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Journal articles on the topic 'Low attention'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Mäki-Marttunen, Verónica, Natasha Pickard, Anne-Kristin Solbakk, Keith H. Ogawa, Robert T. Knight, and Kaisa M. Hartikainen. "Low attentional engagement makes attention network activity susceptible to emotional interference." NeuroReport 25, no. 13 (September 2014): 1038–43. http://dx.doi.org/10.1097/wnr.0000000000000223.

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2

Guarnera, Maria, and Antonella D’Amico. "Training of Attention in Children With Low Arithmetical Achievement." Europe’s Journal of Psychology 10, no. 2 (May 28, 2014): 277–90. http://dx.doi.org/10.5964/ejop.v10i2.744.

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This study focuses on the role of attentional processes in arithmetical skills and examines if training of basic attentive skills may improve also working memory abilities reducing arithmetic difficulties. In order to study the efficacy of attentional treatment in arithmetic achievement and in enhancing working memory abilities a test-treatment-retest quasi experimental design was adopted. The research involved 14 children, attending fourth and fifth grades, with Arithmetical Learning Disabilities (ALD) assigned to experimental and control conditions. The numerical comprehension and calculation processes were assessed using the ABCA battery (Lucangeli, Tressoldi, & Fiore, 1998). Attentional abilities were evaluated using a multitask computerized assessment battery Attenzione e Concentrazione (Di Nuovo, 2000). WM abilities were evaluated by Listening span task, Digit span backward, Making verbal trails and Making colour trails. The results showed that intensive computerized attention training increased basic attentive skills and arithmetical performances with respect to numeric system in children with ALD. No effect on working memory abilities was found. Results are also important from a clinical perspective, since they may suggest strategies for planning individualized training programs.

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3

Millichap, J. Gordon. "Low Birth Weight and Attention Deficit Disorder." Pediatric Neurology Briefs 21, no. 3 (March 1, 2007): 21. http://dx.doi.org/10.15844/pedneurbriefs-21-3-8.

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4

Gasparini, Francesca. "Low-quality image enhancement using visual attention." Optical Engineering 46, no. 4 (April 1, 2007): 040502. http://dx.doi.org/10.1117/1.2721764.

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5

Bach Jensen, Morten, and Anna Lund Jepsen. "Low attention advertising processing in B2B markets." Journal of Business & Industrial Marketing 22, no. 5 (August 7, 2007): 342–48. http://dx.doi.org/10.1108/08858620710773477.

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6

Yang, Howard, Peng Sun, Charles Chubb, and George Sperling. "Complex Attention Filters for Low Contrast Items." Journal of Vision 16, no. 12 (September 1, 2016): 681. http://dx.doi.org/10.1167/16.12.681.

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7

Du, Wenchao, Hu Chen, Peixi Liao, Hongyu Yang, Ge Wang, and Yi Zhang. "Visual Attention Network for Low-Dose CT." IEEE Signal Processing Letters 26, no. 8 (August 2019): 1152–56. http://dx.doi.org/10.1109/lsp.2019.2922851.

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8

Santoso, Irene, Malcolm J. Wright, Giang Trinh, and Mark Avis. "Mind the attention gap: how does digital advertising impact choice under low attention?" European Journal of Marketing 56, no. 2 (December 31, 2021): 442–66. http://dx.doi.org/10.1108/ejm-01-2021-0031.

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Purpose This study aims to investigate whether digital advertising can be effective despite consumer inattention and how certain common combinations of ad characteristics increase or decrease ad effectiveness under conditions of low attention. Design/methodology/approach Using two online experiments in naturalistic environment, the authors compare ad effects under focussed, divided and incidental attention, for certain ad characteristics, namely, appeal type and (mis)matching between appeal and brand type. The results are analysed using logistic regression. Findings Ad exposure under low attention does increase brand consideration and choice. The greatest uplift in impact occurs when moving from non-exposure to incidental attention. Under incidental attention, emotive advertising was more effective than rational advertising, as was matching rather than mismatching an emotional appeal to a hedonic brand. Conversely, under divided attention, rational advertising and mismatching a rational appeal to a hedonic brand were more effective. Research limitations/implications This research explores the effectiveness of Twitter ads with an emotional or a rational appeal and the (mis)matching between appeal and utilitarian or hedonic brand type. Future research can examine other formats and creative elements of digital advertising that can affect the low-attention processing and the effects that occur. Practical implications Intrusive, attention-getting advertising strategies may not be necessary. Certain common creative devices can increase advertising effectiveness despite low attention, so marketers can ensure consumer-centric marketing communication. Originality/value There has previously been limited understanding of low-attention mechanisms in advertising and little evidence of ad effectiveness under conditions of low attention. The research also demonstrates that certain ad characteristics, linked to common creative devices, enhance the impact of advertising despite low attention.

