Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis.

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

Comparing the effects of an acute bout of physical exercise with an acute bout of interactive mental and physical exercise on electrophysiology and executive functioning in younger and older adults.

BACKGROUND: Physical exercise has been shown to improve cognitive and neural functioning in older adults. AIMS AND METHODS: The current study compared the effects of an acute bout of physical exercise with a bout of interactive mental and physical exercise (i.e., "exergaming") on executive (Stroop) task performance and event-related potential (ERP) amplitudes in younger and older adults. RESULTS: Results revealed enhanced executive task performance in younger and older adults after exercise, with no differences in performance between exercise conditions. Stroop (RT) performance in older adults improved more than in younger adults from pre- to post-exercise. A significant increase in EEG amplitude from pre- to post-exercise was found at the Cz site from 320 to 700 ms post-stimulus for both younger and older adults, with older adults demonstrating a larger Stroop interference effect. While younger adults exhibited overall greater EEG amplitudes than older adults, they showed no differences between congruent and incongruent trials (i.e., minimal interference). Compared to peers with higher BMI (body mass index), older adults with lower BMI showed a greater reduction in Stroop interference effects from pre- to post-exercise. DISCUSSION AND CONCLUSIONS: The beneficial effects of an acute bout of physical exercise on cognitive and neural functioning in younger and older adults were confirmed, with no difference between standard exercise and exergaming. Findings suggest that BMI, sometimes used as a proxy for fitness level, may modulate benefits that older adults derive from an acute bout of exercise. Findings have implications for future research that seeks to investigate unique effects of exergaming when compared to standard physical exercise.

The interactive effects of physical fitness and acute aerobic exercise on electrophysiological coherence and cognitive performance in adolescents.

The current study examined the effects of physical fitness and aerobic exercise on cognitive functioning and coherence of the electroencephalogram in 30 adolescents between the ages of 13 and 14 years. Participants were first classified as fit or unfit and then performed a modified Eriksen flanker task after a bout of acute exercise and after a period of relaxation. Analysis of behavioural differences between the fit and unfit groups revealed an interaction between fitness levels and acute physical exercise. Specifically, fit participants had significantly faster reaction times in the exercise condition in comparison with the rest condition; unfit, but not fit, participants had higher error rates for NoGo relative to Go trials in the rest condition. Furthermore, unfit participants had higher levels of lower alpha, upper alpha, and beta coherence in the resting condition for NoGo trials, possibly indicating a greater allocation of cognitive resources to the task demands. The higher levels of alpha coherence are of particular interest in light of its reported role in inhibition and effortful attention. The results suggest that physical fitness and acute exercise may enhance cognition by increasing the efficacy of the attentional system.

Age-related task sensitivity of frontal EEG entropy during encoding predicts retrieval.

Age-related declines in memory may be due in part to changes in the complexity of neural activity in the aging brain. Electrophysiological entropy provides an accessible measure of the complexity of ongoing neural activity. In the current study, we calculated the permutation entropy of the electroencephalogram (EEG) during encoding of relevant (to be learned) and irrelevant (to be ignored) stimuli by younger adults, older adults, and older cognitively declined adults. EEG entropy was differentially sensitive to task requirements across groups, with younger and older controls exhibiting greater control of encoding-related activity than older declined participants. Task sensitivity of frontal EEG during encoding predicted later retrieval, in line with previous evidence that cognitive decline is associated with reduced ability to self-initiate encoding-related processes.

Topological Alteration Is Associated with Non-dependent Alcohol Use in Bipolar Disorder.

