What is established, what is observed, what is hypothesised — and what still needs to be tested
Functional Neuro-physiological Integration — FNI — developed through extended clinical observation and refinement.
Clinical experience can generate useful observations, patterns and hypotheses.
It cannot by itself establish scientific validity.
For this reason, FNI deliberately separates:
established scientific knowledge
from
external areas of convergence
from
clinical observations made during FNI
from
hypotheses proposed to explain those observations
from
direct evidence specifically testing FNI.
This distinction is fundamental to the development of FNI.
Related research can make an FNI observation more plausible or help design an experiment.
It does not prove FNI.
A central research principle is therefore:
Isomorphs generate predictions — not proof.
The FNI evidence framework
| Evidence category | What it means | Current role in FNI |
|---|---|---|
| Established scientific knowledge | Findings supported within relevant scientific disciplines | Provides background mechanisms and measurement methods |
| External convergence | Similar relationships observed in another therapy, discipline or experimental field | Generates comparisons and research questions |
| FNI clinical observation | A pattern repeatedly observed during FNI practice | Generates a testable clinical hypothesis |
| FNI hypothesis | A proposed explanation or prediction arising from those observations | Must survive controlled testing |
| Direct FNI evidence | Research specifically testing defined FNI procedures | Required before claiming scientific validation of FNI |
The boundaries matter.
For example, research showing that proprioception influences motor control does not prove that a particular FNI muscle response measures proprioceptive change.
Research showing that imagery can alter physiological activity does not prove that an FNI semantic construct produces a particular physiological mechanism.
Research showing relationships between cervical proprioception, vision and balance does not validate the complete FNI Pre-Screen.
Each FNI-specific proposition must eventually be tested directly.
Current scientific status of FNI
FNI is currently best described as a:
defined, testable, developing clinical modality.
Its clinical procedures are increasingly being formalised.
Its primary feedback method has been defined more precisely.
Its decision process is becoming reproducible enough to investigate.
Its major hypotheses can now be expressed in ways that can potentially be confirmed or falsified.
However, the complete FNI system has not yet been independently scientifically validated.
The peer-reviewed literature reviewed for this page does not establish the reliability, validity or clinical effectiveness of the complete FNI process.
That distinction should remain explicit.
The central research question
The most important question is not:
“Does kinesiology work?”
Nor is it simply:
“Does muscle testing work?”
These questions combine too many different methods.
The more useful FNI question is:
When an FNI assessment is carefully qualified and calibrated, does a defined stimulus produce a reproducible change in the measured state, and can that change be altered by a specific intervention when the original stimulus is presented again?
The experimental structure becomes:
baseline → controlled stimulus → measured change → intervention → same stimulus → reassessment
That is a question that can be tested.
Manual Muscle Testing: an important distinction
Manual Muscle Testing is used in several very different ways.
Conventional neurological and musculoskeletal MMT commonly evaluates voluntary muscle performance or strength.
Applied Kinesiology has also used MMT as a response indicator during structural, chemical, mental and other “challenge” procedures.
FNI uses something different again.
The FNI test is intended to identify a rapid change in the resistance or compliance of a gently stabilised joint–muscle system relative to the person’s own calibrated state.
It is not designed to measure maximum strength.
And importantly:
Evidence for ordinary strength testing cannot automatically be used as evidence for FNI challenge testing.
This distinction has been a significant problem in earlier MMT literature.
What does the current MMT evidence say?
The evidence is mixed.
A 2025 systematic review specifically examining Applied Kinesiology MMT found intra- and inter-examiner reliability ranging from nonexistent to very strong depending on the procedure and muscle tested.
Importantly, the review found that testing involving non-musculoskeletal challenge procedures showed nonexistent reliability in the included studies.
The authors therefore did not recommend those challenge applications on the basis of the available evidence.
Some muscle tests without those challenges showed considerably better reliability.
Earlier criticism of the AK literature also warned against assuming that evidence supporting conventional orthopedic muscle testing validates the distinctive diagnostic claims made through AK challenge procedures.
