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Journal articles on the topic 'Focal attention'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Castiello, Umberto, and Carlo Umiltà. "Splitting focal attention." Journal of Experimental Psychology: Human Perception and Performance 18, no. 3 (1992): 837–48. http://dx.doi.org/10.1037/0096-1523.18.3.837.

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2

Julesz, Bela. "Early vision and focal attention." Reviews of Modern Physics 63, no. 3 (1991): 735–72. http://dx.doi.org/10.1103/revmodphys.63.735.

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3

McElree, Brian. "Working memory and focal attention." Journal of Experimental Psychology: Learning, Memory, and Cognition 27, no. 3 (2001): 817–35. http://dx.doi.org/10.1037/0278-7393.27.3.817.

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4

Nothdurft, Hans-Christoph. "Focal attention in visual search." Vision Research 39, no. 14 (1999): 2305–10. http://dx.doi.org/10.1016/s0042-6989(99)00006-1.

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5

Kabata, Takashi, Takemasa Yokoyama, Yasuki Noguchi, and Shinichi Kita. "Location Probability Learning Requires Focal Attention." Perception 43, no. 4 (2014): 344–50. http://dx.doi.org/10.1068/p7589.

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6

Saarinen, Jukka. "Focal Visual Attention and Pattern Discrimination." Perception 22, no. 5 (1993): 509–15. http://dx.doi.org/10.1068/p220509.

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Pattern discrimination in the presence of distractor patterns is improved when the stimulus display is preceded by a precue designating the location of the target pattern. Experiments were conducted to determine how big an improvement the precue produced. The specific question of whether the observer is able to process selectively the stimulus pattern in the cued location of the display and ignore the patterns of the noncued locations was addressed. In order to study this, reaction time for pattern discrimination on a blank background (no distractors) was compared with the reaction time when the observer performed the same discrimination task in the presence of distractors and a precue had indicated the location of the stimulus pattern to be discriminated. The results showed that these two reaction times were equal if the cue preceded the stimulus patterns at intervals which were longer than some minimum time. Hence, stimuli outside the ‘aperture’ of focal attention can be ignored. These results could not be attributed to eye movements, because the longest duration of the whole sequence of precue and stimulus patterns was only 200 ms.

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7

Block, Ned. "Rich conscious perception outside focal attention." Trends in Cognitive Sciences 18, no. 9 (2014): 445–47. http://dx.doi.org/10.1016/j.tics.2014.05.007.

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8

Renninger, L., and S. Ghahghaei. "Crowding of parafoveal targets without focal attention." Journal of Vision 12, no. 9 (2012): 325. http://dx.doi.org/10.1167/12.9.325.

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9

Mantyla, Timo. "Recollective Experience Following Suppression of Focal Attention." European Journal of Cognitive Psychology 8, no. 2 (1996): 195–204. http://dx.doi.org/10.1080/095414496383158.

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10

Mackeben, Manfred. "Sustained focal attention and peripheral letter recognition." Spatial Vision 12, no. 1 (1999): 51–72. http://dx.doi.org/10.1163/156856899x00030.

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11

Krejtz, Krzysztof, Andrew Duchowski, Izabela Krejtz, Agnieszka Szarkowska, and Agata Kopacz. "Discerning Ambient/Focal Attention with Coefficient K." ACM Transactions on Applied Perception 13, no. 3 (2016): 1–20. http://dx.doi.org/10.1145/2896452.

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12

Richardson, Benjamin N., Barbara Shinn-Cunningham, and Jasmine Kwasa. "Variance of alpha oscillation power corresponds to behavioral performance in spatial auditory attention." Journal of the Acoustical Society of America 151, no. 4 (2022): A259. http://dx.doi.org/10.1121/10.0011256.