Introduction: Structural alterations in cortical thickness and the microstructural organization of white matter are independently associated with non-dependent alcohol consumption and bipolar disorder (BD). Identifying their interactive and network-level effects on brain topology may identify the impact of alcohol on reward and emotion circuitry, and its contribution to relapse in BD. Materials and Methods: Thirty-four BD-I (DSM-IV-TR) and 38 healthy controls (HC) underwent T1 and diffusion-weighted magnetic resonance imaging scanning, and the Alcohol Use Disorders Identification Test-Consumption to assess alcohol use. Connectomes comprising 34 cortical and 9 subcortical nodes bilaterally (Freesurfer v5.3) connected by fractional anisotropy-weighted edges derived from non-tensor based deterministic constrained spherical deconvolution tractography (ExploreDTI v4.8.6) underwent permutation-based topological analysis (NBS v1.2) and were examined for the effects of alcohol use and diagnosis-by-alcohol use accounting for age, sex, and diagnosis. Results: Alcohol was significantly related to a subnetwork, encompassing connections between fronto-limbic, basal ganglia, and temporal nodes (Frange = 5-8.4, p = 0.031) and it was not detected to have an effect on global brain integration or segregation. A portion of this network (18%), involving cortico-limbic and basal ganglia connections, was differentially impacted by alcohol in the BD relative to the control group (Frange = 5-8.8, p = 0.033), despite the groups' consuming similar amounts of alcohol (BD: mean ± standard deviation 4.95 ± 3.0; HC 3.62 ± 3.0, T = 1.88, p = 0.06). Discussion: Non-dependent alcohol use impacts brain architectural organization and connectivity within salience, reward, and affective circuitry. The relationship between alcohol use and topology of the network in BD suggests an interactive effect between specific biological vulnerability and alcohol use, which may explain the susceptibility to an increased risk of relapse in the disorder. Impact statement The association between non-dependent alcohol use and neural architecture in bipolar disorder (BD) is unknown, despite the poor clinical trajectory and increased likelihood of relapse associated with alcohol use in BD. We demonstrate that together alcohol and a diagnosis of BD is associated with a subnetwork involving nodes of the cortico-limbic and reward networks. This subnetwork, demonstrated in BD and absent in controls, differentially involves nodes that are specific to reward and emotion processes. This suggests a diagnosis-specific biological vulnerability for alcohol use and may be consistent with known mood lability and thus relapse associated with alcohol use in BD.

Normalization of impaired emotion inhibition in bipolar disorder mediated by cholinergic neurotransmission in the cingulate cortex.

The muscarinic-cholinergic system is involved in the pathophysiology of bipolar disorder (BD), and contributes to attention and the top-down and bottom-up cognitive and affective mechanisms of emotional processing, functionally altered in BD. Emotion processing can be assessed by the ability to inhibit a response when the content of the image is emotional. Impaired regulatory capacity of cholinergic neurotransmission conferred by reduced M2-autoreceptor availability is hypothesized to play a role in elevated salience of negative emotional distractors in euthymic BD relative to individuals with no history of mood instability. Thirty-three euthymic BD type-I (DSM-V-TR) and 50 psychiatrically-healthy controls underwent functional magnetic resonance imaging (fMRI) and an emotion-inhibition paradigm before and after intravenous cholinergic challenge using the acetylcholinesterase inhibitor, physostigmine (1 mg), or placebo. Mood, accuracy, and reaction time on either recognizing or inhibiting a response associated with an image involving emotion and regional functional activation were examined for effects of cholinergic challenge physostigmine relative to placebo, prioritizing any interaction with the diagnostic group. Analyses revealed that (1) at baseline, impaired behavioral performance was associated with lower activation in the anterior cingulate cortex in BD relative to controls during emotion processing; (2) physostigmine (vs. placebo) affected behavioral performance during the inhibition of negative emotions, without altering mood, and increased activation in the posterior cingulate cortex in BD (vs. controls); (3) In BD, lower accuracy observed during emotion inhibition of negative emotions was remediated by physostigmine and was associated with cingulate cortex overactivation. Our findings implicate abnormal regulation of cholinergic neurotransmission in the cingulate cortices in BD, which may mediate exaggerated emotional salience processing, a core feature of BD.

