Dysconnectivity of the Agency Network in Schizophrenia: A Functional Magnetic Resonance Imaging Study

Background: Self-disturbances in schizophrenia have recently been explained by an abnormality in the sense of agency (SoA). The cerebral structures of SoA in healthy people are considered to mainly include the insula and inferior parietal lobule. In contrast, the functional lesion of aberrant SoA in schizophrenia is not yet fully understood. Considering the recent explanation of establishing SoA from the standpoint of associative learning, the “agency network” may include not only the insula and inferior parietal lobule but also the striatum. We hypothesized that aberrant SoA in schizophrenia is based on a deficit in the “agency network.”Methods: Functional magnetic resonance imaging data were acquired while patients with schizophrenia (n = 15) and matched controls (n = 15) performed our adaptation method of agency attribution task on a trial-by-trial basis to assess participants' explicit experience of the temporal causal relationship between an action and an external event with temporal biases. Analysis of functional connectivity was done using the right supramarginal gyrus and the right middle frontal gyrus as seed regions.Results: In healthy controls, analyses revealed increased activation of the right inferior parietal lobule (mainly the supramarginal gyrus), right insula, and right middle frontal gyrus as an activation of the agency condition. We defined activated Brodmann areas shown in the agency condition of healthy controls as the seed region for connectivity analysis. The connectivity analysis revealed lower connectivity between the head of the left caudate nucleus and right supramarginal gyrus in the patients compared to healthy controls.Conclusions: This dysconnectivity of the agency network in schizophrenia may lead to self-disturbance through deficits in associative learning of SoA. These findings may explain why pathological function of the striatum in schizophrenia leads to self-disturbance

Retrospective surprise: A computational component for active inference

In the free energy principle (FEP), proposed by Friston, it is supposed that agents seek to minimize the “surprise”–the negative log (marginal) likelihood of observations (i.e., sensory stimuli)–given the agents' current belief. This is achieved by minimizing the free energy, which provides an upper bound on the surprise. The FEP has been applied to action selection in a framework called “active inference,” where agents are supposed to select an action so that they minimize the “expected free energy” (EFE). While the FEP and active inference have attracted the attention of researchers in a wide range of fields such as psychology and psychiatry, as well as neuroscience, it is not clear which psychological construct EFE is related to. To facilitate the discussion and interpretation of psychological processes underlying active inference, we introduce a computational component termed the “retrospective (or residual) surprise,” which is the surprise of an observation after updating the belief given the observation itself. We show that the predicted retrospective surprise (PRS) provides a lower bound on EFE: EFE is always larger than PRS. We illustrate the properties of EFE and PRS using examples of inference for a binary hidden cause given a binary observation. Essentially, EFE and PRS show similar behavior; however, in certain situations, they provide different predictions regarding action selection. This study also provides insights into the mechanism of active inference based on EFE

Aberrant sense of agency induced by a delayed prediction signal in schizophrenia: a computational modeling study

Background Aberrant sense of agency (SoA, a feeling of control over one’s own actions and their subsequent events) has been considered as key to understanding the pathology of schizophrenia. Behavioral studies demonstrated that both excessive and diminished SoAs were observed in schizophrenia. Several neurophysiological studies have suggested that such aberrant SoA may be due to temporal delays (TDs) in sensory-motor prediction signals. In the current study, we examined this hypothesis via a computational modeling approach using a recurrent neural network (RNN) model. Methods The sensory-motor prediction process in the behavioral task of SoA was modeled using an RNN model that can learn to reproduce the SoA task performance of human participants. The RNN model receives inputs of the states of visual, auditory, and proprioceptive senses, and generates forward predictions for those at the next time step and SoA judgement. In the simulation, the RNN models were trained using the actual behavioral data of 17 healthy controls completing an SoA task; then, our hypothesis was tested by adding TDs in the signals between context units of the RNN. Results The RNN model successfully reproduced the behavioral features of the healthy controls. Moreover, bidirectional (i.e., excessive and diminished) schizophrenia-pattern SoA was reproduced with the TDs in context units. Three control experiments (random noise addition, TDs in outputs, and TDs in inputs) with quantitative analysis demonstrated no schizophrenia-pattern aberrant SoA. Conclusions The results theoretically support the proposed hypothesis that the aberrant SoA in schizophrenia may be due to TDs in sensory-motor prediction signals

Reduced sense of agency in chronic schizophrenia with predominant negative symptoms

Self-disturbances in schizophrenia have been regarded as a fundamental vulnerability marker for this disease, and have begun to be studied from the standpoint of an abnormal “sense of agency (SoA)” in cognitive neuroscience. To clarify the nature of aberrant SoA in schizophrenia, it needs to be investigated in various clinical subtypes and stages. The residual type of chronic schizophrenia with predominant negative symptoms (NS) has never been investigated for SoA. Accordingly, we investigated SoA by an original agency attribution task in NS-predominant schizophrenia, and evaluated the dynamic interplay between the predictive and postdictive components of SoA in the optimal cue integration framework. We studied 20 patients with NS-predominant schizophrenia, and compared with 30 patients with paranoid-type schizophrenia and 35 normal volunteers. NS-predominant schizophrenia showed markedly diminished SoA compared to normal controls and paranoid-type schizophrenia, indicating a completely opposite direction in agency attribution compared with excessive SoA demonstrated in paranoid-type schizophrenia. Reduced SoA was detected in experimental studies of schizophrenia for the first time. According to the optimal cue integration framework, these results indicate that there was no increase in compensatory contributions of the postdictive processes despite the existence of inadequate predictions, contrary to the exaggerated postdictive component in paranoid-type schizophrenia