Science

This note maps Baseworks mechanics onto established frameworks in movement science and neuroscience. The organizing principle is: Baseworks emerged from iterative refinement optimizing for communicability of movement; we are describing what emerged, why it works, and how it connects to existing science.

The scientific grounding here was significantly validated and refined through a meeting with Paul Cisek (January 2026) — the first substantive peer feedback on this work since the reverse engineering began in ~2016. Cisek’s affordance competition hypothesis is one of the central frameworks referenced. Where his input specifically shaped or validated a point, this is noted.

---

Part 1: Scientific Frameworks

Why These Frameworks

The frameworks below were selected because they address the specific problems Baseworks solves: how movements are selected and specified (Cisek), how redundant degrees of freedom are managed (Bernstein, UCM), how perceptual categories form (Grossberg), how skills develop (Fitts & Posner), and where conscious muscular sensation originates (Luu et al., Proske). They are not applied decoratively — each connects to a specific Baseworks mechanism.

1.1 The Motor Equivalence Problem (Bernstein, 1967)

Core idea: Any movement instruction under-specifies the movement because the body has far more degrees of freedom (DOF) than an instruction can constrain. The parameters not explicitly specified are filled in by the learner’s sensorimotor system based on existing habits and biases.

Why it matters for Baseworks: This is the foundational problem that communicability addresses. When an instructor says “tilt forward with a straight spine,” the learner’s motor system must resolve hundreds of unspecified DOF. Without perceptual access to those DOF, the learner cannot detect whether their execution matches the instruction. The motor equivalence problem is not just a theoretical concern — it is the daily reality of movement education, and it is the reason iterative refinement converged on the solutions it did.

1.2 The Affordance Competition Hypothesis (Cisek, 2007)

Core idea: The brain does not first perceive the world, then decide, then act in sequence. Instead, multiple potential actions (affordances) are simultaneously specified in frontoparietal cortex, and they compete for selection. The dorsal stream is not just about spatial vision — it is fundamentally about action specification.

Key details relevant to Baseworks:

• Frontoparietal cortex contains what Cisek calls “idiosyncratic maps” — specialized circuits adapted for different behavioral repertoires (reaching, grasping, locomotion, hand-to-mouth). Each map has its own spatial reference frame and its own relevant sensory inputs (Graziano’s action maps; Borra et al./Caminiti’s anatomical modules).
• These maps are not interchangeable. The reaching map cares about peripersonal space; the locomotion map cares about distant space and obstacles. They have their own descending projections to the spinal cord — they don’t all route through primary motor cortex.
• Habitual movement can be understood as falling into large attractors within these maps. Cisek described it as: “any nearby movement, you will just get pulled into doing that particular pattern.” This is not mere habit in the colloquial sense — it is a deep structural property of how frontoparietal circuits are organized.
• Cisek validation (Jan 2026): Cisek confirmed that the convergence on perceptual skill training through communicability optimization “makes sense” within his framework, though he noted he “wouldn’t have predicted it” — because his hypothesis addresses moment-to-moment action selection, not learning per se. He explicitly validated the idea that without perceptual differentiation, “nothing competes with nothing — it’s just one option.”

Connection to Baseworks:

• GS and FSA specify multiple simultaneous targets across the body, forcing multiple body points to become “specified targets” in frontoparietal space (Cisek’s term during the meeting). This is equivalent to expanding the task-relevant dimensions of the controlled manifold.
• DA+MM may work partly by preventing the suppression of competing movements. Cisek agreed with this interpretation: “So you mean because you’re preventing the suppression of all those moves.” This is a direct connection to basal ganglia gating mechanisms.
• The Baseworks training process can be understood as creating “new constellations” of frontoparietal maps that “have to work together” (Cisek’s phrasing) — analogous to how eye-hand coordination develops through necessity, but for body configurations that daily life never required to be coordinated.

1.3 Uncontrolled Manifold Hypothesis (Scholz & Schöner, 1999; Latash)

Core idea: In a high-dimensional movement space, variability is structured: the motor system allows variability along dimensions that don’t affect the task goal (the “uncontrolled manifold”) while constraining variability along dimensions that do matter. This is computationally efficient — you don’t waste control effort on DOF that are irrelevant to the current task.

Why it matters for Baseworks: This framework explains both the problem Baseworks addresses and the mechanism it uses:

The problem: In habitual movement, people specify only a few task-relevant variables (usually visually dominated — hand endpoint, gaze target) and allow all other DOF to vary freely. The trunk, pelvis, scapular position, ankle alignment — these all fall into the uncontrolled manifold. This is efficient for daily tasks but means people have no perceptual access to those dimensions and cannot detect errors in them.

The Baseworks solution: GS and FSA systematically move DOF out of the uncontrolled manifold and into the controlled space. By requiring that the pelvis stays parallel, the ribcage stays stacked, the arm line stays straight — simultaneously — the learner must control dimensions that are normally free. This forces the development of both the motor commands and the perceptual capacity to monitor those dimensions.

Cisek connection (Jan 2026): Cisek introduced this framework unprompted within the first 5 minutes of the conversation, saying “I think this is possibly related” and “I think it’s quite fundamental.” He connected it directly to Asia’s description of how people fail at Baseworks tasks: learners specify visually dominated variables and allow everything else to modulate. The framework was recommended for further study alongside the work of Gregor Schöner and Steve Scott (optimal feedback control).

Note on optimal feedback control: Cisek noted that the related framework of optimal feedback control captures a similar principle (defining the task in terms of control variables, and the system finds ways to use available DOF to solve it) but carries “extra baggage” in its specific mathematical optimization assumptions that may not be biologically plausible. The way the problem is defined in that framework is “very informative and insightful” even if the specific mathematics are debatable. For Baseworks, the relevant insight is: how you define the task (which variables matter) determines what gets controlled and what gets ignored.

1.4 Adaptive Resonance Theory (Grossberg, 1987, 2017)

Core idea: Conscious perceptual states arise through resonance — a stable, mutually reinforcing loop between bottom-up sensory signals and top-down expectations/categories. Mismatch between expected and actual sensory input drives learning (the “WHERE stream mismatch signal”).

Relevance to Baseworks:

• DA and MM continuously generate sensory input that can be compared against expected states. This amplifies mismatch signals — when the body is not in the intended configuration, the discrepancy between intended and actual proprioceptive input becomes detectable.
• The development of new perceptual categories (e.g., distinguishing gluteus medius from gluteus maximus as separate sensations, or distinguishing “pelvis parallel” from “pelvis tilted”) may follow ART-like dynamics: the category forms when there is enough sensory signal to sustain a resonance state.
• Grossberg’s observation that “any defined point could be moved” (in the context of motor planning) was a key insight for understanding Baseworks: the system extends the set of “defined points” from the typical few (hands, feet, head) to many points across the trunk and limbs.

Limitation noted by Cisek: Grossberg’s framework treats movement itself as non-conscious (a vector moving toward zero = mismatch reduction, not resonance). Cisek suggested that the consciousness question is “a bit of a black hole for theories” and that for practical purposes, what matters is whether people “are able to control certain aspects of their movement or not” — a more pragmatic framing. The question of whether proprioceptive position sense constitutes a resonance state remains theoretically interesting but is not essential for the practical science of Baseworks.

1.5 Fitts & Posner Three Stages of Motor Learning (1967)

Core idea: Motor skill acquisition progresses through cognitive → associative → autonomous stages. The autonomous stage is the goal of conventional training — smooth, effortless, automatic performance.

The Baseworks inversion: Baseworks deliberately returns practitioners to the cognitive stage for movements that are already autonomous. Basic movements (trunk rotation, knee bending, shoulder positioning) have been automated through millions of daily repetitions. Automaticity is efficient but creates a perceptual problem: we lose conscious access to movement details, embedding unconscious habits and compensatory patterns.

By decomposing familiar movements into micro-components and asking novel perceptual questions (“Are your arms truly aligned on one line?”), Baseworks forces the nervous system to engage with dimensions it has never needed to monitor. This is not “mindful movement” (passive awareness of existing sensations) — it is active development of perceptual capacities that did not previously exist.

Neuroplastic basis: Motor learning research demonstrates that physical training changes perceptual capacity, not just motor output. The classic Blakemore & Cooper (1970) finding — kittens raised with only horizontal stripes subsequently cannot perceive verticals — illustrates that sensory resolution is shaped by experience. If this applies to vision (our dominant sense), the effect should be magnified for somatosensation, which receives far less cultural and educational attention.

1.6 The Three Trainable Body Awareness Capacities: Framework Overview

Baseworks distinguishes three types of body awareness as distinct, differentially trainable perceptual capacities: Spatial Awareness, Localized Proprioceptive Awareness, and Interoceptive Awareness. These were identified through reverse-engineering of the outcome of the iterative refinement of the Baseworks Practice as practically separable categories — they fail differently in learners, require different training, and have different neural substrates. Focus on training these distinct capacities is what the method converged onto when continuously refined for better communicability of movement. This matters: a method optimized for different goals — retention rate, aesthetic appeal, emotional satisfaction — would likely converge on a different set of trainable capacities. The body awareness taxonomy reflects the specific optimization target of Baseworks, not a universal classification.

