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Executive function (EF) refers as to a set of high-level cognitive abilities that are critical to many aspects of daily life. Despite its importance in human daily life, the neural networks responsible for the development of EF in childhood are not well understood. The present study thus aimed to examine the development of task-dependent brain network organization and its relationship to age-related improvements in EF. To address this issue, we recruited eighty-eight Chinese children ranging in age from 7 to 12 years old, and collected their functional magnetic resonance imaging (fMRI) data when they performed an EF task. By utilizing graph theory, we found that the task-dependent brain network modules became increasingly segregated with age. Specifically, the intra-module connections within the default-mode network (DMN), frontal-parietal network (FPN) and sensorimotor network (SMN) increased significantly with age. In contrast, the inter-module connections of the visual network to both the FPN/SMN decreased significantly with age. Most importantly, modular segregation of the FPN significantly mediated the relationship between age and EF performance. These findings add to our growing understanding of how development changes in task-dependent brain network organization support vast behavioral improvements in EF observed during childhood.

Despite extensive research into executive function (EF), the precise relationship between brain dynamics and flexible cognition remains unknown. Using a large, publicly available dataset (189 participants), we find that functional connections measured throughout 56 minutes of resting state fMRI data comprise five distinct connectivity states. Elevated EF performance as measured outside of the scanner was associated with greater episodes of more frequently occurring connectivity states, and fewer episodes of less frequently occurring connectivity states. Frequently occurring states displayed metastable properties, where cognitive flexibility may be facilitated by attenuated correlations and greater functional connection variability. Less frequently occurring states displayed properties consistent with low arousal and low vigilance. These findings suggest that elevated EF performance may be associated with the propensity to occupy more frequently occurring brain configurations that enable cognitive flexibility, while avoiding less frequently occurring brain configurations related to low arousal/vigilance states. The current findings offer a novel framework for identifying neural processes related to individual differences in executive function.

Executive function is a quintessential human capacity that emerges late in development and displays different developmental trends in males and females. Sex differences in executive function in youth have been linked to vulnerability to psychopathology as well as to behaviors that impinge on health, wellbeing, and longevity. Yet, the neurobiological basis of these differences is not well understood, in part due to the spatiotemporal complexity inherent in patterns of brain network maturation supporting executive function. Here we test the hypothesis that sex differences in impulsivity in youth stem from sex differences in the controllability of structural brain networks as they rewire over development. Combining methods from network neuroscience and network control theory, we characterize the network control properties of structural brain networks estimated from diffusion imaging data acquired in males and females in a sample of 879 youth aged 8-22 years. We summarize the control properties of these networks by estimating average and modal controllability, two statistics that probe the ease with which brain areas can drive the network towards easy versus difficult-to-reach states. We find that females have higher modal controllability in frontal, parietal, and subcortical regions while males have higher average controllability in frontal and subcortical regions. Furthermore, controllability profiles in males are negatively related to the false positive rate on a continuous performance task, a common measure of impulsivity. Finally, we find associations between average controllability and individual differences in activation during an n-back working memory task. Taken together, our findings support the notion that sex differences in the controllability of structural brain networks can partially explain sex differences in executive function. Controllability of structural brain networks also predicts features of task-relevant activation, suggesting the potential for controllability to represent context-specific constraints on network state more generally.

The goal of the present study was to examine relationships between individual differences in resting state functional connectivity as ascertained by fMRI (rs-fcMRI) and performance on tasks of executive function (EF), broadly defined as the ability to regulate thoughts and actions. Unlike most previous research that focused on the relationship between rs-fcMRI and a single behavioral measure of EF, in the current study we examined the relationship of rs-fcMRI with individual differences in subcomponents of EF. Ninety-one adults completed a resting state fMRI scan and three separate EF tasks outside the magnet: inhibition of prepotent responses, task set shifting, and working memory updating. From these three measures, we derived estimates of common aspects of EF, as well as abilities specific to working memory updating and task shifting. Using Independent Components Analysis (ICA), we identified across the group of participants several networks of regions (Resting State Networks, RSNs) with temporally correlated time courses. We then used dual regression to explore how these RSNs covaried with individual differences in EF. Dual regression revealed that increased higher common EF was associated with connectivity of a) frontal pole with an attentional RSN, and b) Crus I and II of the cerebellum with the right frontoparietal RSN. Moreover, higher shifting-specific abilities were associated with increased connectivity of angular gyrus with a ventral attention RSN. The results of the current study suggest that the organization of the brain at rest may have important implications for individual differences in EF, and that individuals higher in EF may have expanded resting state networks as compared to individuals with lower EF.

Diffusion magnetic resonance imaging is increasingly used as a non-invasive method to investigate white matter structure in neurological and neuropsychiatric disease. However, many options are available for the acquisition sequence and analysis method. Here we used Parkinson's disease as a model neurodegenerative disorder to compare imaging protocols and analysis options. We investigated fractional anisotropy and mean diffusivity of white matter in patients and age-matched controls, comparing two datasets acquired with different imaging protocols. One protocol prioritised the number of b value acquisitions, whilst the other prioritised the number of gradient directions. The dataset with more gradient directions was more sensitive to reductions in fractional anisotropy in Parkinson's disease, whilst the dataset with more b values was more sensitive to increases in mean diffusivity. Moreover, the areas of reduced fractional anisotropy were highly similar to areas of increased mean diffusivity in PD patients. Next, we compared two widely used analysis methods: tract-based spatial statistics identified reduced fractional anisotropy and increased mean diffusivity in Parkinson's disease in many of the major white matter tracts in the frontal and parietal lobes. Voxel-based analyses were less sensitive, with similar patterns of white matter pathology observed only at liberal statistical thresholds. We also used tract-based spatial statistics to identify correlations between a test of executive function (phonemic fluency), fractional anisotropy and mean diffusivity in prefrontal white matter in both Parkinson's disease patients and controls. These findings suggest that in Parkinson's disease there is widespread pathology of cerebral white matter, and furthermore, pathological white matter in the frontal lobe may be associated with executive dysfunction. Diffusion imaging protocols that prioritised the number of directions versus the number of b values were differentially sensitive to alternative markers of white matter pathology, such as fractional anisotropy and mean diffusivity., Highlights ► DTI shows abnormal frontal white matter in Parkinson's disease. ► FA and MD in the frontal lobe correlate with executive function in PD. ► The number of directions and b values affects sensitivity to FA/MD changes in PD. ► TBSS is more sensitive than VBM to white matter change in Parkinson's disease.

Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals.

Research on the processing of objects at different hierarchical levels has suggested that understanding superordinate concepts (e.g. fruit), relative to basic level concepts (e.g. apple), requires greater semantic control demands. Yet, it is unclear which factors underlie this difference in executive processing. We built on previous research showing that superordinate concepts have less shared features among their members and therefore may involve higher semantic control requirements. To test this hypothesis, we developed an fMRI study in which we orthogonally manipulated feature sharedness (more shared vs. less shared) and concept level (superordinate vs. basic) in a sentence verification task. Sentences involving less shared features, relative to more shared features, significantly engaged the L lateral PFC. Importantly, sentences that included superordinate concepts, relative to those with basic level concepts, also revealed a stronger response in L lateral PFC, along with posterior temporal gyrus activation. There was also a significant interaction between feature sharedness and concept level in several PFC regions and L posterior temporal areas. The results suggest that relative to basic level concepts, processing superordinate concepts requires extra semantic control in L lateral PFC to coordinate information that is less shared by other members of the category level. These findings demonstrate that feature sharedness impacts the neural basis of semantic knowledge, and is a critical dimension in the processing of superordinate concepts.

Despite the practical implication of mild exercise, little is known about its influence on executive function and its neural substrates. To address these issues, the present study examined the effect of an acute bout of mild exercise on executive function and attempted to identify potential neural substrates using non-invasive functional near-infrared spectroscopy (fNIRS). Twenty-five young individuals performed a color-word matching Stroop task (CWST) and a two-dimensional scale to measure changes of psychological mood states both before and after a 10-minute exercise session on a cycle ergometer at light intensity (30% v(·)o2peak) and, for the control session, without exercise. Cortical hemodynamic changes in the prefrontal area were monitored with fNIRS during the CWST in both sessions. The acute bout of mild exercise led to improved Stroop performance, which was positively correlated with increased arousal levels. It also evoked cortical activations regarding Stroop interference on the left dorsolateral prefrontal cortex and frontopolar area. These activations significantly corresponded with both improved cognitive performance and increased arousal levels. Concurrently, this study provides empirical evidence that an acute bout of mild exercise improves executive function mediated by the exercise-induced arousal system, which intensifies cortical activation in task-related prefrontal sub-regions.

Dynamic networking of brain regions is suggested to be one of the key factors involved in various brain computations. Central executive function typically requires instantaneous coordination among the medial prefrontal regions and other distant regions, depending on the on-going task situation. In human scalp-recorded electroencephalography (EEG), the medial prefrontal area is estimated to be the current source of the theta rhythm, while there is no direct evidence that the theta rhythm is involved in the dynamic networking of central executive circuits. Here we hypothesize that the central executive circuit over the prefrontal and task-related cortices is dynamically linked by theta synchronization. By using simultaneous functional magnetic resonance imaging (fMRI) and EEG, we elucidated cortical circuits emerging with theta phase synchronization during free pacing repeated subtraction. Theta phase synchronization in the scalp EEG was found to emerge at two major clusters of electrode pairs, between the right frontal and left parietal sites and between the frontal and right parietal sites. The phase synchronization of two clusters is accompanied by fMRI responses in the cortical regions responsible for central executive function, working memory, visual imagery and cognitive action sequence. Here we report the first evidence that theta phase synchronization dynamically coordinates the central executive circuits, including the medial prefrontal cortex and relevant cortical regions.

Using fMRI, neural substrates of the executive system were investigated with respect to differences in working memory capacity. To explore the executive control processes, reading span test (RST) and read conditions were performed. Two subject groups were selected: those with large working memory capacities, labeled high-span subjects (HSS) according to the reading span test, and those with small working memory capacities, labeled low-span subjects (LSS). Significant activation was found mainly in three regions in comparison with the control: anterior cingulate cortex (ACC), left inferior frontal gyrus (IFG), visual association cortex (VAC) and superior parietal lobule (SPL). For both groups, the fMRI signal intensity increased in ACC and IFG during the RST condition compared to that under the read condition. A group difference was also found in the ACC and IFG region, specifically a significant increase in signal intensity was observed only for the HSS group but not for the LSS group. Behavioral data also showed that the performance was better in HSS than in LSS. Moreover, the cross correlation of signal change between ACC and IFG was higher in HSS than in LSS, indicating that the network system between ACC and IFG was more activated in HSS compared to that of LSS. These results suggest that executive function, that is, working attention controlling system is more active in HSS than in LSS. Moreover, the results confirmed our hypothesis that there is a general neural basis for the central executive function in both RST and previous LST (listening span test) tasks despite differences in modality-specific buffers.

Executive functions, such as working memory, must intersect with functions that determine value for the organism. Functional imaging work in humans and single-unit recordings in non-human primates provide evidence that PFC might integrate motivational context with working memory. With functional magnetic resonance imaging (fMRI), we addressed the question of motivation and working memory, using a trial-related design in an object-working memory task. The design permitted the analysis of BOLD signal at separate stages, corresponding to encoding, maintenance, and retrieval. Subjects were motivated by a financial incentive during the task, such that they could gain a high or a low reward. The two different levels of reward also entailed greater or lesser risk of losing money for incorrect responses. In the high, relative to the low, reward condition, subjects shifted response bias, and showed a trend to greater sensitivity. We found main effects in fMRI BOLD signal for reward, which overlapped with BOLD effects for maintenance of information, in the right superior frontal sulcus and bilateral intraparietal sulcus. We also found an interaction between reward and retrieval from working memory in the right dorsolateral prefrontal cortex. Main effects of load and reward occurred in adjacent regions of the ventrolateral PFC during retrieval. The data demonstrate that when subjects perform a simple working memory task, financial incentives motivate performance and interact with some of the same neural networks that process various stages of working memory. Areas of overlap and interaction may integrate information about value, or they may represent a general effect of motivation increasing neural effort.

