Breakdown of Whole-brain Dynamics in Preterm-born Children.

The brain operates at a critical point that is balanced between order and disorder. Even during rest, unstable periods of random behavior are interspersed with stable periods of balanced activity patterns that support optimal information processing. Being born preterm may cause deviations from this normal pattern of development. We compared 33 extremely preterm (EPT) children born at < 27 weeks of gestation and 28 full-term controls. Two approaches were adopted in both groups, when they were 10 years of age, using structural and functional brain magnetic resonance imaging data. The first was using a novel intrinsic ignition analysis to study the ability of the areas of the brain to propagate neural activity. The second was a whole-brain Hopf model, to define the level of stability, desynchronization, or criticality of the brain. EPT-born children exhibited fewer intrinsic ignition events than controls; nodes were related to less sophisticated aspects of cognitive control, and there was a different hierarchy pattern in the propagation of information and suboptimal synchronicity and criticality. The largest differences were found in brain nodes belonging to the rich-club architecture. These results provide important insights into the neural substrates underlying brain reorganization and neurodevelopmental impairments related to prematurity.

Disrupted brain structural connectivity in Pediatric Bipolar Disorder with psychosis.

Bipolar disorder (BD) has been linked to disrupted structural and functional connectivity between prefrontal networks and limbic brain regions. Studies of patients with pediatric bipolar disorder (PBD) can help elucidate the developmental origins of altered structural connectivity underlying BD and provide novel insights into the aetiology of BD. Here we compare the network properties of whole-brain structural connectomes of euthymic PBD patients with psychosis, a variant of PBD, and matched healthy controls. Our results show widespread changes in the structural connectivity of PBD patients with psychosis in both cortical and subcortical networks, notably affecting the orbitofrontal cortex, frontal gyrus, amygdala, hippocampus and basal ganglia. Graph theoretical analysis revealed that PBD connectomes have fewer hubs, weaker rich club organization, different modular fingerprint and inter-modular communication, compared to healthy participants. The relationship between network features and neurocognitive and psychotic scores was also assessed, revealing trends of association between patients' IQ and affective psychotic symptoms with the local efficiency of the orbitofrontal cortex. Our findings reveal that PBD with psychosis is associated with significant widespread changes in structural network topology, thus strengthening the hypothesis of a reduced capacity for integrative processing of information across brain regions. Localised network changes involve core regions for emotional processing and regulation, as well as memory and executive function, some of which show trends of association with neurocognitive faculties and symptoms. Together, our findings provide the first comprehensive characterisation of the alterations in local and global structural brain connectivity and network topology, which may contribute to the deficits in cognition and emotion processing and regulation found in PBD.

Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder.

Neurobiological models to explain vulnerability of major depressive disorder (MDD) are scarce and previous functional magnetic resonance imaging studies mostly examined "static" functional connectivity (FC). Knowing that FC constantly evolves over time, it becomes important to assess how FC dynamically differs in remitted-MDD patients vulnerable for new depressive episodes. Using a recently developed method to examine dynamic FC, we characterized re-emerging FC states during rest in 51 antidepressant-free MDD patients at high risk of recurrence (≥2 previous episodes), and 35 healthy controls. We examined differences in occurrence, duration, and switching profiles of FC states after neutral and sad mood induction. Remitted MDD patients showed a decreased probability of an FC state (p < 0.005) consisting of an extensive network connecting frontal areas-important for cognitive control-with default mode network, striatum, and salience areas, involved in emotional and self-referential processing. Even when this FC state was observed in patients, it lasted shorter (p < 0.005) and was less likely to switch to a smaller prefrontal-striatum network (p < 0.005). Differences between patients and controls decreased after sad mood induction. Further, the duration of this FC state increased in remitted patients after sad mood induction but not in controls (p < 0.05). Our findings suggest reduced ability of remitted-MDD patients, in neutral mood, to access a clinically relevant control network involved in the interplay between externally and internally oriented attention. When recovering from sad mood, remitted recurrent MDD appears to employ a compensatory mechanism to access this FC state. This study provides a novel neurobiological profile of MDD vulnerability.

Neural responses during the anticipation and receipt of olfactory reward and punishment in human.

