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.

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.

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.

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.

Evaluating patient reported outcomes and experiences in a novel proton beam clinic - challenges, activities, and outcomes of the ProtonCare project

BACKGROUND

The ProtonCare Study Group (PCSG) was formed with the purpose to develop and implement a framework for evaluation of proton beam therapy (PBT) and the related care at a novel clinic (Skandionkliniken), based on patient reported data.

METHOD

A logic model framework was used to describe the process of development and implementation of a structured plan for evaluation of PBT for all diagnoses based on patient reported data. After the mission for the project was determined, meetings with networks and stakeholders were facilitated by PCSG to identify assumptions, resources, challenges, activities, outputs, outcomes, and outcome indicators.

RESULT

This paper presents the challenges and accomplishments PCSG made so far. We describe required resources, activities, and accomplished results. The long-term outcomes that were outlined as a result of the process are two; 1) Improved knowledge about health outcomes of patients that are considered for PBT and 2) The findings will serve as a base for clinical decisions when patients are referred for PBT.

CONCLUSION

Using the logical model framework proved useful in planning and managing the ProtonCare project. As a result, the work of PCSG has so far resulted in long-lasting outcomes that creates a base for future evaluation of patients' perspective in radiotherapy treatment in general and in PBT especially. Our experiences can be useful for other research groups facing similar challenges. Continuing research on patients´ perspective is a central part in ongoing and future research. Collaboration, cooperation, and coordination between research groups/networks from different disciplines are a significant part of the work aiming to determine the more precise role of PBT in future treatment options.

The effects of a 15-week physical exercise intervention on pain modulation in fibromyalgia: Increased pain-related processing within the cortico-striatal- occipital networks, but no improvement of exercise-induced hypoalgesia

Dysfunctional top-down pain modulation is a hallmark of fibromyalgia (FM) and physical exercise is a cornerstone in FM treatment. The aim of this study was to explore the effects of a 15-week intervention of strengthening exercises, twice per week, supervised by a physiotherapist, on exercise-induced hypoalgesia (EIH) and cerebral pain processing in FM patients and healthy controls (HC). FM patients (n = 59) and HC (n = 39) who completed the exercise intervention as part of a multicenter study were examined at baseline and following the intervention. Following the exercise intervention, FM patients reported a reduction of pain intensity, fibromyalgia severity and depression. Reduced EIH was seen in FM patients compared to HC at baseline and no improvement of EIH was seen following the 15-week resistance exercise intervention in either group. Furthermore, a subsample (Stockholm site: FM n = 18; HC n = 19) was also examined with functional magnetic resonance imaging (fMRI) during subjectively calibrated thumbnail pressure pain stimulations at baseline and following intervention. A significant main effect of exercise (post > pre) was observed both in FM patients and HC, in pain-related brain activation within left dorsolateral prefrontal cortex and caudate, as well as increased functional connectivity between caudate and occipital lobe bordering cerebellum (driven by the FM patients). In conclusion, the results indicate that 15-week resistance exercise affect pain-related processing within the cortico-striatal-occipital networks (involved in motor control and cognition), rather than directly influencing top-down descending pain inhibition. In alignment with this, exercise-induced hypoalgesia remained unaltered.

Motor inhibition and its contribution to recovery of dexterous hand use after stroke

Recovery of dexterous hand use is critical for functional outcome after stroke. Grip force recordings can inform on maximal motor output and modulatory and inhibitory cerebral functions, but how these actually contribute to recovery of dexterous hand use is unclear. This cohort study used serially assessed measures of hand kinetics to test the hypothesis that behavioural measures of motor modulation and inhibition explain dexterity recovery beyond that explained by measures of motor output alone. We also investigated the structural and functional connectivity correlates of grip force control recovery.

Eighty-nine adults (median age = 54 years, 26% females) with first-ever ischaemic or haemorrhagic stroke and persistent arm and hand paresis were assessed longitudinally, at 3 weeks, and at 3 and 6 months after stroke. Kinetic measures included: maximal grip force, accuracy of precision and power grip force control, and ability to release force abruptly. Dexterous hand use was assessed clinically with the Box and Block Test and motor impairment with the upper extremity Fugl-Meyer Assessment. Structural and functional MRI was used to assess weighted corticospinal tract lesion load, voxel-based lesion symptom mapping and interhemispheric resting-state functional connectivity.

