Mapping connections of single neurons using a holographic light beam

November 18, 2017

Controlling single neurons using optogenetics (credit: the researchers)

Researchers at MIT and Paris Descartes University have developed a technique for precisely mapping connections of individual neurons for the first time by triggering them with holographic laser light.

The technique is based on optogenetics (using light to stimulate or silence light-sensitive genetically modified protein molecules called “opsins” that are embedded in specific neurons). Current optogenetics techniques can’t isolate individual neurons (and their connections) because the light strikes a relatively large area — stimulating axons and dendrites of other neurons simultaneously (and these neurons may have different functions, even when nearby).

The new technique stimulates only the soma (body) of the neuron, not its connections. To achieve that, the researchers combined two new advances: an optimized holographic light-shaping microscope* and a localized, more powerful opsin protein called CoChR.

Two-photon computer-generated holography (CGH) was used to create three-dimensional sculptures of light that envelop only a target cell, using a conventional pulsed laser coupled with a widefield epifluorescence imaging system. (credit: Or A. Shemesh et al./Nature Nanoscience)

The researchers used an opsin protein called CoChR, which generates a very strong electric current in response to light, and fused it to a small protein that directs the opsin into the cell bodies of neurons and away from axons and dendrites, which extend from the neuron body, forming “somatic channelrhodopsin” (soCoChR). This new opsin enabled photostimulation of individual cells (regions of stimulation are highlighted by magenta circles) in mouse cortical brain slices with single-cell resolution and with less than 1 millisecond temporal (time) precision — achieving connectivity mapping on intact cortical circuits without crosstalk between neurons. (credit: Or A. Shemesh et al./Nature Nanoscience)

In the new study, by combining this approach with new ““somatic channelrhodopsin” opsins that cluster in the cell body, the researchers showed they could stimulate individual neurons with not only precise spatial control but also great control over the timing of the stimulation. When they target a specific neuron, it responds consistently every time, with variability that is less than one millisecond, even when the cell is stimulated many times in a row.

“For the first time ever, we can bring the precision of single-cell control toward the natural timescales of neural computation,” says Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research. Boyden is co-senior author with Valentina Emiliani, a research director at France’s National Center for Scientific Research (CNRS) and director of the Neurophotonics Laboratory at Paris Descartes University, of a study that appears in the Nov. 13 issue of Nature Neuroscience.

Mapping neural connections in real time

Using this technique, the researchers were able to stimulate single neurons in brain slices and then measure the responses from cells that are connected to that cell. This may pave the way for more precise diagramming of the connections of the brain, and analyzing how those connections change in real time as the brain performs a task or learns a new skill.

Optogenetics was co-developed in 2005 by Ed Boyden (credit: MIT)

One possible experiment, Boyden says, would be to stimulate neurons connected to each other to try to figure out if one is controlling the others or if they are all receiving input from a far-off controller.

“It’s an open question,” he says. “Is a given function being driven from afar, or is there a local circuit that governs the dynamics and spells out the exact chain of command within a circuit? If you can catch that chain of command in action and then use this technology to prove that that’s actually a causal link of events, that could help you explain how a sensation, or movement, or decision occurs.”

As a step toward that type of study, the researchers now plan to extend this approach into living animals. They are also working on improving their targeting molecules and developing high-current opsins that can silence neuron activity.

The research was funded by the National Institutes of Health, France’s National Research Agency, the Simons Foundation for the Social Brain, the Human Frontiers Science Program, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the Defense Advanced Research Projects Agency.

* Traditional holography is based on reproducing, with light, the shape of a specific object, in the absence of that original object. This is achieved by creating an “interferogram” that contains the information needed to reconstruct an object that was previously illuminated by a reference beam. In computer-generated holography, the interferogram is calculated by a computer without the need of any original object. Combined with two-photon excitation, CGH can be used to refocus laser light to precisely illuminate a cell or a defined group of cells in the brain.


Abstract of Temporally precise single-cell-resolution optogenetics

Optogenetic control of individual neurons with high temporal precision within intact mammalian brain circuitry would enable powerful explorations of how neural circuits operate. Two-photon computer-generated holography enables precise sculpting of light and could in principle enable simultaneous illumination of many neurons in a network, with the requisite temporal precision to simulate accurate neural codes. We designed a high-efficacy soma-targeted opsin, finding that fusing the N-terminal 150 residues of kainate receptor subunit 2 (KA2) to the recently discovered high-photocurrent channelrhodopsin CoChR restricted expression of this opsin primarily to the cell body of mammalian cortical neurons. In combination with two-photon holographic stimulation, we found that this somatic CoChR (soCoChR) enabled photostimulation of individual cells in mouse cortical brain slices with single-cell resolution and <1-ms temporal precision. We used soCoChR to perform connectivity mapping on intact cortical circuits.

