Intracranial Recordings of the Human Orbitofrontal Cortical Activity during Self-Referential Episodic and Valenced Self-Judgments.

We recorded directly from the orbital (oPFC) and ventromedial (vmPFC) subregions of the orbitofrontal cortex (OFC) in 22 (9 female, 13 male) epilepsy patients undergoing intracranial electroencephalography (iEEG) monitoring during an experimental task in which the participants judged the accuracy of self-referential autobiographical statements as well as valenced self-judgments (SJs). We found significantly increased high-frequency activity (HFA) in ∼13% of oPFC sites (10/18 subjects) and 16% of vmPFC sites (4/12 subjects) during both of these self-referential thought processes, with the HFA power being modulated by the content of self-referential stimuli. The location of these activated sites corresponded with the location of fMRI-identified limbic network. Furthermore, the onset of HFA in the vmPFC was significantly earlier than that in the oPFC in all patients with simultaneous recordings in both regions. In 11 patients with available depression scores from comprehensive neuropsychological assessments, we documented diminished HFA in the OFC during positive SJ trials among individuals with higher depression scores; responses during negative SJ trials were not related to the patients' depression scores. Our findings provide new temporal and anatomical information about the mode of engagement in two important subregions of the OFC during autobiographical memory and SJ conditions. Our findings from the OFC support the hypothesis that diminished brain activity during positive self-evaluations, rather than heightened activity during negative self-evaluations, plays a key role in the pathophysiology of depression.

Brain network integration, segregation and quasi-periodic activation and deactivation during tasks and rest.

Previous studies have shown that a re-organization of the brain's functional connectome expressed in terms of network integration and segregation may play a pivotal role for brain function. However, it has been proven difficult to fully capture both processes independently in a single methodological framework. In this study, by starting from pair-wise assessments of instantaneous phase synchronization and community membership, we assemble spatiotemporally flexible networks that reflect changes in integration/segregation that occur at a spectrum of spatial as well as temporal scales. This is achieved by iteratively assembling smaller networks into larger units under the constraint that the smaller units should be internally integrated, i.e. belong to the same community. The assembled subnetworks can be partly overlapping and differ in size across time. Our results show that subnetwork integration and segregation occur simultaneously in the brain. During task performance, global changes in synchronization between networks arise that are tied to the underlying temporal design of the experiment. We show that a hallmark property of the dynamics of the brain's functional connectome is a presence of quasi-periodic patterns of network activation and deactivation, which during task performance becomes intertwined with the underlying temporal structure of the experimental paradigm. Additionally, we show that the degree of network integration throughout a n-back working memory task is correlated to performance.

Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought.

In vast areas of the world, forests and vegetation are water limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take hydraulic risks by operating at water potentials (ψ) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment. The model explains the relationship between the tolerance to negative water potential (ψ50 ) and the environmentally dependent minimum ψ (ψmin ) across a large number of species, and along the xylem pathway within individuals of two species studied. The wider hydraulic safety margin in gymnosperms compared to angiosperms can be explained as an adaptation to a higher susceptibility to accumulation of embolism. The model provides a novel optimality-based perspective on the relationship between xylem safety and efficiency.

Anti-satellite glia cell IgG antibodies in fibromyalgia patients are related to symptom severity and to metabolite concentrations in thalamus and rostral anterior cingulate cortex.

