Structural Interactions within the Default Mode Network Identified by Bayesian Network Analysis in Alzheimer’s Disease

Alzheimer’s disease (AD) is a well-known neurodegenerative disease that is associated with dramatic morphological abnormalities. The default mode network (DMN) is one of the most frequently studied resting-state networks. However, less is known about specific structural dependency or interactions among brain regions within the DMN in AD. In this study, we performed a Bayesian network (BN) analysis based on regional grey matter volumes to identify differences in structural interactions among core DMN regions in structural MRI data from 80 AD patients and 101 normal controls (NC). Compared to NC, the structural interactions between the medial prefrontal cortex (mPFC) and other brain regions, including the left inferior parietal cortex (IPC), the left inferior temporal cortex (ITC) and the right hippocampus (HP), were significantly reduced in the AD group. In addition, the AD group showed prominent increases in structural interactions from the left ITC to the left HP, the left HP to the right ITC, the right HP to the right ITC, and the right IPC to the posterior cingulate cortex (PCC). The BN models significantly distinguished AD patients from NC with 87.12% specificity and 81.25% sensitivity. We then used the derived BN models to examine the replicability and stability of AD-associated BN models in an independent dataset and the results indicated discriminability with 83.64% specificity and 80.49% sensitivity. The results revealed that the BN analysis was effective for characterising regional structure interactions and the AD-related BN models could be considered as valid and predictive structural brain biomarker models for AD. Therefore, our study can assist in further understanding the pathological mechanism of AD, based on the view of the structural network, and may provide new insights into classification and clinical application in the study of AD in the future.     

Positive Facial Affect – An fMRI Study on the Involvement of Insula and Amygdala

Imitation of facial expressions engages the putative human mirror neuron system as well as the insula and the amygdala as part of the limbic system. The specific function of the latter two regions during emotional actions is still under debate. The current study investigated brain responses during imitation of positive in comparison to non-emotional facial expressions. Differences in brain activation of the amygdala and insula were additionally examined during observation and execution of facial expressions. Participants imitated, executed and observed happy and non-emotional facial expressions, as well as neutral faces. During imitation, higher right hemispheric activation emerged in the happy compared to the non-emotional condition in the right anterior insula and the right amygdala, in addition to the pre-supplementary motor area, middle temporal gyrus and the inferior frontal gyrus. Region-of-interest analyses revealed that the right insula was more strongly recruited by (i) imitation and execution than by observation of facial expressions, that (ii) the insula was significantly stronger activated by happy than by non-emotional facial expressions during observation and imitation and that (iii) the activation differences in the right amygdala between happy and non-emotional facial expressions were increased during imitation and execution, in comparison to sole observation. We suggest that the insula and the amygdala contribute specifically to the happy emotional connotation of the facial expressions depending on the task. The pattern of the insula activity might reflect increased bodily awareness during active execution compared to passive observation and during visual processing of the happy compared to non-emotional facial expressions. The activation specific for the happy facial expression of the amygdala during motor tasks, but not in the observation condition, might reflect increased autonomic activity or feedback from facial muscles to the amygdala.     

Default Mode Network in the Effects of Δ9-Tetrahydrocannabinol (THC) on Human Executive Function

Evidence is increasing for involvement of the endocannabinoid system in cognitive functions including attention and executive function, as well as in psychiatric disorders characterized by cognitive deficits, such as schizophrenia. Executive function appears to be associated with both modulation of active networks and inhibition of activity in the default mode network. In the present study, we examined the role of the endocannabinoid system in executive function, focusing on both the associated brain network and the default mode network. A pharmacological functional magnetic resonance imaging (fMRI) study was conducted with a placebo-controlled, cross-over design, investigating effects of the endocannabinoid agonist Δ9-tetrahydrocannabinol (THC) on executive function in 20 healthy volunteers, using a continuous performance task with identical pairs. Task performance was impaired after THC administration, reflected in both an increase in false alarms and a reduction in detected targets. This was associated with reduced deactivation in a set of brain regions linked to the default mode network, including posterior cingulate cortex and angular gyrus. Less deactivation was significantly correlated with lower performance after THC. Regions that were activated by the continuous performance task, notably bilateral prefrontal and parietal cortex, did not show effects of THC. These findings suggest an important role for the endocannabinoid system in both default mode modulation and executive function. This may be relevant for psychiatric disorders associated with executive function deficits, such as schizophrenia and ADHD.     

