > 0.05). Accuracy was unaltered for Flanker and 2-back tasks, while hits and false alarms increased for memory recognition post-exercise (p < 0.05). Modeling results indicated changes in memory hits/false alarms were due to significant changes in stimulus bias post-exercise. RT decreased for Flanker and memory recognition tasks and was driven by reductions in post-exercise non-decision time (p < 0.05). Our data indicate acute exercise resulted in similar, beneficial cognitive responses in both middle-age HTN and non-HTN adults, marked by unaltered task accuracy, and accelerated RT post-exercise. Additionally, drift-diffusion modeling revealed that beneficial acceleration of cognitive processing post-exercise (RT) is driven by changes in non-decision components (encoding/motor response) rather than the decision-making process itself.

Changes in cognitive function and latent processes of decision-making during incremental ascent to high altitude.

High altitude sojourn is broadly associated with impaired cognitive function, although there are inconsistencies within the literature. Incorporation of mathematical modeling to gain insight into latent aspects of decision-making may strengthen the ability to characterize changes in cognitive function during high altitude sojourn. This study sought to examine the effects of high altitude on cognitive function and underlying constructs of decision-making during an 11-d incremental ascent to 5160 m in 18 healthy adults (26 ±â€¯12 yrs). Participants underwent cognitive testing at 116 m, 3440 m, 4240 m, and 5160 m. Cognitive function was assessed using standard metrics of accuracy and reaction time (RT) during working memory (2-back) and attention (Flanker) tasks. Behavioral data were additionally analyzed using drift-diffusion modeling to interrogate latent neural (strength of evidence, non-decision time) and behavioral (caution, bias) processes of decision-making. Flanker accuracy was unaltered during incremental ascent to high altitude, while 2-back accuracy decreased at 5160 m (p < 0.01). RT was faster at 4240 m for the Flanker, and faster at all altitudes compared to 116 m for the 2-back (p < 0.01). Incremental ascent to high altitude elicited modest reductions in caution and non-decision time, increases in bias and strength of evidence for non-match items during the 2-back (0.04 ≥ p > 0.01). These data indicate that while RT may appear to improve during incremental ascent to high altitude, increases in speed may be driven by participants 1) accumulating less evidence before initiating a response (i.e., less cautious) and 2) preferentially attending to (more biased), and extracting more evidence from, frequent/easier stimuli, rather than improved processing per se. Taken together, changes in cognitive function during incremental ascent to high altitude may reflect subtle changes in neural and behavioral components of decision-making intended to reduce cognitive load and conserve brain resources under challenging environmental conditions.

The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models.

Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.

Individual differences in emotion processing: how similar are diffusion model parameters across tasks?

The goal of this study was to replicate findings of diffusion model parameters capturing emotion effects in a lexical decision task and investigating whether these findings extend to other tasks of implicit emotion processing. Additionally, we were interested in the stability of diffusion model parameters across emotional stimuli and tasks for individual subjects. Responses to words in a lexical decision task were compared with responses to faces in a gender categorization task for stimuli of the emotion categories: happy, neutral and fear. Main effects of emotion as well as stability of emerging response style patterns as evident in diffusion model parameters across these tasks were analyzed. Based on earlier findings, drift rates were assumed to be more similar in response to stimuli of the same emotion category compared to stimuli of a different emotion category. Results showed that emotion effects of the tasks differed with a processing advantage for happy followed by neutral and fear-related words in the lexical decision task and a processing advantage for neutral followed by happy and fearful faces in the gender categorization task. Both emotion effects were captured in estimated drift rate parameters-and in case of the lexical decision task also in the non-decision time parameters. A principal component analysis showed that contrary to our hypothesis drift rates were more similar within a specific task context than within a specific emotion category. Individual response patterns of subjects across tasks were evident in significant correlations regarding diffusion model parameters including response styles, non-decision times and information accumulation.

Is brain response to food rewards related to overeating? A test of the reward surfeit model of overeating in children.

