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Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training

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A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 17723

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Dr. Kurtulus Izzetoglu

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School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
Interests: neuroimaging; biomedical signal processing; functional brain imaging; near-infrared spectroscopy; traumatic brain injury; anesthesia care; human performance; human autonomy teaming; learning and training
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Special Issue Information

Dear Colleagues,

The goal of this Special Issue is to provide studies focusing on neuroimaging and key cognitive areas of interest when attempting to explore the correlation between neurophysiological state, cognitive performance, learning, and skill development. We are soliciting a number of studies whereby wearable physiological and neurophysiological sensors and neuroimaging devices, including but not limited to functional near infrared spectroscopy (fNIRS), electroencephallogram (EEG), functional magnetic resonance imaging (fMRI), eye tracking, and galvanic skin response (GSR), are used to explore and improve the understanding human performance, learning, and training in real-life situations.

Dr. Kurtulus Izzetoglu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Functional brain imaging
fNIRS
fMRI
EEG
Eye tracking
Learning
Training
Cognitive performance
Mental workload

Published Papers (7 papers)

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Research

15 pages, 2013 KiB

Open AccessArticle

EEG-Based Target Detection Using an RSVP Paradigm under Five Levels of Weak Hidden Conditions

by Jinling Lian, Xin Qiao, Yuwei Zhao, Siwei Li, Changyong Wang and Jin Zhou

Brain Sci. 2023, 13(11), 1583; https://doi.org/10.3390/brainsci13111583 - 12 Nov 2023

Viewed by 1283

Abstract

Although target detection based on electroencephalogram (EEG) signals has been extensively investigated recently, EEG-based target detection under weak hidden conditions remains a problem. In this paper, we proposed a rapid serial visual presentation (RSVP) paradigm for target detection corresponding to five levels of weak hidden conditions quantitively based on the RGB color space. Eighteen subjects participated in the experiment, and the neural signatures, including P300 amplitude and latency, were investigated. Detection performance was evaluated under five levels of weak hidden conditions using the linear discrimination analysis and support vector machine classifiers on different channel sets. The experimental results showed that, compared with the benchmark condition, (1) the P300 amplitude significantly decreased (8.92 ± 1.24 μV versus 7.84 ± 1.40 μV, p = 0.021) and latency was significantly prolonged (582.39 ± 25.02 ms versus 643.83 ± 26.16 ms, p = 0.028) only under the weakest hidden condition, and (2) the detection accuracy decreased by less than 2% (75.04 ± 3.24% versus 73.35 ± 3.15%, p = 0.029) with a more than 90% reduction in channel number (62 channels versus 6 channels), determined using the proposed channel selection method under the weakest hidden condition. Our study can provide new insights into target detection under weak hidden conditions based on EEG signals with a rapid serial visual presentation paradigm. In addition, it may expand the application of brain–computer interfaces in EEG-based target detection areas. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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19 pages, 4520 KiB

Open AccessArticle

An Examination of the Effects of Virtual Reality Training on Spatial Visualization and Transfer of Learning

by Kristen Betts, Pratusha Reddy, Tamara Galoyan, Brian Delaney, Donald L. McEachron, Kurtulus Izzetoglu and Patricia A. Shewokis

Brain Sci. 2023, 13(6), 890; https://doi.org/10.3390/brainsci13060890 - 31 May 2023

Cited by 1 | Viewed by 3007

Abstract

Spatial visualization ability (SVA) has been identified as a potential key factor for academic achievement and student retention in Science, Technology, Engineering, and Mathematics (STEM) in higher education, especially for engineering and related disciplines. Prior studies have shown that training using virtual reality (VR) has the potential to enhance learning through the use of more realistic and/or immersive experiences. The aim of this study was to investigate the effect of VR-based training using spatial visualization tasks on participant performance and mental workload using behavioral (i.e., time spent) and functional near infrared spectroscopy (fNIRS) brain-imaging-technology-derived measures. Data were collected from 10 first-year biomedical engineering students, who engaged with a custom-designed spatial visualization gaming application over a six-week training protocol consisting of tasks and procedures that varied in task load and spatial characteristics. Findings revealed significant small (Cohen’s d: 0.10) to large (Cohen’s d: 2.40) effects of task load and changes in the spatial characteristics of the task, such as orientation or position changes, on time spent and oxygenated hemoglobin (HbO) measures from all the prefrontal cortex (PFC) areas. Transfer had a large (d = 1.37) significant effect on time spent and HbO measures from right anterior medial PFC (AMPFC); while training had a moderate (d = 0.48) significant effect on time spent and HbR measures from left AMPFC. The findings from this study have important implications for VR training, research, and instructional design focusing on enhancing the learning, retention, and transfer of spatial skills within and across various VR-based training scenarios. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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15 pages, 2617 KiB

