Independent Component Analysis Applied to Pharmacological Magnetic Resonance Imaging (phMRI): New Insights Into the Functional Networks Underlying Panic Attacks as Induced by CCK-4

Abstract

Pharmacological magnetic resonance imaging (phMRI) is a method to study effects of psychopharmacological agents on neural activation. Changes of the blood oxygen level dependent (BOLD), the basis of functional MRI (fMRI), are typically obtained at relatively high sampling frequencies. This has more recently been exploited in the field of fMRI by applying independent component analysis (ICA), an explorative data analysis method decomposing activation into distinct neural networks. While already successfully used to investigate resting network and task-induced activity, its use in phMRI is new. Further extension of this method to tensorial probabilistic ICA (tensor PICA) allows to group similar brain activation across the anatomical, temporal, subject or session domain. This approach is useful for pharmacological experiments when no pharmacokinetic model exists. We exemplify this method using data from a placebo-controlled cholecystokinine-4 (CCK-4) injection experiment performed on 16 neuropsychiatrically and medically healthy males (age 25.6 +/- 4.2 years). Tensor PICA identified strong increases in activity in 12 networks. Comparison with results gained from the standard approach (voxelwise regression analysis) revealed good reproduction of areas previously associated with CCK-4 action, such as the anterior cingulate, orbitofrontal cortex, cerebellum, temporolateral, left parietal and insular areas, striatum, and precuneus. Several other components such as the dorsal anterior cingulate and medial prefrontal cortex were identified, suggesting higher sensitivity of the method. Exploration of the time courses of each activated network revealed differences, that might be lost when a fixed time course is modeled, e. g. neuronal responses to an acoustic warning signal prior to injection. Comparison of placebo and CCK-4 runs further showed that a proportion of networks are newly elicited by CCK-4 whereas other components are significantly active in the placebo conditions but further enhanced by CCK-4. In conclusion, group ICA is a promising tool for phMRI studies that allows quantifying and visualizing the modulation of neural networks by pharmacological interventions.

In-vivo EEG Changes During A Panic Attack in A Patient With Specific Phobia

“…Reduced delta and increased beta power was positively correlated to increased functional connectivity [14]. We suggest that panic induced changes in functional connectivity patterns as found previously on resting state fMRI [15] in areas as the frontal brain, the temporal and parietal cortex and subcortical regions.…”

Gender-specific abnormalities in the serotonin transporter system in panic disorder

“…Notably, the regions where 5-HTT binding was abnormally increased in males with PD previously have been implicated in the neurobiology of PD by physiological and receptor pharmacological data. For example, the cerebral blood flow and glucose metabolism have been shown to increase in the anterior insula and the ACC during panic attacks induced by a variety of panicogens in healthy volunteers (Benkelfat et al 1995 ;Cameron et al 2000 ;Dieler et al 2008 ;Javanmard et al 1999 ;Schunck et al 2006) and patients with PD (Reiman et al 1989). Moreover, the haemodynamic activity in the insula and the ACC increased during augmentation of the subjective salience of interoceptive stimuli associated with panic and dread (reviewed in Charney & Drevets, 2002) and direct stimulation of the ACC reportedly elicits panic-like response in humans and experimental animals (reviewed in Price et al 1996).…”

Biological markers for anxiety disorders, OCD and PTSD: A consensus statement. Part II: Neurochemistry, neurophysiology and neurocognition

“…The key regions of the fear network, such as basolateral amygdala (Del Boca et al 2012), hypothalamus, periaqueductal grey, or cortical regions such as the anterior cingulate cortex (ACC), seem to be connected by CCK-ergic pathways (Dieler et al 2008). Moreover, these effects seem to be modulated by molecular mechanisms, since neurochemical alterations were dependent on neuropeptide S genotype (Ruland et al 2015).…”