Concept: Brodmann area
Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.
Noninvasive brain stimulation has shown considerable promise for enhancing cognitive functions by the long-term manipulation of neuroplasticity [1-3]. However, the observation of such improvements has been focused at the behavioral level, and enhancements largely restricted to the performance of basic tasks. Here, we investigate whether transcranial random noise stimulation (TRNS) can improve learning and subsequent performance on complex arithmetic tasks. TRNS of the bilateral dorsolateral prefrontal cortex (DLPFC), a key area in arithmetic [4, 5], was uniquely coupled with near-infrared spectroscopy (NIRS) to measure online hemodynamic responses within the prefrontal cortex. Five consecutive days of TRNS-accompanied cognitive training enhanced the speed of both calculation- and memory-recall-based arithmetic learning. These behavioral improvements were associated with defined hemodynamic responses consistent with more efficient neurovascular coupling within the left DLPFC. Testing 6 months after training revealed long-lasting behavioral and physiological modifications in the stimulated group relative to sham controls for trained and nontrained calculation material. These results demonstrate that, depending on the learning regime, TRNS can induce long-term enhancement of cognitive and brain functions. Such findings have significant implications for basic and translational neuroscience, highlighting TRNS as a viable approach to enhancing learning and high-level cognition by the long-term modulation of neuroplasticity.
Evidence suggests that pathological eating behaviours in bulimia nervosa (BN) are underpinned by alterations in reward processing and self-regulatory control, and by functional changes in neurocircuitry encompassing the dorsolateral prefrontal cortex (DLPFC). Manipulation of this region with transcranial direct current stimulation (tDCS) may therefore alleviate symptoms of the disorder.
The lateral prefrontal and orbitofrontal cortices have both been implicated in emotion regulation, but their distinct roles in regulation of negative emotion remain poorly understood. To address this issue we enrolled 58 participants in an fMRI study in which participants were instructed to reappraise both negative and neutral stimuli. This design allowed us to separately study activations reflecting cognitive processes associated with reappraisal in general and activations specifically related to reappraisal of negative emotion. Our results confirmed that both the dorsolateral prefrontal cortex (DLPFC) and the lateral orbitofrontal cortex (OFC) contribute to emotion regulation through reappraisal. However, activity in the DLPFC was related to reappraisal independently of whether negative or neutral stimuli were reappraised, whereas the lateral OFC was uniquely related to reappraisal of negative stimuli. We suggest that relative to the lateral OFC, the DLPFC serves a more general role in emotion regulation, perhaps by reflecting the cognitive demand that is inherent to the regulation task.
We solve problems by applying previously learned rules. The dorsolateral prefrontal cortex (DLPFC) plays a pivotal role in automating this process of rule induction. Despite its usual efficiency, this process fails when we encounter new problems in which past experience leads to a mental rut. Learned rules could therefore act as constraints which need to be removed in order to change the problem representation for producing the solution. We investigated the possibility of suppressing the DLPFC by transcranial direct current stimulation (tDCS) to facilitate such representational change. Participants solved matchstick arithmetic problems before and after receiving cathodal, anodal or sham tDCS to the left DLPFC. Participants who received cathodal tDCS were more likely to solve the problems that require the maximal relaxation of previously learned constraints than the participants who received anodal or sham tDCS. We conclude that cathodal tDCS over the left DLPFC might facilitate the relaxation of learned constraints, leading to a successful representational change.
Human beings are social animals and they vary in the degree to which they share information about themselves with others. Although brain networks involved in self-related cognition have been identified, especially via the use of resting-state experiments, the neural circuitry underlying individual differences in the sharing of self-related information is currently unknown. Therefore, we investigated the intrinsic functional organization of the brain with respect to participants' degree of self-related information sharing using resting state functional magnetic resonance imaging and self-reported social media use. We conducted seed-based correlation analyses in cortical midline regions previously shown in meta-analyses to be involved in self-referential cognition: the medial prefrontal cortex (MPFC), central precuneus (CP), and caudal anterior cingulate cortex (CACC). We examined whether and how functional connectivity between these regions and the rest of the brain was associated with participants' degree of self-related information sharing. Analyses revealed associations between the MPFC and right dorsolateral prefrontal cortex (DLPFC), as well as the CP with the right DLPFC, the left lateral orbitofrontal cortex and left anterior temporal pole. These findings extend our present knowledge of functional brain connectivity, specifically demonstrating how the brain’s intrinsic functional organization relates to individual differences in the sharing of self-related information.