Fifty-three per cent of patients had severe initial motor impairment and a majority still had residual force control impairments at 6 months. Force release at 3 weeks explained 11% additional variance of Box and Block Test outcome at 6 months, above that explained by initial scores (67%). Other kinetic measures did not explain additional variance of recovery. The predictive value of force release remained significant when controlling for corticospinal tract lesion load and clinical measures. Corticospinal tract lesion load correlated with recovery in grip force control measures. Lesions involving the parietal operculum, insular cortex, putamen and fronto-striatal tracts were also related to poorer force modulation and release. Lesions to fronto-striatal tracts explained an additional 5% of variance in force release beyond the 43% explained by corticospinal injury alone. Interhemispheric functional connectivity did not relate to force control recovery.

We conclude that not only voluntary force generation but also force release (reflecting motor inhibition) are important for recovery of dexterous hand use after stroke. Although corticospinal injury is a main determinant of recovery, lesions to integrative somatosensory areas and fronto-parietal white matter (involved in motor inhibition) explain additional variance in post-stroke force release recovery. Our findings indicate that post-stroke upper limb motor impairment profiling, which is essential for targeted treatment, should consider both voluntary grasp generation and inhibition.

Multiple spatial scale mapping of time-resolved brain network reconfiguration during evoked pain in patients with rheumatoid arthritis

Functional brain networks and the perception of pain can fluctuate over time. However, how the time-dependent reconfiguration of functional brain networks contributes to chronic pain remains largely unexplained. Here, we explored time-varying changes in brain network integration and segregation during pain over a disease-affected area (joint) compared to a neutral site (thumbnail) in 28 patients with rheumatoid arthritis (RA) in comparison with 22 healthy controls (HC). During functional magnetic resonance imaging, all subjects received individually calibrated pain pressures corresponding to visual analog scale 50 mm at joint and thumbnail. We implemented a novel approach to track changes of task-based network connectivity over time. Within this framework, we quantified measures of integration (participation coefficient, PC) and segregation (within-module degree z-score). Using these network measures at multiple spatial scales, both at the level of single nodes (brain regions) and communities (clusters of nodes), we found that PC at the community level was generally higher in RA patients compared to HC during and after painful pressure over the inflamed joint and corresponding site in HC. This shows that all brain communities integrate more in RA patients than in HC for time points following painful stimulation to a disease-relevant body site. However, the elevated community-related integration seen in patients appeared to not pertain uniquely to painful stimulation at the inflamed joint, but also at the neutral thumbnail, as integration and segregation at the community level did not differ across body sites in patients. Moreover, there was no specific nodal contribution to brain network integration or segregation. Altogether, our findings indicate widespread and persistent changes in network interaction in RA patients compared to HC in response to painful stimulation.

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.

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.

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.

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.

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.

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.

A tree's quest for light-optimal height and diameter growth under a shading canopy

For trees in forests, striving for light is matter of life and death, either by growing taller toward brighter conditions or by expanding the crown to capture more of the available light. Here, we present a mechanistic model for the development path of stem height and crown size, accounting for light capture and growth, as well as mortality risk. We determine the optimal growth path among all possible trajectories using dynamic programming. The optimal growth path follows a sequence of distinct phases: (i) initial crown size expansion, (ii) stem height growth toward the canopy, (iii) final expansion of the crown in the canopy and (iv) seed production without further increase in size. The transition points between these phases can be optimized by maximizing fitness, defined as expected lifetime reproductive production. The results imply that to reach the canopy in an optimal way, trees must consider the full profile of expected increasing light levels toward the canopy. A shortsighted maximization of growth based on initial light conditions can result in arrested height growth, preventing the tree from reaching the canopy. The previous result can explain canopy stratification, and why canopy species often get stuck at a certain size under a shading canopy. The model explains why trees with lower wood density have a larger diameter at a given tree height and grow taller than trees with higher wood density. The model can be used to implement plasticity in height versus diameter growth in individual-based vegetation and forestry models.

Mandibulotomy access to tumour sites: fewer complications for postoperative compared with preoperative radiotherapy

The purpose of this study was to compare complication rates at the mandibulotomy site between patients receiving preoperative radiotherapy (RT) and those receiving postoperative RT during treatment for oral and oropharyngeal cancer where the surgical procedure required a mandibular osteotomy to gain access to the tumour. Sixty-four consecutive patients treated during the period 2000-2015 were available for analysis. Their medical records were reviewed retrospectively. All patients were followed for at least 1year postoperatively. A subgroup of patients received RT on several occasions or long before the mandibulotomy, therefore the statistical comparisons focused on the two groups of patients receiving RT on one occasion and within 6 months prior to or following surgery. Seventeen patients presented a total of 29 complications, yielding an overall complication rate of 27%. Orocutaneous fistula was the most common complication. Patients who received RT preoperatively presented a higher complication rate (9/15; 60%) when compared to those who received RT postoperatively (2/31; 6.5%) (odds ratio 21.8, P<0.001). This study demonstrated fewer complications in the mandibulotomy area exposed to postoperative RT compared with preoperative RT. It is therefore suggested that, when possible, RT should be given postoperatively if combination treatment with RT and surgery, including a mandibulotomy, is planned.

