Authored by Carissa Nair
Art by Audrey Trivedi
The human brain is an enigma. While the neural processes that dictate our daily lives derive from this all-important organ, it is still unchartered territory. In short, there is much we don’t know about neurological function and disorders. In the last decade, however, there have been several developments in the scientific field of connectomics in an attempt to address the uncertainty surrounding neural structure and function [1]. Connectomics involves the process of neural mapping, by which networks, cell types, and regions within the brain are charted and systematized to understand their implications for the field of diagnostic healthcare [2].
In the past few years, newly formed connections between pathology and neural structure have influenced significant advances in neuroscience. Zhu et al. explored how neural mapping algorithms that integrated functional and structural knowledge could be used to uncover diagnosis possibilities for epilepsy in 2021. While machine-learning had long been considered an effective tool of diagnosis for neurological disorders, there were some limitations to existing neural network models which these researchers addressed [3]. On the subject of treatments and disease—in 2022, Ye et al. observed the pathways of hippocampal neural circuits in mice with a virus tracking mechanism. Researchers were able to detect and map differences in circuits between control mice and mice that overexpressed the amyloid protein (a characteristic linked to Alzheimer’s disease) [4]. Additionally, there were some attempts at refining this technology, stemming from the need to conclusively address the knowledge gap in neuroscience. Siddiqi et al. detailed the transition from correlational to causal neural mapping in a 2022 article, explaining how these techniques, when combined with imaging methods, could yield valuable information for disease treatments. These combinatorial methods could include altering disease symptoms through neural stimulation, comparative data processing from different brain regions, and understanding precise details of circuitry. These techniques have already yielded promising results for neuropsychiatric disorders and Parkinson’s disease [5].
The implications of neural mapping do not, however, solely extend to pathophysiological progress. Some experiments with this technique are attempts to understand neural structure through improvement of imaging techniques, such as in the case of Sun et al. in 2022. These researchers attempted to investigate how a combination of PET and diffusion MRI imaging could improve images of gray/white matter in the brain through denoising [6]. Another example of this trend in structural discovery is the BRAIN Initiative Cell Census Network, where scientists mapped the mammalian primary motor cortex with combinatorial imaging and genomic analysis methods [7]. This scientific development is a sign of immense progress in understanding the previously-unknown complete structure of many functional regions of the brain—one of which was the primary motor cortex.
Neural mapping is a technique that can provide insight into a variety of medical disciplines. Mapping is the key to the future of neuroscience, especially considering the sheer amount of international initiatives created to address this novel technology. Some approaches to neural mapping deal with structure, while others determine influences on pathology and disease progression. Both are immeasurably important for healthcare, medicine, and scientific exploration.
Works Cited
Caruso, C. (2023, January 19). A New Field of Neuroscience Aims to Map Connections in the Brain. https://hms.harvard.edu/news/new-field-neuroscience-aims-map-connections-brain
Abbott, Alison. “How the World’s Biggest Brain Maps Could Transform Neuroscience.” Nature News, Nature Publishing Group, 6 Oct. 2021, www.nature.com/articles/d41586-021-02661-w
Zhu, Q., Yang, J., Xu, B., Hou, Z., Sun, L., & Zhang, D. (2021). Multimodal Brain Network Jointly Construction and Fusion for Diagnosis of Epilepsy. Frontiers in neuroscience, 15, 734711. https://doi.org/10.3389/fnins.2021.734711
Ye, Q., Gast, G., Su, X., Saito, T., Saido, T. C., Holmes, T. C., & Xu, X. (2022). Hippocampal neural circuit connectivity alterations in an Alzheimer's disease mouse model revealed by monosynaptic rabies virus tracing. Neurobiology of disease, 172, 105820. https://doi.org/10.1016/j.nbd.2022.105820
Siddiqi, S. H., Kording, K. P., Parvizi, J., & Fox, M. D. (2022). Causal mapping of human brain function. Nature reviews. Neuroscience, 23(6), 361–375. https://doi.org/10.1038/s41583-022-00583-8
Sun, Z., Meikle, S., & Calamante, F. (2022). CONN-NLM: A Novel CONNectome-Based Non-local Means Filter for PET-MRI Denoising. Frontiers in neuroscience, 16, 824431. https://doi.org/10.3389/fnins.2022.824431
BRAIN Initiative Cell Census Network (BICCN) (2021). A multimodal cell census and atlas of the mammalian primary motor cortex. Nature, 598(7879), 86–102. https://doi.org/10.1038/s41586-021-03950-0.
Comments