FNI takes this criticism seriously.
It does not assume:
MMT has scientific literature → therefore FNI-MMT is validated.
Instead:
The specific FNI test must earn its own reliability and validity.
That means testing the actual procedure FNI uses:
the stabilisation;
the direction of force;
the low-force engagement;
the rate of engagement;
the immediate response window;
the defined stimulus;
the same-stimulus retest;
and the correction procedure.
Why the FNI muscle test may be experimentally useful
Although its validity still needs to be established, FNI-MMT has several properties that make it potentially measurable.
The response is described as occurring rapidly near the beginning of engagement.
The test uses relatively low force.
The practitioner compares the response against the same person’s calibrated baseline rather than against a population strength standard.
The same triggering stimulus can be repeated.
The original stimulus can be replayed after correction.
This creates measurable variables such as:
time from stimulus to test
force at onset
rate of force application
force–displacement relationship
compliance
muscle activity
response latency
response recovery
and
same-trigger pre/post change.
Instead of asking a researcher to judge whether a muscle “feels weak”, future FNI studies could record the complete force-time and movement response.
FNI does not treat the muscle response as truth
This is an important scientific safeguard.
A changed FNI response does not prove that a statement is factually true.
It does not diagnose disease.
It does not demonstrate that an imagined structure physically exists.
And it does not by itself reveal the mechanism producing the change.
Within FNI, the appropriate reasoning sequence is:
response → pattern → question → hypothesis → cross-check → reassessment
A muscle response is therefore treated as an observation channel.
The validity of what that channel measures remains an empirical question.
Sensorimotor integration and proprioception
One of the strongest established scientific foundations relevant to FNI is the importance of sensory feedback in motor control.
Proprioceptive information from muscles, joints and related structures contributes continuously to estimates of body position and movement.
This information interacts with motor commands throughout the nervous system.
Modern sensorimotor research describes movement as a continuously updated feedback process rather than a one-directional command from brain to muscle.
Recent work continues to show that proprioceptive signals contribute to internal estimates of limb state, including position and movement velocity.
This provides a legitimate scientific background for the general proposition:
changes in sensory input can influence motor output.
It does not, by itself, establish that the FNI muscle response measures a particular central process.
That requires direct FNI testing.
Vision, cervical proprioception and postural control
The FNI Pre-Screen pays particular attention to eye tracking, head movement, cervical organisation and compensatory body movement.
There is established scientific evidence that visual, vestibular and cervical proprioceptive information are integrated in maintaining coordinated movement of the eyes, head, neck and body.
Cervical proprioceptive disturbance can alter this integration.
Research into cervicogenic dizziness, for example, describes sensory conflict among cervical proprioceptive, visual and vestibular inputs.
This provides a scientific reason to investigate eye–head–body coordination.
It does not mean that an abnormal eye movement automatically identifies an upper cervical lesion or any particular pathology.
Within FNI:
eye-tracking distortion is an investigational finding, not a diagnosis.
Position and gravity as a challenge
FNI may compare findings while a person is lying down, sitting and standing.
This is based on a simple experimental principle.
Changing position changes the operating conditions of the sensorimotor system.
Standing introduces greater requirements for balance, gravitational orientation, cervical and postural control and coordinated muscle activity.
A finding that is absent while lying down but reappears while standing may therefore represent context dependence.
The research question is not whether standing is inherently more diagnostic.
It is:
Does the measured response remain stable when the operating context changes?
That can be investigated objectively.
Memory, imagery and physiological response
FNI sometimes uses words, memories, imagined situations, spatial constructs or sensory imagery as controlled stimuli.
There is established evidence that imagination and emotional memory can be accompanied by measurable physiological responses.
Research has shown relationships between emotional states and autonomic activity.
Mental imagery can recruit neural systems associated with perception, emotion and action.
Modern reviews of emotional imagery describe associative representations incorporating stimulus information, semantic meaning and somatic or autonomic response information.
