Individual Differences In Brain Activity Research Articles

Linking caregiving quality during infancy to brain activity in early childhood and later executive function.

There is no relationship more vital than the one a child shares with their primary caregivers early in development. Yet many children worldwide are raised in settings that lack the warmth, connection, and stimulation provided by a responsive primary caregiver. In this study, we used data from the Bucharest Early Intervention Project (BEIP), a longitudinal study of institutionally-reared and family-reared children, to test how caregiving quality during infancy is associated with average EEG power over the first 3.5 years of life in alpha, beta, and theta frequency bands, and associations with later executive function (EF) at age 8 years. The sample comprised 189 children (129 institutionally-reared; 60 family-reared) who contributed data on observed caregiving quality during infancy (baseline; average age of 22 months), resting EEG power at baseline, 30, and 42 months, and performance-based data on a series of EF tasks at 8 years. Using Bayesian estimation, observed caregiving quality at baseline was marginally linked with higher average alpha and beta power, and lower theta power, from baseline to 42 months. In turn, higher average beta power and lower average theta power were marginally associated with higher EF at 8 years. In indirect effects models, higher caregiving quality at baseline was associated with higher EF at 8 years, with a marginal indirect effect through average theta power from baseline to 42 months. Variation in the quality of the early caregiving environment may be associated with later executive function, which is partially underpinned by individual differences in brain activity during early childhood. RESEARCH HIGHLIGHTS: Examined associations between caregiving quality during infancy, brain activity during early childhood, and executive function during mid-childhood in sample of never-institutionalized and institutionally-reared children. Significant associations between higher quality caregiving during infancy and higher executive function during middle childhood. Marginal associations between caregiving quality during infancy and brain activity during early childhood. Marginal associations between brain activity during early childhood and executive function during mid-childhood.

Explicit face memory abilities are positively related to the non-intentional encoding of faces: Behavioral and ERP evidence

Individual differences in face memory abilities have been shown to be related to individual differences in brain activity. The present study investigated brain-behavior relationships for the N250 component in event-related brain potentials, which is taken as a neural sign of face familiarity. We used a task in which a designated, typical target face and several (high- and low-distinctive) nontarget faces had to be distinguished during multiple presentations across a session. Separately, face memory/recognition abilities were measured with easy versus difficult tasks. We replicated an increase of the N250 amplitude to the target face across the session and observed a similar increase for the non-target faces, indicating the build-up of memory representations also for these faces. On the interindividual level, larger across-session N250 amplitude increases to low-distinctive non-target faces were related to faster face recognition as measured in an easy task. These findings indicate that non-intentional encoding of non-target faces into memory is associated with the swift recognition of explicitly learned faces; that is, there is shared variance of incidental and intentional face memory.

Composite Measures of Brain Activation Predict Individual Differences in Behavioral Stroop Interference.

The goal of the current study was to interrogate aspects of the cascade-of-control model [Banich, M. T. The Stroop effect occurs at multiple points along a cascade of control: Evidence from cognitive neuroscience approaches. Frontiers in Psychology, 10, 2164, 2019] (Banich, 2009), a neurocognitive model that posits how portions of pFC interact in a cascade-like manner to overcome interference from task-irrelevant information, and to test whether it could be used to predict individual differences in cognitive control outside the scanner. Participants (n = 62) completed two fMRI Word-Picture Stroop tasks, one containing emotional stimuli and one containing non-emotional stimuli, as well as a behavioral out-of-scanner Color-Word Stroop task at each of two time points. In a departure from the traditional approach of using a single task contrast to index neural activation across all ROIs, the current study utilized specific ROI by contrast pairings selected based on the specific level of control hypothesized by the cascade-of-control model to occur within that region. In addition, data across both tasks and both time points were combined to create composite measures of neural activation and of behavior. Consistent with the cascade-of-control model, individual differences in brain activation for specific contrasts within each of the three ROIs were associated with behavioral interference on the standard Color-Word Stroop task. Testing of alternative models revealed that these brain-behavior relationships were specific to the theoretically driven ROI by contrast pairings. Furthermore, such relationships were not observed across single-task and single-time point measures, but instead emerged from the composite measures. These findings provide evidence that brain activation observed across multiple regions of frontal cortex, each of which likely exerts cognitive control in a differential manner, is capable of predicting individual differences in behavioral performance.

