Systems Neuroengineering: Understanding and Interacting with the Brain
Open accessAbstract
In this paper, we review the current state-of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering: neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity (via a neuroimaging modality) through a neural interface (invasive or noninvasive) and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering-to develop neurotechniques for enhancing the understanding of whole-brain function and dysfunction, and the management of neurological and mental disorders.
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ESI separates sensor-level data to expose the dynamics of regional activity or inter-regional connectivity, providing insights into healthy and diseased brain function.
“ESI also disentangles the sensor-level signals to reveal electrophysiological dynamics in regional activity or inter-regional connectivity, yielding new insights to brain functions in health (193) and disease (194–196).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [194]
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- Authors
- Edelman, B. J., Johnson, N., Sohrabpour, A., Tong, S., Thakor, N., & He, B.
- Affiliations
- University of Minnesota (US)
- Shanghai Jiao Tong University (CN)
- Johns Hopkins University (US)
- Corresponding author
- He, Bin
- Venue
- Engineering
- Publisher
- Elsevier BV
- Published
- 2015-09
- Volume
- 1
- Issue
- 3
- Pages
- 292-308
- ISSN
- 2095-8099 (ISSN-L)
- PMC
- PMC8323844
- OpenAlex
- W2155061149
- Cited by
- 45
- References
- 167
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 4 · 2023: 4 · 2022: 7 · 2021: 4 · 2020: 4 · 2019: 1 · 2018: 3 · 2017: 3 · 2016: 6
- FWCI
- 1.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Engineering (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- US National Institutes of Health (NIH) (EB006433, EY023101, EB008389, HL117664)
- US National Science Foundation (NSF)
- CBET (1450956, 1264782)
- DGE (1069104)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Keywords
- neuroimaging, neural interfaces, neuromodulation, brain networks, neural decoding, neurological disorders, mental illness, brain dysfunction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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