Schizophrenia Research Forum - A Catalyst for Creative Thinking

Learning Differences May Predict Vulnerability to Psychoses

9 July 2006. People with psychoses can have a very different outlook on the world from those who are spared the pain of such psychological problems—delusions are a well-characterized symptom of schizophrenia, for example. Though it is still a mystery as to exactly how psychoses precipitate delusional thinking, some new research reinforces the view that difficulty with associative learning, a process that is crucial for establishing a rational view of what goes on in one’s daily life, may be at least partly responsible for delusions. The study, carried out at Aldenbrooke’s Hospital, Cambridge, England, and published in the June issue of Archive of General Psychiatry, also fingers the prefrontal cortex as the region of the brain where such associative learning problems may begin to manifest themselves.

The research, led by Paul Fletcher, University of Cambridge, set out to examine one particular facet of associative learning: prediction error. There have been suggestions that schizophrenic patients react differently from normal individuals when something they believe to be true actually turns out to be false. In the normal brain, such prediction errors are believed to play an important part in molding our view of the world because by reinforcing or negating our perception of causal associations, they help us to separate the meaningful from the insignificant as we try to put daily happenings in some kind of logical perspective.

To examine the relationship between prediction error and psychoses, first author Philip Corlett and colleagues in the University of Cambridge, and also at University College London, measured brain activity in normal people faced with a prediction error, then correlated that activity with their susceptibility to psychoses. Brain activity was measured by functional magnetic resonance imaging (fMRI), while the drug ketamine, a glutamate antagonist, was used to mimic a psychotic state.

To challenge the subjects with a prediction error, the researchers used a simple computer-based associative learning task. On the screen the volunteers saw an image of a mystery person’s meal, for example, a juicy-looking hamburger and two bananas. They learned that the meal would lead to an allergic reaction in the unfortunate mystery character. In a second stage, the volunteers learned that the burger by itself did not cause a reaction. Ergo, it must have been the bananas. This test thus creates in the volunteers an association, with a resulting strong expectation that when they see the bananas, they’ll see an allergic reaction. But next came the maddening part—the old bait and switch.

The computer experiment was set up to deliver that answer only half the time, so when the volunteer would make a logical prediction that bananas were the allergenic culprit, half of their predictions would be wrong. While the volunteers frustratingly found themselves making prediction errors, the researchers recorded fMRI scans of brain.

Corlett and colleagues found that the right prefrontal cortex (rPFC) became highly activated when the volunteers made a prediction error compared to when their prediction was confirmed (see also Fletcher et al., 2001). But if the volunteers did the test under the influence of ketamine, then the rPFC was activated even when they did not make an error, while prediction error elicited much less of a response than normal. So the psychotomimetic ketamine seems to both augment the rPFC response to normal stimuli and attenuate its response to prediction errors. “Taken together, our observations suggest that the perturbation of prediction error signaling may manifest as both decreases in appropriate signaling and increases in inappropriate signaling,” write the authors. While they also found that prediction error versus confirmation elicited different responses in the striatum, substantia nigra, and hippocampus, none of these differences were altered by administering ketamine.

These findings suggest that associative learning responses are compromised in a model of a psychotic state, but what about the development of psychoses and associative learning problems? It appears there may be a connection there, too. The authors addressed this question by correlating rPFC activation in normal individuals on placebo, with subsequent susceptibility to ketamine-induced psychosis. Significantly, they found that those individuals who had the greatest activation of the rPFC in response to a prediction error also reported the most severe psychotic episodes when given high doses of ketamine later on (plasma levels averaging 210 ng/mL). Using the Clinician-Administered Dissociative States Scale (CADSS) and the Present State Examination, which are designed to evaluate the extent of dissociation and of psychosis, respectively, Corlett and colleagues found direct relationships between prediction error-elicited rPFC activation and perceptual illusions and delusional thoughts.

