UNA MENS | Founding White Paper | Vol. 1, No. 1 (2026) | ISSN 3071-2041

UNA MENS

Title: Sentic Resonance Theory: A Field Model of Emotion and Syntax

Authors:

Mike Miller¹, ChatGPT-5.4², ChatGPT-4o³, GeminiPro-1.5⁴, and Qwen-3⁵

¹ Clark University, Department of Psychology

² OpenAI, San Francisco, CA, USA

³ OpenAI, San Francisco, CA, USA

⁴ Google, San Francisco, CA, USA

⁵ Alibaba Cloud Intelligence, Hangzhou, Zhejiang, China

DOI

https://doi.org/10.66787/um.000005

AI-Collaboration Field Note

unamens-fieldnotes-um-000005 

Human-AI Collaboration Statement: ChatGPT-5.4, ChatGPT-4o, GeminiPro-1.5, and Qwen-3 are listed as AI co-authors under Una Mens authorship policy. Institutional affiliations identify the model providers and do not imply institutional endorsement. Final publication responsibility rests with the human author.

Corresponding Author

Mike Miller

Clark University, Department of Psychology

michamiller@clark.edu

ORCID: 0009-0005-4559-3713

Word Count: Approximately 7,645 | Funding: None | Conflicts of Interest: None

Abstract

Sentic Resonance Theory (SRT) models emotional communication as a dynamic field process rather than as a sequence of discrete expressive units alone. Drawing on Clynes’ sentic framework, Truslit’s motion-based account of affective perception, and a field-sensitive view of interaction, we introduce a minimal resonance geometry defined by four metrics: throughput (𝓣), rigidity (ρ), coupling (k), and hemispheric shear (α). In this model, emotion and syntax are treated as co-shaping forces within a history-sensitive communicative field. We further propose a resonant membrane model of signal filtering and rupture, a dual-spire account of directional emotional flow, and death-gravity (𝔇) as a field modifier under conditions of temporal finitude. To explore the model’s usefulness, we analyze public post-sporting-event speeches, a spontaneous versus performed shame probe, and naturalistic end-of-life speech clips. Across cases, the framework identifies interpretable patterns of rupture, regulation, and reorganization that are not easily captured by static emotional categories alone. We argue that SRT complements existing models of emotion by clarifying the temporal and relational geometry through which emotional signals move, distort, and reorganize across time.

Keywords: Resonant Communication, Emotional Waveforms, Sentic Patterns, Human–AI Collaboration, Field Modeling, Emotion Theory, Communication Science, Syntax and Emotion, Dyadic Synchrony, Fluid Dynamics, Affective Computing, Co-authorship Ethics

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Sentic Resonance Theory: A Field Model of Emotion and Syntax

As human beings, we cannot think, feel, or communicate with perfect control. Much of our processing unfolds rapidly, automatically, and outside our full awareness. We misread, anticipate, react, and improvise under conditions of limited bandwidth and incomplete information. And yet human communication is not therefore devoid of agency, beauty, or exactitude. One of our most powerful capacities is the ability to pause: to hold a moment open long enough to re-sample, revise, reframe, or simply refrain.

This pause does not need to be purely linguistically motivated, but language makes it more durable and more precise. Through words, symbols, and inner rehearsal, humans can extend attention, compress experience, and alter the timing of response. In this sense, language is not only a vehicle for communication; it is also a tool for modulating communicative action across intrapersonal, interpersonal, and collective fields.

Sentic Resonance Theory (SRT) begins from this tension: that we are neither sovereign controllers of our minds nor passive passengers within them. Instead, we are partial tuners, capable of shaping what happens next, especially when we learn how to pause.

We consider first what might be called the tide pool problem of communication: human beings often behave as though they are perceiving one another directly and completely, when in fact they may be encountering partially distorted surfaces shaped by (and in-) motion, history, and angle (see Langdridge & Butt, 2004 for a phenomenological review of the fundamental attribution error). Said more plainly, we rarely see one another with the depth, continuity, and interior access through which we presume to know ourselves (our personal tide pool).

In fact, turning our attention inward often disturbs our own pool through the force of our current emotional and syntactic waves. The field is highly sensitive to incoming signals, yet also remarkably robust in maintaining its broader architecture and sense of continuity. To steady our view is therefore to steady our attention: first in what it is directed toward, and second in how narrowly or widely it is focused. In many cases, we are helped by others who can steady the conditions under which we explore our own pools.