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.

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.

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.

Altered cerebral pain processing of noxious stimuli from inflamed joints in rheumatoid arthritis: An event-related fMRI study

OBJECTIVE

To our knowledge, this is the first study assessing brain activation in response to painful stimulation over disease-relevant (finger joint) vs. neutral area (thumb nail) in patients suffering from rheumatoid arthritis (RA) compared to healthy controls (HC).

METHOD

Thirty-one RA patients and 23 HC underwent functional magnetic resonance imaging (fMRI) while stimulated with subjectively calibrated painful pressures corresponding to a pain sensation of 50 mm on a 100 mm VAS scale (P50) at disease-affected finger joint and thumbnail (left hand), and corresponding sites in HC.

RESULTS

Compared to controls, RA patients had significantly increased pain sensitivity (lower P50) at the inflamed joints but not at the thumbnail. RA patients exhibited significantly less activation in regions related to pain- and somatosensory processing (S1, M1, anterior insula, S2, SMG and MCC) during painful joint stimulation, compared to HC. No group difference in cerebral pain processing was found for the non-affected thumbnail. Within RA patients, significantly less brain activation was found in response to painful stimulation over disease-affected joint compared to non-affected thumbnail in bilateral S1, bilateral S2, and anterior insula. Further, RA patients exhibited a right-sided dlPFC deactivation, psycho-physiologically interacting (PPI) with the left dlPFC in response to painful stimulation at disease-affected joints.

CONCLUSION

The results indicate normal pain sensitivity and cerebral pain processing in RA for non-affected sites, while the increased sensitivity at inflamed joints indicate peripheral/spinal sensitization. Brain imaging data suggest that disease-relevant pain processing in RA is marked by aberrations and a failed initiation of cortical top-down regulation.

Adaptive frequency-based modeling of whole-brain oscillations: Predicting regional vulnerability and hazardousness rates

Whole-brain computational modeling based on structural connectivity has shown great promise in successfully simulating fMRI BOLD signals with temporal coactivation patterns that are highly similar to empirical functional connectivity patterns during resting state. Importantly, previous studies have shown that spontaneous fluctuations in coactivation patterns of distributed brain regions have an inherent dynamic nature with regard to the frequency spectrum of intrinsic brain oscillations. In this modeling study, we introduced frequency dynamics into a system of coupled oscillators, where each oscillator represents the local mean-field model of a brain region. We first showed that the collective behavior of interacting oscillators reproduces previously shown features of brain dynamics. Second, we examined the effect of simulated lesions in gray matter by applying an in silico perturbation protocol to the brain model. We present a new approach to map the effects of vulnerability in brain networks and introduce a measure of regional hazardousness based on mapping of the degree of divergence in a feature space.

Single institution followed by national implementation of systematic surgical quality control and feedback for radical prostatectomy: a 20-year journey

Purpose

The demand for objective and outcome-based facts about surgical results after radical prostatectomy (RP) is increasing. Systematic feedback is also essential for each surgeon to improve his/her performance.

Methods

RP outcome data (e.g., pT-stage and margin status) have been registered at Sahlgrenska University Hospital (SUH) since 1988 and patient-related outcome measures (PROM) have been registered since 2001. The National Prostate Cancer Registry (NPCR) has covered all Regions in Sweden since 1998 and includes PROM-data from 2008. Initially PROM was on-paper questionnaires but due since 2018 all PROMs are collected electronically. In 2014 an on-line “dashboard” panel was introduced, showing the results for ten quality-control variables in real-time. Since 2017 all RP data on hospital, regional, and national levels are publicly accessible on-line on “www.npcr.se/RATTEN”.

Results

The early PROM-data from SUH have been used for internal quality control. As national clinical and PROM-data from the NPCR have been made accessible on-line and in real-time we have incorporated this into our pre-existing protocol. Our data are now internally available as real-time NPCR reports on the individual surgeons’ results, as well as ePROM data. We can compare the results of each surgeon internally and to other departments’ aggregated data. The public can access data and compare hospital level data on “RATTEN”.