Electroencephalographic coherence, aging, and memory: distinct responses to background context and stimulus repetition in younger, older, and older declined groups.

The current study examines the EEG coherence of young, old, and old declined adults performing a visual paired-associates task. In order to examine the effects of encoding context and stimulus repetition, target pairs were presented on either detailed or white backgrounds and were repeatedly presented during both early and late phases of encoding. Younger adults were found to have lower levels of frontal-temporal and temporal-parietal coherence, but higher levels of frontal-parietal coherence, particularly for the gamma frequency band. A number of differential coherence responses to background context and early- versus late-encoding phases were also observed across the groups, particularly for lower alpha and upper alpha frequencies. Coherence-performance maps were generated to further explore topographical differences in the relationship between coherence and performance across groups. Results revealed a more diffuse pattern of negative coherence-performance relations in older declined adults. Results are discussed in light of the literature on age-related cognitive decline.

White matter microstructure and structural networks in treatment-resistant schizophrenia patients after commencing clozapine treatment: A longitudinal diffusion imaging study.

This study investigates changes on white matter microstructure and neural networks after 6 months of switching to clozapine in schizophrenia patients compared to controls, and whether any changes are related to clinical variables. T1 and diffusion-weighted MRI images were acquired at baseline before commencing clozapine and after 6 months of treatment for 22 patients with treatment-resistant schizophrenia and 23 controls. The Tract-based spatial statistics approach was used to compare changes over time between groups in fractional anisotropy (FA). Changes in structural network organisation weighted by FA and number of streamlines were assessed using graph theory. Patients displayed a significant reduction of FA over time (p<0.05) compared to controls in the genu and body of the corpus callosum and bilaterally in the anterior and superior corona radiata. There was no correlation between FA change in patients and changes in clinical variables or serum level of clozapine. There was no changes in structural network organisation between groups (F(7,280)=2.80;p = 0.187). This longitudinal study demonstrated progressive focal FA abnormalities in key anterior tracts, but preserved brain structural network organisation in patients. The FA reduction was independent of any clinical measures and may reflect progression of the underlying pathophysiology of this malignant form of schizophrenia illness.

Resting-State Network Patterns Underlying Cognitive Function in Bipolar Disorder: A Graph Theoretical Analysis.

Background: Synchronous and antisynchronous activity between neural elements at rest reflects the physiological processes underlying complex cognitive ability. Regional and pairwise connectivity investigations suggest that perturbations in these activity patterns may relate to widespread cognitive impairments seen in bipolar disorder (BD). Here we take a network-based perspective to more meaningfully capture interactions among distributed brain regions compared to focal measurements and examine network-cognition relationships across a range of commonly affected cognitive domains in BD in relation to healthy controls. Methods: Resting-state networks were constructed as matrices of correlation coefficients between regionally averaged resting-state time series from 86 cortical/subcortical brain regions (FreeSurferv5.3.0). Cognitive performance measured using the Wechsler Adult Intelligence Scale, Cambridge Automated Neuropsychological Test Battery (CANTAB), and Reading the Mind in the Eyes tests was examined in relation to whole-brain connectivity measures and patterns of connectivity using a permutation-based statistical approach. Results: Faster response times in controls (n = 49) related to synchronous activity between frontal, parietal, cingulate, temporal, and occipital regions, while a similar response times in BD (n = 35) related to antisynchronous activity between regions of this subnetwork. Across all subjects, antisynchronous activity between the frontal, parietal, temporal, occipital, cingulate, insula, and amygdala regions related to improved memory performance. No resting-state subnetworks related to intelligence, executive function, short-term memory, or social cognition performance in the overall sample or in a manner that would explain deficits in these facets in BD. Conclusions: Our results demonstrate alterations in the intrinsic connectivity patterns underlying response timing in BD that are not specific to performance or errors on the same tasks. Across all individuals, no strong effects of resting-state global topology on cognition are found, while distinct functional networks supporting episodic and spatial memory highlight intrinsic inhibitory influences present in the resting state that facilitate memory processing. Impact Statement Regional and pairwise-connectivity investigations suggest altered interactions between brain areas may contribute to impairments in cognition that are observed in bipolar disorder. However, the distributed nature of these interactions across the brain remains poorly understood. Using recent advances in network neuroscience, we examine functional connectivity patterns associated with multiple cognitive domains in individuals with and without bipolar disorder. We discover distinct patterns of connectivity underlying response-timing performance uniquely in bipolar disorder and, independent of diagnosis, inhibitory interactions that relate to memory performance.