Assessment of impaired consciousness using EEG-based connectivity features and convolutional neural networks.

Growing electroencephalogram (EEG) studies have linked the abnormities of functional brain networks with disorders of consciousness (DOC). However, due to network data's high-dimensional and non-Euclidean properties, it is difficult to exploit the brain connectivity information that can effectively detect the consciousness levels of DOC patients via deep learning. To take maximum advantage of network information in assessing impaired consciousness, we utilized the functional connectivity with convolutional neural network (CNN) and employed three rearrangement schemes to improve the evaluation performance of brain networks. In addition, the gradient-weighted class activation mapping (Grad-CAM) was adopted to visualize the classification contributions of connections among different areas. We demonstrated that the classification performance was significantly enhanced by applying network rearrangement techniques compared to those obtained by the original connectivity matrix (with an accuracy of 75.0%). The highest classification accuracy (87.2%) was achieved by rearranging the alpha network based on the anatomical regions. The inter-region connections (i.e., frontal-parietal and frontal-occipital connectivity) played dominant roles in the classification of patients with different consciousness states. The effectiveness of functional connectivity in revealing individual differences in brain activity was further validated by the correlation between behavioral performance and connections among specific regions. These findings suggest that our proposed assessment model could detect the residual consciousness of patients.

On the relationship between the social brain, social connectedness, and wellbeing.

The emergence of social neuroscience in the past two decades has offered a useful neurocognitive framework for understanding human social behavior. Of importance, social neuroscience research aimed to provide mechanistic explanations for the established link between wellbeing and social behavioral phenomena-particularly those reflective of social connectedness. Here, we provide an overview of the relevant literature focusing on recent work using functional magnetic resonance imaging (fMRI). In general, fMRI research demonstrated that aspects of social connectedness that are known to either positively (e.g., social acceptance) or negatively (e.g., social isolation) impact wellbeing also modulated the activity of subcortical reward system accordingly. Similar modulatory influence was found for the activity of other brain regions such as the medial prefrontal cortex, which are typically regarded as components of the "social brain" that support a wide range of functions related to social cognition and behavior. Elucidating such individual differences in brain activity may shed light onto the neural underpinnings of the link between social connectedness and wellbeing.

Adolescent novelty seeking is associated with greater ventral striatal and prefrontal brain response during evaluation of risk and reward.

Adolescence is a period during which reward sensitivity is heightened. Studies suggest that there are individual differences in adolescent reward-seeking behavior, attributable to a variety of factors, including temperament. This study investigated the neurobiological underpinnings of risk and reward evaluation as they relate to self-reported pleasure derived from novel experiences on the revised Early Adolescent Temperament Questionnaire (EATQ-R). Healthy participants (N = 265, ~50% male), aged 12-17 years, underwent functional magnetic resonance imaging during a modified Wheel of Fortune task, where they evaluated choices with varying probability of winning different monetary rewards. Across all participants, there was increased brain response in salience, reward, and cognitive control circuitry when evaluating choices with larger (compared with moderate) difference in risk/reward. Whole brain and a priori region-of-interest regression analyses revealed that individuals reporting higher novelty seeking had greater activation in bilateral ventral striatum, left middle frontal gyrus, and bilateral posterior cingulate cortex when evaluating the choices for largest difference in risk/reward. These novelty seeking associations with brain response were seen in the absence of temperament-related differences in decision-making behavior. Thus, while heightened novelty seeking in adolescents might be associated with greater neural sensitivity to risk/reward, accompanying increased activation in cognitive control regions might regulate reward-driven risk-taking behavior. More research is needed to determine whether individual differences in brain activation associated with novelty seeking are related to decision making in more ecologically valid settings.

Test-Retest Reliability of Neural Correlates of Response Inhibition and Error Monitoring: An fMRI Study of a Stop-Signal Task.

