Researchers look to the eye for insights about the brain

Researchers seeking to unravel the mysteries of how our amazingly complex brains do what they do, often start with the eye. An extension of neural tissue connecting the eye and brain, the retina, the light-sensing tissue at the back of the eye has long been a model for scientists to explore how the brain works.

 “Much of what we know about the brain comes from studies of the retina because it is far more accessible for investigation,” said Santa Tumminia, Ph.D., acting director of the National Eye Institute (NEI), part of the National Institutes of Health.

“Decades of NEI-supported research on retinal cells has led to fundamental discoveries about how one nerve cell communicates with another, how different cell types process different kinds of sensory information, and how neural tissue develops and organizes itself into circuits,” she said.

Studies of the retina, optic nerve and primary visual cortex therefore are a part of the Federally led moonshot project called the BRAIN Initiative, which aims to elucidate how the brain functions in health and disease. The hope is that such knowledge will help accelerate progress in treating and preventing brain disorders such as Alzheimer’s and Parkinson’s disease, depression and traumatic brain injury.

Since launching six years ago, the BRAIN initiative, short for Brain Research through Advancing Innovative Neurotechnologies, has funded dozens of vision-related projects. About 40% of BRAIN projects involve vision-related research or involve investigators currently or formerly funded by the NEI.

The NIH leads the public-private initiative in coordination with partners from industry, academia and other federal research agencies, including the NEI. BRAIN launched in 2014 as part of the 21st Century Cures Act. Signed into law by Congress in December 2016, the Act was designed to accelerate the development of medical innovations and therapeutic advances.

Taking inventory

The brain is a complex tissue comprising a diverse range of uncharacterized cell types. Many initial BRAIN projects are therefore aimed at figuring out how to discriminate cell types in such a complex tissue. These “cell census” projects aspire to create a whole-brain atlas that systematically characterizes cell diversity. Classifying cell types by their morphology, molecular and functional properties, and connectivity is seen as a starting point for understanding how the brain works.

Researchers looking to validate tools for sorting cell types in the brain start with the retina since much is already known about its various cell types, according to BRAIN Investigator, Joshua Sanes, Ph.D., professor of molecular and cellular biology at Harvard University.

Such is the case with Drop-seq, a technique that analyzes different cell types within a complex tissue. Though its development was not funded by BRAIN, Drop-seq was first deployed on a slice of mouse retina in a BRAIN-funded project as a way of validating whether the technique would be up to the task of sorting through cell types in the brain.

Sanes and a team led by Steve McCarroll, Ph.D., professor of biomedical science and genetics at Harvard Medical School, identified 44,808 single-cell profiles in their sample of retina, from which they teased out 39 distinct cell populations according to genetic information stored in each cell’s RNA. Reassuringly, Drop-seq was able to confirm the identities of many mouse retinal cell types that had previously been identified. The investigators went on to generate a complete cell atlas of the mouse retina, and then used this as a foundation to generate atlases of human and other retinas.²

Most importantly, the findings confirmed Drop-seq’s potential usefulness as a tool to sort through and catalogue the various cell types in the brain.³

 “Drop seq is a great way to quickly go through a tissue and tell what sorts of genes are expressed in the tissue by different cell types,” said Thomas Greenwell, Ph.D., program director for retinal neuroscience at the NEI.

Developed in McCarroll’s lab, Drop-seq quickly, inexpensively, and simultaneously profiles the gene expression of many different cell types in a complex tissue, and it does so cell by cell. The technique uses microfluidics to encapsulate single cells in droplets and microbeads covered with barcoded primers. The system allows researchers to capture and barcode a useful fraction of RNA, which labels gene expression from each cell. Future studies can then start to look how each cell type functions over time, and in health and disease.

From cells to circuits

Similarly, another project, EyeWire, began by classifying cell types in the retina as a step toward understanding how neurons form circuits. Led by Sebastian Seung, Ph.D., professor of computer science at the Princeton Neuroscience Institute, EyeWire is a citizen science project that has amassed a 3D interactive online “museum” of retinal cell types as well as their connections with other neurons.

The project began with 3D electron microscopy scanning of a section of mouse retina. The result was millions of 2D grayscale, cross-sectional images that lack depth information. Seung and his team turned to public crowdsourcing for help translating the greyscale images into colorful 3D representations of the neurons. The online game EyeWire assigns each player a cube of microscopy images — each cube is only a fraction of the width of a single hair. Gamers earn points by selecting and coloring the pathway of a neuron’s branches through their cube in collaboration with an artificial intelligence algorithm.

Since 2012, EyeWire gamers have mapped thousands of retinal neurons, including nearly 400 retinal ganglion cells, the types of cells that form the optic nerve that connects the eye and the brain.⁴ In addition, the project identified six new types of neurons in the retina and reconstructed previously unknown circuits.