Recent translational work has shown that fibromyalgia might be an autoimmune condition with pathogenic mechanisms mediated by a peripheral, pain-inducing action of immunoglobulin G (IgG) antibodies binding to satellite glia cells (SGC) in the dorsal root ganglia. A first clinical assessment of the postulated autoimmunity showed that fibromyalgia subjects (FMS) had elevated levels of antibodies against SGC (termed anti-SGC IgG) compared to healthy controls and that anti-SGC IgG were associated with a more severe disease status. The overarching aim of the current study was to determine whether the role of anti-SGC IgG in driving pain is exclusively through peripheral mechanisms, as indirectly shown so far, or could be attributed also to central mechanisms. To this end, we wanted to first confirm, in a larger cohort of FMS, the relation between anti-SGC IgG and pain-related clinical measures. Secondly, we explored the associations of these autoantibodies with brain metabolite concentrations (assessed via magnetic resonance spectroscopy, MRS) and pressure-evoked cerebral pain processing (assessed via functional magnetic resonance imaging, fMRI) in FMS. Proton MRS was performed in the thalamus and rostral anterior cingulate cortex (rACC) of FMS and concentrations of a wide spectrum of metabolites were assessed. During fMRI, FMS received individually calibrated painful pressure stimuli corresponding to low and high pain intensities. Our results confirmed a positive correlation between anti-SGC IgG and clinical measures assessing condition severity. Additionally, FMS with high anti-SGC IgG levels had higher pain intensity and a worse disease status than FMS with low anti-SGC IgG levels. Further, anti-SGC IgG levels negatively correlated with metabolites such as scyllo-inositol in thalamus and rACC as well as with total choline and macromolecule 12 in thalamus, thus linking anti-SGC IgG levels to the concentration of metabolites in the brain of FMS. However, anti-SGC IgG levels in FMS were not associated with the sensitivity to pressure pain or the cerebral processing of evoked pressure pain. Taken together, our results suggest that anti-SGC IgG might be clinically relevant for spontaneous, non-evoked pain. Our current and previous translational and clinical findings could provide a rationale to try new antibody-related treatments in FMS.

Augmented pain inhibition and higher integration of pain modulatory brain networks in women with self-injury behavior.

Individuals who engage in nonsuicidal self-injury (NSSI) have demonstrated insensitivity to pain compared with individuals without NSSI. Yet, the neural mechanisms behind this difference are unknown. The objective of the present study was to determine which aspects of the pain regulatory system that account for this decreased sensitivity to pain. In a case-control design, 81 women, aged 18-35 (mean [SD] age, 23.4 [3.9]), were included (41 with NSSI and 40 healthy controls). A quantitative sensory testing protocol, including heat pain thresholds, heat pain tolerance, pressure pain thresholds, conditioned pain modulation (assessing central down-regulation of pain), and temporal summation (assessing facilitation of pain signals) was used. Pain-evoked brain responses were assessed by means of fMRI scanning during thermal pain. NSSI participants showed a more effective central down-regulation of pain, compared to controls, assessed with conditioned pain modulation. The neural responses to painful stimulation revealed a stronger relation between nociceptive and pain modulatory brain regions in NSSI compared to controls. In line with previous studies, pressure and heat pain thresholds were higher in participants with NSSI, however, there were no correlations between pain outcomes and NSSI clinical characteristics. The augmented pain inhibition and higher involvement of pain modulatory brain networks in NSSI may represent a pain insensitive endophenotype associated with a greater risk for developing self-injurious behavior.

Brain network segregation and integration during painful thermal stimulation.

The present study aimed to determine changes in brain network integration/segregation during thermal pain using methods optimized for network connectivity events with high temporal resolution. Participants (n = 33) actively judged whether thermal stimuli applied to the volar forearm were painful or not and then rated the warmth/pain intensity after each trial. We show that the temporal evolution of integration/segregation within trials correlates with the subjective ratings of pain. Specifically, the brain shifts from a segregated state to an integrated state when processing painful stimuli. The association with subjective pain ratings occurred at different time points for all networks. However, the degree of association between ratings and integration/segregation vanished for several brain networks when time-varying functional connectivity was measured at lower temporal resolution. Moreover, the increased integration associated with pain is explained to some degree by relative increases in between-network connectivity. Our results highlight the importance of investigating the relationship between pain and brain network connectivity at a single time point scale, since commonly used temporal aggregations of connectivity data may result in that fine-scale changes in network connectivity may go unnoticed. The interplay between integration/segregation reflects shifting demands of information processing between brain networks and this adaptation occurs both for cognitive tasks and nociceptive processing.

Genetic Influence on Nociceptive Processing in the Human Brain-A Twin Study.

Nociceptive processing in the human brain is complex and involves several brain structures and varies across individuals. Determining the structures that contribute to interindividual differences in nociceptive processing is likely to improve our understanding of why some individuals feel more pain than others. Here, we found specific parts of the cerebral response to nociception that are under genetic influence by employing a classic twin-design. We found genetic influences on nociceptive processing in the midcingulate cortex and bilateral posterior insula. In addition to brain activations, we found genetic contributions to large-scale functional connectivity (FC) during nociceptive processing. We conclude that additive genetics influence specific brain regions involved in nociceptive processing. The genetic influence on FC during nociceptive processing is not limited to core nociceptive brain regions, such as the dorsal posterior insula and somatosensory areas, but also involves cognitive and affective brain circuitry. These findings improve our understanding of human pain perception and increases chances to find new treatments for clinical pain.

