scholarly journals How Does Approaching a Lead Vehicle and Monitoring Request Affect Drivers’ Takeover Performance? A Simulated Driving Study with Functional MRI

2021 ◽  
Vol 19 (1) ◽  
pp. 412
Author(s):  
Chimou Li ◽  
Xiaonan Li ◽  
Ming Lv ◽  
Feng Chen ◽  
Xiaoxiang Ma ◽  
...  
Keyword(s):  
Distance Perception ◽  
Lateral Displacement ◽  
Reaction Times ◽  
Memory Search ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Automated Driving ◽  
Cognitive Behaviors ◽  
Visual Reaction ◽  
Middle Occipital Gyrus

With the popularization and application of conditionally automated driving systems, takeover requirements are becoming more and more frequent, and the subsequent takeover safety problems have attracted attention. The present study used functional magnetic resonance imaging (fMRI) technology, combined with driving simulation experiments, to study in depth the effects of critical degree and monitor request (MR) 30 s in advance on drivers’ visual behavior, takeover performance and brain activation. Results showed that MR can effectively improve the driver’s visual and takeover performance, including visual reaction times, fixation frequency and duration, takeover time, and takeover mode. The length of the reserved safety distance can significantly affect the distribution of longitudinal acceleration. Critical or non-critical takeover has a significant impact on the change of pupil diameter and the standard deviation of lateral displacement. Five brain regions, including the middle occipital gyrus (MOG), fusiform gyrus (FG), middle temporal gyrus (MTG), precuneus and precentral, are activated under the stimulation of a critical takeover scenario, and are related to cognitive behaviors such as visual cognition, distance perception, memory search and movement association.

Common and distinct neural mechanisms of visual and tactile extinction: A large scale VBM study in sub-acute stroke

2012 ◽  
Vol 25 (0) ◽  
pp. 17
Author(s):  
Magdalena Chechlacz ◽  
Anna Terry ◽  
Pia Rotshtein ◽  
Wai-Ling Bickerton ◽  
Glyn Humphreys
Keyword(s):  
Large Scale ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Middle Temporal Gyrus ◽  
Visual Modality ◽  
Voxel Based Morphometry ◽  
White Matter Damage ◽  
Sensory Modalities ◽  
Middle Occipital Gyrus

Extinction is diagnosed when patients respond to a single contralesional item but fail to detect this item when an ipsilesional item is present concurrently. It is considered to be a disorder of attention characterized by a striking bias for the ipsilesional stimulus at the expense of the contralesional stimulus. Extinction has been studied mainly in the visual modality but it occurs also in other sensory modalities (touch, audition) and hence can be considered a multisensory phenomenon. The functional and neuroanatomical relations between extinction in different modalities are poorly understood. It could be hypothesised that extinction deficits in different modalities emerge after damage to both common (attention specific) and distinct (modality specific) brain regions. Here, we used voxel-based morphometry to examine the neuronal substrates of visual versus tactile extinction in a large group of stroke patients (). We found that extinction deficits in the two modalities were significantly correlated (; ). Lesions to inferior parietal lobule and middle frontal gyrus were linked to visual extinction, while lesions involving the superior temporal gyrus were associated with tactile extinction. Damage within the middle temporal gyrus was linked to both types of deficits but interestingly these lesions extended into the middle occipital gyrus in patients with visual but not tactile extinction. White matter damage within the temporal lobe was associated with both types of deficits, including lesions within long association pathways involved in spatial attention. Our findings indicate both common and distinct neural mechanisms of visual and tactile extinction.

scholarly journals To Go or Not to Go: Exploring brain activation during response inhibition reading tasks

Spectrum ◽  
2019 ◽  
Author(s):  
Julia Craig ◽  
Amberley V. Ostevik ◽  
Lindsey Westover ◽  
Bill Hodgetts ◽  
Jacqueline Cummine
Keyword(s):  
Decision Making ◽  
Response Inhibition ◽  
Inferior Frontal Gyrus ◽  
Objective Response ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Middle Temporal Gyrus ◽  
Maximal Response ◽  
Decision Making Processes ◽  
Middle Occipital Gyrus

Objective: Response inhibition is an understudied component of reading that aids in the selection of appropriate responses amidst complicated tasks. Our objective was to explore the contribution of brain regions associated with response inhibition processing in reading tasks that vary in difficulty of response inhibition. Method: Participants (N = 15) completed two go/no-go reading tasks while in a functional magnetic resonance imaging (fMRI) scanner, with the instructions to “name aloud the letter strings that spell a real word.” For the minimal response inhibition condition, the foils, which are stimuli that should not be repsonded to, were nonwords with unfamiliar spelling and sound (e.g., “bink”). For the maximal response inhibition condition, the foils were pseudohomophones with unfamiliar spelling but familiar sound (e.g., “pynt”). The following brain regions associated with decision-making processes were analyzed: the anterior cingulate cortex (ACC), the dorsomedial prefrontal cortex (DMPFC), the inferior frontal gyrus (IFG), the middle temporal gyrus (MTG), the middle occipital gyrus (MOG), and the posterior insula (PI). Results: Significant differences in activation within the nonword task were found for the DMPFC and the PI (the ACC approached significance). Significant differences in activation within the pseudohomophone task were found for the ACC, the MTG, and the PI. The IFG was found to be greatly activated for all words that had familiar phonemes (sounds). The MOG was found to be activated across all tasks. Conclusion: We provide evidence for differential response inhibition processing in the decision-making network during reading tasks. This work is a necessary step in better understanding response inhibition ability for individuals with and without reading impairments.

