Non-invasive brain to brain communication to allow a human to mentally control movement of a rats tail

Harvard researchers have created the first noninvasive brain-to-brain interface (BBI) between a human and a rat. The interface allows the human to control the rat’s tail. This is computer mediated telepathy and remote control of another body from someone elses brain.

The human BCI has an accuracy of 94%, and that it generally takes around 1.5 seconds for the entire process — from the human deciding to look at the screen, through to the movement of the rat’s tail.

More accurate brain mapping is needed to achieve more precise and complex control

Transcranial focused ultrasound (FUS) is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI). In conjunction with the use of brain-to-computer interface (BCI) techniques that translate brain function to generate computer commands, we investigated the feasibility of using the FUS-based CBI to non-invasively establish a functional link between the brains of different species (i.e. human and Sprague-Dawley rat), thus creating a brain-to-brain interface (BBI). The implementation was aimed to non-invasively translate the human volunteer’s intention to stimulate a rat’s brain motor area that is responsible for the tail movement. The volunteer initiated the intention by looking at a strobe light flicker on a computer display, and the degree of synchronization in the electroencephalographic steady-state-visual-evoked-potentials (SSVEP) with respect to the strobe frequency was analyzed using a computer. Increased signal amplitude in the SSVEP, indicating the volunteer’s intention, triggered the delivery of a burst-mode FUS (350 kHz ultrasound frequency, tone burst duration of 0.5 ms, pulse repetition frequency of 1 kHz, given for 300 msec duration) to excite the motor area of an anesthetized rat transcranially. The successful excitation subsequently elicited the tail movement, which was detected by a motion sensor. The interface was achieved at 94.0±3.0% accuracy, with a time delay of 1.59±1.07 sec from the thought-initiation to the creation of the tail movement. Our results demonstrate the feasibility of a computer-mediated BBI that links central neural functions between two biological entities, which may confer unexplored opportunities in the study of neuroscience with potential implications for therapeutic applications.

Brain-to-computer interface (BCI) refers to the hardware and software environment that detects and translates brain activity to control computers or stored-program architecture devices without involving muscles or the peripheral nervous system. To characterize a specific function of the brain, invasive means such as implantable cortical microelectrode arrays that directly detect the electrical field potentials/spikes from the somatomotor areas have been used, for example, to provide BCI control options for quadriplegic patients. Nicolelis and colleagues explored the method of obtaining the neural electrical signals directly from the motor cortex of primates using an implanted cortical electrode array, and decoded the signals obtained during complex motor intentions, into the appropriate machine control used intracortical recording schemes in monkeys to convert motor cortex neural activity into a correlated mechanized prosthetic arm movement used for self-feeding. Other than these BCI methods which require a surgery to implant electrodes to the brain surface, non-invasive functional imaging modalities such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) have also been adopted in implementation of BCI. For example, non-invasive EEG-based BCI, with the combinatory inclusion of navigation algorithms, was successfully implemented to allow for thought processes to control the direction of a wheelchair movement. Yoo and colleagues used fMRI, with real-time processing capabilities, to provide computer cursor directional commands based on spatial patterns of cortical activity that were linked to predetermined thought processes. This ability was later expanded to the generation of computer keyboard commands via combining spatial activation patterns with different temporal hemodynamic patterns associated with the task onset delays controlled by human subjects. Magneto-encephalography (MEG), near infrared spectroscopy (NIRS), and functional trascranial doppler sonography (fTCD) have also emerged recently as potential candidates for non-invasive BCI.

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