The brain is one of the biggest scientific puzzles that scientists have ever attempted to solve. The first ever recorded evidence of neuroscientific research was ca. 4000 B.C. when the Sumerians recorded the euphoric effects of the poppy plant (Chudler, n.d.). Humans have always been curious about how our brain functions, why some brains function differently, and how our brains function. This fascination with the brain has led to massive projects that have garnered immense financial support. As we learn how to manipulate the brain more and more, the stakes increase and so does the value of neuroscientific discovery. Here we will explore the top ten highest-budget neuroscience projects to date.
Here Are the Highest Budget Neuroscience Projects
1. BRAIN Initiative
Project Details
| Budget | $4.5 Billion |
| Duration | 12 Years |
| Start Date | 2013 |
| Funding Source | National Institute of Health (NIH) |
The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative was created with the goal of revolutionizing our understanding of the human brain (Brain Initiative, n.d.). In 2013, at a White House event, President Barack Obama announced The BRAIN Initiative. The initially proposed expenditures for the 2014 fiscal year were approximately $110 million from the Defense Advanced Research Projects Agency (DARPA), the National Institutes of Health (NIH), and the National Science Foundation (NSF). Since this project was a massive undertaking, the NIH established a high-level Advisory Committee to help shape this new initiative. In June 2014, this committee released a report called BRAIN 2025: A Scientific Vision that articulated the scientific goals, timeline, milestones, and cost estimates of The BRAIN Initiative (Brain Initiative, n.d.).
By developing technologies, The BRAIN Initiative researchers hope to produce a new view of the brain that shows how individual cells and complex neural circuits interact in both time and space (Brain Initiative, n.d.). This greater understanding of the brain will pave the way for research that works to treat, cure, and prevent brain disorders. The Brain Initiative has allocated funding for 7 specific priority research areas: Cell Type, Circuit Diagrams, Monitor Neural Activity, Interventional Tools, Theory & Data Analysis Tools, Human Neuroscience, and Integrated Approaches (Brain Initiative, n.d.). We’ll briefly review each of these research areas and the work The BRAIN Initiative has done to advance research in these areas.
The goal of the Cell Type priority area is the discover diversity. Essentially, The BRAIN Initiative hopes to identify and provide experimental access to the different brain cell types to determine their roles in health and disease. The project envisions an integrated, systematic census of neuronal and glial cell types, and new genetic and non-genetic tools to deliver genes, proteins, and chemicals to cells of interest in non-human animals and in humans (Brain Initiative, n.d.). The BRAIN Initiative Cell Census Network (BICCN) represents the research The BRAIN Initiative has done on cell types. The goal of the BICCN is to identify unique cell type markers for understanding and accessing neural circuits as well as unveiling the regulatory code that controls cell type formation, maintenance, and transition in health and disease (Brain Initiative, n.d.).
Within the Circuit Diagrams priority area, The BRAIN Initiative seeks to create maps at multiple scales. In other words, generate circuit diagrams that vary in resolution from synapses to the whole brain. The goal is to improve technologies for the anatomic reconstruction of neural circuits at all scales, from non-invasive whole human brain imaging to dense reconstruction of synaptic inputs and outputs at the subcellular level (Brain Initiative, n.d.).
The Monitor Neural Activity research area is focused on the brain in action. The goal is to produce a dynamic picture of the functioning brain by developing and applying improved methods for large-scale monitoring of neural activity. The BRAIN Initiative is challenging themselves to record dynamic neuronal activity from complete neural networks over a long period of time in all areas of the brain. The research into monitoring neural activity includes funding for new research, new technologies/approaches, and optimizing existing technologies for large-scale recording and modulation in the nervous system (Brain Initiative, n.d.).
The BRAIN Initiative’s priority area Interventional Tools is hoping to demonstrate causality in the brain. They want to link brain activity to behavior with precise interventional tools that change neural circuit dynamics. They hope to do this by developing a new generation of tools for optogenetics, chemogenetics, and biochemical and electromagnetic modulation that they want to use in animals and eventually in human patients (Brain Initiative, n.d.).
Within the Theory & Data Analysis Tools, the BRAIN Initiative wants to identify fundamental principles. By this, they mean that they want to produce conceptual foundations for understanding the biological basis of mental processes through the development of new theoretical and data analysis tools. To speed this analysis up, the BRAIN Initiative hopes here more than in any other research area to encourage collaborations between experimentalists and scientists from statistics, physics, mathematics, engineering, and computer science (Brain Initiative, n.d.).
