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How Many Subjects Constitute a Study?
Abstract
In fMRI there are two classes of inference: one aims to make a comment about the "typical" characteristics of a population, and the other about "average" characteristics. The first pertains to studies of normal subjects that try to identify some qualitative aspect of normal functional anatomy. The second class necessarily applies to clinical neuroscience studies that want to make an inference about quantitative differences of a regionally specific nature. The first class of inferences is adequately serviced by conjunction analyses and fixed-effects models with relatively small numbers of subjects. The second requires random-effect analyses and larger cohorts.
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“However, small sample sizes can be informative about typicality of a feature in a population, when features are identified in the majority of cases sampled[18].”
From In vivo PET imaging of neuroinflammation in familial frontotemporal dementia (2021) · cites this paper as [18]
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Ideographic characters call for extra processing to correspond with phonemes
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“Individual analysis was performed with a fixed effect model, whereas group analysis was performed with a random effect model (Friston et al., 1999).”
MethodEndogenous Opioid Antagonism in Physiological Experimental Pain Models: A Systematic Review
Werner, M. U., Pereira, M. P., Andersen, L. P. H., & Dahl, J. B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0125887 · Cited by 20
Visceromotor roots of aesthetic evaluation of pain in art: an fMRI study
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The Neural Substrates of Self-Evaluation of Mental Fatigue: A Magnetoencephalography Study
Ishii, A., Tanaka, M., & Watanabe, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095763 · Cited by 20
“Significant signal changes from the control to the evaluation trials for each contrast were assessed using t statistic on a voxel-by-voxel basis [45].”
MethodInfluentialLong, Z., Hanson, D. P., Mullan, B. P., et al. (2018) · Journal of Neuroimaging · doi:10.1111/jon.12496 · Cited by 20
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BackgroundMethodInfluentialTakada, K., Ishii, A., Matsuo, T., Nakamura, C., Uji, M., & Yoshikawa, T. (2018) · Scientific Reports · doi:10.1038/s41598-018-21383-0 · Cited by 22
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“In order to draw population-based inferences [39], a second-level random effect group analysis was carried-out.”
MethodMok, L. W. (2012) · Neuroscience · doi:10.1016/j.neuroscience.2012.09.005 · Cited by 19
“Although this did not allow for generalization of the obtained results to the population of healthy young adults, it allowed for interpretation of the ‘‘typical’’ characteristics of typically-functioning individuals (Friston et al., 1999).”
ResultVenkatasubramanian, G., Puthumana, D. T., Jayakumar, P., & Gangadhar, B. N. (2010) · Indian Journal of Psychiatry · doi:10.4103/0019-5545.74304 · Cited by 19
“[57] However, the following factors might be construed as potential limitations of our study.”
The right temporoparietal junction encodes efforts of others during action observation
Mizuguchi, N., Nakata, H., & Kanosue, K. (2016) · Scientific Reports · doi:10.1038/srep30274 · Cited by 19
Dissociable Neural Activations of Conscious Visibility and Attention
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“Individual analysis was performed with a fixed effect model, and group analysis was performed with a random effect model (Friston, Holmes, & Worsley, 1999 ).”
MethodDoes hippocampus associate discontiguous events? Evidence from event‐related fMRI
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“In contrast to the recognition memory that could be achieved through a familiarity heuristic, the semantic relatedness judgment can only be accomplished through an associative process (Henke et al., 1999; Lepage et al, 2000; Luo and Niki, 2002).”