This makes the general proposition that imagined or remembered material can alter present physiological state scientifically plausible.
It does not demonstrate that a particular FNI semantic representation has a specific biological meaning.
Eye movement and memory
FNI’s eye work developed from clinical observation rather than from EMDR.
Later comparison revealed areas of convergence.
Experimental eye-movement research provides evidence that performing eye movements or other working-memory-demanding tasks during memory recall can reduce the later vividness or emotional intensity of some memories.
A 2021 meta-analysis of 53 laboratory studies found reductions in reported vividness and emotionality after dual-task procedures that included eye movement.
More recent replication work has continued to find reductions in some aspects of memory vividness and emotionality.
This literature is relevant because it demonstrates that:
changing the conditions under which a memory is accessed can change aspects of the later experience of that memory.
However, this research does not validate FNI’s eye-field map, FNI eye-distortion corrections or FNI’s proposed relationships among particular gaze directions and semantic themes.
Those remain FNI-specific research questions.
Emotion and autonomic physiology
Emotional states are not purely verbal or cognitive events.
Research has repeatedly demonstrated changes in autonomic variables associated with emotional processing, including heart activity, vascular responses, skin conductance and respiration.
The relationship is complex.
There is not a simple one-emotion/one-physiological-pattern dictionary.
Individual differences and context matter.
This aligns with an important FNI principle:
physiological response may contain information without having a single universal interpretation.
FNI should therefore avoid claims such as:
“this physiological response proves this emotion.”
The more appropriate question is:
Did the person’s state change reproducibly when this particular stimulus was presented?
Learning and conditioned physiological responses
Physiological responses can become associated with cues through learning.
Classical conditioning research has demonstrated conditioned autonomic and endocrine responses under some experimental conditions.
This provides an established framework through which a previously neutral cue may later produce a physiological response.
It also provides one plausible bridge for understanding why a word, place, image, memory or person might evoke a rapid bodily response.
FNI sometimes uses a Pavlovian analogy:
stimulus → learned state response → bodily output
followed by:
same stimulus + altered feedback → reassessment of response.
This remains a conceptual bridge.
It should not be interpreted as proof that all FNI responses are Pavlovian conditioning.
Paired movements and cross-system motor relationships
The FNI Pre-Screen also observes unexpected movement relationships.
Examples include eye movement accompanied by jaw activity or hand movement accompanied by jaw movement.
Human motor control is not organised as completely isolated muscles and body parts.
Research demonstrates coordinated motor synergies and distributed representations.
Human cortical stimulation studies have identified integrated hand–mouth motor relationships, including patterns in which hand and mouth movements are coordinated within common motor representations.
This provides a plausible scientific reason to investigate reproducible paired movement.
Again, the boundary matters:
a paired movement is a clue to functional relationship — not proof of pathology.
The FNI Multiplex
FNI uses Manual Muscle Testing as the primary continuous navigation channel.
Other responses may appear alongside it, including changes in breathing, posture, movement, swallowing, facial expression, tension, sensation, pain, thought flow, imagery or emotion.
FNI describes these as additional coherence channels.
The research opportunity is significant.
If a stimulus produces:
an MMT change;
a respiratory change;
an EMG change;
and a postural change
at approximately the same time, those independent measurements may provide stronger evidence for a genuine state transition than any single channel alone.
However:
multiple correlated signals still do not automatically identify the mechanism.
They demonstrate convergence.
Mechanism requires further testing.
Clinical observations currently requiring direct FNI research
Several patterns have been observed during FNI practice but should remain classified as clinical observations until they are independently tested.
These include the rapid change in MMT resistance/compliance following particular stimuli.
They include the apparent restoration of the calibrated response after correction and same-trigger retesting.
They include intermittent changes in respiration, posture, sensation, movement, pain, thought or emotion occurring alongside MMT changes.
They include eye-tracking distortions and paired movement patterns.
They include changes that appear different under lying, sitting or standing conditions.
