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1 Resting-state fMRI: Algorithms and Applications to Brain Disorders ZANG Yu-Feng 臧玉峰 M.D. YAN Chao-Gan 严超赣 Ph. D. State.

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Presentation on theme: "1 Resting-state fMRI: Algorithms and Applications to Brain Disorders ZANG Yu-Feng 臧玉峰 M.D. YAN Chao-Gan 严超赣 Ph. D. State."— Presentation transcript:

1 1 Resting-state fMRI: Algorithms and Applications to Brain Disorders ZANG Yu-Feng 臧玉峰 M.D. YAN Chao-Gan 严超赣 Ph. D. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China

2 2 Outline What is resting-state fMRI? Computational methodology Applications to brain disorders

3 3 Functional MRI? Generally Blood oxygenation level dependent (BOLD) Perfusion Diffusion Magnetic resonance spectroscopy (MRS) ……

4 4 Functional MRI? More Specifically BOLD-fMRI Perfusion Most Specifically BOLD-fMRI

5 5 Functional MRI?

6 6 Task-state fMRI? T C T C T C Design Expected signal Contrast within a scanning session is necessary!

7 7 Task-state fMRI baseline or control activated delta What is activation?

8 8 Task-state fMRI Abnormal baseline? Abnormal activated level? Abnormal delta What is abnormal activation for patients? So, baseline is important!

9 9 What is resting-state fMRI? Eyes closed or open with no task Continuously Quite a few minutes or more Not to fall asleep Not to think of anything in particular Low frequency fluctuation (LFF, 0.01 – 0.08 Hz)

10 10 The nature of task BOLD “the haemodynamic response seems to be better correlated with the LFPs, implying that activation in an area is often likely to reflect the incoming input and the local processing in a given area rather than the spiking activity.” (Logothetis et al., 2001, Nature) BOLD ≈ LFP

11 11 The nature of spontaneous BOLD “It was found that the impulse response function computed from LFP and BOLD under conditions of no stimulation can predict the response under stimulation conditions.” (Logothetis et al., 2001, Nature) Spontaneous BOLD ≈ spontaneous LFP

12 12 Resting-state BOLD-fMRI signal reflects: However, also physiological noise (respiration, cardiovascular pulsation, etc) (Cordes et al., 2001; Birn et al., 2006)

13 13 Outline What is resting-state fMRI? Computational methodology Applications to AD studies

14 14 Task-state fMRI Functional integration (inter-regional relationship or connectivity) Functional segregation (activation detection) 1 >> 2

15 15 Most of resting-state fMRI studies : integration (connectivity)  Correlation: (Biswal et al., 1995; ……)  ICA: (Kiviniemi et al., 2003; van de Ven et al., 2004; Greicius et al., 2004)  Hierarchical Clustering: (Cordes et al., 2000; Salvador et al., 2005)  Self Organization Map: (Peltier et al., 2003) ....

16 16 The first Resting-state fMRI study (Biswal et al., 1995) Bilateral finger tapping (task vs. rest) Resting-state correlation of low frequency fluctuation (LFF, 0.01 – 0.08 Hz) (Courtesy of Dr. WENG Xu-Chu)

17 17 Linear Correlation Spontaneous LFF was highly synchronous among:  Bilateral motor cortices (Biswal et al., 1995)  Bilateral visual cortices (Lowe et al., 1998; Kiviniemi et al., 2004)  Bilateral auditory cortices (Cordes et al., 2001)  Bilateral amygdala (Lowe et al., 1998)  Bilateral thalamus (Stein et al., 2000)  Language cortices (Hampson et al., 2002)  Default mode network (Greicius et al., 2003; Fox et al., )

18 18 A default mode of brain function (Raichle et al., 2001) PCC, MPFC, IPL etc., 1) Consistently show task-independent deactivation (TID) during a wide range of tasks with cognitive demand 2) Highest metabolic rate in the brain during resting state 1) 2)

19 19 Functions of the default mode network Intrinsic activities (Fransson, 2005): Self-reflection, self-referential processing, self awareness Task-unrelated thought (TUT) Mind wandering or daydreaming Streams of consciousness Memory retrieval of autobiographic events ……

20 20 Most of resting-state fMRI studies : integration (connectivity)  Correlation: (Biswal et al., 1995; ……)  ICA: (Kiviniemi et al., 2003; van de Ven et al., 2004; Greicius et al., 2004)  Hierarchical Cluster: (Cordes et al., 2000; Salvador et al., 2005)  Self Organization Map: (Peltier et al., 2003) ....

