scholarly journals Divergence of fMRI and neural signals in V1 during perceptual suppression in the awake monkey

2008 ◽  
Vol 11 (10) ◽  
pp. 1193-1200 ◽  
Author(s):  
Alexander Maier ◽  
Melanie Wilke ◽  
Christopher Aura ◽  
Charles Zhu ◽  
Frank Q Ye ◽  
...  
Keyword(s):  
Neural Signals ◽  
Awake Monkey

Dissociated neural signals of conflict and surprise in effortful decision Making: Theta activity reflects surprise while alpha and beta activity reflect conflict

2021 ◽  
Vol 155 ◽  
pp. 107793
Author(s):  
Chad C. Williams ◽  
Thomas D. Ferguson ◽  
Cameron D. Hassall ◽  
Bruce Wright ◽  
Olave E. Krigolson
Keyword(s):  
Decision Making ◽  
Theta Activity ◽  
Beta Activity ◽  
Neural Signals

scholarly journals Ear-Bot: Locust Ear-on-a-Chip Bio-Hybrid Platform

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 228
Author(s):  
Idan Fishel ◽  
Yoni Amit ◽  
Neta Shvil ◽  
Anton Sheinin ◽  
Amir Ayali ◽  
...  
Keyword(s):  
Proof Of Concept ◽  
Robotic Platform ◽  
Neural Signals ◽  
Technological Approach ◽  
Hybrid Platform ◽  
And Control ◽  
Robust Sensing ◽  
Robotic Sensing ◽  
Sound Pulses

During hundreds of millions of years of evolution, insects have evolved some of the most efficient and robust sensing organs, often far more sensitive than their man-made equivalents. In this study, we demonstrate a hybrid bio-technological approach, integrating a locust tympanic ear with a robotic platform. Using an Ear-on-a-Chip method, we manage to create a long-lasting miniature sensory device that operates as part of a bio-hybrid robot. The neural signals recorded from the ear in response to sound pulses, are processed and used to control the robot’s motion. This work is a proof of concept, demonstrating the use of biological ears for robotic sensing and control.

scholarly journals Effortless Retaliation: the Neural Dynamics of Interpersonal Intentions in a Chicken Game Using Brain-Computer Interface

2021 ◽  
Author(s):  
Yiwen Wang ◽  
Yuxiao Lin ◽  
Chao Fu ◽  
Zhihua Huang ◽  
Rongjun Yu ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Computer Interface ◽  
Neural Mechanisms ◽  
Computer Interface ◽  
Neural Dynamics ◽  
Neural Signals ◽  
Chicken Game ◽  
Common Response ◽  
Tit For Tat ◽  
Novel Method

Abstract The desire for retaliation is a common response across a majority of human societies. However, the neural mechanisms underlying aggression and retaliation remain unclear. Previous studies on social intentions are confounded by low-level response related brain activity. Using an EEG-based brain-computer interface (BCI) combined with the Chicken Game, our study examined the neural dynamics of aggression and retaliation after controlling for nonessential response related neural signals. Our results show that aggression is associated with reduced alpha event-related desynchronization (ERD), indicating reduced mental effort. Moreover, retaliation and tit-for-tat strategy use are also linked with smaller alpha-ERD. Our study provides a novel method to minimize motor confounds and demonstrates that choosing aggression and retaliation is less effortful in social conflicts.

scholarly journals Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications

2016 ◽  
Vol 24 (9) ◽  
pp. 993-1002 ◽  
Author(s):  
Danilo Pani ◽  
Gianluca Barabino ◽  
Luca Citi ◽  
Paolo Meloni ◽  
Stanisa Raspopovic ◽  
...  
Keyword(s):  
Real Time ◽  
Neural Signals ◽  
Dsp Processors
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