Similarly, a recently launched BRAIN-funded project is underway to reconstruct some 100,000 neurons and their synapses in brain tissue. The Machine Intelligence from Cortical Networks (MICrONS Explorer) program, is developing a visualization tool that features excitatory cortical neurons from mouse primary visual cortex. The dataset includes electron microscopy-based reconstructions of circuitry, along with corresponding connectivity and functional imaging data collected by a consortium of laboratories and led by NEI-funded investigators, Seung at Princeton;  R Clay Reid, M.D., Ph.D., the Allen Institute for Brain Science; and Andreas Tolias, Ph.D., Baylor College of Medicine.

All together now: Visual processing as a model for studying brain circuitry

Vision researchers have used behaving-animal models and other techniques to develop detailed maps of how the many visual areas throughout the brain are functionally organized and interconnected. This information allows interesting questions to be addressed such as how circuits function to control eye movement, to guide the motion of our bodies and vehicles through space, to recognize complex objects such as faces, and in cognitive processes such as selective attention and visual memory.

BRAIN researcher,  R Clay Reid, M.D., Ph.D., senior investigator at the Allen Institute for Brain Science, studies brain circuitry by building on the knowledge of how neurons in the visual system respond to visual stimuli. He hopes to not only map circuits within the visual system, but capture the physiology of those circuits, how each cell functions and contributes to the circuit working properly.

Reid is using a modified virus to label ensembles of visual cortex neurons, all of which connect with a single ‘target’ neuron in each experiment. Once the neurons are labeled, they are using an advanced form of scanning-laser imaging to make movies of each neuron’s activity in response to carefully chosen visual stimuli.

Together, these tools will allow them to probe the functional logic of wiring within three visual cortical areas. They will then examine the functional logic of connections between these areas.

“The data we collect will serve as a foundation for understanding connections among cortical circuits and provide new, data-driven models of cortical function,” Reid said.

Engineering vision — without the eye

Other BRAIN investigators are attempting to artificially produce vision with a strategy that bypasses the eyes. The concept that our brains are capable of visual perception without the eyes has a long history including an observation in 1918. During brain surgery to remove bone fragments from a bullet wound, the patient’s brain was stimulated with a small electrical current, and he reported seeing small flashes of light in his visual field despite the absence of such light.

Numerous studies since have sought to leverage the ability to stimulate the visual cortex to produce percepts of light, called phosphenes. Biomedical engineering advances have yielded technologies to wirelessly power and control electrodes in the brain to stimulate light percepts.

Building on those advances, NEI-supported researcher Daniel Yoshor, M.D., formerly chair and professor of neurosurgery at Baylor College of Medicine, clinically tested a visual prosthesis system to help people with ocular causes of blindness regain at least some functional vision.

The device, called Orion, generates visual perception via an array of stimulating electrodes implanted on the surface of the visual cortex to deliver patterned electrical stimuli.  A camera mounted on the patient’s glasses captures video images and then a computer translates those images into a series of small electrical pulses transmitted wirelessly to the electrodes implanted on the visual cortex.

“Imagine that for every spot in a person’s visual field, there’s a corresponding set of visual cortical neurons that represents that area. The idea is to precisely stimulate someone’s visual cortical neurons such that we produce the perception of a spot of light corresponding to the visual world to reproduce vision,” said Yoshor, who is now chair and professor of neurosurgery at the the University of Pennsylvania.

Yoshor collaborated with BRAIN investigators, Nader Pouratian M.D., Ph.D., University of California Los Angeles; Robert Greenberg, M.D., Ph.D., Alfred E. Mann Foundation; and Jessy Dorn, Ph.D., Second Sight Medical Products, which developed the device.

“The team has had remarkable early success tuning the stimuli and training wearers of the device to achieve some moderately useful vision,” said Martha Flanders, Ph.D., director of the Central Visual Processing Program at the NEI.

In a recent study, the team successfully calibrated the prosthesis system so that stimulation of the visual cortex conveyed the act of drawing of letters. Device wearers were able to reproduce letters on a touchscreen, with a striking correspondence between the predicted shape of the letters and the perceived shape of the letters.¹

NEI and BRAIN funding for the projects include grants: 1U01MH105960-01 to Sanes; U19NS104648 to Seung; R01NS104949, RF1MH117820 to Reid; R01EY023336 to Yoshor; and 1UH3NS103442 to Pouratian.  

 

1              Beauchamp, M. S. et al. Dynamic Stimulation of Visual Cortex Produces Form Vision in Sighted and Blind Humans. Cell 181, 774-783.e775, doi:10.1016/j.cell.2020.04.033 (2020).

2              Peng, Y.-R. et al. Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina. Cell 176, 1222-1237.e1222, doi:https://doi.org/10.1016/j.cell.2019.01.004 (2019).

3              Macosko, Evan Z. et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell 161, 1202-1214, doi:https://doi.org/10.1016/j.cell.2015.05.002 (2015).

4              Bae, J. A. et al. Digital Museum of Retinal Ganglion Cells with Dense Anatomy and Physiology. Cell 173, 1293-1306.e1219, doi:https://doi.org/10.1016/j.cell.2018.04.040 (2018).

 

 

 

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