Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …

Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

In this chapter, we explore Support Vector Machine (SVM)—a machine learning method that
has become exceedingly popular for neuroimaging analysis in recent years. Because of …

Synapse density is reduced in postmortem cortical tissue from schizophrenia patients, which
is suggestive of increased synapse elimination. Using a reprogrammed in vitro model of …

Both the discovery of biomarkers of schizophrenia and the verification of biological
hypotheses of schizophrenia are an essential part of the process of understanding the …

Schizophrenia is associated with increased levels of oxidative stress, as reflected by an
increase in the concentrations of damaging reactive species and a reduction in anti-oxidant …

Schizophrenia and major depression disorders, both being of pathological synaptogenesis,
are the most common psychiatric disorders worldwide. These diseases, if not treated …

Schizophrenia is a debilitating disease that presents with both positive and negative
symptoms affecting cognition and emotions. Extensive studies have analyzed the different …

Neuroscience is advancing standardization and tool development to support rigor and
transparency. Consequently, data pipeline complexity has increased, hindering FAIR …

This work provides an overview of the most consistent alterations in bipolar disorder (BD),
attempting to unify them in an internally coherent working model of the pathophysiology of …