This instrument maps a dynamic state frame (or frame of intention) — the purposive sequence of reaching for, grasping, raising, and ingesting a cup of coffee — together with its pre-state frame: the prior state in which deep expectations are already active before intention forms. In computing, a 'cold start' describes a system booting with no prior state loaded; biological systems never cold-start — there is always prior activation, always a history of predictions already running. The instrument models the dynamics of an organic neural system using the framework of active inference, which applies concepts from mathematical physics to biological prediction and action. Three layers are distinguished throughout: the mathematical model — the repertoire space and upper/lower bounds within which the system can vary; the neuronal dynamics — the actual trajectory of precision weighting across the 11 systems; and the lived behaviour — the intersection, where the model meets the dynamics and produces minded behaviour. Each system's precision weighting at each moment represents its coupling coefficient with the intentional act — the strength and direction of its functional relationship to the task. A coupling coefficient, in the statistical sense, measures how much a change in one variable produces a change in another. A high coupling coefficient means the system is tightly bound to the act at that moment; a low one means it is running in the background. The dual-register ovals show gross anatomical wiring (grey inner core) and learned adaptation (coloured outer oval); the gap between them is the space within which conscious access operates. Panel 4 is explicitly theoretical.
This panel maps the dynamic state frame (or frame of intention) across seven body systems, showing how their precision weighting — their coupling coefficient with the intentional act — varies across the four phases of the coffee sequence. The instrument approaches the sequence from the perspective of 11 integrated bodily systems in total (the remaining four — persistent and canalised — appear in Panel 2). Each curve represents how tightly a given system is coupled to the task at each moment: a high value means the system is strongly bound to the act; a low value means it is running in the background, present but not leading.
The underlying substrate is a biochemical neural network — billions of neurones connected by synapses, transmitting electrochemical signals, continuously active. This instrument models the dynamics of that organic system using the framework of active inference — a theory of brain function developed by Karl Friston and colleagues, which applies concepts from mathematical physics to biological prediction and action. In this framework, the brain is understood as a prediction machine: rather than passively receiving sensory information, it continuously generates predictions about the world and updates them when prediction errors arise. The mathematical model describes what the neural system is doing in principle; the neural dynamics are what is happening in tissue; the lived behaviour is the intersection where the two produce minded action.
The mathematics of active inference is organised around a quantity called variational free energy. This is a mathematical construct — not electrochemical or metabolic energy, which cannot be directly measured in this context. The term is borrowed from statistical physics by analogy, but it lives entirely within the mathematical model. It measures how well the brain's current generative model accounts for incoming sensory data: minimising it means making the model as accurate as possible while penalising excessive revision of stored expectations. The weighting of each system — its coupling coefficient — reflects how much variational free energy is being allocated to it at any moment.
Central to active inference is the concept of priors — the brain's stored expectations about how something will unfold, built from past experience. When you reach for a coffee cup, you are not computing the reach from scratch; you are running a prediction shaped by thousands of prior reaches, correcting it as sensation arrives. A deep prior is a highly consolidated expectation, resistant to revision — the system runs largely on stored structure and its coupling coefficient changes slowly. A shallow prior is less consolidated: the system depends more heavily on current sensory data to guide behaviour, and its coupling coefficient can shift rapidly. This distinction drives the width of the mathematical envelope and the size of the dual-register ovals.
There is supporting evidence from magnetoencephalography research — particularly emerging OPM-MEG work consistent with hierarchical prediction error signalling in sensorimotor tasks — but no study has simultaneously mapped precision weighting across all 11 systems during a naturalistic action sequence. This instrument is therefore explicitly illustrative.