Morphologic and Functional Connectivity Alterations of Corticostriatal and Default Mode Network in Treatment-Na?ve Patients with Obsessive-Compulsive Disorder

Background

Previous studies have demonstrated that structural deficits and functional connectivity imbalances might underlie the pathophysiology of obsessive-compulsive disorder (OCD). The purpose of the present study was to investigate gray matter deficits and abnormal resting-state networks in patients with OCD and further investigate the association between the anatomic and functional alterations and clinical symptoms.

Methods

Participants were 33 treatment-naïve OCD patients and 33 matched healthy controls. Voxel-based morphometry was used to investigate the regions with gray matter abnormalities and resting-state functional connectivity analysis was further conducted between each gray matter abnormal region and the remaining voxels in the brain.

Results

Compared with healthy controls, patients with OCD showed significantly increased gray matter volume in the left caudate, left thalamus, and posterior cingulate cortex, as well as decreased gray matter volume in the bilateral medial orbitofrontal cortex, left anterior cingulate cortex, and left inferior frontal gyrus. By using the above morphologic deficits areas as seed regions, functional connectivity analysis found abnormal functional integration in the cortical-striatum-thalamic-cortical (CSTC) circuits and default mode network. Subsequent correlation analyses revealed that morphologic deficits in the left thalamus and increased functional connectivity within the CSTC circuits positively correlated with the total Y-BOCS score.

Conclusion

This study provides evidence that morphologic and functional alterations are seen in CSTC circuits and default mode network in treatment-naïve OCD patients. The association between symptom severity and the CSTC circuits suggests that anatomic and functional alterations in CSTC circuits are especially important in the pathophysiology of OCD.     

A Mechanism for Ultra-Slow Oscillations in the Cortical Default Network

When the brain is in its noncognitive “idling” state, functional MRI measurements reveal the activation of default cortical networks whose activity is suppressed during cognitive processing. This default or background mode is characterized by ultra-slow BOLD oscillations (∼0.05 Hz), signaling extremely slow cycling in cortical metabolic demand across distinct cortical regions. Here we describe a model of the cortex which predicts that slow cycling of cortical activity can arise naturally as a result of nonlinear interactions between temporal (Hopf) and spatial (Turing) instabilities. The Hopf instability is triggered by delays in the inhibitory postsynaptic response, while the Turing instability is precipitated by increases in the strength of the gap-junction coupling between interneurons. We comment on possible implications for slow dendritic computation and information processing.     

Personality Functioning and the Cortical Midline Structures – An Exploratory fMRI Study

Objective

Recent neuroscience studies explored the neuronal mechanisms underlying our sense of self. Thereby the cortical midline structures and their anterior and posterior regions have been shown to be central. What remains unclear though is how both, self and cortical midline structures, are related to the identity of the self which is of central importance in especially personality disorders.

Methods

Conducting an exploratory study with a dimensional approach, we here compared subjects with high and low level of personality functioning and identity integration as measured in a standardized way in fMRI during both, emotion- and reward-related tasks.

Results

Low levels of personality functioning and identity integration were predicted by significantly decreased degrees of deactivation in the anterior and posterior cortical midline structures.

Conclusions

Though exploratory our results show for the first time direct relationship between cortical midline structures and personality functioning in terms of identity integration. This does not only contribute to our understanding of the neuronal mechanism underlying self and identity but carries also major implications for the treatment of patients with personality disorders.     

Gap Junctions and Epileptic Seizures – Two Sides of the Same Coin?