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9

Sokhadze, E. M., B. Hillard, M. Eng, A. S. El-Baz, A. Tasman, and L. Sears. "ELECTROENCEPHALOGRAPHIC BIOFEEDBACK IMPROVES FOCUSED ATTENTION IN ATTENTION DEFICIT/HYPERACTIVITY DISORDER." Bulletin of Siberian Medicine 12, no. 2 (April 28, 2013): 182–94. http://dx.doi.org/10.20538/1682-0363-2013-2-182-194.

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EEG biofeedback (so called neurofeedback) is considered as an efficacious treatment for ADHD. We propose that operant conditioning of EEG in neurofeedback training mode, aimed to mitigate inattention and low arousal in ADHD, will be accompanied by changes in EEG bands' relative power. Patients were 18 children diagnosed with ADHD. The neurofeedback protocol (“Focus/Alertness” by Peak Achievement Trainer, Neurotek, KY) used to train patients has focused attention training procedure, which according to specifications, represents wide band EEG amplitude suppression training. Quantitative EEG analysis was completed on each of 25 min long twelve sessions to determine the relative power of each of the EEG bands of interest throughout each session, and from the first session to the last session. Additional statistical analysis was performed to determine significant changes in relative power within sessions (from minute 1 to minute 25), and between sessions (from session 1 to session 12) for an individual patient. We performed analysis of relative power of Theta, Alpha, Low and High Beta, Theta/Alpha, Theta/Beta, and Theta/Low Beta and Theta/High Beta ratios. We performed also analysis between the “Focus”measure and changes in relative power of above EEG rhythms and their ratios. Additional secondary measures of patients’ post-neurofeedback outcomes were assessed using an audio-visual selective attention test (IVA + Plus) and behavioral evaluation scores from Aberrant Behavior Checklist. We found that, as expected, Theta/Low Beta and Theta/Alpha ratios decreased significantly from Session 1 to Session 12 and from minute 1 to minute 25 within sessions. The ‘Focus” measure of protocol showed high negative correlation with both Theta/Alpha and Theta/Beta ratios. The findings regarding EEG changes resulting from self-regulation training along with behavioral evaluations will help in elucidation of neural mechanisms of neurofeedback aimed to improve focused attention and alertness in ADHD.

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10

Scheel, Jennifer F., Karin Schielke, Stefan Lautenbacher, Sabine Aust, Simone Kremer, and Jörg Wolstein. "Low-Dose Alcohol Effects on Attention in Adolescents." Zeitschrift für Neuropsychologie 24, no. 2 (January 2013): 103–11. http://dx.doi.org/10.1024/1016-264x/a000094.

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Objective: Relatively little is known about the effects of low-dose alcohol effects on attentional performance in adolescents. In the present study, we examined these effects compared to those in adults. Method: 44 healthy subjects (21 adolescents and 23 adults) received either an alcoholic cocktail (average blood alcohol concentration: 0.054 %) or a placebo drink (randomized placebo-controlled). Before and after consuming the drink, participants completed tests on Alertness, Working Memory, Flexibility and Divided Attention. Results: Significant effects were found for the subtest Flexibility, which showed less improvement in the adolescents with alcohol compared to the non-alcohol condition and adults. Furthermore, an age-independent alcohol-induced impairment of the subtest Working Memory was observed. Conclusions: These findings point to a particular vulnerability for alcohol effects in adolescents regarding cognitive flexibility.

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11

Lee, Joonyeol, and John H. R. Maunsell. "The Effect of Attention on Neuronal Responses to High and Low Contrast Stimuli." Journal of Neurophysiology 104, no. 2 (August 2010): 960–71. http://dx.doi.org/10.1152/jn.01019.2009.