BackgroundManjaly, Z. M., Marshall, J. C., Stephan, K. E., Gurd, J. M., Zilles, K., & Fink, G. R. (2005) · Cognitive Neuropsychology · doi:10.1080/02643290442000149 · Cited by 19
Miyanari, A., Kaneoke, Y., Noguchi, Y., Honda, M., Sadato, N., Sagara, Y., & Kakigi, R. (2007) · Neuroscience Letters · doi:10.1016/j.neulet.2007.06.039 · Cited by 19
Language for action: Motor resonance during the processing of human and robotic voices
Cesare, G. D., Errante, A., Marchi, M., & Cuccio, V. (2017) · Brain and Cognition · doi:10.1016/j.bandc.2017.08.001 · Cited by 19
Neural regulatory mechanism of desire for food: Revealed by magnetoencephalography
Yoshikawa, T., Tanaka, M., Ishii, A., Fujimoto, S., & Watanabe, Y. (2013) · Brain Research · doi:10.1016/j.brainres.2013.11.005 · Cited by 21
Neural Mechanism of Facilitation System during Physical Fatigue
Tanaka, M., Ishii, A., & Watanabe, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080731 · Cited by 18
“Significant signal changes for each contrast were assessed by means of t statistics on a voxel-by-voxel basis [20].”
MethodInfluentialForkmann, K., Wiech, K., Sommer, T., & Bingel, U. (2015) · Pain · doi:10.1097/j.pain.0000000000000194 · Cited by 20
Expectation influences the interruptive function of pain: Behavioural and neural findings
Sinke, C., Schmidt, K., Forkmann, K., & Bingel, U. (2016) · European Journal of Pain · doi:10.1002/ejp.928 · Cited by 17
“At group level, a random-effects approach was used (Friston et al., 1999), treating inter-subject variability as a random factor and including non-sphericity.”
MethodButler, M. J. R., Lee, N. J., & Senior, C. (2017) · Human Relations · doi:10.1177/0018726716684381 · Cited by 18
“(Hayasaka et al., 2007: 721) Friston et al. (1999) argued that there are two classes of inference in neuroimaging research, which has implications for sample size, and the selection of the most appropriate analysis depends on the research question being asked.”
A Role for Broca’s Area Beyond Language Processing: Evidence from Neuropsychology and fMRI
Fink, G. R., Manjaly, Z. M., Stephan, K. E., Gurd, J. M., Zilles, K., Amunts, K., & Marshall, J. C. (2006) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195177640.003.0016 · Cited by 21
Neural mechanism of central inhibition during physical fatigue: A magnetoencephalography study
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“Significant signal changes for each contrast were assessed by means of t statistics on a voxel-byvoxel basis (Friston et al., 1999).”
InfluentialVisual Activation in Functional Magnetic Resonance Imaging at Very High Field (4 Tesla)
Miki, A., Liu, G. T., Raz, J. A., et al. (2001) · Journal of Neuro-Ophthalmology · doi:10.1097/00041327-200103000-00002 · Cited by 18
“Spatial normalization enables us to perform a group data analysis, which is more appropriate in making inferences at the population level than an individual data analysis (20).”
MethodJamieson, A. J., Leonards, C. A., Davey, C. G., & Harrison, B. J. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02734-0 · Cited by 23
“Additional work examining the predictive validity and clinical utility of these connectivity parameters longitudinaly will aid in providing a more nuanced understanding of the neurobiological mechanisms underlying treatment response in depression.”
BackgroundWomen’s Brain Health: Midlife Ovarian Removal Affects Associative Memory
Brown, A., Gervais, N. J., Rieck, J. R., Almey, A., Gravelsins, L. L., Reuben, R. B., Karkaby, L., Rajah, M. N., Grady, C. L., & Einstein, G. (2023) · Molecular Neurobiology · doi:10.1007/s12035-023-03424-6 · Cited by 19
“These studies, like ours, are likely to have smaller cohort sizes, yet retain the power to identify important group differences [60, 61].”
