diff --git a/example1/resources/README.md b/example1/README.md
similarity index 59%
rename from example1/resources/README.md
rename to example1/README.md
index 7de8b90af73eb18195feb6b674583b69edb8d6ab..a2f3a3b290414760c0a9664199cef7e466b1e628 100644
--- a/example1/resources/README.md
+++ b/example1/README.md
@@ -1,8 +1,33 @@
 # Bidscoin Example 1
 
-## Introduction
+## Table of contents
+
+- [Introduction](#intro)
+- [Experiment description](#exp)
+  - [High Cognitive Load (HCL) session](#exp_hcl)
+  - [Low Cognitive Load (LCL) session](#exp_lcl)
+  - [Stroop session](#exp_stroop)
+	- [Working memory task description](#exp_mem)
+	- [Assessment description](#exp_ass)
+- [Dataset structure](#ds)
+  - [Acquired data files](#ds_data)
+	- [Additional files](#ds_aux)
+  - [Bidscoin files](#ds_bids)
+- [How to run example](#run)
+	- [Data preparation](#run_prep)
+	- [Bidsmap creation](#run_map)
+	- [Data processing](#run_proc)
+	- [Data bidsification](#run_bids)
+	
+Task results are formatted following [bids](https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/05-task-events.html),
+and stored in `source/<subject>/<session>/nii/FCsepNBack.tsv` file.
+
+The results are formatted following [bids](https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#phenotypic-and-assessment-data),
+and stored in `source/<subject>/<session>/nii/VAS.tsv`
 
-This dataset is an purely fictional, designed to demonstrate the core 
+## <a name="intro"></a> Introduction
+
+This dataset is a purely fictional, designed to demonstrate the core 
 features of `bidscoin` bidsifier tool. 
 
 The structure of dataset is modelled of real-life dataset, currently unpublished.
@@ -15,108 +40,83 @@ for [SPM12](https://www.fil.ion.ucl.ac.uk/spm/software/spm12/).
 All `.nii` images are replaced by an empty file, and any personal information is removed
 from json files.
 
-## Experiment description
-
-The experiment is designed to study of effect of fatigue on memory performance.
-
-5 participants are separated into pairs with matched sex, age and years of education.
-First persons of pairs are used for study (patient group), while paired persons are used for control.
-
-During experiment, each participant is scanned 3 times (sessions), for each of session they are asked to perform either a memory or a stroop task:
-
-- **HLC** with memory task performed after a tiring task (High Cognitive Load)
-  - In additional to functional and structural, a diffusion scan is present
-- **LCL** with memory task performed without tiring task (Low Cognitive Load)
-  - Session contains structural and functional MRI scans
-- **STROOP** with a standard stroop task
-  - session contains only multi parametric mapping MRI (MPM)
-
-The order in which each scan is performed may vary from participant to participant.
-
-## Original dataset structure
-
-The original data is stored in `source` directory. Data corresponding to each participants
-is stored in `source/<participant id>` sub-folder, where `<participant id>` the code of 
-participant padded with `0`.
-
-Inside participants sub-folders, 3 folders of session data is places. The folder names 
-don't have a direct correspondence with session, bit represent a code applied by a scanner,
-in form `sXYZ`.
-
-The image data is stored directly in session sub-folder `nii`.
-For **LCL** and **HCL** sessions, task and assessment are stored in `inp` sub-folder.
-
-Tiring task, and stroop task data are not present in dataset.
-
-### Memory task description
-
-Task consist of a classic n-back working memory update task.
-A set of letters is presented to participant. Each letter is presented during `1.7s`,
-followed by `0.5s` fixation cross presentation. Participant is asked to remember 
-if such letter was present in the last, 2 cards ago or 3 cards age (1back, 2back, 3back).
-A participant response ("c" for correct, "n" for non-correct) is registered alongside with
-expected response. 
-A fill task consists of 18 blocks of 1,2,3-back tasks, with 16 presented letters in each block.
+## <a name="exp_descr"></a>Experiment description
 
-Task results are formatted following [bids](https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/05-task-events.html),
-and stored in `source/<subject>/<session>/nii/FCsepNBack.tsv` file.
+The experiment is designed to study of effect of fatigue on cognition
+(working memory and processing speed) and to identify brain
+correlates of cognitive fatigue in patterns with multiple sclerosis
+compared to healthy controls.
 
