Re-evaluating dorsolateral prefrontal cortex activation during working memory in schizophrenia

Abstract

Previous neuroimaging studies of working memory (WM) in schizophrenia have generated conflicting findings of hypo- and hyper-frontality, discrepancies potentially driven by differences in task difficulty and/or performance. This study proposes and tests a new model of the performance-activation relationship in schizophrenia by combining changes by load with overall individual differences in performance. Fourteen patients with recent-onset schizophrenia and eighteen controls underwent functional magnetic resonance imaging while performing a parametric verbal WM task. Group level differences followed a linear "cross-over" pattern, such that in controls, activation in the dorsolateral prefrontal cortex (DLPFC) increased as performance decreased, while patients showed the opposite. Overall, low performing patients were hypoactive and high performing patients hyperactive relative to controls. However, patients and controls showed similar functions of activation by load in which activation rises with task difficulty but levels off or slightly decreases at higher loads. Moreover, across all loads and at their own WM capacity, higher performing patients showed greater DLPFC activation than controls, while lower performing patients activated least. This study establishes a novel framework for predicting the relationship between functional activation and WM performance by combining changes of activation by WM load occurring within each subject with the overall differences in activation associated with general WM performance. Essentially, increasing task difficulty correlates asymptotically with increasing activation in all subjects, but depending on their behavioral performance, patients show overall hyper- versus hypofrontality, a pattern potentially derived from individual differences in underlying cellular changes that may relate to levels of functional disability.

Figure 1

Proposed model: 1a. Inverted-U shaped curve representing the hypothetical signal change in DLPFC as a response to increasing working memory load in patients with schizophrenia and controls (Callicott et al, 2003; Manoach, 2003), 1b Between-subjects crossover model (based on Karlsgodt, 2007), plotting individual differences in overall performance (averaged across the entire task) against individual differences in overall functional activation (averaged across the entire task), 1c Proposed Multi-level model. Each inverted curve shaped function represents the change in activation of an individual subject as load changes. The placement of the curves is determined by individual differences in performance, which influence the range of activation within which the subject changes. As a group, controls increase activation as performance decreases, while patients do the opposite. Independently of this, all subjects show similar functions of activation changes with load.

Figure 2

Behavioral performance (percent correct ± standard error) on the verbal working memory task across memory load (number of letters presented). The patient group is divided at the median to constitute “low performing” and “high performing” subgroups.

Figure 3

Between-subjects linear regression investigating the relationship in working memory performance (percent correct) and functional activation (percent change in BOLD signal ± standard error) in patient and control groups in left (A) and right (C) DLPFC. Within-subjects functional activation across working memory load in left (B) and right (D) DLPFC ROIs. All subject groups demonstrate similar functions, however high performing patients are hyperactive to controls while low performing patients are hypoactive. Functionally defined regions of interest in left and right DLPFC (E).

Figure 4

Analysis of functional activation (percent change in BOLD signal ± standard error) in each group, calculated by pooling across the activation observed at each subjects individually calculated working memory capacity (Equation 1).

Figure 5

DLPFC performance-activation data from the current first episode sample and previously analyzed chronic sample (Karlsgodt, 2007) demonstrating the replicability of the cross-over pattern in these two samples.