In the Human Neuroscience priority area, the BRAIN Initiative wants to develop innovative technologies to understand the human brain and treat its disorders as well as to create and support integrated human brain research networks. This priority area requires closely integrated research teams that perform according to the highest ethical standards of clinical care and research on consenting human subjects (Brain Initiative, n.d.).
Lastly, the Integrated Approaches priority area is focused primarily on integrating the new technological and conceptual approaches produced in the other six research areas to discover how dynamic patterns of neural activity are transformed into cognition, emotion, perception, and action in health and disease (Brain Initiative, n.d.).
2. Human Brain Project
Project Details
| Budget | $1.6 Billion |
| Duration | 10 Years |
| Start Date | 2013 |
| Funding Source | European Union |
The Human Brain Project (HBP) started in 2013 with the bold goal of building a simulation of the human brain (Theil, 2015). The project has been split up into phases, with each phase supplied with separate funding. The first was called the “Ramp-Up Phase” (2013-2016). In this phase, the HBP agreed on an overall plan and road map for the project (Human Brain Project, n.d.). The second was called the first Operational Phase (2016-2018). This phase laid the rest of the foundations for the world’s first integrated ICT-based (Information and Communication Technology) infrastructure for academic and industrial brain research and development (Human Brain Project, n.d.). This phase included the public release of six prototype Platforms in March 2016. The third phase is called the second Operational Phase (2018-2020). This phase saw the individual infrastructure platforms extended and integrated into a single service called EBRAINS which makes the HBP services accessible to the neuroscience community. The current and last phase of the HBP (2020-2023) seeks to develop the services of EBRAINS. More specifically, in its final phase, the HBP is focused on three scientific areas: brain networks, consciousness, and artificial neural nets (Human Brain Project, n.d.).
The HBP uses several methods to study these three focus areas. They have a multiscale investigation of brain networks across different spatial and temporal scales. With this investigation, they hope to see the significance of specific brain networks in processes underlying consciousness and disorders of consciousness. The HBP also seeks to determine how artificial neural networks derived from the brain are developed (Human Brain Project, n.d.).
Their brain network research focuses primarily on the human multiscale brain connectome and its variability. The research utilizes HBP developments such as the Brain Atlases, multiscale subcellular and cellular data-driven models, and a large-scale network model. The HBP research on consciousness includes generating data-driven models from the networks that underly brain cognition and consciousness. These models carry out cognitive tasks like object recognition or decision-making while expressing realistic brain dynamics in different states (sleep, awake, anesthesia) (Human Brain Project, n.d.). Lastly, the HBP research on artificial neural nets includes creating adaptive networks for cognitive architectures. These networks emulate the architecture and operation of the brain and apply them to address cognitive problems in an embodied setting. This research results in the creation of concepts and algorithms for neuro-inspired technologies, both hardware (neuromorphic, neurorobotics), and network architectures (Human Brain Project, n.d.).
3. China Brain Project
Project Details
| Budget | Estimated $1 billion |
| Duration | 15 Years |
| Start Date | 2016 |
| Funding Source | Chinese Government |
In 2015, the Chinese government announced the China Brain Project after two years of discussion about which direction China’s scientific research should take. This project, entitled “Brain Science and Brain-Inspired Intelligence,” is formulated as a 15-year plan, which coincides with China’s 13th five-year plan for national social and economic development (Poo, 2016). The China Brain Project aims to study the pathogenic mechanisms and to develop effective diagnostic and therapeutic approaches for brain disorders that are developmental (e.g., autism), neuropsychiatric (e.g., depression and addiction), and neurodegenerative (e.g., Alzheimer’s disease and Parkinson’s disease) (Poo, 2016). Furthermore, the China Brain Project aims to better understand the mechanisms and principles of the brain at multiple levels. This broad goal is expected to promote deep and close collaboration between neuroscientists and AI researchers. The China Brain Project will focus its efforts on developing cognitive robotics as a platform for integrating brain-inspired computational models and devices. The goal is to build intelligent robots that are highly interactive with humans and properly reactive in uncertain environments, with the skills for solving various problems that can grow through interactive learning, and the ability to transfer and generalize knowledge acquired from different tasks—even to share learned knowledge with other robots (Poo, 2016).
Ultimately, the China Brain Project aspires to achieve a balance between basic and applied neuroscience, in which some research scientists can pursue their interest in exploring the secrets of the brain, while others may apply what we know already for preventing and curing brain disorders and for developing brain-inspired intelligence technology (Poo, 2016).
