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UF²C - User Friendly Functional Connectivity


UF²C Introduction

UF²C is an open source software developed at the Neuroimaging Laboratory at Unicamp that aims to simplify and organize functional studies in neuroimaging through clean and validated methodologies.

UF²C has a full processing pipeline: The user only needs to select the raw functional and structural NIfTI files from the subjects. The graphical user interface makes the processing and analysis options accessible for neuroscientists, with reasonable choices of default settings. UF²C allows the user to study functional connectivity both through a quantitative view that provides detailed values of average connectivity and through a spatial view that provides statistical maps that can be directly used for further analyses. All results are carefully organized in distinct folder for each subject, and a common folder is generated with a log file reporting the quantitative results of all the analyzed subjects.

Several UF²C modalities and tools runs combined with Statistical Parametric Mapping functions.

UF²C is open source software, distributed under a BSD-style License


UF²C Team
Coordinator and developer
         Brunno M. de Campos, Ph.D.
Collaborator Developer
         Raphael Fernandes Casseb, Ph.D.
Theoretical Collaborators
         Fernando Cendes, MD, Ph.D.; Marina Weiler, PhD; Elise Facer-Childs, Ph.D.

UF²C Team

UF²C Requirement

  • Windows, Linux or Mac OS X operating system Statistical Parametric Mapping, version 8 or 12.

  • MATLAB version R2010a or later, required by SPM.

  • MATLAB Statistics toolbox

  • MATLAB Signal Processing toolbox

  • MATLAB Image Processing toolbox


It is a great effort to make UF²C compatible with all possible combinations of operational systems, Matlab and SPM versions.
Some problems can occur in Matlab older than 2010 versions, for example. Please contact me if you find any compatibility problems.
Thank you!

UF²C Requirement

UF²C has currently the following modalities:

   Modalities for Functional Connectivity:

  • Seed based functional connectivity (Statistical maps and quantitative outputs)</li>

  • Functional Interactivity - Automated multi-seed positioning (Statistical maps outputs)</li>

  • ROIs Cross-Correlation - Connectivity between coordinates or ROIs (corr-matrix, graphos and quantitative outputs)</li>

  • Cross-Correlation Second level - Comparison between groups (corr-matrix and graphos outputs)</li>

  • Sliding window connectivity - (Statistical maps, graphics and quantitative outputs)</li>

   Modalities for Functional MRI analysis:

  • fMRI Preprocessing

  • First Level Blok Design Analysis (code by Raphael Fernandes Casseb)

UF²C has currently the following tools:

  • Movement Viewer (graphical visualization)

  • Movement Analysis (quantifies sample head motion)

  • Image Editor (remove volumes, temporal parts and etc...)

  • Filename Changer (in mass file name changer)

  • Tissue Segmentation (SPM tool)

  • Volumetry - calculates the volume (mm³, mL and L) of image (ROI) added or the intracranial volume

  • Interpolation tool - convert image bounding box and voxel sizes to SPM8 default

  • R-score to z-score tranformation (Fisher's) - works on .mat files (vector, matrices..) and NIfTI files


UF²C Interface and output examples:

UF²C Main Interface
3D Brain Representation of Functional connectivity alterations
2D Brain Representation of Functional connectivity alterations
Connectivity Matrix, r-score color encoded
Circular Connectome with color encoded networks. The lines shows altered connectios
Circular Connectome with color encoding the r-score statistical significancy
UF²C Seed Based Results Example Map (DMN). Renderized with MRicroGL
UF²C Seed Based Results Example Map (DMN). Renderized with MRicroGL
UF²C Seed Based Results Example Map (DMN). Renderized with MRicroGL
UF²C Users

Who is using UF²C

  • de Campos, B. M., Coan, A. C., Lin Yasuda, C., Casseb, R. F. and Cendes, F. (2016), Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy. Hum. Brain Mapp.. doi: 10.1002/hbm.23231


  • Almeida, S. R. M., Vicentini, J., Bonilha, L., De Campos, B. M., Casseb, R. F. and Min, L. L. (2016), Brain Connectivity and Functional Recovery in Patients With Ischemic Stroke. Journal of Neuroimaging. doi: 10.1111/jon.12362