Electrical synapses (gap junctions) play a pivotal role in the synchronization of neuronal ensembles which also makes them likely agonists of pathological brain activity. Although large body of experimental data and theoretical considerations indicate that coupling neurons by electrical synapses promotes synchronous activity (and thus is potentially epileptogenic), some recent evidence questions the hypothesis of gap junctions being among purely epileptogenic factors. In particular, an expression of inter-neuronal gap junctions is often found to be higher after the experimentally induced seizures than before. Here we used a computational modeling approach to address the role of neuronal gap junctions in shaping the stability of a network to perturbations that are often associated with the onset of epileptic seizures. We show that under some circumstances, the addition of gap junctions can increase the dynamical stability of a network and thus suppress the collective electrical activity associated with seizures. This implies that the experimentally observed post-seizure additions of gap junctions could serve to prevent further escalations, suggesting furthermore that they are a consequence of an adaptive response of the neuronal network to the pathological activity. However, if the seizures are strong and persistent, our model predicts the existence of a critical tipping point after which additional gap junctions no longer suppress but strongly facilitate the escalation of epileptic seizures. Our results thus reveal a complex role of electrical coupling in relation to epileptiform events. Which dynamic scenario (seizure suppression or seizure escalation) is ultimately adopted by the network depends critically on the strength and duration of seizures, in turn emphasizing the importance of temporal and causal aspects when linking gap junctions with epilepsy.     

Daylight and absenteeism – Evidence from Norway

Based on administrative register data from Norway, we examine the impact of hours of daylight on sick-leave absences among workers. Our preferred estimates imply that an additional hour of daylight increases the daily entry rate to absenteeism by 0.5 percent and the corresponding recovery rate by 0.8 percent, ceteris paribus. The overall relationship between absenteeism and daylight hours is negative. Absenteeism is also sensitive to weather conditions. Heavy snowfall raises the incidence of absence during the winter, while warm weather reduces the probability of returning to work during the summer.     

Political Systems Affect Mobile and Sessile Species Diversity – A Legacy from the Post-WWII Period

Political ideologies, policies and economy affect land use which in turn may affect biodiversity patterns and future conservation targets. However, few studies have investigated biodiversity in landscapes with similar physical properties but governed by different political systems. Here we investigate land use and biodiversity patterns, and number and composition of birds and plants, in the borderland of Austria, Slovenia and Hungary. It is a physically uniform landscape but managed differently during the last 70 years as a consequence of the political “map” of Europe after World War I and II. We used a historical map from 1910 and satellite data to delineate land use within three 10-kilometre transects starting from the point where the three countries meet. There was a clear difference between countries detectable in current biodiversity patterns, which relates to land use history. Mobile species richness was associated with current land use whereas diversity of sessile species was more associated with past land use. Heterogeneous landscapes were positively and forest cover was negatively correlated to bird species richness. Our results provide insights into why landscape history is important to understand present and future biodiversity patterns, which is crucial for designing policies and conservation strategies across the world.     

Uncovering the spatio-temporal dynamics of value-based decision-making in the human brain: a combined fMRI–EEG study

While there is a growing body of functional magnetic resonance imaging (fMRI) evidence implicating a corpus of brain regions in value-based decision-making in humans, the limited temporal resolution of fMRI cannot address the relative temporal precedence of different brain regions in decision-making. To address this question, we adopted a computational model-based approach to electroencephalography (EEG) data acquired during a simple binary choice task. fMRI data were also acquired from the same participants for source localization. Post-decision value signals emerged 200 ms post-stimulus in a predominantly posterior source in the vicinity of the intraparietal sulcus and posterior temporal lobe cortex, alongside a weaker anterior locus. The signal then shifted to a predominantly anterior locus 850 ms following the trial onset, localized to the ventromedial prefrontal cortex and lateral prefrontal cortex. Comparison signals between unchosen and chosen options emerged late in the trial at 1050 ms in dorsomedial prefrontal cortex, suggesting that such comparison signals may not be directly associated with the decision itself but rather may play a role in post-decision action selection. Taken together, these results provide us new insights into the temporal dynamics of decision-making in the brain, suggesting that for a simple binary choice task, decisions may be encoded predominantly in posterior areas such as intraparietal sulcus, before shifting anteriorly.     