Normal Olfactory Functional Connectivity Despite Lifelong Absence of Olfactory Experiences.

Congenital blindness is associated with atypical morphology and functional connectivity within and from visual cortical regions; changes that are hypothesized to originate from a lifelong absence of visual input and could be regarded as a general (re) organization principle of sensory cortices. Challenging this is the fact that individuals with congenital anosmia (lifelong olfactory sensory loss) display little to no morphological changes in the primary olfactory cortex. To determine whether olfactory input from birth is essential to establish and maintain normal functional connectivity in olfactory processing regions, akin to the visual system, we assessed differences in functional connectivity within the olfactory cortex between individuals with congenital anosmia (n = 33) and matched controls (n = 33). Specifically, we assessed differences in connectivity between core olfactory processing regions as well as differences in regional homogeneity and homotopic connectivity within the primary olfactory cortex. In contrast to congenital blindness, none of the analyses indicated atypical connectivity in individuals with congenital anosmia. In fact, post-hoc Bayesian analysis provided support for an absence of group differences. These results suggest that a lifelong absence of olfactory experience has a limited impact on the functional connectivity in the olfactory cortex, a finding that indicates a clear difference between sensory modalities in how sensory cortical regions develop.

The Hypothesis of Subliminal Cue Reactivity in Addiction Revisited: An fMRI Study.

INTRODUCTION: Exposure to conditioned cues is a common trigger of relapse in addiction. It has been suggested that such cues can activate motivationally relevant neurocircuitry in individuals with substance use disorders even without being consciously perceived. We aimed to see if this could be replicated in a sample with severe amphetamine use disorder and a control group of healthy subjects. METHODS: We used fMRI to test the hypothesis that individuals with amphetamine use disorder, but not healthy controls, exhibit a specific neural reactivity to subliminally presented pictures related to amphetamine use. Twenty-four amphetamine users and 25 healthy controls were recruited and left data of sufficient quality to be included in the final analysis. All subjects were exposed to drug-related and neutral pictures of short duration (13.3 ms), followed by a backward visual mask image. The contrast of interest was drug versus neutral subliminal pictures. RESULTS: There were no statistically significant differences in BOLD signal between the drug and neutral cues, neither in the limbic regions of primary interest nor in exploratory whole-brain analyses. The same results were found both in amphetamine users and controls. DISCUSSION/CONCLUSION: We found no evidence of neural reactivity to subliminally presented drug cues in this sample of subjects with severe amphetamine dependence. These results are discussed in relation to the earlier literature, and the evidence for subliminal drug cue reactivity in substance use disorders is questioned.

Spatiotemporally flexible subnetworks reveal the quasi-cyclic nature of integration and segregation in the human brain.

Though the organization of functional brain networks is modular at its core, modularity does not capture the full range of dynamic interactions between individual brain areas nor at the level of subnetworks. In this paper we present a hierarchical model that represents both flexible and modular aspects of intrinsic brain organization across time by constructing spatiotemporally flexible subnetworks. We also demonstrate that segregation and integration are complementary and simultaneous events. The method is based on combining the instantaneous phase synchrony analysis (IPSA) framework with community detection to identify a small, yet representative set of subnetwork components at the finest level of spatial granularity. At the next level, subnetwork components are combined into spatiotemporally flexibly subnetworks where temporal lag in the recruitment of areas within subnetworks is captured. Since individual brain areas are permitted to be part of multiple interleaved subnetworks, both modularity as well as more flexible tendencies of connectivity are accommodated for in the model. Importantly, we show that assignment of subnetworks to the same community (integration) corresponds to positive phase coherence within and between subnetworks, while assignment to different communities (segregation) corresponds to negative phase coherence or orthogonality. Together with disintegration, i.e. the breakdown of internal coupling within subnetwork components, orthogonality facilitates reorganization between subnetworks. In addition, we show that the duration of periods of integration is a function of the coupling strength within subnetworks and subnetwork components which indicates an underlying metastable dynamical regime. Based on the main tendencies for either integration or segregation, subnetworks are further clustered into larger meta-networks that are shown to correspond to combinations of core resting-state networks. We also demonstrate that subnetworks and meta-networks are coarse graining strategies that captures the quasi-cyclic recurrence of global patterns of integration and segregation in the brain. Finally, the method allows us to estimate in broad terms the spectrum of flexible and/or modular tendencies for individual brain areas.

Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.

Recent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD group according to the level of distance of each individual's empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to parsimoniously mimic clinical neuro-stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on the key network measures derived from the simulated brain network and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex.

BACKGROUND: Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders. METHODS: We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics. RESULTS: Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network. LIMITATIONS: Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined. CONCLUSION: Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.

Temporal flow of hubs and connectivity in the human brain.

Hubs in brain network connectivity have previously been observed using neuroimaging techniques and are generally believed to be of pivotal importance to establish and maintain a functional platform on which cognitively meaningful and energy-efficient neuronal communication can occur. However, little is known if hubs are static (i.e. a brain region is always a hub) or if these properties change over time (i.e. brain regions fluctuate in their 'hubness'). To address this question, we introduce two new methodological concepts, the flow of brain connectivity and node penalized shortest paths which are then applied to time-varying functional connectivity fMRI BOLD data. We show that the constellations of active hubs change over time in a non-trivial way and that activity of hubs is dependent on the temporal scale of investigation. Slower fluctuations in the number of active hubs that exceeded the degree expected by chance alone were detected primarily in subcortical structures. Moreover, we observed faster fluctuations in hub activity residing predominately in the default mode network that suggests dynamic events in brain connectivity. Our results suggest that the temporal behavior of connectivity hubs is a multilayered and complex issue where method-specific properties of temporal sensitivity to time-varying connectivity must be taken into account. We discuss our results in relation to the on-going discussion of the existence of discrete and stable states in the resting-brain and the role of network hubs in providing a scaffold for neuronal communication across time.

Dynamic synergetic configurations of resting-state networks in ADHD.

Attention deficit hyperactivity disorder (ADHD) is characterized by high distractibility and impaired executive functions. Notably, there is mounting evidence suggesting that ADHD could be regarded as a default mode network (DMN) disorder. In particular, failure in regulating the dynamics of activity and interactions of the DMN and cognitive control networks have been hypothesized as the main source of task interference causing attentional problems. On the other hand, previous studies indicated pronounced fluctuations in the strength of functional connections over time, particularly for the inter-network connections between the DMN and fronto-parietal control networks. Hence, characterization of connectivity disturbances in ADHD requires a thorough assessment of time-varying functional connectivity (FC). In this study, we proposed a dynamical systems perspective to assess how the DMN over time recruits different configurations of network segregation and integration. Specifically, we were interested in configurations for which both intra- and inter-network connections are retained, as opposed to commonly used methods which assess network segregation as a single measure. From resting-state fMRI data, we extracted three different stable configurations of FC patterns for the DMN, namely synergies. We provided evidence supporting our hypothesis that ADHD differs compared to controls, both in terms of recruitment rate and topology of specific synergies between resting-state networks. In addition, we found a relationship between synergetic cooperation patterns of the DMN with cognitive control networks and a behavioral measure which is sensitive to ADHD-related symptoms, namely the Stroop color-word task.

Simulations to benchmark time-varying connectivity methods for fMRI.

There is a current interest in quantifying time-varying connectivity (TVC) based on neuroimaging data such as fMRI. Many methods have been proposed, and are being applied, revealing new insight into the brain's dynamics. However, given that the ground truth for TVC in the brain is unknown, many concerns remain regarding the accuracy of proposed estimates. Since there exist many TVC methods it is difficult to assess differences in time-varying connectivity between studies. In this paper, we present tvc_benchmarker, which is a Python package containing four simulations to test TVC methods. Here, we evaluate five different methods that together represent a wide spectrum of current approaches to estimating TVC (sliding window, tapered sliding window, multiplication of temporal derivatives, spatial distance and jackknife correlation). These simulations were designed to test each method's ability to track changes in covariance over time, which is a key property in TVC analysis. We found that all tested methods correlated positively with each other, but there were large differences in the strength of the correlations between methods. To facilitate comparisons with future TVC methods, we propose that the described simulations can act as benchmark tests for evaluation of methods. Using tvc_benchmarker researchers can easily add, compare and submit their own TVC methods to evaluate its performance.

