EEG in Cognitive and Affective Neuroscience

Dear Colleagues,

Affective and cognitive neuroscience has a very important role in several applications: computing, security, brain computer interfaces, neurofeedback technology for improving cognitive performance and prevention affective disorders, neurology, and psychology. Affective and cognitive neuroscience mainly focuses on the neural mechanisms of perception, selective attention, memory, language, emotion, self-control, and psychomotor functions. It is at the intersection of psychology and neuroscience but also overlaps with physiological psychology, cognitive psychology, and neuropsychology. Usually, cognitive and affective functions are captured by measuring external personal behavior, facial expressions, eye movements, sweating, heartbeat rate, tremor, hormone level, etc. through different measuring systems.

However, these parameters, though numerous, are not sufficient or cannot explain the whole set of cognitive and affective functions. Moreover, they could be deceived. Imagine what could occur when using a “truth machine".

EEG is a non-invasive technique that can be effectively used for registering the true electrical activity generated by cognitive action and emotions and could be sufficient alone for capturing these brain functions. The proposed Special Issue aims at unambiguously identifying the cognitive and affective functions from EEG signals.

This Special Issue will discuss major aspects of performing research using EEG/ERP-based experiments including the recording of the signals, removing noise, and signal analysis for better understanding the neural correlates of processes involved in cognitive functions and emotions. The use of this methodology will further enhance our understanding of the neural processes involved in cognitive and affective functions.

We welcome contributions on, but not limited to, the following subjects:

• Unbiased elicitation protocols and tasks;
• Brain-bandwidth mapping strategies;
• Design and testing of innovative and efficient signal processing;
• Classification strategies.

Papers should be in the form of original research articles, review articles, technology reports and evaluation and comparison of technologies, case reports, also in a short form.

Dr. Olga M. Bazanova
Guest Editor

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