Analysis of EEG data from hypnotized individuals

I con­duc­ted an in-depth inves­ti­ga­ti­on of a new­ly coll­ec­ted EEG data­set to explo­re whe­ther mea­sura­ble dif­fe­ren­ces exist bet­ween indi­vi­du­als with high and low hyp­no­tiza­bi­li­ty. The stu­dy focu­sed on two key aspects: spec­tral power and func­tion­al brain con­nec­ti­vi­ty.

After an exten­si­ve lite­ra­tu­re review and the appli­ca­ti­on of advan­ced sta­tis­ti­cal methods, I found that spec­tral power alo­ne does not ser­ve as a relia­ble indi­ca­tor of hyp­no­tic sus­cep­ti­bi­li­ty. Howe­ver, distinct pat­terns of increased func­tion­al con­nec­ti­vi­ty bet­ween spe­ci­fic brain regi­ons were obser­ved in high­ly hyp­no­tizable indi­vi­du­als — a result that remain­ed sta­tis­ti­cal­ly signi­fi­cant even after Bon­fer­ro­ni cor­rec­tion.

The­se fin­dings sug­gest that the neu­ral basis of hyp­no­tiza­bi­li­ty may lie less in loca­li­zed acti­vi­ty and more in the inte­gra­ti­on and com­mu­ni­ca­ti­on bet­ween brain net­works.

My tasks were:

• Data extra­c­tion using Python
• Lear­ning signal pro­ces­sing from scratch
• Cal­cu­la­ti­on of key figu­res
• Sel­ec­tion and appli­ca­ti­on of sta­tis­ti­cal methods
• For­mu­la­ti­on and illus­tra­ti­on of the results in the form of a master’s the­sis
• For­mu­la­ti­on and illus­tra­ti­on of the results in the form of a sci­en­ti­fic artic­le