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FMRI hemodynamic response function (HRF) as a novel marker of brain function: applications for understanding obsessive-compulsive disorder pathology and treatment response

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Abstract

The hemodynamic response function (HRF) represents the transfer function linking neural activity with the functional MRI (fMRI) signal, modeling neurovascular coupling. Since HRF is influenced by non-neural factors, to date it has largely been considered as a confound or has been ignored in many analyses. However, underlying biophysics suggests that the HRF may contain meaningful correlates of neural activity, which might be unavailable through conventional fMRI metrics. Here, we estimated the HRF by performing deconvolution on resting-state fMRI data from a longitudinal sample of 25 healthy controls scanned twice and 44 adults with obsessive-compulsive disorder (OCD) before and after 4-weeks of intensive cognitive-behavioral therapy (CBT). HRF response height, time-to-peak and full-width at half-maximum (FWHM) in OCD were abnormal before treatment and normalized after treatment in regions including the caudate. Pre-treatment HRF predicted treatment outcome (OCD symptom reduction) with 86.4% accuracy, using machine learning. Pre-treatment HRF response height in the caudate head and time-to-peak in the caudate tail were top-predictors of treatment response. Time-to-peak in the caudate tail, a region not typically identified in OCD studies using conventional fMRI activation or connectivity measures, may carry novel importance. Additionally, pre-treatment response height in caudate head predicted post-treatment OCD severity (R = -0.48, P = 0.001), and was associated with treatment-related OCD severity changes (R = -0.44, P = 0.0028), underscoring its relevance. With HRF being a reliable marker sensitive to brain function, OCD pathology, and intervention-related changes, these results could guide future studies towards novel discoveries not possible through conventional fMRI approaches like standard BOLD activation or connectivity.

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References

  • Aguirre, G. K., Zarahn, E., & D'esposito, M. (1998). The variability of human, BOLD hemodynamic responses. Neuroimage, 8(4), 360–369.

    Article  CAS  PubMed  Google Scholar 

  • Amico, E., Gomez, F., Di Perri, C., Vanhaudenhuyse, A., Lesenfants, D., Boveroux, P., Bonhomme, V., Brichant, J. F., Marinazzo, D., & Laureys, S. (2014). Posterior cingulate cortex-related co-activation patterns: a resting state FMRI study in propofol-induced loss of consciousness. PLoS One, 9(6), e100012.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Anticevic, A., Hu, S., Zhang, S., Savic, A., Billingslea, E., Wasylink, S., Repovs, G., Cole, M., Bednarski, S., Krystal, J., Bloch, M., Li, C.-S., & Pittenger, C. (2014). Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder. Biological Psychiatry, 75, 595–605.

    Article  PubMed  Google Scholar 

  • Apostolova, I., Block, S., Buchert, R., Osen, B., Conradi, M., Tabrizian, S., Gensichen, S., Schroder-Hartwig, K., Fricke, S., Rufer, M., Weiss, A., Hand, I., Clausen, M., & Obrocki, J. (2010). Effects of behavioral therapy or pharmacotherapy on brain glucose metabolism in subjects with obsessive–compulsive disorder as assessed by brain FDG PET. Psychiatry Research: Neuroimaging, 184, 105–116.

    Article  CAS  PubMed  Google Scholar 

  • Arbabshirani, M., Plis, S., Sui, J., & Calhoun, V. (2017). Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage, 145(Pt B), 137–165.

    Article  PubMed  Google Scholar 

  • Arcaro, M., Pinsk, M., & Kastner, S. (2015). The anatomical and functional Organization of the Human Visual Pulvinar. Journal of Neuroscience, 35(27), 9848–9871.

    Article  CAS  PubMed  Google Scholar 

  • Aylward, E., Sparks, B., Field, K., Yallapragada, V., Shpritz, B., Rosenblatt, A., Brandt, J., Gourley, L. M., Liang, K., Zhou, H., Margolis, R. L., & Ross, C. A. (2004). Onset and rate of striatal atrophy in preclinical Huntington disease. Neurology, 63(1), 66–72.

  • Banca, P., Voon, V., Vestergaard, M., Philipiak, G., Almeida, I., Pocinho, F., et al. (2015). Imbalance in habitual versus goal directed neural systems during symptom provocation in obsessive-compulsive disorder. Brain, 138(Pt 3), 798–811.

