In neuroimaging the typical analysis approach is a “mass univariate”, where a univariate model is independently fit to each voxel (volume element) in parallel. This approach can be applied to a large range of datasets including: functional MRI, anatomical MRI (with Voxel-Based Morphometry), PET, EEG and MEG data.

The three major software analysis package for neuroimaging: SPM (Statistical Parametric Mapping) and FSL (FMRIB Software Library) and AFNI (AFNI) provide implementations of mass univariate analyses. While there are many commonalities across software packages, there are also software-specific outputs that can be of interest for the end-user.

This document describes the encoding of results of a mass univariate neuroimaging analysis using the NIDM data model ([[!KEATORNI13]]). The goal of this specification is to provide a unified representation of neuroimaging results across analysis software. When a piece of information is only available in a specific software, software-specific extensions are provided.

NIDM-Results is a part of NIDM as depicted in .

NIDM-Results as part of NIDM
NIDM-Results as part of NIDM.

NIDM Family of Documents

This document is part of the NIDM family of documents.

Please Send Comments

This document was published by the NIDASH NIDM Working Group as a Candidate Release. If you wish to make comments regarding this document, please report using the NIDM issue tracker or send them to nidm-users@googlegroups.com. All comments are welcome.

Introduction

NIDM-Results is a NIDM compliant structured representation of the results of a massively univariate neuroimaging study.

NIDM-Results specification formally describes the encoding of the massively univariate neuroimaging results into a NIDM representation. Extensions are provided to describe software-specific objects for SPM (Statistical Parametric Mapping) and FSL (FMRIB Software Library) analysis software.

Structure of this Document

Section 2 provides an overview of NIDM-Results, distinguishing a core set of types and relations, commonly found in provenance, from extended structures catering for more specific uses. It also introduces a modular organization of the data model in components.

Section 3 illustrates how NIDM-Results can be used to express the results of a neuroimaging study in SPM and FSL.

Section 4 provides the definitions (and examples) of NIDM-Results concepts, structured according to three components.

Notational Conventions

The key word "OPTIONAL" in this document is to be interpreted as described in [RFC2119].

Examples throughout this document use the PROV-N Provenance Notation, specified in a separate document [[prov-n]].

Namespaces

The following namespaces prefixes are used throughout this document.

Table 1: Prefix and Namespaces used in this specification
prefixnamespace IRI definition
nidmhttp://purl.org/nidash/nidm#The NIDM namespace
provhttp://www.w3.org/ns/prov#The PROV namespace [[prov-dm]]
xsdhttp://www.w3.org/2000/10/XMLSchema#XML Schema Namespace [[XMLSCHEMA11-2]]
(others)(various)All other namespace prefixes are used in examples only.
In particular, IRIs starting with "http://example.com" represent
some application-dependent IRI [[RFC3987]]

Overview

This section introduces neuroimaging results concepts with informal explanations and illustrative examples (e.g. see SPM results). NIDM-Results distinguishes software-agnostic structures, forming the essence of the results, from software-specific structures catering for more specific uses of results by different analysis software. Core and extended structures are respectively presented in Section 2.1 and Section 2.2.

Domain covered by NIDM-Results

NIDM-Results is concerned with the modelling of model fitting and inference in the context of massively univariate analyses. A typical example is the analysis of functional MRI data but studies involving other modalities (such as PET) and sequences (e.g. anatomical MRI through VBM) can also be modelled. The domain covered by NIDM-Results data model is represented in .

Domain overview

NIDM-Results Core Structures

The concepts found in the core of NIDM-Results are introduced in the rest of this section.

Overview

The core NIDM-Results structures are presented in . NIDM-Results has three main activities: nidm:'Model Parameters Estimation', nidm:'Contrast Estimation' and nidm:'Inference'. Each activity along with its inputs and outputs are presented in details in the following sections , and .
Core structures overview. Color-coding indicates prov:type (blue: prov:Entity, red: prov:Activity, green:prov:agent).

Re-use of PROV-DM Structures

PROV relations used in NIDM-Results are summarized in Table 2.

Table 2: PROV relations in use in NIDM-Results
NIDM-Results ConceptsTypes or Relation (PROV concepts)NameOverview
Generation PROV Relations
WasGeneratedBy PROV-DM wasGeneratedBy
UsageUsedPROV-DM used
DerivationWasDerivedFromPROV-DM wasDerivedFrom

NIDM-Results: Types and relations

General

This section describes the NIDM-Results entity and introduces general neuroimaging concepts with definitions and illustrative examples. These concepts are shared with other NIDM specifications.
Table 3:NIDM-Results General Concepts
NIDM-Results Concept PROV type Identifier
nlx:'SPM' prov:'Agent' nlx:nif-0000-00343
nlx:'FSL' nlx:birnlex_2067
nidm:'NIDM-Results' prov:'Entity' nidm:NIDM_0000027
nidm:'Map' nidm:NIDM_0000052
nidm:'Coordinate Space' nidm:NIDM_0000016

nlx:'SPM'

nlx:'SPM': Software package for the analysis of brain imaging data sequences. The sequences can be a series of images from different cohorts, or time-series from the same subject. The current release is designed for the analysis of fMRI, PET, SPECT, EEG and MEG.

nlx:'SPM' is a prov:'Agent'.

A nlx:'SPM' has attributes:
  • rdfs:label: (OPTIONAL) Human readable description of the nlx:'SPM'.
  • nidm:'software Version': (OPTIONAL) Name and number that specifies the software version. For SPM, this includes the main software version followed by the revision number (e.g. 8.6225 for SPM8 revision 6225). (range xsd:string).

nlx:'FSL'

nlx:'FSL': A comprehensive library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. The tools include registration, atlases, Diffusion MRI tools for parameter reconstruction and probabilistic taractography, and a viewer. FSL runs on Apple and PCs (Linux and Windows), and is very easy to install. Most of the tools can be run both from the command line and as GUIs ('point-and-click' graphical user interfaces). Several complementary brain atlases, integrated into FSLView and Featquery, allowing viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Atlases included with FSL: * Harvard-Oxford cortical and subcortical structural atlases * Julich histological atlas * JHU DTI-based white-matter atlases * Oxford thalamic connectivity atlas * Talairach atlas * MNI structural atlas * Cerebellum atlas FSL is written mainly by members of the Analysis Group, FMRIB, Oxford, UK.

nlx:'FSL' is a prov:'Agent'.

A nlx:'FSL' has attributes:
  • rdfs:label: (OPTIONAL) Human readable description of the nlx:'FSL'.
  • fsl:'feat Version': (OPTIONAL) Version of the FEAT software. (range xsd:string).
  • nidm:'software Version': (OPTIONAL) Name and number that specifies the software version. For SPM, this includes the main software version followed by the revision number (e.g. 8.6225 for SPM8 revision 6225). (range xsd:string).

nidm:'NIDM-Results'

nidm:'NIDM-Results': NIDM Object model representing the results of a mass univariate neuroimaging study and targeting the application of meta-analysis. The specification is available at: http://nidm.nidash.org/specs/nidm-results.html.

nidm:'NIDM-Results' is a nidm:'NIDM Object Model'.

A nidm:'NIDM-Results' has attributes:

nidm:'Map'

nidm:'Map': Ordered set of values corresponding to the discrete sampling of some process (e.g. brain MRI data measured on a regular 3D lattice; or brain cortical surface data measured irregularly over the cortex).

nidm:'Map' is a prov:'Entity' and has the following children: nidm:'Binary Map', nidm:'Cluster Labels Map', nidm:'Contrast Explained Mean Square Map', nidm:'Contrast Map', nidm:'Contrast Standard Error Map', nidm:'Contrast Variance Map', nidm:'Excursion Set Map', nidm:'Grand Mean Map', nidm:'Parameter Estimate Map', nidm:'Resels Per Voxel Map', nidm:'Residual Mean Squares Map', nidm:'Statistic Map'.

A nidm:'Map' has attributes:

nidm:'Map Header'

nidm:'Map Header': A file associated with a Map to provide header information (e.g. NIfTI header file).

nidm:'Map Header' is a prov:'Entity'.

A nidm:'Map Header' has attributes:

nidm:'Coordinate Space'

nidm:'Coordinate Space': An entity with spatial attributes (e.g., dimensions, units, and voxel-to-world mapping) that provides context to a Map (e.g., a Statistic Map, a Contrast Map...).

nidm:'Coordinate Space' is a prov:'Entity'.

