2026 ECNP Congress

PS04-4175

Altered perturbational cortical complexity across cognitive biotypes in psychosis and bipolar disorder: a transcranial magnetic stimulation electroencephalography study

Emma Osorio-Iriarte — Á. Díez, I. Fernandez-Liinsenbarth, A. Arjona-Valladares, R. Beño-Ruiz-de-la-Sierra, A. Roig-Herrero, V. Molina · Universidad de Valladolid, Dpto. Pediatría e Inmunología- Obstetricia y Ginecología- Nutrición y Bromatología- Psiquiatría e Historia de la Ciencia, Valladolid, Spain

2026 ECNP Congress

Psychotic disorders, including schizophrenia and bipolar disorder, are highly heterogeneous conditions characterised by marked variability in symptoms, cognition, functional outcome, and underlying neurobiology. This heterogeneity has hindered the identification of reliable biomarkers capable of distinguishing clinically meaningful subgroups and guiding personalised treatment approaches. Cognitive dysfunction represents one of the most consistent transdiagnostic dimensions across the psychosis spectrum and has been proposed as a useful framework for biologically informed stratification [1,2]. In particular, impairments in executive function, attention, and working memory have been consistently associated with poor functional outcomes. The perturbational complexity index (PCI), derived from transcranial magnetic stimulation combined with electroencephalography (TMS-EEG), quantifies the brain’s capacity to generate integrated and differentiated responses following direct cortical perturbation, providing a systems-level measure of cortical information processing that is independent of task performance [3]. The present study aimed to investigate whether cognitively defined subgroups of patients differ in cortical complexity and how these differences compare with those observed in healthy individuals.

TMS-EEG was recorded in individuals diagnosed with schizophrenia and bipolar disorder, together with a healthy control group. All participants underwent standardised clinical and neuropsychological assessments prior to neurophysiological recording. Based on previously validated neuropsychological clustering procedures [2], patients were stratified into two cognitive subgroups: Cluster 1 (N=11; more severely impaired) and Cluster 2 (N=35; moderately impaired). A healthy control group (N=18) was included for comparison. Single-pulse TMS was delivered over the left dorsolateral prefrontal cortex, a region critically involved in executive functioning and consistently implicated in psychosis-spectrum disorders. Stimulation parameters were kept constant across participants to ensure comparability. TMS-evoked electroencephalographic responses were quantified using the perturbational complexity index-state transitions (PCI-ST), an optimised and computationally efficient measure of spatiotemporal cortical complexity [4]. Group differences in PCI values were examined using the Kruskal–Wallis test, followed by Bonferroni-corrected pairwise comparisons.

Significant group differences in cortical complexity were observed (Kruskal–Wallis H(2)=19.80, p<.001). Cluster 1 showed the lowest PCI values (mean=6.46, SD=1.98), indicating the greatest reduction in perturbational complexity. Cluster 2 displayed intermediate values (mean=8.65, SD=2.25), whereas healthy controls exhibited the highest scores (mean=11.71, SD=4.32). Pairwise comparisons demonstrated significantly higher PCI values in controls compared with Cluster 1 (p<.001) and Cluster 2 (p=.022), as well as higher values in Cluster 2 relative to Cluster 1 (p=.025). This stepwise pattern suggests that increasing cognitive impairment is associated with reduced cortical complexity across groups.

These findings indicate that alterations in cortical integration and differentiation vary across cognitive subgroups within the psychosis spectrum rather than being uniformly distributed. Reduced PCI in the severely impaired subgroup may reflect diminished capacity for flexible information processing, disrupted large-scale network coordination, or greater illness burden [3,5]. Overall, the results support the relevance of stratifying psychotic disorders using cognitive and neurophysiological dimensions rather than relying solely on categorical diagnoses. Such an approach may contribute to improved biomarker development, better prognostic stratification, and more precise characterisation of clinical heterogeneity. Future studies should examine the longitudinal stability of PCI alterations and their association with treatment response, illness progression, and clinical outcomes.

References

  1. Clementz, B.A., Sweeney, J.A., Hamm, J.P., Ivleva, E.I., Ethridge, L.E., Pearlson, G.D., et al., 2016. Identification of distinct psychosis biotypes using brain-based biomarkers. Am. J. Psychiatry 173, 373–384.
  2. Fernández-Linsenbarth, I., et al., 2021. Cognitive subtypes in psychosis identified through clustering analysis: clinical and neurobiological correlates. Psychiatry Res. 302, 114012.
  3. Casali, A.G., Gosseries, O., Rosanova, M., Boly, M., Sarasso, S., Casali, K.R., et al., 2013. A theoretically based index of consciousness independent of sensory processing and behaviour. Sci. Transl. Med. 5, 198ra105.
  4. Molina, V., et al., 2025. Perturbational cortical complexity in psychosis: a TMS-EEG study of large-scale brain dynamics. Brain Stimul. 18.
  5. Van Os, J., Kapur, S., 2009. Schizophrenia. Lancet 374, 635–645.