    Article  PubMed Central  PubMed  Google Scholar 

  • Behzadi, Y., Restom, K., Liau, J., & Liu, T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage, 37(1), 90–101.

    Article  PubMed  Google Scholar 

  • Beucke, J., Sepulcre, J., Talukdar, T., Linnman, C., Zschenderlein, K., Endrass, T., Kaufmann, C., & Kathmann, N. (2013). Abnormally high degree connectivity of the orbitofrontal cortex in obsessive-compulsive disorder. JAMA Psychiatry, 70(6), 619–629.

    Article  PubMed  Google Scholar 

  • Biessmann, F., Murayama, Y., Logothetis, N., Müller, K., & Meinecke, F. (2012). Improved decoding of neural activity from fMRI signals using non-separable spatiotemporal deconvolutions. Neuroimage, 61(4), 1031–1042.

    Article  PubMed  Google Scholar 

  • Boly, M., Sasai, S., Gosseries, O., Oizumi, M., Casali, A., Massimini, M., & Tononi, G. (2015). Stimulus set meaningfulness and neurophysiological differentiation: a functional magnetic resonance imaging study. PLoS One, 10(5), e0125337.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Brennan, B., Rauch, S., Jensen, J., & Pope, H. (2013). A critical review of magnetic resonance spectroscopy studies of obsessive-compulsive disorder. Biological Psychiatry, 73(1), 24–31.

    Article  PubMed  Google Scholar 

  • Brown, G. G., Eyler Zorrilla, L. T., Georgy, B., Kindermann, S. S., Wong, E. C., & Buxton, R. B. (2003). BOLD and perfusion response to finger-thumb apposition after acetazolamide administration: Differential relationship to global perfusion. Journal of Cerebral Blood Flow and Metabolism, 23(7), 829–837.

    Article  CAS  PubMed  Google Scholar 

  • Busija, D. W., Bari, F., Domoki, F., & Louis, T. (2007). Mechanisms involved in the cerebrovascular dilator effects of N-methyl-d-aspartate in cerebral cortex. Brain Research Reviews, 56(1), 89–100.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Buxton, R. (2002). Introduction to functional magnetic resonance imaging: principles and techniques. Energy, 24(2), xi 523

  • Buxton, R., Wong, E., & Frank, L. (1998). Dynamics of blood flow and oxygenation changes during brain activation: The balloon model. Magnetic Resonance in Medicine, 39(6), 855–864.

    Article  CAS  PubMed  Google Scholar 

  • Buzsáki, G., Kaila, K., & Raichle, M. (2007). Inhibition and brain work. Neuron, 56(5), 771–783.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Chen, J., & Glover, G. (2015). BOLD fractional contribution to resting-state functional connectivity above 0.1 Hz. Neuroimage, 107, 207–218.

    Article  PubMed  Google Scholar 

  • Cheng, Y., Xu, J., Nie, B., Luo, C., Yang, T., Li, H., Lu, J., Xu, L., Shan, B., & Xu, X. (2013). Abnormal resting-state activities and functional connectivities of the anterior and the posterior cortexes in medication-naïve patients with obsessive-compulsive disorder. PLoS One, 8(6), e67478.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Cohen, Z., Bonvento, G., Lacombe, P., & Hamel, E. (1996). Serotonin in the regulation of brain microcirculation. Progress in Neurobiology, 50(4), 335–362.

    Article  CAS  PubMed  Google Scholar 

  • Craddock, R., Holtzheimer III, P., Hu, X., & Mayberg, H. (2009). Disease state prediction from resting state functional connectivity. Magnetic Resonance in Medicine, 62(6), 1619–1628.

    Article  PubMed Central  PubMed  Google Scholar 

  • David, O., Guillemain, I., Saillet, S., Reyt, S., Deransart, S., Segebarth, C., & Depaulis, A. (2008). Identifying neural drivers with functional MRI: An electrophysiological validation. PLoS Biology, 23(6), 2683–2697.

    Google Scholar 

  • Deshpande, G., Sathian, K., & Hu, X. (2010a). Effect of hemodynamic variability on granger causality analysis of fMRI. Neuroimage, 52(3), 884–896.