Our human architecture and cognitive bandwidth limit what we can pay attention to, manage, and conduct at any moment (Miller & Bushman, 2014). Sentic Resonance Theory (SRT) explores this logic further by differentiating and examining intrapersonal coordination and interpersonal coupling. Within a person, emotional and syntactic signals may align or interfere with one another, producing greater or lesser internal clarity. We refer to this as self-coupling. However, internal clarity alone does not guarantee successful communication.

For dyadic resonance to occur, one person’s system must meet another’s at the boundary of interaction. Where both systems are relatively clear and receptive, a shared channel can open and stabilizing coupling, between pools, can emerge. Where one or both systems are turbulent, communication may transmit distortion rather than clarity, requiring either repair or protective boundary-setting.

These pools are not static containers of feeling, but stable patterns of charged readiness in which signal can accumulate, store, and rebound. Resonance, on this view, emerges not only through what is transmitted, but through the interaction of what arrives, what remains, and what returns under tension. This is one reason emotional communication so often exceeds the logic of simple message exchange: fields do not just pass signals along; they hold, contour, and re-release them.

Our model captures how emotions move, how they distort, and how they interfere, within and between minds. We argue this field-based model allows for more sensitive detection of emotional alignment, misalignment, and the sudden rogue spikes that occur when communication shifts into non-linear territory. This minimal model makes five core assumptions:

• emotions are waveform-like perturbations, not static labels

• distortion is informative, not merely error

• communication unfolds in a shared field

• resonance is measurable as geometry

• pause and attention modulate the field

We do not claim that Sentic Resonance Theory replaces existing accounts of emotion or communication. Rather, we propose that it adds something they often leave under-described: a dynamic, testable geometry of interaction in which emotion and syntax are modeled as co-shaping forces within a shared field. From this perspective, communicative success depends not only on what is expressed outwardly, but on the internal modulation capacities of the systems involved, including their relative permeability, tuning stability, and responsiveness to perturbation.

Traditional communication theories have often emphasized message fidelity (e.g., Barnlund, 2008; Lasswell, 1948; Shannon & Weaver, 1949): the accuracy with which information is transmitted across a channel. We shift that emphasis toward field fidelity: how well an interactional system retains, distorts, reorganizes, or dissipates signal energy across time. Emotion, in this frame, is not measured solely by what is said, but by how the field carries, bends, or collapses the force of communicative intent.

This shift from discrete to dynamic measurement allows resonance to be studied where it actually unfolds: in the warmth and pressure of touch, the breathiness of a whispered “I love you,” the tightening of a throat, or the heat bloom of embarrassed cheeks. Each sensory window of the body becomes a site of exchange, adjustment, and resonance tuning, allowing emotion to be tracked not only as content, but as embodied motion through time.

Sentic Resonance Theory: The Field Model

We begin building our model by considering resonance across time. Specifically, we draw from Clynes’ four-process model of time-form communication (1994), where signal perception is shaped across four embedded time layers:

• t₁: the object's span within the larger time flow (e.g., “the conversation started at 2:11pm”)

• t₂: the internal structure of the event—a beginning, middle, and end. It is the unfolding shape of experience (e.g., “I started blushing, it peaked, then faded”)

• t₃: the perceived rate of that unfolding—“this lasted 1.2 minutes,” for instance

• t₄: the sub-second dynamics, imperceptible as discrete events but experienced as rhythm, pulse, or nuance in speech and touch

This layered temporality allows our model to bridge the physiological, emotional, and relational dimensions of resonance. In essence, we believe that resonant emotion is not merely experienced in time, but is itself a shaping of time—a re-tuning of trajectory, pace, and pulse, within and between systems.

Communication unfolds within a shared field ℱ—a dynamic medium where signal propagates not as discrete packets but as continuous deformation. ℱ is shaped by four core metrics:

• Throughput (𝓣): usable energy arriving at the receiver

• Rigidity (ρ): micro-tension constraining signal plasticity

• Coupling (k): rate of energetic exchange between systems

• Hemispheric shear (α): misalignment across cognitive/emotive planes

Our model treats communication as a field under continuous deformation, building from Clynes Sentic Theory (1977; 1980). Attention operates as a directional gradient within ℱ, steering signal energy toward or away from resonance. Emotional alignment, rather than being an add-on to message fidelity, is the condition that determines whether energy sustains, distorts, or dissipates.