They include subtle relative heel or body-position changes.
They include spontaneous motor reactions during some sessions.
And they include the observation that the characteristic FNI MMT response may remain clinically readable when some patients appear to fall asleep.
These observations are valuable because they generate experiments.
They are not presented as established mechanisms.
The FNI sleep observation
Some patients become deeply relaxed and occasionally appear to fall asleep during a session while the FNI tonal response remains clinically detectable.
If confirmed during objectively verified physiological sleep, this could become an important experimental finding.
A rigorous study would require objective sleep staging rather than visual judgement alone.
EEG or polysomnography could identify sleep state while force measurement, EMG, respiration and stimulus timing were recorded simultaneously.
If the characteristic FNI response disappeared under verified sleep, the clinical model would need to account for that.
If it remained measurable under defined sleep stages, that would narrow the range of plausible mechanisms.
Either result would be useful.
The same-trigger retest
One of the most important features of FNI is the repeated use of the original stimulus.
The basic logic is:
stimulus A → measurable change
followed by:
correction
followed by:
stimulus A again → reassessment.
This creates a stronger experimental structure than simply observing a change after treatment.
It also creates a major confound that must be controlled:
spontaneous recovery.
If an altered response naturally returns toward baseline after time alone, apparent “correction” could simply represent recovery.
Future studies therefore need to compare:
active correction
with
time-matched sham correction
and
no correction / natural recovery.
Only if the active procedure produces a reproducibly greater effect can correction specificity begin to be established.
The transient response window
Clinically, some FNI responses appear to change for a relatively short period before naturally returning toward baseline.
This is experimentally useful.
The recovery curve can potentially be measured.
Instead of describing the response only as strong or weak, research can examine:
magnitude of change over time.
The key variables become:
baseline;
stimulus response;
maximum change;
time to recovery;
correction response;
and same-trigger retest.
If the response has a consistent time course, that prediction can be tested.
If it does not, the model must be revised.
Practitioner influence
Practitioner influence is one of the most important potential confounders in manual testing.
Force, timing, direction, expectation and subtle behavioural cues could alter a response.
FNI therefore treats practitioner calibration as a research problem rather than dismissing it.
Future experiments should instrument both patient and practitioner.
Load cells, motion tracking and EMG can measure whether the practitioner’s force vector or engagement rate changes between test conditions.
Stimuli can be computer-randomised so the practitioner does not know which condition is being presented.
Where possible, data analysis should also be blinded.
A genuine FNI signal should survive progressively stronger controls against practitioner expectation.
Patient expectation and voluntary influence
Patient expectation is another plausible confound.
A participant may consciously or unconsciously alter resistance if they know what response is expected.
Future studies should therefore compare known and blinded stimuli.
Standardised recorded prompts can reduce differences in practitioner voice and delivery.
Participants can be prevented from knowing the experimental category being tested.
Surface EMG and movement tracking can identify deliberate or delayed recruitment patterns.
The FNI claim that the most informative distinction occurs very early in engagement produces a useful prediction:
the relevant change should appear before prolonged voluntary resistance becomes the dominant feature of the test.
That prediction can be measured.
Research Programme 1 — Instrument the FNI muscle test
The first priority is not to prove clinical effectiveness.
It is to determine whether the physical signal itself can be measured reliably.
A force sensor could record the applied load.
Motion tracking could record arm displacement.
Surface EMG could measure biceps and antagonist activation.
Testing could record:
trigger time → engagement time → response onset → release → recovery.
The immediate goal would be to determine whether practitioner-described “solid” and “spongy” responses correspond with reproducible objective differences.
If expert practitioners cannot reliably distinguish instrumented response classes, the FNI MMT model would require revision before more complex research was justified.
Research Programme 2 — Blinded stimulus specificity
Once the physical test can be measured, the next question is whether a predefined relevant stimulus differs from an appropriate neutral control.
Personalised stimuli could be identified before testing.
