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Journal articles on the topic 'Imagery'

To see the other types of publications on this topic, follow the link: Imagery.

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Hishitani, Shinsuke, and Shiho Murakami. "What is Vividness of Imagery? Characteristics of Vivid Visual Imagery." Perceptual and Motor Skills 75, no. 3_suppl (December 1992): 1291–307. http://dx.doi.org/10.2466/pms.1992.75.3f.1291.

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Two experiments were conducted to examine the characteristics of vivid visual imagery. In Exps. 1 and 2, analysis showed that the subjects' drawings of their imagery indicated more visual features for the vivid imagers than for the non-vivid imagers and no difference in sketching time between the two groups. Image-construction time was shorter for the vivid imagers than for the non-vivid ones in Exp. 2, but no difference was found in Exp. 1. On the basis of these results, the mechanism underlying individual differences in vividness of imagery was discussed in relation to the model of imagery processes proposed by Kosslyn (1980) and his colleagues.

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2

Campos, Alfredo. "Vividness of Imagery and Positive and Negative Values of Emotionality of Words." Perceptual and Motor Skills 67, no. 2 (October 1988): 433–34. http://dx.doi.org/10.2466/pms.1988.67.2.433.

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We estimated the correlations of scores on vividness of imagery of 122 undergraduates using Marks's imagery questionnaire with positive and negative emotionality values of words. We also studied the influence of imagery vividness (good and poor imagers) in emotionality. Analysis indicates a significant correlation for the 52 men and for the total group between imagery vividness and emotionality. The good imagers gave higher emotionality scores than poor imagers.

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3

Livesey, D. J., and M. Kangas. "The Role of Visual Movement Imagery in Kinaesthetic Sensitivity and Motor Performance." Australian Educational and Developmental Psychologist 14, no. 1 (May 1997): 2–10. http://dx.doi.org/10.1017/s0816512200027607.

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ABSTRACTThe relationship between vividness of visual movement imagery and performance on tests of kinaesthetic sensitivity was examined in high school students by comparing performance on three tests of kinaesthesis by high and low imagery students, selected using the Vividness of Movement Imagery Questionnaire. High imagers performed significantly better than low imagers when relying on kinaesthetic information. Level of movement imagery predicted performance on a motor task (a manual placement task) when the task was performed in the absence of visual cues (blindfolded). These results reflect the reliance on visual information when performing motor tasks and indicate that, in the absence of visual cues, such information is created from kinaesthetic input via visual imagery. This has important implications for our understanding of the development of kinaesthesis and motor control and may contribute to the development of remedial programmes for children with poor motor ability.

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4

Williams, Sarah E., Jennifer Cumming, Nikos Ntoumanis, Sanna M. Nordin-Bates, Richard Ramsey, and Craig Hall. "Further Validation and Development of the Movement Imagery Questionnaire." Journal of Sport and Exercise Psychology 34, no. 5 (October 2012): 621–46. http://dx.doi.org/10.1123/jsep.34.5.621.

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This research validated and extended the Movement Imagery Questionnaire-Revised (MIQ-R; Hall & Martin, 1997). Study 1 (N = 400) examined the MIQ-R’s factor structure via multitrait-multimethod confirmatory factor analysis. The questionnaire was then modified in Study 2 (N = 370) to separately assess the ease of imaging external visual imagery and internal visual imagery, as well as kinesthetic imagery (termed the Movement Imagery Questionnaire-3; MIQ-3). Both Studies 1 and 2 found that a correlated-traits correlated-uniqueness model provided the best fit to the data, while displaying gender invariance and no significant differences in latent mean scores across gender. Study 3 (N = 97) demonstrated the MIQ-3’s predictive validity revealing the relationships between imagery ability and observational learning use. Findings highlight the method effects that occur by assessing each type of imagery ability using the same four movements and demonstrate that better imagers report greater use of observational learning.

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5

Maesaroh, Wahyudin, and Mitha Erlisya Puspandhani. "Pengaruh Relaksasi Gu Ided Imagery Terhadap Body Image Pada Pasien Stroke Di Wilayah Kerja Puskesmas Klangenan Kabupaten Cirebon." Jurnal Health Sains 1, no. 2 (August 26, 2020): 52–60. http://dx.doi.org/10.46799/jhs.v1i2.21.