4. Allen Institute for Brain Science
Project Details
| Budget | ~$765 million |
| Duration | Ongoing |
| Start Date | 2003 |
| Funding Source | Paul G. Allen |
In 2003, investor and philanthropist Paul G. Allen committed $100 million in seed money dedicated to brain research and unveiled the Allen Institute for Brain Science in Seattle. The inaugural project, the Allen Mouse Brain Atlas, set out to combine neuroscience and genetics to create a map of the mammalian brain at the cellular level. Instead of researching genes one at a time, the Allen Mouse Brain Atlas project sought to give scientists a view of the portion of the genome that is active in the brain (Allen Institute, 2003). In 2006, the Allen Mouse Brain Atlas project was completed. The map of genome-wide gene expression over the entire brain of the adult laboratory mouse was released to the public on September 26, 2006 (Allen Institute, n.d.).
Following the success of the Allen Mouse Brain Atlas, researchers at the Allen Institute completed the Allen Spinal Cord Atlas in 2008. This was the world’s first genome-wide map of gene expression in the mouse spinal cord (Allen Institute, n.d.). In 2011, after four years of hard work, the Allen Human Brain Atlas was released. This project consisted of a precise map of the human brain, and the most comprehensive characterization of the human brain to that point (Allen Institute, n.d.). In 2012, Mr. Allen committed an additional $300 million to expand the Allen Institute for Brain Science. This time with the goal of building a new observatory to record the activity of thousands of nerve cells and to obtain a census of all cell types in the brain over the course of 10 years (Allen Institute, n.d.). This was just the beginning of a long chain of successes for the Allen Institute for Brain Science. Most recently, in April 2020, the Allen Institute announced a new phase of neuroscience research focused on building high-resolution maps of Alzheimer’s patients’ brains and identifying how their neurons and other brain cells differ from those of healthy people (Allen Institute, 2020).
5. Korea Brain Initiative (KBI)
Project Details
| Budget | $350 million |
| Duration | 10 Years |
| Start Date | 2018 |
| Funding Source | Daegu City Government |
The Korea Brain Initiative (KBI) was announced on May 30, 2016, with a plan featuring the development of novel neurotechnologies and the reinforcement of the neuro industry with a vision to advance brain science by establishing and facilitating local, national, and global collaborative networks. The project’s main goal is to produce a dynamic picture of healthy and diseased brains (Jeong et al., 2016). Specifically, they want to map a functional connectome with searchable, multidimensional, and information-integrated features. There are four core areas that make up the KBI: (1) constructing brain maps at multiple scales; (2) developing brain mapping neurotechnologies; (3) strengthening artificial intelligence; and (4) developing personalized medicine for neurological disorders (Jeong et al., 2016).
The KBI’s brain mapping plan has a two-track strategy. One track focuses on understanding the structure and mechanics of higher brain functions like decision-making, attention, and memory. The other track focuses on exploring the progression of neurological disorders, particularly those related to aging. The KBI expects to develop two types of specialized brain maps by 2023 (Jeong et al., 2016). The KBI hopes to develop brain mapping neurotechnologies to better understand the full complexity of the brain, particularly of circuit-function relationships. Part of their plans includes developing neuro-tools for multiscale brain mapping, circuit-mining, and high-resolution wide-field recording (Jeong et al., 2016). For the third core area, KBI intends its initiatives to contribute to AI development. “Neural circuit studies of higher brain functions such as sensory integration, perceptual decision-making, and natural intelligence are important for the advancement of AI, developing next-generation AI algorithms and models and neural devices” (Jeong et al., 2016). KBI’s work to develop personalized medicine includes developing precision medicine technology to prevent and diagnose neurological disorders and to develop customized disease-prevention and treatment strategies for brain disorders (Jeong et al., 2016).
6. Brain/MINDS
A common marmoset, which is the focus of Japan’s Brain/MINDS project
Project Details
| Budget | $310 million |
| Duration | 10 Years |
| Start Date | 2014 |
| Funding Source | Japan Agency for Medical Research and Development (AMED) |
In 2014, Japan started a 10-year brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) (Okano et al., 2015). The goal of the Brain/MINDS project is to map the marmoset brain to accelerate our understanding of human neurological disorders such as Alzheimer’s disease and schizophrenia (Cyranoski, 2014). There are several reasons to study marmosets. For example, since marmosets are a primate, the marmoset brain shares some aspects of the developmental process and anatomical structure of the human brain. Another reason to study marmosets is that they have similar social behaviors as humans, including strong relationships between parents and offspring (Okano et al., 2015). The objectives the Brain/MINDS project intends to focus on to complete this goal can be split up into three major areas: (1) structural and functional marmoset brain mapping; (2) development of brain mapping neurotechnologies; and (3) human brain mapping and clinical research (Okano et al., 2015). We will briefly go over the Brain/MINDS project’s plans for each area.