These three types are not an exhaustive taxonomy of all signals involved in movement. Many capacities (postural reflexes, vestibular balance, reflexive stabilization) contribute to movement without being foregrounded as separately trainable skills. The three types were identified because they represent clearly separable targets for deliberate perceptual training.

Each follows the same structure as the established proprioception / proprioceptive awareness distinction: there is an underlying system running continuously below consciousness, and there is awareness of it — trained, consciously accessible, and cultivated through practice. The goal of Baseworks is the awareness, not just the underlying system.

The three capacities are interdependent in practice. Localized proprioceptive awareness provides real-time sensory information that scaffolds spatial learning; interoceptive awareness maintains the self-regulatory conditions under which fine perceptual work is possible. The developmental direction tends to run from localized proprioceptive awareness (sensory signal detection) toward spatial awareness (configuration building and simulation), with interoceptive awareness as the ongoing substrate for both.

---

1.6a Spatial Awareness

The Baseworks definition — and how it diverges from conventional usage

Spatial awareness, as Baseworks uses the term, is the capacity to construct, maintain, and use a high-resolution body-space representation — including the relative positions of body parts, the space the body occupies and extends into, and the deployment of that representation for both physical and non-physical tasks.

This definition diverges significantly from what is typically meant by “spatial awareness.” In conventional usage, spatial awareness refers roughly to kinesthetic localization — knowing where your body is in space, particularly in relation to objects in the environment. The Baseworks definition includes this but extends it in two directions: toward the peripersonal space the body projects into and can consciously perceive, and toward the mental simulation of spatial configurations independent of any external task. This extension is not terminological — it reflects what training systematically reveals: the same neural substrate (PPC-mediated) underlies all three manifestations, and all three respond to the same training approach (spatial constraint + gravitational variation).

This capacity is modality-independent: built from proprioceptive, visual, vestibular, and auditory inputs, but the resulting representation is not reducible to any single modality. It is also not strictly a sensory capacity — it is representational and pre-planning-oriented. The trained state is not felt as a sensation (the way muscle activation is felt) but as a quality of spatial precision, readiness, and richness.

Three manifestations (all PPC-mediated):

1. Kinesthetic localization — the classical position sense dimension: knowing where limbs and body parts are without visual input, being able to produce or reproduce a body configuration without visual feedback, sensing the mutual positioning of multiple points simultaneously.

The empirical anchor is Proske & Weber (2026). Their repositioning paradigm — memorize a joint angle, reproduce it — reveals a mechanism that is gravity-independent and spindle-independent: unaffected by muscle thixotropy or altered gravity in parabolic flight. Proske terms this a “central memory mechanism” and explicitly acknowledges that how the memory is encoded, stored, and retrieved remains an open question. This placeholder framing is worth noting: “central memory mechanism” is a functional description by a spindle specialist who identified something beyond his field’s established vocabulary — not a mechanistic explanation. The mechanism is better addressed by predictive processing frameworks (§1.15). Whatever the theoretical framing, the empirical finding stands: there is a central, non-peripherally-driven system for encoding and reproducing body configurations, and its accuracy improves with longer encoding exposure (Goble, 2010) — directly supporting the Baseworks practices of slow movement, deliberate dwelling in positions (DA+MM), and spatial constraints that require precise positioning (GS, FSA).

Note: Proske’s repositioning method involves active reproduction (the arm returns passively to start, then the subject actively repositions it). This is analogous to Baseworks tasks — passive initial demonstration, active reproduction — confirming the direct relevance.

2. Peripersonal space and the extended body schema — the spatial representation does not end at the skin. The brain represents the space immediately surrounding the body in a multisensory, body-relative coordinate system (Graziano et al., 1994; Rizzolatti & Luppino, 2001). This peripersonal representation is plastic — it extends to encompass tools during skilled use, contracts under threat, and is organized around effector-specific action zones.

Importantly, the peripersonal space (PPS) is not a single unified coordinate system. Evidence from neurophysiology and psychophysics points to multiple PPSs organized around the needs and affordances of different effector systems: face-defensive space, hand-manipulation space, arm-reaching space, and others (Trends in Cognitive Sciences, 2018). This plurality directly maps onto Cisek’s idiosyncratic frontoparietal action maps (§1.2) and Graziano’s action zones in primate motor cortex (§1.10): different effectors maintain dedicated spatial representations that are normally loosely coupled and action-specific. The PPS literature itself acknowledges this fragmentation — many papers open by noting the field lacks consensus on how many PPSs there are, where their boundaries lie, and how they relate. This may partly reflect the same epistemological problem as muscular mechanosensation research (§3.2): studying a phenomenon in subjects who have little conscious access to it makes it difficult to characterize.

For Baseworks, this heterogeneity matters in two ways:

First, GS-based training with allocentric reference frames — gridlines imposed across the whole body simultaneously — may specifically function to integrate these normally action-specific PPSs. “Teaching the idiosyncratic maps to talk to each other” (Cisek’s phrasing, §1.2, endorsed during the January 2026 meeting) is not just metaphor: if the face-defensive map, hand-manipulation map, and trunk-postural map are normally activated in isolation, then training that requires simultaneous spatial specification across all body regions may create integrative representations that habitual movement never requires. Action maps form through what Grossberg (§1.4) calls circular reactions — repeated act-sense-adjust cycles — and GS training applies exactly this mechanism systematically across all body regions simultaneously.

Second — and this distinction is critical — the Baseworks training goal is not functional PPS competence. Everyone has operational PPS: object manipulation, protective flinching, rough awareness of limb positions all work fine without training. What Baseworks cultivates is spatial awareness of the peripersonal space — consciously accessible, refined, aesthetically salient. In the trained state, the spatial field the body projects into becomes an object of awareness in itself, not a background computational resource. What practitioners describe as “feeling the space,” or the sense of the body schema extending outward, is this cultivated conscious access — the PPS analogue of proprioceptive awareness as distinct from proprioception.

3. Mental spatial simulation — the body schema as a coordinate system for non-physical tasks. Mental rotation tasks (Shepard & Metzler, 1971) show that spatial transformation of objects is performed through simulated motor actions, sharing neural substrates with actual movement execution. Working memory for spatial content relies on partially-expressed motor predictions in frontal-parietal systems — what Baddeley’s model calls the visuospatial sketchpad (§1.15). Mnemonic techniques that map content onto body positions exploit this directly: a well-trained body schema is a high-resolution, stable spatial coordinate system the brain uses constantly, so content mapped onto it benefits from that existing infrastructure.

In this third manifestation, spatial awareness extends into mentally constructed space — but the body-relative reference frame remains the foundation. A more precisely trained body schema provides more stable reference points, more differentiable positions, and a richer substrate for spatial simulation and working memory.

The common neural substrate:

All three manifestations involve posterior parietal cortex (PPC) — particularly areas involved in spatial working memory, visuospatial processing, action specification, and peripersonal space encoding. This is why the three manifestations are treated as a single trainable capacity: they engage the same neural machinery at different scales and on different inputs. This PPC substrate overlaps with the visuospatial sketchpad of working memory and the dorsal stream spatial processing discussed in §2.6. The modality-independence of spatial awareness reflects PPC’s integrative function: it receives proprioceptive, visual, vestibular, and auditory input and maintains a stable spatial reference frame not reducible to any one modality.

Counterfactual richness — the trained phenomenological dimension:

At high levels of training, spatial awareness acquires a dimension that is neither purely sensory nor purely motor: the immediate action possibility space becomes directly perceptible. This is not simply knowing where you are — it is simultaneously sensing which precise movements are available from here, as a background readout rather than an explicit calculation.

Within Cisek’s affordance competition framework (§1.2), multiple potential actions are continuously specified in frontoparietal cortex and compete for selection. At low training levels, this competition involves a small set of coarse macro-movement candidates. As the body-space representation becomes more precise — as more degrees of freedom are encoded in the central representation at higher resolution — the competition involves many more, much finer candidates. The felt quality of spatial readiness that experienced practitioners describe is the conscious correlate of this expanded, finer-grained candidate set.

Safron (2021) supplies the appropriate term: counterfactual richness — “the extent and variety of evoked affordance-related predictive abilities” that determine the quality of agency and presence (§1.15). A more precisely trained body-space representation generates a richer set of counterfactual configurations — states not currently realized but immediately actionable. This is the motor/planning dimension of what Baseworks calls sensory resolution: where localized proprioceptive awareness involves a more differentiable map of real-time sensory signals, counterfactual richness involves a more differentiable map of action possibilities. The two are the sensory and motor sides of the same trained resolution.

The STRUCTURE/GRAVITY pairing as spatial awareness training:

Baseworks practice systematically pairs two types of constraints: STRUCTURE (alignment, symmetry, gridlines — specifying what the body configuration should be) and GRAVITY (the context of loading — standing, plank, inclined, inverted). The pairing is not incidental. The goal is to develop the capacity to achieve and maintain the same body configuration across different gravitational contexts. The Plank, for instance, is not a strength exercise in the Baseworks context — it is a spatial awareness exercise. The practitioner must replicate in a horizontal, loaded position the same configuration of body segments that can be achieved standing on two legs.

