The independence and interdependence of coacting observers in regard to performance efficiency, workload, and stress in a vigilance task

Objective We investigated performance, workload, and stress in groups of paired observers who performed a vigilance task in a coactive (independent) manner. Background Previous studies have demonstrated that groups of coactive observers detect more signals in a vigilance task than observers working alone. Therefore, the use of such groups might be effective in enhancing signal detection in operational situations. However, concern over appearing less competent than one's cohort might induce elevated levels of workload and stress in coactive group members and thereby undermine group performance benefits. Accordingly, we performed the initial experiment comparing workload and stress in observers who performed a vigilance task coactively with those of observers who performed the vigilance task alone. Method Observers monitored a video display for collision flight paths in a simulated unmanned aerial vehicle control task. Self-reports of workload and stress were secured via the NASA-Task Load Index and the Dundee Stress State Questionnaire, respectively. Results Groups of coactive observers detected significantly more signals than did single observers. Coacting observers did not differ significantly from those operating by themselves in terms of workload but did in regard to stress; posttask distress was significantly lower for coacting than for single observers. Conclusion Performing a visual vigilance task in a coactive manner with another observer does not elevate workload above that of observers working alone and serves to attenuate the stress associated with vigilance task performance. Application The use of coacting observers could be an effective vehicle for enhancing performance efficiency in operational vigilance

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

Complex lithium ion dynamics in simulated LiPO3 glass studied by means of multi-time correlation functions

Molecular dynamics simulations are performed to study the lithium jumps in LiPO3 glass. In particular, we calculate higher-order correlation functions that probe the positions of single lithium ions at several times. Three-time correlation functions show that the non-exponential relaxation of the lithium ions results from both correlated back-and-forth jumps and the existence of dynamical heterogeneities, i.e., the presence of a broad distribution of jump rates. A quantitative analysis yields that the contribution of the dynamical heterogeneities to the non-exponential depopulation of the lithium sites increases upon cooling. Further, correlated back-and-forth jumps between neighboring sites are observed for the fast ions of the distribution, but not for the slow ions and, hence, the back-jump probability depends on the dynamical state. Four-time correlation functions indicate that an exchange between fast and slow ions takes place on the timescale of the jumps themselves, i.e., the dynamical heterogeneities are short-lived. Hence, sites featuring fast and slow lithium dynamics, respectively, are intimately mixed. In addition, a backward correlation beyond the first neighbor shell for highly mobile ions and the presence of long-range dynamical heterogeneities suggest that fast ion migration occurs along preferential pathways in the glassy matrix. In the melt, we find no evidence for correlated back-and-forth motions and dynamical heterogeneities on the length scale of the next-neighbor distance.Comment: 12 pages, 13 figure

Corrigendum: The Importance of the Validation of M/EEG With Current Biomarkers in Alzheimer's Disease

Current biomarkers used in research and in clinical practice in Alzheimer's Disease (AD) are the analysis of cerebral spinal fluid (CSF) to detect levels of Aβ42 and phosphorylated-tau, amyloid and FDG-PET, and MRI volumetry. Some of these procedures are still invasive for patients or expensive. Electroencephalography (EEG) and Magnetoencephalography (MEG) are two non-invasive techniques able to detect the early synaptic dysfunction and track the course of the disease. However, in spite of its added value they are not part of the standard of care in clinical practice in dementia. In this paper we review what these neurophysiological techniques can add to the early diagnosis of AD, whether results in both modalities are related to each other or not, as well as the need of its validation against current biomarkers. We discuss their potential implications for the better understanding of the pathophysiological mechanisms of the disease as well as the need of performing simultaneous M/EEG recordings to better understand discrepancies between these two techniques. Finally, more studies are needed studying M/EEG with amyloid and Tau biomarkers

The Importance of the Validation of M/EEG With Current Biomarkers in Alzheimer's Disease

Current biomarkers used in research and in clinical practice in Alzheimer's Disease (AD) are the analysis of cerebral spinal fluid (CSF) to detect levels of Aβ42 and phosphorylated-tau, amyloid and FDG-PET, and MRI volumetry. Some of these procedures are still invasive for patients or expensive. Electroencephalography (EEG) and Magnetoencephalography (MEG) are two non-invasive techniques able to detect the early synaptic dysfunction and track the course of the disease. However, in spite of its added value they are not part of the standard of care in clinical practice in dementia. In this paper we review what these neurophysiological techniques can add to the early diagnosis of AD, whether results in both modalities are related to each other or not, as well as the need of its validation against current biomarkers. We discuss their potential implications for the better understanding of the pathophysiological mechanisms of the disease as well as the need of performing simultaneous M/EEG recordings to better understand discrepancies between these two techniques. Finally, more studies are needed studying M/EEG with amyloid and Tau biomarkers

Ratiometric high-resolution imaging of JC-1 fluorescence reveals the subcellular heterogeneity of astrocytic mitochondria

