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Brain-to-Brain Networks Established in Rodents and Primates

Neuroscientists at Duke University have introduced a new paradigm for brain-machine interfaces that investigates the physiological properties and adaptability of brain circuits, and how the brains of two or more animals can work together to complete simple tasks.

These brain networks, or Brainets, are described in two articles to be published in the July 9, 2015, issue of Scientific Reports. In separate experiments reported in the journal, the brains of monkeys and the brains of rats are linked, allowing the animals to exchange sensory and motor information in real time to control movement or complete computations.

In one example, scientists linked the brains of rhesus macaque monkeys, who worked together to control the movements of the arm of a virtual avatar on a digital display in front of them. Each animal controlled two of three dimensions of movement for the same arm as they guided it together to touch a moving target.

In the rodent experiment, scientists networked the brains of four rats complete simple computational tasks involving pattern recognition, storage and retrieval of sensory information, and even weather forecasting.

Brain-machine interfaces (BMIs) are computational systems that allow subjects to use their brain signals to directly control the movements of artificial devices, such as robotic arms, exoskeletons or virtual avatars.

The Duke researchers, working at the Center for Neuroengineering, have previously built BMIs to capture and transmit the brain signals of individual rats, monkeys, and even human subjects to artificial devices.

“This is the first demonstration of a shared brain-machine interface, a paradigm that has been translated successfully over the past decades from studies in animals all the way to clinical applications,” said Miguel Nicolelis, M.D., Ph. D., co-director of the Center for Neuroengineering at the Duke University School of Medicine and principal investigator for the study. “We foresee that shared BMIs will follow the same track, and could soon be translated to clinical practice.”

To complete the experiments, Nicolelis and his team outfitted the animals with arrays implanted in their motor and somatosensory cortices to capture and transmit their brain activity.

For one experiment highlighted in the primate article, researchers recorded the electrical activity of more than 700 neurons from the brains of three monkeys as they moved a virtual arm toward a target. In this experiment, each monkey mentally controlled two out of three dimensions (i.e., x-axis and y-axis; see video) of the virtual arm.

The monkeys could be successful only when at least two of them synchronized their brains to produce continuous 3-D signals that moved the virtual arm. As the animals gained more experience and training in the motor task, researchers found that they adapted to the challenge.

This image shows a prefrontal-limbic-midbrain circuit is responsible for the genetic transfer of an anxious temperament.

Three monkeys share control over the movement of a virtual arm in 3-D space. Each monkey contributes to two of three axes (X, Y and Z). Monkey C contributes to y- and z-axes (red dot), monkey M contributes to x- and y-axes (blue dot), and monkey K contributes to y- and z-axes (green dot). The contribution of the two monkeys to each axis is averaged to determine the arm position (represented by the black dot). Image credit: Miguel Nicolelis, Duke Medicine.

The study described in the second paper used groups of three or four rats whose brains were interconnected via microwire arrays in the somatosensory cortex of the brain and received and transmitted information via those wires.

In one experiment, rats received temperature and barometric pressure information and were able to combine information with the other rats to predict an increased or decreased chance of rain. Under some conditions, the authors observed that the rat Brainet could perform at the same level or better than one rat on its own.

These results support the original claim of the same group that Brainets may serve as test beds for the development of organic computers created by the interfacing of multiple animal brains with computers.

Nicolelis and colleagues of the Walk Again Project, based in the project’s laboratory in Brazil, are currently working on a non-invasive human Brainet to be used for neuro-rehabilitation training in paralyzed patients.

About this neuroscience research

Funding: The research was funded by the National Institutes of Health, NIH/National Institute of Mental Health, and Fundacao BIAL.

Source: Susan Halkiotis – Duke Medicine
Image Credit: Image is credited to Miguel Nicolelis, Duke Medicine
Original Research: Full open access research for “Computing Arm Movements with a Monkey Brainet” by Arjun Ramakrishnan, Peter J. Ifft, Miguel Pais-Vieira, Yoon Woo Byun, Katie Z. Zhuang, Mikhail A. Lebedev and Miguel A.L. Nicolelis in Scientific Reports. Published online July 9 2015 doi:10.1038/srep10767
Full open access research for “Building an organic computing device with multiple interconnected brains” by Miguel Pais-Vieira, Gabriela Chiuffa, Mikhail Lebedev, Amol Yadav and Miguel A. L. Nicolelis in Scientific Reports. Published online July 9 2015 doi:10.1038/srep11869


Abstract

Computing Arm Movements with a Monkey Brainet

Traditionally, brain-machine interfaces (BMIs) extract motor commands from a single brain to control the movements of artificial devices. Here, we introduce a Brainet that utilizes very-large-scale brain activity (VLSBA) from two (B2) or three (B3) nonhuman primates to engage in a common motor behaviour. A B2 generated 2D movements of an avatar arm where each monkey contributed equally to X and Y coordinates; or one monkey fully controlled the X-coordinate and the other controlled the Y-coordinate. A B3 produced arm movements in 3D space, while each monkey generated movements in 2D subspaces (X-Y, Y-Z, or X-Z). With long-term training we observed increased coordination of behavior, increased correlations in neuronal activity between different brains, and modifications to neuronal representation of the motor plan. Overall, performance of the Brainet improved owing to collective monkey behaviour. These results suggest that primate brains can be integrated into a Brainet, which self-adapts to achieve a common motor goal.

“Computing Arm Movements with a Monkey Brainet” by Arjun Ramakrishnan, Peter J. Ifft, Miguel Pais-Vieira, Yoon Woo Byun, Katie Z. Zhuang, Mikhail A. Lebedev and Miguel A.L. Nicolelis in Scientific Reports. Published online July 9 2015 doi:10.1038/srep10767


Abstract

Building an organic computing device with multiple interconnected brains

Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers.

“Building an organic computing device with multiple interconnected brains” by Miguel Pais-Vieira, Gabriela Chiuffa, Mikhail Lebedev, Amol Yadav and Miguel A. L. Nicolelis in Scientific Reports. Published online July 9 2015 doi:10.1038/srep11869

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