Pleasure experience is an important part of normal healthy life and is essential for general and mental well-being. Many neuroimaging studies have investigated the underlying neural processing of verbal and visual modalities of reward. However, how the brain processes rewards in the olfactory modality is not fully understood. This study aimed to examine the neural basis of olfactory rewards in 25 healthy participants using functional magnetic resonance imaging (fMRI). We developed an Olfactory Incentive Delay (OLID) imaging task distinguishing between the anticipation and receipt of olfactory rewards and punishments. We found that the pallidum was activated during the anticipation of both olfactory rewards and punishments. The bilateral insula was activated independently from the odours' hedonic valence during the receipt phase. In addition, right caudate activation during the anticipation of unpleasant odours was correlated with self-reported anticipatory hedonic traits, whereas bilateral insular activation during the receipt of pleasant odours was correlated with self-reported consummatory hedonic traits. These findings suggest that activity in the insula and the caudate may be biomarkers of anhedonia. These findings also highlight a useful and valid paradigm to study the neural circuitry underlying reward processing in people with anhedonia.

Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson's disease.

Deep brain stimulation (DBS) for Parkinson's disease is a highly effective treatment in controlling otherwise debilitating symptoms. Yet the underlying brain mechanisms are currently not well understood. Whole-brain computational modeling was used to disclose the effects of DBS during resting-state functional Magnetic Resonance Imaging in ten patients with Parkinson's disease. Specifically, we explored the local and global impact that DBS has in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts global brain dynamics of patients towards a Healthy regime. This effect was more pronounced in very specific brain areas such as the thalamus, globus pallidus and orbitofrontal regions of the right hemisphere (with the left hemisphere not analyzed given artifacts arising from the electrode lead). Global aspects of integration and synchronization were also rebalanced. Empirically, we found higher communicability and coherence brain measures during DBS-ON compared to DBS-OFF. Finally, using our model as a framework, artificial in silico DBS was applied to find potential alternative target areas for stimulation and whole-brain rebalancing. These results offer important insights into the underlying large-scale effects of DBS as well as in finding novel stimulation targets, which may offer a route to more efficacious treatments.

Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data.

During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies. Considering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.

The most relevant human brain regions for functional connectivity: Evidence for a dynamical workspace of binding nodes from whole-brain computational modelling.

In order to promote survival through flexible cognition and goal-directed behaviour, the brain has to optimize segregation and integration of information into coherent, distributed dynamical states. Certain organizational features of the brain have been proposed to be essential to facilitate cognitive flexibility, especially hub regions in the so-called rich club which show dense interconnectivity. These structural hubs have been suggested to be vital for integration and segregation of information. Yet, this has not been evaluated in terms of resulting functional temporal dynamics. A complementary measure covering the temporal aspects of functional connectivity could thus bring new insights into a more complete picture of the integrative nature of brain networks. Here, we use causal whole-brain computational modelling to determine the functional dynamical significance of the rich club and compare this to a new measure of the most functionally relevant brain regions for binding information over time ("dynamical workspace of binding nodes"). We found that removal of the iteratively generated workspace of binding nodes impacts significantly more on measures of integration and encoding of information capability than the removal of the rich club regions. While the rich club procedure produced almost half of the binding nodes, the remaining nodes have low degree yet still play a significant role in the workspace essential for binding information over time and as such goes beyond a description of the structural backbone.

Insights into Brain Architectures from the Homological Scaffolds of Functional Connectivity Networks.

In recent years, the application of network analysis to neuroimaging data has provided useful insights about the brain's functional and structural organization in both health and disease. This has proven a significant paradigm shift from the study of individual brain regions in isolation. Graph-based models of the brain consist of vertices, which represent distinct brain areas, and edges which encode the presence (or absence) of a structural or functional relationship between each pair of vertices. By definition, any graph metric will be defined upon this dyadic representation of the brain activity. It is however unclear to what extent these dyadic relationships can capture the brain's complex functional architecture and the encoding of information in distributed networks. Moreover, because network representations of global brain activity are derived from measures that have a continuous response (i.e., interregional BOLD signals), it is methodologically complex to characterize the architecture of functional networks using traditional graph-based approaches. In the present study, we investigate the relationship between standard network metrics computed from dyadic interactions in a functional network, and a metric defined on the persistence homological scaffold of the network, which is a summary of the persistent homology structure of resting-state fMRI data. The persistence homological scaffold is a summary network that differs in important ways from the standard network representations of functional neuroimaging data: (i) it is constructed using the information from all edge weights comprised in the original network without applying an ad hoc threshold and (ii) as a summary of persistent homology, it considers the contributions of simplicial structures to the network organization rather than dyadic edge-vertices interactions. We investigated the information domain captured by the persistence homological scaffold by computing the strength of each node in the scaffold and comparing it to local graph metrics traditionally employed in neuroimaging studies. We conclude that the persistence scaffold enables the identification of network elements that may support the functional integration of information across distributed brain networks.