Using the mitochondrial potential (ΔΨm) marker JC-1 (5,5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolylcarbocyanine iodide) and high-resolution imaging, we functionally analyzed mitochondria in cultured rat hippocampal astrocytes. Ratiometric detection of JC-1 fluorescence identified mitochondria with high and low ΔΨm. Mitochondrial density was highest in the perinuclear region, whereas ΔΨm tended to be higher in peripheral mitochondria. Spontaneous ΔΨm fluctuations, representing episodes of increased energization, appeared in individual mitochondria or synchronized in mitochondrial clusters. They continued upon withdrawal of extracellular Ca2+, but were antagonized by dantrolene or 2-aminoethoxydiphenylborate (2-APB). Fluo-3 imaging revealed local cytosolic Ca2+ transients with similar kinetics that also were depressed by dantrolene and 2-APB. Massive cellular Ca2+ load or metabolic impairment abolished ΔΨm fluctuations, occasionally evoking heterogeneous mitochondrial depolarizations. The detected diversity and ΔΨm heterogeneity of mitochondria confirms that even in less structurally polarized cells, such as astrocytes, specialized mitochondrial subpopulations coexist. We conclude that ΔΨm fluctuations are an indication of mitochondrial viability and are triggered by local Ca2+ release from the endoplasmic reticulum. This spatially confined organelle crosstalk contributes to the functional heterogeneity of mitochondria and may serve to adapt the metabolism of glial cells to the activity and metabolic demand of complex neuronal networks. The established ratiometric JC-1 imaging—especially combined with two-photon microscopy—enables quantitative functional analyses of individual mitochondria as well as the comparison of mitochondrial heterogeneity in different preparations and/or treatment conditions

Validation and characterisation of a novel peptide that binds monomeric and aggregated beta-amyloid and inhibits the formation of neurotoxic oligomers

Although the formation of β-amyloid (Aβ) deposits in the brain is a hallmark of Alzheimer disease (AD), the soluble oligomers rather than the mature amyloid fibrils most likely contribute to Aβ toxicity and neurodegeneration. Thus, the discovery of agents targeting soluble Aβ oligomers is highly desirable for early diagnosis prior to the manifestation of a clinical AD phenotype and also more effective therapies. We have previously reported that a novel 15-amino acid peptide (15-mer), isolated via phage display screening, targeted Aβ and attenuated its neurotoxicity (Taddei, K., Laws, S. M., Verdile, G., Munns, S., D'Costa, K., Harvey, A. R., Martins, I. J., Hill, F., Levy, E., Shaw, J. E., and Martins, R. N. (2010) Neurobiol. Aging 31, 203–214). The aim of the current study was to generate and biochemically characterize analogues of this peptide with improved stability and therapeutic potential. We demonstrated that a stable analogue of the 15-amino acid peptide (15M S.A.) retained the activity and potency of the parent peptide and demonstrated improved proteolytic resistance in vitro (stable to t = 300 min, c.f. t = 30 min for the parent peptide). This candidate reduced the formation of soluble Aβ42 oligomers, with the concurrent generation of non-toxic, insoluble aggregates measuring up to 25–30 nm diameter as determined by atomic force microscopy. The 15M S.A. candidate directly interacted with oligomeric Aβ42, as shown by coimmunoprecipitation and surface plasmon resonance/Biacore analysis, with an affinity in the low micromolar range. Furthermore, this peptide bound fibrillar Aβ42 and also stained plaques ex vivo in brain tissue from AD model mice. Given its multifaceted ability to target monomeric and aggregated Aβ42 species, this candidate holds promise for novel preclinical AD imaging and therapeutic strategies

Validation of MIPAS ClONO2 measurements

Altitude profiles of ClONO2 retrieved with the IMK (Institut fur Meteorologie und Klimaforschung) science-oriented data processor from MIPAS/Envisat (Michelson Interferometer for Passive Atmospheric Sounding on Envisat) mid-infrared limb emission measurements between July 2002 and March 2004 have been validated by comparison with balloon-borne (Mark IV, FIRS2, MIPAS-B), airborne (MIPAS-STR), ground-based (Spitsbergen, Thule, Kiruna, Harestua, Jungfraujoch, Izana, Wollongong, Lauder), and spaceborne (ACE-FTS) observations. With few exceptions we found very good agreement between these instruments and MIPAS with no evidence for any bias in most cases and altitude regions. For balloon-borne measurements typical absolute mean differences are below 0.05 ppbv over the whole altitude range from 10 to 39 km. In case of ACE-FTS observations mean differences are below 0.03 ppbv for observations below 26 km. Above this altitude the comparison with ACE-FTS is affected by the photochemically induced diurnal variation of ClONO2. Correction for this by use of a chemical transport model led to an overcompensation of the photochemical effect by up to 0.1 ppbv at altitudes of 30-35 km in case of MIPAS-ACE-FTS comparisons while for the balloon-borne observations no such inconsistency has been detected. The comparison of MIPAS derived total column amounts with ground-based observations revealed no significant bias in the MIPAS data. Mean differences between MIPAS and FTIR column abundances are 0.11 +/- 0.12 x 10(14) cm(-2) (1.0 +/- 1.1%) and -0.09 +/- 0.19 x 10(14) cm(-2) (-0.8 +/- 1.7%), depending on the coincidence criterion applied. chi(2) tests have been performed to assess the combined precision estimates of MIPAS and the related instruments. When no exact coincidences were available as in case of MIPAS-FTIR or MIPAS-ACE-FTS comparisons it has been necessary to take into consideration a coincidence error term to account for chi(2) deviations. From the resulting chi(2) profiles there is no evidence for a systematic over/underestimation of the MIPAS random error analysis.Peer reviewe