The reward surfeit model of overeating suggests that heightened brain response to rewards contributes to overeating and subsequent weight gain. However, previous studies have not tested whether brain response to reward is associated with food intake, particularly during childhood, a period of dynamic development in reward and inhibitory control neurocircuitry. We conducted functional magnetic resonance imaging (fMRI) with 7-11-year-old children (n = 59; healthy weight, n = 31; overweight, n = 28; 54% female) while they played a modified card-guessing paradigm to examine blood-oxygen-level-dependent (BOLD) response to anticipating and winning rewards (food, money, neutral). Food intake was assessed at three separate meals that measured different facets of eating behavior: 1) typical consumption (baseline), 2) overindulgence (palatable buffet), and 3) eating in the absence of hunger (EAH). A priori regions of interest included regions implicated in both reward processing and inhibitory control. Multiple stepwise regressions were conducted to examine the relationship between intake and BOLD response to rewards. Corrected results showed that a greater BOLD response in the medial prefrontal cortex for anticipating food compared to money positively correlated with how much children ate at the baseline and palatable buffet meals. BOLD response in the dorsolateral prefrontal cortex for winning food compared to money was positively correlated with intake at the palatable buffet meal and EAH. All aforementioned relationships were independent of child weight status. Findings support the reward surfeit model by showing that increased brain response to food compared to money rewards positively correlates with laboratory measures of food intake in children.

Metastudies for robust tests of theory.

We describe and demonstrate an empirical strategy useful for discovering and replicating empirical effects in psychological science. The method involves the design of a metastudy, in which many independent experimental variables-that may be moderators of an empirical effect-are indiscriminately randomized. Radical randomization yields rich datasets that can be used to test the robustness of an empirical claim to some of the vagaries and idiosyncrasies of experimental protocols and enhances the generalizability of these claims. The strategy is made feasible by advances in hierarchical Bayesian modeling that allow for the pooling of information across unlike experiments and designs and is proposed here as a gold standard for replication research and exploratory research. The practical feasibility of the strategy is demonstrated with a replication of a study on subliminal priming.

Testing the validity of conflict drift-diffusion models for use in estimating cognitive processes: A parameter-recovery study.

Researchers and clinicians are interested in estimating individual differences in the ability to process conflicting information. Conflict processing is typically assessed by comparing behavioral measures like RTs or error rates from conflict tasks. However, these measures are hard to interpret because they can be influenced by additional processes like response caution or bias. This limitation can be circumvented by employing cognitive models to decompose behavioral data into components of underlying decision processes, providing better specificity for investigating individual differences. A new class of drift-diffusion models has been developed for conflict tasks, presenting a potential tool to improve analysis of individual differences in conflict processing. However, measures from these models have not been validated for use in experiments with limited data collection. The present study assessed the validity of these models with a parameter-recovery study to determine whether and under what circumstances the models provide valid measures of cognitive processing. Three models were tested: the dual-stage two-phase model (Hübner, Steinhauser, & Lehle, Psychological Review, 117(3), 759-784, 2010), the shrinking spotlight model (White, Ratcliff, & Starns, Cognitive Psychology, 63(4), 210-238, 2011), and the diffusion model for conflict tasks (Ulrich, Schröter, Leuthold, & Birngruber, Cogntive Psychology, 78, 148-174, 2015). The validity of the model parameters was assessed using different methods of fitting the data and different numbers of trials. The results show that each model has limitations in recovering valid parameters, but they can be mitigated by adding constraints to the model. Practical recommendations are provided for when and how each model can be used to analyze data and provide measures of processing in conflict tasks.

Decision mechanisms underlying mood-congruent emotional classification.

There is great interest in understanding whether and how mood influences affective processing. Results in the literature have been mixed: some studies show mood-congruent processing but others do not. One limitation of previous work is that decision components for affective processing and responses biases are not dissociated. The present study explored the roles of affective processing and response biases using a drift-diffusion model (DDM) of simple choice. In two experiments, participants decided if words were emotionally positive or negative while listening to music that induced positive or negative mood. The behavioural results showed weak, inconsistent mood-congruency effects. In contrast, the DDM showed consistent effects that were selectively driven by an a-priori bias in response expectation, suggesting that music-induced mood influences expectations about the emotionality of upcoming stimuli, but not the emotionality of the stimuli themselves. Implications for future studies of emotional classification and mood are subsequently discussed.

Electrophysiological correlates of the drift diffusion model in visual word recognition.

This study was designed to explore the electrophysiological correlates of the diffusion models drift rate parameter in cognitive decision making. Eighty-two participants completed a lexical decision task while their stimulus-dependent event-related potentials (ERP) and theta frequency band power were measured. A mass univariate approach was applied to examine the timeline at which correlations were evident. Individual differences in drift rate parameter and condition-wise within-subject differences in drift rates for word emotionality and item repetition were found to be related to amplitude differences in the late positive complex (LPC). No relations to theta frequency band power changes were obtained. The drift rate parameter captures information accumulation of noisy evidence, while LPC amplitudes are discussed to reflect the strength of a memory trace. While these results point to a common underlying cognitive mechanism to explain drift rates and LPC modulation, they also provide a new angle on the timeline of visual word processing following word identification. Further confirmations of the results are needed to approve the LPC as neurophysiological marker of information accumulation. Hum Brain Mapp 38:5616-5627, 2017. © 2017 Wiley Periodicals, Inc.