A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking. One of the EEG signatures of performance monitoring in response to events signaling the need to adjust motor responses, are error-related potential (error-ERP) features. To examine whether error-ERP features may index executive control during gait adaptation, we analyzed high-density (108-channel) EEG data from an auditory gait pacing study. Participants (N = 18) walking on a steadily moving treadmill were asked to step in time to an auditory cue tone sequence, and then to quickly adapt their step length and rate, to regain step-cue synchrony following occasional unexpected shifts in the pacing cue train to a faster or slower cue tempo. Decomposition of the continuous EEG data by independent component analysis revealed a negative deflection in the source-resolved event-related potential (ERP) time locked to ‘late’ cue tones marking a shift to a slower cue tempo. This vertex-negative ERP feature, localized primarily to posterior medial frontal cortex (pMFC) and peaking 250 ms after the onset of the tempo-shift cue, we here refer to as the step-cue delay negativity (SDN). SDN source, timing, and polarity resemble other error-related ERP features, e.g., the Error-Related Negativity (ERN) and Feedback-Related Negativity (FRN) in (seated) button press response tasks. In single trials, SDN amplitude varied with the magnitude of the cue latency deviation (the time interval between the expected and actual cue onsets). Regression analysis also identified linear coupling between SDN amplitude and the subsequent speed of gait tempo adaptation (as measured by the increase in length of the ensuing adaptation step). The SDN in this paradigm thus seems both to index the perceived need for and the subsequent magnitude of the immediate gait adjustment, consistent with performance-monitoring models. Future research might investigate relationships of these control processes to the impairment of gait adjustment in motor disorders and cognitive decline, for example to develop a biomarker for fall risk prediction in early-stage Parkinson's.

Aberrant patterns of brain functional connectivity in the default mode network (DMN) have been observed across different classes of substance use disorder (SUD) and are associated with craving and relapse. In addicted individuals resting functional connectivity (RSFC) of the anterior DMN, which participates in attribution of personal value and emotional regulation, tends to be decreased, whereas RSFC of the posterior DMN, which directs attention to the internal world, tends to be increased. Aberrant RSFC within the DMN is believed to contribute to impaired self-awareness, negative emotions and to ruminations in addiction. Additionally, the disrupted connectivity between DMN and cortical regions involved with executive function, memory and emotion could be critical to drug-taking regardless of negative consequences and to stress-triggered relapse. At the system level, the dynamics of DMN interactions with the executive control and the salience networks are also disturbed in addiction. The DMN is prominently engaged during the withdrawal and preoccupation phases of the addiction cycle at the expense of the executive control network and with an enhanced participation of the salience network. In contrast, DMN prominence appears to be transitorily decreased during the intoxication phases. There is also growing evidence that disruption of the DMN in addiction reflects in part changes in dopaminergic, glutamatergic, and GABAergic signaling associated with acute and chronic drug use. Findings are starting to reveal DMN RSFC as a potential biomarker for predicting clinical outcomes in SUD and identify the DMN as a promising target for the treatment of addiction.

Social relationships change across the lifespan as social networks narrow and motivational priorities shift to the present. Interestingly, aging is also associated with changes in executive function, including decision-making abilities, but it remains unclear how age-related changes in both domains interact to impact financial decisions involving other people. To study this problem, we recruited 50 human participants (Nyounger = 26, ages 18-34; Nolder = 24, ages 63-80) to play an economic trust game as the investor with three partners (friend, stranger, and computer) who played the role of investee. Investors underwent functional magnetic resonance imaging (fMRI) during the trust game while investees were seated outside of the scanner. Building on our previous work with younger adults showing both enhanced striatal responses and altered default-mode network (DMN) connectivity as a function of social closeness during reciprocated trust, we predicted that these relations would exhibit age-related differences. We found that striatal responses to reciprocated trust from friends relative to strangers and computers were blunted in older adults relative to younger adults, thus supporting our primary pre-registered hypothesis regarding social closeness. We also found that older adults exhibited enhanced DMN connectivity with the temporoparietal junction (TPJ) during reciprocated trust from friends compared to computers while younger adults exhibited the opposite pattern. Taken together, these results advance our understanding of age-related differences in sensitivity to social closeness in the context of trusting others.

Growing evidence suggests that both the medial prefrontal cortex (mPFC) and the subthalamic nucleus (STN) play crucial roles in conflict processing, but how these two structures coordinate their activities remains poorly understood. We simultaneously recorded electroencephalogram from the mPFC and local field potentials from the STN using deep brain stimulation electrodes in 13 Parkinson's disease patients while they performed a Stroop task. Both mPFC and STN showed significant increases in theta activities (2-8 Hz) in incongruent trials compared to the congruent trials. The theta activity in incongruent trials also demonstrated significantly increased phase synchronization between mPFC and STN. Furthermore, the amplitude of gamma oscillation was modulated by the phase of theta activity at the STN in incongruent trials. Such theta-gamma phase-amplitude coupling (PAC) was much stronger for incongruent trials with faster reaction times than those with slower reaction times. Elevated theta-gamma PAC in the STN provides a novel mechanism by which the STN may operationalize its proposed “hold-your-horses” role. The co-occurrence of mPFC-STN theta phase synchronization and STN theta-gamma PAC reflects a neural substrate for fronto-subthalamic communication during conflict processing. More broadly, it may be a general mechanism for neuronal interactions in the cortico-basal ganglia circuits via a combination of long-range, within-frequency phase synchronization and local cross-frequency PAC.

Studies of occipital cortex plasticity in blindness provide insight into how intrinsic constraints interact with experience to determine cortical specialization. We tested the cognitive nature and anatomical origins of occipital responses during non-verbal, non-spatial auditory tasks. In a go/no-go task, congenitally blind (N=23) and sighted (N=24) individuals heard rapidly occurring (

Cognitive trajectories vary greatly across older individuals, and the neural mechanisms underlying these differences remain poorly understood. Here, we investigate the cognitive variability in older adults by linking the influence of white matter microstructure on the task-related organization of fast and effective communications between brain regions. Using diffusion tensor imaging and electroencephalography, we show that individual differences in white matter network organization are associated with network clustering and efficiency in the alpha and high-gamma bands, and that functional network dynamics partly explain individual differences in cognitive control performance in older adults. We show that older individuals with high versus low structural network clustering differ in task-related network dynamics and cognitive performance. These findings were corroborated by investigating magnetoencephalography networks in an independent dataset. This multimodal (fMRI and biological markers) brain connectivity framework of individual differences provides a holistic account of how differences in white matter microstructure underlie age-related variability in dynamic network organization and cognitive performance.