Dissociations in processing derivational morphology: The right basal ganglia involvement
Marangolo, P., & Piras, F. (2007) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2007.07.025 · Cited by 17
Spatial and temporal dissociation in prefrontal cortex during action execution
Hunter, M. D., Green, R. D. J., Wilkinson, I. D., & Spence, S. A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.047 · Cited by 17
Central luminance flicker can activate peripheral retinotopic representation
Stenbacka, L., & Vanni, S. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.08.029 · Cited by 17
“the results at the group level ( Friston, et al. 1999 ) and used a false discovery rate (FDR;”
ResultVerbal Working Memory Dysfunction in Schizophrenia: An fMRI Investigation
Pae, C., Juh, R., Yoo, S., Choi, B.-G., Lim, H. K., Lee, C., Paik, I., Jeun, S. S., & Lee, C. (2008) · International Journal of Neuroscience · doi:10.1080/00207450701591131 · Cited by 16
Seretny, M., Romaniuk, L., Whalley, H. C., Sladdin, K., Lawrie, S. M., Warnaby, C. E., Roberts, N., Colvin, L., Tracey, I., & Fallon, M. (2022) · British Journal of Anaesthesia · doi:10.1016/j.bja.2022.09.026 · Cited by 16
The representation of social interaction in episodic memory: A functional MRI study
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“Summary data of all participants were analyzed using a randomeffect model (Friston et al., 1999) with a full-factorial model which included one factor and five conditions as levels to make inferences at the population level with a non-sphericity correction, as implemented in SPM5 (Worsley and…”
Barbour, T. A., Pruitt, P. J., & Diwadkar, V. A. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.11.036 · Cited by 18
“The advantage of using functional neuroimaging is that fMRI signals offer greater power for detecting differences than structural MRI measures (Diwadkar et al., 2011b; Friston et al., 1999).”
BackgroundIshii, A., Tanaka, M., & Watanabe, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0109740 · Cited by 16
“Significant signal changes from the control to the decision trials, and from the control to the rest and continuation trials, were assessed using t statistics on a voxel-by-voxel basis [22].”
MethodInfluentialAltered prefrontal connectivity after acute heroin administration during cognitive control
Schmidt, A., Borgwardt, S., Gerber, H., Schmid, O., Wiesbeck, G. A., Riecher‐Rössler, A., Bendfeldt, K., Smieskova, R., Lang, U. E., Rubia, K., et al. (2014) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145714000297 · Cited by 18
“…activity without a change in behavioural performance is a consistent finding in fMRI research (Wilkinson and Halligan, 2004), and can be explained by the fact that fMRI data on small subject numbers are relatively robust (Friston et al., 1999), while behavioural indexes are typically underpowered.”
Residual fMRI sensitivity for identity changes in acquired prosopagnosia
Fox, C. J., Iaria, G., Duchaine, B., & Barton, J. J. S. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00756 · Cited by 16
“The power of group analyses lies in the averaging of results across a number of subjects (Friston et al., 1999).”
BackgroundCommon and Distinct Functional Brain Networks for Intuitive and Deliberate Decision Making
Erdeniz, B., & Done, J. (2019) · Brain Sciences · doi:10.3390/brainsci9070174 · Cited by 15
“Although the total number of participants in the current study and the significance levels are adequate according to previously reported standards [54,95,96], more recent studies suggest that an increased number of participants of up to 100 dramatically increases the replicability of the fMRI studies [97].”
ResultPhillips, S. D., & Niki, K. (2002) · NeuroImage · doi:10.1006/nimg.2002.1190 · Cited by 16
“…P Ͼ 1 Ϫ ␣ c , corrected, is given by the expression ␥ c Ն ͩ ␣ c Ϫ P n 1 Ϫ P n ͪ 1/n Ϫ ␣ m 1 Ϫ ␣ m , where n is the number of subjects, ␣ m is minimum threshold specificity for each subject in the conjunction , and P n is the corrected P value for the region of interest (Friston et al., 1999a, Eq.”
BackgroundMethodInfluentialFunctional BOLD MRI: comparison of different field strengths in a motor task
Meindl, T., Born, C., Britsch, S., et al. (2008) · European Radiology · doi:10.1007/s00330-008-0869-1 · Cited by 16
“Therefore, it is necessary to examine a large cohort of volunteers or patients to achieve a reliable statistical analysis and reliable activations [ 4 ].”
