Insects Neural Model: Potential Alternate to Mammals for Electrophysiological Studies

Author(s):  
Julie Gaburro ◽  
Saeid Nahavandi ◽  
Asim Bhatti
Author(s):  
Fabrice B. R. Parmentier ◽  
Pilar Andrés

The presentation of auditory oddball stimuli (novels) among otherwise repeated sounds (standards) triggers a well-identified chain of electrophysiological responses: The detection of acoustic change (mismatch negativity), the involuntary orientation of attention to (P3a) and its reorientation from the novel. Behaviorally, novels reduce performance in an unrelated visual task (novelty distraction). Past studies of the cross-modal capture of attention by acoustic novelty have typically discarded from their analysis the data from the standard trials immediately following a novel, despite some evidence in mono-modal oddball tasks of distraction extending beyond the presentation of deviants/novels (postnovelty distraction). The present study measured novelty and postnovelty distraction and examined the hypothesis that both types of distraction may be underpinned by common frontally-related processes by comparing young and older adults. Our data establish that novels delayed responses not only on the current trial and but also on the subsequent standard trial. Both of these effects increased with age. We argue that both types of distraction relate to the reconfiguration of task-sets and discuss this contention in relation to recent electrophysiological studies.


1974 ◽  
Vol 35 (C5) ◽  
pp. C5-7-C5-7
Author(s):  
J. P. JEUKENNE ◽  
A. LEJEUNE ◽  
C. MAHAUX

2014 ◽  
Vol 1 ◽  
pp. 739-742
Author(s):  
Tetsuya Shimokawa ◽  
Kenji Leibnitz ◽  
Ferdinand Peper

Author(s):  
A. Syahputra

Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.


2019 ◽  
Author(s):  
Scott D. Blain ◽  
Rachael Grazioplene ◽  
Yizhou Ma ◽  
Colin G. DeYoung

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance, were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.


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