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To analyze an acoustic stream from a desired location, the brain focuses spatial selective attention, which causes shifts in parieto-occipital alpha power (∼8i–12 Hz). We explored whether neurotypical (N = 10) and ADHD (N = 36) adults differ in performance and in the time course of alpha in a spatial attention task. Subjects reported the order of syllables presented in spatially separated streams while EEG was recorded. In each trial, subjects either maintained attention on a central “target” stream (focal attention) or reported the content of a possible “interrupter” from the left (broad attention). Previously, we found that performance correlates with individual differences in how strongly listeners suppress, in focal trials, event-related potentials elicited by the interrupter. We hypothesized that oscillatory alpha signatures would differ for focal and broad attention, reflecting top-down control of spatial attention. Instead, we found that higher consistency in alpha oscillations correlated with better behavioral outcomes. Rather than deploying spatial attention differently in focal and broad conditions, good listeners may use the same listening strategy in both, but be better in staying on task (i.e., overall “focus”). We propose that the unpredictable interrupter engages bottom-up attentional pathways that are functionally separate from previously demonstrated spatial attention steering mechanisms.

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13

Unverricht, James, Yusuke Yamani, Sarah Yahoodik, Jing Chen, and William J. Horrey. "Attention maintenance training: Are young drivers getting better or being more strategic?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 1991–95. http://dx.doi.org/10.1177/1071181319631142.

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Young drivers are particularly poor at maintaining attention to the forward roadway where imminent hazards may occur. Existing training programs such as FOrward Concentration and Attention Learning (FOCAL) have been shown to improve young drivers’ attention maintenance performance. The current study examines two competing hypotheses for the effectiveness of FOCAL: 1) Drivers disregard the secondary task to focus on maintaining attention, or 2) FOCAL improves drivers’ multitasking ability on the driving and the secondary tasks. FOCAL- and placebo-trained drivers navigated through four distinct scenarios in a driving simulator. During each scenario, they were asked to perform a secondary task interacting with a mock in-vehicle navigation system. Results showed that FOCAL improved driver attention maintenance performance and, surprisingly, their secondary task performance. These results suggest the possibility that FOCAL in fact increases not only their ability to maintain their attention to the forward roadway but also a drivers’ multitasking performance. Future works should use a variety of in-vehicle tasks with different visual processing demands to determine the generalizability of the current finding.

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14

Wang, Zhiguo, and Raymond M. Klein. "Focal spatial attention can eliminate inhibition of return." Psychonomic Bulletin & Review 19, no. 3 (2012): 462–69. http://dx.doi.org/10.3758/s13423-012-0226-x.

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15

Kubovy, Michael, Dale J. Cohen, and Jeff Hollier. "Feature integration that routinely occurs without focal attention." Psychonomic Bulletin & Review 6, no. 2 (1999): 183–203. http://dx.doi.org/10.3758/bf03212326.

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16

Liang, Junwei, Lu Jiang, Liangliang Cao, Yannis Kalantidis, Li-Jia Li, and Alexander G. Hauptmann. "Focal Visual-Text Attention for Memex Question Answering." IEEE Transactions on Pattern Analysis and Machine Intelligence 41, no. 8 (2019): 1893–908. http://dx.doi.org/10.1109/tpami.2018.2890628.

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17

Latimer, Cyril. "Binary oppositions and what focuses in focal attention." Behavioral and Brain Sciences 22, no. 3 (1999): 383–84. http://dx.doi.org/10.1017/s0140525x99412026.

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Pylyshyn makes a convincing case that early visual processing is cognitively impenetrable, and although I question the utility of binary oppositions such as penetrable/impenetrable, for the most part I am in agreement. The author does not provide explicit designations or denotations for the terms penetrable and impenetrable, which appear quite arbitrary. Furthermore, the use of focal attention smacks of an homunculus, and the account appears to slip too easily between the perceptual, the cognitive, and the neurophysiological.

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18

Harvey, Alistair J. "When alcohol narrows the field of focal attention." Quarterly Journal of Experimental Psychology 69, no. 4 (2016): 669–77. http://dx.doi.org/10.1080/17470218.2015.1040803.

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19

Julesz, Bela. "Consciousness and focal attention: Answer to John Searle." Behavioral and Brain Sciences 16, no. 1 (1993): 191–93. http://dx.doi.org/10.1017/s0140525x00029605.

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20

Solomon, J. "Pre-cues alleviate supercrowding without attracting focal attention." Journal of Vision 13, no. 9 (2013): 632. http://dx.doi.org/10.1167/13.9.632.

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21

Nakayama, Ken, and Manfred Mackeben. "Sustained and transient components of focal visual attention." Vision Research 29, no. 11 (1989): 1631–47. http://dx.doi.org/10.1016/0042-6989(89)90144-2.