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Stroke adalah suatu gangguan dimana penderita mengalami keterbatasan dalam menjalankan aktifitas sehari-hari sehingga mengakibatkan body image yang negatif, Untuk meningkatkan body image yang negatif dapat dilakukan salah satunya dengan relaksasi guided imagery. Penelitian ini bertujuan untuk mengetahui pengaruh relaksasi guided imagery terhadap body image pada pasien stroke di wilayah kerja puskesmas klangenan kabupaten Cirebon. Desain penelitian ini menggunakan quasi experimental dengan rancangan one grup pre test-post test design. Teknik pengambilan sampel dalam penelitian menggunakan purposive sampling dengan jumlah sampel 23 responden. Uji statistik yang digunakan dalam penelitian ini adalah uji paired t-test dengan α 0,05 (5%). Hasil dari penelitian ini didapatkan bahwa body image pasien stroke sebelum diberikan relaksasi guided imageri sebagian besar dengan kategori negatif yaitu 20 orang (87%), Body image setelah dilakukan relaksasi guided imageri sebagian besar dengan kategori negatif yaitu 12 orang (52,2%). dan ada pengaruh relaksasi guided imagery terhadap body image pada pasien adalah (p=0,000) . Kesimpulan dari penelitian ini ada pengaruh secara signifikan relaksasi guided imagery terhadap body image pada pasien stroke di Wilayah Kerja Puskesmas Klangenan Kabupaten Cirebon. Saran peneliti, relaksasi guided imageri dapat dijadikan tindakan keperawatan nonfarmakologis untuk meningkatkan body image pada pasien strokesecara mandiri.

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6

Hillger, Donald. "Synthetic advanced baseline imager true-color imagery." Journal of Applied Remote Sensing 5, no. 1 (January 1, 2011): 053520. http://dx.doi.org/10.1117/1.3576112.

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Gothard, Andrew, Daniel Jones, Andre Green, Michael Torrez, Alessandro Cattaneo, and David Mascareñas. "Digital coded exposure formation of frames from event-based imagery." Neuromorphic Computing and Engineering 2, no. 1 (January 28, 2022): 014005. http://dx.doi.org/10.1088/2634-4386/ac4917.

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Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

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8

Corlett, John T., John Anton, Steve Kozub, and Michel Tardif. "Is Locomotor Distance Estimation Guided by Visual Imagery?" Perceptual and Motor Skills 69, no. 3_suppl (December 1989): 1267–72. http://dx.doi.org/10.2466/pms.1989.69.3f.1267.

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70 subjects were tested for their visual subscale scores on the Movement Imagery Questionnaire and also for their ability to walk, without vision, to a previously viewed target location 9 m away. Imagery ability was hypothesized to correlate with accuracy of “blind” target-directed walking which the literature suggests, without empirical support, is imagery-dependent. No support for this hypothesis was found. Low, medium, and high imagers showed no differences in ability to reproduce target distance accurately or consistently by walking the estimated distance without further visual updating. The results call into question whether task performance is imagery-based or whether subjects use alternative strategies to approach the target.

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Corlett, John T., John Anton, Steve Kozub, and Michel Tardif. "Is Locomotor Distance Estimation Guided by Visual Imagery?" Perceptual and Motor Skills 69, no. 3-2 (December 1989): 1267–72. http://dx.doi.org/10.1177/00315125890693-237.

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70 subjects were tested for their visual subscale scores on the Movement Imagery Questionnaire and also for their ability to walk, without vision, to a previously viewed target location 9 m away. Imagery ability was hypothesized to correlate with accuracy of “blind” target-directed walking which the literature suggests, without empirical support, is imagery-dependent. No support for this hypothesis was found. Low, medium, and high imagers showed no differences in ability to reproduce target distance accurately or consistently by walking the estimated distance without further visual updating. The results call into question whether task performance is imagery-based or whether subjects use alternative strategies to approach the target.

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10

Banks, Martin S. "Display Imagery vs . Real Imagery." Information Display 33, no. 1 (January 2017): 4. http://dx.doi.org/10.1002/j.2637-496x.2017.tb00961.x.

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Campos, Alfredo, and María José Pérez. "High and Low Imagers and Their Scores on Creativity." Perceptual and Motor Skills 68, no. 2 (April 1989): 403–6. http://dx.doi.org/10.2466/pms.1989.68.2.403.

