Increased resting state functional connectivity in the default mode network in recovered anorexia nervosa.

Functional brain imaging studies have shown abnormal neural activity in individuals recovered from anorexia nervosa (AN) during both cognitive and emotional task paradigms. It has been suggested that this abnormal activity which persists into recovery might underpin the neurobiology of the disorder and constitute a neural biomarker for AN. However, no study to date has assessed functional changes in neural networks in the absence of task-induced activity in those recovered from AN. Therefore, the aim of this study was to investigate whole brain resting state functional connectivity in nonmedicated women recovered from anorexia nervosa. Functional magnetic resonance imaging scans were obtained from 16 nonmedicated participants recovered from anorexia nervosa and 15 healthy control participants. Independent component analysis revealed functionally relevant resting state networks. Dual regression analysis revealed increased temporal correlation (coherence) in the default mode network (DMN) which is thought to be involved in self-referential processing. Specifically, compared to healthy control participants the recovered anorexia nervosa participants showed increased temporal coherence between the DMN and the precuneus and the dorsolateral prefrontal cortex/inferior frontal gyrus. The findings support the view that dysfunction in resting state functional connectivity in regions involved in self-referential processing and cognitive control might be a vulnerability marker for the development of anorexia nervosa.

Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks

Human minds often wander away from their immediate sensory environment. It remains unknown whether such mind wandering is unsystematic or whether it lawfully relates to an individual’s tendency to attend to salient stimuli such as pain and their associated brain structure/function. Studies of pain–cognition interactions typically examine explicit manipulation of attention rather than spontaneous mind wandering. Here we sought to better represent natural fluctuations in pain in daily life, so we assessed behavioral and neural aspects of spontaneous disengagement of attention from pain. We found that an individual’s tendency to attend to pain related to the disruptive effect of pain on his or her cognitive task performance. Next, we linked behavioral findings to neural networks with strikingly convergent evidence from functional magnetic resonance imaging during pain coupled with thought probes of mind wandering, dynamic resting state activity fluctuations, and diffusion MRI. We found that (i) pain-induced default mode network (DMN) deactivations were attenuated during mind wandering away from pain; (ii) functional connectivity fluctuations between the DMN and periaqueductal gray (PAG) dynamically tracked spontaneous attention away from pain; and (iii) across individuals, stronger PAG–DMN structural connectivity and more dynamic resting state PAG–DMN functional connectivity were associated with the tendency to mind wander away from pain. These data demonstrate that individual tendencies to mind wander away from pain, in the absence of explicit manipulation, are subserved by functional and structural connectivity within and between default mode and antinociceptive descending modulation networks.

Disorder-specific functional abnormalities during sustained attention in youth with Attention Deficit Hyperactivity Disorder (ADHD) and with Autism

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are often comorbid and share behavioural-cognitive abnormalities in sustained attention. A key question is whether this shared cognitive phenotype is based on common or different underlying pathophysiologies. To elucidate this question, we compared 20 boys with ADHD to 20 age and IQ matched ASD and 20 healthy boys using functional magnetic resonance imaging (fMRI) during a parametrically modulated vigilance task with a progressively increasing load of sustained attention. ADHD and ASD boys had significantly reduced activation relative to controls in bilateral striato–thalamic regions, left dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex. Both groups also displayed significantly increased precuneus activation relative to controls. Precuneus was negatively correlated with the DLPFC activation, and progressively more deactivated with increasing attention load in controls, but not patients, suggesting problems with deactivation of a task-related default mode network in both disorders. However, left DLPFC underactivation was significantly more pronounced in ADHD relative to ASD boys, which furthermore was associated with sustained performance measures that were only impaired in ADHD patients. ASD boys, on the other hand, had disorder-specific enhanced cerebellar activation relative to both ADHD and control boys, presumably reflecting compensation. The findings show that ADHD and ASD boys have both shared and disorder-specific abnormalities in brain function during sustained attention. Shared deficits were in fronto–striato–parietal activation and default mode suppression. Differences were a more severe DLPFC dysfunction in ADHD and a disorder-specific fronto–striato–cerebellar dysregulation in ASD.

Resting-state functional connectivity following a single dose treatment with CB1 neutral antagonist tetrahydrocannabivarin (THCv) in healthy volunteers

BACKGROUND: The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. METHOD: We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. RESULTS: Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. CONCLUSION: Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions.

Connectivity-based parcellation of the human frontal polar cortex

The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity.