Conclusions

The process of quality control of RP locally at SUH, and nationally through the NPCR, has been long but fruitful. The online design, with direct real-time feedback to the institutions that report the data, is essential.

Cue reactivity and opioid blockade in amphetamine dependence: A randomized, controlled fMRI study

BACKGROUND

The opioid antagonist, naltrexone, has been shown to reduce the risk of relapse in amphetamine dependence, but the mechanisms behind this effect are not well understood. We aimed to investigate if naltrexone attenuates cue reactivity and craving in amphetamine dependence.

METHODS

Forty men with severe, intravenous amphetamine dependence were randomized to one dose of naltrexone (50 mg) or placebo. In a BOLD fMRI cue reactivity paradigm, they were exposed to drug-related and neutral films and gave subjective ratings of craving after each film. Twenty-nine patients left data of sufficient quality to be included in the final analysis.

RESULTS

The drug-related films elicited strong subjective craving and BOLD activations of the striatum, cingulate cortex, and occipito-temporal visual attention networks. Longer history of amphetamine use was associated with greater activations of the prefrontal cortex. Naltrexone as compared to placebo had no significant effects on brain activations or subjective ratings.

CONCLUSION

Patients with severe stimulant use disorder exhibit strong neural cue reactivity, the patterns of which are modulated by duration of drug use. In this sample, we found no evidence for any effects of naltrexone on cue reactivity.

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.

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.

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.

Intrinsic brain connectivity after partial sleep deprivation in young and older adults: results from the Stockholm Sleepy Brain study

Sleep deprivation has been reported to affect intrinsic brain connectivity, notably reducing connectivity in the default mode network. Studies to date have however shown inconsistent effects, in many cases lacked monitoring of wakefulness, and largely included young participants. We investigated effects of sleep deprivation on intrinsic brain connectivity in young and older participants. Participants aged 20–30 (final n = 30) and 65–75 (final n = 23) years underwent partial sleep deprivation (3 h sleep) in a cross-over design, with two 8-minutes eyes-open resting state functional magnetic resonance imaging (fMRI) runs in each session, monitored by eye-tracking. We assessed intrinsic brain connectivity using independent components analysis (ICA) as well as seed-region analyses of functional connectivity, and also analysed global signal variability, regional homogeneity, and the amplitude of low-frequency fluctuations. Sleep deprivation caused increased global signal variability. Changes in investigated resting state networks and in regional homogeneity were not statistically significant. Younger participants had higher connectivity in most examined networks, as well as higher regional homogeneity in areas including anterior and posterior cingulate cortex. In conclusion, we found that sleep deprivation caused increased global signal variability, and we speculate that this may be caused by wake-state instability.

The role of long-term physical exercise on performance and brain activation during the Stroop colour word task in fibromyalgia patients

The Stroop colour word test (SCWT) has been widely used to assess changes in cognitive performance such as processing speed, selective attention and the degree of automaticity. Moreover, the SCWT has proven to be a valuable tool to assess neuronal plasticity that is coupled to improvement in performance in clinical populations. In a previous study, we showed impaired cognitive processing during SCWT along with reduced task-related activations in patients with fibromyalgia. In this study, we used SCWT and functional magnetic resonance imagingFMRI to investigate the effects of a 15-week physical exercise intervention on cognitive performance, task-related cortical activation and distraction-induced analgesia (DIA) in patients with fibromyalgia and healthy controls. The exercise intervention yielded reduced fibromyalgia symptoms, improved cognitive processing and increased task-related activation of amygdala, but no effect on DIA. Our results suggest beneficial effects of physical exercise on cognitive functioning in FM.

From static to temporal network theory: Applications to functional brain connectivity

Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain's network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i) to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii) to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto.

Spatial confluence of psychological and anatomical network constructs in the human brain revealed by a mass meta-analysis of fMRI activation

It is well-known that the brain's activity is organized into networks but it is unclear how many networks exist. Additionally, there is also a risk of ambiguity since different names for the same network are frequently reported in the literature. In this study, we employed a mass meta-analysis of fMRI data associated with network constructs originating from both psychology and neuroscience. Based on the results from the meta-analysis, we derived a spatial similarity map between all construct terms, showing that the brain's networks cluster hierarchically into several levels. The results presented are useful as a first step in developing a unified terminology for large-scale brain network and a platform for a queryable network atlas.

Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity

The brain is organized into large scale spatial networks that can be detected during periods of rest using fMRI. The brain is also a dynamic organ with activity that changes over time. We developed a method and investigated properties where the connections as a function of time are derived and quantified. The point based method (PBM) presented here derives covariance matrices after clustering individual time points based upon their global spatial pattern. This method achieved increased temporal sensitivity, together with temporal network theory, allowed us to study functional integration between resting-state networks. Our results show that functional integrations between two resting-state networks predominately occurs in bursts of activity. This is followed by varying intermittent periods of less connectivity. The described point-based method of dynamic resting-state functional connectivity allows for a detailed and expanded view on the temporal dynamics of resting-state connectivity that provides novel insights into how neuronal information processing is integrated in the human brain at the level of large-scale networks.

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

The translocator protein gene is associated with symptom severity and cerebral pain processing in fibromyalgia

The translocator protein (TSPO) is upregulated during glia activation in chronic pain patients. TSPO constitutes the rate-limiting step in neurosteroid synthesis, thus modulating synaptic transmission. Related serotonergic mechanisms influence if pro- or anti-nociceptive neurosteroids are produced. This study investigated the effects of a functional genetic polymorphism regulating the binding affinity to the TSPO, thus affecting symptom severity and cerebral pain processing in fibromyalgia patients. Gene-to-gene interactions with a functional polymorphism of the serotonin transporter gene were assessed. Fibromyalgia patients (n=126) were genotyped regarding the polymorphisms of the TSPO (rs6971) and the serotonin transporter (5-HTTLPR/rs25531). Functional magnetic resonance imaging (n=24) was used to study brain activation during individually calibrated pressure pain. Compared to mixed/low TSPO affinity binders, the high TSPO affinity binders rated more severe pain (p=0.016) and fibromyalgia symptoms (p=0.02). A significant interaction was found between the TSPO and the serotonin transporter polymorphisms regarding pain severity (p<0.0001). Functional connectivity analyses revealed that the TSPO high affinity binding group had more pronounced pain-evoked functional connectivity in the right frontoparietal network, between the dorsolateral prefrontal area and the parietal cortex. In conclusion, fibromyalgia patients with the TSPO high affinity binding genotype reported a higher pain intensity and more severe fibromyalgia symptoms compared to mixed/low affinity binders, and this was modulated by interaction with the serotonin transporter gene. To our knowledge this is the first evidence of functional genetic polymorphisms affecting pain severity in FM and our findings are in line with proposed glia-related mechanisms. Furthermore, the functional magnetic resonance findings indicated an effect of translocator protein on the affective-motivational components of pain perception.

The functional brain connectome of the child and autism spectrum disorders

Brain connectomics is a relatively new field of research that maps the brain's large-scale structural and functional networks at rest. The connectome of the human brain develops progressively from early infancy to late adolescence, and this review describes the theory behind the concept and its applicability to studying the development and dynamics of brain networks through graph theoretical metrics. We also describe how the brain connectome concept could further our understanding of autism spectrum disorders (ASD) CONCLUSION: Further research into the functional child brain connectome concept could enhance our understanding of atypical brain connectivity patterns presumed to be linked to ASD.

Intrinsic functional connectivity of insular cortex and symptoms of sickness during acute experimental inflammation

Task-based fMRI has been used to study the effects of experimental inflammation on the human brain, but it remains unknown whether intrinsic connectivity in the brain at rest changes during a sickness response. Here, we investigated the effect of experimental inflammation on connectivity between areas relevant for monitoring of bodily states, motivation, and subjective symptoms of sickness. In a double-blind randomized controlled experiment, 52 healthy volunteers were injected with 0.6ng/kg LPS (lipopolysaccharide) or placebo, and participated in a resting state fMRI experiment after approximately 2h 45min. Resting state fMRI data were available from 48 participants, of which 28 received LPS and 20 received placebo. Bilateral anterior and bilateral posterior insula sections were used as seed regions and connectivity with bilateral orbitofrontal and cingulate (anterior and middle) cortices was investigated. Back pain, headache and global sickness increased significantly after as compared to before LPS, while a non-significant trend was shown for increased nausea. Compared to placebo, LPS was followed by increased connectivity between left anterior insula and left midcingulate cortex. This connectivity was significantly correlated to increase in back pain after LPS and tended to be related to increased global sickness, but was not related to increased headache or nausea. LPS did not affect the connectivity from other insular seeds. In conclusion, the finding of increased functional connectivity between left anterior insula and middle cingulate cortex suggests a potential neurophysiological mechanism that can be further tested to understand the subjective feeling of malaise and discomfort during a sickness response.