-### Assesment description
+In total dataset contains 4 participants, two in `patient` group and two
+in `control` group with matched demographic information (age, sex and
+years of educations).
+The demographic data for each matched pair is randomly generated.
 
-Each task is followed by visual analogue assessment (VAS) questioner, where participant is 
-asked to estimate his psychological state from bad (0) to good (100).
-In particular the next estimations are requested:
+During experiment, each participant is scanned 3 times (sessions),
+during three separate days. 
+Each session started with a cognitive task outside the scanner:
+either a Stroop task or dual-task (Time Load Dual Back) in which
+cognitive was manipulated.
 
-- **Motivation**
-- **Hapiness**
-- **Fatigue**
-- **Openness**
-- **Stress**
-- **Anxiety**
-- **Effort**
+The order in which each scan is performed was counterbalanced from participant
+to participant.
 
-The results are formatted following [bids](https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#phenotypic-and-assessment-data),
-and stored in `source/<subject>/<session>/nii/VAS.tsv`
+### <a name="exp_hcl"></a>High Cognitive Load (HCL) session
 
-### MRI scanning sessions
+High Cognitive Load (HCL) session was performed with dual-task performed
+in a tiring condition.
+Functional acquisition were performed while participant where answering 
+to a classical working memory task (N-back) with three levels of difficulty,
+as well as during resting state.
 
-#### LCL
+During HCL session following MRI acquisitions has been acquired:
 
-During the LCL session, the next acquisitions are taken:
- 
 - localisation (protocol: `localizer`)
 - a short fMRI sequence with inverted phase-encoding direction
-(protocol: `cmrr_mbep2d_bold_mb2_invertpe`)  
-- a fMRI sequence during nBack task execution (protocol: `cmrr_mbep2d_bold_mb2_task_nfat`)
+(protocol: `cmrr_mbep2d_bold_mb2_invertpe`) 
+- a fMRI sequence during nBack task execution (protocol:
+`cmrr_mbep2d_bold_mb2_task_fat`)
 - a short fMRI sequence with inverted phase-encoding direction
-(protocol: `cmrr_mbep2d_bold_mb2_invertpe`)  
-- a fMRI sequence without task execution -- in resting state (protocol: `cmrr_mbep2d_bold_mb2_rest`)
+(protocol: `cmrr_mbep2d_bold_mb2_invertpe`) 
+- a fMRI sequence without task execution -- in resting state (protocol:
+`cmrr_mbep2d_bold_mb2_rest`)
 - a magnitude encoded fieldmap sequence (protocol: `gre_field_mapping`)
 - a phase-difference fieldmap sequence (protocol: `gre_field_mapping`)
-- a FLAIR sequence (protocol: `t1_mpr_sag_p2_iso`)
-- a T2 weighted sequence (protocol: `t2_spc_da-fl_sag_p2_iso`)
+- a diffusion sequence with inverted gradient direction (protocol:
+`cmrr_mbep2d_diff_NODDI_invertpe`)
+- a diffusion sequence with normal gradient direction (protocol:
+`cmrr_mbep2d_diff_NODDI`)
+- a diffusion sequence without RF-pulse (protocol:
+`cmrr_mbep2d_diff_NODDI_noise`)
 
-#### HCL
+### <a name="exp_lcl"></a> Low Cognitive Load (LCL) session
 
-During HCL session, the next acquisitions are taken:
+Low Cognitive Load (LCL) session was performed in control conditions.
+Functional acquisition were performed while participant where answering 
+to a classical working memory task (N-back) with three levels of difficulty,
+as well as during resting state.
 