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Why the “You” in an Afterlife Wouldn’t Really Be You

July 23, 2017

The Discovery is a 2017 Netflix film in which Robert Redford plays a scientist who proves that the afterlife is real. “Once the body dies, some part of our consciousness leaves us and travels to a new plane,” the scientist explains, evidenced by his machine that measures, as another character puts it, “brain wavelengths on a subatomic level leaving the body after death.”

This idea is not too far afield from a real theory called quantum consciousness, proffered by a wide range of people, from physicist Roger Penrose to physician Deepak Chopra. Some versions hold that our mind is not strictly the product of our brain and that consciousness exists separately from material substance, so the death of your physical body is not the end of your conscious existence. Because this is the topic of my next book, Heavens on Earth: The Scientific Search for the Afterlife, Immortality, and Utopia (Henry Holt, 2018), the film triggered a number of problems I have identified with all such concepts, both scientific and religious.

First, there is the assumption that our identity is located in our memories, which are presumed to be permanently recorded in the brain: if they could be copied and pasted into a computer or duplicated and implanted into a resurrected body or soul, we would be restored. But that is not how memory works. Memory is not like a DVR that can play back the past on a screen in your mind. Memory is a continually edited and fluid process that utterly depends on the neurons in your brain being functional. It is true that when you go to sleep and wake up the next morning or go under anesthesia for surgery and come back hours later, your memories return, as they do even after so-called profound hypothermia and circulatory arrest. Under this procedure, a patient’s brain is cooled to as low as 50 degrees Fahrenheit, which causes electrical activity in neurons to stop—suggesting that long-term memories are stored statically. But that cannot happen if your brain dies. That is why CPR has to be done so soon after a heart attack or drowning—because if the brain is starved of oxygen-rich blood, the neurons die, along with the memories stored therein.

Second, there is the supposition that copying your brain’s connectome—the diagram of its neural connections—uploading it into a computer (as some scientists suggest) or resurrecting your physical self in an afterlife (as many religions envision) will result in you waking up as if from a long sleep either in a lab or in heaven. But a copy of your memories, your mind or even your soul is not you. It is a copy of you, no different than a twin, and no twin looks at his or her sibling and thinks, “There I am.” Neither duplication nor resurrection can instantiate you in another plane of existence.

Third, your unique identity is more than just your intact memories; it is also your personal point of view. Neuroscientist Kenneth Hayworth, a senior scientist at the Howard Hughes Medical Institute and president of the Brain Preservation Foundation, divided this entity into the MEMself and the POVself. He believes that if a complete MEMself is transferred into a computer (or, presumably, resurrected in heaven), the POVself will awaken. I disagree. If this were done without the death of the person, there would be two memory selves, each with its own POVself looking out at the world through its unique eyes. At that moment, each would take a different path in life, thereby recording different memories based on different experiences. “You” would not suddenly have two POVs. If you died, there is no known mechanism by which your POVself would be transported from your brain into a computer (or a resurrected body). A POV depends entirely on the continuity of self from one moment to the next, even if that continuity is broken by sleep or anesthesia. Death is a permanent break in continuity, and your personal POV cannot be moved from your brain into some other medium, here or in the hereafter.

If this sounds dispiriting, it is just the opposite. Awareness of our mortality is uplifting because it means that every moment, every day and every relationship matters. Engaging deeply with the world and with other sentient beings brings meaning and purpose. We are each of us unique in the world and in history, geographically and chronologically. Our genomes and connectomes cannot be duplicated, so we are individuals vouchsafed with awareness of our mortality and self-awareness of what that means. What does it mean? Life is not some temporary staging before the big show hereafter—it is our personal proscenium in the drama of the cosmos here and now.”

This article was originally published with the title “Who Are You?”

ABOUT THE AUTHOR(S)

Michael Shermer is publisher of Skeptic magazine (www.skeptic.com) and a Presidential Fellow at Chapman University. His next book is Heavens on Earth. Follow him on Twitter @michaelshermer

https://www.scientificamerican.com/article/why-the-ldquo-you-rdquo-in-an-afterlife-wouldnt-really-be-you/

Chip with Brain-inspired Non-Von Neumann Architecture has 1M Neurons, 256M Synapses

August 28, 2014

synapse chip infographic_07-30-14a

San Jose, CA Scientists from IBM have unveiled the first neurosynaptic computer chip to achieve an unprecedented scale of one million programmable neurons, 256 million programmable synapses and 46 billion synaptic operations per second per watt. At 5.4 billion transistors, this fully functional and production-scale chip is currently one of the largest CMOS chips ever built, yet, while running at biological real time, it consumes a minuscule 70mW — orders of magnitude less power than a modern microprocessor. A neurosynaptic supercomputer the size of a postage stamp that runs on the energy equivalent of a hearing-aid battery, this technology could transform science, technology, business, government and society by enabling vision, audition and multi-sensory applications.