    Article  PubMed  Google Scholar 

  • Deshpande, G., Li, Z., Santhanam, P., Coles, C., Lynch, M., Hamann, S., & Hu, X. (2010b). Recursive cluster elimination based support vector machine for disease state prediction using resting state functional and effective brain connectivity. PLoS One, 5(12), e14277.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Duarte, J., Pereira, J., Quendera, B., Raimundo, M., Moreno, C., Gomes, L., Carrilho, F., & Castelo-Branco, M. (2015). Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: An fMRI study. Journal of Cerebral Blood Flow and Metabolism, 35(10), 1671–1680.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Feng, C., Deshpande, G., Liu, C., Gu, R., Luo, Y.-J., & Krueger, F. (2015). Diffusion of responsibility attenuates altruistic punishment: A functional magnetic resonance imaging effective connectivity study. Human Brain Mapping, 37(2), 663–677.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Friston, K., Harrison, L., & Penny, W. (2013). Dynamic causal modelling. Neuroimage, 19(4), 1273–1302.

    Article  Google Scholar 

  • Glover, G. (1999). Deconvolution of impulse response in event-related BOLD fMRI. Neuroimage, 9(4), 416–429.

    Article  CAS  PubMed  Google Scholar 

  • Golestani, A., Wei, L., & Chen, J. (2016). Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults. Neuroimage, 138, 147–163.

    Article  PubMed  Google Scholar 

  • Goodman, W., Price, L., Rasmussen, S., Mazure, C., Fleischmann, R., Hill, C., Heninger, G., & Charney, D. (1989). The Yale-Brown obsessive compulsive scale. I. Development, use, and reliability. Archives of General Psychiatry, 46(11), 1006–1011.

  • Goozée, R., Handley, R., Kempton, M., & Dazzan, P. (2014). A systematic review and meta-analysis of the effects of antipsychotic medications on regional cerebral blood flow (rCBF) in schizophrenia: Association with response to treatment. Neuroscience and Biobehavioral Reviews, 43, 118–136.

    Article  CAS  PubMed  Google Scholar 

  • Grant, M., Wood, K., Sreenivasan, K., Wheelock, M., White, D., Thomas, J., Knight, D., & Deshpande, G. (2015). Influence of early life stress on intra- and extra-amygdaloid causal connectivity. Neuropsychopharmacology, 40(7), 1782–1793.

    Article  PubMed Central  PubMed  Google Scholar 

  • Grieder, M., Crinelli, R., Jann, K., Federspiel, A., Wirth, M., Koenig, T., Stein, M., Wahlund, L., & Dierks, T. (2013). Correlation between topographic N400 anomalies and reduced cerebral blood flow in the anterior temporal lobes of patients with dementia. Journal of Alzheimer's Disease, 36(4), 711–731.

    Article  PubMed  Google Scholar 

  • Gürsel, D., Avram, M., Sorg, C., Brandl, F., & Koch, K. (2018). Frontoparietal areas link impairments of large-scale intrinsic brain networks with aberrant fronto-striatal interactions in OCD: A meta-analysis of resting-state functional connectivity. Neuroscience and Biobehavioral Reviews, 87, 151–160.

    Article  PubMed  Google Scholar 

  • Halani, S., Kwinta, J., Golestani, A., Khatamian, Y., & Chen, J. (2015). Comparing cerebrovascular reactivity measured using BOLD and cerebral blood flow MRI: The effect of basal vascular tension on vasodilatory and vasoconstrictive reactivity. Neuroimage, 110, 110–123.

    Article  PubMed  Google Scholar 

  • Hamilton, J., Farmer, M., Fogelman, P., & Gotlib, I. (2015). Depressive rumination, the default-mode network, and the dark matter of clinical neuroscience. Biological Psychiatry, 78, 224–230.

    Article  PubMed Central  PubMed  Google Scholar 

  • Hampstead, B., Khoshnoodi, M., Yan, W., Deshpande, G., & Sathian, K. (2016). Patterns of effective connectivity between memory encoding and retrieval differ between patients with mild cognitive impairment and healthy older adults. NeuroImage, 124(A), 997–1008.

    Article  CAS  PubMed  Google Scholar 

  • Handwerker, D. A., Ollinger, J. M., & D’Esposito, M. (2004). Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses. Neuroimage, 21(4), 1639–1651.

    Article  PubMed  Google Scholar 

  • Handwerker, D. A., Gonzalez-Castillo, J., D'Esposito, M., & Bandettini, P. A. (2012). The continuing challenge of understanding and modeling hemodynamic variation in fMRI. Neuroimage, 62(2), 1017–1023.

