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The Promises and Perils of Neural Connectomics


Image Attribution: Google DeepMind


The Promises and Perils of Neural Connectomics


Author: Mashiyat Ahmed

Editor: Raayan Dhar


INTRODUCTION

To say that the human brain is an incredibly complex system is an understatement. The capacity of the brain, which allows our species to be highly sophisticated in speech, behavior, and thought, has long stunned scientists regarding its structural and functional makeup. Historically, neuroscience has focused on studying the individual components of the nervous system—cells, lobes, tissues, brain chemistry, and anatomical structures—but only recently have scientists endeavored to produce a body of knowledge denoting the one feature of the brain that may just explain its unique capacities: neural connectivity (Betzel, 2022). Simply put neurons in the brain talk to other neurons via electrochemical signaling, creating lines of communication that eventually intersect with other “conversations”, or communication pathways, to build the elaborate structure of connections that facilitate every unconscious and conscious demand of the human experience.

Neural connectomics relies on the fundamental theory that brain function—both healthy and pathological—depends on the nature of brain connectivity (e.g., connective trajectories and number of connections).In 2009, the National Institute of Health (NIH) ambitiously launched the Human Connectome Project (HCP), which is a globally collaborative research effort to produce an entire “map” of neural connections of a healthy human brain in the hopes of gaining new insight into the structure and function of mammalian brains (National Institute of Mental Health, 2023). Since 2009, research labs around the world have used high-resolution, non-invasive neuroimaging, machine learning, and statistical methods to develop precise connective maps of various locations of the brain where neurons are densely packed; these areas include specific cortex regions, the cerebellum, and the retina (Connectome Coordination Facility, 2023). The HCP is using a connectomics approach (building neural connective maps using technology) in assessing the structural and functional differences of brains in healthy, diseased, and life-span individuals, which includes infants, adolescents, and aging populations (Connectome Coordination Facility, 2023). Scientists hope that by acquiring extremely detailed connective maps there will be a greater understanding of neuroscience and that aspects of physical and mental health, as well as health care, will also improve. The remainder of this article will dive deeper into the technical approaches involved in connectomics and the potential applications of it in areas directly relevant to human health. Lastly, the ethical and philosophical consequences of advances in connectomics will be briefly explored as the world continues to evolve, both scientifically and culturally.



Image attribution: The Human Connectome Project


RESEARCH TECHNIQUES AND TECHNOLOGIES

Connectomics, first and foremost, is a technological and computational feat. To build maps of brain connectivity, both functional and structural imaging insights are required: functional data is obtained from functional magnetic resonance imaging (fMRI), which renders an image of blood flow activity in the white matter and deeper brain regions, indicating which areas are active. Subsequently, to refine the data from fMRI and obtain structural data, diffusion tensor imaging (DTI) and tractography techniques are used to construct higher-resolution images that precisely show the mapping of neural tracts through the brain (Sughrue, 2022). DTI is an MRI-based imaging technique that is able to give precise readings on microstructural characteristics of nervous tissue via tracking the diffusion of water molecules in the myelinated (fat) insulation of axons. Lastly, tractography is a powerful 3D modeling tool that visually represents functional and structural data obtained from previous imaging data. The result of these technologies combined is a colorful and strikingly clear image of nerve tracts and their connections with each other as they navigate different brain areas (Doyen, 2022). The most important part of the process is the interpretation and analysis of mapping results in relation to previous neuroscientific knowledge. But sometimes, analysis can be tedious and time-consuming. Advances in machine learning (e.g., algorithms) and Artificial Intelligence (AI) have made it easier for researchers to understand their results with more confidence and focus more on sophisticated interpretations not done by computers (Doyen, 2022).


REAL-WORLD APPLICATIONS

A common critique of connectomics is that research in this area often lacks positive tangible consequences for the health of patients. The imaging, measuring, and building of connective maps with the precision of the HCP require time and funding, and it is likely to take a substantial amount of time before any meaningful benefits are seen. However, it is overwhelmingly obvious that brain connectivity plays a major role in certain neurological diseases and psychological disorders, which continue to impact millions around the world. For example, the deployment of mass brain mapping can dramatically influence the diagnostic reality of psychological disorders, of which physicians and psychologists often lack a physical basis for diagnosis (Kaiser, 2013). Disorders like depression present as abnormalities in higher brain states (e.g., thinking, behavior, or speech); as such, the specific biomarkers (e.g., lesions, abnormal connectivity, neurotransmitter problems) causing mental disorders are not strongly acknowledged in diagnosing individuals with conditions that require medications or other therapeutic agents (Kaiser, 2013). The availability of patient-specific brain maps, along with other diagnostic procedures, can influence the diagnostic decision-making of professionals, allowing them to make better decisions about patient health and treatment plans (Kaiser, 2013). According to Omniscient Neurotechnology, “machine learning capabilities offer new opportunities to diagnose mental illness based on patterns of brain network function and connectivity” (Sughrue, 2022).

On top of this, neurosurgeons can benefit from connectomic data from their patients to be able to better identify and surgically target anatomical brain regions; neurosurgeons can, with more certainty, predict what each incision in the brain will mean for the patient given the detailed information available in the patient’s brain map (Sughrue, 2022). For neurologists and psychiatrists, brain mapping can provide novel insights into which functional areas are experiencing deficits, therefore, allowing them to supply patient-specific rehabilitation (Sughrue, 2022). Lastly, along with advancing health outcomes through increasing diagnostic certainty, the HCP can affirm pre-established understandings of how things work in the brain. For example, depression, classically, is understood to be a result of neurotransmitter abnormalities, but research also suggests that structural size and connectivity can also play a role in depression (Kaiser, 2013). The HCP confirms that in patients with major depressive disorders (MDD), there are fewer connections between the brain’s attentional and emotional centers, possibly explaining depression symptoms using a connectomics point of view (Kaiser, 2013). However, the exact scope of brain mapping in different areas of society remains to be seen.


CONCLUSION: ETHICS AND PHILOSOPHY OF IT ALL

Connectomics is a fascinating and ambitious area of neuroscience that shows great potential in revolutionizing our conceptualization and understanding of the human brain. But there remain some important ethical and philosophical considerations in connectomics that scientists and philosophers alike don’t have the answer to. For example, can brain mapping allow neurostimulation technologies to precisely target brain areas that are associated with mental performance, thus, potentially making cognitive enhancement even easier? Can connectomics become so incredibly precise that neuroscientists can now discern differences between brains differentiated by ethnicity, race, or gender, and if so, what ethical guidelines are needed to make sure that this information does not become abused or exploited? As to the existential questions involved, will our understanding of what makes us humans change due to connectomics, and what will be the philosophical consequences of redefining what it means to be ourselves? Given the power and potential of brain mapping, these questions, and more, are still relatively new in the broader connectomics discussion, but they are absolutely essential to answer if neuroscience is to continue responsibly.


References (APA Format)

Connectome Coordination Facility. (2017, March 1st). HCP Young Adult. https://www.humanconnectome.org/study/hcp-young-adult

Doyen, S. (2022) What is Tractography? Omniscient Neurotechnology. https://www.o8t.com/blog/tractography

Kaiser, M. (2013). The potential of the human connectome as a biomarker for brain disease. Frontiers in Human Neuroscience. 7(10), Article 484. https://doi.org/10.3389/fnhum.2013.00484

Sughrue, M. (2022). What is Connectomics? Omniscient Neurotechnology. https://www.o8t.com/blog/connectomics



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