by Al Gourrier Jr., Neuroscience & Psychology Major, Class of 2019
My blog post is an annotated bibliography about various cognitive neuroscience methods to study the adolescent brain and how efficiency is not a sufficient concept in explaining activation differences of these neuroimaging measures. I chose this topic so that I could inform the general public about these neuroimaging methods.
Article
Name:
Neuroimaging: just a collection of
brain image files?
APA Citation: Seixas,
D., & Ayres Basto, M. (2009). Neuroimaging: just a collection of brain image files?. Frontiers
in human neuroscience, 3, 47.
Summary
MRI
and fMRI are two of the most common neuroimaging techniques that we use today
for clinical and research purposes. The “protection of human subjects”,
participants and patients alike, is essential (Seixas & Ayres, 2009). Thus, this concern for
protection leads to many necessary precautionary steps taken before the
administration of one of these neuroimaging tools. For instance, metal
screening is expected for magnet safety. Human safety is a must. However, it
shouldn’t be the only issue explored with these techniques. Seixas and Ayres explore the many
issues that go unexplored with these techniques. Specifically, they explore issues
such as: informed consent, incidental findings, image use, confidentiality,
vulnerable groups, and expectations and motivations of participants (Seixas & Ayres, 2009).
Informed consent, confidentiality and privacy
are expected within clinical and research purposes for the protection of the subject/volunteer
and the institution. Incidental findings, however, are more common than most
people think, and the probability/unlikelihood of these findings should be
stated within the informed consent so that people are aware under all
circumstances. Furthermore, computerized systems that randomly utilize medical
images should not be given the green light without informed consent. Vulnerable
groups are another issue of concern due to safety risks and their inability to
provide informed consent at times. Finally, the expectations and motivations of
participants are an issue to ponder because the findings could be
systematically different (or at least interestingly interpreted) if the
expectations/motivations lead to a specific type of person to volunteer.
Figure 1: MRI diagnostic imaging. https://www.aboutkidshealth.ca/Article?contentid=1334&language=English
Article
Name:
Is “efficiency” a useful concept
in cognitive neuroscience?
APA
Citation: Poldrack,
R. A. (2015). Is “efficiency” a useful concept in cognitive
neuroscience?. Developmental cognitive neuroscience, 11,
12-17.
Summary
Scientific
research, especially neuroscience, strive to find “mechanistic explanations of
natural phenomena (Poldrack, 2015).”
This type of explanation can be described as reductive materialism.
Nonetheless, cognitive neuroscience investigates a plethora of problems with
this point of view even though a very small number of theories in cognitive
neuroscience possess “simple explanatory power” (Poldrack, 2015). Poldrack argues that “efficiency” is not a
sufficient concept in explaining activation differences. Instead, “efficiency”
is simply restating differential activation without providing any explanation,
reason, or additional information (according to Poldrack).
Poldrack proposes that neuronal computation and
energetics, network communication, and task performance explain action
differences, which is something “efficiency” as a concept cannot do for
differential activation. Neural computation, according to Poldrack, often
influence task performance through changes in development (e.g. childhood to
adolescence) and learning. For instance, prior experiences and learned
abilities via exposure increases task performance. Thus, past experiences
rather than universal task instructions affect performance and dictate which
condition performs well. This leads to a misinterpretation and mislabeling of a
particular group as “efficient”, when in reality the groups were being tested
on two different things. Furthermore, biophysical changes, such as neuronal
structure and synaptic signaling (form of network communication), influence
energy usage. Equivalent neuronal firing patterns, for instance, can result in
“differential amounts of energy” due to offset neuronal signaling, which
includes action potentials, synaptic processes, and resting potentials
(Poldrack, 2015).
Article
Name:
Early identity recognition of
familiar faces is not dependent on holistic processing.
Summary
Electroencephalography
(EEG) is a noninvasive neuroimaging measure that uses electrodes attached to
the scalp to detect electrical activity in the cortex through measuring
excitatory post-synaptic potentials from a population of neurons (Luck
& Kappenman, 2011). An EEG measure provides time-locked Event Related
Potentials (ERPs) as a direct result to a stimulus onset. The N250r is a
well-known ERP component systematically associated with functional aspects of
facial identity processing. Specifically, the N250r is a negative deflection,
at ~250 milliseconds (ms) post-stimulus, that measures repetition priming.
In
the current study, Mohr, Wang, and
Engell investigate whether isolated facial features, specifically the
eyes, facilitate N250r activation in the recognition of familiar faces. The methodological paradigm was a 2
(prime, unprimed) x 2 (whole face, isolated eyes) x 2 (isolated eyes prime,
isolated eyes target) design. The participants viewed a grey fixation screen
for 500 ms, a prime image (e.g. whole face or isolated eyes) for 500 ms, and
then a grey screen with a green dot in the center for 500 ms. The participant
then viewed the target image (e.g. prime-same, prime-different) for 500 ms
before a grey screen was displayed for an 1800 ms interstimulus interval. The
participants were instructed to press the spacebar when they observed a
prime-target change of identity (e.g. prime image of Owen Wilson and target
image of Michael Jackson). Mohr et al.’s findings suggest that familiar
face recognition can be elicited by feature-based processing, such as the eyes,
and the recognition of familiar faces is not dependent on holistic processing.
Figure 2: Image of myself with an EEG electrode cap.
References
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