Effects of acute alcohol intoxication on executive functions controlling self-regulated behavior.

Alcohol consumption may lead to deficits in the executive functions that govern self-regulation. These deficits could lead to risk-taking behaviors; therefore, it is important to determine the magnitude of these deficits on executive functioning. The purpose of this experiment was to investigate the acute effects of alcohol on three of the executive functions that are hypothesized to affect self-regulation, which are inhibition, set shifting, and working memory, using a mixed-methods study design. The participants were 75 moderate or heavy drinkers between the ages of 21 and 35 who were randomized into one of three beverage conditions (control, placebo, or 0.65-g alcohol dose/kg body weight). Performance on working memory, set shifting, and inhibition were measured pre- and post-beverage consumption. The results showed only a significant interaction in the working memory data, as there was an increase in performance post-beverage relative to pre-beverage for the control participants as compared to the alcohol and placebo participants. It was concluded that the dose of alcohol (BAC = 0.063%) given to moderate to heavy drinkers was not sufficient to cause significant impairment in the executive functions tested. The results were further discussed and methodological concerns were considered, such as the low BAC achieved, practice effects, and insensitivity of tasks.

Acute Stimulant Treatment and Reinforcement Increase the Speed of Information Accumulation in Children with ADHD.

The current studies utilized drift diffusion modeling (DDM) to examine how reinforcement and stimulant medication affect cognitive task performance in children with ADHD. In Study 1, children with (n = 25; 88 % male) and without ADHD (n = 33; 82 % male) completed a 2-choice discrimination task at baseline (100 trials) and again a week later under alternating reinforcement and no-reinforcement contingencies (400 trials total). In Study 2, participants with ADHD (n = 29; 72 % male) completed a double-blind, placebo-controlled trial of 0.3 and 0.6 mg/kg methylphenidate and completed the same task utilized in Study 1 at baseline (100 trials). Children with ADHD accumulated information at a much slower rate than controls, as evidenced by a lower drift rate. Groups were similar in nondecision time and boundary separation. Both reinforcement and stimulant medication markedly improved drift rate in children with ADHD (ds = 0.70 and 0.95 for reinforcement and methylphenidate, respectively); both treatments also reduced boundary separation (ds = 0.70 and 0.39). Reinforcement, which emphasized speeded accuracy, reduced nondecision time (d = 0.37), whereas stimulant medication increased nondecision time (d = 0.38). These studies provide initial evidence that frontline treatments for ADHD primarily impact cognitive performance in youth with ADHD by improving the speed/efficiency of information accumulation. Treatment effects on other DDM parameters may vary between treatments or interact with task parameters (number of trials, task difficulty). DDM, in conjunction with other approaches, may be helpful in clarifying the specific cognitive processes that are disrupted in ADHD, as well as the basic mechanisms that underlie the efficacy of ADHD treatments.

Effect of hypoxia on cerebrovascular and cognitive function during moderate intensity exercise.