Altered Baseline Brain Activity with 72 h of Simulated Microgravity – Initial Evidence from Resting-State fMRI

To provide the basis and reference to further insights into the neural activity of the human brain in a microgravity environment, we discuss the amplitude changes of low-frequency brain activity fluctuations using a simulated microgravity model. Twelve male participants between 24 and 31 years old received resting-state fMRI scans in both a normal condition and after 72 hours in a −6° head down tilt (HDT). A paired sample t-test was used to test the amplitude differences of low-frequency brain activity fluctuations between these two conditions. With 72 hours in a −6° HDT, the participants showed a decreased amplitude of low-frequency fluctuations in the left thalamus compared with the normal condition (a combined threshold of P<0.005 and a minimum cluster size of 351 mm³ (13 voxels), which corresponded with the corrected threshold of P<0.05 determined by AlphaSim). Our findings indicate that a gravity change-induced redistribution of body fluid may disrupt the function of the left thalamus in the resting state, which may contribute to reduced motor control abilities and multiple executive functions in astronauts in a microgravity environment.     

Assessing the Sensitivity of Seabed Species and Biotopes – The Marine Life Information Network (MarLIN)

Science-based approaches to support the conservation of marine biodiversity have been developed in recent years. They include measures of ‘rarity’, ‘diversity’, ‘importance’, biological indicators of water ‘quality’ and measures of ‘sensitivity’. Identifying the sensitivity of species and biotopes, the main topic of this contribution, relies on accessing and interpreting available scientific data in a structured way and then making use of information technology to disseminate suitably presented information to decision makers. The Marine Life Information Network (MarLIN) has achieved that research for a range of environmentally critical species and biotopes over the past four years and has published the reviews on the MarLIN Web site (www.marlin.ac.uk). Now, by linking the sensitivity database and databases of survey information, sensitivity mapping approaches using GIS are being developed. The methods used to assess sensitivity are described and the approach is advocated for wider application in Europe.     

Early Prefrontal Brain Responses to the Hedonic Quality of Emotional Words – A Simultaneous EEG and MEG Study

The hedonic meaning of words affects word recognition, as shown by behavioral, functional imaging, and event-related potential (ERP) studies. However, the spatiotemporal dynamics and cognitive functions behind are elusive, partly due to methodological limitations of previous studies. Here, we account for these difficulties by computing combined electro-magnetoencephalographic (EEG/MEG) source localization techniques. Participants covertly read emotionally high-arousing positive and negative nouns, while EEG and MEG were recorded simultaneously. Combined EEG/MEG current-density reconstructions for the P1 (80–120 ms), P2 (150–190 ms) and EPN component (200–300 ms) were computed using realistic individual head models, with a cortical constraint. Relative to negative words, the P1 to positive words predominantly involved language-related structures (left middle temporal and inferior frontal regions), and posterior structures related to directed attention (occipital and parietal regions). Effects shifted to the right hemisphere in the P2 component. By contrast, negative words received more activation in the P1 time-range only, recruiting prefrontal regions, including the anterior cingulate cortex (ACC). Effects in the EPN were not statistically significant. These findings show that different neuronal networks are active when positive versus negative words are processed. We account for these effects in terms of an “emotional tagging” of word forms during language acquisition. These tags then give rise to different processing strategies, including enhanced lexical processing of positive words and a very fast language-independent alert response to negative words. The valence-specific recruitment of different networks might underlie fast adaptive responses to both approach- and withdrawal-related stimuli, be they acquired or biological.     

Reality?=?Relevance? Insights from Spontaneous Modulations of the Brain's Default Network when Telling Apart Reality from Fiction

Background

Although human beings regularly experience fictional worlds through activities such as reading novels and watching movies, little is known about what mechanisms underlie our implicit knowledge of the distinction between reality and fiction. The first neuroimaging study to address this issue revealed that the mere exposure to contexts involving real entities compared to fictional characters led to engagement of regions in the anterior medial prefrontal and posterior cingulate cortices (amPFC, PCC). As these core regions of the brain''s default network are involved during self-referential processing and autobiographical memory retrieval, it was hypothesized that real entities may be conceptually coded as being more personally relevant to us than fictional characters.

Methodology/Principal Findings

In the present functional magnetic resonance imaging (fMRI) study, we directly test the hypothesis that entity-associated personal relevance is the critical factor underlying the differential engagement of these brain regions by comparing the brain''s response when processing contexts involving family or friends (high relevance), famous people (medium relevance), or fictional characters (low relevance). In line with predictions, a gradient pattern of activation was observed such that higher entity-associated personal relevance was associated with stronger activation in the amPFC and the PCC.