A nidm:'Coordinate Space' has attributes:
@prefix nidm_CoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000016> .
@prefix nidm_voxelToWorldMapping: <http://purl.org/nidash/nidm#NIDM_0000132> .
@prefix nidm_voxelUnits: <http://purl.org/nidash/nidm#NIDM_0000133> .
@prefix nidm_voxelSize: <http://purl.org/nidash/nidm#NIDM_0000131> .
@prefix nidm_inWorldCoordinateSystem: <http://purl.org/nidash/nidm#NIDM_0000105> .
@prefix nidm_MNICoordinateSystem: <http://purl.org/nidash/nidm#NIDM_0000051> .
@prefix nidm_numberOfDimensions: <http://purl.org/nidash/nidm#NIDM_0000112> .
@prefix nidm_dimensionsInVoxels: <http://purl.org/nidash/nidm#NIDM_0000090> .


niiri:coordinate_space_id_1 a prov:Entity , nidm_CoordinateSpace: ;
	rdfs:label "Coordinate space 1" ;
	nidm_voxelToWorldMapping: "[[-3, 0, 0, 78],[0, 3, 0, -112],[0, 0, 3, -50],[0, 0, 0, 1]]"^^xsd:string ;
	nidm_voxelUnits: "[ \"mm\", \"mm\", \"mm\" ]"^^xsd:string ;
	nidm_voxelSize: "[ 3, 3, 3 ]"^^xsd:string ;
	nidm_inWorldCoordinateSystem: nidm_MNICoordinateSystem: ;
	nidm_numberOfDimensions: "3"^^xsd:int ;
	nidm_dimensionsInVoxels: "[ 53, 63, 46 ]"^^xsd:string .

nidm:'World Coordinate System'

nidm:'World Coordinate System': Reference space on which real-world positions are expressed (cf. Nifti-1 FAQ question 14](http://nifti.nimh.nih.gov/nifti-1/documentation/faq#Q14) and [Understanding affines on nipy ). A world coordinate system can be represented by an image obtained by registering an initial set of images, using a given normalization algorithm to match a target template.

nidm:'World Coordinate System' is a prov:'Entity' and has the following children: nidm:'Standardized Coordinate System', nidm:'Subject Coordinate System'.

A nidm:'World Coordinate System' has attributes:

nidm:'Standardized Coordinate System'

A nidm:'Standardized Coordinate System' has attributes:

nidm:'Custom Coordinate System'

nidm:'Custom Coordinate System': Custom (unknown) reference space selected by the user.

nidm:'Custom Coordinate System' is a nidm:'Standardized Coordinate System'.

A nidm:'Custom Coordinate System' has attributes:

nidm:'MNI Coordinate System'

nidm:'MNI Coordinate System': MNI 305 coordinate system or any coordinate system derived from MNI 305.

nidm:'MNI Coordinate System' is a nidm:'Standardized Coordinate System'.

A nidm:'MNI Coordinate System' has attributes:
Examples of nidm:'MNI Coordinate System' includes
  • nidm:'Icbm Mni152 Linear Coordinate System': Reference space which is the average of 152 T1-weighted MRI scans, linearly transformed onto the MNI 305 reference space (definition adapted from: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152Lin). This is the default in SPM99 to SPM8 (cf. MRC CBSU Wiki and spm8/spm_templates.man.
  • nidm:'Icbm Mni152 Non Linear2009a Asymmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans, non-linearly transformed to MNI152 linear space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details).
  • nidm:'Icbm Mni152 Non Linear2009a Symmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans, non-linearly transformed to to form a symmetric model in MNI152 linear space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details).
  • nidm:'Icbm Mni152 Non Linear2009b Asymmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans in high-resolution, non-linearly transformed to MNI152 linear space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details).
  • nidm:'Icbm Mni152 Non Linear2009b Symmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans in high-resolution, non-linearly transformed to form a symmetric model in MNI152 linear space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details).
  • nidm:'Icbm Mni152 Non Linear2009c Asymmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans, non-linearly transformed to MNI152 linear space using the N3 algorithm (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details).
  • nidm:'Icbm Mni152 Non Linear2009c Symmetric Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans, non-linearly transformed to form a symmetric model in MNI152 linear space using the N3 algorithm (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 for more details). This is the default for DARTEL toolbox in SPM12b (cf. spm12/spm_templates.man).
  • nidm:'Icbm Mni152 Non Linear6th Generation Coordinate System': Reference space defined as the average of 152 T1-weighted MRI scans, linearly and non-linearly (6 iterations) transformed to form a symmetric model in Talairach space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin6).
  • nidm:'Icbm452 Air Coordinate System': Reference space defined as the average of 452 T1-weighted MRIs of normal young adult brains after 12 parameter AIR linear transform to the MNI 305 space (cf. http://www.loni.usc.edu/ICBM/Downloads/Downloads_452T1.shtml and http://imaging.mrc-cbu.cam.ac.uk/imaging/MniTalairach).
  • nidm:'Icbm452 Warp5 Coordinate System': Reference space defined as the average of 452 T1-weighted MRIs of normal young adult brains after affine and 5 order polynomial non-linear warping to the MNI 305 space (cf. http://www.loni.usc.edu/ICBM/Downloads/Downloads_452T1.shtml and http://imaging.mrc-cbu.cam.ac.uk/imaging/MniTalairach).
  • nidm:'Ixi549 Coordinate System': Reference space defined by the average of the 549 subjects from the IXI dataset linearly transformed to the ICBM MNI 452 (cf. spm12/spm\_templates.man and http://biomedic.doc.ic.ac.uk/brain-development/index.php?n=Main.Datasets). This is the default in SPM12 (cf. spm12/spm_templates.man).
  • nidm:'Mni305 Coordinate System': Reference space defined as the average of 305 T1-weighted MRI scans, linearly transformed to Talairach space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/MNI305 for more details).

nidm:'Talairach Coordinate System'

nidm:'Talairach Coordinate System': Reference space defined by the dissected brain used for the Talairach and Tournoux atlas (cf. http://www.talairach.org/about.html).

nidm:'Talairach Coordinate System' is a nidm:'Standardized Coordinate System'.

A nidm:'Talairach Coordinate System' has attributes:
Examples of nidm:'Standardized Coordinate System' includes
  • nidm:'Colin27 Coordinate System': Reference space defined as the stereotaxic average of 27 T1-weighted MRI scans of the same individual transformed into the Talairach stereotaxic space (cf. http://www.bic.mni.mcgill.ca/ServicesAtlases/Colin27Highres and http://neuro.debian.net/pkgs/mni-colin27-nifti.html). This is the default in SPM96 (cf. MRC CBSU Wiki.

nidm:'Subject Coordinate System'

nidm:'Subject Coordinate System': Reference space corresponding to the subject brain (no spatial normalization applied).

nidm:'Subject Coordinate System' is a nidm:'World Coordinate System'.

A nidm:'Subject Coordinate System' has attributes:

Parameters estimation

NIDM-Results Parameters Estimation
Table 4:NIDM-Results Parameters estimation Concepts
NIDM-Results Concept PROV type Identifier
nidm:'Model Parameters Estimation' prov:'Activity' nidm:NIDM_0000056
nidm:'Data Scaling' prov:'Entity' nidm:NIDM_0000018
nidm:'Design Matrix' nidm:NIDM_0000019
nidm:'Error Model' nidm:NIDM_0000023
nidm:'Grand Mean Map' nidm:NIDM_0000033
nidm:'Mask Map' nidm:NIDM_0000054
nidm:'Parameter Estimate Map' nidm:NIDM_0000061
nidm:'Resels Per Voxel Map' nidm:NIDM_0000144
nidm:'Residual Mean Squares Map' nidm:NIDM_0000066

nidm:'Model Parameters Estimation'

@prefix nidm_ModelParametersEstimation: <http://purl.org/nidash/nidm#NIDM_0000056> .
@prefix nidm_withEstimationMethod: <http://purl.org/nidash/nidm#NIDM_0000134> .
@prefix obo_ordinaryleastsquaresestimation: <http://purl.obolibrary.org/obo/STATO_0000370> .


niiri:model_pe_id prov:used niiri:error_model_id ;
	a prov:Activity , nidm_ModelParametersEstimation: ;
	rdfs:label "Model parameters estimation" ;
	nidm_withEstimationMethod: obo_ordinaryleastsquaresestimation: ; # obo:'ordinary least squares estimation'
	prov:used niiri:design_matrix_id ;
    prov:used niiri:data_id ;
    prov:used niiri:error_model_id ;
    prov:wasAssociatedWith niiri:software_id .

nidm:'Data Scaling'

nidm:'Data Scaling': Scaling applied to the data before parameter estimation, including specification of the target intensity.

nidm:'Data Scaling' is a prov:'Entity' used by nidm:'Model Parameters Estimation'.