    Article  PubMed  Google Scholar 

  • Havlicek, M., Jan, J., Brazdil, M., & Calhoun, V. (2010). Dynamic granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data. Neuroimage, 53(1), 65–77.

    Article  PubMed  Google Scholar 

  • Havlicek, M., Friston, K. J., Jan, J., Brazdil, M., & Calhoun, V. D. (2011). Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering. Neuroimage, 56(4), 2109–2128.

    Article  PubMed  Google Scholar 

  • Hou, J.-M., Zhao, M., Zhang, W., Song, L.-H., Wu, W.-J., Wang, J., Zhou, D.-Q., Xie, B., He, M., Guo, J.-W., Qu, W., & Li, H.-T. (2014). Resting-state functional connectivity abnormalities in patients with obsessive–compulsive disorder and their healthy first-degree relatives. Journal of Psychiatry and Neuroscience, 39(5), 304–311.

    Article  PubMed Central  PubMed  Google Scholar 

  • Johnson, A., & Paulsen, J. (2014). Understanding behavior. In D. Lovecky & K. Tarapata (Eds.), Huntington’s disease: A guide for professionals. New York: Huntington’s Disease Society of America.

    Google Scholar 

  • Kim, J., & Ress, D. (2016). Arterial impulse model for the BOLD response to brief neural activation. Neuroimage, 124(Pt A), 394–408.

    Article  PubMed  Google Scholar 

  • Kim, H., Ghazizadeh, A., & Hikosaka, O. (2014). Separate groups of dopamine neurons innervate caudate head and tail encoding flexible and stable value memories. Frontiers in Neuroanatomy, 8, 120.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lacey, S., Stilla, R., Sreenivasan, K., Deshpande, G., & Sathian, K. (2014). Spatial imagery in haptic shape perception. Neuropsychologia, 60, 144–158.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lamichhane, B., Adhikari, B. M., Brosnan, S. F., & Dhamala, M. (2014). The neural basis of perceived unfairness in economic exchanges. Brain Connectivity, 4(8), 619–630.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lanka, P., Rangaprakash, D., Dretsch, M. N., Katz, J. S., Denney, T. S., Jr., & Deshpande, G. (2019). Supervised machine learning for diagnostic classification from large-scale neuroimaging datasets. Brain imaging and behavior. https://doi.org/10.1007/s11682-019-00191-8

    Article  Google Scholar 

  • Lemke, H., de Castro, A., Schlattmann, P., Heuser, I., & Neu, P. (2010). Cerebrovascular reactivity over time-course - from major depressive episode to remission. Journal of Psychiatry Research, 44(3), 132–136.

    Article  Google Scholar 

  • Len, T. K., & Neary, J. P. (2011). Cerebrovascular pathophysiology following mild traumatic brain injury. Clinical Psychology and Functional Imaging, 31(2), 85–93.

    CAS  Google Scholar 

  • Levin, J., Ross, M., Mendelson, J., Kaufman, M., Lange, N., Maas, L., Mello, N., Cohen, B., & Renshaw, P. (1998). Reduction in BOLD fMRI response to primary visual stimulation following alcohol ingestion. Psychiatry Research, 82(3), 135–146.

    Article  CAS  PubMed  Google Scholar 

  • Libero, L., DeRamus, T., Lahti, A., Deshpande, G., & Kana, R. (2015). Multimodal neuroimaging based classification of autism spectrum disorder using anatomical, neurochemical, and white matter correlates. Cortex, 66, 46–59.

    Article  PubMed Central  PubMed  Google Scholar 

  • Liu, F., Zhuo, C., & Yu, C. (2016). Altered Cerebral Blood Flow Covariance Network in Schizophrenia. Frontiers in neuroscience, 10, 308.

    PubMed Central  PubMed  Google Scholar 

  • Maia, T., Cooney, R., & Peterson, B. (2008). The neural bases of obsessive-compulsive disorder in children and adults. Development and Psychopathology, 20(4), 1251–1283.

    Article  PubMed Central  PubMed  Google Scholar 

  • Maltby, N., Tolin, D., Worhunsky, P., O’Keefe, T., & Kiehl, K. (2005). Dysfunctional action monitoring hyperactivates frontal–striatal circuits in obsessive–compulsive disorder: An event-related fMRI study. Neuroimage, 24, 495–503.