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It remains unclear how attention affects the tuning of individual neurons in visual cerebral cortex. Some observations suggest that attention preferentially enhances responses to low contrast stimuli, whereas others suggest that attention proportionally affects responses to all stimuli. Resolving how attention affects responses to different stimuli is essential for understanding the mechanism by which it acts. To explore the effects of attention on stimuli of different contrasts, we recorded from individual neurons in the middle temporal visual area (MT) of rhesus monkeys while shifting their attention between preferred and nonpreferred stimuli within their receptive fields. This configuration results in robust attentional modulation that makes it possible to readily distinguish whether attention acts preferentially on low contrast stimuli. We found no evidence for greater enhancement of low contrast stimuli. Instead, the strong attentional modulations were well explained by a model in which attention proportionally enhances responses to stimuli of all contrasts. These data, together with observations on the effects of attention on responses to other stimulus dimensions, suggest that the primary effect of attention in visual cortex may be to simply increase the strength of responses to all stimuli by the same proportion.

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12

Jaworski, Jessica L. Bean, and Inge-Marie Eigsti. "Low-level visual attention and its relation to joint attention in autism spectrum disorder." Child Neuropsychology 23, no. 3 (November 15, 2015): 316–31. http://dx.doi.org/10.1080/09297049.2015.1104293.

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13

Martin, Jean-Rémy, Jérôme Sackur, and Zoltan Dienes. "Attention or instruction: Do sustained attentional abilities really differ between high and low hypnotisable persons?" Psychological Research 82, no. 4 (March 7, 2017): 700–707. http://dx.doi.org/10.1007/s00426-017-0850-1.

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14

Yap, David, Samantha Denefrio, and Tracy A. Dennis-Tiwary. "Low working memory load facilitates attention bias modification training." Behaviour Research and Therapy 139 (April 2021): 103828. http://dx.doi.org/10.1016/j.brat.2021.103828.

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15

Lu, Bibo, Zebang Pang, Yanan Gu, and Yanmei Zheng. "Channel splitting attention network for low‐light image enhancement." IET Image Processing 16, no. 5 (January 17, 2022): 1403–14. http://dx.doi.org/10.1049/ipr2.12418.

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16

Liang, Xiwen, Xiaoning Yan, Nenghua Xu, Xiaoyan Chen, and Hao Feng. "Low light enhancement CNN Network based on attention mechanism." Proceedings of International Conference on Artificial Life and Robotics 27 (January 20, 2022): 466–69. http://dx.doi.org/10.5954/icarob.2022.os11-2.

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17

Vaish, Rajan, Peter Organisciak, Kotaro Hara, Jeffrey Bigham, and Haoqi Zhang. "Low Effort Crowdsourcing: Leveraging Peripheral Attention for Crowd Work." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 62–63. http://dx.doi.org/10.1609/hcomp.v2i1.13191.

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Crowdsourcing systems leverage short bursts of focused attention from many contributors to achieve a goal. By requiring people’s full attention, existing crowdsourcing systems fail to leverage people’s cognitive surplus in the many settings for which they may be distracted, performing or waiting to perform another task, or barely paying attention. In this paper, we study opportunities for low-effort crowdsourcing that enable people to contribute to problem solving in such settings. We discuss the design space for low-effort crowdsourcing, and through a series of prototypes, demonstrate interaction techniques, mechanisms, and emerging principles for enabling low-effort crowdsourcing.

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18

Verkerk, G., B. Houtzager, M. JeukensVisser, A. v. WassenaerLeemhuis, K. Koldewijn, F. Nollet, and J. Kok. "325 Attention Problems in Very Low Birth Weight Preschoolers." Archives of Disease in Childhood 97, Suppl 2 (October 1, 2012): A95. http://dx.doi.org/10.1136/archdischild-2012-302724.0325.

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19

Bisserbe, J. C., E. De Rosa, J. P. Mialet, P. Boyer, and J. P. Boulenger. "VISUAL ATTENTION IN LOW AND HIGH ANXIETY TRAIT SUBJECTS." Clinical Neuropharmacology 15 (1992): 571B. http://dx.doi.org/10.1097/00002826-199202001-01113.