A nidm:'Data Scaling' has attributes:
  • rdfs:label: (OPTIONAL) Human readable description of the nidm:'Data Scaling'.
  • nidm:'grand Mean Scaling': (OPTIONAL) Binary flag defining whether the data was scaled (true for scaled). Specifically, "grand mean scaling" refers to multiplication of every voxel in every scan by a common (or session-specific) value. (range xsd:boolean).
  • nidm:'target Intensity': (OPTIONAL) Value to which the grand mean of the Data was scaled (applies only if grand mean scaling is true). (range xsd:float).
@prefix nidm_DataScaling: <http://purl.org/nidash/nidm#NIDM_0000018> .
@prefix nidm_grandMeanScaling: <http://purl.org/nidash/nidm#NIDM_0000096> .
@prefix nidm_targetIntensity: <http://purl.org/nidash/nidm#NIDM_0000124> .


niiri:data_id a prov:Entity , nidm_DataScaling: , prov:Collection ;
    rdfs:label "Data" ;
    nidm_grandMeanScaling: "true"^^xsd:boolean ;
    nidm_targetIntensity: "100"^^xsd:float .

nidm:'Design Matrix'

nidm:'Design Matrix': A stato:design matrix, with additional neuroimaging attributes, including HRF and drift for first level fMRI models.

nidm:'Design Matrix' is a prov:'Entity' used by nidm:'Contrast Estimation', nidm:'Model Parameters Estimation'.

A nidm:'Design Matrix' has attributes:
@prefix nidm_DesignMatrix: <http://purl.org/nidash/nidm#NIDM_0000019> .


niiri:design_matrix_id a prov:Entity , nidm_DesignMatrix: ;
	rdfs:label "Design Matrix" ;
	prov:atLocation "file:///path/to/DesignMatrix.csv"^^xsd:anyURI ;
	dct:format "text/csv"^^xsd:string ;
	nfo:fileName "DesignMatrix.csv"^^xsd:string ;
	dc:description niiri:design_matrix_png_id .

nidm:'Convolution Basis Set'

A nidm:'Convolution Basis Set' has attributes:

nidm:'Custom Basis Set'

A nidm:'Custom Basis Set' has attributes:

nidm:'Finite Impulse Response Basis Set'

nidm:'Finite Impulse Response Basis Set': Set of Finite impulse response (FIR) filters, with FIR the convolution kernel is represented as a set of discrete fixed-width "impulses" (definition adapted from FSL wiki.

nidm:'Finite Impulse Response Basis Set' is a nidm:'Convolution Basis Set'.

A nidm:'Finite Impulse Response Basis Set' has attributes:

nidm:'Fourier Basis Set'

A nidm:'Fourier Basis Set' has attributes:

nidm:'Gamma Basis Set'

nidm:'Gamma Basis Set': Set of gamma probability density functions.

nidm:'Gamma Basis Set' is a nidm:'Convolution Basis Set'.

A nidm:'Gamma Basis Set' has attributes:

nidm:'Hemodynamic Response Function Derivative'

nidm:'Hemodynamic Response Function Derivative': Hemodynamic response function basis which is the derivative of an hemodynamic response function.

nidm:'Hemodynamic Response Function Derivative' is a nidm:'Convolution Basis Set'.

A nidm:'Hemodynamic Response Function Derivative' has attributes:
Examples of nidm:'Hemodynamic Response Function Derivative' includes
  • fsl:'FSL's Temporal Derivative': Hemodynamic response function basis that is the derivative with respect to time of the FSL's Gamma Difference heamodynamic response function.
  • spm:'SPM's Dispersion Derivative': Hemodynamic response function basis that is the derivative with respect to spatial dispersion of the SPM's Canonical heamodynamic response function.
  • spm:'SPM's Temporal Derivative': Hemodynamic response function basis that is the derivative with respect to time of the SPM's Canonical heamodynamic response function.

nidm:'Hemodynamic Response Function'

nidm:'Hemodynamic Response Function': Hemodynamic response function basis that can on its own be used to represent the idealised hemodynamic response function.

nidm:'Hemodynamic Response Function' is a nidm:'Convolution Basis Set' and has the following children: nidm:'Gamma Difference HRF', nidm:'Gamma HRF', nidm:'Gaussian HRF'.

A nidm:'Hemodynamic Response Function' has attributes:

nidm:'Gamma Difference HRF'

nidm:'Gamma Difference HRF': Hemodynamic response function which is a difference of two gamma probability density functions.

nidm:'Gamma Difference HRF' is a nidm:'Hemodynamic Response Function'.

A nidm:'Gamma Difference HRF' has attributes:
Examples of nidm:'Gamma Difference HRF' includes
  • fsl:'FSL's Gamma Difference HRF': Hemodynamic response function which is a fixed difference of two gamma probability density functions - a standard positive function at normal lag, and a small, delayed, negated gamma probability density function, which attempts to model the late undershoot (definition adapted FSL wiki. This is the default in FSL.
  • spm:'SPM's Canonical HRF': Hemodynamic response function which is a fixed difference of two gamma probability density functions and is denoted by "canonical HRF" in SPM. This is the default in SPM.

nidm:'Gamma HRF'

nidm:'Gamma HRF': Hemodynamic response function which is a gamma probability density function.

nidm:'Gamma HRF' is a nidm:'Hemodynamic Response Function'.

A nidm:'Gamma HRF' has attributes:

nidm:'Gaussian HRF'

nidm:'Gaussian HRF': Hemodynamic response function which is a gaussian kernel.

nidm:'Gaussian HRF' is a nidm:'Hemodynamic Response Function'.

A nidm:'Gaussian HRF' has attributes:

nidm:'Linear Spline Basis Set'

nidm:'Linear Spline Basis Set': A Linear (order 1) spline, providing an estimate that is continuous over time (in contrast to a FIR basis, which is discontinuous between each time bin). This is called TENT in AFNI's 3dDeconvolve program.

nidm:'Linear Spline Basis Set' is a nidm:'Convolution Basis Set'.

A nidm:'Linear Spline Basis Set' has attributes:

nidm:'Sine Basis Set'

nidm:'Sine Basis Set': A set of Sine waves of differing frequencies (definition adapted from FSL wiki.

nidm:'Sine Basis Set' is a nidm:'Convolution Basis Set'.

A nidm:'Sine Basis Set' has attributes:

nidm:'Drift Model'

nidm:'Drift Model': A model used to compensate for low frequency baseline drifts when analyzing functional MRI data at the subject level.

nidm:'Drift Model' is a prov:'Entity' and has the following children: fsl:'Gaussian Running Line Drift Model', spm:'DCT Drift Model'.

A nidm:'Drift Model' has attributes:
@prefix fsl_GaussianRunningLineDriftModel: <http://purl.org/nidash/fsl#FSL_0000002> .
@prefix fsl_driftCutoffPeriod: <http://purl.org/nidash/fsl#FSL_0000004> .


niiri:drift_model_id a prov:Entity , fsl_GaussianRunningLineDriftModel: ;
	rdfs:label "FSL's Gaussian Running Line Drift Model" ;
	fsl_driftCutoffPeriod: "2"^^xsd:float .
@prefix spm_DCTDriftModel: <http://purl.org/nidash/spm#SPM_0000002> .
@prefix spm_SPMsDriftCutoffPeriod: <http://purl.org/nidash/spm#SPM_0000001> .


niiri:drift_model_id a prov:Entity , spm_DCTDriftModel: ;
	rdfs:label "SPM's DCT Drift Model" ;
	spm_SPMsDriftCutoffPeriod: "128"^^xsd:float .

fsl:'Gaussian Running Line Drift Model'

fsl:'Gaussian Running Line Drift Model': A drift model in which the drifts are modeled with a Gaussian-weighted running line smoother, fit to and subtracted from the data and each column of the design matrix.

fsl:'Gaussian Running Line Drift Model' is a nidm:'Drift Model'.