Stimuli could then be randomised and presented without the practitioner knowing which condition is active.
The primary outcome would be the instrumented FNI response rather than the practitioner’s interpretation alone.
A strong FNI prediction would be:
predefined relevant stimuli produce reproducible response differences beyond neutral stimuli and chance classification.
Failure to demonstrate this under appropriately powered blinded conditions would directly challenge the stimulus-specific FNI model.
Research Programme 3 — Correction specificity
If stimulus specificity is demonstrated, correction can then be tested.
Participants showing a reproducible response would be randomly allocated, where practicable, to:
active FNI correction
sham or control intervention
or
time-only recovery.
The original stimulus would then be replayed.
The relevant question is:
Does the FNI correction alter the same-trigger response more than sham intervention or natural recovery?
This is one of the most important possible tests of FNI.
Research Programme 4 — Inter-practitioner reproducibility
A clinical modality should not depend entirely on one practitioner’s hands.
Once a standard physical procedure has been documented, independently trained practitioners should test the same participants under blinded conditions.
Research should examine both:
agreement on the observed response
and
agreement on the resulting clinical decision.
A modality can be clinically sophisticated and still fail if essential observations cannot be transferred between practitioners.
For FNI to become independently teachable, practitioner reproducibility is essential.
Research Programme 5 — Multiplex measurement
The MMT channel can then be studied alongside independent physiological and mechanical measurements.
Depending on the experiment, these might include:
respiration;
heart-rate variability;
surface EMG;
electrodermal activity;
eye tracking;
head and body motion;
postural sway;
relative heel position;
split-table displacement;
and EEG.
The strongest finding would not simply be that several variables change.
It would be:
multiple independent channels change in a reproducible, time-locked manner following the same controlled stimulus and change again following intervention.
This would support the proposition that the FNI test is detecting part of a wider state transition.
It would still not, by itself, determine the underlying mechanism.
Research Programme 6 — Eye tracking and the FNI Pre-Screen
The eye-tracking component can be investigated separately from the rest of FNI.
Digital eye tracking can measure:
gaze trajectory;
velocity;
smoothness;
fixation;
saccadic behaviour;
range;
head substitution;
jaw co-activation;
and postural movement.
The first question should be simple:
Can trained FNI practitioners reliably identify the same eye-tracking abnormalities that objective measurement detects?
A later study could ask whether the FNI correction changes those measurements.
A still later study could examine whether those changes influence downstream FNI calibration.
This staged approach prevents a complex clinical observation from being treated as one indivisible claim.
Research Programme 7 — Paired movement
Eye–jaw and hand–jaw coupling can also be tested independently.
High-speed video and surface EMG could determine:
which movement occurs first;
whether the relationship is repeatable;
whether it changes with position;
whether it changes with task difficulty;
and whether a specific intervention changes the coupling.
The scientific question is not:
“Does this prove a TMJ problem?”
It is:
“Is there a reproducible cross-effector relationship, and under what conditions does it change?”
Research Programme 8 — Clinical outcomes
Only after the measurement system is adequately characterised should larger clinical-effectiveness claims be made.
Outcome research should distinguish:
what the patient came for
from
what the FNI test measured
from
what intervention occurred
from
what changed afterwards.
Relevant outcomes may include function, symptom intensity, reaction patterns, patient-defined goals, quality of life and durability of change.
Where a patient has a diagnosed medical condition, FNI outcome reporting should remain separate from medical diagnostic status unless that status has been independently reassessed using appropriate clinical criteria.
Historical patient outcomes
Long-term clinical practice has produced patient reports describing substantial changes.
These reports are important historical clinical observations.
They are not equivalent to controlled evidence.
Where sufficient records remain, selected historical cases may provide material for retrospective case documentation.
The strongest historical cases would contain:
documented baseline diagnosis or presentation
clinical notes
other concurrent treatments
FNI intervention timeline
patient-reported change
objective before/after findings where available
and
long-term follow-up.
Such cases can generate hypotheses and demonstrate feasibility.