Available online 30 April 2019. Behavioral adaptations during performance rely on predicting and evaluating the consequences of our actions through action monitoring. Previous studies revealed that proprioceptive and exteroceptive signals contribute to error-monitoring processes, which are implemented in the posterior medial frontal cortex. Interestingly, errors also trigger changes in autonomic nervous system activity such as pupil dilation or heartbeat deceleration. Yet, the contribution of implicit interoceptive signals of bodily states to error-monitoring during ongoing performance has been overlooked. This study investigated whether cardiovascular interoceptive signals influence the neural correlates of error processing during performance, with an emphasis on the early stages of error processing. We recorded musicians’ electroencephalography and electrocardiogram signals during the performance of highly-trained music pieces. Previous event-related potential (ERP) studies revealed that pitch errors during skilled musical performance are preceded by an error detection signal, the pre-error-negativity (preERN), and followed by a later error positivity (PE). In this study, by combining ERP, source localization and multivariate pattern classification analysis, we found that the error-minus-correct ERP waveform had an enhanced amplitude within 40–100 ms following errors in the systolic period of the cardiac cycle. This component could be decoded from single-trials, was dissociated from the preERN and PE, and stemmed from the inferior parietal cortex, which is a region implicated in cardiac autonomic regulation. In addition, the phase of the cardiac cycle influenced behavioral alterations resulting from errors, with a smaller post-error slowing and less perturbed velocity in keystrokes following pitch errors in the systole relative to the diastole phase of the cardiac cycle. Lastly, changes in the heart rate anticipated the upcoming occurrence of errors. This study provides the first evidence of preconscious visceral information modulating neural and behavioral responses related to early error monitoring during skilled performance. The study was supported by Goldsmiths University of London, the British Academy, through grant SG161006, and the German Research Foundation, through project HE 6013/1-2 to MHR.

Warning stimuli in sensorimotor tasks induce a state of preparedness characterized by increased alertness, focused attention and immobility. This state of attentive anticipation is associated with heart rate deceleration. Ageing affects the amplitude of the anticipatory cardiac deceleration responses; yet, the impact of this physiological change on cognitive performance is still to be elucidated. In fact, how cardiac deceleration relates to brain function and cognitive performance in the context of perceptual decision-making and different levels of decision complexity remains unknown. Here, we aimed to investigate the relationship between cardiac deceleration, brain function, and performance in perceptual decision tasks and how these associate with age-related changes. We measured simultaneously the electrocardiogram, the pupilogram, and the electroencephalogram in 36 young and 39 older adults, while they were engaged in two auditory cued reaction time tasks: a detection task and a go/no-go task requiring inhibitory control. We observed robust cardiac deceleration responses that increased with increasing task complexity. Notably, stronger modulation of the cardiac response across tasks was associated with the ability to maintain response speed as decision complexity increased suggesting a link between cardiac deceleration and facilitation of perceptual decisions. Additionally, cardiac deceleration appears to have a cortical origin as it correlated with frontocentral event-related potentials. In contrast, beta oscillations at baseline and task-related beta suppression were not predictive of cardiac deceleration suggesting a dissociation between sensorimotor oscillatory activity and this cardiac response. Importantly, we found age-related changes in anticipatory cardiac deceleration associated with deficits in perceptual decision-making.

For bilinguals, language control is needed for selecting the target language during language production. Numerous studies have examined the neural correlates of language control and shown a close relationship between language control and domain-general cognitive control. However, it remains unknown how these brain regions coordinate with each other when bilinguals exert cognitive control over linguistic and nonlinguistic representations. We addressed this gap using an extended unified structural equation modeling (euSEM) approach. Sixty-five Chinese-English bilinguals performed language switching and nonverbal switching tasks during functional magnetic resonance imaging (fMRI) scanning. The results showed that language control was served by a cooperative brain network, including the frontal lobe, the parietal cortex, subcortical areas, and the cerebellum. More importantly, we found that language control recruited more subcortical areas and connections from frontal to subcortical areas compared with domain-general cognitive control, demonstrating a reconfigurable brain network. In addition, the reconfiguration efficiency of the brain network was mainly determined by general cognitive ability but was also mediated by second language (L2) proficiency. These findings provide the first data-driven connectivity model that specifies the brain network for language control in bilinguals and also shed light on the relationship between language control and domain-general cognitive control.

Structural and functional analyses of the human claustrum, a poorly understood telencephalic gray matter structure, are hampered by its sheet-like anatomical arrangement. Here, we first describe a functional magnetic resonance imaging (fMRI) method to reveal claustrum signal with no linear relationship with adjacent regions in human subjects. We applied this approach to resting state functional connectivity (RSFC) analysis of the claustrum at high resolution (1.5 mm isotropic voxels) using a 7T dataset (n = 20) and a separate 3T dataset for replication (n = 35). We then assessed claustrum activation during performance of a cognitive task, the multi-source interference task, at 3T (n = 33). Extensive functional connectivity was observed between claustrum and cortical regions associated with cognitive control, including anterior cingulate, prefrontal and parietal cortices. Cognitive task performance was associated with widespread activation and deactivation that overlapped with the cortical areas showing functional connectivity to the claustrum. Furthermore, during high cognitive conflict conditions of the task, the claustrum was significantly activated at the onset of the task, but not during the remainder of the difficult condition. Both of these findings suggest that the human claustrum can be functionally isolated with fMRI, and that it may play a role in cognitive control, and specifically task switching, independent of sensorimotor processing.

Reward learning has the ability to bias both attention and behaviour. The current study presents behavioural and neural evidence that irrelevant responses evoked by previously reward-associated stimuli are more robustly represented in the motor system using a combined go/no-go and flankers task. Following a colour-reward association training, participants were instructed to respond to a central target only in a response-relevant context, while ignoring flankers that appeared either in a high-value or low-value colour. The motor cortex and cerebellum exhibited reduced activation to low-value flankers in a response-irrelevant context, consistent with goal-directed response suppression. However, these same regions exhibited similar activation to high-value flankers regardless of their response relevance, indicating less effective suppression, and the resulting interaction in motor cortex activation was strongly predicted by the influence of the flankers on behaviour. These findings suggest that associative reward learning produces a general approach bias, which is particularly evident when it conflicts with task goals, extending the principle of value-driven attention to stimulus-evoked responses in the motor system.

