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Active inference, sensory attenuation and illusions.

Brown H, Adams RA, Parees I, Edwards M, Friston K - Cogn Process (2013)

Bottom Line: Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly.This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia.It also provides a functional account of deficits in syndromes characterised by false inference and impaired movement--like schizophrenia and Parkinsonism--syndromes that implicate abnormal modulatory neurotransmission.

View Article: PubMed Central - PubMed

Affiliation: Institute of Neurology, The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London, WC1N 3BG, UK, harriet.brown.09@ucl.ac.uk.

ABSTRACT
Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can actively change sensory input to fulfil our predictions. In active inference, this action is mediated by classical reflex arcs that minimise proprioceptive prediction error created by descending proprioceptive predictions. However, this creates a conflict between action and perception; in that, self-generated movements require predictions to override the sensory evidence that one is not actually moving. However, ignoring sensory evidence means that externally generated sensations will not be perceived. Conversely, attending to (proprioceptive and somatosensory) sensations enables the detection of externally generated events but precludes generation of actions. This conflict can be resolved by attenuating the precision of sensory evidence during movement or, equivalently, attending away from the consequences of self-made acts. We propose that this Bayes optimal withdrawal of precise sensory evidence during movement is the cause of psychophysical sensory attenuation. Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly. Finally, if attenuation is removed, the force-matching illusion disappears and false (delusional) inferences about agency emerge. This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia. Active inference therefore links the neuromodulatory optimisation of precision to sensory attenuation and illusory phenomena during the attribution of agency in normal subjects. It also provides a functional account of deficits in syndromes characterised by false inference and impaired movement--like schizophrenia and Parkinsonism--syndromes that implicate abnormal modulatory neurotransmission.

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Related in: MedlinePlus

Simulation of the force-matching task. In the first part of this simulation (left hand panels), an internal force is generated (from a prior belief about the hidden cause νi), followed by the presentation of an external force. The estimates of the hidden states (upper right panel) are similar, but the confidence interval around the force for the internally generated state is much broader. If perceptual inference is associated with the lower 90 % confidence bound of the estimate of the hidden state, it will be lower when the force is self-generated (double-headed arrow, upper right panel). This is demonstrated in the right-hand panels. This is a simulation the force-matching paradigm where the external force is matched to the lower bound of the 90 % confidence interval of the internal force. This means that internally generated force is now greater than the externally applied force (double-headed arrow, upper left panel)
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Fig6: Simulation of the force-matching task. In the first part of this simulation (left hand panels), an internal force is generated (from a prior belief about the hidden cause νi), followed by the presentation of an external force. The estimates of the hidden states (upper right panel) are similar, but the confidence interval around the force for the internally generated state is much broader. If perceptual inference is associated with the lower 90 % confidence bound of the estimate of the hidden state, it will be lower when the force is self-generated (double-headed arrow, upper right panel). This is demonstrated in the right-hand panels. This is a simulation the force-matching paradigm where the external force is matched to the lower bound of the 90 % confidence interval of the internal force. This means that internally generated force is now greater than the externally applied force (double-headed arrow, upper left panel)

Mentions: Clearly, reducing the precision of sensory prediction errors reduces the posterior confidence in beliefs about their causes. Figure 3 shows an inflation of the posterior uncertainty (90 % grey confidence intervals) due to sensory attenuation. The consequence of this transient uncertainty—due to a temporary suspension of attention to sensory input—provides a simple explanation for sensory attenuation in terms of psychophysical detection. This can be demonstrated fairly easily by presenting the forces generated by the subject exogenously and comparing the posterior beliefs about internal and external hidden states (forces). The left panels of Fig. 6 show the results of this simulation, in which there has been a veridical inference about the succession of internal and external hidden causes (blue and green lines in the lower left panels), with a reasonable degree of confidence. Furthermore, the predictions about internally and externally generated sensations are accurate and subtended by veridical conditional expectations. However, the confidence interval around the estimate of the internal hidden state is much greater than for the external hidden state. This means that if we asked the subject to report somatosensory sensations at 90 % confidence, the externally generated sensations would be detected much more readily than the internally generated sensations. This is the essence of sensory attenuation in psychophysical studies and—in this simulation—rests upon the inflation of the confidence interval associated with internally generated consequences. In other words, we would expect a reduction in d-prime for events that were self-generated, relative to exactly the same events that were generated externally—as demonstrated experimentally (Cardoso-Leite et al. 2010). As this reduction in precision is applied to the entire sensory channel for the duration of the movement, a reduction in d-prime will also been seen for external stimuli produced during voluntary movement. This result has also been demonstrated experimentally (Juravle and Spence 2011; Van Hulle et al. 2013). This attenuation is shown by the double-headed arrow in Fig. 6. Exactly the same interpretation can be applied to the force-matching paradigm:Fig. 6


Active inference, sensory attenuation and illusions.