Response inhibition (RI) and error monitoring (EM) are important processes of adaptive goal-directed behavior, and neural correlates of these processes are being increasingly used as transdiagnostic biomarkers of risk for a range of neuropsychiatric disorders. Potential utility of these purported biomarkers relies on the assumption that individual differences in brain activation are reproducible over time; however, available data on test-retest reliability (TRR) of task-fMRI are very mixed. This study examined TRR of RI and EM-related activations using a stop signal task in young adults (n = 56, including 27 pairs of monozygotic (MZ) twins) in order to identify brain regions with high TRR and familial influences (as indicated by MZ twin correlations) and to examine factors potentially affecting reliability. We identified brain regions with good TRR of activations related to RI (inferior/middle frontal, superior parietal, and precentral gyri) and EM (insula, medial superior frontal and dorsolateral prefrontal cortex). No subcortical regions showed significant TRR. Regions with higher group-level activation showed higher TRR; increasing task duration improved TRR; within-session reliability was weakly related to the long-term TRR; motion negatively affected TRR, but this effect was abolished after the application of ICA-FIX, a data-driven noise removal method.

Context Matters: Situational Stress Impedes Functional Reorganization of Intrinsic Brain Connectivity during Problem-Solving.

Extensive research has established a relationship between individual differences in brain activity in a resting state and individual differences in behavior. Conversely, when individuals are engaged in various tasks, certain task-evoked reorganization occurs in brain functional connectivity, which can consequently influence individuals' performance as well. Here, we show that resting state and task-dependent state brain patterns interact as a function of contexts engendering stress. Findings revealed that when the resting state connectome was examined during performance, the relationship between connectome strength and performance only remained for participants under stress (who also performed worse than all other groups on the math task), suggesting that stress preserved brain patterns indicative of underperformance whereas non-stressed individuals spontaneously transitioned out of these patterns. Results imply that stress may impede the reorganization of a functional network in task-evoked brain states. This hypothesis was subsequently verified using graph theory measurements on a functional network, independent of behavior. For participants under stress, the functional network showed less topological alterations compared to non-stressed individuals during the transition from resting state to task-evoked state. Implications are discussed for network dynamics as a function of context.

Transient spectral events in resting state MEG predict individual task responses

Even in response to simple tasks such as hand movement, human brain activity shows remarkable inter-subject variability. Recently, it has been shown that individual spatial variability in fMRI task responses can be predicted from measurements collected at rest; suggesting that the spatial variability is a stable feature, inherent to the individual’s brain. However, it is not clear if this is also true for individual variability in the spatio-spectral content of oscillatory brain activity. Here, we show using MEG (N ​= ​89) that we can predict the spatial and spectral content of an individual’s task response using features estimated from the individual’s resting MEG data. This works by learning when transient spectral ‘bursts’ or events in the resting state tend to reoccur in the task responses. We applied our method to motor, working memory and language comprehension tasks. All task conditions were predicted significantly above chance. Finally, we found a systematic relationship between genetic similarity (e.g. unrelated subjects vs. twins) and predictability. Our approach can predict individual differences in brain activity and suggests a link between transient spectral events in task and rest that can be captured at the level of individuals.

Reconstruction of behavior-relevant individual brain activity: an individualized fMRI study.

Different patterns of brain activity are observed in various subjects across a wide functional domain. However, these individual differences, which are often neglected through the group average, are not yet completely understood. Based on the fundamental assumption that human behavior is rooted in the underlying brain function, we speculated that the individual differences in brain activity are reflected in the individual differences in behavior. Adopting 98 behavioral measures and assessing the brain activity induced at seven task functional magnetic resonance imaging states, we demonstrated that the individual differences in brain activity can be used to predict behavioral measures of individual subjects with high accuracy using the partial least square regression model. In addition, we revealed that behavior-relevant individual differences in brain activity transferred between different task states and can be used to reconstruct individual brain activity. Reconstructed individual brain activity retained certain individual differences which were lost in the group average and could serve as an individual functional localizer. Therefore, our results suggest that the individual differences in brain activity contain behavior-relevant information and should be included in group averaging. Moreover, reconstructed individual brain activity shows a potential use in precise and personalized medicine.

Influence of childhood adversity, approach motivation traits, and depression on individual differences in brain activation during reward anticipation

Reward anticipation dysfunction is associated with major depressive disorder (MDD), but is not universally observed in individuals with MDD. Reward anticipation deficits have also been linked to childhood adversity (CA) and approach/avoidance traits. The present study evaluated whether severity of CA (as measured by the Childhood Trauma Questionnaire) and approach/avoidance traits predict individual differences in blood oxygen level dependent (BOLD) response to reward anticipation beyond MDD diagnosis alone. Participants were individuals with MDD (n = 23) and healthy controls (n = 27). Multiple regression was conducted using CTQ scores, trait approach/avoidance scores, and diagnosis to predict activation during reward anticipation in a monetary incentive delay fMRI task. Across groups, higher trait reward responsiveness predicted increased activation in the hippocampus, cingulate cortex, and medial frontal gyrus. Greater CTQ scores predicted increased reward network activation. Overall, CTQ and reward responsiveness scores predicted more variance in reward anticipation activation than diagnosis. These findings suggest that clinicians should assess history of childhood adversity and trait reward responsiveness when treating individuals with MDD.