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20

Mitchell, J., K. Sundberg, and J. Reynolds. "Attention reduces low frequency correlated noise in macaque V4." Journal of Vision 9, no. 8 (September 3, 2010): 93. http://dx.doi.org/10.1167/9.8.93.

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21

FIMM, B., K. WILLMES, and W. SPIJKERS. "The effect of low arousal on visuo-spatial attention." Neuropsychologia 44, no. 8 (2006): 1261–68. http://dx.doi.org/10.1016/j.neuropsychologia.2006.01.027.

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22

Santoso, Irene, Malcolm Wright, Giang Trinh, and Mark Avis. "Is digital advertising effective under conditions of low attention?" Journal of Marketing Management 36, no. 17-18 (August 19, 2020): 1707–30. http://dx.doi.org/10.1080/0267257x.2020.1801801.

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23

Grimes, Anthony. "Towards an integrated model of low attention advertising effects." European Journal of Marketing 42, no. 1/2 (February 15, 2008): 69–86. http://dx.doi.org/10.1108/03090560810840916.

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24

van der Meere, Jaap, Norbert A. Börger, Stephanus Theron Potgieter, Silja Pirila, and Paul De Cock. "Very Low Birth Weight and Attention Deficit/Hyperactivity Disorder." Child Neuropsychology 15, no. 6 (October 28, 2009): 605–18. http://dx.doi.org/10.1080/09297040902984482.

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25

Amado Diago, Carlos A., and José A. Amado Señaris. "Should we pay more attention to low creatinine levels?" Endocrinología, Diabetes y Nutrición (English ed.) 67, no. 7 (August 2020): 486–92. http://dx.doi.org/10.1016/j.endien.2020.09.003.

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26

Kelly, Charlotte, and Juan Guevara Pinto. "Biasing Global and Local Attention During Low Prevalence Search." Journal of Vision 22, no. 14 (December 5, 2022): 3221. http://dx.doi.org/10.1167/jov.22.14.3221.

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27

Luo, Yu, Jiarong Zhou, Wei Bao, Jing Qiu, Jingqing Nian, and Yu Zhang. "Working memory content guides attention." Journal of Pacific Rim Psychology 15 (January 2021): 183449092110347. http://dx.doi.org/10.1177/18344909211034752.

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Previous studies showed that working memory (WM) content can guide attention; however, whether working memory capacity (WMC) and state anxiety could affect this remains unclear. This study aimed to examine the effect of WMC and state anxiety on attention guided by WM content. Participants with high and low WMC were assigned to either a neutral or an anxiety condition. They were asked to perform a modified change detection task with irrelevant singletons while their event-related potentials were recorded. N2pc and Pd were observed in the low-WMC and anxiety group, and Pd was observed in both the high-WMC and anxiety and the high-WMC and control groups, whereas neither N2pc nor Pd was found in the low-WMC and control group. These findings suggest that attention is guided or suppressed by WM content, depending on the WMC and anxiety level of the individual. This study provides a new perspective on WM content-guided attention.

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28

Shin, Sungho, Joosoon Lee, Junseok Lee, Seungjun Choi, and Kyoobin Lee. "Low-Resolution Image Classification Using Knowledge Distillation From High-Resolution Image Via Self-Attention Map." Journal of KIISE 47, no. 11 (November 30, 2020): 1027–31. http://dx.doi.org/10.5626/jok.2020.47.11.1027.

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29

Lv, Feifan, Yu Li, and Feng Lu. "Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset." International Journal of Computer Vision 129, no. 7 (May 7, 2021): 2175–93. http://dx.doi.org/10.1007/s11263-021-01466-8.

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30

Yang, Yadong, Xiaofeng Wang, Quan Zhao, and Tingting Sui. "Two-Level Attentions and Grouping Attention Convolutional Network for Fine-Grained Image Classification." Applied Sciences 9, no. 9 (May 11, 2019): 1939. http://dx.doi.org/10.3390/app9091939.

