Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy

Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

Age, Motion, Medical, and Psychiatric Associations With Incidental Findings in Brain MRI

Importance

Few investigations have evaluated rates of brain-based magnetic resonance imaging (MRI) incidental findings (IFs) in large lifespan samples, their stability over time, or their associations with health outcomes.

Objectives

To examine rates of brain-based IFs across the lifespan, their persistence, and their associations with phenotypic indicators of behavior, cognition, and health; to compare quantified motion with radiologist-reported motion and evaluate its associations with IF rates; and to explore IF consistency across multiple visits.

Design, Setting, and Participants

This cross-sectional study included participants from the Nathan Kline Institute-Rockland Sample (NKI-RS), a lifespan community-ascertained sample, and the Healthy Brain Network (HBN), a cross-sectional community self-referred pediatric sample focused on mental health and learning disorders. The NKI-RS enrolled participants (ages 6-85 years) between March 2012 and March 2020 and had longitudinal participants followed up for as long as 4 years. The HBN enrolled participants (ages 5-21 years) between August 2015 and October 2021. Clinical neuroradiology MRI reports were coded for radiologist-reported motion as well as presence, type, and clinical urgency (category 1, no abnormal findings; 2, no referral recommended; 3, consider referral; and 4, immediate referral) of IFs. MRI reports were coded from June to October 2021. Data were analyzed from November 2021 to February 2023.

Main Outcomes and Measures

Rates and type of IFs by demographic characteristics, health phenotyping, and motion artifacts; longitudinal stability of IFs; and Euler number in projecting radiologist-reported motion.

Results

A total of 1300 NKI-RS participants (781 [60.1%] female; mean [SD] age, 38.9 [21.8] years) and 2772 HBN participants (976 [35.2%] female; mean [SD] age, 10.0 [3.5] years) had health phenotyping and neuroradiology-reviewed MRI scans. IFs were common, with 284 of 2956 children (9.6%) and 608 of 1107 adults (54.9%) having IFs, but rarely of clinical concern (category 1: NKI-RS, 619 [47.6%]; HBN, 2561 [92.4%]; category 2: NKI-RS, 647 [49.8%]; HBN, 178 [6.4%]; category 3: NKI-RS, 79 [6.1%]; HBN, 30 [1.1%]; category 4: NKI-RS: 12 [0.9%]; HBN, 6 [0.2%]). Overall, 46 children (1.6%) and 79 adults (7.1%) required referral for their IFs. IF frequency increased with age. Elevated blood pressure and BMI were associated with increased T2 hyperintensities and age-related cortical atrophy. Radiologist-reported motion aligned with Euler-quantified motion, but neither were associated with IF rates.

Conclusions and Relevance

In this cross-sectional study, IFs were common, particularly with increasing age, although rarely clinically significant. While T2 hyperintensity and age-related cortical atrophy were associated with BMI and blood pressure, IFs were not associated with other behavioral, cognitive, and health phenotyping. Motion may not limit clinical IF detection.

An open-access dataset of naturalistic viewing using simultaneous EEG-fMRI

In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.

A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps

Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem becomes more acute. Software that operates on imaging data defined using the Brain Imaging Data Structure (BIDS) - BIDS Apps - have provided a substantial advance. However, even using BIDS Apps, a full audit trail of data processing is a necessary prerequisite for fully reproducible research. Obtaining a faithful record of the audit trail is challenging - especially for large datasets. Recently, the FAIRly big framework was introduced as a way to facilitate reproducible processing of large-scale data by leveraging DataLad - a version control system for data management. However, the current implementation of this framework was more of a proof of concept, and could not be immediately reused by other investigators for different use cases. Here we introduce the BIDS App Bootstrap (BABS), a user-friendly and generalizable Python package for reproducible image processing at scale. BABS facilitates the reproducible application of BIDS Apps to large-scale datasets. Leveraging DataLad and the FAIRly big framework, BABS tracks the full audit trail of data processing in a scalable way by automatically preparing all scripts necessary for data processing and version tracking on high performance computing (HPC) systems. Currently, BABS supports jobs submissions and audits on Sun Grid Engine (SGE) and Slurm HPCs with a parsimonious set of programs. To demonstrate its scalability, we applied BABS to data from the Healthy Brain Network (HBN; n=2,565). Taken together, BABS allows reproducible and scalable image processing and is broadly extensible via an open-source development model.

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.

Enhancing Collaborative Neuroimaging Research: Introducing COINSTAC Vaults for Federated Analysis and Reproducibility

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.

Omnipresence of the sensorimotor-association axis topography in the human connectome

Low-dimensional representations are increasingly used to study meaningful organizational principles within the human brain. Most notably, the sensorimotor-association axis consistently explains the most variance in the human connectome as its so-called principal gradient, suggesting that it represents a fundamental organizational principle. While recent work indicates these low dimensional representations are relatively robust, they are limited by modeling only certain aspects of the functional connectivity structure. To date, the majority of studies have restricted these approaches to the strongest connections in the brain, treating weaker or negative connections as noise despite evidence of meaningful structure among them. The present work examines connectivity gradients of the human connectome across a full range of connectivity strengths and explores the implications for outcomes of individual differences, identifying potential dependencies on thresholds and opportunities to improve prediction tasks. Interestingly, the sensorimotor-association axis emerged as the principal gradient of the human connectome across the entire range of connectivity levels. Moreover, the principal gradient of connections at intermediate strengths encoded individual differences, better followed individual-specific anatomical features, and was also more predictive of intelligence. Taken together, our results add to evidence of the sensorimotor-association axis as a fundamental principle of the brain's functional organization, since it is evident even in the connectivity structure of more lenient connectivity thresholds. These more loosely coupled connections further appear to contain valuable and potentially important information that could be used to improve our understanding of individual differences, diagnosis, and the prediction of treatment outcomes.

Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images' metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.

Spiking Neural Networks Diagnosis of ADHD subtypes through EEG Signals Evaluation

Attention-deficit hyperactivity disorder (ADHD) affects at least 5% of the world population and can disturb normal development causing serious issues in adulthood. Therefore, it is important to develop tools to help detecting ADHD so that treatment can start as soon as possible. Plus, the differentiation of ADHD in its subtypes is important to define the recommended treatment. Here we present original research to investigate the hypothesis of using a Spiking Neural Networks (SNN) EEG signals classifier for automated diagnostic of ADHD subtypes. This research used data from 243 patients and healthy volunteers acquired as part of the Healthy Brain Network. These resting state EEG signals were collected from 5-minutes scan with a 128 channel 500 Hz system. For benchmarking, we present a comparison of the SNN performance with a support vector machine, a k-nearest neighborhood, a random forest algorithm and a multi-layer perceptron. We present experiments for both the diagnostics of ADHD and for detecting which ADHD subtype the patient has. SNN presented a 72.00% accuracy for detecting ADHD surpassing all the other techniques by 9.1 % and 68% in detecting if the subject is a member of the Combined ADHD, Inattentive ADHD or control groups (18% better than the second-best technique). Clinical Relevance - This work has shown a resource that can be useful allied to other tools to help diagnosing ADHD and its subtypes.

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.

ASLPrep: a platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion

Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines that ensure the reproducible and generalizable processing of ASL MRI data.

Diminished insulin sensitivity is associated with altered brain activation to food cues and with risk for obesity - Implications for individuals born small for gestational age

While classically linked to memory, the hippocampus is also a feeding behavior modulator due to its multiple interconnected pathways with other brain regions and expression of receptors for metabolic hormones. Here we tested whether variations in insulin sensitivity would be correlated with differential brain activation following exposure to palatable food cues, as well as with variations in implicit food memory in a cohort of healthy adolescents, some of whom were born small for gestational age (SGA). Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was positively correlated with activation in the cuneus, and negatively correlated with activation in the middle frontal lobe, superior frontal gyrus and precuneus when presented with palatable food images versus non-food images in healthy adolescents. Additionally, HOMA-IR and insulinemia were higher in participants with impaired food memory. SGA individuals had higher snack caloric density and greater chance for impaired food memory. There was also an interaction between the HOMA-IR and birth weight ratio influencing external eating behavior. We suggest that diminished insulin sensitivity correlates with activation in visual attention areas and inactivation in inhibitory control areas in healthy adolescents. Insulin resistance also associated with less consistency in implicit memory for a consumed meal, which may suggest lower ability to establish a dietary pattern, and can contribute to obesity. Differences in feeding behavior in SGA individuals were associated with insulin sensitivity and hippocampal alterations, suggesting that cognition and hormonal regulation are important components involved in their food intake modifications throughout life.

Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

Resting-state functional magnetic resonance imaging (R-fMRI) studies of the neural correlates of medication treatment in attention-deficit/hyperactivity disorder (ADHD) have not been systematically reviewed. Our objective was to systematically identify, assess and summarize within-subject R-fMRI studies of pharmacological-induced changes in patients with ADHD. We critically appraised strengths and limitations, and provide recommendations for future research.

METHOD

Systematic review of published original reports in English meeting criteria in pediatric and adult patients with ADHD up to July 1, 2020. A thorough search preceded selection of studies matching prespecified criteria. Strengths and limitations of selected studies, regarding design and reporting, were identified based on current best practices.

RESULTS

We identified and reviewed 9 studies (5 pediatric and 4 adult studies). Sample sizes were small-medium (16-38 patients), and included few female participants. Medications were methylphenidate, amphetamines, and atomoxetine. Wide heterogeneity was observed in designs, analyses and results, which could not be combined quantitatively. Qualitatively, the multiplicity of brain regions and networks identified, some of which correlated with clinical improvements, do not support a coherent mechanistic hypothesis of medication effects. Overall, reports did not meet current standards to ensure reproducibility.

CONCLUSION

In this emerging field, the few studies using R-fMRI to analyze the neural correlates of medications in patients with ADHD suggest a potential modulatory effect of stimulants and atomoxetine on several intrinsic brain activity metrics. However, methodological heterogeneity and reporting issues need to be addressed in future research to validate findings which may contribute to clinical care. Such a goal is not yet at hand.

Resting-State fMRI to Identify the Brain Correlates of Treatment Response to Medications in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: Lessons From the CUNMET Study

Neuroimaging research seeks to identify biomarkers to improve the diagnosis, prognosis, and treatment of attention-deficit/hyperactivity disorder (ADHD), although clinical translation of findings remains distant. Resting-state functional magnetic resonance imaging (R-fMRI) is increasingly being used to characterize functional connectivity in the brain. Despite mixed results to date and multiple methodological challenges, dominant hypotheses implicate hyperconnectivity across brain networks in patients with ADHD, which could be the target of pharmacological treatments. We describe the experience and results of the Clínica Universidad de Navarra (Spain) Metilfenidato (CUNMET) pilot study. CUNMET tested the feasibility of identifying R-fMRI markers of clinical response in children with ADHD undergoing naturalistical pharmacological treatments. We analyzed cross-sectional data from 56 patients with ADHD (18 treated with methylphenidate, 18 treated with lisdexamfetamine, and 20 treatment-naive patients). Standard preprocessing and statistical analyses with attention to control for head motion and correction for multiple comparisons were performed. The only results that survived correction were noted in contrasts of children who responded clinically to lisdexamfetamine after long-term treatment vs. treatment-naive patients. In these children, we observed stronger negative correlations (anticorrelations) across nodes in six brain networks, which is consistent with higher across-network functional segregation in patients treated with lisdexamfetamine, i.e., less inter-network interference than in treatment-naive patients. We also note the lessons learned, which could help those pursuing clinically relevant multidisciplinary research in ADHD en route to eventual personalized medicine. To advance reproducible open science, our report is accompanied with links providing access to our data and analytic scripts.