Investigations into the neurophysiological underpinnings of control suggest that frontal theta activity is increased with the need for control. However, these studies typically show this link by reporting associations between increased theta and RT slowing – a process that is contemporaneous with cognitive control but does not strictly reflect the specific use of control. In this study, we assessed frontal theta responses that underpinned the switch cost in task switching – a specific index of cognitive control that does not rely exclusively on RT slowing. Here, we utilised a single-trial regression approach to assess 1) how cognitive control demands beyond simple RT slowing were linked to midfrontal theta and 2) whether midfrontal theta effects remained stable over time. In a large cohort that included a longitudinal subsample, we found that midfrontal theta was modulated by switch costs, with enhanced theta power when preparing to switch vs. repeating a task. These effects were reliable after a two-year interval (Cronbach's α.39-0.74). In contrast, we found that trial-by-trial modulations of midfrontal theta power predicted the size of the switch cost – so that switch trials with increased theta produced smaller switch costs. Interestingly, these relationships between theta and behaviour were less stable over time (Cronbach's α 0-0.61), with participants first using both delta and theta bands to influence behaviour whereas after two years only theta associations with behaviour remained. Together, these findings suggest midfrontal theta supports the need for control beyond simple RT slowing and reveal that midfrontal theta effects remain relatively stable over time.

A mental set generally refers to the human brain's tendency to persist with a familiar solution and stubbornly ignore alternatives. However, if a familiar solution is unable to solve a problem similar to a previous problem, does it continue to hinder alternative solutions, and if so, how and why? To answer these questions, a Chinese character decomposition task was adopted in this study. Participants were asked to perform a practice problem that could be solved by a familiar loose chunk decomposition (LCD) solution followed by a test problem that was similar to the practice problem but could only be solved by an unfamiliar tight chunk decomposition (TCD) solution or were asked to repeatedly perform 3-5 practice problems followed by a test problem; the former is the base-set condition, and the latter is the enhanced-set condition. The results showed that the test problem recruited more activation of the inferior frontal gyrus (IFG), middle occipital cortex (MOG), superior parietal lobule (SPL) and dorsal anterior cingulate cortex (dACC) than the practice problem in the latter operation and verification stage, but almost equal activation of the dACC occurred in the early exploration stage. This likely implied that people did not think that the familiar but currently invalid LCD solution could not be used to solve the test problem; thus, it continuously competed for attention with the unfamiliar TCD solution, which required more executive control to suppress. Moreover, compared with the base-set condition, the test problem in the enhanced-set condition recruited greater activations of the IFG, SPL and dACC in the latter verification stage but less activations of regions in the left IFG and MOG in the early exploration stage. These results revealed that people less actively explored and had to work harder to operate the unfamiliar TCD solution, particularly to resolve competition from the familiar but currently invalid LCD solution. In conclusion, people lost the ability to identify errors in the familiar but currently invalid solution, which in turn decreased the exploration efforts and increased the processing demands associated with alternative solutions in the form of attentional bias and competition. This finding broadly explains the dilemma of creative problem solving.

We demonstrate a data-driven approach for calculating a “causal connectome” of directed connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non-Gaussian edge orientations. We used this approach to construct n=442 causal connectomes. These connectomes were very sparse in comparison to typical Pearson correlation-based graphs (roughly 2.25% edge density) yet were fully connected in nearly all cases. Prominent highly connected hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles: attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hub networks are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal connectivity analysis in psychiatry.

Highlights • We performed meta-analyses on fMRI/PET studies of human intentional decision. • Intentional choices activate a brain network maximal in the medial frontal cortex. • Four types of intentional decision paradigms are identified in the literature. • Intentional decisions rely on regions with distinct cognitive and computational roles., Brain-imaging research on intentional decision-making often employs a “free-choice” paradigm, in which participants choose among options with identical values or outcomes. Although the medial prefrontal cortex has commonly been associated with choices, there is no consensus on the wider network that underlies diverse intentional decisions and behaviours. Our systematic literature search identified 35 fMRI/PET experiments using various free-choice paradigms, with appropriate control conditions using external instructions. An Activation Likelihood Estimate (ALE) meta-analysis showed that, compared with external instructions, intentional decisions consistently activate the medial and dorsolateral prefrontal cortex, the left insula and the inferior parietal lobule. We then categorized the studies into four different types according to their experimental designs: reactive motor intention, perceptual intention, inhibitory intention, and cognitive intention. We conducted conjunction and contrast meta-analyses to identify consistent and selective spatial convergence of brain activation within each specific category of intentional decision. Finally, we used meta-analytic decoding to probe cognitive processes underlying free choices. Our findings suggest that the neurocognitive process underlying intentional decision incorporates anatomically separated components subserving distinct cognitive and computational roles.

In real life, humans make decisions by taking into account multiple independent factors, such as delay and probability. Cognitive psychology suggests that cognitive control mechanisms play a key role when facing such complex task conditions. However, in value-based decision-making, it still remains unclear to what extent cognitive control mechanisms become essential when the task condition is complex. In this study, we investigated decision-making behaviors and underlying neural mechanisms using a multifactor gambling task where participants simultaneously considered probability and delay. Decision-making behavior in the multifactor task was modulated by both probability and delay. The behavioral effect of probability was stronger than delay, consistent with previous studies. Furthermore, in a subset of conditions that recruited fronto-parietal activations, reaction times were paradoxically elongated despite lower probabilistic uncertainty. Notably, such a reaction time elongation did not occur in control tasks involving single factors. Meta-analysis of brain activations suggested an association between the paradoxical increase of reaction time and strategy switching. Together, these results suggest a novel aspect of complex value-based decision-makings that is strongly influenced by fronto-parietal cognitive control.Highlights•A value-based decision task with concurrent delay and probabilistic uncertainty•Stronger behavioral effect of probability than delay•Paradoxically long reaction time despite low probabilistic uncertainty•The task activated fronto-parietal cognitive control network•Reaction time elongation coincided with activation similar to strategy switching

