Behavioral Neurobiology of Schizophrenia and Its Treatment

Cronenwett WJ, Csernansky J, Will J. Cronenwett, John Csernansky, Cronenwett, Will J., Csernansky, John

The thalamus plays a critical role in the coordination of information as it passes from region to region within the brain. A disruption of that information flow may give rise to some of the cardinal symptoms of schizophrenia. In support of this hypothesis, schizophrenia-like syndromes emerge when illnesses, such as stroke, selectively damage the thalamus while sparing the rest of the brain. Evidence from many sources has implicated thalamic dysfunction in schizophrenia. In postmortem studies, several subregions of the thalamus, including the mediodorsal nucleus and the pulvinar, have been shown to have fewer neurons in schizophrenia. Neurochemical disturbances are also seen, with changes in both the glutamate and dopamine systems; thalamic glutamate receptor expression is altered in schizophrenia, and dopamine appears to be elevated in thalamic subregions, while evidence exists of an imbalance between dopamine and other neurotransmitters. In vivo studies using magnetic resonance imaging have demonstrated smaller thalamic volumes in schizophrenia, as well as shape deformations suggesting changes in those thalamic regions that are most densely connected to the portions of the brain responsible for executive function and sensory integration. These changes seem to be correlated with clinical symptoms. The thalamus is a starting point for several parallel, overlapping networks that extend from thalamic nuclei to the cortex. Evidence is emerging that changes in the thalamic nodes of these networks are echoed by changes at other points along the chain; this suggests that schizophrenia might be a disease of disrupted thalamocortical neural networks. This model distributes the pathology throughout the network, but also concentrates attention on the thalamus as a critical structure, especially because of its role in coordinating the flow of information within and between neural networks.