Epilepsy after congenital zika virus infection: EEG and neuroimaging features

PURPOSE

To describe epilepsy after congenital Zika virus infection (ZIKV) and its relationship with structural neuroimaging findings.

METHODS

This was a cross-sectional study in children (aged 13-42 months) who were born with microcephaly due to ZIKV infection between 2015-2017. Patients underwent a brain imaging scan (magnetic resonance) and a video-EEG study.

RESULTS

Among the patients (n = 43), 55.8 % were male, 88.4 % were born at term, mean head circumference at the birth was 29.7 ± 1.8 cm, and 44.8 % were infected in the first trimester of pregnancy. Neuroimaging was moderately abnormal in 30.2 % and severely abnormal in 46.5 % of patients. Early seizures (<6 months of age) were observed in 41.9 %. EEG background was abnormal when asleep or awake in 72.1 % and during sleep in 62.8 %. The interictal epileptogenic activity was recorded on 41/43 of the EEGs and was predominantly multifocal (62.8 %). An ictal EEG was obtained in 22 patients and 31.8 % had more than one seizure type. Sleep EEG (background) patterns, interictal epileptogenic activity (p = 0.046), interictal discharge localization (p = 0.015), type of ictal epileptogenic activity (p = 0.002), and localization of ictal discharge (p = 0.024) were significantly different between neuroimaging groups. The mild neuroimaging group had a higher chance of having more frequently normal sleep EEG patterns, no interictal epileptogenic activity and a further increase in the probability of walking without limitations, and less neurodevelopment delay.

CONCLUSION

In patients with congenital Zika virus syndrome, epilepsy tended to be early and refractory. EEG features correlated with degree of neuroimaging abnormalities.

Joint embedding: A scalable alignment to compare individuals in a connectivity space

A common coordinate space enabling comparison across individuals is vital to understanding human brain organization and individual differences. By leveraging dimensionality reduction algorithms, high-dimensional fMRI data can be represented in a low-dimensional space to characterize individual features. Such a representative space encodes the functional architecture of individuals and enables the observation of functional changes across time. However, determining comparable functional features across individuals in resting-state fMRI in a way that simultaneously preserves individual-specific connectivity structure can be challenging. In this work we propose scalable joint embedding to simultaneously embed multiple individual brain connectomes within a common space that allows individual representations across datasets to be aligned. Using Human Connectome Project data, we evaluated the joint embedding approach by comparing it to the previously established orthonormal alignment model. Alignment using joint embedding substantially increased the similarity of functional representations across individuals while simultaneously capturing their distinct profiles, allowing individuals to be more discriminable from each other. Additionally, we demonstrated that the common space established using resting-state fMRI provides a better overlap of task-activation across participants. Finally, in a more challenging scenario - alignment across a lifespan cohort aged from 6 to 85 - joint embedding provided a better prediction of age (r2 = 0.65) than the prior alignment model. It facilitated the characterization of functional trajectories across lifespan. Overall, these analyses establish that joint embedding can simultaneously capture individual neural representations in a common connectivity space aligning functional data across participants and populations and preserve individual specificity.

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individua differences. However, test–retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test–retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test–retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed – a process likely to be limited for most due to the lack of test–retest samples to enable parameter optimization.

Plantar stimulation alters brain connectivity in idiopathic Parkinson's disease

OBJECTIVE

Individuals with Parkinson's disease (PD) and freezing of gait (FOG) present peripheral and central sensitivity disturbances that impair motor performance. This study aimed to investigate long-term effects of plantar sensory stimulation on brain activity, brain connectivity, and gait velocity of individuals with PD and FOG.

METHODS

Twenty-five participants were enrolled in this clinical trial (NCT02594540). Plantar sensory stimulation was delivered using the Automated Mechanical Peripheral Stimulation therapy (AMPS). Volunteers were randomly assigned to real or placebo AMPS groups and received eight sessions of treatment. The primary outcome was brain activity (task-based fMRI-active ankle dorsi-plantar flexion). Secondary outcomes were brain connectivity (resting state-RS fMRI) and gait velocity. fMRI was investigated on the left, right, and mid-sensory motor regions, left and right basal ganglia.

RESULTS

No changes in brain activity were observed when task-based fMRI was analyzed. After real AMPS, RS functional connectivity between basal ganglia and sensory-related brain areas increased (insular and somatosensory cortices). Gait velocity also increased after real AMPS. A positive correlation was found between gait velocity and the increased connectivity between sensory, motor and supplementary motor cortices.

CONCLUSION

Plantar sensory stimulation through AMPS was not able to modify brain activity. AMPS increased the RS brain connectivity mainly in areas related to sensory processing and sensorimotor integration. Plantar stimulation could be a way to improve plantar sensitivity and consequently ameliorate gait performance. However, the mechanisms behind the way AMPS influences brain pathways are still not completely known.

Comparative evaluation of video-based on-line course versus serious game for training medical students in cardiopulmonary resuscitation: A randomised trial

Purpose

To estimate the effect size of a serious game for cardiopulmonary resuscitation (CPR) training in comparison with a video-based on-line course in terms of learning outcomes among medical students before simulation-based CPR using a manikin.

Methods

Participants were 45 first-year medical students randomly assigned to CPR self-training using either a video-based Apple Keynote presentation (n = 22) or a serious game developed in a 3D learning environment (n = 23) for up to 20 min. Each participant was evaluated on a written, multiple-choice test (theoretical test) and then on a scenario of cardiac arrest (practical test) before and after exposure to the self-learning methods. The primary endpoint was change in theoretical and practical baseline scores during simulated CPR. This study was conducted in 2017.