    Article  PubMed  Google Scholar 

  • Marinazzo, D. (2013). “Code for HRF blind deconvolution,” [Online]. Available: http://users.ugent.be/~dmarinaz/HRF_deconvolution.html. [Accessed Sept 2016].

  • Mataix-Cols, D., Fernández de la Cruz, L., Nordsletten, A., Lenhard, F., Isomura, K., & Simpson, H. (2016). Towards an international expert consensus for defining treatment response, remission, recovery and relapse in obsessive-compulsive disorder. World Psychiatry, 15(1), 80–81.

  • McDonough, I., Bender, A., Patihis, L., Stinson, E., Letang, S. & Miller, W. (2019). The trouble interpreting fMRI studies in populations with cerebrovascular risk: the use of a subject-specific hemodynamic response function in a study of age, vascular risk, and memory. bioRxiv, https://doi.org/10.1101/512343

  • Menzies, L., Chamberlain, S., Laird, A., Thelen, S., Sahakian, B., & Bullmore, E. (2008). Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: The orbitofronto-striatal model revisited. Neuroscience and Biobehavioral Reviews, 32(3), 525–549.

    Article  PubMed  Google Scholar 

  • Miezin, F., Maccotta, L., Ollinger, J., Petersen, S., & Buckner, R. (2000). Characterizing the hemodynamic response: Effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing. Neuroimage, 11(6 Pt 1), 735–759.

    Article  CAS  PubMed  Google Scholar 

  • Milad, M., Furtak, S., Greenberg, J., Keshaviah, A., Im, J., Falkenstein, M., Jenike, M., Rauch, S., & Wilhelm, S. (2013). Deficits in conditioned fear extinction in obsessive-compulsive disorder and neurobiological changes in the fear circuit. JAMA Psychiatry, 70(6), 608–618.

    Article  PubMed  Google Scholar 

  • Mintzopoulos, D., Gillis, T., Robertson, H., Dalia, T., Feng, G., Rauch, S., & Kaufman, M. (2016). Striatal magnetic resonance spectroscopy abnormalities in young adult SAPAP3 knockout mice. Biol Psychiatry Cogn Neurosci Neuroimaging., 1(1), 39–48.

    PubMed Central  PubMed  Google Scholar 

  • Moody, T., Morfini, F., Cheng, G., Sheen, C., Tadayonnejad, R., Reggente, N., O'Neill, J., & Feusner, J. (2017). Mechanisms of cognitive-behavioral therapy for obsessive-compulsive disorder involve robust and extensive increases in brain network connectivity. Translational Psychiatry, 7(9), e1230.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Morris, L., Baek, K., & Voon, V. (2017). Distinct cortico-striatal connections with subthalamic nucleus underlie facets of compulsivity. Cortex, 88, 143–150.

    Article  PubMed Central  PubMed  Google Scholar 

  • Muthukumaraswamy, S. D., Evans, C. J., Edden, R. A., Wise, R. G., & Singh, K. D. (2012). Individual variability in the shape and amplitude of the BOLD-HRF correlates with endogenous GABAergic inhibition. Human Brain Mapping, 33(2), 455–465.

    Article  PubMed  Google Scholar 

  • Nakatani, E., Nakgawa, A., Ohara, Y., Goto, S., Uozumi, N., Iwakiri, M., Yamamoto, Y., Motomura, K., Iikura, Y., & Yamagami, T. (2003). Effects of behavior therapy on regional cerebral blood flow in obsessive–compulsive disorder. Psychiatry Research: Neuroimaging, 124, 113–120.

    Article  PubMed  Google Scholar 

  • Niu, Q., Yang, L., Song, X., Chu, C., Liu, H., Zhang, L., Li, Y., Zhang, X., Cheng, J., & Li, Y. (2017). Abnormal resting-state brain activities in patients with first-episode obsessive-compulsive disorder. Neuropsychiatric Disease and Treatment, 13, 507–513.

    Article  PubMed Central  PubMed  Google Scholar 

  • Noseworthy, M., Alfonsi, J., & Bells, S. (2003). Attenuation of brain BOLD response following lipid ingestion. Human Brain Mapping, 20(2), 116–121.

    Article  PubMed Central  PubMed  Google Scholar 

  • O’Neill, J., Lai, T., Sheen, C., Salgari, G., Ly, R., Armstrong, C., Chang, S., Levitt, J., Salamon, N., Alger, J., & Feusner, J. (2016). Cingulate and thalamic metabolites in obsessive-compulsive disorder. Psychiatry Research, 254, 34–40.

