SPM12：脑科研强大工具，处理多模态医学成像

SPM12

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SPM12 Manual 是关于 Statistical Parametric Mapping (SPM) 的一个关键资源，它是 SPM8 的后续升级版本，特别强调了在脑科学研究领域的应用。SPM12 是一套强大的工具，专为处理多种类型的医学影像数据设计，包括功能性磁共振成像（fMRI）和正电子发射断层扫描（PET）等。该手册详尽介绍了 SPM12 的核心功能和处理流程，旨在帮助研究人员高效分析和解析神经影像数据。 **一、时间处理** 1. **片层时间校准 (SliceTiming)**: 这部分指导用户如何校正不同脑部层面的数据采集时间差异，确保所有层面的时间同步。参数包括每个session的层面数量、重复时间（TR）、回波时间（TE），以及确定参考层面的顺序和文件前缀设置。 **二、空间处理** 2. **再定位 (Realign)**: SPM12 提供了图像的运动校准功能，包括两个步骤：估计和重采样。首先，用户需提供数据，并选择估计选项，如运动参数估计的方法和细节。其次，重新采样环节允许用户调整和对齐图像，同时提供了不同的重采样选项以适应不同的需求。 3. **再定位与去扭曲 (Realign & Unwarp)**: 这部分关注的是更深入的空间校正，可能涉及到头动引起的变形校正，以便消除头部运动对数据质量的影响。这部分同样涉及数据输入，估计参数的选择，以及针对特定问题的特殊处理方法。 **重要性与应用** SPM12 Manual 对于进行脑功能成像研究的科学家至关重要，它不仅提供了详细的操作指南，还解释了各种参数和过程背后的理论基础。通过掌握这些技术，研究人员能够确保他们的数据分析准确无误，从而得到可靠的结果。此外，随着版本的更新，SPM12不断优化处理算法，提高了数据处理的效率和精确度，对于推动神经科学领域的发展具有重要作用。 SPM12 Manual 是脑科学研究者必备的参考文献，它详细讲解了如何使用这一软件进行高效的影像分析，无论是新手还是经验丰富的用户，都能从中获益良多。理解并熟练运用其中的工具和技术，将有助于提升科研项目的质量和创新性。

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16 CONTENTS

45 DCM for Cross Spectral Densities: Anaesthesia Depth in Rodent Data 455

45.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455

45.2 Main Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456

45.3 Using the Graphical User Interface to Obtain those Results . . . . . . . . . . . . . 456

45.3.1 The data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456

45.3.2 Dynamic Causal Modelling of Cross Spectral Densities . . . . . . . . . . . . 456

45.3.3 Comparing models using Bayesian Model Selection . . . . . . . . . . . . . . 460

46 DCM for fNIRS 463

46.1 Example: Motor Execution and Imagery Data . . . . . . . . . . . . . . . . . . . . . 464

46.2 SPM Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464

46.3 Specifying and Estimating the DCM . . . . . . . . . . . . . . . . . . . . . . . . . . 464

47 Using Dartel 471

47.1 Using Dartel for VBM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471

47.1.1 Using Spatial→Segment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471

47.1.2 Using Dartel Tools→Run Dartel (create Template) . . . . . . . . . . . . . . 472

47.1.3 Using Dartel Tools→Normalise to MNI Space . . . . . . . . . . . . . . . . . 472

47.2 Spatially normalising functional data to MNI space . . . . . . . . . . . . . . . . . . 474

47.2.1 An alternative approach for using Dartel to spatially normalise to MNI Space477

47.3 Warping Images to Existing Templates . . . . . . . . . . . . . . . . . . . . . . . . . 479

47.4 Warping one individual to match another . . . . . . . . . . . . . . . . . . . . . . . 479

VIII Batch Interface 483

48 Batch tutorial 485

48.1 Single subject . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485

48.1.1 Study speciﬁc input data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486

48.1.2 Necessary processing steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486

48.1.3 Add modules to the batch . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486

48.1.4 Conﬁgure subject-independent data . . . . . . . . . . . . . . . . . . . . . . 486

48.1.5 Data ﬂow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 488

48.1.6 Entering subject-speciﬁc data . . . . . . . . . . . . . . . . . . . . . . . . . . 491

48.2 Advanced features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491

48.2.1 Multiple sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491

48.2.2 Processing multiple subjects in GUI . . . . . . . . . . . . . . . . . . . . . . 493

48.2.3 Command line interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493

48.2.4 Modifying a saved job . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495

49 Developer’s guide 497

49.1 SPM and Matlabbatch code organisation . . . . . . . . . . . . . . . . . . . . . . . . 497

49.1.1 Code organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497

49.1.2 Interfaces between SPM and Matlabbatch . . . . . . . . . . . . . . . . . . . 497

49.2 Conﬁguration Code Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497

49.2.1 Virtual Outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 498

49.2.2 SPM Startup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 498

49.2.3 Defaults Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 498

49.3 Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

49.3.1 Batch Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

49.3.2 MATLAB Code Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

49.3.3 Conﬁguration Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

IX Bibliography 501

Chapter 1

Slice Timing

Contents

1.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.1.1 Session . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.2 Number of Slices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.3 TR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.4 TA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.5 Slice order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1.6 Reference Slice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

1.7 Filename Preﬁx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Correct diﬀerences in image acquisition time between slices. Slice-time corrected ﬁles are

prepended with an ’a’.