Structural brain mapping will involve mapping the marmoset brain at three different resolutions: macroscopic, mesoscopic, and microscopic. The functional brain mapping will utilize functional magnetic resonance imaging (fMRI-based) mapping, positron emission tomography (PET) imaging, electrophysiological recording, and calcium imaging (Okano et al., 2015). This functional mapping will also be performed on diseased marmoset brains (i.e., Alzheimer’s disease models, Parkinson’s disease models, etc.). The research group focused on developing neurotechnologies is further split into three subgroups: (1) developing techniques for high resolution and fast imaging of brain structures and functions; (2) developing techniques to control neural activity; and (3) developing neuroinformatic technology to handle lots of data (Okano et al., 2015). The human brain mapping research area will map the brains of healthy subjects and neuropsychiatric patients. This data will generate a database of patient MRI data and will provide feedback to the marmoset researchers (Okano et al., 2015).
7. Blue Brain Project
Project Details
| Budget | $220 million |
| Duration | 10 Years |
| Start Date | 2013 |
| Funding Source | Swiss Government |
The Blue Brain Project was created in 2005 as a Swiss research initiative that looked at the intersection of neuroscience and big data (Blue Brain, n.d.). The goal of the Blue Brain Project is to develop technology and science to digitally reconstruct and stimulate the mouse brain. By around 2024, the Blue Brain Project hopes to create a cellular-level model of an entire mouse brain (Blue Brain, n.d.).
In 2015, Blue Brain Project published their first draft of the digital reconstruction of neocortical microcircuitry (Markram et al., 2015). This study confirmed the plausibility of digitally reconstructing a portion of neocortical tissue in fine detail using experimental data and fundamental principles to fill in blanks in our knowledge. The study showed the if you can copy biology closely, then the digital brain tissue naturally behaves like real brain tissue which means that we can study this digital tissue almost like real brain tissue (Blue Brain, n.d.).
The biggest question you might ask is why mice? How does building a model of a mouse brain help scientists understand the human brain? The Blue Brain Project says that they chose mice because there is more data to begin with which makes the problem easier for them. Plus, mice are mammals, so the project can determine what type of mammal-specific challenges they may face which will later make it easier to make necessary adjustments to simulate the human brain. Additionally, to digitally reconstruct the human brain, we first need to solve the general problem of how to digitally reconstruct any brain from a small amount of data. Once they figure out how to do this with one type of brain (i.e., the mouse brain), then you can apply the same process to any brain (Blue Brain, n.d.).
Thus far, the Blue Brain Project has published over 175 papers, many of which are frequently cited and have thousands of views. The Project has also released over 31,000 model neurons, over a million data traces, and millions of predicted missing data in its web portals (Blue Brain, n.d.). All models are built by gathering data from cell morphology and physiology neuroscience research; this process is called data-driven model building. These biologically realistic simulations can be validated by comparing modeling results to experimental data on the behavior of real-life brain networks. In these two ways, the model is tied to experimental data. However, much testing and rebuilding is required to build a more accurate model (Blue Brain, n.d.). As time goes on, the Blue Brain Project can test and rebuild more and more which then creates more precise models and allows for more accurate predictions.
8. Neuralink
Project Details
| Budget | $158 million |
| Duration | Ongoing |
| Start Date | 2016 |
| Funding Source | Elon Musk |
Elon Musk, the founder of SpaceX and chief executive officer of Tesla inc., created a start-up in 2016 called Neuralink. Musk himself invested $100 million in the project. Musk claims that they are “designing the first neural implant that will let you control a computer or mobile device anywhere you go” (Musk, n.d.). This presents a lot of questions, of course. What is a Neuralink? What is the science behind this project? What is the link supposed to do specifically? When will this implant be ready for use by humans?
Neuralink is a BMI, or brain-machine interface, which is a device that translates neuronal information into commands capable of controlling external software or hardware such as a computer or robotic arm (Nature, n.d.). BMIs such as prosthetic limbs are often used as assisted living devices for individuals with motor or sensory impairments. The link itself is an implant that is connected to micron-scale threads that are inserted into the areas of the brain that control movement. Each neural thread contains many electrodes that are used to detect neural signals. The link, on the other hand, processes, stimulates, and transmits neural signals (Musk, n.d.). The last component is the charger which wirelessly connects to the implant to charge the battery from the outside. The Neuralink app would allow you to control your mobile device or computer with the activity of your brain, just by thinking about it.
