Araştırma Makalesi
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fMRI analizinde faktöriyel tasarımlar: Tam ve esnek faktöriyel yaklaşımların karşılaştırmalı bir araştırması

Yıl 2025, Cilt: 31 Sayı: 2, 244 - 255, 29.04.2025

Cemre Candemir

Öz

İnsan beyninin karmaşıklıklarının anlayabilmek, fonksiyonel Manyetik Rezonans Görüntüleme (fMRG) gibi dinamik fonksiyonel nörogörüntüleme verilerinin titiz bir analizini gerektirir. Bu makale, fMRI çalışmalarında beyin aktivitesini araştırmak için iki güçlü analitik yaklaşımın (tam ve esnek faktöriyel analiz) uygulanmasını araştırmaktadır. İlk olarak, her yöntemin temel ilkeleri, güçlü yönleri ve sınırlamaları vurgulanarak geniş bir şekilde verilmektedir. Daha sonra tasarım yapıları, uyarlanabilirlik, veri karmaşıklığı, esneklik ve faktör etkileri bu bağlamda ele alınmaktadır. Teorik ve gerçek dünyadaki fMRI senaryolarından yararlanılarak, tam ve faktöriyel analizlerin basit ve karmaşık tasarımlarda faktör kombinasyonlarını nasıl sağladığı gösterilmiştir. Bu içgörülerden yola çıkarak, seçilen yaklaşımın her fMRI çalışmasının spesifik araştırma sorusu ve veri yapısı ile uyumlu hale getirilmesinin kritik rolü vurgulanmaktadır. Araştırmacılar bu istatistiksel analizleri, çeşitli deneysel tasarımlarla beyin aktivitesinin karmaşık yapısını ortaya çıkarmak için kullanabilirler. Tam ve esnek faktöriyel analizin benzersiz güçlü yönlerini ve sınırlamalarını sergileyen bu makale, araştırmacıların araştırmaları için doğru metodolojiyi seçmelerini amaçlamaktadır.

Anahtar Kelimeler

Beyin görüntüleme Faktöriyel tasarım fMRG analizi Tam faktöriyel Esnek faktöriyel

Kaynakça

  • [1] Bandettini PA. “Twenty years of functional MRI: The science and the stories”. NeuroImage, 62(2), 575588, 2012.
  • [2] Logothetis NK. “What we can do and what we cannot do with fMRI”. Nature, 453(7197), 869 -878, 2008.
  • [3] Bandettini PA, Birn RM, Donahue KM. Functional MRI: Background, Methodology, Limits, and Implementation. Editors: Cacioppo JT, Tassinary LT, Berntson GG. Handbook of Psychophysiology, 978-101, New York, US, Cambridge University Press, 2000.
  • [4] Ogawa S. “Finding the BOLD effect in brain images”. NeuroImage, 62(2), 608–609, 2012.
  • [5] Kiebel SJ, Holmes AP. The General Linear Model. Editors: Ashburner J, Friston KJ, Penny W. Human Brain Function, 2-58, 2nd ed, San Diago, California, USA, Academic Press, 2004.
  • [6] Monti MM, “Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach”. Frontiers in Human Neuroscience, 5, 1-13, 2011.
  • [7] Poldrack RA, Mumford JA, Nichols, TE. Handbook of Functional MRI Data Analysis. Cambridge: Cambridge University Press, 2011.
  • [8] Friston K, Price C. “Modules and brain mapping”. Cognitive Neuropsychology, 28, 41–50, 2011.
  • [9] Ischebeck A, Hiebel H, Miller J, Höfler M, Gilchrist ID, Körner C. “Target processing in overt serial visual search involves the dorsal attention network: A fixation-based event-related fMRI study”. Neuropsychologia, 153, 107763, 2021.
  • [10] Layher E, Santander T, Chakravarthula P, Marinsek N, Turner BO, Eckstein MP, Miller MB. “Widespread frontoparietal fMRI activity is greatly affected by changes in criterion placement, not discriminability, during recognition memory and visual detection tests”. NeuroImage, 279, 120307, 2023.
  • [11] Wang X, Xia Y, Yan R, Sun H, Huang Y, Zou H, Du Y, Hua L, Tang H, Zhou H, Yao Z, Lu Q. The sex differences in anhedonia in major depressive disorder: A resting-state fMRI study”. Journal of Affective Disorders, 340, 555–566, 2023.
  • [12] Fang Z, Wen H, Zhou Y, Gao X. “Comparisons are Odious? The neural basis of in-group and out-group social comparison among game players: An fMRI study”. Behavioral Brain Research, 458, 114735, 2024.
  • [13] Dobbelaar S, Achterberg M, Van Duijvenvoorde ACK, Van IJzendoorn MH, Crone EA. “Developmental patterns and individual differences in responding to social feedback: A longitudinal fMRI study from childhood to adolescence”. Developmental Cognitive Neuroscience, 62, 101264, 2023.
  • [14] Mazancieux A, Mauconduit F, Amadon A, Willem de Gee J, Donner TH, Meyniel F. “Brainstem fMRI signaling of surprise across different types of deviant stimuli”. Cell Representation, 42(11), 113405, 2023.
  • [15] Torrecuso R, Mueller K, Holiga S, Sieger T, Vymazal J, Ruzicka F, Roth J, Ruzicka E, Schroeter ML, Jech R, Möller HE. “Improving fMRI in Parkinson’s disease by accounting for brain region-specific activity patterns”. NeuroImage Clinical, 38, 103396, 2023.
  • [16] Murray R.J, Kreibig SD, Pehrs C, Vuilleumier P, Gross JJ, Samson AC. “Mixed emotions to social situations: An fMRI investigation”. NeuroImage, 271, 119973, 2023.
  • [17] Tomasino B, Maggioni E, Pianni MC, Bonivento C, D’Agostini S, Balestrieri M, Brambilla P. “The mental simulation of state/psychological stimuli in anxiety disorders: A 3T fMRI study”. Journal of Affective Disorders, 345, 435–442, 2024.
  • [18] Antony J. Design of Experiments for Engineers and Scientists. 3rd ed. Amsterdam, Elsevier, 2023.
  • [19] Güneş E, Cihan MT. “COD and color removal from wastewaters: optimization of fenton process”. Pamukkale University Journal of Engineering Science, 21(6), 239–247, 2015.
  • [20] Ashburner J. “SPM: A history”. NeuroImage, 62(2), 791–800, 2011.
  • [21] Ozkul B, Candemir C, Oguz K, Eroglu-Koc S, Kizilates-Evin G, Ugurlu O, Erdogan Y, Mull DD, Eker MC, Kitis O, Gonul AS. “Gradual Loss of Social Group Support during Competition Activates Anterior TPJ and Insula but Deactivates Default Mode Network”. Brain Science, 13, 1509, 2023.
  • [22] Candemir C, “A Practical Estimation of the Required Sample Size in fMRI Studies”. Mugla Journal of Science and Technology, 9(2), 56–63, 2023.

Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches

Yıl 2025, Cilt: 31 Sayı: 2, 244 - 255, 29.04.2025

Cemre Candemir

Öz

Understanding the intricacies of the human brain demands rigorous analysis of dynamic functional neuroimaging data like functional Magnetic Resonance Imaging (fMRI). This paper investigates the application of two powerful analytical approaches - full and flexible factorial analysis - for exploring brain activity in fMRI studies. First, the main principles of each method are given broadly, by highlighting their strengths and limitations. Then, design structures, adaptability, data complexity, flexibility, and factor effects are handled in this context. Utilizing theoretical and real-world fMRI scenarios, it is shown how full and factorial analyses provide the factor combinations in simple and complex designs. Drawing on these insights, the critical role of aligning the chosen approach with the specific research question and data structure of each fMRI study is emphasized. Researchers can use these statistical analyses to reveal the complex structure of brain activity by diverse experimental designs. By exhibiting the unique strengths and limitations of full and flexible factorial analysis, this paper aims for researchers to choose the right methodology for their research.

Anahtar Kelimeler

Brain imaging Factorial designs fMRI analysis Full factorial Flexible factorial

Kaynakça

  • [1] Bandettini PA. “Twenty years of functional MRI: The science and the stories”. NeuroImage, 62(2), 575588, 2012.
  • [2] Logothetis NK. “What we can do and what we cannot do with fMRI”. Nature, 453(7197), 869 -878, 2008.
  • [3] Bandettini PA, Birn RM, Donahue KM. Functional MRI: Background, Methodology, Limits, and Implementation. Editors: Cacioppo JT, Tassinary LT, Berntson GG. Handbook of Psychophysiology, 978-101, New York, US, Cambridge University Press, 2000.
  • [4] Ogawa S. “Finding the BOLD effect in brain images”. NeuroImage, 62(2), 608–609, 2012.
  • [5] Kiebel SJ, Holmes AP. The General Linear Model. Editors: Ashburner J, Friston KJ, Penny W. Human Brain Function, 2-58, 2nd ed, San Diago, California, USA, Academic Press, 2004.
  • [6] Monti MM, “Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach”. Frontiers in Human Neuroscience, 5, 1-13, 2011.
  • [7] Poldrack RA, Mumford JA, Nichols, TE. Handbook of Functional MRI Data Analysis. Cambridge: Cambridge University Press, 2011.
  • [8] Friston K, Price C. “Modules and brain mapping”. Cognitive Neuropsychology, 28, 41–50, 2011.
  • [9] Ischebeck A, Hiebel H, Miller J, Höfler M, Gilchrist ID, Körner C. “Target processing in overt serial visual search involves the dorsal attention network: A fixation-based event-related fMRI study”. Neuropsychologia, 153, 107763, 2021.
  • [10] Layher E, Santander T, Chakravarthula P, Marinsek N, Turner BO, Eckstein MP, Miller MB. “Widespread frontoparietal fMRI activity is greatly affected by changes in criterion placement, not discriminability, during recognition memory and visual detection tests”. NeuroImage, 279, 120307, 2023.
  • [11] Wang X, Xia Y, Yan R, Sun H, Huang Y, Zou H, Du Y, Hua L, Tang H, Zhou H, Yao Z, Lu Q. The sex differences in anhedonia in major depressive disorder: A resting-state fMRI study”. Journal of Affective Disorders, 340, 555–566, 2023.
  • [12] Fang Z, Wen H, Zhou Y, Gao X. “Comparisons are Odious? The neural basis of in-group and out-group social comparison among game players: An fMRI study”. Behavioral Brain Research, 458, 114735, 2024.