+During LCL session following MRI acquisitions has been acquired:
+ 
 - localisation (protocol: `localizer`)
 - a short fMRI sequence with inverted phase-encoding direction
-(protocol: `cmrr_mbep2d_bold_mb2_invertpe`)  
-- a fMRI sequence during nBack task execution (protocol: `cmrr_mbep2d_bold_mb2_task_fat`)
+(protocol: `cmrr_mbep2d_bold_mb2_invertpe`) 
+- a fMRI sequence during nBack task execution (protocol:
+`cmrr_mbep2d_bold_mb2_task_nfat`)
 - a short fMRI sequence with inverted phase-encoding direction
-(protocol: `cmrr_mbep2d_bold_mb2_invertpe`)  
-- a fMRI sequence without task execution -- in resting state (protocol: `cmrr_mbep2d_bold_mb2_rest`)
+(protocol: `cmrr_mbep2d_bold_mb2_invertpe`) 
+- a fMRI sequence without task execution -- in resting state (protocol:
+`cmrr_mbep2d_bold_mb2_rest`)
 - a magnitude encoded fieldmap sequence (protocol: `gre_field_mapping`)
 - a phase-difference fieldmap sequence (protocol: `gre_field_mapping`)
-- a diffusion sequence with inverted gradient direction (protocol: `cmrr_mbep2d_diff_NODDI_invertpe`)
-- a diffusion sequence with normal gradient direction (protocol: `cmrr_mbep2d_diff_NODDI`)
-- a diffusion sequence without RF-pulse (protocol: `cmrr_mbep2d_diff_NODDI_noise`)
-
+- a T1 FLAIR sequence (protocol: `t1_mpr_sag_p2_iso`)
+- a T2 FLAIR sequence (protocol: `t2_spc_da-fl_sag_p2_iso`)
 
-#### STROOP
+### <a name="exp_stroop"></a>STROOP session
 
-During STROOP session, the next acquisitions are taken:
+STROOP session was performed with a computerized Stroop task.
+The session contains only multi parametric mapping MRI (MPM), consisting in
+following acquisitions:
 
 - localisation (protocol: `localizer`)
 - head-localised fieldmap for PD weighted sMRI (protocol: `al_mtflash3d_sensArray`) 
@@ -135,11 +135,79 @@ During STROOP session, the next acquisitions are taken:
 - a magnitude encoded fieldmap sequence (protocol: `gre_field_mapping`)
 - a phase-difference fieldmap sequence (protocol: `gre_field_mapping`)
 
-### Additional files
+### <a name="exp_mem"></a>Working Memory task description
 
-All non-data files corresponding to dataset are stored in `resources` subfolder
+Task consist of a classic n-back working memory update task.
+A set of letters is presented to participant. 
+Each letter is presented during 1.7 seconds, followed by 0.5 seconds
+fixation cross presentation. 
+For each letter, participant was asked to determine if it matches the
+one presented N positions before it (*1back*: the previous one,
+*2back*: the second last, *3back*: the third last letter presented).
+A participant response (*c* for yes, *n* for no) is registered alongside
+expected response. 
+A full task consists of 6 blocks of 16 stimuli for each condition, in
+total 18 blocks.
+At the end of each block, a fixation cross was presented for 12 seconds.
 
-#### Participants bookkeeping `Appariement.xlsx`
+
+### <a name="exp_ass"></a>Assessment description
+
+Each task is followed the Karolinska sleepiness Scale as well as visual
+analogue scale (VAS), where participant is asked to estimate his
+psychological state from low (0) to high (100).
+In particular the next estimations are requested:
+
+- **Motivation**
+- **Hapiness**
+- **Fatigue**
+- **Openness**
+- **Stress**
+- **Anxiety**
+- **Effort** to perform task
+
+
+## <a name="ds_descr"></a>Dataset structure
+
+The non-bidsified dataset is stored in `source` directory.
+
+Additional files, needed to bidsify dataset are stored in `resources`
+directory
+
+
+### <a name="ds_data"></a>Acquired data files
+
+Data corresponding to each participants is stored in `source/<participant id>`
+sub-folder, where `<participant id>` the code of participant padded with `0`.
+
+Inside participants sub-folders, 3 folders of session data is places.
+The folder names don't have a direct correspondence with session,
+but represent a code applied by a scanner, in form `sXYZ`.
+
+The MRI image data is stored directly in session sub-folder `nii`. 
+The image file format simulates the DICOM format converted to Nifti
+by  [hmri toolbox](https://hmri-group.github.io/hMRI-toolbox/).
+The `.nii` data files are empty files, and `.json` files contains DICOM
+header bump.
+
+Task and assessment files (if present) are stored in `inp` sub-folders.
+They are formatted following BIDS (for
+[task](https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/05-task-events.html),
+and for 
+[assessement](https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#phenotypic-and-assessment-data)).
+
+Dual-task, and Stroop task data are not present in dataset.
+
+### <a name="ds_aux"></a>Additional files
+
+A set of files, containing additional information needed for bidsification
+is stored in `resources` folder.
+It contains a number of
+[sidecar json](https://bids-specification.readthedocs.io/en/stable/02-common-principles.html#tabular-files) 
+files for various bids tables, a table of participants and gradient direction
+files needed for diffusion data.
+
+#### <a name="ds_aux_part"></a>Participants bookkeeping `Appariement.xlsx`
 