Proske’s finding that the central repositioning mechanism is gravity-independent (while spindle-based methods are not) provides direct support for this approach. If the central mechanism is what Baseworks calls spatial awareness, then practicing configuration-matching across gravitational contexts is specifically exercising that central, gravity-independent representational capacity — not the peripheral spindle system. The STRUCTURE focus (what configuration to achieve) trains the content of the central representation; the GRAVITY variation (across which contexts it must be achieved) trains its robustness and generalizability.

Similarly, GS principles (gridlines, symmetry requirements, alignment specifications) are primarily tools for training spatial awareness: they provide allocentric reference frames that allow practitioners to specify and verify body configurations in terms that don’t depend on having the localized proprioceptive sensation yet. A practitioner can learn to use spatial reasoning — “my shoulder should be over my wrist, my hip should be over my ankle” — as an external scaffold while the internal sensory capacity is still developing.

The developmental relationship between spatial and proprioceptive awareness:

From applied experience: localized proprioceptive awareness supports the development of spatial awareness at the training phase. If a practitioner can consciously sense what a muscle is doing — its activation level, its direction of pull — they have real-time sensory information that can be used to calibrate the central body model. This is not to say the two capacities are equivalent: spatial awareness is representational and pre-planning-oriented; localized proprioceptive awareness is real-time and sensation-based. But in the context of learning, the sensory signal scaffolds the representational capacity. This is consistent with Goble’s finding that more encoding time improves repositioning accuracy — it suggests the central model can be enriched by sustained sensory engagement with a position, not just by being placed in it.

DA+MM (distributed activation + micro-movements) are the primary training tools for localized proprioceptive awareness. GS+FSA (grid system + form sequencing approach) are the primary tools for spatial awareness. But in practice, DA is always present during GS-based work — precisely because the sensory scaffold supports the spatial learning.

[SPECULATIVE] Spatial awareness training and visuospatial cognition:

The central body-configuration representation underlying spatial awareness is almost certainly implemented in PPC, the same substrate as the visuospatial sketchpad (Baddeley’s model) and the dorsal stream spatial processing discussed in §2.6. This raises a speculative but testable hypothesis: systematic Baseworks positional training may constitute a form of training for PPC-mediated spatial working memory more broadly. The mechanism — via partially-expressed motor predictions (§1.15) — is mechanistically plausible and directionally specific: it predicts transfer to the specific sub-type of cognition grounded in the same PPC/frontal-parietal substrate as spatial body-map encoding, not to general cognitive improvement. From personal experience (Asia): a subjective shift from linguistic to spatial strategies in tasks with spatial solutions (e.g., physics problems) over ~9 years of Baseworks training — n=1, uncontrolled, not an advertised outcome. See §3.6 for the formal open question and proposed experimental design.

Research implication — the Abi Chebel critique:

From Proske & Weber: A 2022 study found differences in repositioning accuracy between forearm and wrist and attributed them to differences in spindle counts across joints. Proske & Weber critique this: if repositioning is centrally mediated, spindle counts cannot explain the results. The interpretation should be that central representations of the wrist (trained by extensive fine motor use throughout life) are richer than central representations of the elbow — fully consistent with the Baseworks framework. Applied implication: if subjects trained in deliberate elbow micro-control were tested, the pattern might differ, pointing to central representation as the variable rather than peripheral anatomy.

---

1.6b Localized Proprioceptive Awareness

The Baseworks definition: Localized proprioceptive awareness is the conscious awareness of spatially specific sensations arising from muscle spindles and intensified with muscle activation (§1.7) — the real-time, localizable signal that allows moment-to-moment detection of what a specific body region is doing. Phenomenologically similar to touch, but arising from inside the muscle rather than from the skin.

Relation to Proske’s matching/pointing domain:

This capacity is closer to Proske’s matching and pointing domain: live spindle-mediated afference that is disrupted by peripheral conditions (thixotropy, gravity changes). However, localized proprioceptive awareness is more specific than what Proske’s matching/pointing tasks measure. Those tasks measure position sense as a synthesized percept — the brain’s overall sense of where a limb is. Localized proprioceptive awareness as Baseworks uses the term focuses on the consciously localizable sensations within the muscle itself — the unnamed sensation described in mystery-of-proprioceptive-awareness and potentially traceable to fusimotor reafference (Luu et al., 2011). Proske’s matching/pointing domain is the broader category; localized proprioceptive awareness as Baseworks uses it is a subset — real-time, consciously accessible, spatially specific, and trainable.

Summary mapping:

Baseworks term	Proske mechanism	Character
Spatial awareness	Central/memory (repositioning)	Representational; pre-planning; gravity-/spindle-independent; trainable through exposure duration
Localized proprioceptive awareness	Spindle-based (matching/pointing domain)	Real-time afferent; disrupted by peripheral conditions; trainable through perceptual practice

Within this framework, localized proprioceptive awareness refers specifically to the conscious, spatially localized sensation arising from muscle activation — phenomenologically similar to touch but arising from inside the muscle rather than from the skin. The most likely neural basis is fusimotor drive: the reafferent signal from intrafusal fiber contraction (Luu et al., 2011), which constitutes a kind of sensing of ongoing muscle tone. It is not the same as the synthesized percept of body position (which can occur without this sensation, as Proske’s central repositioning mechanism demonstrates). The Baseworks claim is specific: training the ability to consciously detect this sensation — lowering the threshold for its perception — is a trainable skill that accelerates motor learning. It is possible to sense the approximate position of a body segment without access to this localized sensation; the localized sensation is most valuable as a scaffold for developing and refining the central body model.

Note: Fusimotor drive = efferent/descending command to gamma (γ) motor neurons → intrafusal fibers Reafference (Luu’s usage) = ascending afferent signals that result from a motor command you issued. In Luu’s specific model: gamma co-activation during voluntary contraction causes intrafusal shortening → spindle discharge → that ascending signal is the “reafference.” Von Holst’s original concept extends to all receptor systems: any afferent signal caused by your own motor output is reafference. Critical distinction: “Fusimotor reafference” only exists when you are actively contracting (alpha-gamma coactivation). At rest, with no gamma drive, there is no fusimotor component to any sensory signal. The resting tonic spindle discharge is not reafference — it is passive exafference from resting stretch.

Research implication — movement detection threshold:

Proske & Weber note that spindle deterioration in aging raises the movement detection threshold, causing body sway to exceed instability limits more frequently. This is the same concept Baseworks calls perceptual resolution. Open question: can voluntary, attentional training of micro-movement detection (Baseworks MM) contribute to upregulating the automatic spindle-based monitoring that Proske associates with postural stability? This is unresolved; the functional overlap warrants experimental investigation.

For detailed spindle physiology, intrafusal fiber types, afferent classification, survey data on individual variation, and the phenomenological analysis of the resting “hum,” see §1.7 and spindle-physiology-and-phenomenology.

---

1.6c Interoceptive Awareness

The Baseworks definition: Interoceptive awareness is the conscious awareness of sensations related to internal organ functioning, stress, emotions, and metabolic changes. The Baseworks framework for this capacity is directly aligned with Price & Hooven (2018): interoceptive awareness as a trainable perceptual skill, extending Craig’s (2002) interoception into explicit, cultivated conscious access. This is the type of body awareness that most closely overlaps with the existing research literature — see §1.14 for the relation to the Mehling tradition.

Why it belongs in the body awareness framework:

Interoceptive awareness is the self-regulatory substrate on which fine perceptual work depends. A practitioner who cannot monitor their own arousal, stress, and fatigue states cannot maintain the conditions (NB, IM) in which proprioceptive and spatial discrimination are possible. It is not a movement capacity in the direct sense; it is the prerequisite for the attentional conditions that make sustained movement learning possible.

In Baseworks practice:

NB (Natural Breathing) functions as a continuous interoceptive monitoring task — the practitioner must continuously evaluate whether breathing remains conversational. IM (Intensity Modification) requires monitoring internal signals (fatigue, compression, loss of precision) and adjusting behavior in real time. Both train the conscious interoceptive monitoring skill in Price & Hooven’s sense.

References: Price CJ, Hooven C. Interoceptive awareness skills for emotion regulation: theory and approach of MABT. Front Psychol. 2018;9:798. Craig AD. How do you feel? Interoception: the sense of the physiological condition of the body. Nat Rev Neurosci. 2002;3(8):655–666.

Reference added to References section below.

---

1.7 Spindle Afference and the Origin of Muscular Sensation (Luu et al., 2011; Macefield, 2018)

Core idea (Luu et al., 2011): The sense of exerted force and heaviness is largely derived from peripheral afferent inflow — specifically, ascending signals from muscle spindles — rather than from central efference copy alone. This challenges the traditional view that muscle spindles only signal limb position and movement.

Why it matters for Baseworks: This provides the best available explanation for what practitioners experience as “muscular mechanosensation” — localized sensations arising from muscle state that have no established scientific name.

The mechanism during active contraction: When a muscle contracts voluntarily, alpha-gamma coactivation drives both extrafusal fibers (producing force) and intrafusal fibers (maintaining spindle sensitivity). The resulting spindle afference — Group Ia and II fiber discharge — scales with contraction strength and constitutes reafference related to the motor command. This signal is available for conscious processing and is what practitioners may detect as localized muscular sensation during contraction.