    Article  PubMed Central  PubMed  Google Scholar 

  • Olatunji, B., Ferreira-Garcia, R., Caseras, X., Fullana, M., Wooderson, S., Speckens, A., Lawrence, N., Giampietro, V., Brammer, M., Phillips, M., Fontenelle, L., & Mataix-Cols, D. (2014). Predicting response to cognitive behavioral therapy in contamination-based obsessive-compulsive disorder from functional magnetic resonance imaging. Psychological Medicine, 44(10), 2125–2137.

    Article  CAS  PubMed  Google Scholar 

  • O'Neill, J., & Feusner, J. (2015). Cognitive-behavioral therapy for obsessive-compulsive disorder: Access to treatment, prediction of long-term outcome with neuroimaging. Psychology Research and Behavior Management, 8, 211–223.

    Article  PubMed Central  PubMed  Google Scholar 

  • Power, J. D., Schlaggar, B. L., & Petersen, S. E. (2015). Recent progress and outstanding issues in motion correction in resting state fMRI. Neuroimage, 105, 536–551.

    Article  PubMed  Google Scholar 

  • Qiu, L., Fu, X., Wang, S., Tang, Q., Chen, X., Cheng, L., Zhang, F., Zhou, Z., & Tian, L. (2017). Abnormal regional spontaneous neuronal activity associated with symptom severity in treatment-naive patients with obsessive-compulsive disorder revealed by resting-state functional MRI. Neuroscience Letters, 640, 99–104.

    Article  CAS  PubMed  Google Scholar 

  • Raemaekers, M., du Plessis, S., Ramsey, N., Weusten, J., & Vink, M. (2012). Test-retest variability underlying fMRI measurements. Neuroimage, 60(1), 717–727.

    Article  CAS  PubMed  Google Scholar 

  • Rangaprakash, D., Deshpande, G., Daniel, T., Goodman, A., Robinson, J., Salibi, N., Katz, J., Denney, T., & Dretsch, M. (2017a). Compromised hippocampus-striatum pathway as a potential imaging biomarker of mild traumatic brain injury and posttraumatic stress disorder. Human Brain Mapping, 38(6), 2843–2864.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Rangaprakash, D., Dretsch, M. N., Yan, W., Katz, J. S., Denney, T. S., & Deshpande, G. (2017b). Hemodynamic variability in soldiers with trauma: Implications for functional MRI connectivity studies. NeuroImage: Clinical, 16, 409–417.

    Article  CAS  Google Scholar 

  • Rangaprakash, D., Dretsch, M. N., Yan, W., Katz, J. S., Denney, T. S., & Deshpande, G. (2017c). Hemodynamic response function parameters obtained from resting-state functional MRI data in soldiers with trauma. Data in Brief, 14, 558–562.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Rangaprakash, D., Dretsch, M., Venkatraman, A., Katz, J., Denney, T., & Deshpande, G. (2018a). Identifying disease foci from static and dynamic effective connectivity networks: Illustration in soldiers with trauma. Human Brain Mapping, 39(1), 264–287.

    Article  CAS  PubMed  Google Scholar 

  • Rangaprakash, D., Wu, G.-R., Marinazzo, D., Hu, X., & Deshpande, G. (2018b). Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity. Magnetic Resonance in Medicine, 80(4), 1697–1713.

  • Rasgon, A., Lee, W., Leibu, E., Laird, A., Glahn, D., Goodman, W., & Frangou, S. (2017). Neural correlates of affective and non-affective cognition in obsessive compulsive disorder: A meta-analysis of functional imaging studies. European Psychiatry, 46, 25–32.

    Article  CAS  PubMed  Google Scholar 

  • Rauch, S., Whalen, P., Savage, C., Curran, T., Kendrick, A., Brown, H., Bush, G., Breiter, H., & Rosen, B. (1997). Striatal recruitment during an implicit sequence learning task as measured by functional magnetic resonance imaging. Human Brain Mapping, 5(2), 124–132.

    Article  CAS  PubMed  Google Scholar 

  • Reynell, C., & Harris, J. (2013). The BOLD signal and neurovascular coupling in autism. Developmental Cognitive Neuroscience, 6, 72–79.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ryali, S., Supekar, K., Chen, T., & Menon, V. (2011). Multivariate dynamical systems models for estimating causal interactions in fMRI. Neuroimage, 54(2), 807–823.