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22

Wu, Chien-Te, Melissa E. Libertus, Karen L. Meyerhoff, and Marty G. Woldorff. "The Temporal Dynamics of Object Processing in Visual Cortex during the Transition from Distributed to Focused Spatial Attention." Journal of Cognitive Neuroscience 23, no. 12 (2011): 4094–105. http://dx.doi.org/10.1162/jocn_a_00045.

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Several major cognitive neuroscience models have posited that focal spatial attention is required to integrate different features of an object to form a coherent perception of it within a complex visual scene. Although many behavioral studies have supported this view, some have suggested that complex perceptual discrimination can be performed even with substantially reduced focal spatial attention, calling into question the complexity of object representation that can be achieved without focused spatial attention. In the present study, we took a cognitive neuroscience approach to this problem by recording cognition-related brain activity both to help resolve the questions about the role of focal spatial attention in object categorization processes and to investigate the underlying neural mechanisms, focusing particularly on the temporal cascade of these attentional and perceptual processes in visual cortex. More specifically, we recorded electrical brain activity in humans engaged in a specially designed cued visual search paradigm to probe the object-related visual processing before and during the transition from distributed to focal spatial attention. The onset times of the color popout cueing information, indicating where within an object array the subject was to shift attention, was parametrically varied relative to the presentation of the array (i.e., either occurring simultaneously or being delayed by 50 or 100 msec). The electrophysiological results demonstrate that some levels of object-specific representation can be formed in parallel for multiple items across the visual field under spatially distributed attention, before focal spatial attention is allocated to any of them. The object discrimination process appears to be subsequently amplified as soon as focal spatial attention is directed to a specific location and object. This set of novel neurophysiological findings thus provides important new insights on fundamental issues that have been long-debated in cognitive neuroscience concerning both object-related processing and the role of attention.

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23

Shimojo, Shinsuke. "Attention—Dependent Visual Capture in Double Vision." Perception 16, no. 4 (1987): 445–47. http://dx.doi.org/10.1068/p160445.

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When the visual image of a body part, such as a finger, is doubled by a prism, the ‘felt’ position of that body part is captured by one of its visual images. Moving eye fixation from one to the other visual image is accompanied by a quick shift of the felt position. When focal attention is dissociated from foveation, the former determines visual capture. These new observations underline an active role of focal attention in intersensory integration and sensory—motor coordination of body parts.

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24

OKUMURA, Yasuko, Tetsuko KASAI, and Harumitsu MUROHASHI. "Representational Levels of Bilateral N170 for Japanese Hiragana Strings during Focal Spatial Attention to Letters." Japanese Journal of Physiological Psychology and Psychophysiology 33, no. 1 (2015): 5–17. http://dx.doi.org/10.5674/jjppp.1503si.

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25

McElree, Brian, and Barbara Anne Dosher. "The focus of attention across space and across time." Behavioral and Brain Sciences 24, no. 1 (2001): 129–30. http://dx.doi.org/10.1017/s0140525x01373922.

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Measures of retrieval speed for recently presented events show a sharp dichotomy between representations in focal attention and representations that are recently processed but no longer attended. When information is presented over time, retrieval measures show that focal attention and rapid privileged access is limited to the most recently processed unit or chunk, not the last 3–5 chunks that Cowan estimates from various recall procedures.

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26

MAX, JEFFREY E., DONALD A. ROBIN, H. GERRY TAYLOR, et al. "Attention function after childhood stroke." Journal of the International Neuropsychological Society 10, no. 7 (2004): 976–86. http://dx.doi.org/10.1017/s1355617704107066.

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We investigated attentional outcome after childhood stroke and orthopedic diagnosis in medical controls. Twenty-nine children with focal stroke lesions and individually matched children with clubfoot or scoliosis were studied with standardized attention and neuroimaging assessments. Stroke lesions were quite varied in location and commonly involved regions implicated in Posner's model of attention networks. Children with stroke lesions performed significantly more poorly regarding attention function compared with controls. Performance on the Starry Night, a test demanding alerting and sensory-orienting but not executive attention function, was significantly associated with lesion size in the alerting and sensory-orienting networks but not the executive attention network. Furthermore, earlier age at lesion acquisition was significantly associated with poorer attention function even when lesion size was controlled. These findings support the theory of dissociable networks of attention and add to evidence from studies of children with diffuse and focal brain damage that early insults are associated with worse long-term outcomes in many domains of neuropsychological function. In addition, these results may provide clues towards the understanding of mechanisms underlying attention in children. (JINS, 2004,10, 976–986.)