The mechanism at rest: A subset of muscle spindles — particularly Group II secondary endings on nuclear chain fibers — maintain a tonic, regular discharge at rates proportional to current muscle length even in the complete absence of fusimotor drive. This has been confirmed by recordings in spinal cord injury patients, who show identical resting spindle discharge to intact subjects (Macefield, 2018). This passive, fusimotor-independent discharge represents a continuous signal of the mechanical state of each spindle — how taut or slack each small region of muscle is at that moment.

Two distinct signal components: The conscious sensation of muscular “tone” or background “hum” — if it exists as a distinct percept — likely reflects two separable contributions:

• Resting baseline: passive Group II tonic discharge, present at rest and proportional to muscle length; fusimotor-independent
• Contraction-proportional component: spindle reafference scaling with effort via alpha-gamma coactivation (Luu et al., 2011), plus Golgi tendon organ discharge proportional to active force

Key observations from Baseworks context:

• Only ~43% of surveyed non-practitioners report awareness of muscular sensations at rest; ~48% during exercise. This suggests large individual variation in conscious access to this signal.
• Proske (personal communication to Asia) confirmed he does not feel sensations in relaxed muscles and is not aware of literature on constant conscious muscular sensations — suggesting this is a genuine gap in the field.
• Dancers and trained movement practitioners commonly report feeling muscle state continuously — consistent with trained conscious access to ongoing spindle afference.
• The blind participant in Asia’s survey reported the highest intensity of muscular sensation at rest — potentially because reduced visual dominance allows greater cortical resources for somatosensory processing.

Connection to DA and MM: Distributed Activation deliberately co-contracts many muscles simultaneously at low intensity. This increases alpha-gamma coactivation across the activated muscles, elevating spindle afference above resting levels and making it more available for conscious processing. Micro Movements maintain continuous variation in this signal, preventing the sensory adaptation that occurs with static states. Together, DA+MM may function as a strategy for making existing spindle signals — both the passive Group II background and the effort-proportional reafference — more consistently accessible to conscious attention.

For detailed spindle physiology, intrafusal fiber types, afferent classification, and the phenomenological analysis of the “hum” percept, see spindle-physiology-and-phenomenology.

1.8 The Somato-Cognitive Action Network and the Baseworks Effector Model (Gordon et al., 2023)

The paper: Gordon EM, et al. “A somato-cognitive action network alternates with effector regions in motor cortex.” Nature, 2023; 617:351–359.

Core finding: Primary motor cortex (M1) is not a continuous homunculus (Penfield’s model) but instead two interleaved systems:

• Effector-specific regions (foot, hand, mouth): three discrete zones with strong somatotopic organization, highly movement-specific activation, and connectivity restricted to homotopic contralateral M1 and adjacent S1. These handle fine, isolated motor control of specialized appendages.
• Inter-effector / SCAN regions: three zones interdigitated between the effector-specific areas, strongly connected to each other (bilaterally), and to the cingulo-opercular network (CON), SMA, cerebellar vermis, thalamic motor nuclei (VIM, CM), and dorsal putamen. These regions are non-specific for movement type, are active during axial movements (abdominal flexion, eyebrow raising), action planning (especially coordinated multi-limb movements), and are the regions where action-planning signals arrive before the effector-specific regions.

The authors term this the Somato-Cognitive Action Network (SCAN) and describe M1’s organization as an integrate–isolate dual system: effector-specific regions for isolating fine motor control; SCAN for integrating goals, physiology, and whole-body movement.

Why this finding is not surprising from a Baseworks perspective:

The three dominant effectors in the Gordon et al. model — foot, hand, mouth — reflect the behavioral repertoire of a typical untrained person performing daily life tasks. These are the endpoints that habitual, inverse-kinematics-dominated movement specifies. Penfield’s stimulation map overrepresented these because his patients were people whose behavioral repertoire was dominated by manual manipulation, locomotion, and speech.

From the Baseworks framework, this maps directly onto the distinction made explicit in the Cisek MTG slide (Goal Setting / Action Specification, slide 5): habitual movement uses a small set of dominant effectors (head, hand, leg — approximately the SCAN foot/hand/mouth effector-specific circuits), while Baseworks training distributes intentional control across many more body points. The blue-dot Baseworks diagram on that slide is essentially a visual prediction of what the SCAN paper confirms neuroanatomically: there is a whole-body integration network (SCAN/inter-effector) that is underutilized in habitual movement but is structurally present and trainable.

The second point about M1-as-keyboard: the somatotopy assumption (each M1 region maps to specific muscles) is undermined by the inter-effector finding. The SCAN regions are active across diverse movements, are connected to autonomic and physiological regulation circuits (adrenal medulla, CON), and have bilateral spinal cord projections rather than the contralateral, effector-specific projections of posterior M1. This is consistent with the well-established fact that any goal-directed movement requires postural preparation across the entire body — lifting an arm requires stabilizing the trunk, pelvis, and contralateral leg. The SCAN system, not the effector-specific system, is the substrate for this whole-body preparatory and integrative function.

Connections to Baseworks mechanisms:

GS+FSA as SCAN training: The GS principle (gridlines, symmetry, alignment) requires continuous monitoring and adjustment of axial body configuration — trunk position, pelvis orientation, ribcage stacking — precisely the domain the SCAN/inter-effector system is specialized for. The FSA principle forces sequenced attention to each body region, moving control up the kinematic chain rather than relying on effector-endpoint specification. Both systematically exercise the integrate function of the integrate–isolate system.

DA as inter-effector system priming: Distributed Activation creates simultaneous low-level activation across many body regions, including trunk, pelvis, scapular, and limb muscles that are normally in the uncontrolled manifold. This may prime the SCAN network specifically, since SCAN regions are active during axial movement and multi-effector coordination — exactly the kind of whole-body distributed activation that DA produces.

The SCAN–Baseworks alignment: The paper’s description of SCAN as enabling “pre-action anticipatory postural, breathing, cardiovascular and arousal changes” and integrating “body control (motor and autonomic) and action planning” maps closely onto what Baseworks produces experientially: practitioners report improved postural organization, breathing integration with movement, and a sense of whole-body coordination that is distinct from individual effector skill. This experiential shift may reflect increased engagement and development of SCAN circuitry.

Parkinson’s disease note: The authors flag that Parkinson’s symptom profile — postural instability, autonomic dysfunction, reduced self-initiated activity — mirrors SCAN connections. If DA partially bypasses basal ganglia suppression (§1.9), and SCAN connects to the same thalamic targets affected in Parkinson’s (VIM, CM), there may be a clinically relevant intersection worth exploring.

Reference added to References section below.

---

1.9 Two-Arm Matching, Bilateral Proprioceptive Coupling, and the Symmetry Principle (Proske & Weber, 2026; Baseworks applied observation)

Proske’s two-arm matching task — bringing one arm to the position where the other is perceived to be — is spindle-dependent (disrupted by thixotropy and gravity changes; §1.6). The fact that this task is possible and accurate under normal conditions implies an active neural mechanism for cross-body proprioceptive comparison: the brain maintains bilateral reference frames and can use one limb’s position signal to specify a target for the other.

This mechanism — interlimb proprioceptive coupling — has direct relevance to how the Baseworks symmetry principle is applied in injury and limitation contexts.

The applied case: In a form like Star (arms extended at shoulder height), a practitioner with an acute shoulder injury on one side will typically adopt a compensatory strategy: the instructed (healthy) arm completes the movement while the injured arm defaults to a protected, lowered position. The result is asymmetry and compensatory loading. The Baseworks go-to response in this situation is the reverse: instruct the healthy arm to adopt the same position as the injured arm — deliberately matching the limited range rather than the ideal instructed range.

Why this is mechanistically sound: This instruction is exploiting the bilateral matching mechanism Proske’s research confirms. Rather than using the central body model to specify the ideal position and having one limb fail to achieve it, the instruction asks the healthy limb to use its live proprioceptive matching capacity to reference the injured limb. The central representation is updated to a symmetric configuration that is achievable, rather than an asymmetric compensation that embeds the injury pattern.

This is not merely injury management. The broader principle is: symmetric configurations are neurally privileged because bilateral matching is a built-in mechanism. When any asymmetry is present — whether from injury, habit, or structural difference — instructing symmetry leverages this mechanism to produce a body-configuration representation that is coherent and reproducible rather than compensatory and drifting.

Connection to SCAN: The SCAN inter-effector regions are specifically active during coordinated multi-limb movements and action planning (§1.8), not during isolated single-limb movements. Bilateral symmetric movement is exactly the kind of cross-effector coordination that engages inter-effector SCAN circuits rather than effector-specific circuits. Instructing symmetry is thus not just a proprioceptive strategy — it may specifically recruit the whole-body integration network.

Connection to spatial awareness (§1.6): The Proske central memory mechanism underlying spatial awareness is the substrate for the body-configuration representation that symmetric instruction is updating. When a practitioner learns to maintain bilateral symmetry, they are training the quality and coherence of their central body model — making the simulation capacity described in §1.6 more accurate and more reliably achievable across conditions.

Note on future investigation: Proske’s matching paradigm provides a ready experimental design for testing this applied observation. Comparing repositioning accuracy (central mechanism) and matching accuracy (spindle-based mechanism) in Baseworks-trained vs. untrained subjects, with specific attention to bilateral symmetry of errors, could directly test whether training changes the central body model independently of peripheral proprioceptive function.