The neural mechanism of hedonic processing and judgment of pleasant odors: An activation likelihood estimation meta-analysis.

OBJECTIVE: Pleasure is essential to normal healthy life. Olfaction, as 1 of the neurobehavioral probes of hedonic capacity, has a unique advantage compared to other sensory modalities. However, it is unclear how olfactory hedonic information is processed in the brain. This study aimed to investigate olfactory hedonic processing in the human brain. METHOD: We conducted an activation likelihood estimation (ALE) meta-analysis on 16 functional imaging studies that examined brain activation in olfactory hedonic processing-related tasks in healthy adults. RESULTS: The results show that there is a core olfactory hedonic processing network, which consists of the bilateral parahippocampal gyrus/amygdala (BA34), the left middle frontal gyrus (BA6), the right middle frontal gyrus/lateral orbitofrontal cortex (OFC; BA10), the bilateral cingulate gyrus (BA32), the right lentiform nucleus/lateral globus pallidus, the right medial frontal gyrus/medial OFC (BA11), the left superior frontal gyrus (BA10), and the right insula (BA13). Moreover, our findings highlight that the right hemisphere is predominant in explicit odor hedonic judgment. Finally, the results indicate that there are significant differences in brain activation for hedonic judgment and passive smelling. CONCLUSION: These results support the hypothesis that the OFC plays a key role in explicit hedonic judgment. (PsycINFO Database Record

Tractography Study of Deep Brain Stimulation of the Anterior Cingulate Cortex in Chronic Pain: Key to Improve the Targeting.

BACKGROUND: Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) is a new treatment for alleviating intractable neuropathic pain. However, it fails to help some patients. The large size of the ACC and the intersubject variability make it difficult to determine the optimal site to position DBS electrodes. The aim of this work was therefore to compare the ACC connectivity of patients with successful versus unsuccessful DBS outcomes to help guide future electrode placement. METHODS: Diffusion magnetic resonance imaging (dMRI) and probabilistic tractography were performed preoperatively in 8 chronic pain patients (age 53.4 ± 6.1 years, 2 females) with ACC DBS, of whom 6 had successful (SO) and 2 unsuccessful outcomes (UOs) during a period of trialing. RESULTS: The number of patients was too small to demonstrate any statistically significant differences. Nevertheless, we observed differences between patients with successful and unsuccessful outcomes in the fiber tract projections emanating from the volume of activated tissue around the electrodes. A strong connectivity to the precuneus area seems to predict unsuccessful outcomes in our patients (UO: 160n/SO: 27n), with (n), the number of streamlines per nonzero voxel. On the other hand, connectivity to the thalamus and brainstem through the medial forebrain bundle (MFB) was only observed in SO patients. CONCLUSIONS: These findings could help improve presurgical planning by optimizing electrode placement, to selectively target the tracts that help to relieve patients' pain and to avoid those leading to unwanted effects.

Evidence for a Caregiving Instinct: Rapid Differentiation of Infant from Adult Vocalizations Using Magnetoencephalography.

Crying is the most salient vocal signal of distress. The cries of a newborn infant alert adult listeners and often elicit caregiving behavior. For the parent, rapid responding to an infant in distress is an adaptive behavior, functioning to ensure offspring survival. The ability to react rapidly requires quick recognition and evaluation of stimuli followed by a co-ordinated motor response. Previous neuroimaging research has demonstrated early specialized activity in response to infant faces. Using magnetoencephalography, we found similarly early (100-200 ms) differences in neural responses to infant and adult cry vocalizations in auditory, emotional, and motor cortical brain regions. We propose that this early differential activity may help to rapidly identify infant cries and engage affective and motor neural circuitry to promote adaptive behavioral responding, before conscious awareness. These differences were observed in adults who were not parents, perhaps indicative of a universal brain-based "caregiving instinct."

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation.

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Hypoactivation in right inferior frontal cortex is specifically associated with motor response inhibition in adult ADHD.