scholarly journals Watching the brain as it binds: Beta synchronization relates to distractor-response binding

2020 ◽  
Author(s):  
Bernhard Pastötter ◽  
Birte Moeller ◽  
Christian Frings
Keyword(s):  
Reaction Times ◽  
Human Action ◽  
Brain Regions ◽  
Correlation Effect ◽  
Stimulus Onset ◽  
Event File ◽  
Stimulus Interval ◽  
Stimulus Response ◽  
Event Files ◽  
Middle Occipital Gyrus

Human action control relies on event files, i.e., short-term stimulus-response bindings that result from the integration of perception and action. The present electroencephalography (EEG) study examined oscillatory brain activities related to the integration and disintegration of event files in the distractor-response binding (DRB) task, which relies on a sequential prime-probe structure with orthogonal variation of distractor and response relations between prime and probe. Behavioral results indicated a DRB effect in reaction times (RT), which was moderated by the duration of the response-stimulus interval (RSI) between prime response and probe stimulus onset. Indeed, a DRB effect was observed for a short RSI of 500 ms but not for a longer RSI of 2000 ms, indicating disintegration of event files over time. EEG results revealed a positive correlation between individual DRB in the RSI-2000 condition and post-movement beta synchronization after both prime and probe responses. Beamformer analysis localized this correlation effect to the middle occipital gyrus, which also showed highest coherency with precentral and inferior parietal brain regions. Together, these findings suggest that post-movement beta synchronization is a marker of event-file disintegration, with the left middle occipital gyrus being a hub region for stimulus-response bindings in the present visual DRB task.

Face and Word Recognition in Patients with Left and Right Hemispheric Lesions: Evidence from Reaction Times and ERPs

2002 ◽  
Vol 13 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Stefan R. Schweinberger ◽  
Thomas Klos ◽  
Werner Sommer
Keyword(s):  
Slow Wave ◽  
Reaction Times ◽  
Memory Search ◽  
Event Related Potentials ◽  
Performance Deficits ◽  
Set Size ◽  
Left Brain ◽  
Related Potentials ◽  
Abstract Words ◽  
Left Brain Damage

Abstract: We recorded reaction times (RTs) and event-related potentials (ERPs) in patients with unilateral lesions during a memory search task. Participants memorized faces or abstract words, which were then recognized among new ones. The RT deficit found in patients with left brain damage (LBD) for words increased with memory set size, suggesting that their problem relates to memory search. In contrast, the RT deficit found in patients with RBD for faces was apparently related to perceptual encoding, a conclusion also supported by their reduced P100 ERP component. A late slow wave (720-1720 ms) was enhanced in patients, particularly to words in patients with LBD, and to faces in patients with RBD. Thus, the slow wave was largest in the conditions with most pronounced performance deficits, suggesting that it reflects deficit-related resource recruitment.

Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

2021 ◽  
pp. 1-29
Author(s):  
Kangyu Jin ◽  
Zhe Shen ◽  
Guoxun Feng ◽  
Zhiyong Zhao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Resting State ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

scholarly journals Supervision of a self-driving vehicle unmasks latent sleepiness relative to manually controlled driving

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Erin E. Flynn-Evans ◽  
Lily R. Wong ◽  
Yukiyo Kuriyagawa ◽  
Nikhil Gowda ◽  
Patrick F. Cravalho ◽  
...  
Keyword(s):  
Human Error ◽  
Reaction Times ◽  
Modern Society ◽  
Accident Risk ◽  
Road Accidents ◽  
Automated Driving ◽  
High Prevalence ◽  
Driving Task ◽  
Sleep Deficiency ◽  
Monitoring Performance

AbstractHuman error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had more involuntary transitions to sleep, had slower reaction times and more attentional failures, and showed substantial modifications in brain synchronization during and following an autonomous drive compared to a manually controlled drive. Our findings suggest that the introduction of partial self-driving capabilities in vehicles has the potential to paradoxically increase accident risk.

scholarly journals IN VIVO ASSESSMENT OF AMYLOID AND GLUCOSE SIGNATURES IN SUBJECTIVE COGNITIVE DECLINE SUBJECTS

2021 ◽  
pp. 2140018
Author(s):  
XIAOFENG YU ◽  
ZHILONG ZHU ◽  
SHUZHAN ZHENG ◽  
JIAN JIANG ◽  
JUANJUAN JIANG ◽  
...  
Keyword(s):  
Cognitive Decline ◽  
Characteristic Curve ◽  
Standardized Uptake Value ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Subjective Cognitive Decline ◽  
Middle Temporal ◽  
Main Effect ◽  
Heschl Gyrus

Subjective cognitive decline (SCD), characterized by self-perceived subtle cognitive impairment ahead of the appearance of explicit and measurable cognitive deficits, is regarded as the preclinical manifestation of the pathological change continuum of Alzheimer’s disease (AD). We were committed to exploring the amyloid and glucose metabolic signatures related to imminent brain metabolic changes in SCD subjects. This study included 39 subjects (mean age = 71.9 years; 14 males and 25 females) diagnosed with SCD disease and 39 gender-matched healthy controls (HCs) (mean age = 75.2; 16 males and 23 females) with brain [18F] fluorodeoxyglucose positron emission tomography (PET) images and [18F] florbetapir PET images. The standardized uptake value ratios (SUVRs) of PET images within the regions of interest (ROIs) were calculated. Inter-group SUVR differences were assessed by two-sample [Formula: see text]-testing and receiver operating characteristic curve (ROC) analyses. A generalized linear model (GLM) was employed to evaluate the correlations between amyloid and FDG uptake. Compared with HCs, SCD subjects showed significantly increased amyloid SUVR, as well as significantly increased glucose SUVR in the olfactory, amygdala, thalamus, heschl gyrus, superior and middle temporal gyrus and temporal pole (all [Formula: see text]). The amyloid SUVR of thalamus was found to have a better ROC result (area under the curve (AUC): 0.77, 95% confidence interval (CI): 0.66–0.86) in the HC group, as was the case with the glucose SUVR of the middle temporal gyrus (AUC: 0.83, 95% CI: 0.73–0.91). There were significant positive correlations between amyloid and glucose SUVRs ([Formula: see text]). The amyloid SUVR of the thalamus showed a significantly better main effect (odd ratio [Formula: see text] 2.91, 95% CI: 1.44–6.7, [Formula: see text]), and the glucose SUVR of the heschl gyrus indicated an enhanced main effect (odd ratio [Formula: see text] 5.08, 95% CI: 1.86–18.15, [Formula: see text]). SCD subjects demonstrated significant amyloid accumulation and glucose hypermetabolism in specific brain regions, and amyloid pathology overlapped with regions of glucose abnormality. These findings may advance the understanding of imminent pathological changes in the SCD stage and help to provide clinical guidelines for interventional management.

scholarly journals A Machine Learning Approach to Unmask Novel Gene Signatures and Prediction of Alzheimer’s Disease Within Different Brain Regions

2021 ◽  
Author(s):  
Abhibhav Sharma ◽  
Pinki Dey
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Non Coding Rna ◽  
Machine Learning Approach ◽  
Microarray Datasets ◽  
Rna Genes

AbstractAlzheimer’s disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unrevealed the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.

scholarly journals Brain Activation of College Students in China With Premenstrual Syndrome Localized by BOLD-fMRI

2021 ◽  
Author(s):  
Dongmei Gao ◽  
Mingzhou Gao ◽  
Li An ◽  
Yanhong Yu ◽  
Jieqiong Wang ◽  
...  
Keyword(s):  
College Students ◽  
Premenstrual Syndrome ◽  
Brain Area ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Anterior Lobe ◽  
Middle Temporal Gyrus ◽  
Cerebellar Tonsil ◽  
Bold Fmri ◽  
Significant Difference

Abstract Background: Most studies on the mechanism behind premenstrual syndrome (PMS) have focused on fluctuating hormones, but little evidence exists regarding functional abnormalities in the affected brain regions of college students. Thus, the aim of this study is to localize PMS's abnormal brain regions by BOLD-fMRI in college students.Methods: Thirteen PMS patients and fifteen healthy control (HC) subjects underwent a BOLD-fMRI scan during the luteal phase induced by depressive emotion pictures. The BOLD-fMRI data were processed by SPM 8 software and rest software based on MATLAB platform. Each cluster volume threshold (cluster) was greater than 389 continuous voxels, and the brain area with single voxel threshold P < 0.05 (after correction) was defined as the area with a significant difference. The emotion report form and the instruction implementation checklist were used to evaluate the emotion induced by picture.Results: Compared to the HC, right inferior occipital gyrus, right middle occipital gyrus, right lingual gyrus, right fusiform gyrus, right inferior temporal gyrus, cerebelum_crus1_R，cerebelum_6_R, culmen, the cerebellum anterior lobe, tuber, cerebellar tonsil of PMS patients were enhanced activation. Sub-lobar，sub-gyral，extra-nuclear，right orbit part of superior frontal gyrus, right middle temporal gyrus, right Orbit part of inferior frontal gyrus, limbic lobe, right insula, bilateral anterior and adjacent cingulate gyrus, bilateral caudate, caudate head, bilateral putamen, left globus pallidus were decreased activation.Conclusion: Our findings may improve our understanding of the neural mechanisms involved in PMS.

Sequential visual reaction times

1988 ◽  
Vol 8 (1) ◽  
pp. 63-66
Author(s):  
J.M. Artigas ◽  
A. Felipe ◽  
F.W. Campbell
Keyword(s):  
Reaction Times ◽  
Visual Reaction
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