https://doi.org/
Clinical EEG and Neuroscience
1–7
© EEG and Clinical Neuroscience
Society (ECNS) 2020
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DOI: 10.1177/1550059420916636
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Special Issue: Update on QEEG and NeuroBiofeedback
Introduction
The practice of mental health can benefit from brain-based
models of emotional responses in a format that exposes an
understanding of decision-making pathways.
1,2
There is a need
for models that can be used by counselors and other mental
health professionals with or without the use of extra physiologi-
cal monitoring or biofeedback equipment. The creation of such
a model must make use of scientific methods and processes that
reveal brain activity related to thoughts, feelings, and behaviors,
in a global context.
From a neurological perspective, the brain is a pattern-rec-
ognition and decision-making machine that is tailored to oper-
ate in the body of a human. Even though it is a part of the
human body, it has its own goals and its own means of seeking
those goals. Whereas an individual may have goals that include
safety, nourishment, comfort, social interactions, and other
high-level goals, the brain itself has a much simpler scope. The
brain’s goals are better understood in terms of the mechanics of
recognizing patterns, detecting danger, considering options,
determining the safety of various options, and, finally, control-
ling the motor functions that allow the organism to operate in
its environment.
Neuroscience provides a unique perspective on human
behavior and mental health. By understanding the underpin-
nings of the brain’s roles and priorities, we can better under-
stand why an individual would think, feel, and act in a certain
way. The individual may believe that he or she is in control of
their life, making their own decisions and setting their own pri-
orities. But the fact that everyone is dependent on a properly
functioning brain for this to happen means that what we think
is going on may be far from the facts.
We approached this problem from a conceptually high level.
Given that we have tools that rely on self-report, which we
have extensively analyzed using traditional statistical proto-
cols, how can we produce corroborating measures that do not
rely on the subject’s own perception and ultimate reporting?
We are concerned with the fundamental problem of the reli-
ability and veracity of self-report, given the myriad of compli-
cating factors and hidden agendas that mediate internal
awareness as well as the willingness or ability to disclose.
Establishing the Ground Work for the
Role of Emotions in Decisions
In his book, Descartes’ Error; Emotions, Reasons, and the
Human Brain, Antonio Damasio
2,3
describes his study of people
with brain damage to parts of the brain where emotions are
1
Target Training International, Scottsdale, AZ, USA
2
Brain Enrichment Center, Bedford, OH, USA
Corresponding Author:
Ronald J. Bonnstetter, Target Training International, 17785 North Pacesetter
Way, Scottsdale, AZ 85255, USA.
Email: ron@ttisi.com
Brain Activation Imaging in Emotional
Decision Making and Mental Health: A
Review—Part 1
Ronald J. Bonnstetter
1
and Thomas F. Collura
2
Abstract
In part 1 of this article, we describe an approach and methodology that bridges 2 worlds: the internal, subjective experience of
emotions and thoughts, and the external world of brain electrical activity. Using a novel event-related brain activation imaging
method, we demonstrate that within single trials, short-term mental processes, on the order of 100 ms, can be clearly related
to observed brain activation in controlled experiments. We use an ipsative assessment validation process that combines self-
report with real-time EEG recordings to provide a combined picture of both the mental and the brain activity, during short-term
reactions, emotions, and decisions regarding controlled information. Part 2 provides a detailed description of the emerging
emotional decision-making model.
Keywords
EEG electroencephalograph, electromagnetic tomographic analysis, gamma asymmetry, response process validity, sLORETA,
approach-avoidance, decision making, mental health, human performance
Received May 29, 2019; revised February 28, 2020; accepted March 6, 2020.