Results

Both groups improved scores after exposure. The video group had superior performance in both the theoretical test (7.56±0.21 vs 6.51±0.21 for the game group; p = 0.001) and the practical test (9.67±0.21 vs 8.40±0.21 for the game group; p < 0.001). However, students showed a preference for using games, as suggested by the longer time they remained interested in the method (18.57±0.66 min for the game group vs 7.41±0.43 for the video group; p < 0.001).

Conclusions

The self-training modality using a serious game, after a short period of exposure, resulted in inferior students’ performance in both theoretical and practical CPR tests compared to the video-based self-training modality. However, students showed a clear preference for using games rather than videos as a form of self-training.

Effect of corporal suspension and pendulum exercises on neuromuscular properties and functionality in patients with medullar thoracic injury

BACKGROUND

Traumatic spinal cord injury (TSCI) is one of the most devastating injuries that has a physical impact on patients. The CHORDATA® method involves suspension and pendulous exercises and has been clinically used to treat patients with TSCI. Although empirically used to treat neurological patients, there is no scientific evidence of the efficacy of this method.

PURPOSE

To evaluate the chronic effects of CHORDATA® method on torque, muscle activation, muscle thickness, and functionality in patients with traumatic spinal cord injury.

METHODS

Twenty-six male patients with medullar thoracic injury were randomly categorised into two groups: intervention group (n = 14) and control group (n = 12). Rehabilitation program comprised of 16 sessions of body suspension and pendulum exercises (twice/week). The maximal voluntary isometric trunk flexion and extension torques, muscle activation and thickness (external and internal oblique, rectus and transversus abdominis, longissimus, and multifidus muscles), and functionality (adapted reach test) were evaluated before and after of rehabilitation program.

FINDINGS

A significant increase was observed in maximal voluntary isometric torque (flexion, 58%; extension, 76%), muscle activation of the rectus abdominis muscle, and muscle thickness of all intervention group muscles, without changes in the control group. Compared to the pre-intervention period, the intervention group also showed improvement in functionality at post-intervention, but no such differences were noted in the control group.

INTERPRETATION

The corporal suspension and pendulum exercises training improved rectus abdominis muscle activation, trunk muscles structure and strength, and reaching capacity in medullar thoracic injury patients.

Increased brain cortical thickness associated with visceral fat in adolescents

BACKGROUND

There has been a growing amount of evidence indicating that excess visceral fat is associated with alterations in brain structure and function, including brain cortical thinning in adults.

OBJECTIVES

This study aims to investigate the relationship between brain cortical thickness with obesity assessments, in adolescents.

METHODS

In this study, we measured three different obesity assessments within an adolescent population (aged 15 - 18 years): body mass index (BMI), visceral fat ratio measured with an MRI and hepatorenal gradient measured with an ultrasound. Volunteers also underwent an MRI scan to measure brain structure.

RESULTS

Results indicated that there was no relationship of BMI or hepatorenal gradient with brain cortical dimensions. However, there was a significant association between visceral fat ratio and an increase of cortical thickness throughout the brain.

CONCLUSIONS

These results suggest that visceral fat, but not BMI, is correlated with cortical thickening in adolescence.

Brainhack: a collaborative workshop for the open neuroscience community

Brainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science.

Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data

With resting-state functional MRI (rs-fMRI) there are a variety of post-processing methods that can be used to quantify the human brain connectome. However, there is also a choice of which preprocessing steps will be used prior to calculating the functional connectivity of the brain. In this manuscript, we have tested seven different preprocessing schemes and assessed the reliability between and reproducibility within the various strategies by means of graph theoretical measures. Different preprocessing schemes were tested on a publicly available dataset, which includes rs-fMRI data of healthy controls. The brain was parcellated into 190 nodes and four graph theoretical (GT) measures were calculated; global efficiency (GEFF), characteristic path length (CPL), average clustering coefficient (ACC), and average local efficiency (ALE). Our findings indicate that results can significantly differ based on which preprocessing steps are selected. We also found dependence between motion and GT measurements in most preprocessing strategies. We conclude that by using censoring based on outliers within the functional time-series as a processing, results indicate an increase in reliability of GT measurements with a reduction of the dependency of head motion.

Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimer's disease

Alzheimer's disease (AD) is characterized by mental and cognitive problems, particularly with memory, language, visuospatial skills (VS), and executive functions (EF). Advances in the neuroimaging of AD have highlighted dysfunctions in functional connectivity networks (FCNs), especially in the memory related default mode network (DMN). However, little is known about the integrity and clinical significance of FNCs that process other cognitive functions than memory. We evaluated 22 patients with mild AD and 26 healthy controls through a resting state functional MRI scan. We aimed to identify different FCNs: the DMN, language, EF, and VS. Seed-based functional connectivity was calculated by placing a seed in the DMN (posterior cingulate cortex), language (Broca's and Wernicke's areas), EF (right and left dorsolateral prefrontal cortex), and VS networks (right and left associative visual cortex). We also performed regression analyses between individual connectivity maps for the different FCNs and the scores on cognitive tests. We found areas with significant decreases in functional connectivity in patients with mild AD in the DMN and Wernicke's area compared with controls. Increased connectivity in patients was observed in the EF network. Regarding multiple linear regression analyses, a significant correlation was only observed between the connectivity of the DMN and episodic memory (delayed recall) scores. In conclusion, functional connectivity alterations in mild AD are not restricted to the DMN. Other FCNs related to language and EF may be altered. However, we only found significant correlations between cognition and functional connectivity in the DMN and episodic memory performance.