Exercise in hypoxia places added demands on the brain and cerebrovasculature that can impact cognitive function. The purpose of this study was to investigate the effect of acute hypoxia on cerebrovascular hemodynamics, markers of neuro-steroidal modulation and brain-blood barrier (BBB) integrity, and cognition during exercise. Thirty healthy participants (21±4yrs., BMI 24.0±2.6kg∙m(-2); 15 men) were randomized to both a≈2.5h normoxic (FiO2 20.0%) and hypoxic (FiO2 12.5%) condition on two separate days. After 1.25h, participants underwent 10min of exercise-alone (cycling at 55% HRmax) and 15min of exercise+cognitive testing. Prefrontal cortex (PFC) tissue oxygenation and middle cerebral artery (MCA) mean blood velocity (MnV) were measured using near-infrared spectroscopy and transcranial Doppler respectively at rest, during exercise-alone, and during exercise+cognitive testing. Salivary levels of dehydroepiandosterone [DHEA], DHEA-sulfate [DHEAS]) and neuron specific enolase (NSE) were measured pre and post exercise. Cognition was assessed using standard metrics of accuracy and reaction time (RT), and advanced metrics from drift-diffusion modeling across memory recognition, N-Back and Flanker tasks. MCA MnV increased from rest to exercise (p<0.01) and was unchanged with addition of cognitive testing during exercise in both normoxia and hypoxia. PFC oxygenation increased during exercise (p<0.05) and was further increased with addition of cognitive challenge in normoxia but decreased during exercise in hypoxia (p<0.05) with further reductions occurring with addition of cognitive tasks (p<0.05). DHEA and NSE increased and decreased post-exercise, respectively, in both normoxia and hypoxia (p<0.01). Accuracy on cognitive tasks was similar in normoxia compared to hypoxia, while RT was slower in hypoxia vs normoxia across memory recognition (p<0.01) and Flanker tasks (p=0.04). Drift-diffusion modeling suggested changes in memory RT were due to increases in caution (p<0.01). Overall cognitive performance is maintained during exercise in hypoxia concomitant with slower RT in select cognitive tasks and reduced oxygenation in the PFC. These changes were accompanied by slight increases in neuro-steroidal modulation but appear independent of changes in NSE, a biomarker of BBB integrity. Maintained accuracy and select increases in RT during hypoxic exercise may be related behavioral changes in caution.

Using Decision Models to Enhance Investigations of Individual Differences in Cognitive Neuroscience.

There is great interest in relating individual differences in cognitive processing to activation of neural systems. The general process involves relating measures of task performance like reaction times or accuracy to brain activity to identify individual differences in neural processing. One limitation of this approach is that measures like reaction times can be affected by multiple components of processing. For instance, some individuals might have higher accuracy in a memory task because they respond more cautiously, not because they have better memory. Computational models of decision making, like the drift-diffusion model and the linear ballistic accumulator model, provide a potential solution to this problem. They can be fitted to data from individual participants to disentangle the effects of the different processes driving behavior. In this sense the models can provide cleaner measures of the processes of interest, and enhance our understanding of how neural activity varies across individuals or populations. The advantages of this model-based approach to investigating individual differences in neural activity are discussed with recent examples of how this method can improve our understanding of the brain-behavior relationship.

Effect of acute nitrate supplementation on neurovascular coupling and cognitive performance in hypoxia.

The matching of oxygen supply to neural demand (i.e., neurovascular coupling (NVC)) is an important determinant of cognitive performance. The impact of hypoxia on NVC remains poorly characterized. NVC is partially modulated by nitric oxide (NO), which may initially decrease in hypoxia. This study investigated the effect of acute NO-donor (nitrate) supplementation on NVC and cognitive function in hypoxia. Twenty healthy men participated in this randomized, double-blind, crossover design study. Following normoxic cognitive/NVC testing, participants consumed either nitrate (NIT) or a NIT-depleted placebo (PLA). Participants then underwent 120 min of hypoxia (11.6% ± 0.1% O2) and all cognitive/NVC testing was repeated. NVC was assessed as change in middle cerebral artery (MCA) blood flow during a cognitive task (incongruent Stroop) using transcranial Doppler. Additional computerized cognitive testing was conducted separately to assess memory, executive function, attention, sensorimotor, and social cognition domains. Salivary nitrite significantly increased following supplementation in hypoxia for NIT (+2.6 ± 1.0 arbitrary units (AU)) compared with PLA (+0.2 ± 0.3 AU; p < 0.05). Memory performance (-6 ± 13 correct) significantly decreased (p < 0.05) in hypoxia while all other cognitive domains were unchanged in hypoxia for both PLA and NIT conditions (p > 0.05). MCA flow increased during Stroop similarly in normoxia (PLA +5 ± 6 cm·s(-1), NIT +7 ± 7 cm·s(-1)) and hypoxia (PLA +5 ± 9 cm·s(-1), NIT +6 ± 7 cm·s(-1)) (p < 0.05) and this increase was not altered by PLA or NIT (p > 0.05). In conclusion, acute hypoxia resulted in significant reductions in memory concomitant with preservation of executive function, attention, and sensorimotor function. Hypoxia had no effect on NVC. Acute NIT supplementation had no effect on NVC or cognitive performance in hypoxia.

Using decision models to decompose anxiety-related bias in threat classification.