A fsl:'Gaussian Running Line Drift Model' has attributes:

spm:'DCT Drift Model'

spm:'DCT Drift Model': A drift model in which the drifts are modeled by a Discrete Cosine Transform basis added to regression model.

spm:'DCT Drift Model' is a nidm:'Drift Model'.

A spm:'DCT Drift Model' has attributes:

nidm:'fMRI Design Type'

nidm:'fMRI Design Type': The type of stimulus presentation used in the data acquisition, one of block-based design event-related design or mixed design.

nidm:'fMRI Design Type' is a prov:'Entity'.

A nidm:'fMRI Design Type' has attributes:
Examples of nidm:'fMRI Design Type' includes

nidm:'Error Model'

nidm:'Error Model': Model used to describe the random variation of the error term as part of parameter estimation, including specification of the error probability distribution, its variance and dependence both spatially and across observations.

nidm:'Error Model' is a prov:'Entity' used by nidm:'Model Parameters Estimation'.

A nidm:'Error Model' has attributes:
@prefix nidm_ErrorModel: <http://purl.org/nidash/nidm#NIDM_0000023> .
@prefix nidm_hasErrorDistribution: <http://purl.org/nidash/nidm#NIDM_0000101> .
@prefix nidm_GaussianDistribution: <http://purl.org/nidash/nidm#NIDM_0000032> .
@prefix nidm_errorVarianceHomogeneous: <http://purl.org/nidash/nidm#NIDM_0000094> .
@prefix nidm_varianceMapWiseDependence: <http://purl.org/nidash/nidm#NIDM_0000126> .
@prefix nidm_IndependentParameter: <http://purl.org/nidash/nidm#NIDM_0000073> .
@prefix nidm_hasErrorDependence: <http://purl.org/nidash/nidm#NIDM_0000100> .
@prefix nidm_IndependentError: <http://purl.org/nidash/nidm#NIDM_0000048> .
@prefix nidm_dependenceMapWiseDependence: <http://purl.org/nidash/nidm#NIDM_0000089> .


niiri:error_model_id a prov:Entity , nidm_ErrorModel: ;
    nidm_hasErrorDistribution: nidm_GaussianDistribution: ;
    nidm_errorVarianceHomogeneous: "true"^^xsd:boolean ;
    nidm_varianceMapWiseDependence: nidm_IndependentParameter: ;
    nidm_hasErrorDependence: nidm_IndependentError: ;
    nidm_dependenceMapWiseDependence: nidm_IndependentParameter: .

nidm:'Error Distribution'

A nidm:'Error Distribution' has attributes:

nidm:'Binomial Distribution'

nidm:'Binomial Distribution': The binomial distribution is a discrete probability distribution which describes the probability of k successes in n draws with replacement from a finite population of size N. The binomial distribution is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N. The binomial distribution gives the discrete probability distribution of obtaining exactly n successes out of N Bernoulli trials (where the result of each Bernoulli trial is true with probability p and false with probability q=1-p ) notation: B(n,p) The mean is N*p The variance is N*p*q. (Definition from STATO).

nidm:'Binomial Distribution' is a nidm:'Error Distribution'.

A nidm:'Binomial Distribution' has attributes:

nidm:'Gaussian Distribution'

nidm:'Gaussian Distribution': A normal distribution is a continuous probability distribution described by a probability distribution function described here: http://mathworld.wolfram.com/NormalDistribution.html (Definition from STATO).

nidm:'Gaussian Distribution' is a nidm:'Error Distribution'.

A nidm:'Gaussian Distribution' has attributes:

nidm:'Non Parametric Distribution'

nidm:'Non Parametric Distribution': Probability distribution estimated empirically on the data without assumptions on the shape of the probability distribution.

nidm:'Non Parametric Distribution' is a nidm:'Error Distribution'.

A nidm:'Non Parametric Distribution' has attributes:

nidm:'Non Parametric Symmetric Distribution'

nidm:'Non Parametric Symmetric Distribution': Probability distribution estimated empirically on the data assuming only symmetry of the probability distribution.

nidm:'Non Parametric Symmetric Distribution' is a nidm:'Error Distribution'.

A nidm:'Non Parametric Symmetric Distribution' has attributes:

nidm:'Poisson Distribution'

nidm:'Poisson Distribution': Poisson distribution is a probability distribution used to model the number of events occurring within a given time interval. It is defined by a real number (λ) and an integer k representing the number of events and a function. The expected value of a Poisson-distributed random variable is equal to λ and so is its variance. (Definition from STATO).

nidm:'Poisson Distribution' is a nidm:'Error Distribution'.

A nidm:'Poisson Distribution' has attributes:

nidm:'Error Parameter Map-Wise Dependence'

nidm:'Error Parameter Map-Wise Dependence': Map-wise dependence structure of a parameter in the error model (i.e. variance or dependence parameter). For example, whether a temporal autocorrelation parameter is estimated at each element separately, estimated using data in a local neighbourhood, or estimated using all elements in the map.

nidm:'Error Parameter Map-Wise Dependence' is a prov:'Entity' and has the following children: nidm:'Constant Parameter', nidm:'Independent Parameter', nidm:'Regularized Parameter'.

A nidm:'Error Parameter Map-Wise Dependence' has attributes:

nidm:'Constant Parameter'

nidm:'Constant Parameter': Parameter estimated as constant over a entire set of elements considered (e.g. those in the analysis mask).

nidm:'Constant Parameter' is a nidm:'Error Parameter Map-Wise Dependence'.

A nidm:'Constant Parameter' has attributes:

nidm:'Independent Parameter'

nidm:'Independent Parameter': Parameter whose estimation at a given element does not depend on any other element.

nidm:'Independent Parameter' is a nidm:'Error Parameter Map-Wise Dependence'.

A nidm:'Independent Parameter' has attributes:

nidm:'Regularized Parameter'

nidm:'Regularized Parameter': Parameter whose estimation at a given element depends on a local neighborhood of elements.

nidm:'Regularized Parameter' is a nidm:'Error Parameter Map-Wise Dependence'.

A nidm:'Regularized Parameter' has attributes:

nidm:'Grand Mean Map'

nidm:'Grand Mean Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is the mean over all observations of that element in the input maps (after any scaling of those input maps).

nidm:'Grand Mean Map' is a nidm:'Map' generated by nidm:'Model Parameters Estimation'.

A nidm:'Grand Mean Map' has attributes:
@prefix nidm_GrandMeanMap: <http://purl.org/nidash/nidm#NIDM_0000033> .
@prefix nidm_maskedMedian: <http://purl.org/nidash/nidm#NIDM_0000107> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:grand_mean_map_id a prov:Entity , nidm_GrandMeanMap: ;
	rdfs:label "Grand Mean Map" ;
	prov:atLocation "file:///path/to/GrandMean.nii.gz"^^xsd:anyURI ;
	nfo:fileName "GrandMean.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_maskedMedian: "115"^^xsd:float ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
    prov:wasGeneratedBy niiri:model_pe_id .

nidm:'Mask Map'

nidm:'Mask Map': A binary map representing the exact set of elements (e.g., pixels, voxels, vertices, and faces) in which an activity was performed (e.g. the mask map generated by the model parameter estimation activity represents the exact set of voxels in which the mass univariate model was estimated) and/or restraining the space in which an activity was performed (e.g. the mask map used by inference).

nidm:'Mask Map' is a nidm:'Binary Map' used by nidm:'Contrast Estimation', nidm:'Model Parameters Estimation' and generated by nidm:'Model Parameters Estimation'. It has the following child: nidm:'Search Space Mask Map'.

A nidm:'Mask Map' has attributes:
@prefix nidm_MaskMap: <http://purl.org/nidash/nidm#NIDM_0000054> .
@prefix nidm_isUserDefined: <http://purl.org/nidash/nidm#NIDM_0000106> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:model_pe_id prov:used niiri:mask_id_2 .
niiri:mask_id_2 a prov:Entity , nidm_MaskMap: ;
	rdfs:label "Mask" ;
    nidm_isUserDefined: "false"^^xsd:boolean ;
	prov:atLocation "file:///path/to/Mask.nii.gz"^^xsd:anyURI ;
	nfo:fileName "Mask.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string .

nidm:'Parameter Estimate Map'

nidm:'Parameter Estimate Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is a model parameter estimate.

nidm:'Parameter Estimate Map' is a nidm:'Map' used by nidm:'Contrast Estimation' and generated by nidm:'Model Parameters Estimation'.