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We studied the relation between vividness of imagery and four aspects of creativity, fluency, flexibility, originality, and elaboration. We studied too the difference in creativity of high and low imagers. We obtained for 122 children (69 boys and 53 girls) significant, but low correlations, between imagery vividness and creativity for girls (fluency = .30, flexibility = .32, originality = .24, elaboration = .33) and in the total group (fluency = .24, flexibility = .23, originality = .14, elaboration = .21), but not for boys (fluency = .13, flexibility = .09, originality = .02, elaboration = .11). Differences between high ( n = 35) and low ( n = 45) imagers in creativity were significant.

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12

Gao, Lyuzhou, Liqin Cao, Yanfei Zhong, and Zhaoyang Jia. "Field-Based High-Quality Emissivity Spectra Measurement Using a Fourier Transform Thermal Infrared Hyperspectral Imager." Remote Sensing 13, no. 21 (November 5, 2021): 4453. http://dx.doi.org/10.3390/rs13214453.

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Emissivity information derived from thermal infrared (TIR) hyperspectral imagery has the advantages of both high spatial and spectral resolutions, which facilitate the detection and identification of the subtle spectral features of ground targets. Despite the emergence of several different TIR hyperspectral imagers, there are still no universal spectral emissivity measurement standards for TIR hyperspectral imagers in the field. In this paper, we address the problems encountered when measuring emissivity spectra in the field and propose a practical data acquisition and processing framework for a Fourier transform (FT) TIR hyperspectral imager—the Hyper-Cam LW—to obtain high-quality emissivity spectra in the field. This framework consists of three main parts. (1) The performance of the Hyper-Cam LW sensor was evaluated in terms of the radiometric calibration and measurement noise, and a data acquisition procedure was carried out to obtain the useful TIR hyperspectral imagery in the field. (2) The data quality of the original TIR hyperspectral imagery was improved through preprocessing operations, including band selection, denoising, and background radiance correction. A spatial denoising method was also introduced to preserve the atmospheric radiance features in the spectra. (3) Three representative temperature-emissivity separation (TES) algorithms were evaluated and compared based on the Hyper-Cam LW TIR hyperspectral imagery, and the optimal TES algorithm was adopted to determine the final spectral emissivity. These algorithms are the iterative spectrally smooth temperature and emissivity separation (ISSTES) algorithm, the improved Advanced Spaceborne Thermal Emission and Reflection Radiometer temperature and emissivity separation (ASTER-TES) algorithm, and the Fast Line-of-sight Atmospheric Analysis of Hypercubes-IR (FLAASH-IR) algorithm. The emissivity results from these different methods were compared to the reference spectra measured by a Model 102F spectrometer. The experimental results indicated that the retrieved emissivity spectra from the ISSTES algorithm were more accurate than the spectra retrieved by the other methods on the same Hyper-Cam LW field data and had close consistency with the reference spectra obtained from the Model 102F spectrometer. The root-mean-square error (RMSE) between the retrieved emissivity and the standard spectra was 0.0086, and the spectral angle error was 0.0093.

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13

Schmit, Timothy J., Paul Griffith, Mathew M. Gunshor, Jaime M. Daniels, Steven J. Goodman, and William J. Lebair. "A Closer Look at the ABI on the GOES-R Series." Bulletin of the American Meteorological Society 98, no. 4 (April 1, 2017): 681–98. http://dx.doi.org/10.1175/bams-d-15-00230.1.

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Abstract The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) is America’s next-generation geostationary advanced imager. GOES-R launched on 19 November 2016. The ABI is a state-of-the-art 16-band radiometer, with spectral bands covering the visible, near-infrared, and infrared portions of the electromagnetic spectrum. Many attributes of the ABI—such as spectral, spatial, and temporal resolution; radiometrics; and image navigation/registration—are much improved from the current series of GOES imagers. This paper highlights and discusses the expected improvements of each of these attributes. From ABI data many higher-level-derived products can be generated and used in a large number of environmental applications. The ABI’s design allows rapid-scan and contiguous U.S. imaging automatically interleaved with full-disk scanning. In this paper the expected instrument attributes are covered, as they relate to signal-to-noise ratio, image navigation and registration, the various ABI scan modes, and other parameters. There will be several methods for users to acquire GOES-R imagery and products depending on their needs. These include direct reception of the imagery via the satellite downlink and an online-accessible archive. The information from the ABI on the GOES-R series will be used for many applications related to severe weather, tropical cyclones and hurricanes, aviation, natural hazards, the atmosphere, the ocean, and the cryosphere. The ABI on the GOES-R series is America’s next-generation geostationary advanced imager and will dramatically improve the monitoring of many phenomena at finer time and space scales.