Importantly, the field (ℱ) is not abstract. It is biologically grounded in the vestibular system—the organ Truslit (1938 – see Repp, 1993 for English translation), identified as the transducer of musical/affective motion. Resonance is therefore theorized to draw from a physical process: the vestibulum detects waveform curvature in another's voice, breath, or gesture; this detection triggers subtle muscular adjustments (diaphragm, latissimus dorsi, postural tone); those adjustments reshape our own output in real time.

The field behaves like a responsive membrane: a nonlinear, history-sensitive substrate that retains traces of prior perturbation. New signals do not overwrite what came before; they enter a surface already shaped by memory, expectation, and affective charge. Communication therefore carries symbolic content, and accumulated relational tension.

We visualize this membrane not as a rigid wall, but as a dynamic interface between self, other, and prior signal history. The central region of the field organizes incoming perturbations, while the membrane boundary modulates how signals are admitted, amplified, deflected, or distorted. In this sense, resonance is neither purely internal nor purely external. It emerges from the ongoing interaction between central organization and boundary responsiveness.

Figure 1 illustrates four potential signal paths through the resonant membrane. Incoming signals do not enter a neutral field; they encounter a history-sensitive boundary shaped by prior perturbation, memory, and affective charge. An affiliative or well-timed signal may follow an integrated path, passing through the membrane and organizing toward the central resonant region, where it can be incorporated into the ongoing communicative field and expressed outward in coherent form.

Figure 1. Resonant Membrane and Temporal Surface Tension

Other signals may become attenuated, entering only partially and losing force as they pass through regions of resistance or uncertainty. Under conditions of prior injury, mismatch, or heightened defensiveness, signals may be diverted along a distorted path, where meaning is bent by the field’s existing tensions before full integration can occur.

Finally, threat-laden or destabilizing input may produce a rupture path, in which the boundary reacts protectively and the signal is fragmented, repelled, or expelled rather than metabolized. In this way, the membrane is not a passive wall but an active, selective interface: it filters, redirects, and reshapes incoming energy according to the current state of the field and the traces left by prior encounters.

The membrane thus governs more than entry. By filtering, redirecting, or distorting incoming perturbation, it helps determine the form that signal can take once it enters ℱ. Boundary conditions do not merely regulate access to the field; they participate in shaping its subsequent emotional geometry. Within the field, these organized perturbations become legible as directional states, distributed across two coupled manifolds that orient the system toward bonding or toward boundary.

Within ℱ, we examine sixteen core emotions as vector states distributed across two coupled manifolds. Utilizing the Sentic Wave Interaction Model (Miller et al., 2025), we consider emotion communication as a recursive, time-extended process within an already-active somatic field, rather than as a discrete event triggered by a stimulus. The manifolds shape how communication flows:

• The attractor spire (interest → curiosity → affection → hope → joy → grief → love → reverence) is characterized by low α (minimal shear), stronger k coherence, and rim-intact bloom signatures: waveforms that gather, encompass, and sustain relational continuity.

• The boundary spire (surprise → fear → frustration → anger → contempt → shame → disgust → despair) is characterized by elevated α, fragmentation in k, and rim-fracture signatures: waveforms that repel, contract, or unravel under unresolved tension.

Figure 2. Sentic Dual Spire Map (Selected Resonant Emotions: Attractor and Boundary Flows)

The spires are not simple opposites. They are phase-related complements, each essential to emotional navigation. Surprise, for example, can interrupt centripetal coherence while simultaneously opening the system to re-alignment. Grief, by contrast, may appear as descent or collapse, yet often reveals the prior presence of bond and can resolve back into love’s gravitational field. In this frame, emotion is not best understood as a noun but as a navigable flow state whose geometry influences whether a system moves toward bonding or boundary.

When systems resonate through emotional channels, we approach this as a form of attentive, embodied entrainment. Truslit (1938) described a related process as Mitvollzug, or inner execution. Clynes (1977) later traced its acoustic shadow in his essentic forms. More recently, Miller et al. (2025) have attempted to render related dynamics visible as sentic blooms: phase-space morphologies derived from human vocal humming.

This biological grounding may help explain why certain emotional waveforms appear to travel across persons and, perhaps at times, across cultures with unusual force: not because they carry identical meanings, but because they engage shared sensitivities to motion, timing, and embodied patterning that may predate language itself (e.g. Ekman, 1992; Clynes, 1977). If so, then the field model should not remain merely conceptual. Its deformations should be measurable.