They cannot establish causation in the way a controlled prospective study can.
What would count as evidence against FNI?
A system that can explain every possible result cannot be scientifically tested.
FNI therefore needs conditions under which its propositions would be modified or rejected.
Evidence against important elements of the current model would include:
trained practitioners failing to reproduce the defined FNI response;
instrumentation showing no reliable physical difference between the proposed response states;
predefined relevant stimuli performing no differently from appropriate neutral controls;
the effect disappearing when practitioner expectation is blinded;
active correction performing no better than sham intervention or spontaneous recovery;
different practitioners reaching substantially incompatible results despite adequate training;
proposed multiplex signals failing to converge under objective measurement;
or clinical outcomes failing to exceed appropriate comparison conditions.
A negative result is not a threat to FNI.
It is information about which part of the model needs to change.
Research should be capable of changing FNI
FNI should not use research only to confirm existing beliefs.
The research process must be capable of modifying the clinical model.
The sequence should be:
clinical observation → formal hypothesis → prediction → experiment → result → model update
not:
clinical belief → search for supporting paper → confirmation.
This is particularly important when working across multiple disciplines, because it is easy to find research that resembles part of a clinical model.
Resemblance is useful.
It is not validation.
Independent replication
Evidence becomes substantially stronger when the person who developed the system is no longer necessary to produce the result.
For that reason, long-term FNI research should include practitioners who were not involved in developing the method.
Protocols should be sufficiently detailed that another group can reproduce:
the patient position;
the muscle-test mechanics;
the calibration;
the stimulus;
the correction;
the retest;
and the outcome measurement.
The objective is not merely to demonstrate that FNI works in the founder’s hands.
The objective is to determine whether the underlying observations survive independent replication.
Research transparency
Where possible, future FNI studies should use preregistered hypotheses and outcomes.
Experimental procedures should be defined before analysing results.
Blinding should be used wherever practicable.
Sample-size calculations should occur before recruitment.
Negative findings should be retained and reported.
Exploratory findings should be identified as exploratory.
And new hypotheses generated after seeing the results should not be presented as though they were predicted beforehand.
This protects both FNI and the people evaluating it.
Reliability, validity and effectiveness are different questions
These concepts should not be confused.
Reliability
Does the same test produce sufficiently consistent results?
Validity
Does the test actually measure or predict what is claimed?
Mechanism
What biological, psychological or sensorimotor process produces the observed response?
Clinical effectiveness
Does using the system produce meaningful patient outcomes?
A test can be reliable without being valid.
A clinical intervention can potentially produce benefit even when its proposed mechanism is wrong.
And demonstrating a physiological mechanism does not automatically establish clinical effectiveness.
FNI research should keep these questions separate.
The strongest current FNI research priorities
The first decisive experiments are relatively simple.
Can the gentle FNI MMT response be objectively characterised?
Can predefined stimuli produce reproducible changes under blinded conditions?
Does an FNI correction alter the same-trigger response more than natural recovery or sham intervention?
Can another trained practitioner reproduce the result?
If FNI succeeds under those conditions, considerably more complex questions become worth investigating.
If it fails, the model should be revised before advancing stronger claims.
Why external research still matters
External research remains extremely valuable.
It can reveal plausible mechanisms.
It can suggest measurement methods.
It can identify confounders.
It can show that apparently unusual clinical observations have parallels elsewhere.
It can generate predictions.
But the evidence hierarchy remains:
related science → plausible bridge → FNI hypothesis → direct FNI experiment → replication.
Skipping the experimental steps between related science and FNI validation would weaken the system rather than strengthen it.
Selected scientific literature relevant to FNI
The papers below are examples of external literature relevant to questions raised by FNI. They are not presented as direct validation of FNI.
Soares JR, Stieven FF, Rocha CSD, Miranda IF. (2025). Reliability of Manual Muscle Testing in Applied Kinesiology: A Systematic Review. Journal of Manipulative and Physiological Therapeutics, 48, 862–870. DOI: 10.1016/j.jmpt.2025.10.007.