The relationship between heart rate and functional connectivity of brain regions involved in autonomic control

The peripheral autonomic nervous system (ANS) adjusts the heart rate (HR) to intrinsic and extrinsic demands. It is controlled by a group of functionally connected brain regions assembling the so-called central autonomic network (CAN). More specifically, forebrain cortical regions, limbic and brainstem structures within the CAN have been identified as important components of circuits involved in HR regulation. The present study aimed to investigate whether functional connectivity (FC) between these regions varies in subjects with different heart rates. Thus, 84 healthy subjects were separated according to their HR in slow, medium and fast. We observed a direct association between HR and FC in CAN regions, where stronger FC was related to slower HR. This relationship, however, is non-linear, follows an exponential course and is not restricted to CAN areas only. The network-based analysis (NBS) using time series from 262 independent anatomical ROIs revealed significantly increased functional connectivity in subjects with slow HR compared to subjects with fast HR mainly in regions being part of the salience network, but also of the default-mode network. We additionally simulated the effect of aliasing on the functional connectivity using several TRs and heart rates to exclude the possibility that FC differences might be due to different aliasing effects in the data. The result of the simulation indicated that aliasing cannot explain our findings.Thus, present results imply a functionally meaningful coupling between FC and HR that need to be accounted for in future studies. Moreover, given the established link between HR and emotional, cognitive and social processes, present findings may also be considered to explain individual differences in brain activation or connectivity when using corresponding paradigms in the MR scanner to investigate such processes.

Prefrontal cortex activation during a cognitive reappraisal task is associated with real-life negative affect reactivity.

The neural substrate of cognitive reappraisal has been well-mapped. Individuals who successfully downregulate negative affect (NA) by reshaping their thoughts about a potentially emotional situation show augmented activity in the prefrontal cortex (PFC), with attenuated activity in the amygdala. We performed functional neuroimaging with experience sampling to determine whether individual differences in brain activation correspond to differences in real-life NA. While being scanned, 69 female students (aged 18–25 years) were asked to perform a cognitive reappraisal task. In addition, repeated assessments (5/day, 14 days) of affect and minor events in real-life were conducted. Individual t-maps were created for an instructed downregulation contrast (downregulate negative–attend negative) and an uninstructed regulation contrast (attend negative–attend neutral). Mean beta values were extracted from a priori defined regions of interest in the bilateral amygdala and PFC and were correlated with three daily life NA measures: baseline (mean) NA, NA variability, and NA reactivity to negative events. Only one out of twelve correlations for the amygdalae was nominally significant, which did not survive correction for multiple comparisons. PFC activation in the instructed and uninstructed regulation contrasts explained approximately 10% of the variance in NA reactivity; stronger recruitment during the attend-negative condition was correlated with lower reactivity levels. The degree to which individuals spontaneously engage frontal clusters may be a critical aspect of real-life emotional reactivity. The findings of this study provide a partial external validation of the cognitive reappraisal task, suggesting that frontal brain activation during implicit task conditions may have the strongest connection with real-life behaviors.

Phonological Working Memory for Words and Nonwords in Cerebral Cortex.

The primary purpose of this study was to identify the brain bases of phonological working memory (the short-term maintenance of speech sounds) using behavioral tasks analogous to clinically sensitive assessments of nonword repetition. The secondary purpose of the study was to identify how individual differences in brain activation were related to participants' nonword repetition abilities. We used functional magnetic resonance imaging to measure neurophysiological response during a nonword discrimination task derived from standard clinical assessments of phonological working memory. Healthy adult control participants (N = 16) discriminated pairs of real words or nonwords under varying phonological working memory load, which we manipulated by parametrically varying the number of syllables in target (non)words. Participants' cognitive and phonological abilities were also measured using standardized assessments. Neurophysiological responses in bilateral superior temporal gyrus, inferior frontal gyrus, and supplementary motor area increased with greater phonological working memory load. Activation in left superior temporal gyrus during nonword discrimination correlated with participants' performance on standard clinical nonword repetition tests. These results suggest that phonological working memory is related to the function of cortical structures that canonically underlie speech perception and production.

