@article {964, title = {Default mode network components and its relationship with anomalous self-experiences in schizophrenia: A rs-fMRI exploratory study}, journal = {Psychiatry Research: Neuroimaging}, volume = {324}, year = {2022}, pages = {111495}, abstract = {

Anomalous self-experiences (ASEs) in schizophrenia have been under research for the last 20 years. However, no neuroimage studies have provided insight of the possible biological underpinning of ASEs. In this novel approach, the connectivity within the default mode network, calculated through a ROI-based analysis of functional magnetic resonance imaging data, was correlated to the ASEs scores assessed by the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) in a sample of 22 schizophrenia patients. The Pearson{\textquoteright}s correlation coefficients between IPASE scores and intrahemispheric connectivity of the parahippocampal gyrus with the isthmus cingulate cortex in both hemispheres, and right parahippocampal gyrus with the right rostral anterior cingulate cortex were positive and significant suggesting a relation between hyperactive functional connectivity and anomalous self-experiences intensity. Prior literature reported these areas to have a role in self-processing and consciousness as well as being anatomically connected. Further research with larger sample size and comparison with controls are needed to confirm the relationship of this connectivity with anomalous self-experiences.

}, keywords = {Anterior cingulate cortex, Metacognition, Parahippocampal gyrus, Psychosis, functional magnetic resonance imaging}, issn = {0925-4927}, doi = {https://doi.org/10.1016/j.pscychresns.2022.111495}, url = {https://www.sciencedirect.com/science/article/pii/S0925492722000567}, author = {Roig-Herrero, Alejandro and {\'A}lvaro Planchuelo-G{\'o}mez and Hern{\'a}ndez-Garc{\'\i}a, Marta and de Luis-Garc{\'\i}a, Rodrigo and Fern{\'a}ndez-Linsenbarth, In{\'e}s and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and Molina, Vicente} } @article {923, title = {Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis}, journal = {Schizophrenia Research}, volume = {229}, year = {2021}, pages = {102-111}, abstract = {

Schizophrenia and bipolar disorder include patients with different characteristics, which may hamper the definition of biomarkers. One of the dimensions with greater heterogeneity among these patients is cognition. Recent studies support the identification of different patients{\textquoteright} subgroups along the cognitive domain using cluster analysis. Our aim was to validate clusters defined on the basis of patients{\textquoteright} cognitive status and to assess its relation with demographic, clinical and biological measurements. We hypothesized that subgroups characterized by different cognitive profiles would show differences in an array of biological data. Cognitive data from 198 patients (127 with chronic schizophrenia, 42 first episodes of schizophrenia and 29 bipolar patients) were analyzed by a K-means cluster approach and were compared on several clinical and biological variables. We also included 155 healthy controls for further comparisons. A two-cluster solution was selected, including a severely impaired group and a moderately impaired group. The severely impaired group was associated with higher illness duration and symptoms scores, lower thalamus and hippocampus volume, lower frontal connectivity and basal hypersynchrony in comparison to controls and the moderately impaired group. Moreover, both patients{\textquoteright} groups showed lower cortical thickness and smaller functional connectivity modulation than healthy controls. This study supports the existence of different cognitive subgroups within the psychoses with different neurobiological underpinnings.

}, keywords = {Cognition, Connectivity, Modulation, Volume, bipolar disorder, schizophrenia}, issn = {0920-9964}, doi = {https://doi.org/10.1016/j.schres.2020.11.013}, url = {https://www.sciencedirect.com/science/article/pii/S0920996420305521}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and D{\'\i}ez, {\'A}lvaro and Arjona-Valladares, Antonio and Rodrigo de Luis-Garc{\'\i}a and Mart{\'\i}n-Santiago, {\'O}scar and Benito-S{\'a}nchez, Jos{\'e} Antonio and P{\'e}rez-Laureano, {\'A}ngela and Gonz{\'a}lez-Parra, David and Montes-Gonzalo, Carmen and Melero-Lerma, Raquel and Fern{\'a}ndez Morante, Sonia and Sanz-Fuentenebro, Javier and G{\'o}mez-Pilar, Javier and N{\'u}{\~n}ez-Novo, Pablo and Molina, Vicente} } @article {953, title = {Search for schizophrenia and bipolar biotypes using functional network properties}, journal = {Brain and Behavior}, volume = {11}, year = {2021}, pages = {e2415}, abstract = {

Introduction: Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements.

Methods: A clustering analysis was performed using the electroencephalogram-based network parameters derived from graph-theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons.

Results: We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path-length, and lower small-world index compared to controls. The modulation of clustering coefficient and path-length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients{\textasciiacute} clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation.

Conclusion: These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.

}, keywords = {Biotypes, bipolar disorder, diffusion, electroencephalogram, network, schizophrenia}, doi = {https://doi.org/10.1002/brb3.2415}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/brb3.2415}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and D{\'\i}ez, Alvaro and Arjona, Antonio and P{\'e}rez, Adela and Rodr{\'\i}guez-Lorenzana, Alberto and del Valle, Pilar and de Luis-Garc{\'\i}a, Rodrigo and Mascialino, Guido and Holgado-Madera, Pedro and Segarra-Echevarr{\'\i}a, Rafael and Gomez-Pilar, Javier and N{\'u}{\~n}ez, Pablo and Bote-Boneaechea, Berta and Zambrana-G{\'o}mez, Antonio and Roig-Herrero, Alejandro and Molina, Vicente} }