AMS Colloquium: Network Coupling, Dynamics and Emotional Responses

As one might imagine, the workings of the human brain are an extremely complex subject, and while a great deal has been discovered in this field over the years, there is still much more that remains a mystery. As part of her current research, Professor Anca Radulescu of the Applied Math department at CU-Boulder is part of an exploratory study on the brain’s network-like organization and interactions within that network. At this semester’s final AMS department colloquium, she provided some brief insight into this research in her presentation, “Network Coupling, Dynamics and Emotional Responses.”

What Radulescu and her colleagues were hoping to determine from this study was whether or not a person’s emotional imbalances were due to the circuitry in their prefrontal lobe, particularly the underperformance of regulatory modules within the prefrontal cortex. To test this hypothesis, human subjects with varying emotional responses (from no conditions to documented schizophrenics) were exposed to different visual stimuli and empirical data collected was of a time series via non-invasive imaging techniques such as fMRI. While subjects were exposed to the stimuli, these imaging techniques monitored and recorded signals sent across certain areas of the brain. These recordings were then converted to usable data and sorted by whether the signals were purely random “white” noise versus “pink-“or “brown-colored” noise (emissions that seem to have a preferred temporal scale) through the use of the signals’ Fourier spectra.

Upon analyzing the data and sorting the data into categories by subject (low response to stimuli, high response to stimuli, low anxiety over stimuli, and high anxiety over stimuli), the results were rather interesting. Due to the highest levels of noise being transmitted to the amygdala, or excitatory, arousal nodes, the high response group also had among the highest releases from the BA45 (Brodmann area 45, an inhibitory/extinction module found in the frontal cortex), which was to be expected. However, the high anxiety class received the smallest levels of noise to the amygdala in the study, yet also received the absolute highest levels of release from the BA45. It would make sense that the highest levels of inhibitors combined with the lowest levels of exciters would result in very low responsiveness rather than high anxiety, but as the data suggests it is actually the opposite.

Trying to make sense of this, Radulescu proposed a basic theory that high anxiety levels result from weakened inhibitory devices in the prefrontal lobe, making even the slightest noise within the system difficult to extinguish. Using the data as a starting point, Radulescu has developed a simple model of the situation, and, at this point, it does a decent job of mapping out the basic workings of this system. However, she admits that the model is still very rough and in need of some editing and that, for the time being, this basic understanding of the situation will have to do. As part of her future research, she plans on working out the issues with the model and hopes to produce and even more accurate description of the brain’s networking structure.