BackgroundAloufi, A., Rowe, F. J., & Meyer, G. F. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117673 · Cited by 15
Magnetic resonance morphometry of the loss of gray matter volume in Parkinson's disease patients.
Xia, J., Wang, J., Tian, W., et al. (2013) · PubMed · doi:10.3969/j.issn.1673-5374.2013.27.007 · Cited by 15
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Using small numbers of subjects in fMRI-based research
Savoy, R. L. (2006) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2006.1607669 · Cited by 15
“One particularly clear and useful example is [1], in which the question “How many subjects constitute a study?” is considered.”
Tanaka, M., Ishii, A., & Watanabe, Y. (2015) · Behavioral and Brain Functions · doi:10.1186/s12993-015-0079-3 · Cited by 14
“To enable inferences to be made at a population level, individual data were summarized and incorporated into a random-effect model [18].”
InfluentialToward a Cognitive Neurobiological Account of Free Association
Spence, S. A., Kaylor‐Hughes, C., Cooley, L., Green, R. D., Wilkinson, I. D., Parks, R. W., & Hunter, M. D. (2009) · Neuropsychoanalysis · doi:10.1080/15294145.2009.10773607 · Cited by 14
Enhanced Neural Reinstatement for Evoked Facial Pain Compared With Evoked Hand Pain
Schmidt, K., Forkmann, K., Schultz, H., Gratz, M., Bitz, A. K., Wiech, K., & Bingel, U. (2019) · Journal of Pain · doi:10.1016/j.jpain.2019.03.003 · Cited by 13
Shigihara, Y., Hoshi, H., Poza, J., Rodríguez-González, V., Gómez, C., & Kanzawa, T. (2020) · Aging · doi:10.18632/aging.202270 · Cited by 14
The neural bases of tactile vitality forms and their modulation by social context
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Kami, Y. N., Goto, T. K., Tokumori, K., Yoshiura, T., Kobayashi, K., Nakamura, Y., Honda, H., Ninomiya, Y., & Yoshiura, K. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.04.009 · Cited by 14
Borsook, D., Pendse, G., Aiello‐Lammens, M., Glicksman, M. A., Gostic, J., Sherman, S. J., Korn, J., Shaw, M. E., Stewart, K., Gostic, R., et al. (2007) · Drug Development Research · doi:10.1002/ddr.20163 · Cited by 14
“In addition, studies show that fMRI can yield significant results with relatively small numbers of subjects [Friston et al., 1999].”
BackgroundCommunicative And Affective Components in Processing Auditory Vitality Forms: An fMRI Study
Cesare, G. D., Cuccio, V., Marchi, M., Sciutti, A., & Rizzolatti, G. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab255 · Cited by 13
Shimada, K., Kasaba, R., Fujisawa, T. X., Sakakibara, N., Takiguchi, S., & Tomoda, A. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.12.031 · Cited by 13
Cerebro-Cerebellar Pathways for Verbal Working Memory
Sobczak‐Edmans, M., Lo, Y., Hsu, Y., Chen, Y.-J., Kwok, F. Y., Chuang, K., Tseng, W. I., & Chen, S. A. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00530 · Cited by 13
Kumari, V., Ettinger, U., Lee, S. E., Deuschl, C., Anilkumar, A. P., Schmechtig, A., Corr, P. J., Ffytche, D. H., & Williams, S. (2015) · Psychopharmacology · doi:10.1007/s00213-015-3959-1 · Cited by 13
An fMRI study of face encoding and recognition in first-episode schizophrenia
Anilkumar, A. P., Kumari, V., Mehrotra, R., et al. (2008) · Acta Neuropsychiatrica · doi:10.1111/j.1601-5215.2008.00280.x · Cited by 13
Functional MR study of a motor task and the Tower of London task at 1.0 T
Boghi, A., Rampado, O., Bergui, M., Avidano, F., Manzone, C., Coriasco, M., Mortara, P., Orsi, L., Ropolo, R., & Bradac, G. (2006) · Neuroradiology · doi:10.1007/s00234-006-0119-7 · Cited by 13
“In order to make a population inference of the task-related brain activations, random-effects analyses were performed [29].”