Reconciling variable findings of white matter integrity in major depressive disorder

Diffusion tensor imaging (DTI) has been used to evaluate white matter (WM) integrity in major depressive disorder (MDD), with several studies reporting differences between depressed patients and controls. However, these findings are variable and taken from relatively small studies often using suboptimal analytic approaches. The presented DTI study examined WM integrity in large samples of medication-free MDD patients (n=134) and healthy controls (n=54) using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) approaches, and rigorous statistical thresholds. Compared with health control subjects, MDD patients show no significant differences in fractional anisotropy, radial diffusivity, mean diffusivity, and axonal diffusivity with either the VBM or the TBSS approach. Our findings suggest that disrupted WM integrity does not have a major role in the neurobiology of MDD in this relatively large study using optimal imaging acquisition and analysis; however, this does not eliminate the possibility that certain patient subgroups show WM disruption associated with depression.

Impact of analysis methods on the reproducibility and reliability of resting-state networks

Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors: (1) group versus subject-level analyses (group>subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined>separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based>ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.

Toward a neuroimaging treatment selection biomarker for major depressive disorder

IMPORTANCE

Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact.

OBJECTIVE

To identify a candidate neuroimaging "treatment-specific biomarker" that predicts differential outcome to either medication or psychotherapy.

DESIGN

Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy.

SETTING

Mood and anxiety disorders research program at an academic medical center.

PARTICIPANTS

Men and women aged 18 to 60 years with currently untreated major depressive disorder.

INTERVENTION

Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy.

MAIN OUTCOME AND MEASURE

Remission, defined as a 17-item Hamilton depression rating scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment.

RESULTS

Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy.

CONCLUSIONS AND RELEVANCE

If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression.

TRIAL REGISTRATION

Registered at clinicaltrials.gov (NCT00367341).

The Illness Density Index (IDI): A longitudinal measure of treatment efficacy

BACKGROUND

A reliable and meaningful quantitative index of success is paramount in the trial of any new treatment. However, existing methods for defining response and remission for treatments tested for psychiatric disorders are limited in that they often minimize the variance in change over time among individual patients and generally use arbitrarily chosen levels of functioning at specified times during treatment.

PURPOSE

To suggest and determine the properties of an alternative measure of treatment success, the Illness Density Index (IDI), that may be more sensitive to fluctuations in symptoms over the course of treatment compared to existing measures.

METHODS

We examined data from 64 depressed patients with multiple assessments of the Hamilton Depression Rating Scale (HDRS) over 12 weeks of randomized treatment in order to compare and contrast varying numerical definitions of response and remission, including percent change and linear slope over time.

RESULTS

Examination of the indices comparing the within-sample rank of individual patients revealed that these indices agree in cases where patients have little or no response as well as clear and sustained response, while they differ in patients who have a slow (or late) response as well as relapse during the treatment course.

LIMITATIONS

The measure may not be useful for all types of studies, especially short-term treatment trials.

CONCLUSIONS

The IDI is highly correlated with both categorical (e.g., remission) and continuous (e.g., percent change) definitions of treatment success. Furthermore, it differentiates certain trajectories of change that current definitions do not. Thus, the proposed index may be a valuable addition to current measures of efficacy, especially when trying to identify biological substrates of illness or predictors of long-term outcome.

Modeling conflict and error in the medial frontal cortex

Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal).

Bacterial community dynamics in horizontal flow constructed wetlands with different plants for high salinity industrial wastewater polishing

This study is focused on the diversity of bacterial communities from two series of horizontal subsurface flow constructed wetlands (CW) polishing high salinity tannery wastewater. Each series was planted with Arundo donax or Sarcocornia sp. in a substrate composed by expanded clay and sand. Chemical and biochemical oxygen demand removal efficiencies were similar in each series, varying between 58 and 67% (inlet COD 218 ± 28 mg L(-1)) and 60 and 77% (inlet BOD(5) 37 ± 6 mg L(-1)), respectively. High numbers of culturable bacteria were obtained from substrate and root samples - 5.75 × 10(6)-3.95 × 10(8) CFU g(-1) recovered on marine agar and 1.72 × 10(7)-8.46 × 10(8) CFU g(-1) on nutrient agar. Fifty bacterial isolates were retrieved from the CW, related phylogenetically to Firmicutes, Actinobacteria, Bacteroidetes, α-, β-, and γ-Proteobacteria. Changes in the bacterial communities, from roots and substrate of each series, related to the plant species, hydraulic loading rates and along CW operation were examined using denaturating gradient gel electrophoresis (DGGE). The clustering analysis suggested that a diverse and distinct bacterial community inhabits each series, which was related to the type of plant present in each CW.

Resistance to Phosphinothricin (Glufosinate) and Its Utilization as a Nitrogen Source by Chlamydomonas reinhardtii

Wild-type strain 21gr of the green alga Chlamydomonas reinhardtii was resistant to the ammonium salt of l-phosphinothricin (PPT, also called glufosinate), an irreversible inhibitor of glutamine synthetase activity and the main active component of the herbicide BASTA (AgrEvo, Frankfurt am Main, Germany). Under the same conditions, however, this strain was highly sensitive to l-methionine-S-sulfoximine, a structural analog of PPT which has been reported to be 5 to 10 times less effective than PPT as an inhibitor in plants. Moreover, this alga was able to grow with PPT as the sole nitrogen source when this compound was provided at low concentrations. This utilization of PPT was dependent upon the addition of acetate and light and did not take place in the presence of ammonium. Resistance was due neither to the presence of N-acetyltransferase or transaminase activity nor to the presence of glutamine synthetase isoforms resistant to PPT. By using l-[methyl-(sup14)C]PPT, we demonstrated that resistance is due to lack of PPT transport into the cells. This strongly suggests that PPT and l-methionine-S-sulfoximine enter the cells through different systems. Growth with PPT is supported by its deamination by an l-amino acid oxidase activity which has been previously described to be located at the periplasm.