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The focus of fine-grained image classification tasks is to ignore interference information and grasp local features. This challenge is what the visual attention mechanism excels at. Firstly, we have constructed a two-level attention convolutional network, which characterizes the object-level attention and the pixel-level attention. Then, we combine the two kinds of attention through a second-order response transform algorithm. Furthermore, we propose a clustering-based grouping attention model, which implies the part-level attention. The grouping attention method is to stretch all the semantic features, in a deeper convolution layer of the network, into vectors. These vectors are clustered by a vector dot product, and each category represents a special semantic. The grouping attention algorithm implements the functions of group convolution and feature clustering, which can greatly reduce the network parameters and improve the recognition rate and interpretability of the network. Finally, the low-level visual features and high-level semantic information are merged by a multi-level feature fusion method to accurately classify fine-grained images. We have achieved good results without using pre-training networks and fine-tuning techniques.

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31

Bahri, Toufik. "Covert Orienting of Attention Controls Vigilance Decrement at Low Event Rate." Perceptual and Motor Skills 79, no. 1 (August 1994): 83–92. http://dx.doi.org/10.2466/pms.1994.79.1.83.

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Factors controlling sustained visual orienting were investigated by combining the paradigms of covert orienting and vigilance. Analysis suggests a close relationship between orienting of attention and vigilance which is dependent on the event rare during the vigilance task. At a low event rate both facilitatory and inhibitory effects of orienting are found. Vigilance decrement is related to the accumulation of inhibition over time, supporting Posner, et al.'s 1984 theory. Invalid cues reduce the decrement. At a high event rate, however, neither facilitation nor inhibition effects are reliable, and vigilance decrement is relared to limitations of the allocation of attentional capacity, supporting Parasuraman's multifactorial theory. The results suggest that facilitation and inhibition caused by orienting are important opposing mechanisms in visual attention, allowing the nervous system to control the distribution of attention both over visual space and over time.

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32

Horrigan, Joseph P., and L. Jarrett Barnhill. "Low-Dose Amphetamine Salts and Adult Attention-Deficit/Hyperactivity Disorder." Journal of Clinical Psychiatry 61, no. 6 (June 15, 2000): 414–17. http://dx.doi.org/10.4088/jcp.v61n0604.

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33

Elovic, Elie. "Pharmacology of attention and arousal in the low level patient." NeuroRehabilitation 6, no. 1 (February 1, 1996): 57–67. http://dx.doi.org/10.3233/nre-1996-6107.

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34

Heath, Robert. "Emotional Engagement: How Television Builds Big Brands At Low Attention." Journal of Advertising Research 49, no. 1 (March 2009): 62–73. http://dx.doi.org/10.2501/s0021849909090060.

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35

Landi, Federico, Lorenzo Baraldi, Marcella Cornia, Massimiliano Corsini, and Rita Cucchiara. "Multimodal attention networks for low-level vision-and-language navigation." Computer Vision and Image Understanding 210 (September 2021): 103255. http://dx.doi.org/10.1016/j.cviu.2021.103255.

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36

Hsu, Yi-Fang, Álvaro Darriba, and Florian Waszak. "Attention modulates repetition effects in a context of low periodicity." Brain Research 1767 (September 2021): 147559. http://dx.doi.org/10.1016/j.brainres.2021.147559.

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37

Wang, Renjun, Bin Jiang, Chao Yang, Qiao Li, and Bolin Zhang. "MAGAN: Unsupervised low-light image enhancement guided by mixed-attention." Big Data Mining and Analytics 5, no. 2 (June 2022): 110–19. http://dx.doi.org/10.26599/bdma.2021.9020020.

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38

Leat, Susan J., and Jan E. Lovie-Kitchin. "Visual Function, Visual Attention, and Mobility Performance in Low Vision." Optometry and Vision Science 85, no. 11 (November 2008): 1049–56. http://dx.doi.org/10.1097/opx.0b013e31818b949d.

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39

MICK, ERIC, JOSEPH BIEDERMAN, JEFFERSON PRINCE, MARIANNA J. FISCHER, and STEPHEN V. FARAONE. "Impact of Low Birth Weight on Attention-Deficit Hyperactivity Disorder." Journal of Developmental & Behavioral Pediatrics 23, no. 1 (February 2002): 16–22. http://dx.doi.org/10.1097/00004703-200202000-00004.