MethodRecognition of Objects in Non-Canonical Views: A Functional MRI Study
Terhune, K. P., Liu, G. T., Modestino, E. J., et al. (2005) · Journal of Neuro-Ophthalmology · doi:10.1097/01.wno.0000189826.62010.48 · Cited by 13
“Statistically significant areas across subjects were determined using random effects analysis (28), which involved a first-level analysis consisting of statistical parametric maps generated using the general linear model and random field theory, followed by the application of one sample t test to the individual activa…”
MethodThe Encoding of Temporally Irregular and Regular Visual Patterns in the Human Brain
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“The analyses described below were all performed at the random effects level so that the reliability of measurements could be assessed in relation to the between subject variance [3].”
BackgroundDifferences in Brain Hemodynamics in Response to Achromatic and Chromatic Cards of the Rorschach
石橋, 正., Uchiumi, C., Jung, M., Aizawa, N., Makita, K., Nakamura, Y., & Saito, D. N. (2016) · Rorschachiana Journal of the International Society for the Rorschach · doi:10.1027/1192-5604/a000076 · Cited by 13
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“” For functional MRI, both lower and upper limits have been suggested (Friston, 2012; Friston et al., 1999; Ioannidis, 2005), as well as approaches toward exploring the power of such studies (Thirion et al.”
BackgroundSunami, K., Ishii, A., Takano, S., et al. (2013) · Brain Research · doi:10.1016/j.brainres.2013.09.010 · Cited by 12
“Significant signal changes for each contrast were assessed by means of t-statistics on a voxel-by-voxel basis (Friston et al., 1999).”
InfluentialTanabe, H. C., Sakai, T., Morito, Y., Kochiyama, T., & Sadato, N. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhq066 · Cited by 12
Development of attentional networks during childhood and adolescence: A functional MRI study
Saito, D. N., Fujisawa, T. X., Yanaka, H. T., Fujii, T., Kochiyama, T., Makita, K., Tomoda, A., & Okazawa, H. (2022) · Neuropsychopharmacology Reports · doi:10.1002/npr2.12246 · Cited by 13
Voluntary attention changes the speed of perceptual neural processing
Noguchi, Y., Tanabe, H. C., Sadato, N., Hoshiyama, M., & Kakigi, R. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05552.x · Cited by 12
“All procedures in this study conformed to The Code of Ethics of the World Medical Association (Declaration of Helsinki), and approval for these experiments was obtained from the ethics committee of the National Institute for Physiological Sciences, Okazaki, Japan.”
MethodJackson, T., Gao, X., & Chen, H. (2013) · International Journal of Obesity · doi:10.1038/ijo.2013.245 · Cited by 12
Sakamoto, K., Nakata, H., Inui, K., Perrucci, M. G., Gratta, C. D., Kakigi, R., & Romani, G. L. (2009) · Neuroscience Research · doi:10.1016/j.neures.2009.10.013 · Cited by 12
“Second, the summary data for each individual were incorporated into the second-level analysis using a random-effect model (Friston et al., 1999) to make inferences at a population level.”
MethodThe statistical power of three monkeysPreprint
Laurens, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.10.491373 · Cited by 12
Gibson, E., Fenster, A., & Ward, A. D. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.04.008 · Cited by 11
“…the acceptable error rates, the size of the underlying difference, the characteristics of the population being analyzed, the statistical test (Lipsey, 1990), the types of hypotheses being tested (Hayes and Bennett, 1999; Friston et al., 1999), and the sampling methods used (Donner and Klar, 2000).”