A nidm:'Parameter Estimate Map' has attributes:
@prefix nidm_ParameterEstimateMap: <http://purl.org/nidash/nidm#NIDM_0000061> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:beta_map_id_1 a prov:Entity , nidm_ParameterEstimateMap: ;
    rdfs:label "Beta Map 1" ;
    nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
    prov:wasGeneratedBy niiri:model_pe_id .

nidm:'Resels Per Voxel Map'

nidm:'Resels Per Voxel Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) location is the number of resels per voxel.

nidm:'Resels Per Voxel Map' is a nidm:'Map' used by nidm:'Inference' and generated by nidm:'Model Parameters Estimation'.

A nidm:'Resels Per Voxel Map' has attributes:
@prefix nidm_ReselsPerVoxelMap: <http://purl.org/nidash/nidm#NIDM_0000144> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:resels_per_voxel_map_id a prov:Entity , nidm_ReselsPerVoxelMap: ;
	rdfs:label "Resels per Voxel Map" ;
	prov:atLocation "file:///path/to/ReselsPerVoxel.nii.gz"^^xsd:anyURI ;
	nfo:fileName "ReselsPerVoxel.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
    prov:wasGeneratedBy niiri:model_pe_id.

nidm:'Residual Mean Squares Map'

nidm:'Residual Mean Squares Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is a residual mean square.

nidm:'Residual Mean Squares Map' is a nidm:'Map' used by nidm:'Contrast Estimation' and generated by nidm:'Model Parameters Estimation'.

A nidm:'Residual Mean Squares Map' has attributes:
@prefix nidm_ResidualMeanSquaresMap: <http://purl.org/nidash/nidm#NIDM_0000066> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:residual_mean_squares_map_id a prov:Entity , nidm_ResidualMeanSquaresMap: ;
	rdfs:label "Residual Mean Squares Map" ;
	prov:atLocation "file:///path/to/ResidualMeanSquares.nii.gz"^^xsd:anyURI ;
	nfo:fileName "ResidualMeanSquares.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
    prov:wasGeneratedBy niiri:model_pe_id .

Contrast estimation

NIDM-Results Contrast Estimation
Table 5:NIDM-Results Contrast estimation Concepts
NIDM-Results Concept PROV type Identifier
nidm:'Contrast Estimation' prov:'Activity' nidm:NIDM_0000001
obo:'contrast weight matrix' prov:'Entity' obo:STATO_0000323
nidm:'Contrast Map' nidm:NIDM_0000002
nidm:'Contrast Standard Error Map' nidm:NIDM_0000013
nidm:'Contrast Explained Mean Square Map' nidm:NIDM_0000163
nidm:'Statistic Map' nidm:NIDM_0000076

nidm:'Contrast Estimation'

A nidm:'Contrast Estimation' has attributes:
@prefix nidm_ContrastEstimation: <http://purl.org/nidash/nidm#NIDM_0000001> .


niiri:contrast_estimation_id a prov:Activity , nidm_ContrastEstimation: ;
	rdfs:label "Contrast estimation" ;
	prov:used niiri:mask_id_2 , niiri:residual_mean_squares_map_id , niiri:design_matrix_id , niiri:contrast_id, niiri:beta_map_id_1 ;
    prov:wasAssociatedWith niiri:software_id .

obo:'contrast weight matrix'

obo:'contrast weight matrix': A contrast weight matrix is a information content entity which holds a set of contrast weight, coefficient used in a weighting sum of means defining a contrast.

obo:'contrast weight matrix' is a prov:'Entity' used by nidm:'Contrast Estimation'.

A obo:'contrast weight matrix' has attributes:
[1,0,0]
@prefix nidm_statisticType: <http://purl.org/nidash/nidm#NIDM_0000123> .
@prefix nidm_contrastName: <http://purl.org/nidash/nidm#NIDM_0000085> .
@prefix obo_contrastweightmatrix: <http://purl.obolibrary.org/obo/STATO_0000323> .
@prefix obo_tstatistic: <http://purl.obolibrary.org/obo/STATO_0000176> .


niiri:contrast_id a prov:Entity , obo_contrastweightmatrix: ;
	rdfs:label "Contrast: Listening > Rest" ;
	prov:value "[ 1, 0, 0 ]"^^xsd:string ;
	nidm_statisticType: obo_tstatistic: ; # obo:'t-statistic'
	nidm_contrastName: "listening > rest"^^xsd:string .

nidm:'Contrast Map'

nidm:'Contrast Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is a contrast estimate.

nidm:'Contrast Map' is a nidm:'Map' used by nidm:'Inference' and generated by nidm:'Contrast Estimation'.

A nidm:'Contrast Map' has attributes:
@prefix nidm_ContrastMap: <http://purl.org/nidash/nidm#NIDM_0000002> .
@prefix nidm_contrastName: <http://purl.org/nidash/nidm#NIDM_0000085> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:contrast_map_id a prov:Entity , nidm_ContrastMap: ;
	rdfs:label "Contrast Map: listening > rest" ;
	prov:atLocation "file:///path/to/Contrast.nii.gz"^^xsd:anyURI ;
	dct:format "image/nifti"^^xsd:string ;
	nfo:fileName "Contrast.nii.gz"^^xsd:string ;
	nidm_contrastName: "listening > rest"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
    prov:wasGeneratedBy niiri:contrast_estimation_id .

nidm:'Contrast Standard Error Map'

nidm:'Contrast Standard Error Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is a standard error of a contrast estimate.

nidm:'Contrast Standard Error Map' is a nidm:'Map' generated by nidm:'Contrast Estimation'.

A nidm:'Contrast Standard Error Map' has attributes:
@prefix nidm_ContrastStandardErrorMap: <http://purl.org/nidash/nidm#NIDM_0000013> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:contrast_standard_error_map_id a prov:Entity , nidm_ContrastStandardErrorMap: ;
	rdfs:label "Contrast Standard Error Map" ;
	prov:atLocation "file:///path/to/ContrastStandardError.nii.gz"^^xsd:anyURI ;
	nfo:fileName "ContrastStandardError.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
    prov:wasGeneratedBy niiri:contrast_estimation_id .

nidm:'Contrast Explained Mean Square Map'

nidm:'Contrast Explained Mean Square Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is the extra sum of squares divided by the effect degrees of freedom (i.e. the denumerator of an F-statistic).

nidm:'Contrast Explained Mean Square Map' is a nidm:'Map' generated by nidm:'Contrast Estimation'.

A nidm:'Contrast Explained Mean Square Map' has attributes:

nidm:'Statistic Map'

nidm:'Statistic Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) is a statistic.

nidm:'Statistic Map' is a nidm:'Map' used by nidm:'Inference' and generated by nidm:'Contrast Estimation'.

A nidm:'Statistic Map' has attributes:
@prefix nidm_StatisticMap: <http://purl.org/nidash/nidm#NIDM_0000076> .
@prefix nidm_statisticType: <http://purl.org/nidash/nidm#NIDM_0000123> .
@prefix nidm_contrastName: <http://purl.org/nidash/nidm#NIDM_0000085> .
@prefix nidm_effectDegreesOfFreedom: <http://purl.org/nidash/nidm#NIDM_0000091> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .
@prefix nidm_errorDegreesOfFreedom: <http://purl.org/nidash/nidm#NIDM_0000093> .
@prefix obo_tstatistic: <http://purl.obolibrary.org/obo/STATO_0000176> .


niiri:statistic_map_id a prov:Entity , nidm_StatisticMap: ;
	rdfs:label "Statistic Map: listening > rest" ;
	prov:atLocation "file:///path/to/TStatistic.nii.gz"^^xsd:anyURI ;
	nidm_statisticType: obo_tstatistic: ; # obo:'t-statistic'
	nfo:fileName "TStatistic.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_contrastName: "listening > rest"^^xsd:string ;
	nidm_effectDegreesOfFreedom: "1"^^xsd:float ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
	prov:wasGeneratedBy niiri:contrast_estimation_id;
    nidm_errorDegreesOfFreedom: "72.9999999990787"^^xsd:float .