Conclusions/Significance

The results of the study have several important implications. Firstly, they provide informed grounds for characterizing the dynamics of reality-fiction distinction. Secondly, they provide further insights into the functions of the amPFC and the PCC. Thirdly, in view of the current debate related to the functional relevance and specificity of brain''s default network, they reveal a novel approach by which the functions of this network can be further explored.     

Indication of dynamic neurovascular coupling from inconsistency between EEG and fMRI indices across sleep–wake states

Sleep and Biological Rhythms - Neurovascular coupling (NVC), the transient regional hyperemia following the evoked neuronal responses, is the basis of blood oxygenation level-dependent techniques...     

The relationships between EEG θ and β oscillations and the level of creativity

The interrelations between the level of creativity and both the baseline power and event-related desynchronization/synchronization (ED/ES) of θ and β rhythms during a figural creative task (Torrance’s “Incomplete Figures” test) were studied under the conditions of different motivations. A higher motivation was caused by instruction “to create most unique images” as opposed to the instruction “to create images.” The subjects, right-handed students (14 males and 14 females), were divided into two groups with high and low originality scores (OSs). The baseline power and the ED/ES of the θ₂ and β rhythms of the subjects were found to depend on the level of creativity and person’s sex only in response to the instruction “to create images.” Male subjects with higher OSs differed from those with lower OSs in a stronger ED of the θ₂ rhythm in temporal-parietal-occipital brain regions, whereas these differences were absent in female subjects. Task performance was accompanied by ED of β₁ rhythm in men with higher OSs, whereas in women with higher OSs, ES was recorded in the same band. Only in women with high OSs did analysis of β_{1, 2} reference power show a higher β₁ power in the caudal hemispheric regions as compared to the frontal ones. High-OS subjects of different genders also differed in the lateral patterns of activity in the electrode loci Fp_1/2 (β₁) and Fp_1/2, F_7/8 (β₂). Our results suggest that a high level of creativity in men and women is related to sex-dependent specific patterns of frontal-occipital and lateral activities of θ and β rhythm oscillators in the brain cortex.     

Network genomics – A novel approach for the analysis of biological systems in the post-genomic era

Network Genomics studies genomics and proteomics foundations of cellular networks in biological systems. It complements systems biology in providing information on elements, their interaction and their functional interplay in cellular networks. The relationship between genomic and proteomic high-throughput technologies and computational methods are described, as well as several examples of specific network genomic application are presented.     

Animal Welfare Beyond the Cage … and Beyond the Evidence?

In “Laboratory Rodent Welfare: Thinking Outside the Cage,” Balcombe (2010/this issue) suggests that laboratory cage housing is damaging to rats and mice because it does not meet their evolved needs and may damage their psychological and physical health. The article also indicates that larger and more enriched spaces reduce aggression and mortality and improve the health and friendliness of rodents in the laboratory. Remarkably, many of the studies cited as supporting these assertions fail to provide data bearing on the issues involved or may even report findings opposite to those described by Balcombe, whereas many studies that are highly relevant to these issues are not cited or described. Moreover, although the “evolved needs” of rats and mice are presented as the basis for an analysis of rodent welfare, the important and well-documented changes in needs- or motivation-related behaviors of a rodent in the laboratory (due to human selection over hundreds of generations) is ignored. This pattern of disconnections between data and conclusions is so pervasive as to demolish the scientific value of the exposition.     

Acetylcholinesterases – the structural similarities and differences

Acetylcholinesterase (AChE) is a widely spread enzyme playing a very important role in nerve signal transmission. As AChE controls key processes, its inhibition leads to the very fast death of an organism, including humans. However, when this feature is to be used for killing of unwanted organisms (i.e. mosquitoes), one is faced with the question - how much do AChEs differ between species and what are the differences? Here, a theoretical point of view was utilized to identify the structural basis for such differences. The various primary and tertiary alignments show that AChEs are very evolutionary conserved enzymes and this fact could lead to difficulties, for example, in the search for inhibitors specific for a particular species.