Frontolimbic, Frontoparietal, and Default Mode Involvement in Functional Dysconnectivity in Psychotic Bipolar Disorder.

BACKGROUND: Functional abnormalities, mostly involving functionally specialized subsystems, have been associated with disorders of emotion regulation such as bipolar disorder (BD). Understanding how independent functional subsystems integrate globally and how they relate with anatomical cortical and subcortical networks is key to understanding how the human brain's architecture constrains functional interactions and underpins abnormalities of mood and emotion, particularly in BD. METHODS: Resting-state functional magnetic resonance time series were averaged to obtain individual functional connectivity matrices (using AFNI software); individual structural connectivity matrices were derived using deterministic non-tensor-based tractography (using ExploreDTI, version 4.8.6), weighted by streamline count and fractional anisotropy. Structural and functional nodes were defined using a subject-specific cortico-subcortical mapping (using Desikan-Killiany Atlas, FreeSurfer, version 5.3). Whole-brain connectivity alongside a permutation-based statistical approach and structure-function coupling were employed to investigate topological variance in individuals with predominantly euthymic BD relative to psychiatrically healthy control subjects. RESULTS: Patients with BD (n = 41) exhibited decreased (synchronous) connectivity in a subnetwork encompassing frontolimbic and posterior-occipital functional connections (T > 3, p = .048), alongside increased (antisynchronous) connectivity within a frontotemporal subnetwork (T > 3, p = .014); all relative to control subjects (n = 56). Preserved whole-brain functional connectivity and comparable structure-function coupling among whole-brain and edge-class connections were observed in patients with BD relative to control subjects. CONCLUSIONS: This study presents a functional map of BD dysconnectivity that differentially involves communication within nodes belonging to functionally specialized subsystems-default mode, frontoparietal, and frontolimbic systems; these changes do not extend to be detected globally and may be necessary to maintain a remitted clinical state of BD. Preserved structure-function coupling in BD despite evidence of regional anatomical and functional deficits suggests a dynamic interplay between structural and functional subnetworks.

Neuroanatomical Dysconnectivity Underlying Cognitive Deficits in Bipolar Disorder.

BACKGROUND: Graph theory applied to brain networks is an emerging approach to understanding the brain's topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear. METHODS: We examined the role of anatomical network connectivity derived from T1- and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38). Fractional anisotropy- and number of streamlines-weighted anatomical brain networks were generated by mapping constrained spherical deconvolution-reconstructed white matter among 86 cortical/subcortical bilateral brain regions delineated in the individual's own coordinate space. Intelligence and executive function were investigated as distributed functions using measures of global, rich-club, and interhemispheric connectivity, while memory and social cognition were examined in relation to subnetwork connectivity. RESULTS: Lower executive functioning related to higher global clustering coefficient in participants with BD, and lower IQ performance may present with a differential relationship between global and interhemispheric efficiency in individuals with BD relative to control individuals. Spatial recognition memory accuracy and response times were similar between diagnostic groups and associated with basal ganglia and thalamus interconnectivity and connectivity within extended anatomical subnetworks in all participants. No anatomical subnetworks related to episodic memory, short-term memory, or social cognition generally or differently in BD. CONCLUSIONS: Results demonstrate selective influence of subnetwork patterns of connectivity in underlying cognitive performance generally and abnormal global topology underlying discrete cognitive impairments in BD.

