Neurocomputational Models of Schizophrenia

Schizophrenia is a complex neurodevelopmental disorder with relatively stable prevalence rates estimated at about 0.5% (Saha, Chant, Welham, & McGrath, 2005). Schizophrenia is characterized by co-occurrence of multiple psychopathological symptoms that have been conceptualized as positive symptoms (delusions and hallucinations), negative symptoms (e.g., apathy, avolition, affective flattening, and social withdrawal), affective symptoms and cognitive impairment. These dimensions of schizophrenia psychopathology have complex underlying neural substrates. For instance, alterations in frontotemporal cortical networks have been most consistently related to negative symptoms (Millan, Fone, Steckler, & Horan, 2014), while aberrant neurotransmission within basal ganglia (Perez-Costas, Melendez-Ferro, & Roberts, 2010) and the hippocampus (Heckers, 2001) has been shown to underlie positive symptoms. More complex neural substrates have been shown for the cognitive impairment that is present in about 80% of patients and affects several domains of cognitive performance including attention, memory, reasoning, and processing speed (Barch & Ceaser, 2012; Bora, Yucel, & Pantelis, 2010; Keefe & Fenton, 2007; Keefe & Harvey, 2012).