Neural oscillatory activity in the theta (4–8 Hz) and alpha (8–14 Hz) bands has been associated with the implementation of executive function, with theta in midline frontal cortex and alpha in posterior parietal cortex related to working memory (WM) load. To identify how these spatially and spectrally distinct neural phenomena interact within a large-scale fronto-parietal network organized in service of WM, EEG was recorded while subjects performed an N-back WM task. Frontal theta power increase, paralleled by posterior alpha decrease, tracked participants' successful WM performance. These power fluctuations were inversely related both across and within trials and predicted reaction time, suggesting a functionally important communication channel within the fronto-parietal network. Granger causality analysis revealed directed parietal to frontal communication via alpha and frontal to parietal communication via theta. Results encourage consideration of these bidirectional, power-to-power, cross-frequency control mechanisms as an important feature of cerebral network organization supporting executive function.

There are vast individual differences in reading achievement between students. Besides structural and functional variability in domain-specific brain regions, these differences may partially be explained by the organization of domain-general functional brain networks. In the current study we used resting-state functional MRI data from the Philadelphia Neurodevelopmental Cohort (PNC; N = 553; ages 8–22) to examine the relation between performance on a well-validated reading assessment task, the Wide Range Achievement Word Reading Test (WRAT-Reading) and patterns of functional connectivity. We focused specifically on functional connectivity within and between networks associated with cognitive control, and investigated whether the relationship with academic test performance was mediated by cognitive control abilities. We show that individuals with higher scores on the WRAT-Reading, have stronger lateralization in frontoparietal networks, increased functional connectivity between dorsal striatum and the dorsal attention network, and reduced functional connectivity between dorsal and ventral striatum. The relationship between functional connectivity and reading performance was mediated by cognitive control abilities (i.e., performance on a composite measure of executive function and complex cognition), but not by abilities in other domains, demonstrating the specificity of our findings. Finally, there were no significant interactions with age, suggesting that the observed brain-behavior relationships stay relatively stable over the course of development. Our findings provide important insights into the functional significance of inter-individual variability in the network architecture of the developing brain, showing that functional connectivity in domain-general control networks is relevant to academic achievement in the reading domain.

Physical activity, such as high-intensity intermittent aerobic exercise (HIE), can improve executive functions. Although performing strength or aerobic training might be problematic or not feasible for someone. An experimental situation where there is no actual movement, but the body shows physiological reactions, is during the illusion through immersive virtual reality (IVR). We aimed to demonstrate whether a virtual HIE-based intervention (vHIE) performed exclusively by the own virtual body has physical, cognitive, and neural benefits on the real body. 45 healthy young adults (cross-over design) experienced HIE training in IVR (i.e., the virtual body performed eight sets of 30 s of running followed by 30 s of slow walking, while the subject is completely still) in two random-ordered conditions (administered in two sessions one week apart): the virtual body is displayed in first-person perspective (1PP) or third-person perspective (3PP). During the vHIE, we recorded the heart rate and subjective questionnaires to confirm the effectiveness of the illusion; before and after vHIE, we measured cortical hemodynamic changes in the participants’ left dorsolateral prefrontal cortex (lDLPFC) using the fNIRS device during the Stroop task to test our main hypothesis. Preliminary, we confirmed that the illusion was effective: during the vHIE in 1PP, subjects’ heart rate increased coherently with the virtual movements, and they reported subjective feelings of ownership and agency. Primarily, subjects were faster in executing the Stroop task after the vHIE in 1PP; also, the lDLPFC activity increased coherently. Clinically, these results might be exploited to train cognition and body simultaneously. Theoretically, we proved that the sense of body ownership and agency can affect other parameters, even in the absence of actual movements.

Brain activity typically increases with increasing working memory (WM) load, regardless of age, before reaching an apparent ceiling. However, older adults exhibit greater brain activity and reach ceiling at lower loads than younger adults, possibly reflecting compensation at lower loads and dysfunction at higher loads. We hypothesized that WM training would bolster neural efficiency, such that the activation peak would shift towards higher memory loads after training. Pre-training, older adults showed greater recruitment of the WM network than younger adults across all loads, with decline at the highest load. Ten days of adaptive training on a verbal WM task improved performance and led to greater brain responsiveness at higher loads for both groups. For older adults the activation peak shifted rightward towards higher loads. Finally, training increased task-related functional connectivity in older adults, both within the WM network and between this task-positive network and the task-negative/default-mode network. These results provide new evidence for functional plasticity with training in older adults and identify a potential signature of improvement at the neural level. National Institute on AgingUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Aging (NIA) [R21-AG-045460]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [1S10OD012240-01A1] This research was supported by a National Institute on Aging [R21-AG-045460] grant to P.A.R.-L. and a National Institutes of Health [1S10OD012240-01A1] grant. The authors thank Krisanne Litinas for assistance with MRI data reconstruction and Daniel Weissman for comments on a previous version of the manuscript.

Alzheimer's disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the illness timecourse. These fMRI correlates of unhealthy aging have been studied in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC alterations associated with AD disrupt the flow of activations between brain regions, leading to aberrant task activations. We apply this activity flow model in a large sample of clinically normal older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) AD risk factors. Modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy (at-risk) aged activations. This enabled reliable prediction of at-risk AD task activations, and these predicted activations were related to individual differences in task behavior. These results support activity flow over altered intrinsic functional connections as a mechanism underlying Alzheimer's-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights, this approach raises clinical potential by enabling prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.

Humans experience a sense of self, which is proposed to emerge from the integration of intrinsic and extrinsic self-processing through the propagation of information across brain systems. Using a novel functional magnetic resonance imaging (fMRI) paradigm, we tested this hypothesis in a non-clinical sample by modulating the intrinsic and extrinsic self-relatedness of auditory action consequences in terms of identity and agency, respectively. In addition, the relevance of individual traits associated with altered self-experiences (e.g., psychosis-like experiences) was examined. The task-evoked fMRI results showed distinctive associations between the neural coding of identity and negative affect traits, and between agency and psychosis-like experiences. Most importantly, regarding the functional connectivity analysis, graph theoretical measures demonstrated that the simultaneous processing of identity and agency relies on the functional integration and segregation of default mode, sensorimotor, language, and executive brain networks. Finally, cross-network interactions mediated by executive and sensorimotor regions were negatively associated with psychosis-like experiences when the intrinsic and extrinsic self-relatedness of action consequences conflicted. These findings provide evidence that the self is a multidimensional phenomenon rooted in the functional interactions between large-scale neuronal networks. Such interactions may have particular relevance for self-experience alterations.

