No abstract

The prefrontal cortex (PFC) plays a critical role in the generation and regulation of emotion. However, we lack an integrative framework for understanding how different emotion-related functions are organized across the entire expanse of the PFC, as prior reviews have generally focused on specific emotional processes (e.g., decision making) or specific anatomical regions (e.g., orbitofrontal cortex). Additionally, psychological theories and neuroscientific investigations have proceeded largely independently because of the lack of a common framework. Here, we provide a comprehensive review of functional neuroimaging, electrophysiological, lesion, and structural connectivity studies on the emotion-related functions of 8 subregions spanning the entire PFC. We introduce the appraisal-by-content model, which provides a new framework for integrating the diverse range of empirical findings. Within this framework, appraisal serves as a unifying principle for understanding the PFC's role in emotion, while relative content-specialization serves as a differentiating principle for understanding the role of each subregion. A synthesis of data from affective, social, and cognitive neuroscience studies suggests that different PFC subregions are preferentially involved in assigning value to specific types of inputs: exteroceptive sensations, episodic memories and imagined future events, viscero-sensory signals, viscero-motor signals, actions, others' mental states (e.g., intentions), self-related information, and ongoing emotions. We discuss the implications of this integrative framework for understanding emotion regulation, value-based decision making, emotional salience, and refining theoretical models of emotion. This framework provides a unified understanding of how emotional processes are organized across PFC subregions and generates new hypotheses about the mechanisms underlying adaptive and maladaptive emotional functioning. (PsycINFO Database Record

Meditation is a family of mental practices that encompasses a wide array of techniques employing distinctive mental strategies. We systematically reviewed 78 functional neuroimaging (fMRI and PET) studies of meditation, and used activation likelihood estimation to meta-analyze 257 peak foci from 31 experiments involving 527 participants. We found reliably dissociable patterns of brain activation and deactivation for four common styles of meditation (focused attention, mantra recitation, open monitoring, and compassion/loving-kindness), and suggestive differences for three others (visualization, sense-withdrawal, and non-dual awareness practices). Overall, dissociable activation patterns are congruent with the psychological and behavioral aims of each practice. Some brain areas are recruited consistently across multiple techniques-including insula, pre/supplementary motor cortices, dorsal anterior cingulate cortex, and frontopolar cortex-but convergence is the exception rather than the rule. A preliminary effect-size meta-analysis found medium effects for both activations (d=0.59) and deactivations (d=-0.74), suggesting potential practical significance. Our meta-analysis supports the neurophysiological dissociability of meditation practices, but also raises many methodological concerns and suggests avenues for future research.

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN exhibited stronger connectivity with the DN than the DAN, whereas FPCN exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN may be preferentially involved in the regulation of introspective processes, whereas FPCN may be preferentially involved in the regulation of visuospatial perceptual attention.

No abstract

Anticorrelation between the default network (DN) and dorsal attention network (DAN) is thought to be an intrinsic aspect of functional brain organization reflecting competing functions. However, the effect size of functional connectivity (FC) between the DN and DAN has yet to be established. Furthermore, the stability of anticorrelations across distinct DN subsystems, different contexts, and time, remains unexplored. In study 1 we summarize effect sizes of DN-DAN FC from 20 studies, and in study 2 we probe the variability of DN-DAN interactions across six different cognitive states in a new data set. We show that: (i) the DN and DAN have an independent rather than anticorrelated relationship when global signal regression is not used (median effect size across studies: r=-.06; 95% CI: -.15 to .08); (ii) the DAN exhibits weak negative FC with the DN Core subsystem but is uncorrelated with the dorsomedial prefrontal and medial temporal lobe subsystems; (iii) DN-DAN interactions vary significantly across different cognitive states; (iv) DN-DAN FC fluctuates across time between periods of anticorrelation and periods of positive correlation; and (v) changes across time in the strength of DN-DAN coupling are coordinated with interactions involving the frontoparietal control network (FPCN). Overall, the observed weak effect sizes related to DN-DAN anticorrelation suggest the need to re-conceptualize the nature of interactions between these networks. Furthermore, our findings demonstrate that DN-DAN interactions are not stable, but rather, exhibit substantial variability across time and context, and are coordinated with broader network dynamics involving the FPCN.

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives.

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, in order to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC the default network (DN) and the dorsal attentional network (DAN). This 2-fold FPCN differentiation was observed across four independent data sets, across 9 different conditions (rest and 8 tasks), as well as in meta-analytic co-activation patterns. The extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams.