
READ ME File For 'The neural representation of self data sets'

Dataset DOI: https://doi.org/10.5258/SOTON/D3730

ReadMe Author: Marie Levorsen, University of Southampton, 0000-0003-1158-1659

This dataset supports the thesis entitled The Neural Representation of The Self
AWARDED BY: University of Southampton
DATE OF AWARD: 2025


Date of data collection:July 2019- February 2024

Information about geographic location of data collection: The data collection for the two experiments in Chapter 2 were conducted in Japan (experiment 1 at Tamagawa University and experiment 2 at Kochi University of Technology). The data collected for Chapter 3 was collected at the University of Southampton. The data collection for Chapter 4 was conducted at Kochi University of Technology. 

Licence:
CC BY

Related projects/Funders:
This research was supported by the Economic and Social Research Council (ESRC), the South Coast Doctoral
Training Partnership Grant Number ES/P000673/1 as a PhD studentship (to M.L.). This research was also
supported by the Japan Society for Promotion of Science (JSPS) KAKENHI Grant Number JP19K24680 (to K.I.)
and the Ministry of Education, Culture, Sports, Science and Technology (MEXT) as part of Joint Research
Program implemented at Tamagawa University Brain Science Institute, in Japan




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DATA & FILE OVERVIEW
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The folder Thesis_data is a zip folder containing the following folders/files:

Chapter 2: 

The folder: The Self-Concept is Represented in the mPFC in Terms of Self-Importance

This folder contains:
1)  3 unthresholded statistical map files: 
Ex1_Self_Imp_Self_task_spmT_0001.nii.gz
Ex2_Self_Imp_Self_task_spmT_0001.nii.gz
Mega_Self_Imp_Self_task_spmT_0001.nii.gz

2) And one anatomical brain mask which which was used in the study:
mPFC_aal_Frontal_Sup_medial_Frontal_Mid_Orb_Rectus_ACC_D2.mldatx.nii.gz

Chapter 3: 

The file: dataTable

This file contains all the variables and data for the experiment presented in chapter 3 of the thesis. 

Specifically it includes a 13555x16 matrix with the following coloumns: Trial, block, Item (stimuli presented, RT (Reaction time), Target (target word presented in the priming task), val (valence rating of items, imp (self-importance ratings of items), desc (self-descriptiveness rating of items), correct (whether response in priming task was correct or incorrect, 1 = correct), log_RT (log transformed reaction time), condition (condition in the priming task), standardized_val (standardized valence rating), standardized_desc (standardized self-descriptiveness rating), standardized_imp (standardized self-importance rating), participantNumber, participantID. 

Chapter 4: 

The folder: Decomposing Cognitive Processes in the mPFC During Self-Thinking

This folder contains: 

1) The unthresholded group statistical maps for the univariate analysis, the RSA and the MVPA analysis. 

4a_Self-Semantic_spmT_0001.nii.gz
4b_Other-Semantic_spmT_0001.nii.gz
4c_Introspection-categorization_spmT_0001.nii.gz
4d_Memory-knowledge_spmT_0001.nii.gz
4g_Restvalcatknow_spmT.nii.gz

2) The RSA
5a_RSA_self-other_spmT.nii.gz
5b_RSA_self-introspection_spmT.nii.gz
5c_RSA_self-memory_spmT.nii.gz

3)
5d_MVPA_self-semantic_vs_other-semantic_spmT.nii.gz
5e_MVPA_self-semantic_vs_intro-categ_spmT.nii.gz
5f_MVPA_self-semantic_vs_mem-know_spmT.nii.gz



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METHODOLOGICAL INFORMATION
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Description of methods used for collection/generation and processing of data, and experimental design of the data:

Chapter 2:  https://doi.org/10.1523/JNEUROSCI.2178-22.2023
Chapter 3: Data was collected using online questionnaires and lab based reaction time task (evaluative priming task), reaction time was log transformed and ratings were standardised (both standardised and raw scores are included in the table)
Chapter 4:  https://doi.org/10.1523/JNEUROSCI.2378-24.2025


Software- or Instrument-specific information needed to interpret the data, including software and hardware version numbers:

The “dataTable.mat” file was created in MATLAB R2023b. It can be loaded with:
MATLAB, load(“dataTable.mat”)
The fMRI data can be loaded with SPM implemented in MATLAB. Click “Results” and upload the images. 


People involved with sample collection, processing, analysis and/or submission:

Chapter 2: Marie Levorsen, Ryuta Aoki, Kenji Matsumoto and Keise Izuma
Chapter 3: Marie Levorsen and Keise Izuma
Chapter 4: Marie Levorsen, Ryuta Aoki and Keise Izuma

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DATA-SPECIFIC INFORMATION <Create sections for each datafile or set, as appropriate>
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Variable list, defining any abbreviations, units of measure, codes or symbols used:
  
Chapter 2 variables: 
Self importance

Chapter 3 variables:
Self-importance 
Self_descriptiveness
Valence
Reaction time
Condition (target)

Chapter 4 variables: 
Self-reference
Other-reference
Semantic
Introspection
Categorisation
Memory
General knowledge
Rest

Specialised formats or other abbreviations used: RSA = Representational similarity analysis, MVPA = Multi-voxel pattern analysis

Date that the file was created: October, 2025
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