Inference

NIDM-Results Inference
Table 6:NIDM-Results Inference Concepts
NIDM-Results Concept PROV type Identifier
nidm:'Inference' prov:'Activity' nidm:NIDM_0000049
nidm:'Cluster Definition Criteria' prov:'Entity' nidm:NIDM_0000007
nidm:'Cluster Labels Map' nidm:NIDM_0000008
nidm:'Coordinate' nidm:NIDM_0000015
nidm:'Display Mask Map' nidm:NIDM_0000020
nidm:'Excursion Set Map' nidm:NIDM_0000025
nidm:'Extent Threshold' nidm:NIDM_0000026
nidm:'Height Threshold' nidm:NIDM_0000034
nidm:'Peak' nidm:NIDM_0000062
nidm:'Peak Definition Criteria' nidm:NIDM_0000063
nidm:'Search Space Mask Map' nidm:NIDM_0000068
nidm:'Significant Cluster' nidm:NIDM_0000070

nidm:'Inference'

nidm:'Inference': Statistical inference is a process of drawing conclusions following data analysis using statistical methods (statistical tests) and evaluating whether to reject or accept null hypothesis. (definition from STATO).

nidm:'Inference' is a prov:'Activity' that uses nidm:'Cluster Definition Criteria', nidm:'Contrast Map', nidm:'Display Mask Map', nidm:'Peak Definition Criteria', nidm:'Resels Per Voxel Map', nidm:'Statistic Map' entities and has the following children: nidm:'Conjunction Inference', spm:'Partial Conjunction Inference'.

A nidm:'Inference' has attributes:
@prefix nidm_Inference: <http://purl.org/nidash/nidm#NIDM_0000049> .
@prefix nidm_hasAlternativeHypothesis: <http://purl.org/nidash/nidm#NIDM_0000097> .
@prefix nidm_OneTailedTest: <http://purl.org/nidash/nidm#NIDM_0000060> .


niiri:inference_id a prov:Activity , nidm_Inference: ;
	rdfs:label "Inference" ;
	nidm_hasAlternativeHypothesis: nidm_OneTailedTest: ;
    prov:used niiri:statistic_map_id, niiri:height_threshold_id, niiri:extent_threshold_id, niiri:peak_definition_criteria_id, niiri:cluster_definition_criteria_id, niiri:mask_id ;
    prov:wasAssociatedWith niiri:software_id .

nidm:'Conjunction Inference'

nidm:'Conjunction Inference': Statistically testing for the joint significance of multiple effects, with emphasis on rejecting all (instead of one or more) of the respective null hypotheses.

nidm:'Conjunction Inference' is a nidm:'Inference'.

A nidm:'Conjunction Inference' has attributes:

nidm:'One Tailed Test'

A nidm:'One Tailed Test' has attributes:

nidm:'Two Tailed Test'

nidm:'Two Tailed Test': Re-use "two tailed test" from STATO.

nidm:'Two Tailed Test' is a prov:'Entity'.

A nidm:'Two Tailed Test' has attributes:

spm:'Partial Conjunction Inference'

spm:'Partial Conjunction Inference': The process of testing the joint significance of multiple effects to infer that some (not necessarily all) of the respective effects are real (i.e. their null hypotheses are false). If there are K effects considered, the partial conjunction degree u is the number non-null effects allowed as part of partial conjunction null hypothesis; if the partial conjunction null is rejected, it may be inferred that u+1 or more effects are real. The case of u=K-1 corresponds to proper "conjunction inference", while the case of u=0 corresponds to "global null" conjunction test. See Friston et al. (2005). Conjunction revisited. NeuroImage, 25(3), 661-7..

spm:'Partial Conjunction Inference' is a nidm:'Inference'.

A spm:'Partial Conjunction Inference' has attributes:

nidm:'Cluster Definition Criteria'

nidm:'Cluster Definition Criteria': Set of criterion specified a priori to define the clusters reported after inference (e.g. pixel or voxel connectivity criterion).

nidm:'Cluster Definition Criteria' is a prov:'Entity' used by nidm:'Inference'.

A nidm:'Cluster Definition Criteria' has attributes:
@prefix nidm_ClusterDefinitionCriteria: <http://purl.org/nidash/nidm#NIDM_0000007> .
@prefix nidm_hasConnectivityCriterion: <http://purl.org/nidash/nidm#NIDM_0000099> .
@prefix nidm_voxel18connected: <http://purl.org/nidash/nidm#NIDM_0000128> .


niiri:cluster_definition_criteria_id a prov:Entity , nidm_ClusterDefinitionCriteria: ;
	rdfs:label "Cluster Connectivity Criterion: 18" ;
	nidm_hasConnectivityCriterion: nidm_voxel18connected: .

nidm:'Connectivity Criterion'

nidm:'Connectivity Criterion': The criterion used to characterize two voxels, pixels or vertices as 'connected'.

nidm:'Connectivity Criterion' is a prov:'Entity' and has the following children: nidm:'Pixel Connectivity Criterion', nidm:'Voxel Connectivity Criterion'.

A nidm:'Connectivity Criterion' has attributes:

nidm:'Pixel Connectivity Criterion'

nidm:'Pixel Connectivity Criterion': The criterion used to characterize two pixels as 'connected'. In two dimensions voxels that are connected can share an edge (4-connected) or, edge or corner (8-connected).

nidm:'Pixel Connectivity Criterion' is a nidm:'Connectivity Criterion'.

A nidm:'Pixel Connectivity Criterion' has attributes:
Examples of nidm:'Pixel Connectivity Criterion' includes

nidm:'Voxel Connectivity Criterion'

nidm:'Voxel Connectivity Criterion': The criterion used to characterize two voxels as 'connected'. In three dimensions voxels that are connected can share a voxel face (6-connected), face or edge (18-connectec), or face, edge, or corner (26-connected).

nidm:'Voxel Connectivity Criterion' is a nidm:'Connectivity Criterion'.

A nidm:'Voxel Connectivity Criterion' has attributes:
Examples of nidm:'Voxel Connectivity Criterion' includes

nidm:'Cluster Labels Map'

nidm:'Cluster Labels Map': A map whose value at each element (e.g., pixel, voxel, vertex, or face) denotes cluster membership within the excursion set. Each cluster is denoted by a different integer and all members of the same cluster have the same value.

nidm:'Cluster Labels Map' is a nidm:'Map'.

A nidm:'Cluster Labels Map' has attributes:
@prefix nidm_ClusterLabelsMap: <http://purl.org/nidash/nidm#NIDM_0000008> .


niiri:cluster_label_map_id a prov:Entity , nidm_ClusterLabelsMap: ;
	prov:atLocation "file:///path/to/ClusterLabels.nii.gz"^^xsd:anyURI ;
	nfo:fileName "ClusterLabels.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string .

nidm:'Coordinate'

nidm:'Coordinate':

nidm:'Coordinate' is a prov:'Entity'.

A nidm:'Coordinate' has attributes:
  • rdfs:label: (OPTIONAL) Human readable description of the nidm:'Coordinate'.
  • nidm:'coordinate Vector': (OPTIONAL) A vector with one number per dimension. The first element corresponds to the coordinate along the first dimension measured in map elements (e.g., pixels, voxels, vertices, or faces), the second element to the coordinate along the second dimension etc. (range xsd:string).
  • nidm:'coordinate Vector In Voxels': (OPTIONAL) Coordinate along the first dimension in voxels. (This definition needs to be re-worked as this term was renamed from coordinate1 to coordinate in https://github.com/incf-nidash/nidm/issues/270). (range xsd:string).
@prefix nidm_Coordinate: <http://purl.org/nidash/nidm#NIDM_0000015> .
@prefix nidm_coordinateVector: <http://purl.org/nidash/nidm#NIDM_0000086> .


niiri:coordinate_0001 a prov:Entity , prov:Location , nidm_Coordinate: ;
	rdfs:label "Coordinate: 0001" ;
	nidm_coordinateVector: "[ -60, -28, 13 ]"^^xsd:string .

nidm:'Display Mask Map'

nidm:'Display Mask Map': A binary map used by an activity that changed the voxels displayed, but did not alter the space in which the activity was performed (e.g. at the level of inference, this mask is called "contrast masking" in both FSL & SPM and does not alter voxel-wise corrected p-values).

nidm:'Display Mask Map' is a nidm:'Binary Map' used by nidm:'Inference'.

A nidm:'Display Mask Map' has attributes:
@prefix nidm_DisplayMaskMap: <http://purl.org/nidash/nidm#NIDM_0000020> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .


niiri:display_map_id a prov:Entity , nidm_DisplayMaskMap: ;
	rdfs:label "Display Mask Map" ;
	prov:atLocation "file:///path/to/DisplayMask.nii.gz"^^xsd:anyURI ;
	dct:format "image/nifti"^^xsd:string ;
    nfo:fileName "DisplayMask.nii.gz"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_2 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string .

nidm:'Excursion Set Map'

nidm:'Excursion Set Map': A map in which the set of elements (e.g., pixels, voxels, vertices, or faces) not selected by the inference activity is set to zero or NaN.

nidm:'Excursion Set Map' is a nidm:'Map'.

A nidm:'Excursion Set Map' has attributes:
@prefix nidm_ExcursionSetMap: <http://purl.org/nidash/nidm#NIDM_0000025> .
@prefix nidm_hasClusterLabelsMap: <http://purl.org/nidash/nidm#NIDM_0000098> .
@prefix nidm_hasMaximumIntensityProjection: <http://purl.org/nidash/nidm#NIDM_0000138> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .
@prefix nidm_numberOfSignificantClusters: <http://purl.org/nidash/nidm#NIDM_0000111> .
@prefix nidm_pValue: <http://purl.org/nidash/nidm#NIDM_0000114> .


niiri:excursion_set_map_id a prov:Entity , nidm_ExcursionSetMap: ;
	rdfs:label "Excursion Set Map" ;
	prov:atLocation "file:///path/to/ExcursionSet.nii.gz"^^xsd:anyURI ;
	dct:format "image/nifti"^^xsd:string ;
	nfo:fileName "ExcursionSet.nii.gz"^^xsd:string ;
	nidm_hasClusterLabelsMap: niiri:cluster_label_map_id ;
	nidm_hasMaximumIntensityProjection: niiri:maximum_intensity_projection_id ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_1 ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
	nidm_numberOfSignificantClusters: "8"^^xsd:int ;
	nidm_pValue: "8.95949980872501e-14"^^xsd:float ;
	prov:wasGeneratedBy niiri:inference_id .

nidm:'Extent Threshold'

nidm:'Extent Threshold': A numerical value that establishes a lower bound on cluster-sizes and can be specified by the user in terms of FWER-corrected p-value, uncorrected p-value or minimum cluster size in voxels.

nidm:'Extent Threshold' is a nidm:'Threshold'.

A nidm:'Extent Threshold' has attributes:
@prefix nidm_ExtentThreshold: <http://purl.org/nidash/nidm#NIDM_0000026> .
@prefix nidm_PValueUncorrected: <http://purl.org/nidash/nidm#NIDM_0000160> .


niiri:extent_threshold_unc_id a prov:Entity, nidm_ExtentThreshold:, nidm_PValueUncorrected: ;
    rdfs:label "Extent Threshold: p<0.001 (uncorrected)" ;
    prov:value "0.001"^^xsd:float .
@prefix nidm_ExtentThreshold: <http://purl.org/nidash/nidm#NIDM_0000026> .
@prefix nidm_clusterSizeInVoxels: <http://purl.org/nidash/nidm#NIDM_0000084> .
@prefix nidm_clusterSizeInResels: <http://purl.org/nidash/nidm#NIDM_0000156> .
@prefix obo_statistic: <http://purl.obolibrary.org/obo/STATO_0000039> .


niiri:extent_threshold_stat_id a prov:Entity, nidm_ExtentThreshold:, obo_statistic: ;
    rdfs:label "Extent Threshold: k>=0" ;
    nidm_clusterSizeInVoxels: "0"^^xsd:int ;
    nidm_clusterSizeInResels: "0"^^xsd:float .
@prefix nidm_ExtentThreshold: <http://purl.org/nidash/nidm#NIDM_0000026> .
@prefix nidm_equivalentThreshold: <http://purl.org/nidash/nidm#NIDM_0000161> .
@prefix obo_FWERadjustedpvalue: <http://purl.obolibrary.org/obo/OBI_0001265> .


niiri:extent_threshold_fwer_id a prov:Entity, nidm_ExtentThreshold:, obo_FWERadjustedpvalue: ;
    rdfs:label "Extent Threshold: p<0.05 (FWER-corrected)" ;
    prov:value "0.05"^^xsd:float ;
    nidm_equivalentThreshold: niiri:extent_threshold_stat_id .
@prefix nidm_ExtentThreshold: <http://purl.org/nidash/nidm#NIDM_0000026> .
@prefix obo_qvalue: <http://purl.obolibrary.org/obo/OBI_0001442> .


niiri:extent_threshold_fdr_id a prov:Entity, nidm_ExtentThreshold:, obo_qvalue: ;
    rdfs:label "Extent Threshold: p<0.05 (FDR-corrected)" ;
    prov:value "0.05"^^xsd:float .

nidm:'Threshold'

nidm:'Threshold': A numerical value that establishes a bound on a set of statistic values and can be specified by the user in terms of FWER-corrected p-value, uncorrected p-value, FDR-corrected q-value or statistic value.

nidm:'Threshold' is a prov:'Entity' and has the following children: nidm:'Extent Threshold', nidm:'Height Threshold'.

A nidm:'Threshold' has attributes:

nidm:'Height Threshold'

nidm:'Height Threshold': A numerical value that establishes a lower bound on statistic values and can be specified by the user in terms of FWER-corrected p-value, uncorrected p-value or minimum statistic value.

nidm:'Height Threshold' is a nidm:'Threshold'.

A nidm:'Height Threshold' has attributes:
@prefix nidm_HeightThreshold: <http://purl.org/nidash/nidm#NIDM_0000034> .
@prefix nidm_PValueUncorrected: <http://purl.org/nidash/nidm#NIDM_0000160> .


niiri:height_threshold_unc_id a prov:Entity, nidm_HeightThreshold:, nidm_PValueUncorrected: ;
    rdfs:label "Height Threshold: p<0.001 (uncorrected)" ;
    prov:value "0.001"^^xsd:float .
@prefix nidm_HeightThreshold: <http://purl.org/nidash/nidm#NIDM_0000034> .
@prefix nidm_equivalentThreshold: <http://purl.org/nidash/nidm#NIDM_0000161> .
@prefix obo_FWERadjustedpvalue: <http://purl.obolibrary.org/obo/OBI_0001265> .


niiri:height_threshold_fwer_id a prov:Entity, nidm_HeightThreshold:, obo_FWERadjustedpvalue: ;
    rdfs:label "Height Threshold: p<0.05 (FWER-corrected)" ;
    prov:value "0.05"^^xsd:float ;
    nidm_equivalentThreshold: niiri:height_threshold_stat_id .
@prefix nidm_HeightThreshold: <http://purl.org/nidash/nidm#NIDM_0000034> .
@prefix obo_qvalue: <http://purl.obolibrary.org/obo/OBI_0001442> .


niiri:height_threshold_fdr_id a prov:Entity, nidm_HeightThreshold:, obo_qvalue: ;
    rdfs:label "Height Threshold: p<0.05 (FDR-corrected)" ;
    prov:value "0.05"^^xsd:float .
@prefix nidm_HeightThreshold: <http://purl.org/nidash/nidm#NIDM_0000034> .
@prefix obo_statistic: <http://purl.obolibrary.org/obo/STATO_0000039> .


niiri:height_threshold_stat_id a prov:Entity, nidm_HeightThreshold:, obo_statistic: ;
    rdfs:label "Height Threshold: Z<0.0000000672357409" ;
    prov:value "0.0000000672357409"^^xsd:float .

nidm:'Peak'

nidm:'Peak': A map element (e.g., pixel, voxel, vertex, or face) which is a local maximum in the significant cluster and complies with the peak definition criteria.

nidm:'Peak' is a prov:'Entity' derived from nidm:'Significant Cluster'.