This review is particularly important because it reports widely variable reliability in AK-MMT and nonexistent reliability in the included non-musculoskeletal challenge studies.
Oliveira DG, Oliveira GM, Kirkwood RN. (2022). Clinimetric Properties of the Applied Kinesiology Manual Muscle Test in Adults With and Without Pain: A Methodological Study. Journal of Chiropractic Medicine, 21(4), 260–269. DOI: 10.1016/j.jcm.2022.03.003.
Relevant to the question of how specific AK-style muscle tests can be examined using reliability, validity and responsiveness methodology.
Haas M, Cooperstein R, Peterson D. (2007). Disentangling manual muscle testing and Applied Kinesiology: critique and reinterpretation of a literature review. Chiropractic & Osteopathy, 15, 11. DOI: 10.1186/1746-1340-15-11.
Important methodological criticism showing why evidence for conventional muscle strength testing should not be automatically generalised to distinctive AK diagnostic or challenge procedures.
Mortensen ES, Christensen MS. (2026). Proprioceptive Integration in Motor Control. The Journal of Physiology, 604, 3431–3456. DOI: 10.1113/JP289835.
Relevant to contemporary understanding of proprioceptive information as part of continuously updated estimates used in movement and motor control.
Li Y, Yang L, Dai C, Peng B. (2022). Proprioceptive Cervicogenic Dizziness: A Narrative Review of Pathogenesis, Diagnosis, and Treatment. Journal of Clinical Medicine, 11, 6293. DOI: 10.3390/jcm11216293.
Relevant to interactions among cervical proprioception, visual information, vestibular processing, eye movement and postural organisation.
Kreibig SD. (2010). Autonomic Nervous System Activity in Emotion: A Review. Biological Psychology, 84(3), 394–421. DOI: 10.1016/j.biopsycho.2010.03.010.
A broad review of experimentally measured autonomic changes associated with emotional states and the complexity of physiological response patterns.
Bradley MM, Sambuco N, Lang PJ. (2023). Imagery, emotion, and bioinformational theory: From body to brain. Biological Psychology, 183, 108669. DOI: 10.1016/j.biopsycho.2023.108669.
Relevant to the capacity of language-guided imagery and emotional representation to recruit measurable response systems.
Mertens G, Lund M, Engelhard IM. (2021). The effectiveness of dual-task interventions for modulating emotional memories in the laboratory: A meta-analysis. Acta Psychologica, 220, 103424. DOI: 10.1016/j.actpsy.2021.103424.
A meta-analysis relevant to the observation that manipulating attention and eye movement during recall can alter reported vividness and emotionality of memory.
Desmurget M, Richard N, Harquel S, et al. (2014). Neural representations of ethologically relevant hand/mouth synergies in the human precentral gyrus. Proceedings of the National Academy of Sciences USA, 111(15), 5718–5722. DOI: 10.1073/pnas.1321909111.
Relevant to the FNI observation that hand and jaw movements may sometimes display coordinated cross-effector relationships.
Evidence status
Last research review: October 2026
This page should evolve as evidence evolves.
Research cited here may support background scientific principles, identify limitations or provide experimental parallels.
Unless a study directly investigates Functional Neuro-physiological Integration using a defined FNI protocol, it should not be described as evidence that FNI itself has been validated.
That distinction will remain central to the research development of FNI.
The research position of FNI
FNI does not need every current hypothesis to survive.
It needs a process capable of discovering which ones do.
The long-term objective is therefore not to protect the theory.
It is to progressively determine:
what is reproducible;
what is measurable;
what is clinically meaningful;
what is mechanism;
what is correlation;
what is artefact;
and what should be discarded.
That is how a clinical observation becomes a scientific question.
And it is how a scientific question can eventually become evidence.
Functional Neuro-physiological Integration
Observe → Measure → Challenge → Correct → Replay → Verify → Refine