P.6.d.006 - Gender differences in ‘impulsive choice’ and ‘impulsive action’ among opiate and stimulant users in protracted abstinence

Inhibition of prepotent responses plays a key role in cognitive executive control of goal-directed behavior. Response inhibition in Go/No-Go tasks elicits a distinct midfrontal ERP component, the N2, localized in previous studies to the anterior cingulate cortex. We assessed heritability of the No-Go N2 and the succeeding positive P3 component in 194 young female twins (52 monozygotic and 45 dizygotic pairs) who completed a cued version of the Continuous Performance Test. Genetic model-fitting analysis showed that about 60% of the variance in N2 and P3 amplitudes can be attributed to genetic factors, suggesting that frontal No-Go N2 and P3 components may index genetically transmitted individual differences in brain activity related to conflict processing and can potentially serve as endophenotypes for genetic studies of disorders characterized by neurobehavioral disinhibition.

Gain- and Loss-Related Brain Activation Are Associated with Information Search Differences in Risky Gambles: An fMRI and Eye-Tracking Study.

People differ in the way they approach and handle choices with unsure outcomes. In this study, we demonstrate that individual differences in the neural processing of gains and losses relates to attentional differences in the way individuals search for information in gambles. Fifty subjects participated in two independent experiments. Participants first completed an fMRI experiment involving financial gains and losses. Subsequently, they performed an eye-tracking experiment on binary choices between risky gambles, each displaying monetary outcomes and their respective probabilities. We find that individual differences in gain and loss processing relate to attention distribution. Individuals with a stronger reaction to gains in the ventromedial prefrontal cortex paid more attention to monetary amounts, while a stronger reaction in the ventral striatum to losses was correlated with an increased attention to probabilities. Reaction in the posterior cingulate cortex to losses was also found to correlate with an increased attention to probabilities. Our data show that individual differences in brain activity and differences in information search processes are closely linked.

Task-free MRI predicts individual differences in brain activity during task performance.

When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

Neurofeedback for Peak Performance Training

Neurofeedback has been found to be effective in the treatment of a number of clinical disorders, such as attention-deficit/hyperactivity disorder (ADHD/ADD) (Lubar, 2003), obsessive-compulsive disorder (Hammond, 2003), seizures (Sterman, 2000), and substance abuse (Burkett, Cummins, Dickson, & Skolnick, 2005; Saxby & Peniston, 1995). The benefits of neurofeedback have also been found useful in peak performance training. These benefits include improving attention/concentration, imagery, arousal level, and decreasing worry and rumination (Williams, 2006). The combination of cognitive, emotional, and psychophysiological benefits from neurofeedback results in improved performance. Due to individual differences in brain activity, as well as the large diversity of skills required in different sports, neurofeedback for performance training is not a “one size fits all” approach (Wilson, Thompson, Thompson, & Peper, 2011). In order to obtain optimal results, neurofeedback for peak performance training begins with appropriate assessment and evaluation of an individual's brain wave (electroencephalographic) activity. Individualized training plans are based upon the assessment findings and the specific needs of the targeted sport or activity (Wilson et al., 2011). This article will discuss the benefits and applications of neurofeedback for peak performance training and the importance of assessment to create effective training programs.

Diagnosing Developmental Dyscalculia on the Basis of Reliable Single Case FMRI Methods: Promises and Limitations