Open AccessArticle

Altered Functional Connectivity Density in Type 2 Diabetes Mellitus with and without Mild Cognitive Impairment

by Dongsheng Zhang, Shasha Liu, Yang Huang, Jie Gao, Weirui Liu, Wanting Liu, Kai Ai, Xiaoyan Lei and Xiaoling Zhang

Brain Sci. 2023, 13(1), 144; https://doi.org/10.3390/brainsci13010144 - 13 Jan 2023

Cited by 2 | Viewed by 1810

Abstract

Although disturbed functional connectivity is known to be a factor influencing cognitive impairment, the neuropathological mechanisms underlying the cognitive impairment caused by type 2 diabetes mellitus (T2DM) remain unclear. To characterize the neural mechanisms underlying T2DM-related brain damage, we explored the altered functional architecture patterns in different cognitive states in T2DM patients. Thirty-seven T2DM patients with normal cognitive function (DMCN), 40 T2DM patients with mild cognitive impairment (MCI) (DMCI), and 40 healthy controls underwent neuropsychological assessments and resting-state functional MRI examinations. Functional connectivity density (FCD) analysis was performed, and the relationship between abnormal FCD and clinical/cognitive variables was assessed. The regions showing abnormal FCD in T2DM patients were mainly located in the temporal lobe and cerebellum, but the abnormal functional architecture was more extensive in DMCI patients. Moreover, in comparison with the DMCN group, DMCI patients showed reduced long-range FCD in the left superior temporal gyrus (STG), which was correlated with the Rey auditory verbal learning test score in all T2DM patients. Thus, DMCI patients show functional architecture abnormalities in more brain regions involved in higher-level cognitive function (executive function and auditory memory function), and the left STG may be involved in the neuropathology of auditory memory in T2DM patients. These findings provide some new insights into understanding the neural mechanisms underlying T2DM-related cognitive impairment. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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14 pages, 2551 KiB

Open AccessArticle

Surface-Based Cortical Measures in Multimodal Association Brain Regions Predict Chess Expertise

by Nicolò Trevisan, Assia Jaillard, Giulia Cattarinussi, Prisca De Roni and Fabio Sambataro

Brain Sci. 2022, 12(11), 1592; https://doi.org/10.3390/brainsci12111592 - 21 Nov 2022

Cited by 3 | Viewed by 1816

Abstract

The complex structure of the brain supports high-order cognition, which is crucial for mastering chess. Surface-based measures, including the fractional dimension (FD) and gyrification index (GI), may be more sensitive in detecting cortical changes relative to volumetric indexes. For this reason, structural magnetic resonance imaging data from 29 chess experts and 29 novice participants were analyzed using the CAT12 toolbox. FD and GI for each brain region were compared between the groups. A multivariate model was used to identify surface-based brain measures that can predict chess expertise. In chess experts, FD is increased in the left frontal operculum (p < 0.01), and this change correlates with the starting age of chess practice (ρ = −0.54, p < 0.01). FD is decreased in the right superior parietal lobule (p < 0.01). Chess expertise is predicted by the FD in a network of fronto-parieto-temporal regions and is associated with GI changes in the middle cingulate gyrus (p < 0.01) and the superior temporal sulcus (p < 0.01). Our findings add to the evidence that chess expertise is based on the complex properties of the brain surface of a network of transmodal association areas important for flexible high-level cognitive functions. Interestingly, these changes are associated with long-lasting practice, suggesting that neuroplastic effects develop over time. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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12 pages, 730 KiB

Open AccessArticle

Intersubject Variability in Cerebrovascular Hemodynamics and Systemic Physiology during a Verbal Fluency Task under Colored Light Exposure: Clustering of Subjects by Unsupervised Machine Learning

by Hamoon Zohdi, Luciano Natale, Felix Scholkmann and Ursula Wolf

Brain Sci. 2022, 12(11), 1449; https://doi.org/10.3390/brainsci12111449 - 27 Oct 2022

Cited by 3 | Viewed by 1568

Abstract

There is large intersubject variability in cerebrovascular hemodynamic and systemic physiological responses induced by a verbal fluency task (VFT) under colored light exposure (CLE). We hypothesized that machine learning would enable us to classify the response patterns and provide new insights into the common response patterns between subjects. In total, 32 healthy subjects (15 men and 17 women, age: 25.5 ± 4.3 years) were exposed to two different light colors (red vs. blue) in a randomized cross-over study design for 9 min while performing a VFT. We used the systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS) approach to measure cerebrovascular hemodynamics and oxygenation at the prefrontal cortex (PFC) and visual cortex (VC) concurrently with systemic physiological parameters. We found that subjects were suitably classified by unsupervised machine learning into different groups according to the changes in the following parameters: end-tidal carbon dioxide, arterial oxygen saturation, skin conductance, oxygenated hemoglobin in the VC, and deoxygenated hemoglobin in the PFC. With hard clustering methods, three and five different groups of subjects were found for the blue and red light exposure, respectively. Our results highlight the fact that humans show specific reactivity types to the CLE-VFT experimental paradigm. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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16 pages, 1165 KiB

Open AccessEditor’s ChoiceArticle

Exploring Gender Differences in the Instructor Presence Effect in Video Lectures: An Eye-Tracking Study

by Yuyang Zhang and Jing Yang

Brain Sci. 2022, 12(7), 946; https://doi.org/10.3390/brainsci12070946 - 19 Jul 2022

Cited by 8 | Viewed by 4483

Abstract

The instructor’s presence on the screen has become a popular feature in the video lectures of online learning and has drawn increasing research interest. Studies on the instructor presence effect of video lectures mainly focused on the features of the instructor, and few have taken learners’ differences, such as gender, into consideration. The current study examined whether male and female learners differed in their learning performance and eye movement features when learning video lectures with and without the instructor’s presence. All participants (N = 64) were asked to watch three different types of video lectures: audio-video without instructor presence (AV), picture-video with instructor presence (PV), and video-video with instructor presence (VV). They watched nine videos, three of each condition, and completed a reading comprehension test after each video. Their eye movement data were simultaneously collected when they watched these videos. Results showed that learners gained better outcomes after watching the videos with a talking instructor (VV) than those with the instructor’s picture (PV) or without the instructor (AV). This finding suggests that the dynamic presence of the instructor in video lectures could enhance learning through increased social presence and agency. Gender differences were found in their attention allocation, but not behavioral learning performance. When watching the videos with a talking instructor (VV), female learners dwelt longer on the instructor, while males transited more between the instructor and the text. Our results highlight the value of instructor presence in video lectures and call for more comprehensive explorations of gender differences in online learning outcomes and attention distribution. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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14 pages, 3518 KiB

Open AccessArticle

Improving Attention through Individualized fNIRS Neurofeedback Training: A Pilot Study

by Yue Gu, Liu Yang, He Chen, Wenzheng Liu and Zhenhu Liang

Brain Sci. 2022, 12(7), 862; https://doi.org/10.3390/brainsci12070862 - 29 Jun 2022

Viewed by 2370

Abstract

Attention is a particularly important indicator in life, as inattention can lead to many negative consequences. As a non-invasive intervention, real-time neurofeedback training can effectively enhance individuals’ attention adjustment abilities. However, previous studies have neglected to consider differences among individuals. In this study, an individualized neurofeedback training (INT) method based on functional near-infrared spectroscopy (fNIRS) was proposed for attention improvement and compared with non-individualized neurofeedback training (NINT). The neurofeedback channels and thresholds were determined individually for each subject. Then, participants conducted four runs of neurofeedback training. Two attention tests (i.e., AX version of continuous performance task (AX-CPT) and attention network test (ANT)) were used to assess the performance of the neurofeedback training. The length of time that the two groups of participants continuously kept their oxygenated hemoglobin concentration above a threshold showed an increasing trend, and the improvement rate of the INT group was higher than that of the NINT group. The reaction times for both groups showed a downward trend, but the INT group declined more significantly. In the fNIRS data, it was observed that the activation degree of the INT group in the middle and dorsolateral prefrontal areas was higher than that of the NINT group. It is preliminarily proved that the proposed INT method can effectively improve the attention level, and its overall performance is better than that of the NINT method. Full article

(This article belongs to the Special Issue Brain Imaging and Cognitive Neuroscience in Human Performance, Learning and Training)

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