---

1.10 Synergies and the Cortical Organization of Movement (Graziano; Borra/Caminiti)

Core idea: Motor cortex is not organized as a simple body map (homunculus) but as a patchwork of adapted high-level synergies — ecologically relevant movement patterns (hand-to-mouth, defensive movements, reaching, locomotion). Stimulating a cortical patch produces a complete coordinated movement, not just a muscle twitch.

These synergies form a behavioral repertoire (Cisek’s term: what Baseworks calls “movement vocabulary”). Different synergy modules have their own idiosyncratic spatial reference frames, their own relevant sensory modalities, and even their own descending pathways to spinal cord — not all routing through M1.

Relevance to Baseworks:

• Habitual movement defaults to existing synergies. “Any nearby movement, you will just get pulled into doing that particular pattern” (Cisek). This is why novel Baseworks configurations feel difficult — they don’t correspond to any existing high-level synergy.
• The “sensation splitting” phenomenon (where practitioners report muscular sensations “shifting under the skin” as previously unified muscle groups become perceptually distinct) likely reflects cortical remapping. Cisek suggested this could be experimentally tested with TMS — mapping motor output from a cortical site before and after training, as in the Classen et al. studies showing rapid reorganization of preferred movement direction.
• Cisek noted that what Baseworks calls “movement vocabulary” is essentially what Graziano calls “repertoire” — confirming terminological alignment.
• The Baseworks approach of enforcing a unified external grid across all body points may be understood as “teaching the idiosyncratic maps to talk to each other” (Asia’s formulation, which Cisek endorsed) — creating new constellations of coordinated activity across circuits that normally operate independently.

1.11 Basal Ganglia: Action Selection and Gating

Role in Baseworks context: Basal ganglia receive cortical input (not raw sensory input) and are involved in action selection, reinforcement learning, and commitment to action. The direct/indirect pathway architecture means that when a movement is selected, competing movements involving the same muscles are suppressed.

Key hypothesis: DA may work partly by circumventing basal ganglia suppression. When muscles are already consciously activated (via DA instructions like “pull the legs away,” “draw the shoulders down”), they are not being suppressed as competing actions. This may create a state where it is easier to perform novel motor combinations because the relevant motor units are already cortically engaged. Cisek agreed: “So you mean because you’re preventing the suppression of all those moves.” — “Yes, exactly.”

Cisek’s current view on BG (from meeting): Basal ganglia may be doing high-level selection between behavioral systems (reaching mode vs. locomotion mode) rather than fine-grained movement selection. The massive convergence from cortex (30,000:1) and the broad thalamic projections back suggest low resolution — more about “opening gates” than specifying details. This is relevant because it suggests that the fine-grained movement specification that Baseworks targets happens primarily in frontoparietal cortex, with basal ganglia playing more of a permissive/gating role.

Note: Cisek acknowledged that basal ganglia function remains contested (“you and the rest of the world” trying to understand what they do moment-to-moment). The hypothesis about DA reducing BG suppression is plausible but awaits direct experimental evidence.

1.12 Forward vs. Inverse Kinematics

Standard movement planning typically uses inverse kinematics: define an endpoint target, compute the joint angles needed to reach it. This is efficient but leaves most of the body unspecified.

Baseworks uses forward kinematics (FSA): Move one joint at a time, in a specified sequence, observing what happens at each step. There is no pre-defined endpoint target — the “next target position is just a little bit next version of this movement” (Asia, in Cisek meeting). Combined with IM rules for when to stop (pain, loss of form, breathing change), this creates a movement structure that requires continuous monitoring rather than ballistic execution toward a target.

Connection to the direct model (Grossberg/Bullock): Cisek noted that the “direct model” captures how a redundant system can learn to reach any target through feedback-driven circular reactions — the same mechanism infants use. If you define the effector as the finger, the finger reaches the target; if you define it as the nose, the nose does. Baseworks extends this principle: by defining multiple reference points simultaneously, it creates a multi-target control problem that develops the monitoring capacity for all involved body segments.

1.13 Neuroplasticity Principles (Kleim & Jones, 2008)

The following principles of experience-dependent neuroplasticity are specifically addressed by Baseworks design:

• Repetition matters: Baseworks ensures that exercised movements are indeed repeated (not unconsciously substituted with habitual fillers) through precise, consistent instructions across sessions and instructors.
• Salience matters: DA+MM bring awareness to sensory signals; GS+FSA define spatial goals that require active monitoring — preventing mindless mechanical repetition.
• Transference: Movements are strategically selected for transfer to daily and athletic contexts.
• Interference: The method explicitly highlights when habitual execution must be overridden (“NOT” instructions in the WHILE-NOT-IF-DO algorithm).

1.14 Body Awareness Frameworks and the Mehling Tradition

The field: The most systematic body of research on body awareness as a multi-dimensional construct comes from Wolf Mehling and colleagues at UCSF (Mehling et al., 2009, 2011) and from Cynthia Price’s work on interoceptive awareness as a trainable skill (Price & Hooven, 2018; Price, 2005). These represent the scientific neighborhood closest to what Baseworks addresses. Understanding where Baseworks aligns with and departs from this tradition is important for positioning the research.

The Mehling tradition — what it covers:

Mehling et al. (2009) reviewed existing body awareness assessment tools and found the construct was poorly defined and conflated across dimensions. Their working definition: body awareness is “the subjective, phenomenological aspect of proprioception and interoception that enters conscious awareness, and is modifiable by mental processes including attention, interpretation, appraisal, beliefs, memories, conditioning, attitudes and affect” (Mehling et al., 2011).

Their 2011 phenomenological study gathered experienced practitioners of yoga, Feldenkrais, Alexander technique, MBSR, Somatic Experiencing, Breath Therapy, Tai Chi, and massage in focus groups. The common ground these practitioners shared:

• Body awareness is inseparable from self-awareness; several practitioners explicitly resisted the term “body” (“Feldenkrais himself would never use the word ‘body’ — it was always self-awareness”)
• Awareness is primarily attitudinal: non-judgmental, accepting, present-moment, open — a quality of relationship to sensation rather than a sensory capacity per se
• Common practice elements: breath, repetition and training, noticing/discriminating sensations, mind-body integration in daily life
• Therapeutic goal: integration of mind, body, and life context; resuming an “embodiment process” that has been disrupted

This tradition also underlies the Body Awareness Therapy (BAT) and MABT clinical programs, which have been studied for chronic pain, PTSD, eating disorders, and related conditions. CJ Price, co-author on Mehling 2009 and 2011, developed the MABT interoceptive awareness protocol and is the first author on the Price & Hooven 2018 paper that Baseworks uses for the interoceptive awareness component.

Where Baseworks aligns:

The Baseworks interoceptive awareness component is explicitly aligned with the Price & Hooven framing: interoceptive awareness as “conscious awareness of sensations related to internal organ functioning, stress, emotions, and metabolic changes” — a trainable perceptual skill in the sense of Craig’s interoception extended to practice (Price & Hooven, 2018). This overlap is genuine and should be acknowledged in any scientific communication.

The general emphasis on repetition and training, and on discriminating sensations through deliberate practice, is also shared.

Where Baseworks departs:

The Mehling tradition names both proprioception and interoception in its definition — but in practice reduces almost entirely to interoception and to the attitudinal dimension of awareness. The sensorimotor capacities remain absent:

Proprioceptive awareness — the ability to consciously detect, localize, and distinguish sensations arising from muscle activation — is not developed as a distinct trainable dimension anywhere in the Mehling framework. In Mehling’s 2009 assessment tool review, proprioceptive content appears only as a proxy for psychological distress (“awareness of tension in my muscles”) — not as a neutral or positive sensory capacity in its own right.

Spatial awareness — the capacity to encode, maintain, and reproduce body configurations; the central memory/prediction mechanism (Proske & Weber, 2026) — has no representation in this literature at all.

Both of these capacities are directly relevant to motor learning, movement communicability, and the development of practical movement skill — and both are absent from the Mehling framework not because they are unimportant, but because the framework was developed entirely in therapeutic and mind-body practice contexts where fine motor learning is not the primary goal.

The attitudinal vs. discriminative distinction:

The Mehling tradition treats improved body awareness primarily as a shift in relationship to sensation — learning to observe without judgment, to accept rather than catastrophize, to remain present with discomfort. This is appropriate for its clinical contexts.

Baseworks treats body awareness primarily as discriminative capacity — detection threshold, perceptual resolution, the ability to differentiate between adjacent sensations. The question is not whether a sensation is accepted but whether it can be detected, localized, and used. This is closer to how perceptual learning research defines awareness: a trainable, measurable sensory capacity with a psychophysics.

These are not mutually exclusive — both attitudinal and discriminative dimensions are real — but they have different targets, different training approaches, and different outcome measures.

The clinical connection:

Baseworks works primarily with movement practitioners and healthy adults across a wide range of training backgrounds — from novices to professional movement teachers (for whom Baseworks functions as a calibration and gap-filling tool, surfacing control dimensions their primary practice doesn’t address). However, Baseworks also has observational, non-systematic experience with participants presenting with PTSD, autism, anorexia, Sensory Processing Disorder, and conditions involving dissociation.