The effects of acute fluoxetine administration on temporal discounting in youth with ADHD

Background Serotonin is under-researched in attention deficit hyperactivity disorder (ADHD), despite accumulating evidence for its involvement in impulsiveness and the disorder. Serotonin further modulates temporal discounting (TD), which is typically abnormal in ADHD relative to healthy subjects, underpinned by reduced fronto-striato-limbic activation. This study tested whether a single acute dose of the selective serotonin reuptake inhibitor (SSRI) fluoxetine up-regulates and normalizes reduced fronto-striato-limbic neurofunctional activation in ADHD during TD. Method Twelve boys with ADHD were scanned twice in a placebo-controlled randomized design under either fluoxetine (between 8 and 15 mg, titrated to weight) or placebo while performing an individually adjusted functional magnetic resonance imaging TD task. Twenty healthy controls were scanned once. Brain activation was compared in patients under either drug condition and compared to controls to test for normalization effects. Results Repeated-measures whole-brain analysis in patients revealed significant up-regulation with fluoxetine in a large cluster comprising right inferior frontal cortex, insula, premotor cortex and basal ganglia, which further correlated trend-wise with TD performance, which was impaired relative to controls under placebo, but normalized under fluoxetine. Fluoxetine further down-regulated default mode areas of posterior cingulate and precuneus. Comparisons between controls and patients under either drug condition revealed normalization with fluoxetine in right premotor-insular-parietal activation, which was reduced in patients under placebo. Conclusions The findings show that a serotonin agonist up-regulates activation in typical ADHD dysfunctional areas in right inferior frontal cortex, insula and striatum as well as down-regulating default mode network regions in the context of impulsivity and TD.

Executive control in bilinguals: a concise review on fMRI studies

The investigation of bilingualism and cognition has been enriched by recent developments in functional magnetic resonance imaging (fMRI). Extending how bilingual experience shapes cognition, this review examines recent fMRI studies adopting executive control tasks with minimal or no linguistic demands. Across a range of studies with divergent ages and language pairs spoken by bilinguals, brain regions supporting executive control significantly overlap with brain regions recruited for language control (Abutalebi & Green, this issue). Furthermore, limited but emerging studies on resting-state networks are addressed, which suggest more coherent spatially distributed functional connectivity in bilinguals. Given the dynamic nature of bilingual experience, it is essential to consider both task-related functional networks (externally-driven engagement), and resting-state networks, such as default mode network (internal control). Both types of networks are important elements of bilingual language control, which relies on domain-general executive control.

Epoch-specific functional networks involved in working memory

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

Cloud optical depth retrievals from the Aerosol Robotic Network (AERONET) cloud mode observations

Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale.

A Packet/Frame sync detector based on statistical mode with application to wireless-USB

Wireless Personal Area Networks (WPANs) are offering high data rates suitable for interconnecting high bandwidth personal consumer devices (Wireless HD streaming, Wireless-USB and Bluetooth EDR). ECMA-368 is the Physical (PHY) and Media Access Control (MAC) backbone of many of these wireless devices. WPAN devices tend to operate in an ad-hoc based network and therefore it is important to successfully latch onto the network and become part of one of the available piconets. This paper presents a new algorithm for detecting the Packet/Fame Sync (PFS) signal in ECMA-368 to identify piconets and aid symbol timing. The algorithm is based on correlating the received PFS symbols with the expected locally stored symbols over the 24 or 12 PFS symbols, but selecting the likely TFC based on the highest statistical mode from the 24 or 12 best correlation results. The results are very favorable showing an improvement margin in the order of 11.5dB in reference sensitivity tests between the required performance using this algorithm and the performance of comparable systems.

Givens rotation based fast backward elimination algorithm for RBF neural network pruning

A fast backward elimination algorithm is introduced based on a QR decomposition and Givens transformations to prune radial-basis-function networks. Nodes are sequentially removed using an increment of error variance criterion. The procedure is terminated by using a prediction risk criterion so as to obtain a model structure with good generalisation properties. The algorithm can be used to postprocess radial basis centres selected using a k-means routine and, in this mode, it provides a hybrid supervised centre selection approach.

A single director switching mode for monodomain liquid crystal elastomer

We report rotation of a single director in a nematic monodomain, acrylate based side-chain elastomer which was subjected to mechanical fields applied at angles in the range to the director, , present at the time of network formation. Time and spatially resolving wide angle X-ray scattering, together with polarised light microscopy measurements revealed a pronounced, almost discontinuous switching mode at a critical extension as the strain was applied at angles approaching to , whereas a more continuous rotation was seen when the strain was applied at more acute angles. This director reorientation was more or less uniform across the complete sample and was accompanied by a modest decrease in orientation parameter . At strains sufficient to induce switching there was some continuous distribution of director orientations with fluctuations of 10 although there was no evidence for any localised director inhomogenities such as domain formation. The observed deformation behaviour of these acrylate-based nematic monodomains was in accord with the predictions of a theory developed by Bladon et al., in that the complete set of data could be accounted for through a single parameter describing the chain anisotropy. The experimentally deduced chain anisotropy parameter was in broad agreement with that obtained from small-angle neutron scattering procedures, but was somewhat greater than that obtained by spontaneous shape changes at the nematic-isotropic transition.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.