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Computational Psychiatry & Active Inference

Loss of Agency in Schizophrenia

An integrative infographic mapping how Bayesian belief updating, imprecise efference copies, failed sensory attenuation, and egocentric-allocentric network imbalances dissolve the boundary between self and world.

Intentional Binding
0 ms
Temporal compression loss in active motor action (vs ~80ms in controls)
Force Matching
100% Match
Paradoxical physical accuracy in direct pressing due to zero sensory attenuation
Auditory N1 Suppression
~0% Loss
Absence of electrophysiological attenuation to self-initiated speech/tones
Urbanicity Risk Load
2.5x Salience
Predictability overload accelerating hyper-rigid delusional prior formation
Foundational Architecture

The Dual-Level Agency Dichotomy & Bayesian Inference

The Sense of Agency (SoA) is not a monolithic percept, but a hierarchical synthesis operating across two distinct functional layers. Predictive coding frames the brain as a generative Bayesian machine that continuously minimizes free energy (prediction error) by combining top-down prior expectations with bottom-up sensory likelihoods. In schizophrenia, a systemic misallocation of precision weights shatters this equilibrium.

Feeling vs. Judgment of Agency

Feeling of Agency (FoA)
Pre-reflective / Sensorimotor Level

Implicit, non-conceptual registration of self-causation. Operates automatically in background motor loops, relying on precise forward models, efference copies, and immediate sensory attenuation.

Pathology: Fails due to degraded efference copies, resulting in unattenuated sensory feedback (hypo-binding).
Judgment of Agency (JoA)
Reflective / Conceptual Level

Explicit, belief-like attribution of authorship. Relies on social context, narrative integration, and high-level priors to explain current bodily and environmental states.

Pathology: Becomes hyper-rigid to "explain away" unattenuated sensory errors, forming passivity delusions.
In healthy cognition, FoA and JoA align seamlessly. In schizophrenia, a broken FoA forces the JoA to generate radical delusional hypotheses to preserve internal logical coherence.

The Mathematics of Precision Weighting

Bayesian perception updates internal beliefs (posterior) by weighting prior expectations against sensory input (likelihood) based on their relative precision (inverse variance).

Posterior ∝ Prior × Likelihood
Precision (Gain) = Inverse Variance (1 / Variance)
Healthy State: Precision Balance
High prior precision for self-initiated acts allows smooth attenuation of sensory inputs, yielding low prediction error and clear self-attribution.
Schizophrenic State: Imbalance & Aberrant Salience
Imprecise motor priors + Unattenuated sensory precision = Persistent flood of false prediction errors ("Aberrant Salience"), triggering delusional compensatory priors.
Synaptic Gain Control: Precision is neurobiologically encoded by post-synaptic pyramidal cell gain, regulated by NMDA receptors and striatal/cortical dopamine loops.
Mechanistic Circuitry

Active Inference, Efference Copy & Sensory Attenuation

Under active inference, motor actions are executed by predicting proprioceptive consequences. To initiate voluntary movement without contradictory sensory feedback, the brain temporarily withdraws precision from sensory channels—a process termed sensory attenuation driven by the motor efference copy and corollary discharge.

Motor Execution & Corollary Discharge Cascade

Step 01
Motor Intention

Frontal/Premotor cortex formulates descending proprioceptive predictions to execute movement.

Step 02
Efference Copy

A motor blueprint duplicate is routed to sensory areas via corollary discharge (Cerebellum & Cortical loops).

Step 03
Sensory Attenuation

Precision is withdrawn from sensory channels. Self-generated sensations are muted ("tickle suppression").

Step 04
Agency Registration

Match between predicted and actual feedback suppresses prediction error, confirming self-causation (FoA).

Schizophrenia Disruption: In schizophrenia, Step 02 fails due to impaired efference copy generation and cerebellar dysconnectivity. As a consequence, Step 03 (sensory attenuation) cannot occur. Voluntary motor actions produce unattenuated, highly salient sensory errors, making self-generated actions feel as if they were imposed by external forces.
Systemic Dynamics

The Egocentric-Allocentric Model of Passivity

Patients with schizophrenia display a striking clinical paradox: a diminished sense of agency for their own voluntary movements (hypo-binding) combined with an exaggerated attribution of agency to external forces or alien entities (hyper-binding). This is resolved by analyzing the asymmetry between egocentric and allocentric computational systems.

Eg

Egocentric System

Motor-Based Sensorimotor Forward Model
  • Mechanism: Driven directly by motor efference copies and presynaptic inhibition of reafferent sensory signals.
  • Healthy Function: Rapidly explains away tactile/kinematic sensations during active movements.
  • ×Schizophrenic Deficit: Degradation of motor prediction precision leading to persistent hypo-binding and absence of self-attenuation.
Al

Allocentric System

Perceptual & Contextual Generative Model
  • Mechanism: Functions independently of motor commands, utilizing physical/social priors regarding external causes.
  • Healthy Function: Evaluates external environmental events, social intentions, and unexpected physical contact.
  • ×Schizophrenic Compensation: In the absence of egocentric binding, allocentric hyper-priors step in to assign external agency to self-generated acts.
Quantitative Validation

Empirical Paradigms: Quantifying Computational Deficits

The theoretical tenets of predictive coding and active inference are empirically validated through psychophysical and electrophysiological paradigms. These tasks stress-test sensory attenuation, temporal action-outcome binding, and motor prediction accuracy in clinical populations.