21 21 Independent Component Analysis (ICA) Spatial ICA for fMRI data: separate a mixture of a 4D data into a set of spatially independent components (McKowen et al., 1998)

22 22 Spatial ICA for resting-state fMRI Vascular componentVisual component (Kiviniemi et al., 2000)

23 23 “Integrative” is really good, but: Decreased functional connectivity Question: Is A, B, C, or……abnormal?

24 24 Only A few resting-state fMRI studies : Segregation  rms, power spectrum, ALFF: (Biswal et al., 1995; Li et al., 2000; Kiviniemi et al., 2000; Zang et al., 2007)  TCA: (Liu et al., 2000; Morgan et al., 2004)  Regional Homogeneity: (Zang et al., 2004)  Multiple Regressors: (Fransson, 2005)  Autoregressive Noise Model: (Cordes et al., 2005)  Fractional Gaussian Noise: (Maxim et al., 2005)

25 25 rms, power, ALFF For a given frequency: root mean square (rms) standard deviation amplitude rms: white matter vs. gray matter = 0.6 : 1 (Biswal et al., 1995; Li et al., 2000) Square root of the power

26 26 rms, power, ALFF  Power spectrum: Higher power at 0.033Hz in visual area (Kiviniemi et al., 2000)

27 27 Amplitude of Low Frequency Fluctuation (ALFF) (Zang et al., 2007; Yang et al., 2007) Hz TR 400 ms 1.25 Hz Steps: square root, average of Hz, standardization by global mean

28 28 ALFF (Zang et al., 2007) PET (Raichle et al., 2001) noise

29 29 Abnormal ALFF ADHD vs. controls (n=13) (n=12) (Zang et al., 2007) Early AD vs. controls (He Y et al., 2007) (Please see below for details)

30 30 Improvement: fractional ALFF Suprasellar cistern PCC

31 31 Improvement: fractional ALFF (Zou et al., 2008)

32 32 Regional Homogeneity (ReHo) Similarity or coherence of the time courses within a functional cluster (Zang et al., 2004)

33 33 ReHo: motor task state vs. pure resting state (Zang et al., 2004) Rest > Motor Motor > Rest a) Higher ReHo in bilateral primary motor cortices during motor task b) Higher ReHo in default mode network (PCC, MPFC, IPL) during rest (Raichle et al., 2001; Greicius et al., 2003)

34 34 ReHo applications to brain disorders  ADHD: Zhu et al., 2005, 2007; Cao et al., 2006  AD/MCI: He et al., 2007; Bai et al., 2008  Schizophrenia: Liu et al., 2006, Shi et al., 2007  Aging: Wu et al., 2007  PD: Wu et al., 2008  Depression: Yuan et al., 2008

35 35 Outline What is resting-state fMRI? Computational methodology Applications to brain disorders

36 36 RESTing-state fMRI data analysis toolkit (REST) By Song et al.,

37 37 Data Processing Assistant for Resting-State fMRI (DPARSF) Yan CG* and Zang YF* (2010) DPARSF: a MATLAB toolbox for "pipeline" data analysis of resting-state fMRI. Frontiers in Systems Neuroscience. 4(13)

38 38 Outline What is resting-state fMRI? Computational methodology Applications to brain disorders

39 39 Some issues about resting-state fMRI Definition and instruction? Sampling rates (TR) Length Standard method for data analysis?

40 40 Definition and Instruction? Eyes closed or open with no cognitive task Continuously Not to fall asleep Not to think of anything particular ill defined!

41 41 Different resting conditions? The functional connectivity patterns of the default mode network was minimally disturbed during different resting conditions with limited cognitive demand (Greicius et al., 2003; Fransson, 2005; Fox et al., 2005) Fox et al., 2005

42 42 Different resting conditions? Significantly different between different resting conditions with limited cognitive demand Yan et al., PLoS ONE 2009 Functional connectivity maps

43 43 Different resting conditions? Significantly different between different resting conditions with limited cognitive demand Regional activity (ALFF) Yan et al., PLoS ONE 2009

44 44 Different resting conditions? Suggestion: eyes closed for patients studies

45 45 Is the resting block a resting-state? In block design Long resting No study has compared directly between them yet

46 46 Is the resting block a resting-state? Stimulus Peak: 4-8 s BOLD Post undershoot: > 15 s s

47 47 Some issues about resting-state fMRI Definition and instruction? Sampling rates (TR) Length Standard method for data analysis?