FMRI-studies are mostly based on a group study approach, either analyzing one group or comparing multiple groups, or on approaches that correlate brain activation with clinically relevant criteria or behavioral measures. In this study we investigate the potential of fMRI-techniques focusing on individual differences in brain activation within a test-retest reliability context. We employ a single-case analysis approach, which contrasts dyscalculic children with a control group of typically developing children. In a second step, a support-vector machine analysis and cluster analysis techniques served to investigate similarities in multivariate brain activation patterns. Children were confronted with a non-symbolic number comparison and a non-symbolic exact calculation task during fMRI acquisition. Conventional second level group comparison analysis only showed small differences around the angular gyrus bilaterally and the left parieto-occipital sulcus. Analyses based on single-case statistical procedures revealed that developmental dyscalculia is characterized by individual differences predominantly in visual processing areas. Dyscalculic children seemed to compensate for relative under-activation in the primary visual cortex through an upregulation in higher visual areas. However, overlap in deviant activation was low for the dyscalculic children, indicating that developmental dyscalculia is a disorder characterized by heterogeneous brain activation differences. Using support vector machine analysis and cluster analysis, we tried to group dyscalculic and typically developing children according to brain activation. Fronto-parietal systems seem to qualify for a distinction between the two groups. However, this was only effective when reliable brain activations of both tasks were employed simultaneously. Results suggest that deficits in number representation in the visual-parietal cortex get compensated for through finger related aspects of number representation in fronto-parietal cortex. We conclude that dyscalculic children show large individual differences in brain activation patterns. Nonetheless, the majority of dyscalculic children can be differentiated from controls employing brain activation patterns when appropriate methods are used.

Individual differences in rhythmic ability: Behavioral and neuroimaging investigations.

Rhythmic abilities vary widely in the general population, but little is known about the factors that give rise to this variability. One factor may be musical training. Another may be differences in auditory short-term memory (STM) capacity (the amount of auditory information that can be remembered over a few seconds). Finally, as rhythms with temporal regularity (e.g., a beat) are more easily remembered and reproduced, individual differences in sensitivity to regularity may contribute to rhythmic ability differences. To investigate the contribution of each of these factors to rhythm reproduction ability, we assessed auditory STM capacity (using digit and pseudoword span tasks), sensitivity (using the Beat Alignment Test [BAT]), and levels of musical training. Rhythmic ability was measured using a rhythm reproduction test. We found that STM capacity, sensitivity, and musical training predicted unique variance in rhythm reproduction performance. Using functional magnetic resonance imaging (MRI), we assessed individual differences in brain activity related to the previously measured auditory STM capacity, BAT score, musical training, and rhythmic ability, while participants performed a rhythm discrimination task. Activity in posterior superior temporal gyrus and middle temporal gyrus negatively correlated with auditory STM capacity. Positive correlations with BAT score were found in leftangular gyrus, supplementary motor area, and premotor cortex. Positive correlations with musical training were observed in leftposterior middle temporal gyrus, and negative correlations were observed in leftsupplementary motor area. The findings implicate both auditory and motor areas in factors that underlie individual differences in rhythmic ability.Keywords: music, timing, auditory perceptionSupplemental materials: http://dx.doi.org/10.1037/a0031188.suppAnecdotally, rhythmic ability is thought to vary widely across healthy individuals. Several individuals report having no sense of rhythm, and previous work has investigated individuals with specific rhythmic impairments or beat deafness (Foxton, Nandy, & Griffiths, 2006; Phillips-Silver et al., 2011). However, little work has specifically investigated and reported on the range of rhythmic ability in the general population, and the underlying causes of individual differences in rhythmic ability have yet to be fully elucidated. Three factors seem like promising candidates and form the focus of the current study. The first is auditory short-term memory (STM) capacity, as this has been shown to relate to rhythm reproduction, discrimination, and synchronization ability in previous work (Bailey & Penhune, 2010; Saito, 2001; Wallentin, Nielsen, Friis-Olivarius, Vuust, & Vuust, 2010). The second is sensitivity to the presence of regular temporal structure (e.g., structure). Rhythms that have a regular temporal structure are discriminated and reproduced better than irregular rhythms (Grahn & Brett, 2007; Patel, Iversen, Chen, & Repp, 2005); therefore, it is likely that individuals with better ability to detect this regularity (when it exists) should do better on rhythm tasks. The third factor is musical training. However, musical training may exert an indirect effect by influencing the aforementioned factors: musical training is associated with better auditory STM span (Bailey & Penhune, 2010; Saito, 2001; Wallentin et al., 2010), and seems likely to improve detection, although this has not been tested directly. Music also may have direct effects on rhythmic ability, such as providing a range of strategies for accurate rhythmic encoding and reproduction. The potential role of each of these factors will now be described and considered in more detail.Auditory STMMost models of auditory STM posit two components: one involved in representing the to-be-remembered items and the other involved in maintaining those representations (Baddeley & Hitch, 1974; Cowan, 1999). …