Individuals with high levels of anxiety show preferential processing of threatening information, and this cognitive bias is thought to be an integral component of anxiety disorders. In threat classification tasks, this bias manifests as high-anxiety participants being more likely to classify stimuli as threatening than their low-anxiety counterparts. However, it is unclear which cognitive mechanisms drive this bias in threat classification. To better understand this phenomenon, threat classification data were analyzed with 2 decision models: a signal detection model and a drift-diffusion model. Signal detection models can dissociate measures of discriminability and bias, and diffusion models can further dissociate bias due to response preparation from bias due to stimulus evaluation. Individuals in the study completed a trait anxiety measure and classified threatening and neutral words based on whether they deemed them threatening. Signal detection analysis showed that high-anxiety participants had a bias driven by a weaker threat criterion than low-anxiety participants, but no differences in discriminability. Drift-diffusion analysis further decomposed the threat bias to show that it is driven by both an expectation bias that the threat response was more likely to be correct, and a stimulus bias driven by a weaker criterion for evaluating the stimuli under consideration. These model-based analyses provide valuable insight and show that multiple cognitive mechanisms underlie differential threat processing in anxiety. Implications for theories of anxiety are discussed.

Anxiety-related threat bias in recognition memory: the moderating effect of list composition and semantic-similarity effects.

Individuals with high anxiety show bias for threatening information, but it is unclear whether this bias affects memory. Recognition memory studies have shown biases for recognising and rejecting threatening items in anxiety, prompting the need to identify moderating factors of this effect. This study focuses on the role of semantic similarity: the use of many semantically related threatening words could increase familiarity for those items and obscure anxiety-related differences in memory. To test this, two recognition memory experiments varied the proportion of threatening words in lists to manipulate the semantic-similarity effects. When similarity effects were reduced, participants with high trait anxiety were biased to respond "new" to threatening words, whereas when similarity effects were strong there was no effect of anxiety on memory bias. Analysis of the data with the drift diffusion model showed that the bias was due to differences in processing of the threatening stimuli rather than a simple response bias. These data suggest that the semantic similarity of the threatening words significantly affects the presence or absence of anxiety-related threat bias in recognition memory. The results indicate that trait anxiety is associated with a bias to decide that threatening stimuli were not previously studied, but only when semantic-similarity effects are controlled. Implications for theories of anxiety and future studies in this domain are discussed.

Multiple brain networks contribute to the acquisition of bias in perceptual decision-making.

Bias occurs in perceptual decisions when the reward associated with a particular response dominates the sensory evidence in support of a choice. However, it remains unclear how this bias is acquired and once acquired, how it influences perceptual decision processes in the brain. We addressed these questions using model-based neuroimaging in a motion discrimination paradigm where contextual cues suggested which one of two options would receive higher rewards on each trial. We found that participants gradually learned to choose the higher-rewarded option in each context when making a perceptual decision. The amount of bias on each trial was fit well by a reinforcement-learning model that estimated the subjective value of each option within the current context. The brain mechanisms underlying this bias acquisition process were similar to those observed in reward-based decision tasks: prediction errors correlated with the fMRI signals in ventral striatum, dlPFC, and parietal cortex, whereas the amount of acquired bias correlated with activity in ventromedial prefrontal (vmPFC), dorsolateral frontal (dlPFC), and parietal cortices. Moreover, psychophysiological interaction analysis revealed that as bias increased, functional connectivity increased within multiple brain networks (dlPFC-vmPFC-visual, vmPFC-motor, and parietal-anterior-cingulate), suggesting that multiple mechanisms contribute to bias in perceptual decisions through integration of value processing with action, sensory, and control systems. These provide a novel link between the neural mechanisms underlying perceptual and economic decision-making.

Decomposing decision components in the stop-signal task: a model-based approach to individual differences in inhibitory control.

The stop-signal task, in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision making, a drift-diffusion model of simple decisions was fitted to stop-signal task data from go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the go stimulus correlated with greater activation in the right frontal pole for both go and stop trials. On stop trials, stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and BG. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology.

Memory bias for negative emotional words in recognition memory is driven by effects of category membership.

Recognition memory studies often find that emotional items are more likely than neutral items to be labelled as studied. Previous work suggests this bias is driven by increased memory strength/familiarity for emotional items. We explored strength and bias interpretations of this effect with the conjecture that emotional stimuli might seem more familiar because they share features with studied items from the same category. Categorical effects were manipulated in a recognition task by presenting lists with a small, medium or large proportion of emotional words. The liberal memory bias for emotional words was only observed when a medium or large proportion of categorised words were presented in the lists. Similar, though weaker, effects were observed with categorised words that were not emotional (animal names). These results suggest that liberal memory bias for emotional items may be largely driven by effects of category membership.