Adult ADHD has been linked to impaired motor response inhibition and reduced associated activation in the right inferior frontal cortex (IFC). However, it is unclear whether abnormal inferior frontal activation in adult ADHD is specifically related to a response inhibition deficit or reflects a more general deficit in attentional processing. Using functional magnetic resonance imaging, we tested a group of 19 ADHD patients with no comorbidities and a group of 19 healthy control volunteers on a modified go/no-go task that has been shown previously to distinguish between cortical responses related to response inhibition and attentional shifting. Relative to the healthy controls, ADHD patients showed increased commission errors and reduced activation in inferior frontal cortex during response inhibition. Crucially, this reduced activation was observed when controlling for attentional processing, suggesting that hypoactivation in right IFC in ADHD is specifically related to impaired response inhibition. The results are consistent with the notion of a selective neurocognitive deficit in response inhibition in adult ADHD associated with abnormal functional activation in the prefrontal cortex, whilst ruling out likely group differences in attentional orienting, arousal and motivation.

Targeting the affective component of chronic pain: a case series of deep brain stimulation of the anterior cingulate cortex.

BACKGROUND: Deep brain stimulation (DBS) has shown considerable promise for relieving nociceptive and neuropathic symptoms of refractory chronic pain. Nevertheless, for some patients, standard DBS for pain remains poorly efficacious. Pain is a multidimensional experience with an affective component: the unpleasantness. The anterior cingulate cortex (ACC) is a structure involved in this affective component, and targeting it may relieve patients' pain. OBJECTIVE: To describe the first case series of ACC DBS to relieve the affective component of chronic neuropathic pain. METHODS: Sixteen patients (13 male and 3 female patients) with neuropathic pain underwent bilateral ACC DBS. The mean age at surgery was 48.7 years (range, 33-63 years). Patient-reported outcome measures were collected before and after surgery using a Visual Analog Scale, SF-36 quality of life survey, McGill Pain Questionnaire, and EQ-5D (EQ-5D and EQ-5D Health State) questionnaires. RESULTS: Fifteen patients (93.3%) transitioned from externalized to fully internalized systems. Eleven patients had data to be analyzed with a mean follow-up of 13.2 months. Post-surgery, the Visual Analog Scale score dropped below 4 for 5 of the patients, with 1 patient free of pain. Highly significant improvement on the EQ-5D was observed (mean, +20.3%; range, +0%-+83%; P = .008). Moreover, statistically significant improvements were observed for the physical functioning and bodily pain domains of the SF-36 quality-of-life survey: mean, +64.7% (range, -8.9%-+276%; P = .015) and mean +39.0% (range, -33.8%-+159%; P = .050), respectively. CONCLUSION: Affective ACC DBS can relieve chronic neuropathic pain refractory to pharmacotherapy and restore quality of life.

Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

BACKGROUND: Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. RESULTS: We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. CONCLUSIONS: The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.

Deep brain stimulation of the anterior cingulate cortex: targeting the affective component of chronic pain.

Deep brain stimulation (DBS) has shown promise for relieving nociceptive and neuropathic symptoms of refractory chronic pain. We assessed the efficacy of a new target for the affective component of pain, the anterior cingulate cortex (ACC). A 49-year-old man with neuropathic pain underwent bilateral ACC DBS. Patient-reported outcome measures were collected before and 2 years after surgery using a Visual Analogue Scale, Short-Form 36 quality of life survey, McGill pain questionnaire, EuroQol-5D questionnaires (EQ-5D; Health State) and neuropsychological assessments. The patient improved with DBS. Two years after surgery, the Visual Analogue Scale decreased from 6.7 to 3.0, McGill pain questionnaire improved by 42% and EQ-5D Health State increased by 150%. Stimulating the ACC at 130 Hz, 330 µs and 3 V facilitated neuropathic pain relief. The DBS remained efficacious during the 2-year follow-up period. Affective ACC DBS can relieve chronic neuropathic pain refractory to pharmacotherapy and restore quality of life.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia--measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal--exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

The functional human neuroanatomy of food pleasure cycles.

Food ensures our survival and is a potential source of pleasure and general well-being. In order to survive, the human brain is required to optimize the resource allocation such that rewards are pursued when relevant. This means that food intake follows a similar cyclical time course to other rewards with phases related to expectation, consummation and satiety. Here we develop a multilevel model for the full cycle of eating behavior based on the evidence for the brain networks and mechanisms initiating, sustaining and terminating the various phases of eating. We concentrate on how the underlying reward mechanisms of wanting, liking and learning lead to how human food intake is governed by both hedonic and homeostatic principles. We describe five of the main processing principles controlling food intake: hunger and attentional signal processing; motivation-independent discriminative processing; reward representations; learning-dependent multimodal sensory representations and hedonic experience. Overall, the evidence shows that while human food intake is complex, we are making progress in understanding the underlying mechanisms and that the brain networks supporting the food pleasure cycle are remarkably similar to those underlying the processing of other rewards.