Exploring the impact of multisensory integration and episodic memory with machine learning: a proof-of-concept study in anorexia nervosa

In addition to established body image alterations, abnormal perception and executive functioning in anorexia nervosa (AN), neurocognitive factors including multisensory integration (MSI) and episodic memory (EM) might play a pivotal role in the diagnosis of this disorder. According to the allocentric lock theory, deficits in the updating of distorted memory of body-based episodes through misleading real-time multisensory bodily stimuli could lead to altered body image in AN. In this study, 25 healthy females and nine AN individuals were tested on a set of neurocognitive measures, encompassing unimodal perceptual accuracy and MSI (MSI) ability assessed with the sound-induced flash illusion (SiFI), episodic memory recognition (EMR) evaluated with a remember/know (R/K) task, memory and executive functions tested with the RBMT-3 and the Stroop task. Collected data were analyzed with Bayesian statistics and machine learning algorithms. In the SiFI task, we found that AN compared to control group had lower discrimination accuracy for unimodal visual and auditory stimuli, for bimodal (visual and auditory) stimuli and disrupted MSI ability. Further, we found on the EMR task and the RBMT-3 that AN individuals had higher proportions of false memories than healthy females. Additionally, we found lower inhibition at the Stroop task for the patient group compared to controls. The importance of the considered neurocognitive measures was confirmed by a machine learning feasibility analysis, which showed that SiFI, RBMT-3, Stroop and EMR had more weight than classic eating disorder risk scales of the EDI-3 when computing classification between the AN and control individuals. In conclusion, MSI along with memory could be crucial factors for improving diagnosis and consequently design innovative therapeutic solutions that tap critical bodily and cognitive elements altered in AN with new technologies such as virtual reality.