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27

Vidnyánszky, Z. "Modulation of backward pattern masking by focal visual attention." Acta Biologica Hungarica 53, no. 1-2 (2002): 221–27. http://dx.doi.org/10.1556/abiol.53.2002.1-2.20.

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28

Theeuwes, Jan, Erik Van der Burg, and Artem Belopolsky. "Detecting the presence of a singleton involves focal attention." Psychonomic Bulletin & Review 15, no. 3 (2008): 555–60. http://dx.doi.org/10.3758/pbr.15.3.555.

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29

Yap, Jit Yong, and Stephen Wee Hun Lim. "Media multitasking predicts unitary versus splitting visual focal attention." Journal of Cognitive Psychology 25, no. 7 (2013): 889–902. http://dx.doi.org/10.1080/20445911.2013.835315.

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30

Julesz, B. "Early Vision Is Bottom-up, Except for Focal Attention." Cold Spring Harbor Symposia on Quantitative Biology 55 (January 1, 1990): 973–78. http://dx.doi.org/10.1101/sqb.1990.055.01.091.

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31

Ventura, Caterina, Martine Grice, Michelina Savino, Diana Kolev, Ingmar Brilmayer, and Petra B. Schumacher. "Attention allocation in a language with post-focal prominences." NeuroReport 31, no. 8 (2020): 624–28. http://dx.doi.org/10.1097/wnr.0000000000001453.

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32

Hopf, Jens-Max, Toemme Noesselt, Claus Tempelmann, Jochen Braun, Mircea Ariel Schoenfeld, and Hans-Jochen Heinze. "Popout modulates focal attention in the primary visual cortex." NeuroImage 22, no. 2 (2004): 574–82. http://dx.doi.org/10.1016/j.neuroimage.2004.01.031.

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33

Motter, Brad C., and Eric J. Belky. "The zone of focal attention during active visual search." Vision Research 38, no. 7 (1998): 1007–22. http://dx.doi.org/10.1016/s0042-6989(97)00252-6.

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34

Reddy, Leila, Lavanya Reddy, and Christof Koch. "Face identification in the near-absence of focal attention." Vision Research 46, no. 15 (2006): 2336–43. http://dx.doi.org/10.1016/j.visres.2006.01.020.

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35

Li, Dongdong, Gongjian Wen, Yangliu Kuai, Lingxiao Zhu, and Fatih Porikli. "Robust visual tracking with channel attention and focal loss." Neurocomputing 401 (August 2020): 295–307. http://dx.doi.org/10.1016/j.neucom.2019.10.041.

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36

Pinto, Y., I. Sligte, and V. Lamme. "Working memory requires focal attention, fragile VSTM does not." Journal of Vision 13, no. 9 (2013): 459. http://dx.doi.org/10.1167/13.9.459.

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37

Wykowska, Agnieszka, and Anna Schubö. "On the Temporal Relation of Top–Down and Bottom–Up Mechanisms during Guidance of Attention." Journal of Cognitive Neuroscience 22, no. 4 (2010): 640–54. http://dx.doi.org/10.1162/jocn.2009.21222.

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Two mechanisms are said to be responsible for guiding focal attention in visual selection: bottom–up, saliency-driven capture and top–down control. These mechanisms were examined with a paradigm that combined a visual search task with postdisplay probe detection. Two SOAs between the search display and probe onsets were introduced to investigate how attention was allocated to particular items at different points in time. The dynamic interplay between bottom–up and top–down mechanisms was investigated with ERP methodology. ERPs locked to the search displays showed that top–down control needed time to develop. N2pc indicated allocation of attention to the target item and not to the irrelevant singleton. ERPs locked to probes revealed modulations in the P1 component reflecting top–down control of focal attention at the long SOA. Early bottom–up effects were observed in the error rates at the short SOA. Taken together, the present results show that the top–down mechanism takes time to guide focal attention to the relevant target item and that it is potent enough to limit bottom–up attentional capture.