Working memory (WM) function has traditionally been investigated in terms of two dimensions: within-individual effects of WM load, and between-individual differences in task performance. In human neuroimaging studies, the N-back task has frequently been used to study both. A reliable finding is that activation in frontoparietal regions exhibits an inverted-U pattern, such that activity tends to decrease at high load levels. Yet it is not known whether such U-shaped patterns are a key individual differences factor that can predict load-related changes in task performance. The current study investigated this question by manipulating load levels across a much wider range than explored previously (N ​= ​1–6), and providing a more comprehensive examination of brain-behavior relationships. In a sample of healthy young adults (n ​= ​57), the analysis focused on a distinct region of left lateral prefrontal cortex (LPFC) identified in prior work to show a unique relationship with task performance and WM function. In this region it was the linear slope of load-related activity, rather than the U-shaped pattern, that was positively associated with individual differences in target accuracy. Comprehensive supplemental analyses revealed the brain-wide selectivity of this pattern. Target accuracy was also independently predicted by the global resting-state connectivity of this LPFC region. These effects were robust, as demonstrated by cross-validation analyses and out-of-sample prediction, and also critically, were primarily driven by the high-load conditions. Together, the results highlight the utility of high-load conditions for investigating individual differences in WM function.

Goal-directed behavior is affected by subliminally and consciously induced conflicts. Both seem to be modulated by catecholamines, especially dopamine. On the basis of cognitive theoretical and neurobiological considerations, we investigated the effects of dopamine D1 and D2 signaling with the help of unweighted polygenic scores in n = 207 healthy young human subjects. We used a task that combines subliminal primes with conscious flankers to induce conflicts. Dopamine D1 scores were formed based on DRD1 rs4532, CALY rs2298122 and TH rs10770141 single nucleotide polymorphisms (SNPs), while dopamine D2 scores were formed based on DRD2 rs6277 and NPY2R rs2234759 SNPs. We used EEG recordings and source localization analyses to identify differentially modulated neurophysiological sub-processes and functional neuroanatomical structures. Increased dopamine D1 signaling was associated with decreases in consciously induced conflicts. This decrease was due to enhanced stimulus-response mapping in the premotor cortex (BA6), as reflected by an increased P3 amplitude in incongruent trials. Attentional processes remained unaffected by dopamine D1 signaling. The effect of dopamine D2 signaling on conscious conflicts did not reach significance. Subliminally induced conflicts were neither modulated by dopamine D1, nor by dopamine D2 signaling. Our findings suggest that dopamine D1 signaling benefits consciously induced conflicts, presumably by improving the suppression of distracting information via gain control-initiated increases in top-down control processes associated with pre-motor regions. Dopamine D2 signaling does not seem to mediate behavioral differences. Probably, this is because the D2 state facilitates switching between (conflicting) top-down-selected mental representations, but not necessarily between top-down processes and bottom-up distractor information.

Although covarying for potential confounds or nuisance variables is common in psychological research, relatively little is known about how the inclusion of covariates may influence the relations between psychological variables and indices of brain structure. In Part 1 of the current study, we conducted a descriptive review of relevant articles from the past two years of NeuroImage in order to identify the most commonly used covariates in work of this nature. Age, sex, and intracranial volume were found to be the most commonly used covariates, although the number of covariates used ranged from 0 to 14, with 37 different covariate sets across the 68 models tested. In Part 2, we used data from the Human Connectome Project to investigate the degree to which the addition of common covariates altered the relations between individual difference variables (i.e., personality traits, psychopathology, cognitive tasks) and regional gray matter volume (GMV), as well as the statistical significance of values associated with these effect sizes. Using traditional and random sampling approaches, our results varied widely, such that some covariate sets influenced the relations between the individual difference variables and GMV very little, while the addition of other covariate sets resulted in a substantially different pattern of results compared to models with no covariates. In sum, these results suggest that the use of covariates should be critically examined and discussed as part of the conversation on replicability in structural neuroimaging. We conclude by recommending that researchers pre-register their analytic strategy and present information on how relations differ based on the inclusion of covariates.

Despite the necessity to understand how the brain endures the initial stages of age-associated cognitive decline, no brain mechanism has been quantitatively specified to date. The brain may withstand the effects of cognitive aging through redundancy, a design feature in engineered and biological systems, which entails the presence of substitute elements to protect it against failure. Here, we investigated the relationship between functional network redundancy and age over the human lifespan and their interaction with cognition, analyzing resting-state functional MRI images and cognitive measures from 579 subjects. Network-wide redundancy was significantly associated with age, showing a stronger link with age than other major topological measures, presenting a pattern of accumulation followed by old-age decline. Critically, redundancy significantly mediated the association between age and executive function, with lower anti-correlation between age and cognition in subjects with high redundancy. The results suggest that functional redundancy accrues throughout the lifespan, mitigating the effects of age on cognition.

Cognitive control over conflict, mediated by the prefrontal cortex, is an important skill for successful decision-making. Although it has been shown that cognitive control may operate unconsciously, it has recently been proposed that control operations may be driven by the metacognitive awareness of conflict, e.g. arising from the feeling of task difficulty or the ease of action selection, and therefore crucially depends on conflict awareness. Behavioral and electroencephalography (EEG) data are presented from 64 subjects performing a masked priming paradigm to test this hypothesis. Although the subjective experience of conflict elicited behavioral adaptation, this was also the case when conflict was present, but not experienced. In EEG, typical oscillatory markers of conflict processing in the theta-, alpha- and beta-band were observed (relative broadband), but these were differentially modulated by conflict experience. This demonstrates that conflict adaptation does not depend on conflict experience, but that conflict experience is associated with increased cognitive control.