    Article  PubMed  Google Scholar 

  • Ryali, S., Chen, T., Supekar, K., Tu, T., Kochalka, J., Cai, W., & Menon, V. (2016a). Multivariate dynamical systems-based estimation of causal brain interactions in fMRI: Group-level validation using benchmark data, neurophysiological models and human connectome project data. Journal of Neuroscience Methods, 268, 142–153.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ryali, S., Shih, Y., Chen, T., Kochalka, J., Albaugh, D., Fang, Z., Supekar, K., Lee, J., & Menon, V. (2016b). Combining optogenetic stimulation and fMRI to validate a multivariate dynamical systems model for estimating causal brain interactions. Neuroimage, 132, 398–405.

    Article  PubMed  Google Scholar 

  • Saad, Z. S., Gotts, S. J., Murphy, K., Chen, G., Jo, H. J., Martin, A., & Cox, R. W. (2012). Trouble at rest: How correlation patterns and group differences become distorted after global signal regression. Brain Connectivity, 2(1), 25–32.

    Article  PubMed Central  PubMed  Google Scholar 

  • Saxena, S., & Rauch, S. (2000). Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder. The Psychiatric Clinics of North America, 23(3), 563–586.

    Article  CAS  PubMed  Google Scholar 

  • Saxena, S., Gorbis, E., O'Neill, J., Baker, S., Mandelkern, M., Maidment, K., Chang, S., Salamon, N., Brody, A., Schwartz, J., & London, E. (2009). Rapid effects of brief intensive cognitive-behavioral therapy on brain glucose metabolism in obsessive-compulsive disorder. Molecular Psychiatry, 14(2), 197–205.

    Article  CAS  PubMed  Google Scholar 

  • Seger, C., & Cincotta, C. (2005). The roles of the caudate nucleus in human classification learning. Journal of Neuroscience, 25(11), 2941–2951.

    Article  CAS  PubMed  Google Scholar 

  • Sreenivasan, K., Havlicek, M., & Deshpande, G. (2015). Non-parametric hemodynamic deconvolution of fMRI using homomorphic filtering. IEEE Transactions on Medical Imaging, 34(5), 1155–1163.

    Article  PubMed  Google Scholar 

  • Stern, E., Fitzgerald, K., Welsh, R., Abelson, J., & Taylor, S. (2012). Resting-state functional connectivity between fronto-parietal and default mode networks in obsessive-compulsive disorder. PLoS One, 7(5), e36356.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Tadayonnejad, R., Yang, S., Kumar, A., & Ajilore, O. (2015). Clinical, cognitive, and functional connectivity correlations of resting-state intrinsic brain activity alterations in unmedicated depression. Journal of Affective Disorders, 172, 241–250.

    Article  PubMed  Google Scholar 

  • Tagliazucchi, E., Balenzuela, P., Fraiman, D., & Chialvo, D. R. (2012). Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis. Frontiers in physiology, 3, 15.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tang, W., Zhu, Q., Gong, X., Zhu, C., Wang, Y., & Chen, S. (2016). Cortico-striato-thalamo-cortical circuit abnormalities in obsessive-compulsive disorder: A voxel-based morphometric and fMRI study of the whole brain. Behavioural Brain Research, 313, 17–22.

    Article  PubMed  Google Scholar 

  • Taylor, A., Kim, J., & Ress, D. (2018). Characterization of the hemodynamic response function across the majority of human cerebral cortex. Neuroimage, 173, 322–331.

    Article  PubMed  Google Scholar 

  • van den Heuvel, O., van Wingen, G., Soriano-Mas, C., Alonso, P., Chamberlain, S., Nakamae, T., Denys, D., Goudriaan, A., & Veltman, D. (2016). Brain circuitry of compulsivity. European Neuropsychopharmacology, 26(5), 810–827.

    Article  CAS  PubMed  Google Scholar 

  • van der Straten, A. L., Denys, D., & van Wingen, G. A. (2017). Impact of treatment on resting cerebral blood flow and metabolism in obsessive compulsive disorder: a meta-analysis. Scientific reports, 7(1), 17464.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Wang, Y., Katwal, S., Rogers, B., Gore, J., & Deshpande, G. (2017a). Experimental Validation of Dynamic Granger Causality for Inferring Stimulus-Evoked Sub-100 ms Timing Differences from fMRI. IEEE transactions on neural systems and rehabilitation engineering, 25(6), 539–546.