The faint coloured band around each curve is the mathematical envelope — the repertoire space within which the coupling coefficient can vary. Deep-prior systems (Visual, Musculoskeletal) have narrow envelopes; shallow-prior systems (Thermal — Lips, Thermal — Cheeks) have wider ones. The travelling ovals are notional and illustrative. The outer coloured oval represents the anticipation window — how far ahead the system is already predicting. This is simplified here as hippocampal anticipation, following recent work on hippocampal pre-excitation (Christoff et al., 2009). In practice, anticipation is distributed across multiple neural structures: the cerebellum runs forward models for motor prediction; the basal ganglia anticipate phase transitions; the anterior insula anticipates interoceptive and thermal state changes; the orbitofrontal cortex anticipates reward and outcome. The grey inner core of each oval represents the gross anatomical wiring — the neural connectivity underlying learned behaviour. The gap between core and outer oval is the space within which conscious access operates: the zone where learned anticipation exceeds anatomical structure. The coupling coefficient of each system is readable in that gap — a wide gap means high learned coupling, a narrow gap means the system is running mostly on structure. The sequence begins in the pre-state frame (shaded left region): no system starts from zero.
Four systems run continuously throughout and beyond the sequence — cardiovascular, respiratory, endocrine, and nervous/cerebellar. They do not take turns leading; their coupling coefficients with the intentional act remain narrow-band throughout. They are the biological substrate of the dynamic state frame: the always-present neural and physiological foundation that makes the sequence possible. These systems are not fixed — the cardiovascular system responds continuously to demand, respiratory rhythm shifts with exertion and arousal, the cerebellar system adapts its forward models — but they are dynamic within tight anatomical bounds. Their gross wiring constrains the range of variation, and within that range they are fully active. The distinction from the seven dynamic systems above is not that these four are static, but that their operating range is narrow and deep-prior: they run on consolidated structure rather than on moment-to-moment sensory updating.
The most visible event in this panel is the respiratory dip in Phase IV (Ingest). When liquid crosses the threshold of the lips and the swallowing reflex is triggered, breathing pauses automatically — the airway closes to prevent aspiration of fluid into the lungs. This is swallow apnea: a precisely coordinated deep prior executed entirely below the threshold of conscious access. The respiratory system does not stop; it executes a stored programme, then resumes. Its coupling coefficient with the intentional act briefly inverts — from passive substrate to active suppression — before returning to baseline. This is the clearest demonstration in the entire instrument of a canalised system managing a critical bodily event without any conscious direction.
This panel shows where conscious attention is directed throughout the sequence, and how wide or narrow the attentional beam is at each moment. The vertical axis runs from somatic (bottom) to cognitive (top). The named system reference lines on the right show where each body system sits in the cognitive-somatic register.
The amber centre line is the primary focus of attention at each moment. The filled amber band is the full field of simultaneous conscious access — what is in the foreground and middle ground at once. The faint blue region beyond the band shows what is available but not currently in focus — systems that could be attended to if directed, but are not. The outermost faint region is the neural bandwidth — how wide the attention band could span given the full repertoire of the neural architecture. The gap between this bandwidth and the actual band is where the organism lives: choosing, moment by moment, within the space that its neuronal connectivity makes possible. The mathematical model describes that space; the neural system enacts it; the lived behaviour is the selection between them.
The band is widest during Phase II (Grasp), when multiple systems are simultaneously available to conscious attention. It narrows sharply at the Limit Condition (Phase IV, Ingest), converging almost entirely on the somatic floor — Thermal-Lips dominates, and the rest of the ensemble recedes from conscious access while continuing to run.
This panel is explicitly theoretical. It models the brain/mind interface — the intersection where the mathematical model of the generative process meets the neuronal dynamics of firing, and produces something neither alone can account for: a minded body in purposive action.
The frame of intention — reaching for coffee — requires the activation of deep priors. Those priors are not conscious and cannot be: they are encoded in anatomical structure and in the learned neural network built through thousands of prior reaches. The consciousness envelope (the ovals in Panel 1, the attention band in Panel 3) rides on a vast infrastructure that is, by definition, inaccessible to it. This is not suppression. It is simply how the system is built.
The grey baseline running throughout is the gross-wired anatomical adjacency — the structural connectivity between brain regions that exists regardless of learning. It is always present, always low-amplitude, and represents the biological floor of the dynamic state frame. Above it, stochastic spikes represent topological activation of networks adjacent to the currently active inferential loop. These are not random: they cluster at moments of high network activation (the Grasp spike, the Limit Condition) when intense firing makes excitation of structurally proximate networks more probable. This is consistent with connectome research showing that structural proximity predicts functional co-activation. The Human Connectome Project (HCP) is a large-scale NIH-funded research programme, launched in 2009, which maps the structural and functional connectivity of the human brain using diffusion MRI, resting-state fMRI, and task-based imaging. Its data provide evidence that the physical wiring of the brain — which regions are structurally connected by white-matter tracts — predicts which regions will co-activate during cognitive and motor tasks.