In many of these cases, the existing trauma-informed movement field offers body awareness practices in the Mehling/Price mold: breath focus, parasympathetic regulation, non-judgmental attention. These are appropriate for what they do. But they are not offering skill-building in the sensorimotor domain.

Baseworks observation: low body awareness in the Baseworks sense — inability to detect or localize muscle sensations, poor spatial representation capacity — can be present in these populations and can itself be a meaningful therapeutic target. When movement instruction fails with these participants, it often fails for the same reason it fails with any learner who has low sensory discrimination capacity: the instruction simply doesn’t produce the intended movement. Building the capacity may be therapeutic, not as a substitute for trauma-informed care, but as a complement to it.

This is based on anecdotal and observational data only. No controlled studies. The claim is not that Baseworks is a therapy — it is that sensorimotor skill-building may be a missing component in what is currently offered, and that this is a research question worth pursuing. The BRNet 2026 presentation is partly motivated by the goal of making contact with researchers and clinicians who work in this space.

The CJ Price thread:

The Mehling-to-Baseworks bridge most worth tracking is through CJ Price. Price moved interoceptive awareness from a vague construct (“body awareness includes our feelings”) toward a specific trainable skill with a neural substrate and a clinical protocol (MABT). Baseworks is making the same move in adjacent territory: proprioceptive awareness and spatial awareness as trainable skills with neural substrates and pedagogical protocols. The Baseworks framework can be understood as extending the Price move into the sensorimotor domain that Price’s own work (interoceptive awareness) left outside its scope.

References added:

Mehling WE, Gopisetty V, Daubenmier J, Price CJ, Hecht FM, Stewart A. Body awareness: construct and self-report measures. PloS ONE. 2009;4(5):e5614.

Mehling WE, Wrubel J, Daubenmier JJ, Price CJ, Kerr CE, Silow T, Gopisetty V, Stewart AL. Body Awareness: a phenomenological inquiry into the common ground of mind-body therapies. Philos Ethics Humanit Med. 2011;6:6.

Price CJ, Hooven C. Interoceptive awareness skills for emotion regulation: theory and approach of mindful awareness in body-oriented therapy (MABT). Front Psychol. 2018;9:798.

(Note: Mehling 2009 and 2011 were already in the references section below. Entries consolidated there.)

1.15 Embodied Self-Models, Active Inference, and Counterfactual Richness (Safron, 2021)

The paper: Safron A. “The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again.” Entropy, 2021; 23, 783.

Status note: This is a theoretical synthesis, not an empirical paper. It is cited here for two specific contributions: the concept of Embodied Self-Models (ESMs) as a theoretical framework for understanding what Proske calls the “central memory mechanism,” and the term counterfactual richness as the most precise available description of the trained outcome of spatial awareness development. The empirical grounding for these ideas is stronger in Friston’s primary work on active inference and proprioceptive prediction (Friston, 2011, Neuron).

Core concept — Embodied Self-Models (ESMs):

Safron proposes that body maps organized around 1st-person perspectival reference frames constitute a primary organizing architecture of the brain. These maps are not passive representations — they are predictive-memory systems and cybernetic controllers: systems that continuously predict body states, compare predictions against sensory signals, and generate error signals that drive both perceptual updating and motor action. “Cybernetic” here refers to the feedback-control structure: a system with a goal state, a measurement of current state, error computation, and action to reduce error — this loop running continuously at multiple levels of the nervous system hierarchy.

Addressing Proske’s open question:

Proske & Weber (2026) explicitly acknowledge that “how the memory was laid down, centrally stored and subsequently retrieved remained uncertain.” The ESM framework provides a candidate answer: body configurations are encoded through repeated prediction-error minimization cycles during practice — each movement attempt generates a mismatch between predicted and actual sensory outcome, and this mismatch updates the generative model. Storage is distributed across the generative model’s parameters, not a discrete memory trace. Retrieval happens via active inference: the model generates a prediction of the target configuration, and the motor system executes actions that progressively minimize the discrepancy between prediction and current state.

Safron’s framing is consistent with Goble’s (2010) finding that longer encoding time improves repositioning accuracy: more time = more prediction-error minimization cycles = better-calibrated generative model. It also explains the gravity-independence: a generative model encoding body configuration as a set of geometric relations does not inherently include gravity as a parameter — the central representation is of the configuration itself, not of the configuration-under-gravity.

Counterfactual richness:

Safron introduces this term to describe “the extent and variety of evoked affordance-related predictive abilities” — the range and precision of counterfactual body states (non-actual but immediately actionable configurations) that the ESM can generate. High counterfactual richness corresponds to a richer, more precise generative model: more degrees of freedom represented at sufficient resolution to generate actionable predictions.

This is the term used in §1.6a to describe the advanced phenomenological dimension of spatial awareness — the felt availability of the immediate action space, the background readout of movement possibility. It is also the motor/planning complement to sensory resolution: sensory resolution = finer discrimination among incoming signals; counterfactual richness = finer discrimination among outgoing possibilities. Both are dimensions of the same trained perceptual capacity, approached from opposite directions.

Partially-expressed motor predictions and spatial working memory:

Safron argues that all voluntary attention and working memory are realized through partially-expressed motor predictions — simulated actions covertly biasing sensory processing and organizing working memory content spatially. Spatial working memory in particular relies on partially-expressed head/trunk/eye orienting commands that organize content in body-relative reference frames. This provides the mechanistic bridge for §3.6: Baseworks body-configuration training specifically exercises the partially-expressed motor prediction systems that spatial working memory relies on — not cognition in general, but the specific sub-type of cognition grounded in the same PPC/frontal-parietal substrate as spatial body-map encoding. This is the mechanism by which the transfer observed experientially (§1.6a: subjective shift from symbolic to spatial strategies in physics-type tasks) is mechanistically plausible and directionally specific.

On the representation/enaction question:

Safron explicitly parts ways with radical enactivism (Hutto & Myin) while deeply engaging the embodied cognition tradition. His ESMs are representations — but action-oriented, grounded in sensorimotor contingencies, and without a Cartesian observer. For Baseworks, this theoretical debate is not consequential: the framework is agnostic on whether the central body-space representation is a “representation” in the philosophical sense or a “sensorimotor contingency structure” in the enactivist sense. Both framings predict the same observable outcomes from training, and the empirical questions are independent of the theoretical disagreement.

Reference: Safron A. The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again. Entropy. 2021;23(6):783. https://doi.org/10.3390/e23060783

---

Part 2: Mapping Baseworks Mechanisms to Science

2.1 Proprioceptive Upregulation: DA + MM

What Baseworks does: Activate as many muscles as possible simultaneously at low intensity (DA). Continuously repeat/trace the activations that establish this state (MM).

Scientific account:

Signal enhancement: Voluntary co-contraction increases alpha-gamma coactivation, which increases muscle spindle discharge (fusimotor reafference; Luu et al., 2011). This generates proprioceptive afference that would otherwise remain below conscious threshold. The low-intensity constraint (maintained via IM and NB) ensures that the sensory signal is enhanced without triggering sympathetic hyperactivation or endorphin release that would degrade sensory discrimination.

Habituation prevention: Sensory receptors adapt to constant stimulation. MM — the continuous subtle adjustment of activation patterns — keeps the signal dynamic, preventing the adaptation that would occur with static co-contraction. Fast-adapting mechanoreceptors in skin (responding to movement against clothing) and muscle spindles (responding to length changes) both benefit from continuous variation.

Suppression bypass: As discussed in §1.8, pre-activating muscles via DA may reduce basal ganglia suppression of those motor units, making it easier to recruit them in novel combinations. This could explain why practitioners find that after establishing DA, movements that were previously difficult become more accessible — the relevant neural populations are already cortically engaged.

Cortical remapping: Sustained training with DA+MM likely drives representational changes in somatosensory cortex (areas 3a, 1, 2) and posterior parietal cortex. The “sensation splitting” phenomenon — where previously unified muscular sensations separate into distinct perceptual events — is consistent with cortical remapping analogous to the syndactyly literature (surgical separation of fused fingers produces rapid cortical reorganization within days). Baseworks achieves a functional analog: muscles that were always co-activated as one unit are trained to be activated separately, and the sensory representation follows.

2.2 Deautomation and Deliberate Return to Cognitive Stage: FSA + GS

What Baseworks does: Break movements into single-joint steps (FSA). Impose external spatial constraints — gridlines, symmetry requirements, alignment specifications (GS). This results in forward kinematics rather than inverse kinematics.

Scientific account:

Expanding the controlled manifold: FSA and GS systematically move DOF from the uncontrolled manifold into the task-relevant space (UCM hypothesis). When you require that the pelvis stays parallel, the ribcage stays stacked, and the arm line stays straight — simultaneously — you have specified far more control variables than any habitual movement requires. This forces the development of perceptual monitoring for those variables.

Approximating motor primitives: FSA’s single-joint progression may approximate the motor primitives described by Mussa-Ivaldi & Bizzi (2000) — basic building blocks of movement that can be combined into complex actions. By isolating these building blocks, Baseworks makes them individually accessible for conscious monitoring and modification, rather than having them buried within automated synergies.

