Machine and Deep-learning for Computational Neuroscience

  • 2,977

    Total downloads

  • 24k

    Total views and downloads

Submit your idea

You will be redirected to our submission process.

Submit your manuscript summarySubmit your manuscript

About this Research Topic

Submission closed

Background

As machine learning (ML) and Deep learning (DL) progresses from purely theoretical models to real implementations, the issue of ML safety and fairness becomes increasingly important. In neuroscience, machine learning has demonstrated increasing proficiency, even outperforming humans in some tasks. With the abundance of neuroscience data becoming available in the big data age, ML will be able to attain even greater efficacy in various activities by using it.

However, in addition to the capabilities, the inherent safety and fairness challenges linked with ML have far-reaching consequences. Because ML models are algorithms trained on existing data, they frequently carry the biases of past experience. Even the most well-intentioned ML model can spread the biases existing in the training data in the absence of monitoring and surveillance tools. Furthermore, weaknesses in ML models may be easily exploited by attackers, either intentionally or unintentionally, to generate undesirable outcomes or worsen power inequalities.

Neuroscience is the study of how the brain performs diverse perceptual, cognitive, and motor processes. Big data can now be processed by intelligent computers using ML-based artificial intelligence approaches, opening up new possibilities for neuroscience such as how millions of neurons and nodes cooperate to manage vast amounts of information and how the brain develops and governs actions. Because of the safety and fairness issues with ML models, researchers frequently underestimate the concerns of data-fying neuroscience. The attention has been called to a far more significant and fundamental problem: the safety and fairness issue in ML models exacerbates imbalances and risk, with particularly severe effects for neuroscience.

This Research Topic welcomes Original Research and Review articles that discuss the fairness and safety implications of using ML in real-world neuroscience systems, propose methods to detect, prevent, and/or alleviate undesired fairness and safety issues that ML-based systems may exhibit, analyze the vulnerability of neuroscience ML systems to adversarial attacks and possible defense mechanisms, and, more broadly, any paper that stimulates progress on the topic.

Potential topics include but are not limited to the following:

-Application of of ML/DL in neuroscienc
-Measurement of safety in neuroscience
-Understanding disparities in the predicted outcome
-Construction of unbiased ML models for neuroscience
-Recourse and contestability of biased ML results
-Safe reinforcement learning in neuroscience
-Ethical and legal consequences of using ML in real-world systems

Keywords: machine learning (ML), Deep learning (DL), Neuroscience ML models

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Topic editors

Frequently asked questions

  • Frontiers' Research Topics are collaborative hubs built around an emerging theme.Defined, managed, and led by renowned researchers, they bring communities together around a shared area of interest to stimulate collaboration and innovation.

    Unlike section journals, which serve established specialty communities, Research Topics are pioneer hubs, responding to the evolving scientific landscape and catering to new communities.

  • The goal of Frontiers' publishing program is to empower research communities to actively steer the course of scientific publishing. Our program was implemented as a three-part unit with fixed field journals, flexible specialty sections, and dynamically emerging Research Topics, connecting communities of different sizes and maturity.

    Research Topics originate from the scientific community. Many of our Research Topics are suggested by existing editorial board members who have identified critical challenges or areas of interest in their field.

  • As an editor, Research Topics will help you build your journal, as well as your community, around emerging, cutting-edge research. As research trailblazers, Research Topics attract high-quality submissions from leading experts all over the world.

    A thriving Research Topic can potentially evolve into a new specialty section if there is sustained interest and a growing community around it.

  • Each Research Topic must be approved by the specialty chief editor, and it falls under the editorial oversight of our editorial boards, supported by our in-house research integrity team. The same standards and rigorous peer review processes apply to articles published as part of a Research Topic as for any other article we publish.

    In 2023, 80% of the Research Topics we published were edited or co-edited by our editorial board members, who are already familiar with their journal's scope, ethos, and publishing model. All other topics are guest edited by leaders in their field, each vetted and formally approved by the specialty chief editor.

  • Publishing your article within a Research Topic with other related articles increases its discoverability and visibility, which can lead to more views, downloads, and citations. Research Topics grow dynamically as more published articles are added, causing frequent revisiting, and further visibility.

    As Research Topics are multidisciplinary, they are cross-listed in several fields and section journals – increasing your reach even more and giving you the chance to expand your network and collaborate with researchers in different fields, all focusing on expanding knowledge around the same important topic.

    Our larger Research Topics are also converted into ebooks and receive social media promotion from our digital marketing team.

     

  • Frontiers offers multiple article types, but it will depend on the field and section journals in which the Research Topic will be featured. The available article types for a Research Topic will appear in the drop-down menu during the submission process.

    Check available article types here 

  • Yes, we would love to hear your ideas for a topic. Most of our Research Topics are community-led and suggested by researchers in the field. Our in-house editorial team will contact you to talk about your idea and whether you’d like to edit the topic. If you’re an early-stage researcher, we will offer you the opportunity to coordinate your topic, with the support of a senior researcher as the topic editor. 

    Suggest your topic here 

  • A team of guest editors (called topic editors) lead their Research Topic. This editorial team oversees the entire process, from the initial topic proposal to calls for participation, the peer review, and final publications.

    The team may also include topic coordinators, who help the topic editors send calls for participation, liaise with topic editors on abstracts, and support contributing authors. In some cases, they can also be assigned as reviewers.

  • As a topic editor (TE), you will take the lead on all editorial decisions for the Research Topic, starting with defining its scope. This allows you to curate research around a topic that interests you, bring together different perspectives from leading researchers across different fields and shape the future of your field. 

     

    You will choose your team of co-editors, curate a list of potential authors, send calls for participation and oversee the peer review process, accepting or recommending rejection for each manuscript submitted.

  • As a topic editor, you're supported at every stage by our in-house team. You will be assigned a single point of contact to help you on both editorial and technical matters. Your topic is managed through our user-friendly online platform, and the peer review process is supported by our industry-first AI review assistant (AIRA).

  • If you’re an early-stage researcher, we will offer you the opportunity to coordinate your topic, with the support of a senior researcher as the topic editor. This provides you with valuable editorial experience, improving your ability to critically evaluate research articles and enhancing your understanding of the quality standards and requirements for scientific publishing, as well as the opportunity to discover new research in your field, and expand your professional network.

  • Yes, certificates can be issued on request. We are happy to provide a certificate for your contribution to editing a successful Research Topic.

  • Research Topics thrive on collaboration and their multi-disciplinary approach around emerging, cutting-edge themes, attract leading researchers from all over the world.

  • As a topic editor, you can set the timeline for your Research Topic, and we will work with you at your pace. Typically, Research Topics are online and open for submissions within a few weeks and remain open for participation for 6 – 12 months. Individual articles within a Research Topic are published as soon as they are ready.

    Find out more about our Research Topics

  • Our fee support program ensures that all articles that pass peer review, including those published in Research Topics, can benefit from open access – regardless of the author's field or funding situation.

    Authors and institutions with insufficient funding can apply for a discount on their publishing fees. A fee support application form is available on our website.

  • In line with our mission to promote healthy lives on a healthy planet, we do not provide printed materials. All our articles and ebooks are available under a CC-BY license, so you can share and print copies.

     

Impact

  • 24kTopic views
  • 19kArticle views
  • 2,977Article downloads
View impact