When the frame of intention fires, it does not respect the boundaries of the task. The anatomical wiring and the learned network have their own structure, their own adjacencies. Intense activation in regions serving the reach will excite structurally proximate regions that have nothing to do with coffee. A landscape. A face. A fragment of music. These arisings are determined by the physical and learned topology of the brain. This speculation is supported by behavioural evidence. Dorthe Berntsen (Aarhus, from 1996 onwards) has established that involuntary autobiographical memories — spontaneous memories arising without deliberate retrieval — are not rare intrusions but a basic, frequent mode of remembering, documented in adults, young children, and great apes. They are context-sensitive and associative, favouring material with feature overlap to the current situation. fMRI research confirms that the default mode network partially activates during well-learned motor tasks (Mason et al., 2007), consistent with spontaneous thought arising during habitual action sequences of exactly the kind modelled here.
The adjacency mechanism proposed in this panel is the how: the neurological process by which such material surfaces during purposive action. It does not discriminate by content. It excites whatever is structurally proximate — benign memories, neutral associations, and also, potentially, material carrying affective burden. In the normal case, these arisings coexist with the frame of intention without disturbing it. They are present at the edge of the consciousness envelope but do not derail the reach. The coffee gets picked up. The frame completes. Berntsen's findings confirm this: involuntary autobiographical memories are functional and ordinarily benign.
This is where the relationship to Freud becomes interesting. In the later structural model (The Ego and the Id, 1923; the papers on defence), the unconscious contains material that is actively kept from consciousness by a dynamic force — repression (Verdrängung). Such material exerts continuous pressure to return. Berntsen herself argues that intrusive memories observed clinically after traumatic events should be understood as a dysfunctional subclass of otherwise functional involuntary autobiographical memories. The adjacency mechanism is indifferent to content: it is the general case, operating continuously, mostly producing benign material. Freudian dynamics are a special case within it — the case where adjacently activated material carries enough affective charge to breach the frame of intention. The diagnostic criterion is the disturbance: if the arising disrupts the intentional sequence — hesitation, affect, derailment of the action — then the material may be repressed or suppressed, and its affective burden is the clinical signal. Freud was right about the phenomenon. The Adjacency model supplies a possible neurological mechanism.
Mark Solms has independently argued for grounding Freudian dynamics in the free energy principle — the same active inference framework used throughout this instrument. In The Hidden Spring (2021), he proposed that affect is not epiphenomenal but the primary form of consciousness: the organism's felt registration of prediction error. In The Only Cure (2026), he extends this argument, contending that neuroscience now confirms much of what Freud conjectured. Within the Adjacency model proposed here, Solms's framework is consistent and illuminating: when adjacently activated material carries affective charge, it carries unresolved prediction error — free energy that has not been minimised — and that is what breaches the frame. The disturbance is not a side effect; it is the primary datum. This instrument remains agnostic, as the parent paper does, on Solms's specific claim regarding the brainstem origin of consciousness (see Solms and Friston, 2018).
Three registers are shown. Fugitive activations decay within seconds and do not reach conscious access. Working memory events persist long enough to be available to attention. Consolidation events — the largest spikes, occurring at the Limit Condition — represent moments where the neuronal dynamics update the generative model: this episode is being encoded as a new prior, marginally reshaping the hippocampal model for the next cup of coffee. The coupling coefficients for future reaches are being recalibrated.
In the pre-state frame, pre-ignition events show hippocampal substrate activity warming before the intentional sequence opens, consistent with Christoff et al. (2009), who found hippocampal and default mode network activity preceding conscious awareness by several seconds in meditators observed under fMRI. The panel draws further on Frankland and Bontempi (2005) on systems consolidation, and on Baddeley's model of working memory and its neural implementations. The fugitive activation register is the most speculative element and is acknowledged as such.