Breaking existing synergies: The difficulty of Baseworks tasks (e.g., tilting the trunk diagonally while maintaining arm alignment — the “Star Tilt” task that neurologists found counterintuitive) arises because they require breaking apart well-established cortical synergies. Cisek described these as “large attractors” that pull any nearby movement into the habitual pattern. GS+FSA impose constraints that force the system out of these attractors.

Forward kinematics and continuous monitoring: Because there is no pre-defined endpoint, the practitioner must monitor the unfolding movement continuously. Combined with IM (stop when you hit a limit), this creates a task structure that is inherently attention-demanding — not because of difficulty in the strength/flexibility sense, but because it requires continuous sensory evaluation.

2.3 Degrees of Freedom Management: The Communicability Solution

The core problem in movement education: Instructions under-specify movement (motor equivalence problem). The unspecified DOF are resolved by the learner’s existing habits. Without perceptual access to those DOF, the learner cannot detect whether their resolution matches the instructor’s intent. This creates “movement miscommunication.”

Baseworks’ three-layer solution:

1. GS (spatial specification): Provides explicit, allocentric reference frames that specify DOF normally left free. Gridlines create unambiguous targets that don’t depend on proprioceptive capacity the learner may lack — they can start by thinking geometrically and gradually develop the sensory capacity to feel whether they’re achieving the geometric target.

2. FSA (temporal specification): By isolating one joint movement at a time, FSA reduces the simultaneous DOF that must be managed, making errors attributable to specific joints rather than the whole kinematic chain. The step-by-step structure also specifies transitional movements that are typically left to habit.

3. DA+MM (sensory specification): By creating widespread activation, DA provides the sensory substrate that the learner needs to actually detect whether their body configuration matches the spatial targets set by GS and FSA.

This is the mechanism by which communicability optimization led to perceptual skill training: addressing the bottleneck required enhancing the learner’s sensory capacity, not just improving instructional clarity.

2.4 Affordance Restructuring: Creating New Action-Perception Pairs

What happens in the brain: Baseworks training can be understood as restructuring the affordance landscape:

1. Expanding affordance detection: By developing perceptual capacity for body dimensions that were previously in the uncontrolled manifold, practitioners can detect affordances (possible actions) that were literally invisible before. The pelvis-parallel affordance, the stacked-ribcage affordance, the straight-arm-line affordance — these didn’t exist as action possibilities for a learner who couldn’t sense those dimensions.

2. Creating new synergy constellations: The training forces frontoparietal maps that normally operate independently (e.g., the reaching map, the postural stability map, the trunk control map) to coordinate in new ways. Cisek endorsed this as “creating new constellations that have to work together.” This goes beyond simple skill learning — it is developing new inter-circuit communication patterns.

3. Circular reactions for adults: MM can be understood as a deliberate adult version of infant circular reactions (Piaget; Grossberg/Bullock direct model). The continuous small adjustments create a sensorimotor loop: act → sense the result → act slightly differently → sense again. This is the fundamental mechanism by which the nervous system learns to control new DOF. Baseworks formalizes this into a trainable practice.

4. Aesthetic spatial experience: When symmetry and alignment become habitual and perceptually accessible, practitioners report that spatial perception becomes “aesthetically pleasing” — a form of intrinsic reward. This may reflect the reward value of perceiving order in one’s own body configuration, analogous to how visual symmetry is inherently rewarding. This could be understood through Gallese & Di Dio’s neuroaesthetics framework, or simply as the perceptual consequence of having richer spatial representation.

2.5 Self-Regulation Architecture: NB + IM

What Baseworks does: Maintain conversational breathing even during challenging movements (NB). Modify intensity to comply with breathing, spatial form, and absence of pain/compression (IM).

Scientific account:

Preserving sensory access: High-intensity activity hyperactivates the sympathetic nervous system and HPA axis, triggering endorphin release that numbs proprioceptive discrimination. NB+IM maintain conditions where fine sensory discrimination is possible. As the key-definitions note puts it: “No surgeon would breathe heavily and jump around before performing an operation requiring maximum concentration.”

Interoceptive training: NB serves as a continuous interoceptive monitoring task — the practitioner must continuously evaluate whether breathing is still “conversational.” IM requires monitoring internal signals (fatigue, compression, loss of precision) and adjusting behavior in real time. These are trainable self-regulation skills with documented transfer to stress management and well-being in daily life.

Chronic sensory adaptation: IM creates the sustained, repeated exposure to lower-stimulation/higher-attention conditions that permit neuroplastic changes in sensory discrimination. Just as taste recalibrates after reducing sugar intake, proprioceptive resolution may require sustained exposure to conditions where subtle signals are not masked by high-intensity noise.

2.6 The Dorsal-Ventral Integration Perspective

Cisek emphasized that the dorsal-ventral stream distinction, while discovered through vision research, is fundamentally about action vs. identification — not specifically about vision. In non-primate mammals, these streams are dominated by somatosensation and olfaction, respectively. The primate visual dominance is a specialization, not the underlying principle.

For Baseworks, this means:

• The “spatial” perceptual skills (body configuration, alignment, position in space) are primarily dorsal stream functions — continuous, topographic, about spatial relationships.
• The “categorical” aspects (identifying what type of movement you’re performing, recognizing when you’ve achieved a target configuration) may involve more ventral processing.
• Baseworks pedagogically needs to address both: developing continuous spatial monitoring (dorsal) and building new movement categories (ventral). Cisek suggested this distinction could be communicated to non-scientists as “some things are continuous like your position, and some things might be categorical like what type of thing you’re trying to accomplish.”

2.7 The Sticky Fascia

(draft)

Sticky fascia, or fascial adhesions, refers to connective tissue that has become stiff, thickened, and less pliable, limiting movement and causing pain. DA + MM continuously engage almost every muscle in the body at low intensity. Since we tighten and pull on fascia, it should theoretically be an effective way to rehydrate collagen and make the fibers easier to slide against each other.

---

Part 3: Open Questions and Research Directions

3.1 The DA+MM Question: What Does It Actually Do to M1 Connectivity?

DA+MM is the most distinctive Baseworks mechanism — nothing else in movement education uses simultaneous whole-body low-level co-contraction with continuous micro-adjustment. While GS and FSA are more logically derivable (a hypothetical council designing a high-communicability movement system might converge on something similar), DA+MM is counterintuitive and potentially the most scientifically interesting.

Specific questions:

• What does sustained DA+MM training do to motor cortex organization? Does it change the map from synergy-organized (Graziano) toward more distributed representations?
• Does DA reduce the threshold for recruiting novel motor combinations by pre-activating populations that would otherwise be suppressed?
• Does MM function as a continuous perturbation that keeps the sensorimotor system in a learning-receptive state (preventing consolidation into fixed synergies)?
• Could DA+MM have applications in movement disorders (e.g., Parkinson’s, where basal ganglia dysfunction impairs action selection)? If DA bypasses some BG suppression, could it provide an alternative pathway for movement initiation?
• Could DA+MM address fundamental questions in movement science about the relationship between voluntary co-contraction and cortical representation?

3.2 Muscular Mechanosensation as an Unmapped Sensory Domain

The Baseworks research has identified what appears to be a genuine gap in the scientific literature: conscious localized sensations arising from muscle state (at rest and during contraction) have no established name, no standard measurement, and no systematic research program. The phenomenon sits in a blind spot between skin-based exteroception and the “unconscious” proprioceptive signals that textbooks describe as never reaching awareness (Delhaye et al., 2018).

What we know:

• Large individual variation in awareness (survey data: ~43% at rest, ~48% during exercise)
• No correlation with athletic background or sex
• Onset of awareness at rest: 21.8 ± 13.2 years (mean ± SD)
• 47% of respondents didn’t know how to name the sensation
• Cortical substrate: likely area 3a (receives muscle and joint afference; Proske’s suggestion)
• Training can increase conscious access (Baseworks practitioner reports; dancer reports)

Best candidate mechanisms — distinguished by contraction state:

Resting baseline (the component that persists even without active contraction): Group II secondary endings on nuclear chain fibers maintain tonic, regular discharge proportional to muscle length — independent of fusimotor drive (Macefield, 2018). This is the most plausible substrate for the sensation that “doesn’t fully disappear at rest.” It is not driven by a motor command; it is the spindle population continuously reading the mechanical state of the muscle from within.

Contraction-proportional component (intensifies with effort/load): Spindle afference from both Group Ia and Group II fibers scales with contraction strength via alpha-gamma coactivation. Luu et al. (2011) demonstrated that this ascending spindle signal — not central efference copy — is the dominant source of force and heaviness perception in healthy subjects. Golgi tendon organs contribute a parallel force-proportional signal active at individual motor unit recruitment levels.

This is potentially the most publishable finding — a well-defined, measurable phenomenon that falls between established categories and has practical implications for movement education, rehabilitation, and body awareness research. See spindle-physiology-and-phenomenology for the detailed mechanistic and phenomenological analysis.

3.3 The Star Tilt Problem and UCM

The “Star Tilt” task — tilting the trunk diagonally while maintaining arm alignment as one chunk — is difficult for most people and was found counterintuitive even by neurologists at the ICNN conference. From the UCM perspective, this task is interesting because it requires treating the trunk-arm system as a single rigid segment (one controlled variable) while allowing independent control at other joints. This contradicts the normal synergy structure, where trunk and arms are controlled separately. This is a concrete, testable case for UCM-based experimental design.