Intentional Binding Task

Temporal Compression

Perceived time interval between action & outcome. Healthy controls contract time in voluntary actions. Patients lack temporal compression.

Takeaway: Schizophrenia patients exhibit 0ms temporal compression in active conditions, demonstrating a failure of motor predictions to bind action to outcome.

Force-Matching Paradigm

Sensory Attenuation

Matching target force (2.0N) under direct pressing vs indirect slider. Controls overestimate direct force due to sensory attenuation.

Paradoxical Accuracy: Patients are significantly more accurate in direct pressing (~2.1N vs ~3.2N) because they fail to attenuate their own touch.

Auditory N1 Suppression

Electrophysiology

Auditory cortex potential (N1 component, ~100ms) during self-initiated speech/tones vs passive playback listening.

Neural Deficit: Controls mute self-generated N1 amplitude by ~50%. Schizophrenia patients show unattenuated N1 responses.
Cognitive & Environmental Extension

Inner Speech, Thought Insertion & Urbanicity Load

The computational principles governing motor agency scale directly to cognitive phenomena like Auditory Verbal Hallucinations (AVH) and Thought Insertion. Furthermore, environmental drivers like dense urban environments increase predictability loads, accelerating delusional hyper-prior formation.

Auditory Verbal Hallucinations (AVH)

Inner speech is covert motor action. In healthy individuals, premotor regions generate efference copies that instruct the auditory cortex to attenuate the internal voice. In schizophrenia, degraded audiomotor efference copies leave inner speech unattenuated, highly salient, and perceptually "loud." Impaired Anterior Cingulate Cortex (ACC) source monitoring fails to tag the signal as internal, creating the vivid experience of an external voice.

Thought Insertion & Inner Connectedness

Drawing on classical phenomenological insights, thoughts normally possess an unbroken narrative interconnectedness driven by continuous contextual priors. When higher-order narrative priors weaken, new thoughts emerge unpredicted, generating massive cognitive prediction errors. Lacking predictive dampening, the thought feels intrusive, alien, and "sensory-like." The allocentric system formulates a delusional hyper-prior—"an external entity inserted this thought"—to resolve the computational surprise.

Urban Predictability Load vs Aberrant Salience

Environmental Scatter

Environmental stressor modeling: Densely populated urban environments present chaotic, unpredictable stimuli, overloading impaired sensory gating.

Environmental Stress: High urban stimulus chaos saturates prediction error capacity, driving rapid dopaminergic recalibration and rigid delusional fixation.
Circuit Architecture

Neuroanatomical Substrates of Agency Disruption

Abstract Bayesian parameters map onto dedicated neural architectures. The loss of agency implicates a distributed network centered on the Temporoparietal Junction (TPJ), the Cerebellum, and the Anterior Cingulate Cortex (ACC).

TPJ

Temporoparietal Junction (rTPJ / IPL)

Multimodal Integration & Self-Other Distinction

Synthesizes thalamic, somatosensory, and visual streams to generate allocentric predictions. Encodes Theory of Mind (ToM) and spatial agency boundaries.

Pathology: Bilateral cortical thinning, reduced STS volume, abnormal hyperactivity in right IPL during active movement, and aberrant self/non-self neural map overlap.
CB

Cerebellum & Forward Models

Millisecond Sensorimotor Prediction Engine

Receives immediate efference copies of motor commands and predicts exact sensory consequences to drive sensory attenuation.

Pathology: Cerebellar-parietal dysconnectivity breaks corollary discharge transmission, preventing sensory attenuation before action completion.
ACC

Anterior Cingulate Cortex (ACC)

Conflict Monitoring & Source Monitoring

Evaluates prediction error magnitude, evaluates cognitive conflicts, and tags incoming representations as self-sourced vs externally generated.

Pathology: Gray matter volume loss and functional hypoactivation lead to source-monitoring failures, cementing delusions of external control.
Therapeutic Roadmap

Transdiagnostic Implications & Targeted Neuromodulation

Moving beyond descriptive DSM categories, computational psychiatry enables precise computational phenotyping and personalized circuit-level therapeutics.

01. Dynamic Causal Modeling (DCM)

Combines behavioral psychophysics (intentional binding, force matching) with EEG/fMRI data to quantify an individual's prior precision parameters and efference copy integrity.

02. Glutamatergic Therapeutics

Targets NMDA receptor hypofunction to recalibrate synaptic gain on error-reporting superficial pyramidal cells, restoring bottom-up vs top-down precision balance without sedation.

03. Targeted Neuromodulation (TMS/tDCS)

Frequency-specific Transcranial Magnetic Stimulation (TMS) applied to the right TPJ entrains alpha/beta oscillations to rebuild self-other boundaries and reduce passivity delusions.

This page was medically reviewed by Eric Wexler M.D., Ph.D. on August 14, 2026.