Note: The sliceorder arg that speciﬁes slice acquisition order is a vector of N numbers, where

N is the number of slices per volume. Each number refers to the position of a slice within the

image ﬁle. The order of numbers within the vector is the temporal order in which those slices

were acquired. To check the order of slices within an image ﬁle, use the SPM Display option and

move the cross-hairs to a voxel co-ordinate of z=1. This corresponds to a point in the ﬁrst slice

of the volume.

The function corrects diﬀerences in slice acquisition times. This routine is intended to correct

for the staggered order of slice acquisition that is used during echo-planar scanning. The correction

is necessary to make the data on each slice correspond to the same point in time. Without

correction, the data on one slice will represent a point in time as far removed as 1/2 the TR from

an adjacent slice (in the case of an interleaved sequence).

This routine "shifts" a signal in time to provide an output vector that represents the same

(continuous) signal sampled starting either later or earlier. This is accomplished by a simple shift

of the phase of the sines that make up the signal. Recall that a Fourier transform allows for a

representation of any signal as the linear combination of sinusoids of diﬀerent frequencies and

phases. Eﬀectively, we will add a constant to the phase of every frequency, shifting the data in

time.

Shifter - This is the ﬁlter by which the signal will be convolved to introduce the phase shift.

It is constructed explicitly in the Fourier domain. In the time domain, it may be described as

an impulse (delta function) that has been shifted in time the amount described by TimeShift.

The correction works by lagging (shifting forward) the time-series data on each slice using sinc-

interpolation. This results in each time series having the values that would have been obtained

had the slice been acquired at the same time as the reference slice. To make this clear, consider

a neural event (and ensuing hemodynamic response) that occurs simultaneously on two adjacent

slices. Values from slice "A" are acquired starting at time zero, simultaneous to the neural event,

20 CHAPTER 1. SLICE TIMING

while values from slice "B" are acquired one second later. Without correction, the "B" values

will describe a hemodynamic response that will appear to have began one second EARLIER on

the "B" slice than on slice "A". To correct for this, the "B" values need to be shifted towards

the Right, i.e., towards the last value.

This correction assumes that the data are band-limited (i.e. there is no meaningful information

present in the data at a frequency higher than that of the Nyquist). This assumption is support

by the study of Josephs et al (1997, NeuroImage) that obtained event-related data at an eﬀective

TR of 166 msecs. No physio-logical signal change was present at frequencies higher than our

typical Nyquist (0.25 HZ).

When using the slice timing correction it is very important that you input the correct slice

order, and if there is any uncertainty then users are encouraged to work with their physicist to

determine the actual slice acquisition order.

One can also consider augmenting the model by including the temporal derivative in the

informed basis set instead of slice timing, which can account for +/- 1 second of changes in

timing.

Written by Darren Gitelman at Northwestern U., 1998. Based (in large part) on ACQCOR-

RECT.PRO from Geoﬀ Aguirre and Eric Zarahn at U. Penn.

1.1 Data

Subjects or sessions. The same parameters speciﬁed below will be applied to all sessions.

1.1.1 Session

Select images to slice-time correct.

1.2 Number of Slices

Enter the number of slices.

1.3 TR

Enter the TR (in seconds).

1.4 TA

Enter the TA (in seconds). It is usually calculated as TR-(TR/nslices). You can simply enter

this equation with the variables replaced by appropriate numbers.

If the next two items are entered in milliseconds, this entry will not be used and can be set

to 0.

1.5 Slice order

Enter the slice order. Bottom slice = 1. Sequence types and examples of code to enter are given

below:

ascending (ﬁrst slice=bottom): [1:1:nslices]

descending (ﬁrst slice=top): [nslices:-1:1]

interleaved (middle-top):

for k = 1:nslices

round((nslices-k)/2 + (rem((nslices-k),2) * (nslices - 1)/2)) + 1,

end

interleaved (bottom -> up): [1:2:nslices 2:2:nslices]

interleaved (top -> down): [nslices:-2:1, nslices-1:-2:1]

Alternatively you can enter the slice timing in ms for each slice individually.

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