Intrinsic Brain Connectivity in Chronic Pain: A Resting-State fMRI Study in Patients with Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) is commonly accompanied by pain that is discordant with the degree of peripheral pathology. Very little is known about the cerebral processes involved in pain processing in RA. Here we investigated resting-state brain connectivity associated with prolonged pain in RA.

Methods: 24 RA subjects and 19 matched controls were compared with regard to both behavioral measures of pain perception and resting-resting state fMRI data acquired subsequently to fMRI sessions involving pain stimuli. The resting-state fMRI brain connectivity was investigated using 159 seed regions located in cardinal pain processing brain regions. Additional principal component based multivariate pattern analysis of the whole brain connectivity pattern was carried out in a data driven analysis to localize group differences in functional connectivity.

Results: When RA patients were compared to controls, we observed significantly lower pain resilience for pressure on the affected finger joints (i.e., P50-joint) and an overall heightened level of perceived global pain in RA patients. Relative to controls, RA patients displayed increased brain connectivity predominately for the supplementary motor areas, mid-cingulate cortex, and the primary sensorimotor cortex. Additionally, we observed an increase in brain connectivity between the insula and prefrontal cortex as well as between anterior cingulate cortex and occipital areas for RA patients. None of the group differences in brain connectivity were significantly correlated with behavioral parameters.

Conclusion: Our study provides experimental evidence of increased connectivity between frontal midline regions that are implicated in affective pain processing and bilateral sensorimotor regions in RA patients.

Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy

Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM). However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI) before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown aberrant patterns of intrinsic brain activity in FM. Fourteen FM patients and eleven healthy controls successfully completed the physical exercise treatment. We investigated post- versus pre-treatment changes of brain connectivity, as well as changes in clinical symptoms in the patient group. FM patients reported improvements in symptom severity. Although several brain regions showed a treatment-related change in connectivity, only the connectivity between the right anterior insula and the left primary sensorimotor area was significantly more affected by the physical exercise among the fibromyalgia patients compared to healthy controls. Our results suggest that previously observed aberrant intrinsic brain connectivity patterns in FM are partly normalized by the physical exercise therapy. However, none of the observed normalizations in intrinsic brain connectivity were significantly correlated with symptom changes. Further studies conducted in larger cohorts are warranted to investigate the precise relationship between improvements in fibromyalgia symptoms and changes in intrinsic brain activity.

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Physical exercise reduced the impact of fibromyalgia (FM) in everyday life.

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Longitudinal changes included restored insular-sensory functional connectivity.

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The links between connectivity and symptom improvements require further studies.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

The frequency dimension of fMRI dynamic connectivity: Network connectivity, functional hubs and integration in the resting brain

The large-scale functional MRI connectome of the human brain is composed of multiple resting-state networks (RSNs). However, the network dynamics, such as integration and segregation between and within RSNs is largely unknown. To address this question we created high-resolution "frequency graphlets", connectivity matrices derived across the low-frequency spectrum of the BOLD fMRI resting-state signal (0.01-0.1 Hz) in a cohort of 100 subjects. We then apply and compare graph theoretical measures across the frequency graphlets. Our results show that the within- and between-network connectivity and presence of functional hubs shift as a function of frequency. Furthermore, we show that the small world network property peaks at different frequencies with corresponding spatial connectivity profiles. We conclude that the frequency dependence of the network connectivity and the spatial configuration of functional hubs suggest that the dynamics of large-scale network integration and segregation operate at different time scales.

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.

Phonology and arithmetic in the language-calculation network

Arithmetic and language processing involve similar neural networks, but the relative engagement remains unclear. In the present study we used fMRI to compare activation for phonological, multiplication and subtraction tasks, keeping the stimulus material constant, within a predefined language-calculation network including left inferior frontal gyrus and angular gyrus (AG) as well as superior parietal lobule and the intraparietal sulcus bilaterally. Results revealed a generally left lateralized activation pattern within the language-calculation network for phonology and a bilateral activation pattern for arithmetic, and suggested regional differences between tasks. In particular, we found a more prominent role for phonology than arithmetic in pars opercularis of the left inferior frontal gyrus but domain generality in pars triangularis. Parietal activation patterns demonstrated greater engagement of the visual and quantity systems for calculation than language. This set of findings supports the notion of a common, but regionally differentiated, language-calculation network.