Resting state and task-induced deactivation: A methodological comparison in patients with schizophrenia and healthy controls

Changes in the default mode network (DMN) have been linked to multiple neurological disorders including schizophrenia. The anticorrelated relationship the DMN shares with task-related networks permits the quantification of this network both during task (task-induced deactivations: TID) and during periods of passive mental activity (extended rest). However, the effects of different methodologies (TID vs. extended rest) for quantifying the DMN in the same clinical population are currently not well understood. Moreover, several different analytic techniques, including independent component analyses (ICA) and seed-based correlation analyses, exist for examining functional connectivity during extended resting states. The current study compared both methodologies and analytic techniques in a group of patients with schizophrenia (SP) and matched healthy controls. Results indicated that TID analyses, ICA, and seed-based correlation all consistently identified the midline (anterior and posterior cingulate gyrus) and lateral parietal cortex as core regions of the DMN, as well as more variable involvement of temporal lobe structures. In addition, SP exhibited increased deactivation during task, as well as decreased functional connectivity with frontal regions and increased connectivity with posterior and subcortical areas during periods of extended rest. The increased posterior and reduced anterior connectivity may partially explain some of the cognitive dysfunction and clinical symptoms that are frequently associated with schizophrenia.

Interrater and intermethod reliability of default mode network selection

There has been a growing interest in the neuroimaging community regarding resting state data (i.e., passive mental activity) and the subsequent activation of the so-called default mode network (DMN). Although this network was originally characterized by a pattern of deactivation during active cognitive states, more recent applications of data-driven techniques such as independent component analysis (ICA) have permitted the analysis of brain activation during extended periods of truly passive mental activity. However, ICA requires the resultant components to be evaluated for "goodness of fit" via either human raters or more automated techniques. To our knowledge, an investigation on the reliability of either technique in determining the component that best corresponds to default-mode activity has not been performed. Moreover, it is not clear how automated techniques, which are necessarily dependent upon a template mask, are affected by the structures used to compose the mask. The current study investigated both interrater (human-human) reliability and intermethod (human-machine) reliability for determining DMN activation in 42 healthy controls. Results indicated that near perfect interrater reliability was achieved, whereas intermethod reliability was only within the moderate range. The latter was significantly improved via a weighted combination of the anterior and posterior cingulate nodes of the DMN. Implications for fully automating the component selection process are discussed.

Neuronal modulation of auditory attention by informative and uninformative spatial cues

Sounds provide important information about the spatial environment, including the location of approaching objects. Attention to sounds can be directed through automatic or more controlled processes, which have been well studied in the visual modality. However, little is known about the neural underpinnings of attentional control mechanisms for auditory signals. We studied healthy adults who underwent event-related FMRI while performing a task that manipulated automatic and more controlled auditory orienting by varying the probability that cues correctly predicted target location. Specifically, we examined the effects of uninformative (50% validity ratio) and informative (75% validity ratio) auditory cues on reaction time (RT) and neuronal functioning. The stimulus-onset asynchrony (SOA) between the cue and the target was either 100 or 800 ms. At the 100 ms SOA, RT was faster for valid than invalid trials for both cue types, and frontoparietal activation was greater for invalid than valid trials. At the 800 ms SOA, RT and functional activation depended on whether cues were informative or uninformative, and whether cues correctly or incorrectly predicted the target location. Contrary to our prediction, activation in a frontoparietal network was greater for uninformative than informative cues across several different comparisons and at both SOAs. This finding contrasts with similar research of visual orienting, and suggests that the auditory modality may be more biased toward automatic shifts of attention following uninformative cues.

Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis

The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.

The effects of stimulus modality and frequency of stimulus presentation on cross-modal distraction

Selective attention produces enhanced activity (attention-related modulations [ARMs]) in cortical regions corresponding to the attended modality and suppressed activity in cortical regions corresponding to the ignored modality. However, effects of behavioral context (e.g., temporal vs. spatial tasks) and basic stimulus properties (i.e., stimulus frequency) on ARMs are not fully understood. The current study used functional magnetic resonance imaging to investigate selectively attending and responding to either a visual or auditory metronome in the presence of asynchronous cross-modal distractors of 3 different frequencies (0.5, 1, and 2 Hz). Attending to auditory information while ignoring visual distractors was generally more efficient (i.e., required coordination of a smaller network) and less effortful (i.e., decreased interference and presence of ARMs) than attending to visual information while ignoring auditory distractors. However, these effects were modulated by stimulus frequency, as attempting to ignore auditory information resulted in the obligatory recruitment of auditory cortical areas during infrequent (0.5 Hz) stimulation. Robust ARMs were observed in both visual and auditory cortical areas at higher frequencies (2 Hz), indicating that participants effectively allocated attention to more rapidly presented targets. In summary, results provide neuroanatomical correlates for the dominance of the auditory modality in behavioral contexts that are highly dependent on temporal processing.

The neural networks underlying auditory sensory gating

One of the most consistent electrophysiological deficits reported in the schizophrenia literature is the failure to inhibit, or properly gate, the neuronal response to the second stimulus of an identical pair (i.e., sensory gating). Although animal and invasive human studies have consistently implicated the auditory cortex, prefrontal cortex and hippocampus in mediating the sensory gating response, localized activation in these structures has not always been reported during non-invasive imaging modalities. In the current experiment, event-related FMRI and a variant of the traditional gating paradigm were utilized to examine how the gating network differentially responded to the processing of pairs of identical and non-identical tones. Two single-tone conditions were also presented so that they could be used to estimate the HRF for paired stimuli, reconstructed based on actual hemodynamic responses, to serve as a control non-gating condition. Results supported an emerging theory that the gating response for both paired-tone conditions was primarily mediated by auditory and prefrontal cortex, with potential contributions from the thalamus. Results also indicated that the left auditory cortex may play a preferential role in determining the stimuli that should be inhibited (gated) or receive further processing due to novelty of information. In contrast, there was no evidence of hippocampal involvement, suggesting that future work is needed to determine what role it may play in the gating response.

