Neural Correlates: EMOTION

Gyrus (Gyri) – Ridge(s)
Sulcus (Sulci) – Groove(s)

Emotions are real physically as much as psychologically. How does the brain produce or process emotion? One may want to turn to academic, or scholarly, articles for an answer.  {As an aside, in choosing sources, the rule stands that the more recent the work – the better; unless, of course, it’s a classic. Most place the time limit around 10-20 years.}

To get back on track, the present [very!] short essay briefly discusses neural correlates of emotion. Cerebral mapping, enabling localization of function, can discover these clusters. However, the brain is very active, so the baseline activity must be deducted from the activation during exposure to particular stimuli. The mechanism is called the subtraction method. For the purpose of establishing cerebral correlates of human emotion, the most common stimulus type used is facial expressions. Popular neuroimaging techniques include [PET, CAT, MRI and fMRI]*. Other methods supplying neuroscientific insight include electrophysiology, lesion studies and TMS.

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In a contemporary contribution to science, Vytal & Hamann (2010) combine two research methods to compose their work: a literature review and a statistical technique (meta-analysis). The authors explore basic emotion theory (fear, anger, sadness, happiness, and disgust) and corresponding consistent findings of reliable neural correlates. Nonetheless, some doubt remains in the community.

In their meta-analysis, Kober & Wager (2010) insist that the amygdala, [usually regarded as fundamental in feeling, and reacting to, fear] is not critical for the experience of emotion, but for its perception. The authors maintain that the subcortical structure gets involved when visual stimuli may convey consequential information through emotional display.

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Li et al. (2010) confirm that the parahippocampal gyrus/amygdala becomes activated bilaterally during emotion perception. In their publication, the fusiform gyrus (known for facial recognition) is also active because subjects are trying to process facial expressions of affective states. Further, the relationship extends to the area, together with the right superior frontal gyrus and lentiform nucleus. According to their meta-analytic review of a compilation of neuroimaging studies, patients with schizophrenia appear to have difficulty with the task. The researchers suggest that perhaps this structural dysfunction causes the impaired affect understanding associated with the illness.

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On a final note, all three sources mentioned agree to at times disagree. Thus, in assessing limitations of scientific reports, one must realize that findings are seldom perfectly consistent. Still, validity, replicability and generalizability of effects are conditions for a theory to be supported and accepted.

*Some ABBREVIATIONS commonly used in the field:

ALE – Activation Likelihood Estimation
CAT – Computerized Axial Tomography
CIM –Contrast Indicator Map
CM – Contrast Map
FDR – False Discovery Rate
(f)MRI – (functional) Magnetic Resonance Imaging
FWER – FamilyWise Error Rate
FWHM – Full-Width Half-Maximum
(M)KDA – (Multilevel) Kernel Density Analysis
PET – Positron Emission Tomography
TMS – Transcranial Magnetic Stimulation

References:

  • Kober, H. & Wager, T. D. (2010). WIREs Cognitive Science, 1 (March/April): 293-300.
  • Li, H., Chan, R. C. K., 5, McAlonan, G. M. & Gong, QY. (2010). Facial emotion processing in schizophrenia: A meta-analysis of functional neuroimaging data. Schizophrenia Bulletin, 36 (5): 1029-39.
  • Vytal, K. & S. Hamann, S. (2010). Neuroimaging support for discrete neural correlates of basic emotions: A voxel-based meta-analysis. Journal of Cognitive Neuroscience, 22 (12): 2864-85.

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