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14

Chara, Paul J., and William S. Verplanck. "The Imagery Questionnaire: An Investigation of its Validity." Perceptual and Motor Skills 63, no. 2 (October 1986): 915–20. http://dx.doi.org/10.2466/pms.1986.63.2.915.

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Research investigated from three perspectives the construct validity of one of the most frequently used imagery measures, Marks' (1973) Vividness of Visual Imagery Questionnaire. First, the performance of six self-reported “good” and six self-reported “poor” imagers derived from 63 initial respondents to the questionnaire was compared on a test of the recall of projected slides. Second, subject idiosyncratic and interpersonal uses of the imagery rating scale were examined through a scaling of projected slides procedure and an alternate forms test-retest paradigm. Finally, interviews about the nature of each subject's imaging experiences were conducted. Data indicated a lack of support for the questionnaire's validity.

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15

J, Cynthia, Suguna M, and Senthil S. "Mapping the vegetation soil and water region analysis of Tuticorin district using Landsat images." International Journal of Engineering & Technology 7, no. 1.3 (December 31, 2017): 161. http://dx.doi.org/10.14419/ijet.v7i1.3.10663.

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Mapping of water bodies, soil and vegetation region from satellite imagery has been widely explored in the recent past. Several approaches have been developed to detect water bodies and identify the soil types from different satellite imagery varying in spatial, spectral, and temporal characteristics. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed is increased. Its imagery produces a better result in classifying the soil and water regions. The current study puts forward an approach to map water bodies, soil and vegetation region from a Landsat satellite imagery using the various processing models. In this study, to identify the water region and soil region, we go with water index, vegetation index and soil index measures. By using reflectance bands, it is easy to analyze the water, vegetation and soil regions. The proposed method accurately and quickly discriminated the water, vegetation and soil region from other land cover features.

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Cobb-Stevens, Veda. "Imagery." International Philosophical Quarterly 26, no. 1 (1986): 87–91. http://dx.doi.org/10.5840/ipq198626149.

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Gagan, Jeannette M. "IMAGERY." Perspectives in Psychiatric Care 22, no. 1 (January 16, 2009): 20–25. http://dx.doi.org/10.1111/j.1744-6163.1984.tb00199.x.

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18

Stephens, Rebecca. "Imagery." Clinical Nurse Specialist 7, no. 4 (July 1993): 170–74. http://dx.doi.org/10.1097/00002800-199307000-00004.

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Stephens, Rebecca L. "Imagery." Clinical Nurse Specialist 7, no. 5 (September 1993): 235–40. http://dx.doi.org/10.1097/00002800-199309000-00003.

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Heath, Adria H. "Imagery." Dimensions of Critical Care Nursing 11, no. 1 (January 1992): 57–61. http://dx.doi.org/10.1097/00003465-199201000-00012.

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21

William, Abdu A., and NH Hanover. "Imagery." Spine 26, no. 20 (October 2001): i. http://dx.doi.org/10.1097/00007632-200110150-00001.

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Lander, Richard. "Imagery." Spine 27, no. 3 (February 2002): i. http://dx.doi.org/10.1097/00007632-200202010-00001.

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Dreyfuss, Paul. "Imagery." Spine 27, no. 9 (May 2002): 20A. http://dx.doi.org/10.1097/00007632-200205010-00001.

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Beraneck, Françoise. "Imagery." Spine 27, no. 10 (May 2002): i. http://dx.doi.org/10.1097/00007632-200205150-00001.

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Johnson, Gillian. "Imagery." Spine 27, no. 15 (August 2002): i. http://dx.doi.org/10.1097/00007632-200208010-00001.

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Qi, Qiang. "Imagery." Spine 27, no. 16 (August 2002): i. http://dx.doi.org/10.1097/00007632-200208150-00001.

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27

Seiler, Brian D., Eva V. Monsma, Roger Newman-Norlund, and Ryan Sacko. "Neural Activity During Imagery Supports Three Imagery Abilities as Measured by the Movement Imagery Questionnaire-3." Journal of Sport and Exercise Psychology, 2022, 1–15. http://dx.doi.org/10.1123/jsep.2021-0229.