Bipolar Disorder and Gender Are Associated with Frontolimbic and Basal Ganglia Dysconnectivity: A Study of Topological Variance Using Network Analysis.

Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach. Connectivity matrices were constructed using 34 cortical and 9 subcortical bilateral nodes (Desikan-Killiany), and edges that were weighted by fractional anisotropy and streamline count derived from deterministic tractography using constrained spherical deconvolution. Whole-brain and rich-club connectivity alongside a permutation-based statistical approach was used to investigate topological variance in predominantly euthymic BD relative to healthy volunteers. BP patients (n = 40) demonstrated impairments across whole-brain topological arrangements (density, degree, and efficiency), and a dysconnected subnetwork involving limbic and basal ganglia relative to controls (n = 45). Increased rich-club connectivity was most evident in females with BD, with frontolimbic and parieto-occipital nodes not members of BD rich-club. Increased centrality in females relative to males was driven by basal ganglia and fronto-temporo-limbic nodes. Our subject-specific cortico-subcortical nontensor-based connectome map presents a neuroanatomical model of BD dysconnectivity that differentially involves communication within and between emotion-regulatory and reward-related subsystems. Moreover, the female brain positions more dependence on nodes belonging to these two differently specialized subsystems for communication relative to males, which may confer increased susceptibility to processes dependent on integration of emotion and reward-related information.

A comparative study of segmentation techniques for the quantification of brain subcortical volume.

Manual tracing of magnetic resonance imaging (MRI) represents the gold standard for segmentation in clinical neuropsychiatric research studies, however automated approaches are increasingly used due to its time limitations. The accuracy of segmentation techniques for subcortical structures has not been systematically investigated in large samples. We compared the accuracy of fully automated [(i) model-based: FSL-FIRST; (ii) patch-based: volBrain], semi-automated (FreeSurfer) and stereological (Measure®) segmentation techniques with manual tracing (ITK-SNAP) for delineating volumes of the caudate (easy-to-segment) and the hippocampus (difficult-to-segment). High resolution 1.5 T T1-weighted MR images were obtained from 177 patients with major psychiatric disorders and 104 healthy participants. The relative consistency (partial correlation), absolute agreement (intraclass correlation coefficient, ICC) and potential technique bias (Bland-Altman plots) of each technique was compared with manual segmentation. Each technique yielded high correlations (0.77-0.87, p < 0.0001) and moderate ICC's (0.28-0.49) relative to manual segmentation for the caudate. For the hippocampus, stereology yielded good consistency (0.52-0.55, p < 0.0001) and ICC (0.47-0.49), whereas automated and semi-automated techniques yielded poor ICC (0.07-0.10) and moderate consistency (0.35-0.62, p < 0.0001). Bias was least using stereology for segmentation of the hippocampus and using FreeSurfer for segmentation of the caudate. In a typical neuropsychiatric MRI dataset, automated segmentation techniques provide good accuracy for an easy-to-segment structure such as the caudate, whereas for the hippocampus, a reasonable correlation with volume but poor absolute agreement was demonstrated. This indicates manual or stereological volume estimation should be considered for studies that require high levels of precision such as those with small sample size.

Adaptive Dictionary Reconstruction for Compressed Sensing of ECG Signals.