  • [13] Dobbelaar S, Achterberg M, Van Duijvenvoorde ACK, Van IJzendoorn MH, Crone EA. “Developmental patterns and individual differences in responding to social feedback: A longitudinal fMRI study from childhood to adolescence”. Developmental Cognitive Neuroscience, 62, 101264, 2023.
  • [14] Mazancieux A, Mauconduit F, Amadon A, Willem de Gee J, Donner TH, Meyniel F. “Brainstem fMRI signaling of surprise across different types of deviant stimuli”. Cell Representation, 42(11), 113405, 2023.
  • [15] Torrecuso R, Mueller K, Holiga S, Sieger T, Vymazal J, Ruzicka F, Roth J, Ruzicka E, Schroeter ML, Jech R, Möller HE. “Improving fMRI in Parkinson’s disease by accounting for brain region-specific activity patterns”. NeuroImage Clinical, 38, 103396, 2023.
  • [16] Murray R.J, Kreibig SD, Pehrs C, Vuilleumier P, Gross JJ, Samson AC. “Mixed emotions to social situations: An fMRI investigation”. NeuroImage, 271, 119973, 2023.
  • [17] Tomasino B, Maggioni E, Pianni MC, Bonivento C, D’Agostini S, Balestrieri M, Brambilla P. “The mental simulation of state/psychological stimuli in anxiety disorders: A 3T fMRI study”. Journal of Affective Disorders, 345, 435–442, 2024.
  • [18] Antony J. Design of Experiments for Engineers and Scientists. 3rd ed. Amsterdam, Elsevier, 2023.
  • [19] Güneş E, Cihan MT. “COD and color removal from wastewaters: optimization of fenton process”. Pamukkale University Journal of Engineering Science, 21(6), 239–247, 2015.
  • [20] Ashburner J. “SPM: A history”. NeuroImage, 62(2), 791–800, 2011.
  • [21] Ozkul B, Candemir C, Oguz K, Eroglu-Koc S, Kizilates-Evin G, Ugurlu O, Erdogan Y, Mull DD, Eker MC, Kitis O, Gonul AS. “Gradual Loss of Social Group Support during Competition Activates Anterior TPJ and Insula but Deactivates Default Mode Network”. Brain Science, 13, 1509, 2023.
  • [22] Candemir C, “A Practical Estimation of the Required Sample Size in fMRI Studies”. Mugla Journal of Science and Technology, 9(2), 56–63, 2023.
Toplam 22 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Yazılımı
Bölüm Makale
Yazarlar

Cemre Candemir

Yayımlanma Tarihi 29 Nisan 2025
Gönderilme Tarihi 22 Şubat 2024
Kabul Tarihi 18 Mayıs 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 31 Sayı: 2

Kaynak Göster

APA Candemir, C. (2025). Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 31(2), 244-255.
AMA Candemir C. Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. Nisan 2025;31(2):244-255.
Chicago Candemir, Cemre. “Factorial Designs in FMRI Analysis: A Comparative Exploration of Full and Flexible Factorial Approaches”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31, sy. 2 (Nisan 2025): 244-55.
EndNote Candemir C (01 Nisan 2025) Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31 2 244–255.
IEEE C. Candemir, “Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 31, sy. 2, ss. 244–255, 2025.
ISNAD Candemir, Cemre. “Factorial Designs in FMRI Analysis: A Comparative Exploration of Full and Flexible Factorial Approaches”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31/2 (Nisan 2025), 244-255.
JAMA Candemir C. Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025;31:244–255.
MLA Candemir, Cemre. “Factorial Designs in FMRI Analysis: A Comparative Exploration of Full and Flexible Factorial Approaches”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 31, sy. 2, 2025, ss. 244-55.
Vancouver Candemir C. Factorial designs in fMRI analysis: A comparative exploration of full and flexible factorial approaches. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025;31(2):244-55.





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