Assessment and quantification of head motion in neuropsychiatric functional imaging research as applied to schizophrenia

Differing degrees of head motion have long been recognized as a potential confound in functional neuroimaging studies comparing neuropsychiatric populations to healthy normal volunteers, and studies often cite excessive head motion as a possible reason for the different patterns of functional activation frequently observed between groups. We empirically tested the degree of head motion in 16 patients with chronic schizophrenia and 16, age- and education-matched controls during the acquisition of functional magnetic resonance imaging data. We examined the degree of motion across three different indices (total motion, relative motion, task-correlated motion) during a complex attentional task and the effect of entering the motion parameters as additional regressors in a general linear model analysis. Results indicate that individuals with schizophrenia did not exhibit more task-correlated or total motion compared with controls. Moreover, the residual error term from the general linear model analysis was similar for both groups of subjects. In conclusion, current results suggest that stable patients with schizophrenia are capable of controlling head motion compared with matched normal controls. However, a direct comparison of the motion parameters is an essential step for any quality assurance protocol to determine whether additional corrective techniques need to be implemented.

Morphological and molecular characterization of different Echinochloa spp. and Oryza sativa populations

Echinochloa P. Beauv. is an important genus because many of its species are weeds infesting most paddy fields, which can reduce the rice grain production by up to 80%. A controversy exists about the taxonomy of the genus due to the high level of morphological variations found in these species. Cyhalofop-butyl, an aryloxyphenoxy-propionate herbicide, is used to control Echinochloa spp. in paddy fields, although differences in susceptibility were found between different Echinochloa species. E. colona was highly susceptible [ED50= 34 g of active ingredient (ai) ha(-1)]; very similar results were obtained with the remaining species. By contrast, E. oryzicola (170 g of ai ha(-1)) was less sensitive, with the herbicide symptoms appearing later. Because of this differential susceptibility, morphological and molecular studies were carried out. A morphological study, using 21 characters both quantitative and qualitative of spikelets and seedlings, was capable of clearly distinguishing closely related E. crus-galli plants (two populations), E. muricata and E. crus-pavonis, and E. oryzicola, E. utilis, and E. colona species. The resolution of Echinochloa species at the molecular level, based on RAPD analyses, was fairly consistent with morphological analysis results. Among the 60 primers screened, 21 primers exhibited polymorphic bands and produced a total of 136 RAPD markers. Of all the amplified fragments, 90 were found to be polymorphic. E. oryzicola and E. colona were clearly separated, and the RAPD analyses showed that both E. crus-galli populations were 100% related and 51% related to E. utilis, whereas E. crus-pavonis and E. muricata (73% similarity) appeared as being clearly separated from this group.

Isolation and characterization of polymeric galloyl-ester-degrading bacteria from a tannery discharge place

The culturable bacteria colonizing the rhizosphere of plants growing in the area of discharge of a tannery effluent were characterized. Relative proportions of aerobic, denitrifying, and sulfate-reducing bacteria were determined in the rhizosphere of Typha latifolia, Canna indica, and Phragmites australis. Aerobic bacteria were observed to be the most abundant group in the rhizosphere, and plant type did not seem to influence the abundance of the bacterial types analyzed. To isolate bacteria able to degrade polyphenols used in the tannery industry, enrichments were conducted under different conditions. Bacterial cultures were enriched with individual polyphenols (tannins Tara, Quebracho, or Mimosa) or with an undefined mixture of tannins present in the tannery effluent as carbon source. Cultures enriched with the effluent or Tara tannin were able to degrade tannic acid. Six bacterial isolates purified from these mixed cultures were able to use tannic acid as a sole carbon source in axenic culture. On the basis of 16S ribosomal DNA sequence analysis, these isolates were closely related to organisms belonging to the taxa Serratia, Stenotrophomonas maltophilia, Klebsiella oxytoca, Herbaspirillum chlorophenolicum, and Pseudomonas putida.

Biodegradation of simazine in olive fields

Simazine (2-chloro-4, bis ethylamino-1,3,5-triazine) is a herbicide of the s-triazine group used mainly to control broad-leaved weeds in different crops. Several papers report about simazine and other s-triazine derivates as being actual polluting agents. In fact, simazine has been detected in groundwater and soil. Since this herbicide has been extensively used in Andalusia (south of Spain), we are analyzing the levels of simazine residues found in the soil of olive fields. We are also simazine could be detected isolating live micro organisms able to degrade this compound, and are characterizing the metabolic pathways leading to this degradation and the fate of this compound in nature. With all these data in mind, we will try to develop a strategy for the bioremediation of contaminated soils. We have taken samples of soil from many olive orchards of Andalusia that have been treated with simazine. These samples were located with the help of a handheld GPS. The presence of simazine of these samples was detected by HPLC. In most of the samples taken no, and those where it could be, contained very low levels of this herbicide (lower than 0.5 ppm). Soil samples are being characterized to determine their physicochemical characteristics [pH, organic matter, texture, etc), and we are attempting to correlate all these parameters with the presence or absence of simazine. From some of the soils, we have isolated a group of micro organisms that can grow using simazine as the sole carbon and nitrogen sources. We are analyzing how the addition of carbon or nitrogen can influence the rate of the simazine degradation.