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40

Lueck, Amanda Hall. "Book Review: Selected Attention in Low Acuity Vision: An exploration." Journal of Visual Impairment & Blindness 95, no. 7 (July 2001): 437–40. http://dx.doi.org/10.1177/0145482x0109500706.

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41

Guo, Qipeng, Xipeng Qiu, Xiangyang Xue, and Zheng Zhang. "Low-Rank and Locality Constrained Self-Attention for Sequence Modeling." IEEE/ACM Transactions on Audio, Speech, and Language Processing 27, no. 12 (December 2019): 2213–22. http://dx.doi.org/10.1109/taslp.2019.2944078.

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42

HEATH, ROBERT, and AGNES NAIRN. "Measuring Affective Advertising: Implications of Low Attention Processing on Recall." Journal of Advertising Research 45, no. 02 (December 29, 2005): 269. http://dx.doi.org/10.1017/s0021849905050282.

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43

Tinelli, Francesca, Giovanni Anobile, Monica Gori, David Aagten-Murphy, Mariaelisa Bartoli, David C. Burr, Giovanni Cioni, and Maria Concetta Morrone. "Time, number and attention in very low birth weight children." Neuropsychologia 73 (July 2015): 60–69. http://dx.doi.org/10.1016/j.neuropsychologia.2015.04.016.

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44

Zhu, Xiaobin, Zhuangzi Li, Xianbo Li, Shanshan Li, and Feng Dai. "Attention-aware perceptual enhancement nets for low-resolution image classification." Information Sciences 515 (April 2020): 233–47. http://dx.doi.org/10.1016/j.ins.2019.12.013.

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45

Elovic, E. "Pharmacology of attention and arousal in the low level patient." Neurorehabilitation 6, no. 1 (February 1996): 57–67. http://dx.doi.org/10.1016/1053-8135(95)00148-4.

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46

Choi, Darwin, Zhenyu Gao, and Wenxi Jiang. "Attention to Global Warming." Review of Financial Studies 33, no. 3 (February 14, 2020): 1112–45. http://dx.doi.org/10.1093/rfs/hhz086.

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Abstract We find that people revise their beliefs about climate change upward when experiencing warmer than usual temperatures in their area. Using international data, we show that attention to climate change, as proxied by Google search volume, increases when the local temperature is abnormally high. In financial markets, stocks of carbon-intensive firms underperform firms with low carbon emissions in abnormally warm weather. Retail investors (not institutional investors) sell carbon-intensive firms in such weather, and return patterns are unlikely to be driven by changes in fundamentals. Our study sheds light on peoples’ collective beliefs and actions about global warming.

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47

Mock, Vanessa L., Kimberly L. Luke, Jacqueline R. Hembrook-Short, and Farran Briggs. "Phase shifts in high-beta- and low-gamma-band local field potentials predict the focus of visual spatial attention." Journal of Neurophysiology 121, no. 3 (March 1, 2019): 799–822. http://dx.doi.org/10.1152/jn.00469.2018.

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The local field potential (LFP) contains rich information about activity in local neuronal populations. However, it has been challenging to establish direct links between LFP modulations and task-relevant behavior or cognitive processes, such as attention. We sought to determine whether LFP amplitude or phase modulations are predictive of the allocation of visual spatial attention. LFPs were recorded simultaneously in multiple early visual brain structures of alert macaque monkeys performing attention-demanding detection and discrimination tasks. Attention directed toward the receptive field of recorded neurons generated systematically larger phase shifts in high-beta- and low-gamma-frequency LFPs compared with LFP phase shifts on trials in which attention was directed away from the receptive field. This attention-mediated temporal advance corresponded to ~10 ms. LFP phase shifts also correlated with reaction times when monkeys were engaged in the tasks. Importantly, attentional modulation of LFP phase was consistent across monkeys, tasks, visual brain structures, and cortical layers. In contrast, attentional modulation of LFP amplitude varied across frequency bands, visual structures/layers, and tasks. Because LFP phase shifts were robust, consistent, and predictive of spatial attention, they could serve as a reliable marker for attention signals in the brain. NEW & NOTEWORTHY Local field potentials (LFPs) reflect the activity of spatially localized populations of neurons. Whether alterations in LFP activity are indicative of cognitive processes, such as attention, is unclear. We found that shifts in the phase of LFPs measured in multiple visual brain areas reliably predicted the focus of spatial attention. LFP phase shifts could therefore serve as a marker for behaviorally relevant attention signals in the brain.