A common framework for the problem of deriving estimates of dynamic functional brain connectivity.

The research field of dynamic functional connectivity explores the temporal properties of brain connectivity. To date, many methods have been proposed, which are based on quite different assumptions. In order to understand in which way the results from different techniques can be compared to each other, it is useful to be able to formulate them within a common theoretical framework. In this study, we describe such a framework that is suitable for many of the dynamic functional connectivity methods that have been proposed. Our overall intention was to derive a theoretical framework that was constructed such that a wide variety of dynamic functional connectivity techniques could be expressed and evaluated within the same framework. At the same time, care was given to the fact that key features of each technique could be easily illustrated within the framework and thus highlighting critical assumptions that are made. We aimed to create a common framework which should serve to assist comparisons between different analytical methods for dynamic functional brain connectivity and promote an understanding of their methodological advantages as well as potential drawbacks.

Brain network segregation and integration during an epoch-related working memory fMRI experiment.

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance.

Intrinsic Functional Connectivity in Preterm Infants with Fetal Growth Restriction Evaluated at 12 Months Corrected Age.

Fetal growth restriction (FGR) affects brain development in preterm infants, but little is known about its effects on resting-state functional connectivity. We compared 20 preterm infants, born at <34 weeks of gestation with abnormal antenatal Doppler measurements and birth weights <10th percentile, with 20 appropriate for gestational age preterm infants of similar gestational age and 20 term infants. They were scanned without sedation at 12 months of age and screened for autistic traits at 26 months. Resting functional connectivity was assessed using group independent component analysis and seed-based correlation analysis. The groups showed 10 common resting-state networks involving cortical, subcortical regions, and the cerebellum. Only infants with FGR showed patterns of increased connectivity in the visual network and decreased connectivity in the auditory/language and dorsal attention networks. No significant differences between groups were found using seed-based correlation analysis. FGR infants displayed a higher frequency of early autism features, related to decreased connectivity involving the salience network, than term infants. These data suggest that FGR is an independent risk factor for disrupted intrinsic functional connectivity in preterm infants when they are 1-year old and provide more clues about the neurodevelopmental abnormalities reported in this population.

fMRI Evidence of Magnitude Manipulation during Numerical Order Processing in Congenitally Deaf Signers.

Congenital deafness is often compensated by early sign language use leading to typical language development with corresponding neural underpinnings. However, deaf individuals are frequently reported to have poorer numerical abilities than hearing individuals and it is not known whether the underlying neuronal networks differ between groups. In the present study, adult deaf signers and hearing nonsigners performed a digit and letter order tasks, during functional magnetic resonance imaging. We found the neuronal networks recruited in the two tasks to be generally similar across groups, with significant activation in the dorsal visual stream for the letter order task, suggesting letter identification and position encoding. For the digit order task, no significant activation was found for either of the two groups. Region of interest analyses on parietal numerical processing regions revealed different patterns of activation across groups. Importantly, deaf signers showed significant activation in the right horizontal portion of the intraparietal sulcus for the digit order task, suggesting engagement of magnitude manipulation during numerical order processing in this group.

Addressing a Paradox: Dual Strategies for Creative Performance in Introspective and Extrospective Networks.

Neuroimaging studies of internally generated behaviors have shown seemingly paradoxical results regarding the dorsolateral prefrontal cortex (DLPFC), which has been found to activate, not activate or even deactivate relative to control conditions. On the one hand, the DLPFC has been argued to exert top-down control over generative thought by inhibiting habitual responses; on the other hand, a deactivation and concomitant decrease in monitoring and focused attention has been suggested to facilitate spontaneous associations and novel insights. Here, we demonstrate that prefrontal engagement in creative cognition depends dramatically on experimental conditions, that is, the goal of the task. We instructed professional pianists to perform improvisations on a piano keyboard during fMRI and play, either with a certain emotional content (happy/fearful), or using certain keys (tonal/atonal pitch-sets). We found lower activity in primarily the right DLPFC, dorsal premotor cortex and inferior parietal cortex during emotional conditions compared with pitch-set conditions. Furthermore, the DLPFC was functionally connected to the default mode network during emotional conditions and to the premotor network during pitch-set conditions. The results thus support the notion of two broad cognitive strategies for creative problem solving, relying on extrospective and introspective neural circuits, respectively.