Our capacity to flexibly shift between internally and externally directed attention is crucial for successful performance of activities in our daily lives. Neuroimaging studies have implicated the lateral prefrontal cortex (LPFC) in both internally directed processes, including autobiographical memory retrieval and future planning, and externally directed processes, including cognitive control and selective attention. However, the causal involvement of the LPFC in regulating internally directed attention states is unknown. The current study recorded scalp EEG from patients with LPFC lesions and healthy controls as they performed an attention task that instructed them to direct their attention either to the external environment or their internal milieu. We compared frontocentral midline theta and posterior alpha between externally and internally directed attention states. While healthy controls showed increased theta power during externally directed attention and increased alpha power during internally directed attention, LPFC patients revealed no differences between the two attention states in either electrophysiological measure in the analyzed time windows. These findings provide evidence that damage to the LPFC leads to dysregulation of both types of attention, establishing the important role of LPFC in supporting sustained periods of internally and externally directed attention.

Research on the neural bases of bilingual language control has largely overlooked the role of preparatory processes, which are central to cognitive control. Additionally, little is known about how the processes involved in global language selection may differ from those involved in the selection of words and morpho-syntactic rules for manipulating them. These processes were examined separately in an fMRI experiment, with an emphasis on understanding how and when general cognitive control regions become activated. Results of region-of-interest analyses on 23 early Spanish-English bilinguals showed that the anterior cingulate cortex (ACC) was primarily engaged during the language preparation phase of the task, whereas the left prefrontal (DLPFC) and pre-supplementary motor areas showed increasing activation from preparation to execution. Activation in the basal ganglia (BG), left middle temporal lobe, and right precentral cortical regions did not significantly differ throughout the task. These results suggest that three core cognitive control regions, the ACC, DLPFC, and BG, which have been previously implicated in bilingual language control, engage in distinct neurocognitive processes. Specifically, the results are consistent with the view that the BG “keep track” of the target language in use throughout various levels of language selection, that the ACC is particularly important for top-down target language preparation, and that the left prefrontal cortex is increasingly involved in selection processes from preparation through task execution.

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.

Category learning is a critical neurobiological function that allows organisms to simplify a complex world. Rostrolateral prefrontal cortex (rlPFC) is often active in neurobiological studies of category learning; however, the specific role this region serves in category learning remains uncertain. Previous category learning studies have hypothesized that the rlPFC is involved in switching between rules, whereas others have emphasized rule abstraction and evaluation. We aimed to clarify the role of rlPFC in category learning and dissociate switching and evaluation accounts using two common types of category learning tasks: matching and classification. The matching task involved matching a reference stimulus to one of four target stimuli. In the classification task, participants were shown a single stimulus and learned to classify it into one of two categories. Matching and classification are similar but place different demands on switching and evaluation. In matching, a rule can be known with certainty after a single correct answer. In classification, participants may need to evaluate evidence for a rule even after an initial correct response. This critical difference allows isolation of evaluative functions from switching functions. If the rlPFC is primarily involved in switching between representations, it should cease to be active once participants settle on a given rule in both tasks. If the rlPFC is involved in rule evaluation, its activation should persist in the classification task, but not matching. The results revealed that rlPFC activation persisted into correct trials in classification, but not matching, suggesting that it continues to be involved in the evaluations of evidence for a rule even after participants have arrived at the correct rule.HighlightsDifferences between rule-based matching and classification tasks were highlighted.Rostrolateral prefrontal cortex is involved in evaluation of evidence for a rule in rule-based category learning tasks.

Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square [PLS] regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with correlations between predicted and observed measures of attention as high as 0.9 for internal validation, and 0.6 for external validation (all p's

Detecting regularities in the sensory environment licenses predictions that enable adaptive behaviour. However, it is unclear whether predictions about object category, location, or both dimensions are mediated by overlapping systems, and relatedly, whether constructing predictions about both category and location is associated with processing bottlenecks. To examine this issue, in an fMRI study, we presented participants with image-series in which non-deterministic transition probabilities enabled predictions about either the location of the next image, its semantic category, both dimensions, or neither (the latter forming a “no-regularity” random baseline condition). Speaking to a common system, all three predictable conditions resulted in reduced BOLD activity in four clusters: left rostral anterior cingulate cortex; bilateral putamen, caudate and thalamus; right precentral gyrus, and left visual cortex. Pointing to a processing bottleneck, in some regions, a significant interaction between the two factors was found whereby category-predictable series were associated with lower activity – but only when location regularity was absent. Finally, category regularity decreased activation in areas of the ventral visual stream and semantic areas of lateral temporal cortex, and location regularity decreased activation in a dorsal fronto-parietal cluster, long implicated in the endogenous control of spatial attention. Our findings confirm and expand a role for dACC/dmPFC and striatum in monitoring or responding to uncertainty in the environment and point to a limited capacity bottleneck when multiple predictions are concurrently licensed.

Obesity and maintaining a healthy diet have important implications for physical and mental health. One factor that may influence diet and obesity is inhibitory control. We tested how N2 and P3 amplitude, event-related potential (ERP) components that reflect inhibitory control, and functional magnetic resonance imaging (fMRI) activity in brain regions associated with inhibitory control differed toward high- and low-calorie food stimuli across BMI status. We also assessed the relationship between neural indices of food-related inhibitory control and laboratory and daily food intake. Fifty-four individuals (17 normal-weight; 18 overweight; 19 individuals with obesity) completed two food-based go/no-go tasks (one with high- and one with low-calorie foods as no-go stimuli), once during ERP data acquisition and once during fMRI data acquisition. After testing, participants were presented with an ad libitum weighed food buffet. Participants also recorded their food intake using the Automated Self-Administered 24-hour Dietary Recall (ASA24) system across four days. Individuals recruited more inhibitory control when withholding responses towards high-compared to low-calorie foods, although this effect was more consistent for N2 than P3 or fMRI assessments. BMI status did not influence food-related inhibitory control. A larger inhibitory response as measured by N2 amplitude was related to increased ASA24 food intake; P3 amplitude and fMRI region of interest activity did not predict ASA24 intake; neither method predicted food intake from the buffet. ERP and fMRI measurements show similar neural responses to food, although N2 amplitude may be somewhat more sensitive in detecting differences between food types and predicting self-reports of food intake.