MethodThe Neural Mechanisms of Re-Experiencing Mental Fatigue Sensation: A Magnetoencephalography Study
Ishii, A., Karasuyama, T., Kikuchi, T., Tanaka, M., Yamano, E., & Watanabe, Y. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122455 · Cited by 10
Evidence for unconscious regulation of performance in fatigue
Ishii, A., Tanaka, M., Yoshikawa, T., & Watanabe, Y. (2017) · Scientific Reports · doi:10.1038/s41598-017-16439-6 · Cited by 13
Garibbo, M., Aylward, J., & Robinson, O. J. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz080 · Cited by 10
“A random effect analysis (Friston et al., 1999) was employed to estimate changes in blood-oxygen level-dependent signal across all participants for both tasks.”
MethodYou, Y., Correas, Á., Keehn, R. J. J., Wagner, L. C., Rosen, B. Q., Beaton, L. E., Gao, Y., Brocklehurst, W. T., Fishman, I., Müller, R., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa279 · Cited by 11
“This ROI approach permits further statistical exploration of possible interactions of Group and Condition, by testing for differences in a 2 (Group)-by-3 (Condition) model while controlling for intersubject variability analogous to the “random effects” fMRI analysis (Friston et al. 1999).”
MethodVindras, P., Desmurget, M., & Baraduc, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039059 · Cited by 10
Fusar‐Poli, P. (2009) · European Psychiatry · doi:10.1016/s0924-9338(09)70439-0 · Cited by 11
Understanding the attitude of others by hearing action sounds: the role of the insula
Cesare, G. D., Marchi, M., Pinardi, C., & Rizzolatti, G. (2019) · Scientific Reports · doi:10.1038/s41598-019-50609-y · Cited by 10
Gnecco, G., Nutarelli, F., & Selvi, D. (2020) · Soft Computing · doi:10.1007/s00500-020-05317-5 · Cited by 10
Zapparoli, L., Devoto, F., Mariano, M., Seghezzi, S., Servello, D., Porta, M., & Paulesu, E. (2024) · Translational Psychiatry · doi:10.1038/s41398-023-02711-z · Cited by 10
“Most of the available task-based studies were based on small samples of patients, a matter of concern in terms of statistical power and control of false positives [16, 17].”
Wartenburger, I., Heekeren, H. R., Burchert, F., Bleser, R. D., & Villringer, A. (2003) · Journal of Neurolinguistics · doi:10.1016/s0911-6044(03)00028-9 · Cited by 10
An exploration of the mechanisms underlying the development of repeat and one-time violent offenders
Chambers, J. C. (2010) · Aggression and Violent Behavior · doi:10.1016/j.avb.2010.03.002 · Cited by 10
Frontal cortex BOLD signal changes in premanifest Huntington disease
Ferraro, S., Nanetti, L., Piacentini, S. H. M. J., Mandelli, M. L., Bertolino, N., Ghielmetti, F., Epifani, F., Nigri, A., Taroni, F., Bruzzone, M. G., et al. (2014) · Neurology · doi:10.1212/wnl.0000000000000538 · Cited by 10
Javor, A., Ciumas, C., Ibarrola, D., Ryvlin, P., & Rheims, S. (2019) · Royal Society Open Science · doi:10.1098/rsos.180850 · Cited by 10
Posterior Midline Activation during Symptom Provocation in Acute Stress Disorder: An fMRI Study
Cwik, J. C., Sartory, G., Schürholt, B., Knuppertz, H., & Rj, S. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00049 · Cited by 10
“Even though the number of 19 participants in each group approaches the recommended sample size for fMRI studies (99), a larger sample size would have increased the power of the statistical analyses.”
BackgroundVisual food stimulus changes resting oscillatory brain activities related to appetitive motive
Yoshikawa, T., Tanaka, M., Ishii, A., Yamano, Y., & Watanabe, Y. (2016) · Behavioral and Brain Functions · doi:10.1186/s12993-016-0110-3 · Cited by 10
Negative BOLD during tongue movement: A functional magnetic resonance imaging study
Sakamoto, K., Nakata, H., Perrucci, M. G., Gratta, C. D., Kakigi, R., & Romani, G. L. (2009) · Neuroscience Letters · doi:10.1016/j.neulet.2009.09.038 · Cited by 9
Böttger, S., Haberl, R. L., Prosiegel, M., Audebert, H. J., Rumberg, B., Forsting, M., & Gizewski, E. R. (2010) · Brain Research · doi:10.1016/j.brainres.2010.07.056 · Cited by 9
“Significant signal changes for each contrast were assessed by means of tstatistics on a voxel-by-voxel basis and maximum likelihood estimation, as commonly used for fMRI (Friston et al., 1995b; Friston et al., 1999b).”
