BRAIN Initiative

The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative has focused the attention of the scientific community on the question of what kind of tools are needed to address the ultimate neuroscience goal – understanding how our brain constrains the way we experience the world and controls our behavior. In this article, we express our view on how to tackle this challenge.

We take a broad, interdisciplinary perspective to examine the kinds of technologies that, collectively and within a valid theoretical framework, would facilitate the necessary quantum leap toward understanding brain function and its disruption in disease. One central challenge is to connect the microscopic cellular activity to the dynamics of large cellular ensembles. This can be achieved through coherent technological, experimental and theoretical efforts targeting the development of molecular probes and microscopic imaging that can guide interpretation of macroscopic measures of brain activity achievable in humans. Furthermore, a distinction should be made between the advancement of existing tools, and technological breakthroughs that would depend on surmounting seemingly fundamental limitations. Finally, we outline our collective vision for what might be achieved within a decade of intensified effort, including technological deliverables and neuroscience questions that might become accessible with the advancement of the technology.

Admitting significant technological and theoretical challenges, we nevertheless believe that a robust, appropriately targeted investment in the science of the brain today can position us at the threshold of a very important decade of discovery– one that transforms our understanding of the human brain and mind and sets the course for alleviating brain disorders.

Christopher G.L. Ferri (left) and Mu-Han Yang (right)

The overall goal of the BRAIN Initiative is accelerating the development and application of innovative technologies to “produce a revolutionary new dynamic picture of the brain.” This NIH-funded research project is focused on the development of optical microscopy technology that pushes the limits of how deep we can see into the brain with a cellular and subcellular resolution.

To achieve deep, high-resolution imaging while retaining sufficient signal-to-noise ratio of the measurements for imaging of the cellular- and subcellular-level activity, we are developing an unconventional “non-degenerate” two-photon microscopy capitalizing on the recent practical demonstration of the advantage of using long (infrared) wavelength light (>1 um) for deep imaging.

Our approach is composed of two complementary domains. First, we are designing a new illumination method that uses a combination of two laser beams of different color (illustrated in (a)). This method takes advantage of tissue transparency to infrared light as well as recent advances in adaptive optics to deliver the light, required for excitation of optical probes, deeper in the brain than is possible with commercially available microscopes. Second, we are optimizing the combination of the beam wavelengths (i.e., colors) to enhance the ability of optical probes to absorb the light leading to brighter fluorescence (illustrated in (b)).

Overall, we expect to achieve ~1.6 mm penetration inside the brain tissue while avoiding excessive laser power and retaining the excitation volume (i.e. spatial resolution) characteristic for conventional two-photon microscopy. Because reconstruction of neuronal circuit activity requires high-resolution and high sensitivity measurements throughout the circuit geometry (e.g., throughout the entire depth of the cerebral cortex) the proposed technological advances would open the door for hypothesis-driven experiments that are currently unfeasible.

Check out our recent publication in Optics Express.

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use noninvasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from noninvasive signals in humans.

On the essential path towards this goal is the development of a detailed “bottom-up” forward model bridging neuronal activity at the level of cell-type-specific populations to noninvasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging, fMRI), and electrical currents/potentials (measurable with magneto/electroencephalography, MEG/EEG). This forward model would then provide the “ground truth” for the development of new tools for tackling the inverse problem – estimation of neuronal activity from multimodal noninvasive imaging data.

To illustrate this approach, we focus on the primary somatosensory cortex where bottom-up models can be built and calibrated taking advantage of well-studied neuronal network phenomena such as the surround and transcallosal inhibition. In animals (e.g., mice) we can utilize microscopic measurement technologies to precisely and quantitatively probe concrete microscopic neuronal, vascular, and metabolic parameters while manipulating cell-type-specific neuronal activity (blue boxes in the Figure). These microscopic data can then be used to simulate the corresponding macroscopic physiological parameters (CBF, CMRO₂, and current dipole moment) and their reflection in noninvasive observables (red boxes in the Figure). Thus, in mice, we can develop a detailed forward model bridging neuronal activity at the level of cell-type-specific populations to noninvasive imaging signals. Furthermore, we can validate this model at each step against real data. For human translation, first we would have to calibrate the model parameters to account for systematic differences due to known physical scaling laws such as differences in vessel size or latency of the cortical neuronal response. Then, the remaining uncertainty in the translation of model parameters from mouse to human (as well as the measurement noise and subject-to-subject variability) would be factored into a single Bayesian estimation framework to obtain estimates of the parameters of interest (i.e., activity of cell-type-specific neuronal populations) and quantify the uncertainty of estimation.

Read more on our approach to the physiological underpinning of human noninvasive imaging in our recent publication in Philosophical Transactions of the Royal Society B.

The first issue of Neurophotonics was dedicated to the BRAIN Initiative featuring contributions from the leading scientists in the field. We expect that new optical methods for imaging and manipulation of brain activity (and the underlying structure) will continue to be at the forefront of technological developments enabling acceleration of neuroscience discovery. We launched Neurophotonics with a series of articles providing an overview of the current state-of-the-art on specific areas of application of optics and photonics in neuroscience and offering a vision for future directions. Read our Editorial here.

The available noninvasive measurements provide only indirect information about the activity of brain cells and circuits, leaving a gap between the macroscopic activity patterns available in humans and the rich, detailed, and mechanistic view achievable in model organisms. The mission of our Center is to bridge the gap between microscopic cellular activity to the dynamics of large neuronal ensembles and their reflection in noninvasive “observables”. Laying a solid physiological foundation for human functional neuroimaging would give us the tools we need for getting insights into formation of thoughts, storage and retrieval of memories, and cognitive dysfunction in disorders like schizophrenia, autism, or traumatic brain injury.

As a foundation, we are assembling a suite of micro- and nanoscopic technologies that, collectively, will allow precise and quantitative probing of large numbers of the relevant physiological parameters in animal models. Next, we combine multimodal measurements and system-level analysis/modeling, commonly used in electrical engineering, to understand how specific patterns of microscopic brain activity (and their pathological departures) translate to noninvasive observables. 

Our Center is built around a true interdisciplinary integration of neuroscience, physical sciences, and engineering with the technological advances, experimentation, and theory progressing hand in hand. Our technology is targeted to neuroscience needs; the theory is used to motivate the experiments, and the experiments to advance the theory and inspire further technological developments. We view dissemination of novel tools as part of our mission, enabling UCSD investigators to ask neuroscience questions that are becoming accessible with the advancement of the technology.

This Center has been funded by the UCSD Center for Brain Activity Mapping (CBAM) and the UCSD Frontiers of Innovation program.