  • Vicentini, J.E., Weiler, M., Almeida, S.R.M. et al. Depression and anxiety symptoms are associated to disruption of default mode network in subacute ischemic stroke. Brain Imaging and Behavior (2016). doi:10.1007/s11682-016-9605-7


  • Weiler M, de Campos BM, Teixeira CV, Casseb RF, Carletti-Cassani AF, Vicentini JE, Magalhaes TN, Talib LL, Forlenza OV, Balthazar ML. Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels. J Psychiatry Neurosci. 2017 Apr 4;42(3):160190. doi: 10.1503/jpn.160190


  • TNC Magalhães, M Weiler, CVL Teixeira, T Hayata, AS Moraes, VO Boldrini, LM Dos Santos, BM de Campos, TJR de Rezende, HPG Joaquim, LL Talib, OV Forlenza, F Cendes, Marcio LF Balthazar. Systemic Inflammation and Multimodal Biomarkers in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease. Molecular Neurobiology


  • Silva D, S, Avelar W, M, de Campos B, M, Lino A, P, B, L, Balthazar M, L, F, Figueiredo M, J, O, Cendes F, Coan A, C, Default Mode Network Disruption in Stroke-Free Patients with Atrial Fibrillation. Cerebrovasc Dis 2018;45:78-84


  • Pereira Alessandra M., Campos Brunno M., Coan Ana C., Pegoraro Luiz F., de Rezende Thiago J. R., Obeso Ignacio, Dalgalarrondo Paulo, da Costa Jaderson C., Dreher Jean-Claude, Cendes Fernando. Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism. Frontiers in Neurology, 9, 2018, 539 DOI=10.3389/fneur.2018.00539


  • Weiler M, Casseb RF, de Campos BM, Ligo Teixeira CV, Carletti-Cassani AFMK, Vicentini JE, Magalhães TNC,de Almeira DQ, Talib LL, Forlenza OV, Balthazar MLF, Castellano G.. Cognitive Reserve Relates to Functional Network Efficiency in Alzheimer’s Disease. Frontiers in Aging Neuroscience,2018, 10, 25


  • Elise R Facer-Childs, Brunno M Campos, Benita Middleton, Debra J Skene, Andrew P Bagshaw; Circadian phenotype impacts the brain’s resting-state functional connectivity, attentional performance, and sleepiness, Sleep, zsz033,


  • Sewaybricker LE, Schur EA, Melhorn SJ, et al. Initial evidence for hypothalamic gliosis in children with obesity by quantitative T2 MRI and implications for blood oxygen‐level dependent response to glucose ingestion. Pediatric Obesity. 2019;14:e12486.


  • Raphael F. Casseb, Brunno M. de Campos, Alberto R.M. Martinez, Gabriela Castellano, Marcondes C. França Junior, Selective sensory deafferentation induces structural and functional brain plasticity, NeuroImage: Clinical, 2018, 101633,


  • Garcia, DDS, Polydoro, MS, Alvim, MKM, et al. Anxiety and depression symptoms disrupt resting state connectivity in patients with genetic generalized epilepsies. Epilepsia. 2019; 00: 1– 10.


  • Lopes, Tátila Martins ; Campos, Brunno Machado ; Zanão, Tamires Araújo et al.  Hippocampal atrophy disrupts the language network but not hemispheric language lateralization. EPILEPSIA, v. x, p. epi.14694, 2019.

How to Cite?

If UF²C was useful for your work and you want to cite, please use the following paper:

  • Campos BM, Casseb RF, Cendes F. UF2C — User-Friendly Functional Connectivity: A neuroimaging toolbox for fMRI processing and analyses. SoftwareX, Volume 11, 2020, 100434, ISSN 2352-7110,

For example:
"...UF²C toolbox (User-Friendly Functional Connectivity) ...(Campos et al., 2020)..."
"...UF²C toolbox ( et al., 2020)..."

Thank you for using and citing the UF²C!!

Citing UF²C


     - The updates are cumulative.
     - Please, report bugs!

     - UF²C is always updating due the continuous feedbacks, corrections, ideas or necessities. Thank you!

Contact the Author

Obrigado! Mensagem enviada.

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