In human studies, how averaged activation in a brain region relates to human behavior has been extensively investigated. This approach has led to the finding that positive and negative facial preferences are represented by different brain regions. However, using a functional magnetic resonance imaging (fMRI) decoded neurofeedback (DecNef) method, we found that different patterns of neural activations within the cingulate cortex (CC) play roles in representing opposite directions of facial preference. In the present study, while neutrally preferred faces were presented, multi-voxel activation patterns in the CC that corresponded to higher (or lower) preference were repeatedly induced by fMRI DecNef. As a result, previously neutrally preferred faces became more (or less) preferred. We conclude that a different activation pattern in the CC, rather than averaged activation in a different area, represents and suffices to determine positive or negative facial preference. This new approach may reveal the importance of an activation pattern within a brain region in many cognitive functions.
Humans can resist temptations by exerting willpower, the effortful inhibition of impulses. But willpower can be disrupted by emotions and depleted over time. Luckily, humans can deploy alternative self-control strategies like precommitment, the voluntary restriction of access to temptations. Here, we examined the neural mechanisms of willpower and precommitment using fMRI. Behaviorally, precommitment facilitated choices for large delayed rewards, relative to willpower, especially in more impulsive individuals. While willpower was associated with activation in dorsolateral prefrontal cortex (DLPFC), posterior parietal cortex (PPC), and inferior frontal gyrus, precommitment engaged lateral frontopolar cortex (LFPC). During precommitment, LFPC showed increased functional connectivity with DLPFC and PPC, especially in more impulsive individuals, and the relationship between impulsivity and LFPC connectivity was mediated by value-related activation in ventromedial PFC. Our findings support a hierarchical model of self-control in which LFPC orchestrates precommitment by controlling action plans in more caudal prefrontal regions as a function of expected value.
- The Journal of neuroscience : the official journal of the Society for Neuroscience
- Published about 7 years ago
Despite extensive research on inhibitory control (IC) and its neural systems, the questions of whether IC can be improved with training and how the associated neural systems change are understudied. Behavioral evidence suggests that performance on IC tasks improves with training but that these gains do not transfer to other tasks, and almost nothing is known about how activation in IC-related brain regions changes with training. Human participants were randomly assigned to receive IC training (N = 30) on an adaptive version of the stop-signal task (SST) or an active sham-training (N = 30) during 10 sessions across 3 weeks. Neural activation during the SST before and after training was assessed in both groups using functional magnetic resonance imaging. Performance on the SST improved significantly more in the training group than in the control group. The pattern of neuroimaging results was consistent with a proactive control model such that activity in key parts of the IC network shifted earlier in time within the trial, becoming associated with cues that anticipated the upcoming need for IC. Specifically, activity in the inferior frontal gyrus decreased during the implementation of control (i.e., stopping) and increased during cues that preceded the implementation of IC from pretraining to post-training. Also, steeper behavioral improvement in the training group correlated with activation increases during the cue phase and decreases during implementation in the dorsolateral prefrontal cortex. These results are the first to uncover the neural pathways for training-related improvements in IC and can explain previous null findings of IC training transfer.
A sense of gratitude is a powerful and positive experience that can promote a happier life, whereas resentment is associated with life dissatisfaction. To explore the effects of gratitude and resentment on mental well-being, we acquired functional magnetic resonance imaging and heart rate (HR) data before, during, and after the gratitude and resentment interventions. Functional connectivity (FC) analysis was conducted to identify the modulatory effects of gratitude on the default mode, emotion, and reward-motivation networks. The average HR was significantly lower during the gratitude intervention than during the resentment intervention. Temporostriatal FC showed a positive correlation with HR during the gratitude intervention, but not during the resentment intervention. Temporostriatal resting-state FC was significantly decreased after the gratitude intervention compared to the resentment intervention. After the gratitude intervention, resting-state FC of the amygdala with the right dorsomedial prefrontal cortex and left dorsal anterior cingulate cortex were positively correlated with anxiety scale and depression scale, respectively. Taken together, our findings shed light on the effect of gratitude meditation on an individual’s mental well-being, and indicate that it may be a means of improving both emotion regulation and self-motivation by modulating resting-state FC in emotion and motivation-related brain regions.