The breakthrough, published in Science in collaboration with Cornell Tech, is a significant step toward bringing cognitive computers to society.

There is a huge disparity between the human brain’s cognitive capability and ultra-low power consumption when compared to today’s computers. To bridge the divide, IBM scientists created something that didn’t previously exist — an entirely new neuroscience-inspired scalable and efficient computer architecture that breaks path with the prevailing von Neumann architecture used almost universally since 1946.

This second-generation chip is the culmination of almost a decade of research and development, including the initial single core hardware prototype in 2011 and software ecosystem with a new programming language and chip simulator in 2013.

The new cognitive chip architecture has an on-chip two-dimensional mesh network of 4096 digital, distributed neurosynaptic cores, where each core module integrates memory, computation and communication, and operates in an event-driven, parallel and fault-tolerant fashion. To enable system scaling beyond single-chip boundaries, adjacent chips, when tiled, can seamlessly connect to each other — building a foundation for future neurosynaptic supercomputers. To demonstrate scalability, IBM also revealed a 16-chip system with sixteen million programmable neurons and four billion programmable synapses.

“IBM has broken new ground in the field of brain-inspired computers, in terms of a radically new architecture, unprecedented scale, unparalleled power/area/speed efficiency, boundless scalability, and innovative design techniques. We foresee new generations of information technology systems — that complement today’s von Neumann machines — powered by an evolving ecosystem of systems, software and services,” said Dr. Dharmendra S. Modha, IBM Fellow and IBM Chief Scientist, Brain-Inspired Computing, IBM Research. “These brain-inspired chips could transform mobility, via sensory and intelligent applications that can fit in the palm of your hand but without the need for Wi-Fi. This achievement underscores IBM’s leadership role at pivotal transformational moments in the history of computing via long-term investment in organic innovation.”

The Defense Advanced Research Projects Agency (DARPA) has funded the project since 2008 with approximately $53M via Phase 0, Phase 1, Phase 2, and Phase 3 of the Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program. Current collaborators include Cornell Tech and iniLabs.

Building the Chip

The chip was fabricated using Samsung’s 28nm process technology that has a dense on-chip memory and low-leakage transistors.

“It is an astonishing achievement to leverage a process traditionally used for commercially available, low-power mobile devices to deliver a chip that emulates the human brain by processing extreme amounts of sensory information with very little power,” said Shawn Han, vice president of Foundry Marketing, Samsung Electronics. “This is a huge architectural breakthrough that is essential as the industry moves toward the next-generation cloud and big-data processing. It’s a pleasure to be part of technical progress for next-generation through Samsung’s 28nm technology.”

The event-driven circuit elements of the chip used the asynchronous design methodology developed at Cornell Tech and refined with IBM since 2008.

“After years of collaboration with IBM, we are now a step closer to building a computer similar to our brain,” said Professor Rajit Manohar, Cornell Tech.

The combination of cutting-edge process technology, hybrid asynchronous-synchronous design methodology, and new architecture has led to a power density of 20mW/cm2 which is nearly four orders of magnitude less than today’s microprocessors.

Advancing the SyNAPSE Ecosystem

The new chip is a component of a complete end-to-end vertically integrated ecosystem spanning a chip simulator, neuroscience data, supercomputing, neuron specification, programming paradigm, algorithms and applications, and prototype design models. The ecosystem supports all aspects of the programming cycle from design through development, debugging, and deployment.

To bring forth this fundamentally different technological capability to society, IBM has designed a novel teaching curriculum for universities, customers, partners and IBM employees.

Applications and Vision

This ecosystem signals a shift in moving computation closer to the data, taking in vastly varied kinds of sensory data, analyzing and integrating real-time information in a context-dependent way, and dealing with the ambiguity found in complex, real-world environments.

Looking to the future, IBM is working on integrating multi-sensory neurosynaptic processing into mobile devices constrained by power, volume and speed; integrating novel event-driven sensors with the chip; real-time multimedia cloud services accelerated by neurosynaptic systems; and neurosynaptic supercomputers by tiling multiple chips on a board, creating systems that would eventually scale to one hundred trillion synapses and beyond.

Building on previously demonstrated neurosynaptic cores with on-chip, online learning, IBM envisions building learning systems that adapt in real world settings. While today’s hardware is fabricated using a modern CMOS process, the underlying architecture is poised to exploit advances in future memory, 3-D integration, logic, and sensor technologies to deliver even lower power, denser package, and faster speed.

http://www.scientificcomputing.com/news/2014/08/chip-brain-inspired-non-von-neumann-architecture-has-1m-neurons-256m-synapses