BackgroundMethodInfluentialUehara, S., Mizuguchi, N., Hirose, S., Yamamoto, S., & Naito, E. (2019) · Brain Research · doi:10.1016/j.brainres.2019.146365 · Cited by 10
Functional Imaging of the Mechanisms Underlying the Bilateral Field Advantage
Santhouse, A. M., Ffytche, D. H., Howard, R., et al. (2002) · NeuroImage · doi:10.1006/nimg.2002.1186 · Cited by 9
Aalto, S., Wallius, E., Näätänen, P., Hiltunen, J., Metsähonkala, L., Sipilä, H. T., & Karlsson, H. (2005) · Brain Research Protocols · doi:10.1016/j.brainresprot.2005.06.003 · Cited by 9
Ishii, A., Tanaka, M., & Watanabe, Y. (2016) · Scientific Reports · doi:10.1038/srep25097 · Cited by 8
Sturm, W., Schnitker, R., Grande, M., Huber, W., & Willmes, K. (2011) · Restorative Neurology and Neuroscience · doi:10.3233/rnn-2011-0569 · Cited by 8
Ohnishi, T., Toda, W., Itagaki, S., Sato, A., Matsumoto, J., Ito, H., Ishii, S., Miura, I., & Yabe, H. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1093522 · Cited by 8
Is the Brain's Inertia for Motor Movements Different for Acceleration and Deceleration?
Adhikari, B. M., Quinn, K. M., & Dhamala, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0078055 · Cited by 9
“Brain data analysis fMRI images were preprocessed and analyzed using Statistical Parametric Mapping (SPM8) (Wellcome Trust, London; [40,41], http://www.fil.ion.ucl.ac.uk/spm).”
MethodNeuronal Substrates Underlying Performance Variability in Well-Trained Skillful Motor Task in Humans
Mizuguchi, N., Uehara, S., Hirose, S., Yamamoto, S., & Naito, E. (2016) · Neural Plasticity · doi:10.1155/2016/1245259 · Cited by 7
“To accommodate interparticipant variability, each participant’s contrast imagewas entered into a random-effect group analysis [11].”
MethodFunctional magnetic resonance imaging studies of acupuncture mechanisms: a critique
Beißner, F. (2010) · Focus on Alternative and Complementary Therapies · doi:10.1111/j.2042-7166.2010.01048.x · Cited by 8
Hirose, S., Hagura, N., Matsumura, M., & Naito, E. (2009) · Brain Research · doi:10.1016/j.brainres.2009.11.066 · Cited by 8
Metadata
- Authors
- Friston, K. J., Holmes, A. P., & Worsley, K. J.
- Affiliations
- National Hospital for Neurology and Neurosurgery (GB)
- ORCID
- Friston, Karl J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 1999-07
- Volume
- 10
- Issue
- 1
- Pages
- 1-5
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1966363088
- Cited by
- 814
- References
- 0
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 3 · 2023: 7 · 2022: 9 · 2021: 8 · 2020: 17 · 2019: 13 · 2018: 10 · 2017: 15 · 2016: 31 · 2015: 27 · 2014: 22 · 2013: 35 · 2012: 30
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- sample size, functional MRI, statistical inference, population inference, fixed effects model, random effects models, conjunction analysis, clinical neuroscience, functional anatomy, cohort size
- MeSH terms
- Data Interpretation, Statistical, Humans, Magnetic Resonance Imaging, Research Design, Models, Statistical, Cohort Studies, Patient Selection
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