Functional neuroanatomy of action selection in schizophrenia
Date
24/11/2011Author
Romaniuk, Liana
Metadata
Abstract
Schizophrenia remains an enigmatic disorder with unclear neuropathology. Recent advances
in neuroimaging and genetic research suggest alterations in glutamate-dopamine interactions
adversely affecting synaptic plasticity both intracortically and subcortically. Relating these
changes to the manifestation of symptoms presents a great challenge, requiring a constrained
framework to capture the most salient elements. Here, a biologically-grounded computational
model of basal ganglia-mediated action selection was used to explore two pathological processes
that hypothetically underpin schizophrenia. These were a drop in the efficiency of cortical
transmission, reducing both the signal-to-noise ratio (SNR) and overall activity levels; and
an excessive compensatory upregulation of subcortical dopamine release. It was proposed
that reduced cortical efficiency was the primary process, which led to a secondary disinhibition
of subcortical dopamine release within the striatum. This compensation was believed to
partly recover lost function, but could then induce disorganised-type symptoms - summarised
as selection ”Instability” - if it became too pronounced. This overcompensation was argued
to be countered by antipsychotic medication. The model’s validity was tested during an fMRI
(functional magnetic resonance imaging) study of 16 healthy volunteers, using a novel perceptual
decision-making task, and was found to provide a good account for pallidal activation.
Its account for striatum was developed and improved with a small number of principled model
modifications: the inclusion of fast spiking interneurons within striatum, and their inhibition
by the basal ganglia’s key regulatory nucleus, external globus pallidus. A key final addition
was the explicit modelling of dopaminergic midbrain, which is dynamically regulated by both
cortex and the basal ganglia. This enabled hypotheses concerning the effects of cortical inefficiency,
compensatory dopamine release and medication to be directly tested. The new
model was verified with a second set of 12 healthy controls. Its pathological predictions were
compared to data from 12 patients with schizophrenia. Model simulations suggested that Instability
went hand-in-hand with cortical inefficiency and secondary dopamine upregulation.
Patients with high Instability scores showed a loss of SNR within decision-related cortex (consistent
with cortical inefficiency); an exaggerated response to task demands within substantia
nigra (consistent with dopaminergic upregulation); and had an improved fit to simulated data
derived from increasingly cortically-inefficient models. Simulations representing the healthy
state provided a good account for patients’ motor putamen, but only cortically-inefficient simulations
representing the ill state provided a fit for ventral-anterior striatum. This fit improved
as the simulated model became more medicated (increased D2 receptor blockade). The relative improvement of this account correlated with patients’ medication dosage. In summary,
by distilling the hypothetical neuropathology of schizophrenia into two simplified umbrella processes,
and using a computational model to consider their effects within action selection, this
work has successfully related patients’ fMRI activation to particular symptomatology and antipsychotic
medication. This approach has the potential to improve patient care by enabling
a neurobiological appreciation of their current illness state, and tailoring their medication level
appropriately.