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38

Daini, Roberta, Silvia Primativo, Andrea Albonico, et al. "The Focal Attention Window Size Explains Letter Substitution Errors in Reading." Brain Sciences 11, no. 2 (2021): 247. http://dx.doi.org/10.3390/brainsci11020247.

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Acquired Neglect Dyslexia is often associated with right-hemisphere brain damage and is mainly characterized by omissions and substitutions in reading single words. Martelli et al. proposed in 2011 that these two types of error are due to different mechanisms. Omissions should depend on neglect plus an oculomotor deficit, whilst substitutions on the difficulty with which the letters are perceptually segregated from each other (i.e., crowding phenomenon). In this study, we hypothesized that a deficit of focal attention could determine a pathological crowding effect, leading to imprecise letter identification and consequently substitution errors. In Experiment 1, three brain-damaged patients, suffering from peripheral dyslexia, mainly characterized by substitutions, underwent an assessment of error distribution in reading pseudowords and a T detection task as a function of cue size and timing, in order to measure focal attention. Each patient, when compared to a control group, showed a deficit in adjusting the attentional focus. In Experiment 2, a group of 17 right-brain-damaged patients were asked to perform the focal attention task and to read single words and pseudowords as a function of inter-letter spacing. The results allowed us to confirm a more general association between substitution-type reading errors and the performance in the focal attention task.

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39

Eriksen, Charles W., and James D. St. James. "Visual attention within and around the field of focal attention: A zoom lens model." Perception & Psychophysics 40, no. 4 (1986): 225–40. http://dx.doi.org/10.3758/bf03211502.

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40

Hicks, Jason L., Gabriel I. Cook, and Richard L. Marsh. "Detecting Event-Based Prospective Memory Cues Occurring within and outside the Focus of Attention." American Journal of Psychology 118, no. 1 (2005): 1–12. http://dx.doi.org/10.2307/30039040.

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Abstract Event-based prospective memory cues are environmental stimuli that are associated with a previously established intention to perform an activity. Such cues traditionally have been placed in materials that receive focal attention during an ongoing activity. This article reports a direct comparison of event-based cues that occurred either within the focus of attention or at the periphery of such attention. When the cue occurred outside focal attention, manipulating that cue changed event-based prospective memory. The identical manipulation had no effect on event-based responding if the cue occurred within focal attention. These results suggest that cue characteristics can compensate for attention being directed away from an aspect of an ongoing task that contains event-based prospective memory cues.

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41

Yeh, Su-Ling, and I.-Ping Chen. "Is early visual processing attention impenetrable?" Behavioral and Brain Sciences 22, no. 3 (1999): 400. http://dx.doi.org/10.1017/s0140525x99602023.

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Pylyshyn's effort in establishing the cognitive impenetrability of early vision is welcome. However, his view about the role of attention in early vision seems to be oversimplified. The allocation of focal attention manifests its effect among multiple stages in the early vision system, it is not just confined to the input and the output levels.

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42

Zheng, Hong-Ying, Gang Peng, Jian-Yong Chen, Caicai Zhang, James W. Minett, and William S.-Y. Wang. "The Influence of Tone Inventory on ERP without Focal Attention: A Cross-Language Study." Computational and Mathematical Methods in Medicine 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/961563.

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This study investigates the effect of tone inventories on brain activities underlying pitch without focal attention. We find that the electrophysiological responses to across-category stimuli are larger than those to within-category stimuli when the pitch contours are superimposed on nonspeech stimuli; however, there is no electrophysiological response difference associated with category status in speech stimuli. Moreover, this category effect in nonspeech stimuli is stronger for Cantonese speakers. Results of previous and present studies lead us to conclude that brain activities to the same native lexical tone contrasts are modulated by speakers’ language experiences not only in active phonological processing but also in automatic feature detection without focal attention. In contrast to the condition with focal attention, where phonological processing is stronger for speech stimuli, the feature detection (pitch contours in this study) without focal attention as shaped by language background is superior in relatively regular stimuli, that is, the nonspeech stimuli. The results suggest that Cantonese listeners outperform Mandarin listeners in automatic detection of pitch features because of the denser Cantonese tone system.

