114
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A Brain-to-Brain Interface for Real-Time Sharing of Sensorimotor Information

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          A brain-to-brain interface (BTBI) enabled a real-time transfer of behaviorally meaningful sensorimotor information between the brains of two rats. In this BTBI, an “encoder” rat performed sensorimotor tasks that required it to select from two choices of tactile or visual stimuli. While the encoder rat performed the task, samples of its cortical activity were transmitted to matching cortical areas of a “decoder” rat using intracortical microstimulation (ICMS). The decoder rat learned to make similar behavioral selections, guided solely by the information provided by the encoder rat's brain. These results demonstrated that a complex system was formed by coupling the animals' brains, suggesting that BTBIs can enable dyads or networks of animal's brains to exchange, process, and store information and, hence, serve as the basis for studies of novel types of social interaction and for biological computing devices.

          Related collections

          Most cited references26

          • Record: found
          • Abstract: found
          • Article: not found

          Brain-to-brain coupling: a mechanism for creating and sharing a social world.

          Cognition materializes in an interpersonal space. The emergence of complex behaviors requires the coordination of actions among individuals according to a shared set of rules. Despite the central role of other individuals in shaping one's mind, most cognitive studies focus on processes that occur within a single individual. We call for a shift from a single-brain to a multi-brain frame of reference. We argue that in many cases the neural processes in one brain are coupled to the neural processes in another brain via the transmission of a signal through the environment. Brain-to-brain coupling constrains and shapes the actions of each individual in a social network, leading to complex joint behaviors that could not have emerged in isolation. Copyright © 2011 Elsevier Ltd. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Active tactile exploration enabled by a brain-machine-brain interface

            Brain-machine interfaces (BMIs) 1,2 use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. While BMIs aim to restore the normal sensorimotor functions of the limbs, so far they have lacked tactile sensation. Here we demonstrate the operation of a brain-machine-brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and enables the signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1). Monkeys performed an active-exploration task in which an actuator (a computer cursor or a virtual-reality hand) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in primary motor cortex (M1). ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search and discriminate one out of three visually undistinguishable objects, using the virtual hand to identify the unique artificial texture (AT) associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic, or even virtual prostheses.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex.

              To determine whether simultaneously recorded motor cortex neurons can be used for real-time device control, rats were trained to position a robot arm to obtain water by pressing a lever. Mathematical transformations, including neural networks, converted multineuron signals into 'neuronal population functions' that accurately predicted lever trajectory. Next, these functions were electronically converted into real-time signals for robot arm control. After switching to this 'neurorobotic' mode, 4 of 6 animals (those with > 25 task-related neurons) routinely used these brain-derived signals to position the robot arm and obtain water. With continued training in neurorobotic mode, the animals' lever movement diminished or stopped. These results suggest a possible means for movement restoration in paralysis patients.
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                28 February 2013
                2013
                : 3
                : 1319
                Affiliations
                [1 ]Department of Neurobiology, Duke University , Durham, NC 27710, USA
                [2 ]Department of Biomedical Engineering, Duke University , Durham, NC 27710, USA
                [3 ]Department of Psychology and Neuroscience, Duke University , Durham, NC 27710, USA
                [4 ]Duke Center for Neuroengineering, Duke University , Durham, NC 27710, USA
                [5 ]Edmond and Lily Safra International Institute for Neuroscience of Natal (ELS-IINN) , RN 59066-060, Natal, Brazil
                [6 ]Current address: Neuroscience Research Institute, Peking University, Beijing, 100191.
                Author notes
                Article
                srep01319
                10.1038/srep01319
                3584574
                23448946
                32c8b059-e25a-464c-b596-fc842278bef6
                Copyright © 2013, Macmillan Publishers Limited. All rights reserved

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                : 20 December 2012
                : 08 February 2013
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article