The latter finding leads to some interesting chicken-and-egg scenarios. “That is, does disrupted prediction error produce the perceptual change or vice versa?” question the authors. In this case, they speculate that it is the prediction error signaling that leads to the altered perception because at the doses of ketamine used, the volunteers do not suffer from any significant perceptual change per se, but rather “feel” different about external stimuli.

One aspect of delusions this study does not address, emphasize the authors, is the “fixity” of delusions. While the study indicates links between prediction error signaling and sensory experience, it does not reveal how untenable views of the world become entrenched in the delusional state. The authors do suggest, however, that “repeated experience of abnormal prediction error signal will be an insidious process in which patients are frequently and repeatedly surprised by their experiences.” Thus, fully formed delusions may be the ultimate attempt to account for the uncertainty that seems to permeate their world.—Tom Fagan.

Corlett PR, Honey GD, Aitken MRF, Dickinson A, Shanks DR, Absalom AR, Lee M, Pomarol-Clotet E, Murray GK, McKenna PJ, Robbins TW, Bullmore ET, Fletcher PC. Frontal responses during learning predict vulnerability to the psychotogenic effects of ketamine. Arch Gen Psych. June 2006;63:611-621. Abstract

Comments on News and Primary Papers
Comment by:  Cameron Carter
Submitted 30 June 2006
Posted 30 June 2006

Corlett and the group from Cambridge seek to gain insights into mechanisms related to the formation of delusions, one of the core positive symptoms of schizophrenia, using fMRI and an associative learning task, and as a pharmacological model of psychosis, the ketamine challenge in normal volunteers. They report a number of significant and interesting correlations that they interpret within the framework of the reinforcement learning model of associative learning. Right prefrontal activity associated with unexpected negative feedback during the placebo phase (a prediction error signal) correlates with two measures of “early” delusional thinking during higher-dose ketamine challenge. Measures of sensory disturbances during high-dose ketamine correlate with measures of early delusional thinking. And low-dose ketamine-related changes in the response to feedback are correlated with early delusional thinking during high-dose ketamine. Ketamine also appears to have an effect on the acquisition of associations within this paradigm. The authors conclude that their result implicates altered frontal function and disruptions in error-dependent learning in associative processes that lead to referential thinking and delusion formation. They also implicate a role for NMDA neurotransmission in this deficit.

The paper is very important since it tests a new theoretical model of delusions based upon an explicit model of error-dependent associative learning. Having such an explicit model provides the authors not only with increased insight into mechanisms, but also the ability to design cognitive activation experiments that can test for the presence of predicted deficits as well as their underlying neural circuitry. For this reason, the work is likely to have a very significant impact on our thinking about a previously elusive topic: how delusions form in the brains of people with schizophrenia.

A limitation of the paper is that the findings are correlational and the authors do not precisely specify, in computational terms, the nature of the abnormality in feedback-related learning that leads to delusions. However, they do localize the deficit to the prefrontal cortex and indicate their belief that the primary deficit is associated with the processing of prediction errors that, in turn, depend upon glutamatergic neurotransmission. There are other alternative interpretations of their results which they acknowledge in their discussion, such as the possibility that greater activation in the prefrontal cortex to error feedback is a marker of poorer prefrontal efficiency and that this is associated with psychosis proneness. A second alternative account which they discuss is the possibility that the quality of sensory processing in individual subjects drives the correlations. A third, non-NMDA account of their data involves altered dopaminergic neurotransmission, given that the work of Shultz and Montague have strongly implicated a role for dopaminergic neural activity in prediction error signaling during reinforcement-based associative learning.

One way to test the general PFC inefficiency theory would be to see if activity during other non-associative learning tasks predicts psychosis proneness under ketamine challenge, or that the error-dependent PFC signal predicts non-NMDA-related psychosis-like states such as those induced by cannabis or amphetamine. Given the explicit nature of the reinforcement learning model, there will likely be a number of task manipulations that would manipulate specific parameters in computational models of the task that could be tested using fMRI. One expects that this paper will generate many additional studies that will test the authors’ model and various alternative views regarding the significance of their results for understanding the cognitive and neural mechanisms underlying delusion formation in schizophrenia.

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