Musk writes on the Neuralink website that he expects the first application of Neuralink to be computer control for people with spinal cord injury. He suggests, however, that in the future, other applications could include restoring motor and sensory function and the treatment of neurological disorders (Musk, n.d.). Earlier this year, Musk said in an interview that a monkey has been “wired up” to play video games with its mind (Shead, 2021). In February, Musk claims that the company plans to start initial human trials later this year.
9. SyNAPSE Project
Project Details
| Budget | $102.6 million |
| Duration | 8 Years |
| Start Date | 2008 |
| Funding Source | DARPA |
SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) was started in 2008 and involved designing a multi-chip system capable of emulating 1 million neurons and 1 billion synapses (Wang, 2012). The SyNAPSE program strove to develop electronic neuromorphic machine technology that scales to biological levels. In other words, the program attempted to build a new kind of computer like the mammalian brain that matches a mammalian brain in function, size, and power consumption. It was supposed to recreate 10 billion neurons, 100 trillion synapses, and consume one kilowatt, and occupy less than two liters of space. Such artificial brains could be used to build robots whose intelligence matches that of mice and cats (Wang, 2012).
In 2014, the SyNAPSE program finished developing one of the world’s largest and most complex computer chips ever produced. The chip is loaded with more than 5 billion transistors and boasts more than 250 million “synapses,” or programmable logic points, analogous to the connections between neurons in the brain (DARPA, 2014). That’s still orders of magnitude fewer than the number of actual synapses in the brain, but a giant step toward making ultra-high performance, low-power neuro-inspired systems a reality. There is much potential use for the chip. Gill Pratt, DARPA program manager, said that the chip “could give unmanned aircraft or robotic ground systems with limited power budgets a more refined perception of the environment, distinguishing threats more accurately and reducing the burden on system operators” (DARPA, 2014). Pratt continues by saying that “the extreme energy efficiency achieved by the SyNAPSE program’s accomplishments could enable a much wider range of portable computing applications for defense.” Both points by Pratt point to the chip’s usage as a technology to be utilized for defensive measures. A potential non-defense application of the SyNAPSE-developed chip is neuroscience modeling. A large number of electronic neurons and synapses in each chip and the ability to tile multiple chips could lead to the development of complex, networked neuromorphic simulators for testing network models in neurobiology and deepening the current understanding of brain function (DARPA, 2014).
10. Kernel
Project Details
| Budget | $54 million |
| Duration | 4 Years |
| Start Date | 2016 |
| Funding Source | General Catalyst |
Kernel is an LA-based full-stack neurotech startup founded in 2016 by Bryan Johnson (Etherington, 2020). Johnson’s long-term goal is to “ultimately develop a much deeper understanding in the field of neuroscience” (Etherington, 2020). Their work towards this goal has included the creation of two different imaging headsets.
One of their products, Kernel Flow, is a non-invasive, full-coverage, optical headset that measures blood through the brain to establish precise patterns of brain activity (Etherington, 2020). Kernel Flow takes advantage of the relative transparency of the skull and brain tissue to near-infrared light by beaming photons through the skull and measuring their scatting and absorption, allowing inference about blood flow and oxygenation (Kernel, n.d.). Their other product, Kernel Flux, is a turnkey, non-invasive headset that detects magnetic fields created by the collective activity of neutrons in the brain (Etherington, 2020). Kernel Flux uses an array of alkali vapor sensors (optically pumped magnetometers or OPMs) to directly detect magnetic fields generated by collective neural activity in the brain. These sensors can detect extremely small changes in magnetic fields resulting from a brain’s intrinsic electrical activity across the whole head (Kernel, n.d.). Kernel’s website says, “Flux provides resolution, speed, and fidelity never before available in a system that can operate without strict physical limitations, and at a fraction of the cost of traditional MEG systems” (Kernel, n.d.).
Both Flux and Flow record key signals that researchers and medical practitioners monitor when working with the human brain. However, to monitor these signals, researchers usually use invasive and expensive hardware. Kernel’s short-term goal is to make these services more broadly available.
References
Brain–machine interface—Latest research and news. (n.d.). Nature.
Chudler, Eric H. (n.d.). History of Neuroscience.
Connectome Programs. (n.d.). Blueprint.
Human Connectome Project. (n.d.). Human Connectome Project.
Theil, S. (n.d.). Why the Human Brain Project Went Wrong – and How to Fix It. Scientific American.
Paul G. Allen Commits $100 Million to Brain Research. (2003). Allen Institute.
Seattle researchers team up to build hi-res brain map of Alzheimer’s disease. (2020). Allen Institute.
Wang, B. (2012). DARPA Synapse Project Status. DARPA.
Georgia is an undergraduate student at Dartmouth College majoring in Computer Science and minoring in Neuroscience.