Brown H, Adams RA, Parees I, Edwards M, Friston K - Cogn Process (2013)

Simulation of the force-matching task. In the first part of this simulation (left hand panels), an internal force is generated (from a prior belief about the hidden cause νi), followed by the presentation of an external force. The estimates of the hidden states (upper right panel) are similar, but the confidence interval around the force for the internally generated state is much broader. If perceptual inference is associated with the lower 90 % confidence bound of the estimate of the hidden state, it will be lower when the force is self-generated (double-headed arrow, upper right panel). This is demonstrated in the right-hand panels. This is a simulation the force-matching paradigm where the external force is matched to the lower bound of the 90 % confidence interval of the internal force. This means that internally generated force is now greater than the externally applied force (double-headed arrow, upper left panel)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3824582&req=5

Fig6: Simulation of the force-matching task. In the first part of this simulation (left hand panels), an internal force is generated (from a prior belief about the hidden cause νi), followed by the presentation of an external force. The estimates of the hidden states (upper right panel) are similar, but the confidence interval around the force for the internally generated state is much broader. If perceptual inference is associated with the lower 90 % confidence bound of the estimate of the hidden state, it will be lower when the force is self-generated (double-headed arrow, upper right panel). This is demonstrated in the right-hand panels. This is a simulation the force-matching paradigm where the external force is matched to the lower bound of the 90 % confidence interval of the internal force. This means that internally generated force is now greater than the externally applied force (double-headed arrow, upper left panel)
Mentions: Clearly, reducing the precision of sensory prediction errors reduces the posterior confidence in beliefs about their causes. Figure 3 shows an inflation of the posterior uncertainty (90 % grey confidence intervals) due to sensory attenuation. The consequence of this transient uncertainty—due to a temporary suspension of attention to sensory input—provides a simple explanation for sensory attenuation in terms of psychophysical detection. This can be demonstrated fairly easily by presenting the forces generated by the subject exogenously and comparing the posterior beliefs about internal and external hidden states (forces). The left panels of Fig. 6 show the results of this simulation, in which there has been a veridical inference about the succession of internal and external hidden causes (blue and green lines in the lower left panels), with a reasonable degree of confidence. Furthermore, the predictions about internally and externally generated sensations are accurate and subtended by veridical conditional expectations. However, the confidence interval around the estimate of the internal hidden state is much greater than for the external hidden state. This means that if we asked the subject to report somatosensory sensations at 90 % confidence, the externally generated sensations would be detected much more readily than the internally generated sensations. This is the essence of sensory attenuation in psychophysical studies and—in this simulation—rests upon the inflation of the confidence interval associated with internally generated consequences. In other words, we would expect a reduction in d-prime for events that were self-generated, relative to exactly the same events that were generated externally—as demonstrated experimentally (Cardoso-Leite et al. 2010). As this reduction in precision is applied to the entire sensory channel for the duration of the movement, a reduction in d-prime will also been seen for external stimuli produced during voluntary movement. This result has also been demonstrated experimentally (Juravle and Spence 2011; Van Hulle et al. 2013). This attenuation is shown by the double-headed arrow in Fig. 6. Exactly the same interpretation can be applied to the force-matching paradigm:Fig. 6

Bottom Line: Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly.This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia.It also provides a functional account of deficits in syndromes characterised by false inference and impaired movement--like schizophrenia and Parkinsonism--syndromes that implicate abnormal modulatory neurotransmission.

View Article: PubMed Central - PubMed

Affiliation: Institute of Neurology, The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London, WC1N 3BG, UK, harriet.brown.09@ucl.ac.uk.

ABSTRACT
Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can actively change sensory input to fulfil our predictions. In active inference, this action is mediated by classical reflex arcs that minimise proprioceptive prediction error created by descending proprioceptive predictions. However, this creates a conflict between action and perception; in that, self-generated movements require predictions to override the sensory evidence that one is not actually moving. However, ignoring sensory evidence means that externally generated sensations will not be perceived. Conversely, attending to (proprioceptive and somatosensory) sensations enables the detection of externally generated events but precludes generation of actions. This conflict can be resolved by attenuating the precision of sensory evidence during movement or, equivalently, attending away from the consequences of self-made acts. We propose that this Bayes optimal withdrawal of precise sensory evidence during movement is the cause of psychophysical sensory attenuation. Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly. Finally, if attenuation is removed, the force-matching illusion disappears and false (delusional) inferences about agency emerge. This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia. Active inference therefore links the neuromodulatory optimisation of precision to sensory attenuation and illusory phenomena during the attribution of agency in normal subjects. It also provides a functional account of deficits in syndromes characterised by false inference and impaired movement--like schizophrenia and Parkinsonism--syndromes that implicate abnormal modulatory neurotransmission.

Show MeSH
Related in: MedlinePlus