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Self-report and neural data were examined in 14 right-handed college-age males screened from a pool of 200 to verify neural activity during imagery and that the neural activity (area of brain) varies as a function of the imagery type. Functional magnetic resonance imaging data collected during real-time imagery of the three Movement Imagery Questionnaire-3 abilities indicated frontal areas, motor areas, and cerebellum active during kinesthetic imagery, motor areas, and superior parietal lobule during internal visual imagery, and parietal lobule and occipital cortex during external visual imagery. Central and imagery-specific neural patterns were found providing further biological validation of kinesthetic, internal visual, and external visual complementing results on females. Next, research should (a) compare neural activity between male participants screened by self-reported imagery abilities to determine if good imagers have more efficient neural networks than poor imagers and (b) determine if there is a statistical link between participants’ neural activity during imagery and self-report Movement Imagery Questionnaire-3 scores.

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Gerth, Jordan J., Raymond K. Garcia, David J. Hoese, Scott S. Lindstrom, and Timothy J. Schmit. "SIFTing through satellite imagery with the Satellite Information Familiarization Tool." Journal of Operational Meteorology, December 17, 2020, 121–32. http://dx.doi.org/10.15191/nwajom.2020.0810.

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The Satellite Information Familiarization Tool (SIFT) is an open-source, multi-platform graphical user interface designed to easily display spectral and temporal sequences of geostationary satellite imagery. The Advanced Baseline Imager (ABI) and Advanced Himawari Imager (AHI) on the “new generation” of geostationary satellites collect imagery with a spatial resolution four times greater than previously available. Combined with the increased number of spectral bands and more frequent imaging, the new series imagers collect approximately 60 times more data. Given the resulting large file sizes, the development of SIFT is a multiyear effort to make those satellite imagery data files accessible to the broad community of students, scientists, and operational meteorologists. To achieve the objective of releasing software that provides an intuitive user experience to complement optimum performance on consumer-grade computers, SIFT was built to leverage modern graphics processing units (GPUs) through existing open-source Python packages, and runs on the three major operating systems: Windows, Mac, and Linux. The United States National Weather Service funded the development of SIFT to help enhance the satellite meteorology acumen of their operational meteorologists. SIFT has basic image visualization capabilities and enables the fluid animation and interrogation of satellite images, creation of Red-Green-Blue (RGB) composites and algebraic combinations of multiple spectral bands, and comparison of imagery with numerical weather prediction output. Open for community development, SIFT users and features continue to grow. SIFT is freely available with short tutorials and a user guide online. The mandate for the software, its development, realized applications, and envisioned role in science and training are explained.

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McNeil, Dominic G., Michael Spittle, and Einar B. Thorsteinsson. "Effect of task complexity on ipsilateral motor response programming to physically presented and imagined stimuli." Quarterly Journal of Experimental Psychology, November 27, 2020, 174702182097301. http://dx.doi.org/10.1177/1747021820973013.

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It is unclear whether task representation generated in imagery simulates performance demands in reacting to stimuli. This study investigated whether perceptual and motor control processes used to react to unpredictable stimuli and initiate an ipsilateral movement were replicated during imagery. Fifty-nine undergraduate students ( Mage = 27.01 years, SD = 8.30) completed 30 simple, two-choice congruent and two-choice incongruent ipsilateral finger–foot movement trials in response to a physically presented or imagined stimulus. The results appear to indicate that participants were reacting to imagined and actual stimuli, as the ipsilateral finger–foot programming rule was maintained and reaction time initially slowed as task difficulty increased. These findings support theoretical similarities between imagery and physical performance of reaction tasks, with imagers generating and reacting to unpredictable stimuli. Slower imagery performance than physical performance on the two-choice incongruent task may indicate that task complexity is limited during imagery. Variation in results between the imagery and physical conditions potentially supports that imagers were able to react to the imagined stimulus. However, exploratory processes used to react to stimuli were not replicated during imagery. The present findings have potentially significant implications for the functional and applied use of imagery for skill acquisition.

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Seaman, Curtis J., William Line, Robert Ziel, Jennifer Jenkins, Carl Dierking, and Greg Hanson. "Multispectral Satellite Imagery Products for Fire Weather Applications." Journal of Atmospheric and Oceanic Technology, April 3, 2023. http://dx.doi.org/10.1175/jtech-d-22-0107.1.