Detection of mycoplasmal infections in blood of patients with rheumatoid arthritis

OBJECTIVE

Mycoplasmal infections are associated with several acute and chronic illnesses. Some mycoplasmas can enter a variety of tissues and cells, and cause system-wide or systemic signs and symptoms.

METHODS

Patients (14 female, 14 male) diagnosed with rheumatoid arthritis (RA) were investigated for mycoplasmal infections in their blood leucocytes using a forensic polymerase chain reaction (PCR) procedure. Amplification was performed with genus- and species-specific primers, and a specific radiolabelled internal probe was used for Southern hybridization with the PCR product. Patients were investigated for the presence of Mycoplasma spp., and positive cases were further tested for infections with the following species: M. fermentans, M. hominis, M. pneumoniae and M. penetrans.

RESULTS

The Mycoplasma spp. sequence, which is not entirely specific for mycoplasmas, was amplified from the peripheral blood of 15/28 patients (53.6%) and specific PCR products could not be detected in 13 patients (46.4%). Significant differences (P < 0.001) were found between patients and positive healthy controls in the genus test (3/32) and in the specific tests (0/32). Moreover, the incidence of mycoplasmal infections was similar in female and male patients. Using species-specific primers, we were able to detect infections with M. fermentans (8/28), M. pneumoniae (5/28), M. hominis (6/28) and M. penetrans (1/28) in RA patients. In 36% of the patients, we observed more than one Mycoplasma species in the blood leucocytes. All multiple infections occurred as combinations of M. fermentans with other species.

CONCLUSIONS

The results suggest that a high percentage of RA patients have systemic mycoplasmal infections. Systemic mycoplasmal infections may be an important cofactor in the pathogenesis of RA, and their role needs to be explored further.

Induction and superinduction of auxin-responsive mRNAs with auxin and protein synthesis inhibitors

We have identified a class of small mRNAs (approximately 0.5 kilobases), referred to as small auxin-up RNAs (SAURs), that increases in abundance within minutes after auxin application to excised elongating hypocotyl sections of soybean. In this study, we present evidence that SAURs accumulate in the absence of auxin when protein synthesis is inhibited. Superinduction of SAURs occurs if the synthetic auxin 2,4-dichlorophenoxyacetic acid is added under conditions where protein synthesis is inhibited. Transcription run-on experiments with isolated nuclei show that, unlike 2,4-dichlorophenoxyacetic acid, protein synthesis inhibitors do not activate transcription of the SAUR genes. These results suggest that protein synthesis inhibitors act by stabilizing SAURs and that some labile protein(s) are involved in the rapid turnover of SAURs. This stabilization is not observed with GH3, another auxin-inducible mRNA. Whether induced with 2,4-dichlorophenoxyacetic acid or cycloheximide, SAURs are primarily expressed in epidermal and cortical cells of elongating hypocotyl sections, with little or no expression in vascular tissue. Unlike 2,4-dichlorophenoxyacetic acid-induced SAUR accumulation, the increase in abundance of SAURs induced by cycloheximide is transient, with a peak approximately 1 h after inhibitor addition. Complete inhibition of protein synthesis is not required for SAUR accumulation in the presence of protein synthesis inhibitors.

Regulation by ammonium of nitrate and nitrite assimilation in Chlamydomonas reinhardtii

The inhibitor of mRNA synthesis, 6-methylpurine, inhibited nitrate reductase derepression in either ammonium-grown or methylammonium-treated wild-type cells of Chlamydomonas reinhardtii, but not in nitrogen-starved cells. In contrast, 6-methylpurine did not inhibit nitrate reductase synthesis in the methylammonium-resistant mutant 2170 (ma-1) either grown on ammonium, treated with methylammonium or nitrogen starved, but did inhibit the continuous synthesis of nitrate reductase, which required the presence of nitrate in the media. In both wild-type and mutant 2170 grown on ammonium and transferred to nitrate media, cycloheximide immediately prevented nitrate reductase derepression when added either at the beginning or at different times of induction treatment. Unlike wild-type cells, mutant 2170 was able to take up either nitrate or nitrite simultaneously with ammonium in whose presence nitrate and nitrite reductases were synthesized. However, synthesis of nitrate reductase was progressively inhibited in the mutant cells when the intracellular ammonium levels were raised as a result of an increase in either the external pH or the extracellular ammonium concentrations. The results rule out the existence of maturase-like proteins in Chlamydomonas and indicate that ammonium has a double effect on the regulation of nitrate reductase synthesis: (a) it prevents nitrate reductase mRNA production; and (b) it controls negatively the expression of this mRNA.

Two different carriers transport both ammonium and methylammonium in Chlamydomonas reinhardtii

A new methylammonium-resistant mutant strain from Chlamydomonas reinhardtii, henceforth termed 2172 (ma-2), has been isolated. This mutant is affected in a single mendelian gene different from and linked to the ma-1 locus which is defective in the methylammonium-resistant mutant 2170. Both mutations in ma-1 (2170) and ma-2 (2172) are linked to the nit-1 gene coding for the nitrate reductase apoenzyme. Mutant 2172 is affected in methylammonium but not in ammonium uptake capacity and shows derepressed nitrate and nitrite reductase activities in media containing nitrate plus methylammonium but not in nitrate plus ammonium media. The following two enzymatic components for the transport of both ammonium and methylammonium in wild-type cells have been identified: component 1, with high Vmax and K values, which is constitutive, and component 2, with low Vmax and K values, which is ammonium-repressible. Mutant 2170 lacks component 1 whereas mutant 2172 lacks component 2 for both methylammonium and ammonium transport. From genetic and kinetic evidences we conclude that in C. reinhardtii two different carriers are responsible for the transport of both ammonium and methylammonium and that methylammonium (ammonium) transport is a reversible process probably inhibited by the intracellular ammonium which, in turn, regulates nitrate and nitrite reductase levels.