Improving our understanding of brain function requires interdisciplinary collaborations between theoretical, computational, and experimental disciplines and approaches. The Section “Computational Neuroscience and Neuroinformatics” of Brain Sciences (ISSN: 2076-3425) fosters multidisciplinary interactions between theoretical, computational, and experimental work in the field of neuroscience.

We invite original contributions on a wide range of topics that promote theoretical modeling focused on understanding neural function at the molecular, cellular, and circuit levels via computational and model-based approaches that are experimentally testable. While the Section primarily focuses on theoretical and computational research, it welcomes experimental studies that validate and test theoretical conclusions. Primarily theoretical manuscripts should be highly relevant to the neural mechanisms of the neural function, while primarily experimental manuscripts should have implications for the computational analysis of nervous system function.

Manuscripts investigating physiological mechanisms underlying neuropathologies by combining theoretical and experimental approaches are highly encouraged. Similarly, manuscripts describing novel technological advances in data analysis techniques to further insights into the function of the nervous system are also highly encouraged. Modeling approaches at all levels, from biophysically motivated realistic simulations of neurons and synapses to high-level behavioral models of inference and decision-making, are also welcome.

As all of the articles published in our journal are in an open access format, you have free and unlimited access to the full text. We welcome you to read our most highly cited papers published in 2021 and 2022 listed below:

1. “Pain-Related Brain Connectivity Changes in Migraine: A Narrative Review and Proof of Concept about Possible Novel Treatments Interference”
by Marina de Tommaso, Eleonora Vecchio, Silvia Giovanna Quitadamo, Gianluca Coppola, Antonio Di Renzo, Vincenzo Parisi, Marcello Silvestro, Antonio Russo and Gioacchino Tedeschi
Brain Sci. 2021, 11(2), 234; https://doi.org/10.3390/brainsci11020234
Available online: https://www.mdpi.com/2076-3425/11/2/234

2. “Brain Image Segmentation in Recent Years: A Narrative Review”
by Ali Fawzi, Anusha Achuthan and Bahari Belaton
Brain Sci. 2021, 11(8), 1055; https://doi.org/10.3390/brainsci11081055
Available online: https://www.mdpi.com/2076-3425/11/8/1055

3. “The Directionality of Fronto-Posterior Brain Connectivity Is Associated with the Degree of Individual Autistic Traits”
by Luca Tarasi, Elisa Magosso, Giulia Ricci, Mauro Ursino and Vincenzo Romei
Brain Sci. 2021, 11(11), 1443; https://doi.org/10.3390/brainsci11111443
Available online: https://www.mdpi.com/2076-3425/11/11/1443

4. “Thalamocortical Connectivity in Experimentally-Induced Migraine Attacks: A Pilot Study”
by Daniele Martinelli, Gloria Castellazzi, Roberto De Icco, Ana Bacila, Marta Allena, Arianna Faggioli, Grazia Sances, Anna Pichiecchio, David Borsook, Claudia A. M. Gandini Wheeler-Kingshott et al.
Brain Sci. 2021, 11(2), 165; https://doi.org/10.3390/brainsci11020165
Available online: https://www.mdpi.com/2076-3425/11/2/165

5. “Detection of Resting-State Functional Connectivity from High-Density Electroencephalography Data: Impact of Head Modeling Strategies”
by Gaia Amaranta Taberna, Jessica Samogin, Jessica Samogin and Dante Mantini
Brain Sci. 2021, 11(6), 741; https://doi.org/10.3390/brainsci11060741
Available online: https://www.mdpi.com/2076-3425/11/6/741

6. “Changes in Default Mode Network Connectivity in Resting-State fMRI in People with Mild Dementia Receiving Cognitive Stimulation Therapy”
by Tianyin Liu, Aimee Spector, Daniel C. Mograbi, Gary Cheung and Gloria H. Y. Wong
Brain Sci. 2021, 11(9), 1137; https://doi.org/10.3390/brainsci11091137
Available online: https://www.mdpi.com/2076-3425/11/9/1137

