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Cognitive Related Neural Patterns to Activate Machines

Summary: A new study reveals a functional brain pattern linked to cognition, and with the help of a BMI, used it to activate an iPad’s touch screen.

Source: UAB Barcelona.

Brain-machine interfaces represent a solution for people with physical difficulties to communicate with their physical and social environment. In this work, researchers have identified a functional brain pattern in the prefrontal cortex, associated with cognitive processes, and have used it to activate a screen on a touch device (an iPad touchscreen).

The use of the neural cortical activity for operant conditioning tasks has existed for decades. In this case, however, a device patented by researchers has been used. This device allows the activation of any environmental instrument through specific electrical brain signals selected at will. In this research, authors worked with electrical brain signals that allowed the activation of the presentation of visual stimuli in the iPad’s touchscreen. At the same time, experimental animals had to touch those stimuli presented on the iPad to obtain a reward and, thus, properly complete the task.

One of the most interesting results of this research is that rats learned to increase the frequency of the selected neural pattern throughout successive experimental sessions, with the aim of obtaining the reward. Authors also prove that the selected pattern is connected to cognitive processes and not to motor or behavioral activity, which represents an important progress in the design of brain-machine interfaces. Another result of interest is that the selected brain pattern did not modify its functional properties after being used to activate the associative learning. Therefore, the prefrontal cortex (a brain area particularly connected to mental processes and states) has the ability to produce an oscillatory pattern that rats can generate to control their environment.

Image shows a rat.

A rat touches a touch stimulus that has appeared in an iPad screen. The visual stimulus has been created by a cognitive brain pattern generated by the rat. NeuroscienceNews.com image is credited to Neuroscience Division (UPO) and Neuro-Com (UAB).

From the point of view of the research, it is beneficial to use the conclusions of this work to advance in the area of brain-machine interactions.

About this neuroscience research article

Source: UAB Barcelona
Image Source: NeuroscienceNews.com image is credited to Neuroscience Division (UPO) and Neuro-Com (UAB).
Original Research: Abstract for “A cognition-related neural oscillation pattern, generated in the prelimbic cortex, can control operant learning in rats” by Samuel Hernández-González, Celia Andreu-Sánchez, Miguel Ángel Martín-Pascual, Agnès Gruart and José María Delgado-García in Journal of Neuroscience. Published online May 25 2017 doi:10.1523/JNEUROSCI.3651-16.2017

Cite This NeuroscienceNews.com Article
UAB Barcelona “Cognitive Related Neural Patterns to Activate Machines.” NeuroscienceNews. NeuroscienceNews, 14 June 2017.
<http://neurosciencenews.com/neural-patters-machines-6906/>.
UAB Barcelona (2017, June 14). Cognitive Related Neural Patterns to Activate Machines. NeuroscienceNew. Retrieved June 14, 2017 from http://neurosciencenews.com/neural-patters-machines-6906/
UAB Barcelona “Cognitive Related Neural Patterns to Activate Machines.” http://neurosciencenews.com/neural-patters-machines-6906/ (accessed June 14, 2017).

Abstract

A cognition-related neural oscillation pattern, generated in the prelimbic cortex, can control operant learning in rats

The prelimbic (PrL) cortex constitutes one of the highest levels of cortical hierarchy dedicated to the execution of adaptive behaviors. We have identified a specific local field potential (LFP) pattern generated in the PrL cortex, associated with cognition-related behaviors, and used it to trigger the activation of a visual display on a touch screen as part of an operant conditioning task. Rats learned to increase the presentation rate of the selected theta/beta-gamma transition pattern across training sessions. The selected LFP pattern appeared in coincidence with a significant decrease in the firing of PrL pyramidal neurons and did not seem to propagate to other cortical or subcortical areas. An indication of its cognitive nature is that the experimental disruption of this theta/beta-gamma transition pattern prevented the proper performance of the acquired task without affecting the generation of other motor responses. The use of this LFP pattern to trigger an operant task evoked only minor changes in its electrophysiological properties. Thus, the PrL cortex has the capability of generating an oscillatory pattern able to be used to deal with environmental constraints. In addition, the selected theta/beta-gamma transition pattern could be a useful tool to activate the presentation of external cues or to modify the current circumstances.

SIGNIFICANCE STATEMENT

Brain-machine interfaces represent a solution for physically-impaired people to communicate with external devices. We have identified a specific local field potential pattern generated in the prelimbic cortex, associated with goal-directed behaviors, and used it to trigger the activation of a visual display on a touch screen as part of an operant conditioning task. Rats learned to increase the presentation rate of the selected field potential pattern across training. The selected pattern was not modified when used to activate the touch screen. Electrical stimulation of the recording site prevented the proper performance of the task. Our findings show that the prelimbic cortex has the capability of generating oscillatory patterns that rats can use to control their environment for achieving specific goals.

“A cognition-related neural oscillation pattern, generated in the prelimbic cortex, can control operant learning in rats” by Samuel Hernández-González, Celia Andreu-Sánchez, Miguel Ángel Martín-Pascual, Agnès Gruart and José María Delgado-García in Journal of Neuroscience. Published online May 25 2017 doi:10.1523/JNEUROSCI.3651-16.2017

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