 `Appariement.xlsx` is an excel table containing the list of participants with key 
 demographic data.
@@ -161,7 +229,7 @@ Columns are, in order:
 - **2**: Name of the second scanned session
 - **3**: Name of the third scanned session
 
-#### Sidecar json files
+#### <a name=ds_aux_json></a>Sidecar json files
 
 Prepeared json files to use as [descriptions](https://bids-specification.readthedocs.io/en/stable/02-common-principles.html#tabular-files) 
 for bidsified `.tsv` files:
@@ -174,13 +242,23 @@ demonstration of participant table manipulations by `bidscoin`
 - `VAS.json` is sidecar json file for VAS
 
 
-#### bval and bvec files
+#### <a name="ds_aux-bval"></a>bval and bvec files
 
 `bval` and `bvec` files used to accompany [diffusion data](https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/01-magnetic-resonance-imaging-data.html#diffusion-imaging-data)
-are placed in `resources/diffusion` folder. They are common to all diffusion images used
-in this dataset.
+are placed in `resources/diffusion` folder.
+They are common to all diffusion images used in this dataset.
+
+#### <a name="ds_aux_descr"></a>Dataset description files
+A minimal example of dataset desctiption
+[file](https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#dataset-description)
+is stored at `resources/dataset_description.json`.
+
+### <a name="ds_bids"></a>Bidscoin files
 
-#### Bidsmap files
+A set of files needed to run the example  are stored in `resources/map` and
+`resources/plugins`
+
+#### <a name="ds_bids_map"></a>Bidsmap files
 
 Generated bidsmap files, that can be used to bidsify this dataset are placed in `resources/map` directory:
 
@@ -189,7 +267,7 @@ Generated bidsmap files, that can be used to bidsify this dataset are placed in
 
 These files can be used with `-b` option directly, or copied into `bids/code/bidscoin` directory.
 
-#### Plugins
+#### <a name="ds_bids_plug"></a>Plugins
 
 The plugins are stored in `resources/plugins` directory, and contains commented example of additional data management provided by `bidscoin` infrastructure.
 
@@ -198,28 +276,21 @@ The plugins are stored in `resources/plugins` directory, and contains commented
 - `process_plugin.py` contains some example of intermediate data processing, namely merging functional and diffusion 3D images into 4D images, it also shows example of subject demographic data modification
 - `bidsify_plugin.py` contains examples of recording metadata modification in order to facilitate recordings identification
 
-#### Dataset description files
-[The dataset description](https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#dataset-description)
-consists of two files:
-
-- `dataset_description.json`, a minimal example of json file describing dataset
-- `README.md`, this file
 
-
-## How to run example
+## <a name="run"></a>How to run example
 
 Dataset bidsification is composed of two steps: data preparation and data bidsification.
 An optional data-processing step can be inserted between preparation and bidsification.
 
 A one-time step of bidsmap creation may be necessary.
 
-### Data preparation
+### <a name="run_prep"></a>Data preparation
 
 In this step, a generic user-defined dataset is organized in a standardized way.
 
 To run data preparation, it will be enough to run from `example1` directory
 
-```
+```python
 python3 bidscoin.py prepare --part-template resources/participants.json --recfolder nii=MRI --plugin resources/plugins/rename_plugin.py source/ renamed/
 ```
 
@@ -227,7 +298,7 @@ The options `--part-template resources/participants.json` will tell bidscoin to
 The column `participant_id` will be filled automatically, while other columns will be filled 
 by default by `n/a`, unless they are set in plugin:
 
-```
+```python
 session.sub_values["sex"] = "M"
 ```
 
@@ -245,7 +316,7 @@ After the execution of preparation, the `rename` folder should contain folders a
 - **code/bidscoin**, with log files of the last execution of preparation step
 - **participants.tsv** and **participants.json** files with formatted and filled participant list, all columns for all subjects must be filled except `handiness`, which should contain only `n/a`
 - **sub-00X** folders for subjects 1-4
-  - **ses-HCL** sub-folders with bidsified session name (either `ses-LCL`, if run with plugin, of `ses-s01905` if run without plugin)
+  - **ses-HCL** sub-folders with bidsified session name (either `ses-HCL`, if run with plugin, of `ses-s01905` if run without plugin)
     - **auxiliary** folder with task and VAS tables and json (only if run with plugin)
     - **MRI** subfolder containing MRI data
       - **00x-<seq_name>** folders with original image data organased by sequences
@@ -255,25 +326,25 @@ For example the participant table can be corrected if contain wrong or missing v
 