A nidm:'Peak' has attributes:
  • rdfs:label: (OPTIONAL) Human readable description of the nidm:'Peak'.
  • nidm:'equivalent ZStatistic': (OPTIONAL) Statistic value transformed into Z units; the output of a process which takes a non-normal statistic and transforms it to an equivalent z score. (range xsd:float).
  • nidm:'p Value FWER': (OPTIONAL) "A quantitative confidence value resulting from a multiple testing error correction method which adjusts the p-value used as input to control for Type I error in the context of multiple pairwise tests". (range xsd:float).
  • nidm:'p Value Uncorrected': (OPTIONAL) A p-value reported without correction for multiple testing. . (range xsd:float).
  • nidm:'q Value FDR': (OPTIONAL) A quantitative confidence value that measures the minimum false discovery rate that is incurred when calling that test significant. To compute q-values, it is necessary to know the p-value produced by a test and possibly set a false discovery rate level (same as OBI_0001442). (range xsd:float).
@prefix nidm_Peak: <http://purl.org/nidash/nidm#NIDM_0000062> .
@prefix nidm_pValueUncorrected: <http://purl.org/nidash/nidm#NIDM_0000116> .
@prefix nidm_equivalentZStatistic: <http://purl.org/nidash/nidm#NIDM_0000092> .
@prefix nidm_pValueFWER: <http://purl.org/nidash/nidm#NIDM_0000115> .
@prefix nidm_qValueFDR: <http://purl.org/nidash/nidm#NIDM_0000119> .


niiri:peak_0001 a prov:Entity , nidm_Peak: ;
    rdfs:label "Peak 0001" ;
    prov:atLocation niiri:coordinate_0001 ;
    nidm_pValueUncorrected: "4.44089209850063e-16"^^xsd:float ;
    nidm_equivalentZStatistic: "INF"^^xsd:float ;
    prov:wasDerivedFrom niiri:significant_cluster_0001 ;
    prov:value "13.9346199035645"^^xsd:float ;
	nidm_pValueFWER: "0"^^xsd:float ;
	nidm_qValueFDR: "6.3705194444993e-11"^^xsd:float .

nidm:'Peak Definition Criteria'

nidm:'Peak Definition Criteria': Set of criterion specified a priori to define the peaks reported after inference (e.g. maximum number of peaks within a cluster, minimum distance between peaks).

nidm:'Peak Definition Criteria' is a prov:'Entity' used by nidm:'Inference'.

A nidm:'Peak Definition Criteria' has attributes:
@prefix nidm_PeakDefinitionCriteria: <http://purl.org/nidash/nidm#NIDM_0000063> .
@prefix nidm_minDistanceBetweenPeaks: <http://purl.org/nidash/nidm#NIDM_0000109> .
@prefix nidm_maxNumberOfPeaksPerCluster: <http://purl.org/nidash/nidm#NIDM_0000108> .


niiri:peak_definition_criteria_id a prov:Entity , nidm_PeakDefinitionCriteria: ;
	rdfs:label "Peak Definition Criteria" ;
	nidm_minDistanceBetweenPeaks: "8.0"^^xsd:float ;
    nidm_maxNumberOfPeaksPerCluster: "3"^^xsd:int .

nidm:'Search Space Mask Map'

nidm:'Search Space Mask Map': A mask map representing the set of elements (e.g., pixels, voxels, vertices, or faces) in which the inference was performed.

nidm:'Search Space Mask Map' is a nidm:'Mask Map'.

A nidm:'Search Space Mask Map' has attributes:
@prefix nidm_SearchSpaceMaskMap: <http://purl.org/nidash/nidm#NIDM_0000068> .
@prefix nidm_inCoordinateSpace: <http://purl.org/nidash/nidm#NIDM_0000104> .
@prefix nidm_expectedNumberOfVoxelsPerCluster: <http://purl.org/nidash/nidm#NIDM_0000143> .
@prefix nidm_expectedNumberOfClusters: <http://purl.org/nidash/nidm#NIDM_0000141> .
@prefix nidm_heightCriticalThresholdFWE05: <http://purl.org/nidash/nidm#NIDM_0000147> .
@prefix nidm_heightCriticalThresholdFDR05: <http://purl.org/nidash/nidm#NIDM_0000146> .
@prefix nidm_searchVolumeInVoxels: <http://purl.org/nidash/nidm#NIDM_0000121> .
@prefix nidm_searchVolumeInUnits: <http://purl.org/nidash/nidm#NIDM_0000136> .
@prefix nidm_reselSizeInVoxels: <http://purl.org/nidash/nidm#NIDM_0000148> .
@prefix nidm_searchVolumeInResels: <http://purl.org/nidash/nidm#NIDM_0000149> .
@prefix nidm_noiseFWHMInVoxels: <http://purl.org/nidash/nidm#NIDM_0000159> .
@prefix nidm_noiseFWHMInUnits: <http://purl.org/nidash/nidm#NIDM_0000157> .
@prefix nidm_randomFieldStationarity: <http://purl.org/nidash/nidm#NIDM_0000120> .
@prefix spm_smallestSignificantClusterSizeInVoxelsFWE05: <http://purl.org/nidash/spm#SPM_0000014> .
@prefix spm_smallestSignificantClusterSizeInVoxelsFDR05: <http://purl.org/nidash/spm#SPM_0000013> .
@prefix spm_searchVolumeReselsGeometry: <http://purl.org/nidash/spm#SPM_0000010> .


niiri:search_space_mask_id a prov:Entity , nidm_SearchSpaceMaskMap: ;
	rdfs:label "Search Space Mask Map" ;
	prov:atLocation "file:///path/to/SearchSpaceMask.nii.gz"^^xsd:anyURI ;
	nfo:fileName "SearchSpaceMask.nii.gz"^^xsd:string ;
	dct:format "image/nifti"^^xsd:string ;
	nidm_inCoordinateSpace: niiri:coordinate_space_id_2 ;
	nidm_expectedNumberOfVoxelsPerCluster: "0.553331387916112"^^xsd:float ;
	nidm_expectedNumberOfClusters: "0.0889172687960151"^^xsd:float ;
	nidm_heightCriticalThresholdFWE05: "5.23529984739211"^^xsd:float ;
	nidm_heightCriticalThresholdFDR05: "6.22537899017334"^^xsd:float ;
	spm_smallestSignificantClusterSizeInVoxelsFWE05: "1"^^xsd:int ;
	spm_smallestSignificantClusterSizeInVoxelsFDR05: "3"^^xsd:int ;
	nidm_searchVolumeInVoxels: "65593"^^xsd:int ;
	nidm_searchVolumeInUnits: "1771011"^^xsd:float ;
	nidm_reselSizeInVoxels: "22.9229643140043"^^xsd:float ;
	nidm_searchVolumeInResels: "2552.68032521656"^^xsd:float ;
	spm_searchVolumeReselsGeometry: "[3, 72.3216126440484, 850.716735116472, 2552.68032521656]"^^xsd:string ;
	nidm_noiseFWHMInVoxels: "[ 2.95881189165801, 2.96628446669584, 2.61180425626264 ]"^^xsd:string ;
	nidm_noiseFWHMInUnits: "[ 8.87643567497404, 8.89885340008753, 7.83541276878791 ]"^^xsd:string ;
	nidm_randomFieldStationarity: "false"^^xsd:boolean ;
	crypto:sha512 "e43b6e01b0463fe7d40782137867a..."^^xsd:string ;
	prov:wasGeneratedBy niiri:inference_id .

nidm:'Significant Cluster'

nidm:'Significant Cluster': A cluster of map elements (e.g., pixels, voxels, vertices, and faces) that were selected by the inference activity and are contiguous according to the cluster connectivity criteria.

nidm:'Significant Cluster' is a nidm:'Cluster' derived from nidm:'Excursion Set Map'.

A nidm:'Significant Cluster' has attributes:
@prefix nidm_SignificantCluster: <http://purl.org/nidash/nidm#NIDM_0000070> .
@prefix nidm_clusterSizeInVoxels: <http://purl.org/nidash/nidm#NIDM_0000084> .
@prefix nidm_clusterLabelId: <http://purl.org/nidash/nidm#NIDM_0000082> .
@prefix nidm_clusterSizeInResels: <http://purl.org/nidash/nidm#NIDM_0000156> .
@prefix nidm_pValueUncorrected: <http://purl.org/nidash/nidm#NIDM_0000116> .
@prefix nidm_pValueFWER: <http://purl.org/nidash/nidm#NIDM_0000115> .
@prefix nidm_qValueFDR: <http://purl.org/nidash/nidm#NIDM_0000119> .


niiri:significant_cluster_0001 a prov:Entity , nidm_SignificantCluster: ;
	rdfs:label "Significant Cluster 0001" ;
	nidm_clusterSizeInVoxels: "530"^^xsd:int ;
	nidm_clusterLabelId: "1"^^xsd:int ;
	nidm_clusterSizeInResels: "23.1209189500945"^^xsd:float ;
	nidm_pValueUncorrected: "9.56276736481136e-52"^^xsd:float ;
	nidm_pValueFWER: "0"^^xsd:float ;
	nidm_qValueFDR: "7.65021389184909e-51"^^xsd:float ;
	prov:wasDerivedFrom niiri:excursion_set_map_id .

Release notes: updates since NIDM-Results 1.0.0

Updated terms

noise FWHM (PR 328):

Partial Conjunction Degree in spm namespace (PR 334):

Extent Threshold and Height Threshold attributes (PR 329)