7. “The Relationship between Oscillations in Brain Regions and Functional Connectivity: A Critical Analysis with the Aid of Neural Mass Models”
by Giulia Ricci, Elisa Magosso and Mauro Ursino
Brain Sci. 2021, 11(4), 487; https://doi.org/10.3390/brainsci11040487
Available online: https://www.mdpi.com/2076-3425/11/4/487

8. “Time-Frequency Characterization of Resting Brain in Bipolar Disorder during Euthymia—A Preliminary Study”
by Adrian Andrzej Chrobak, Bartosz Bohaterewicz, Anna Maria Sobczak, Magdalena Marszał-Wiśniewska, Anna Tereszko, Anna Krupa, Anna Ceglarek, Magdalena Fafrowicz, Amira Bryll, Tadeusz Marek et al.
Brain Sci. 2021, 11(5), 599; https://doi.org/10.3390/brainsci11050599
Available online: https://www.mdpi.com/2076-3425/11/5/599

9. “Assessing Multi-Site rs-fMRI-Based Connectomic Harmonization Using Information Theory”
by Facundo Roffet, Claudio Delrieux and Gustavo Patow
Brain Sci. 2022, 12(9), 1219; https://doi.org/10.3390/brainsci12091219
Available online: https://www.mdpi.com/2076-3425/12/9/1219

10. “The Asymmetric Laplace Gaussian (ALG) Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task”
by Mohsen Soltanifar, Michael Escobar, Annie Dupuis, Andre Chevrier and Russell Schachar
Brain Sci. 2022, 12(6), 730; https://doi.org/10.3390/brainsci12060730
Available online: https://www.mdpi.com/2076-3425/12/6/730

11. “Structural MRI-Based Schizophrenia Classification Using Autoencoders and 3D Convolutional Neural Networks in Combination with Various Pre-Processing Techniques”
by Roman Vyškovský, Daniel Schwarz, Vendula Churová and Tomáš Kašpárek
Brain Sci. 2022, 12(5), 615; https://doi.org/10.3390/brainsci12050615
Available online: https://www.mdpi.com/2076-3425/12/5/615

12. “Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model”
by Bin Li, Yuki Todo and Zheng Tang
Brain Sci. 2022, 12(4), 470; https://doi.org/10.3390/brainsci12040470
Available online: https://www.mdpi.com/2076-3425/12/4/470

13. “Optimal Scaling Approaches for Perfusion MRI with Distorted Arterial Input Function (AIF) in Patients with Ischemic Stroke”
by Sukhdeep Singh Bal, Fan Pei Gloria Yang, Yueh-Feng Sung, Ke Chen, Jiu-Haw Yin and Giia-Sheun Peng
Brain Sci. 2022, 12(1), 77; https://doi.org/10.3390/brainsci12010077
Available online: https://www.mdpi.com/2076-3425/12/1/77

14. “Bayesian Optimization of Machine Learning Classification of Resting-State EEG Microstates in Schizophrenia: A Proof-of-Concept Preliminary Study Based on Secondary Analysis”
by Ahmadreza Keihani, Seyed Saman Sajadi, Mahsa Hasani and Fabio Ferrarelli
Brain Sci. 2022, 12(11), 1497; https://doi.org/10.3390/brainsci12111497
Available online: https://www.mdpi.com/2076-3425/12/11/1497

15. “Modeling Cognitive Load as a Self-Supervised Brain Rate with Electroencephalography and Deep Learning”
by Luca Longo
Brain Sci. 2022, 12(10), 1416; https://doi.org/10.3390/brainsci12101416  
Available online: https://www.mdpi.com/2076-3425/12/10/1416

16. “Inhibitory Control and Brain–Heart Interaction: An HRV-EEG Study”
Maria Daniela Cortese, Martina Vatrano, Paolo Tonin, Antonio Cerasa and Francesco Riganello
Brain Sci. 2022, 12(6), 740; https://doi.org/10.3390/brainsci12060740
Available online: https://www.mdpi.com/2076-3425/12/6/740