 Running bidscoin with all options can be tedious. To streamline the experience, the majority of options can be saved in configuration file by running 
 
-```
+```python
 python3 bidscoin.py -c conf.yamel --conf-save prepare <options> source/ renamed/
 ```
 
 This will create a local `conf.yamel` file with passed options. 
 To load the configuration:
 
-```
+```python
 python3 bidscoin.py -c conf.yamel prepare source/ renamed/
 ```
 
 Passing other options and using switch `--conf-save` will update configuration file.
 
 
-### Bidsmap creation
+### <a name="run_map"></a>Bidsmap creation
 
 Bidsmap is created/tested with `map` command:
 
-```
+```python
 python3 bidscoin.py map --plugin resources/plugins/bidsify_plugin.py --template bidsmap_template.yaml renamed/ bids/
 ```
 
@@ -281,7 +352,7 @@ The option `--plugin resources/plugins/bidsify_plugin.py` will load corresponden
 identify scans are applied).
 
 The option `--template bidsmap_template.yaml` tells which template will be used. The template 
-reads the common metatdata and tries to guess the modality. This is based on protocol names and can vary from institute to institute.
+reads the common metadata and tries to guess the modality. This is based on protocol names and can vary from institute to institute.
 The `bidsmap_template.yaml` works with example dataset, but for real data a different template may be needed.
 
 The parameters `renamed/` and `bids/` tells where prepared dataset is stored and where the bidsified dataset will be placed.
@@ -294,7 +365,7 @@ If placed in `bids/code/bidscoin/` directory, the `map` should not produce any w
 
 
 
-### Process step
+### <a name="run_proc"></a>Process step
 
 The process step is an optional step, which allow limited data manipulation before bidsification.
 Without plugins, it just verifies that all data is identifiable, and files with same bids name
@@ -305,7 +376,7 @@ With plugins, it can be used for data manipulation, and metadata completion.
 For example `resources/plugins/process_plugin.py` fills the `nandiness` column, and merges
 fMRI and diffusion images in single 4D image.
 
-```
+```python
 python3 bidscoin.py process --plugin resources/plugins/process_plugin.py renamed/ bids/
 ```
 
@@ -317,11 +388,24 @@ This step can be easily replaced by any custom script and/or pipeline. The only
 is some `bids` and `bidscoin` specific checks and recording identification.
 
 
-### Bidsification step
+### <a name="run_bids"></a>Bidsification step
 
 The final step is bidsification, it is run with `bidsify` command:
 
-```
+```python
 python3 bidscoin.py map --plugin resources/plugins/bidsify_plugin.py renamed/ bids/
 ```
 
+The `--plugin resources/plugins/bidsify_plugin.py` option loads an
+appropriate plugin.
+
+The `renamed/` parameter indicates the paths to prepared dataset.
+
+The bidsified dataset should be found in `bids/` folder and should be 
+fully bids complaint, including the participant and scans json sidecar
+files and json files with exported scans meta-data.
+
+`bidscoin` offer the possibility to rename subjects during bidsification.
+To do so, it will be enough to change value of `scan.subject` in
+`ParticipantEP` function, as demonstrated in 
+`plugin resources/plugins/bidsify_plugin.py` file on lines 85--89.
diff --git a/example1/resources/plugins/bidsify_plugin.py b/example1/resources/plugins/bidsify_plugin.py
index 916ec57db0ae7c4290c9a11568e95877b7b5623f..06255b2f9dede26f3dd817e3974cde1037768e86 100644
--- a/example1/resources/plugins/bidsify_plugin.py
+++ b/example1/resources/plugins/bidsify_plugin.py
@@ -80,12 +80,14 @@ def SubjectEP(scan):
 
     # This will demonstrate the subject renaming
     # namely increasing the id by 1
+    """
     sub_id = int(scan.subject[4:])
     scan.subject = "sub-{:03d}".format(sub_id + 1)
     # changing also in participant.tsv file
     if scan.sub_values["paired"]:
         pair_id = int(scan.sub_values["paired"][4:])
         scan.sub_values["paired"] = "sub-{:03d}".format(pair_id + 1)
+    """
 
     #################################
     # Subject metadata manipulation #