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48

Serrano-Barroso, Almudena, Roma Siugzdaite, Jaime Guerrero-Cubero, Alberto J. Molina-Cantero, Isabel M. Gomez-Gonzalez, Juan Carlos Lopez, and Juan Pedro Vargas. "Detecting Attention Levels in ADHD Children with a Video Game and the Measurement of Brain Activity with a Single-Channel BCI Headset." Sensors 21, no. 9 (May 6, 2021): 3221. http://dx.doi.org/10.3390/s21093221.

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Attentional biomarkers in attention deficit hyperactivity disorder are difficult to detect using only behavioural testing. We explored whether attention measured by a low-cost EEG system might be helpful to detect a possible disorder at its earliest stages. The GokEvolution application was designed to train attention and to provide a measure to identify attentional problems in children early on. Attention changes registered with NeuroSky MindWave in combination with the CARAS-R psychological test were used to characterise the attentional profiles of 52 non-ADHD and 23 ADHD children aged 7 to 12 years old. The analyses revealed that the GokEvolution was valuable in measuring attention through its use of EEG–BCI technology. The ADHD group showed lower levels of attention and more variability in brain attentional responses when compared to the control group. The application was able to map the low attention profiles of the ADHD group when compared to the control group and could distinguish between participants who completed the task and those who did not. Therefore, this system could potentially be used in clinical settings as a screening tool for early detection of attentional traits in order to prevent their development.

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49

Rahnev, Dobromir A., Linda Bahdo, Floris P. de Lange, and Hakwan Lau. "Prestimulus hemodynamic activity in dorsal attention network is negatively associated with decision confidence in visual perception." Journal of Neurophysiology 108, no. 5 (September 1, 2012): 1529–36. http://dx.doi.org/10.1152/jn.00184.2012.

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Attention is thought to improve most aspects of perception. However, we recently showed that, somewhat surprisingly, endogenous attention can also lead to low subjective perceptual ratings ( Rahnev et al., 2011 ). Here we investigated the neural basis of this effect and tested whether spontaneous fluctuations of the attentional state can lead to low confidence in one's perceptual decision. We measured prestimulus functional magnetic resonance imaging activity in the dorsal attention network and used that activity as an index of the level of attention involved in a motion direction discrimination task. Extending our previous findings, we showed that low prestimulus activity in the dorsal attention network, which presumably reflected low level of attention, was associated with higher confidence ratings. These results were explained by a signal detection theoretic model in which lack of attention increases the trial-by-trial variability of the internal perceptual response. In line with the model, we also found that low prestimulus activity in the dorsal attention network was associated with higher trial-by-trial variability of poststimulus peak activity in the motion-sensitive region MT+. These findings support the notion that lack of attention may lead to liberal subjective perceptual biases, a phenomenon we call “inattentional inflation of subjective perception.”

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Pekala, Ronald J., and V. K. Kumar. "Phenomenological Variations in Attention across Low, Medium, and High Susceptible Subjects." Imagination, Cognition and Personality 7, no. 4 (June 1988): 303–14. http://dx.doi.org/10.2190/ea8c-h3yy-81v4-vu8g.

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Phenomenological aspects of attention were assessed across 434 subjects in reference to baseline conditions of eyes-open or closed sitting quietly and an hypnotic induction condition. An attention questionnaire, assessing twelve dimensions of attention, was constructed and subjects completed it retrospectively in reference to the baseline condition and hypnosis. Reliability analyses indicated acceptable reliability for most dimensions. Regression and correlational analyses suggested adequate validity. Comparisons between baseline and hypnosis indicated significant phenomenological intensity differences between stimulus conditions on many attention dimensions. Comparisons among low, medium, and high susceptibles in reference to baseline and hypnosis also yielded many significant intensity differences. In addition, significant interactions between conditions and groups for many of the attention dimensions suggest that hypnosis, in comparison to the baseline conditions, potentiated intensity differences in attention for high, vis-a-vis low (and medium), susceptible subjects.

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