This paper proposes a novel adaptive dictionary (AD) reconstruction scheme to improve the performance of compressed sensing (CS) with electrocardiogram signals (ECG). The method is based on the use of multiple dictionaries, created using dictionary learning (DL) techniques for CS signal reconstruction. The modified reconstruction framework is a two-stage process that leverages information about the signal from an initial signal reconstruction stage. By identifying whether a QRS complex is present and if so, determining a location estimate of the QRS, the most appropriate dictionary is selected and a second stage more refined signal reconstruction can be obtained. The performance of the proposed algorithm is compared with state-of-the-art CS implementations in the literature, as well as the set partitioning in hierarchical trees (SPIHT) wavelet-based lossy compression algorithm. The results indicate that the proposed reconstruction scheme outperforms all existing CS implementations in terms of signal fidelity at each compression ratio tested. The performance of the proposed approach also compares favorably with SPIHT in terms of signal reconstruction quality. Furthermore, an analysis of the overall power consumption of the proposed ECG compression framework as would be used in a body area network (BAN) demonstrates positive results for the proposed CS approach when compared with existing CS techniques and SPIHT.

Energy-efficient Compressed Sensing for ambulatory ECG monitoring.

Advances in Compressed Sensing (CS) are enabling promising low-energy implementation solutions for wireless Body Area Networks (BAN). While studies demonstrate the potential of CS in terms of overall energy efficiency compared to state-of-the-art lossy compression techniques, the performance of CS remains limited. The aim of this study is to improve the performance of CS-based compression for electrocardiogram (ECG) signals. This paper proposes a CS architecture that combines a novel redundancy removal scheme with quantization and Huffman entropy coding to effectively extend the Compression Ratio (CR). Reconstruction is performed using overcomplete sparse dictionaries created with Dictionary Learning (DL) techniques to exploit the highly structured nature of ECG signals. Performance of the proposed CS implementation is evaluated by analyzing energy-based distortion metrics and diagnostic metrics including QRS beat-detection accuracy across a range of CRs. The proposed CS approach offers superior performance to the most recent state-of-the-art CS implementations in terms of signal reconstruction quality across all CRs tested. Furthermore, QRS detection accuracy of the technique is compared with the well-known lossy Set Partitioning in Hierarchical Trees (SPIHT) compression technique. The proposed CS approach outperforms SPIHT in terms of achievable CR, using the area under the receiver operator characteristic (ROC) curve (AUC). For an application where a minimum AUC performance threshold of 0.9 is required, the proposed technique extends the CR from 64.6 to 90.45 compared with SPIHT, ensuring a 40% saving on wireless transmission costs. Therefore, the results highlight the potential of the proposed technique for ECG computer-aided diagnostic systems.

Neural and fuzzy computation techniques for playout delay adaptation in VoIP networks.

Playout delay adaptation algorithms are often used in real time voice communication over packet-switched networks to counteract the effects of network jitter at the receiver. Whilst the conventional algorithms developed for silence-suppressed speech transmission focused on preserving the relative temporal structure of speech frames/packets within a talkspurt (intertalkspurt adaptation), more recently developed algorithms strive to achieve better quality by allowing for playout delay adaptation within a talkspurt (intratalkspurt adaptation). The adaptation algorithms, both intertalkspurt and intratalkspurt based, rely on short term estimations of the characteristics of network delay that would be experienced by up-coming voice packets. The use of novel neural networks and fuzzy systems as estimators of network delay characteristics are presented in this paper. Their performance is analyzed in comparison with a number of traditional techniques for both inter and intratalkspurt adaptation paradigms. The design of a novel fuzzy trend analyzer system (FTAS) for network delay trend analysis and its usage in intratalkspurt playout delay adaptation are presented in greater detail. The performance of the proposed mechanism is analyzed based on measured Internet delays. Index Terms-Fuzzy delay trend analysis, intertalkspurt, intratalkspurt, multilayer perceptrons (MLPs), network delay estimation, playout buffering, playout delay adaptation, time delay neural networks (TDNNs), voice over Internet protocol (VoIP).

Compressed sensing for bioelectric signals: a review.