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43

Rerko, Laura, Alessandra S. Souza, and Klaus Oberauer. "Retro-cue benefits in working memory without sustained focal attention." Memory & Cognition 42, no. 5 (2014): 712–28. http://dx.doi.org/10.3758/s13421-013-0392-8.

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44

Worthington, A. "Focal and global visual attention in left visuo-spatial neglect." Neurocase 2, no. 5 (1996): 441a—447. http://dx.doi.org/10.1093/neucas/2.5.441-a.

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45

Worthington, A., and Y. Young. "Focal and global visual attention in left visuo-spatial neglect." Neurocase 2, no. 5 (1996): 441–47. http://dx.doi.org/10.1080/13554799608402418.

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46

SAKAI, K., and Y. MIYASHITA. "Visual imagery: an interaction between memory retrieval and focal attention." Trends in Neurosciences 17, no. 7 (1994): 287–89. http://dx.doi.org/10.1016/0166-2236(94)90058-2.

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47

Primativo, Silvia, Sebastian Crutch, Ivanna Pavisic, Keir Yong, Alessia Rossetti, and Roberta Daini. "Impaired mechanism of visual focal attention in posterior cortical atrophy." Neuropsychology 34, no. 7 (2020): 799–810. http://dx.doi.org/10.1037/neu0000697.

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48

Hikosaka, Okihide, Satoru Miyauchi, and Shinsuke Shimojo. "Focal visual attention produces illusory temporal order and motion sensation." Vision Research 33, no. 9 (1993): 1219–40. http://dx.doi.org/10.1016/0042-6989(93)90210-n.

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49

Rehman, Aasia, Muheet A. Butt, and Majid Zaman. "Attention Res-UNet." International Journal of Decision Support System Technology 15, no. 1 (2023): 1–17. http://dx.doi.org/10.4018/ijdsst.315756.

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During a dermoscopy examination, accurate and automatic skin lesion detection and segmentation can assist medical experts in resecting problematic areas and decrease the risk of deaths due to skin cancer. In order to develop fully automated deep learning model for skin lesion segmentation, the authors design a model Attention Res-UNet by incorporating residual connections, squeeze and excite units, atrous spatial pyramid pooling, and attention gates in basic UNet architecture. This model uses focal tversky loss function to achieve better trade off among recall and precision when training on smaller size lesions while improving the overall outcome of the proposed model. The results of experiments have demonstrated that this design, when evaluated on publicly available ISIC 2018 skin lesion segmentation dataset, outperforms the existing standard methods with a Dice score of 89.14% and IoU of 81.16%; and achieves better trade off among precision and recall. The authors have also performed statistical test of this model with other standard methods and evaluated that this model is statistically significant.

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50

Dong, Changxu, Yanna Zhao, Gaobo Zhang, et al. "Attention-based Graph ResNet with focal loss for epileptic seizure detection." Journal of Ambient Intelligence and Smart Environments 14, no. 1 (2022): 61–73. http://dx.doi.org/10.3233/ais-210086.

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Epilepsy is a chronic brain disease resulted from the central nervous system lesion, which leads to repeated seizure occurs for the patients. Automatic seizure detection with Electroencephalogram (EEG) has witnessed great progress. However, existing methods paid little attention to the topological relationships of different EEG electrodes. Latest neuroscience researches have demonstrated the connectivity between different brain regions. Besides, class-imbalance is a common problem in EEG based seizure detection. The duration of epileptic EEG signals is much shorter than that of normal signals. In order to deal with the above mentioned two challenges, we propose to model the multi-channel EEG data using the Attention-based Graph ResNet (AGRN). In particular, each channel of the EEG signal represents a node of the graph and the inter-channel relations are modeled via the adjacency matrix in the graph. The loss function of the ARGN model is re-designed using focal loss to cope with the class-imbalance problem. The proposed ARGN with focal model could learn discriminative features from the raw EEG data. Experiments are carried out on the CHB-MIT dataset. The proposed model achieves an average accuracy of 98.70%, a sensitivity of 97.94%, a specificity of 98.66% and a precision of 98.62%. The Area Under the ROC Curve (AUC) is 98.69%.

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