48 48 Sampling rates (TR) Nyquist sampling theorem: Shorter TR ( 2.5 Hz) for heart beating (around 1.3 Hz) Some issues about resting-state fMRI

49 49 But for respiration (around 0.3 Hz)? Is TR <1.5 s fast enough? Simultaneous recording of respiration and heart beat to remove physiological noise (Hu et al., 1995, MRM) Courtesy of SONG Xiao- Wei Sampling rate and physiological noise

50 50 Definition and instruction? Sampling rates (TR) Length Standard data analysis? Some issues about resting-state fMRI

51 51 Length? LFF: Hz Peak around Hz (Kiviniemi et al., 2000, MRM) ≈2/min Some issues about resting-state fMRI 8 min, we used

52 52 Definition and instruction? Sampling rates (TR) Length Standard data analysis? Not yet Some issues about resting-state fMRI

53 53 Applications to brain disorders Functional connectivity (integration) Linear correlation Independent component analysis Regional activity (functional segregation) Regional Homogeneity (ReHo) Amplitude of low frequency fluctuation (ALFF)

54 54 Functional connectivity, linear correlation analysis Multiple Sclerosis: Low-Frequency Temporal Blood Oxygen Level–Dependent Fluctuations Indicate Reduced Functional Connectivity - Initial Results (Lowe et al., 2002)

55 55  Data analysis and results MT: the middle part of corpus callosum (connecting bilateral M1), lower in MS patients (Lowe et al., 2002) Functional connectivity, linear correlation analysis

56 56 Decreased functional connectivity between bilateral sensorimotor cortex (Lowe et al., 2002) Functional connectivity, linear correlation analysis

57 57 Changes in hippocampal connectivity in the early stages of Alzheimer's disease: evidence from resting state fMRI (Wang L et al., 2006) Pure resting state Subject-specific Seed ROIs in bilateral hippocampus Correlation analysis Functional connectivity, linear correlation analysis

58 58 (Wang L et al., 2006) AD: decreased connectivity with the right hippocampus

59 59 Applications to brain disorders Functional connectivity (integration) Linear correlation Independent component analysis Regional activity (functional segregation) Regional Homogeneity (ReHo) Amplitude of low frequency fluctuation (ALFF)

60 60 Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI (Greicius et al., 2004) Functional connectivity, Independent component analysis (ICA)

61 61 Methods  Data: sensorimotor task in event-related design  Independent component analysis (ICA)  Define the default mode network component by “goodness-of-fit” with a PCC-template  Between-group comparison on the Z maps  Between-group comparison on the “goodness-of-fit” (Greicius et al., 2004)

62 62 Increased functional connectivity in normal elderly “Goodness-of-fit” (Greicius et al., 2004)

63 63 Applications to brain disorders Functional connectivity (integration) Linear correlation Independent component analysis Regional activity (functional segregation) Regional Homogeneity (ReHo) Amplitude of low frequency fluctuation (ALFF)

64 64 Regional coherence changes in the early stages of Alzheimer's disease: a combined structural and resting-state functional MRI study (He Y et al., 2007) Pure resting state Regional homogeneity (ReHo) Amplitude of low frequency fluctuation (ALFF)

65 65 MCI: decreased ReHo and ALFF in PCC, while increased in visual cortex (p < 0.001, corrected) (He Y et al., 2007)

66 66 Consistent with PET studies (Reiman et al., 1996; Minoshima et al., 1994) Correlated with MMSE (He Y et al., 2007)

67 67 Summary on the resting-state fMRI  Mechanism: needs further studies  Application to clinical studies: easy, cheap  Combine with other MRI: structure, perfusion (ASL), DTI

68 68 Multiple MRI modalities DTI fMRI: Task, Rest MRS Others Computational Neuroanatomy

69 69 Multiple Disciplines  Neurology and Psychiatry  Neuroradiology  Computer Science  Cognitive Neuroscience  ……

70 70 Thanks to 拼音顺序 : 贺永 贾建平 金真 蒋田仔 李坤成 Kiviniemi, Vesa 杨一鸿 王玉凤 翁旭初 谢晟 张岱 朱朝喆 …… All the group members! NSFC

71 71 Thanks for your attention!


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