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Abstract Two multispectral satellite imagery products are presented that were developed for use within the fire management community. These products, which take the form of false color red-green-blue composites, were designed to aid fire detection and characterization, and for assessment of the environment surrounding a fire. The first, named the Fire Temperature RGB, uses spectral channels near 1.6 μm, 2.2 μm and 3.9 μm for fire detection and rapid assessment of the range of fire intensity through intuitive coloration. The second, named the Day Fire RGB, uses spectral channels near 0.64 μm, 0.86 μm and 3.9 μm for rapid scene assessment. The 0.64 μm channel provides information on smoke, the 0.86 μm channel provides information on vegetation health and burn scars, and the 3.9 μm channel provides active fire detections. Examples of these red-green-blue composite images developed from observations collected by three operational satellite imagers (VIIRS on the polar-orbiting platform and the Advanced Baseline Imager and Advanced Himawari Imager on the geostationary platform) demonstrate that both red-green-blue composites are useful for fire detection and contain valuable information that is not present within operational fire detection algorithms. In particular, it is shown that Fire Temperature RGB and Day Fire RGB images from VIIRS have similar utility for fire detection as the operational VIIRS Active Fire products, with the added benefit that the imagery provides context for more than just the fires themselves.

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Weber, Simon, Thomas Christophel, Kai Görgen, Joram Soch, and John‐Dylan Haynes. "Working memory signals in early visual cortex are present in weak and strong imagers." Human Brain Mapping 45, no. 3 (February 15, 2024). http://dx.doi.org/10.1002/hbm.26590.

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AbstractIt has been suggested that visual images are memorized across brief periods of time by vividly imagining them as if they were still there. In line with this, the contents of both working memory and visual imagery are known to be encoded already in early visual cortex. If these signals in early visual areas were indeed to reflect a combined imagery and memory code, one would predict them to be weaker for individuals with reduced visual imagery vividness. Here, we systematically investigated this question in two groups of participants. Strong and weak imagers were asked to remember images across brief delay periods. We were able to reliably reconstruct the memorized stimuli from early visual cortex during the delay. Importantly, in contrast to the prediction, the quality of reconstruction was equally accurate for both strong and weak imagers. The decodable information also closely reflected behavioral precision in both groups, suggesting it could contribute to behavioral performance, even in the extreme case of completely aphantasic individuals. Our data thus suggest that working memory signals in early visual cortex can be present even in the (near) absence of phenomenal imagery.

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"Imagery." Spine 26, no. 6 (March 2001): i. http://dx.doi.org/10.1097/00007632-200103150-00001.

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"Imagery." Spine 26, no. 7 (April 2001): i. http://dx.doi.org/10.1097/00007632-200104010-00001.

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"Imagery." Spine 26, no. 8 (April 2001): i. http://dx.doi.org/10.1097/00007632-200104150-00001.

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"Imagery." Spine 26, no. 9 (May 2001): i. http://dx.doi.org/10.1097/00007632-200105010-00001.

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"Imagery." Spine 26, no. 10 (May 2001): i. http://dx.doi.org/10.1097/00007632-200105150-00001.

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"Imagery." Spine 26, no. 11 (June 2001): i. http://dx.doi.org/10.1097/00007632-200106010-00006.

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"Imagery." Spine 26, no. 12 (June 2001): i. http://dx.doi.org/10.1097/00007632-200106150-00001.

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"Imagery." Spine 26, no. 13 (July 2001): i. http://dx.doi.org/10.1097/00007632-200107010-00001.

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"Imagery." Spine 26, no. 14 (July 2001): i. http://dx.doi.org/10.1097/00007632-200107150-00001.

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"Imagery." Spine 26, no. 15 (August 2001): i. http://dx.doi.org/10.1097/00007632-200108010-00001.

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"Imagery." Spine 26, no. 16 (August 2001): i. http://dx.doi.org/10.1097/00007632-200108150-00001.

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"Imagery." Spine 26, no. 17 (September 2001): i. http://dx.doi.org/10.1097/00007632-200109010-00001.

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"Imagery." Spine 26, no. 18 (September 2001): i. http://dx.doi.org/10.1097/00007632-200109150-00001.

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"Imagery." Spine 26, no. 21 (November 2001): i. http://dx.doi.org/10.1097/00007632-200111010-00001.

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"Imagery." Spine 26, no. 22 (November 2001): i. http://dx.doi.org/10.1097/00007632-200111150-00001.

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"Imagery." Spine 26, no. 23 (December 2001): i. http://dx.doi.org/10.1097/00007632-200112010-00001.

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"Imagery." Spine 26, no. 24 (December 2001): i. http://dx.doi.org/10.1097/00007632-200112150-00001.

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"Imagery." Spine 27, no. 2 (January 2002): i. http://dx.doi.org/10.1097/00007632-200201150-00001.

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"Imagery." Spine 27, no. 4 (February 2002): i. http://dx.doi.org/10.1097/00007632-200202150-00001.

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