3.4 Testing Cortical Remapping

Cisek suggested that the “sensation splitting” phenomenon could be tested with TMS — mapping motor output from cortical sites before and after Baseworks training to see whether synergy boundaries shift. For hand/arm muscles, this would be straightforward; for trunk muscles (where the splitting is most commonly reported), it would be more challenging but potentially more novel. EMG coherence between muscle pairs before and after training could also index changes in synergy structure.

3.6 Spatial Awareness Training and Visuospatial Working Memory

[SPECULATIVE] If spatial awareness as Baseworks defines it maps onto the PPC-mediated central body-configuration representation described by Proske’s repositioning mechanism (§1.6), and if that substrate overlaps with the visuospatial sketchpad of working memory (Baddeley’s model; dorsal stream spatial processing, §2.6), then systematic positional training might transfer to general visuospatial cognitive capacities.

The specific hypothesis: repeated encoding, retention, and reproduction of body configurations — the cognitive-proprioceptive loop practiced in every Baseworks session — exercises the same neural machinery used for spatial working memory tasks (mental rotation, visuospatial manipulation, map reading, architectural visualization). Improvements in one might generalize to the other.

This is grounded in a subjective observation (Asia, ~9 years practice): a felt improvement in working memory capacity and vividness of mental visualization that appears to coincide with the period of intensive positional training. This observation is n=1, uncontrolled, and not an advertised outcome. It is recorded here as an honest hypothesis from an informed practitioner, not as a claim.

Why it matters if true: it would position Baseworks as relevant not just to movement quality but to a broader cognitive capacity — a significant potential application for populations where visuospatial cognition matters (architects, surgeons, athletes, aging populations).

What a study might look like: standardized visuospatial working memory measures (Corsi block task, mental rotation battery) before and after a structured Baseworks curriculum, compared to an active control (matched movement practice without the systematic positional encoding component). The challenge is isolating the positional encoding component from the broader attentional and well-being effects of regular practice.

---

3.5 Experimental Paradigm: Micro-Movements as Placebo Control

The distinction between macro-movements (visible position changes) and micro-movements (subtle adjustments maintaining or refining position) provides a natural experimental design: a “placebo” group performing the same macro-movements without micro-movement cues. If perceptual gains are driven by DA+MM rather than the macro-movement practice alone, this should be detectable in before/after measures of proprioceptive acuity, spatial awareness, and movement control.

---

Part 4: Research Timeline and Milestones

Presentations

Neuro 2025 (McGill University, Montreal) “Perceptual Skills in Movement Education.” 26th Annual Neuropsychology Day. First formal academic presentation of the Baseworks research.

ICNN 2025 (Nazarbayev University, Astana, Kazakhstan) “Perceptual Skills and Movement Miscommunication in Movement Education and Beyond.” 1st International Conference on Neurosciences and Neurology. Poster presentation with expanded methods and findings.

Key Validation: Paul Cisek Meeting (January 23, 2026)

Two-hour meeting with Paul Cisek (University of Montreal), whose affordance competition hypothesis is one of the central frameworks for understanding Baseworks mechanisms. This was the first substantive peer feedback on the Baseworks reverse engineering since the project began.

What was validated:

• The emergence of perceptual skill focus from communicability optimization “makes sense” within the affordance competition framework
• The interpretation of DA as preventing suppression of competing movements (BG bypass hypothesis)
• The idea that Baseworks creates “new constellations” of coordinated frontoparietal maps
• The terminology alignment: “movement vocabulary” = Graziano’s “repertoire”
• The connection between what Baseworks does and the uncontrolled manifold / degrees of freedom problem
• The term “perceptual skills” was deemed acceptable, with a caution that “perception” can imply conscious reconstruction — “sensorimotor discrimination” may be more precise in some contexts

What was newly introduced:

• The Uncontrolled Manifold Hypothesis as a central framework (Cisek’s first recommendation)
• Borra/Caminiti’s anatomical modules work (detailed map of frontoparietal circuit organization)
• Steve Scott’s work on optimal feedback control
• Gregor Schöner’s computational frameworks
• SCAPPS conference (Ottawa, October 2026) as a venue where “kindred spirits” in motor control and sport psychology would understand this work
• The possibility of TMS experiments to test cortical remapping from Baseworks training

Cisek offered to serve as “a sounding board” — available for bouncing ideas and checking for blind spots. This represents an ongoing advisory relationship.

Recommended Next Steps (from Cisek meeting)

• Study the Uncontrolled Manifold Hypothesis literature (Scholz & Schöner; Latash)
• Look into optimal feedback control (Steve Scott’s reviews)
• Consider submitting to SCAPPS conference (Ottawa, October 2026)
• Consider Psychology of Sports and Exercise journal for theoretical papers
• Explore TMS/EMG experimental designs for testing cortical remapping hypotheses

---

References

Ashby FG, Turner BO, Horvitz JC. Cortical and basal ganglia contributions to habit learning and automaticity. Trends Cogn Sci. 2010;14(5):208-215.

Bernstein NA. The co-ordination and regulation of movements. Oxford: Pergamon Press; 1967.

Blakemore C, Cooper GF. Development of the brain depends on the visual environment. Nature. 1970;228(5270):477-478.

Bufacchi R, Iannetti G. An Action Field Theory of Peripersonal Space. Trends in Cognitive Sciences, 2018; 22, 1076-1090

Cisek P. Cortical mechanisms of action selection: the affordance competition hypothesis. Philos Trans R Soc Lond B Biol Sci. 2007;362(1485):1585-1599.

Cisek P, Pezzulo G. Navigating the affordance landscape: feedback control as a process model of behavior and cognition. Trends Cogn Sci. 2024.

Delhaye BP, Long KH, Bensmaia SJ. Neural basis of touch and proprioception in primate cortex. Compr Physiol. 2018;8(4):1575-1602.

Fitts PM, Posner MI. Human Performance. Brooks/Cole; 1967.

Gallese V, Di Dio C. Neuroesthetics: The body in esthetic experience. In: Ramachandran VS, ed. The Encyclopedia of Human Behavior. Vol 2. Elsevier Academic Press; 2012:687-693.

Graziano MSA. The organization of behavioral repertoire in motor cortex. Annu Rev Neurosci. 2006;29:105-134.

Grossberg S. Competitive learning: From interactive activation to adaptive resonance. Cogn Sci. 1987;11(1):23-63.

Grossberg S. Towards solving the hard problem of consciousness: The varieties of brain resonances and the conscious experiences that they support. Neural Netw. 2017;87:38-95.

Kleim JA, Jones TA. Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. J Speech Lang Hear Res. 2008;51(1):S225-S239.

Latash ML. Synergy. Oxford University Press; 2008.

Luu BL, Day BL, Cole JD, Fitzpatrick RC. The fusimotor and reafferent origin of the sense of force and weight. J Physiol. 2011;589(13):3135-3147.

Mussa-Ivaldi FA, Bizzi E. Motor learning through the combination of primitives. Philos Trans R Soc Lond B Biol Sci. 2000;355(1404):1755-1769.

Price CJ, Hooven C. Interoceptive awareness skills for emotion regulation: theory and approach of mindful awareness in body-oriented therapy (MABT). Front Psychol. 2018;9:798.

Proske U, Gandevia SC. The proprioceptive senses: their roles in signaling body shape, body position and movement, and muscle force. Physiol Rev. 2012;92(4):1651-1697.

Proske U, Weber BM. Measures of human position sense do not always include contributions from peripheral sensory receptors. Eur J Neurosci. 2026;63:e70444.

Goble DJ. Proprioceptive acuity assessment via joint position matching: from basic science to general practice. Phys Ther. 2010;90(8):1176-1184.

Gordon EM, Chauvin RJ, Van AN, et al. A somato-cognitive action network alternates with effector regions in motor cortex. Nature. 2023;617:351-359.

Rizzolatti G, Fabbri-Destro M, Cattaneo L. Mirror neurons and their clinical relevance. Nat Clin Pract Neurol. 2009;5(1):24-34.

Scholz JP, Schöner G. The uncontrolled manifold concept: identifying control variables for a functional task. Exp Brain Res. 1999;126:289-306.

Wolpert DM, Diedrichsen J, Flanagan JR. Principles of sensorimotor learning. Nat Rev Neurosci. 2011;12(12):739-751.

Mehling WE, Gopisetty V, Daubenmier J, Price CJ, Hecht FM, Stewart A. Body awareness: construct and self-report measures. PloS one. 2009 May 19;4(5):e5614.

Mehling WE, Wrubel J, Daubenmier JJ, Price CJ, Kerr CE, Silow T, Gopisetty V, Stewart AL. Body Awareness: a phenomenological inquiry into the common ground of mind-body therapies. Philosophy, ethics, and humanities in medicine. 2011 Apr 7;6(1):6.

Craig AD (2015). How Do You Feel? An Interoceptive Moment with Your Neurobiological Self.Princeton, NJ: Princeton University Press. 10.1515/9781400852727

---

Related

• Key Definitions
• Method Admin