This paper provides a comprehensive review of compressed sensing or compressive sampling (CS) in bioelectric signal compression applications. The aim is to provide a detailed analysis of the current trends in CS, focusing on the advantages and disadvantages in compressing different biosignals and its suitability for deployment in embedded hardware. Performance metrics such as percent root-mean-squared difference (PRD), signal-to-noise ratio (SNR), and power consumption are used to objectively quantify the capabilities of CS. Furthermore, CS is compared to state-of-the-art compression algorithms in compressing electrocardiogram (ECG) and electroencephalography (EEG) as examples of typical biosignals. The main technical challenges associated with CS are discussed along with the predicted future trends.

The effects of cardiorespiratory fitness and acute aerobic exercise on executive functioning and EEG entropy in adolescents.

The current study examined the effects of cardiorespiratory fitness, identified with a continuous graded cycle ergometry, and aerobic exercise on cognitive functioning and entropy of the electroencephalogram (EEG) in 30 adolescents between the ages of 13 and 14 years. Higher and lower fit participants performed an executive function task after a bout of acute exercise and after rest while watching a film. EEG entropy, using the sample entropy measure, was repeatedly measured during the 1500 ms post-stimulus interval to evaluate changes in entropy over time. Analysis of the behavioral data for lower and higher fit groups revealed an interaction between fitness levels and acute physical exercise. Notably, lower fit, but not higher fit, participants had higher error rates (ER) for No Go relative to Go trials in the rest condition, whereas in the acute exercise condition there were no differences in ER between groups; higher fit participants also had significantly faster reaction times in the exercise condition in comparison with the rest condition. Analysis of EEG data revealed that higher fit participants demonstrated lower entropy post-stimulus than lower fit participants in the left frontal hemisphere, possibly indicating increased efficiency of early stage stimulus processing and more efficient allocation of cognitive resources to the task demands. The results suggest that EEG entropy is sensitive to stimulus processing demands and varies as a function of physical fitness levels, but not acute exercise. Physical fitness, in turn, may enhance cognition in adolescence by facilitating higher functionality of the attentional system in the context of lower levels of frontal EEG entropy.

Volume and shape analysis of subcortical brain structures and ventricles in euthymic bipolar I disorder.

Previous structural magnetic resonance imaging (S-MRI) studies of bipolar disorder have reported variable morphological changes in subcortical brain structures and ventricles. This study aimed to establish trait-related subcortical volumetric and shape abnormalities in a large, homogeneous sample of prospectively confirmed euthymic bipolar I disorder (BD-I) patients (n=60), compared with healthy volunteers (n=60). Participants were individually matched for age and gender. Volume and shape metrics were derived from manually segmented S-MR images for the hippocampus, amygdala, caudate nucleus, and lateral ventricles. Group differences were analysed, controlling for age, gender and intracranial volume. BD-I patients displayed significantly smaller left hippocampal volumes and significantly larger left lateral ventricle volumes compared with controls. Shape analysis revealed an area of contraction in the anterior head and medial border of the left hippocampus, as well as expansion in the right hippocampal tail medially, in patients compared with controls. There were no significant associations between volume or shape variation and lithium status or duration of use. A reduction in the head of the left hippocampus in BD-I patients is interesting, given this region's link to verbal memory. Shape analysis of lateral ventricular changes in patients indicated that these are not regionally specific.

Compressive sampling for time critical microwave imaging applications.

Across all biomedical imaging applications, there is a growing emphasis placed on reducing data acquisition and imaging times. This research explores the use of a technique, known as compressive sampling or compressed sensing (CS), as an efficient technique to minimise the data acquisition time for time critical microwave imaging (MWI) applications. Where a signal exhibits sparsity in the time domain, the proposed CS implementation allows for sub-sampling acquisition in the frequency domain and consequently shorter imaging times, albeit at the expense of a slight degradation in reconstruction quality of the signals as the compression increases. This Letter focuses on ultra wideband (UWB) radar MWI applications where reducing acquisition is of critical importance therefore a slight degradation in reconstruction quality may be acceptable. The analysis demonstrates the effectiveness and suitability of CS with UWB applications.