  • Wang, Y., David, O., Hu, X., & Deshpande, G. (2017b). Can Patel’s τ accurately estimate directionality of connections in brain networks from fMRI? Magnetic Resonance in Medicine, 78(5), 2003–2010.

  • Wen, S., Cheng, M., Cheng, M., Yue, J., Li, J., & Xie, L. (2014). Neurocognitive dysfunction and regional cerebral blood flow in medically naïve patients with obsessive-compulsive disorder. Developmental Neuropsychology, 39(1), 37–50.

    Article  CAS  PubMed  Google Scholar 

  • Wu, G., Liao, W., Stramaglia, S., Ding, J., Chen, H., & Marinazzo, D. (2013). A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data. Medical Image Analysis, 17(3), 365–374.

    Article  PubMed  Google Scholar 

  • Yamanishi, T., Nakaaki, S., Omori, I., Hashimoto, N., Shinagawa, Y., Hongo, J., Horikoshi, M., Tohyama, J., Akechi, T., Soma, T., Iidaka, T., & Furukawa, T. (2009). Changes after behavior therapy among responsive and nonresponsive patients with obsessive–compulsive disorder. Psychiatry Research: Neuroimaging, 172, 242–250.

    Article  PubMed  Google Scholar 

  • Yan, W., Rangaprakash, D., & Deshpande, G. (2018a). Estimated hemodynamic response function parameters obtained from resting state BOLD fMRI signals in subjects with autism spectrum disorder and matched healthy subjects. Data in brief, 19, 1305–1309

  • Yan, W., Rangaprakash, D., & Deshpande, G. (2018b). Aberrant hemodynamic responses in autism: Implications for resting state fMRI functional connectivity studies. NeuroImage: Clinical, 19, 320–330.

    Article  Google Scholar 

  • Yang, X.-Y., Sun, J., Luo, J., Zhong, Z.-X., Li, P., Yao, S.-M., Xiong, H.-F., Huang, F.-F., & Li, Z.-J. (2015). Regional homogeneity of spontaneous brain activity in adult patients with obsessive–compulsive disorder before and after cognitive behavioural therapy. Journal of Affective Disorders, 188, 243–251.

    Article  PubMed  Google Scholar 

  • Zuo, X., Di Martino, A., Kelly, C., Shehzad, Z., Gee, D., Klein, D., Castellanos, F., Biswal, B., & Milham, M. (2010). The oscillating brain: Complex and reliable. Neuroimage, 49(2), 1432–1445.

    Article  PubMed  Google Scholar 

  • Zürcher, N., Bhanot, A., McDougle, C., & Hooker, J. (2015). A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neuroscience and Biobehavioral Reviews, 52, 56–73.

    Article  PubMed  Google Scholar 

  • Zurowski, B., Kordon, A., Weber-Fahr, W., Voderholzer, U., Kuelz, A., Freyer, T., Wahl, K., Büchel, C., & Hohagen, F. (2012). Relevance of orbitofrontal neurochemistry for the outcome of cognitive-behavioural therapy in patients with obsessive–compulsive disorder. European Archives of Psychiatry and Clinical Neuroscience, 262(7), 617–624.

    Article  PubMed  Google Scholar 

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Acknowledgements

We acknowledge Michelle Massi and Natalie Abrahami for their role in providing cognitive-behavioral therapy treatment for the participants with obsessive-compulsive disorder in this study.

Funding

This study was supported by US National Institutes of Mental Health (NIMH) grant R01 MH085900 (to Drs. Feusner and O’Neill).

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Correspondence to Jamie D. Feusner.

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All the authors (D.R., R.T., G.D, J.O., J.D.F.) declare no conflicts of interest.

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All procedures involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. UCLA institutional review board (IRB) approved the study procedures.

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Written informed consent was obtained from all individual participants included in the study.

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Rangaprakash, D., Tadayonnejad, R., Deshpande, G. et al. FMRI hemodynamic response function (HRF) as a novel marker of brain function: applications for understanding obsessive-compulsive disorder pathology and treatment response. Brain Imaging and Behavior 15, 1622–1640 (2021). https://doi.org/10.1007/s11682-020-00358-8

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