A risk variant for alcoholism in the NMDA receptor affects amygdala activity during fear conditioning in humans

Neural Mechanism of a Sex-Specific Risk Variant for Posttraumatic Stress Disorder in the Type I Receptor of the Pituitary Adenylate Cyclase Activating Polypeptide

“…This finding is well in line with earlier work from our group on this paradigm, where the strongest hippocampal activation was observed during this phase (12). During cued fear conditioning, participants learn to differentiate CS1/CS2 already during early acquisition (23), most probably owing to the fact that US onset is unpredictable in a context conditioning paradigm compared with a cue conditioning paradigm. Our data suggest that PAC1-R plays a role in the acquisition of fear rather than extinction learning; this might be related to the observation that not "pure" hippocampal activations, but hippocampalprefrontal interactions, are important for contextual extinction (34).…”

“…Also, the stimulus generator has a special certification within the boundaries of the law for medical products for medical use with very high safety standards. The procedure has been used in earlier work from our laboratory (12,23,24).…”

Oxytocin differentially modulates pavlovian cue and context fear acquisition

“…For both, cue and context conditioning, we used the design from our previous studies (Lang et al , 2009; Pohlack et al , 2012; Cacciaglia et al , 2013, 2015), as these produced reliable and valid responses. Such a reference is needed and important when performing a manipulation of effects as it is done with pharmacological interventions.…”

Learned desires

“…Responses were discarded and replaced by the overall individual mean when they were directly preceded by the participant sighing, talking, or moving, or when no responses were recorded due to technical issues (1.34 % of all responses; ambiguous CS+ 1.22 %; CS-0.61 %; non-ambiguous CS+ 1.83 % ; CS-1.70 %) (Weike, Schupp, & Hamm, 2007). The data were rangecorrected by dividing each skin conductance score by the participant's individual maximal conditioned response (e.g., Cacciaglia et al, 2013), and normalized using a square root transformation.…”

“…CDA uses deconvolution to decompose the skin conductance data into its tonic and phasic components, resulting in phasic activity with a zero baseline. CDA is especially advantageous for analysis of overlapping skin conductance responses (i.e., superposition effects), and has been used before for analyzing (fear) conditioning data (e.g., Baeuchl, Meyer, Hoppstädter, Diener, & Flor, 2015;Cacciaglia et al, 2013). The sum of the amplitudes of all skin conductance responses with onsets within a time window was used as dependent variable (AmpSum).…”