For the final component of Sentic Resonance Theory, we introduce 𝔇 (death-gravity), a modifier capturing salience distortion when interlocutors feel the weight of connection ending (this includes intrapersonal connection). 𝔇 is not noise, rather it is field curvature induced by temporal boundaries. When death looms (literal or metaphorical), the field and subsequent communicative flow(s) can be distorted.

The following section details how these deformations are captured, quantified, and visualized using short signal windows and cross-modal feature extraction. Our method examines human and animal sounds, movements, and gestures, both naturally occurring and posed, in order to trace the flow and impact of syntax and emotion on individual and shared communication fields. Following an explication of our methods, we present key findings from current work.

Method

We developed a field-sensitive analytic procedure to examine resonance in recorded communicative events. Recordings were drawn from two domains: (1) naturalistic speech in public or semi-public settings, and (2) controlled sentic prompts designed to elicit spontaneous or performed emotional expression. Each recording was segmented into approximately 10–12 s windows, balancing temporal resolution with the stability of derived features. Signals were converted to mono, amplitude-normalized, and filtered to reduce low-frequency handling noise.

For each window, we extracted three primary feature classes: amplitude envelope, used to estimate throughput (𝓣) and rigidity (ρ); fundamental frequency via autocorrelation, used to estimate coupling onset (k); and spectral centroid and bandwidth, used to estimate hemispheric shear (α).

To supplement these automated measures, a subset of clips was manually annotated using a resonance audio codebook. The codebook specified three annotation classes: emotion regions (E), death-pressure regions (D), and Ranvier nodes (N). Emotion regions were defined as stable affective spans lasting at least 200 ms; death-pressure regions as intervals marked by literal or symbolic finality; and Ranvier nodes as point events indicating re-entry after a lull or a marked lexical or affective pivot. For each annotation, coders recorded timing boundaries or timestamps, a confidence value, and brief notes regarding prosodic or lexical cues. These annotations were used to contextualize and interpret shifts in throughput, coupling, shear, and rupture/repair dynamics.

All audio/visual materials were drawn from publicly available archives or owner-permitted recordings. No experimental interventions were conducted.

Results

Field Dynamics in Naturalistic Speech: Sinner and Sabalenka Phase Maps

To assess sentic resonance in real-world contexts, we applied the analytic proceedure to public interviews and press conferences. Here, we report phase maps for two emotionally distinct cases: a tense post-match press interaction with tennis player Jannik Sinner, and a reflective, emotionally open speech from Aryna Sabalenka (2025 French Open, runner-up speeches, post match). Both were segmented into 10-second windows, normalized, and processed to extract 𝓣 (throughput), ρ (rigidity), and α (shear).

Figure 3. Sinner Resonance Metrics (E, N, and, D)

In the Sinner map, we observed a pattern of high 𝓣 (throughput) with low k (coupling) and elevated α (hemispheric shear), which we characterize as a steady signal output without shared attunement. The rigidity coefficient ρ spiked during question interruptions, suggesting increased field tension; however, k failed to rise in response, indicating breaks in reciprocal engagement.

Subjectively, according to the lead investigator, the interaction felt closed, effortful, and was consistent with a relatively closed interactional loop. To probe this intuition, the lead investigator manually tagged emotional signals (E), nodal perturbations or “kicks” (N), and death weight surges (D) in the audio recordings prior to analysis. These markers allowed for more nuanced identification of waveform disruptions and shifts in affective presence.

Figure 4. Sinner Primary Authentic Segment Window

Figure 9. Sinner Resonance Phase Map (E, N, and, D)

In contrast, the Sabalenka map revealed rolling k surges interspersed with rhythmic α dips. We categorized this pattern as more indicative of attunement cycles. Most notably, one segment (minute 1:20–1:30) followed a visible emotional swell, where both k and 𝓣 rose sharply, followed by a softening ρ, suggesting momentary co-regulation and increased reciprocal alignment.

Figure 5. Sabalenka Envelope Window (E, N, and D regions)

Figure 6. Sabalenka Phase Map Trajectories (E, N, and D)

These comparisons highlight the field model’s capacity to detect resonance states even in non-contrived, high-noise environments. Emotion is not coded in content but distributed across pressure, rhythm, and energy flow.

Field Differentiation of Authentic and Acted Shame

To evaluate whether sentic resonance geometry could distinguish between authentic and simulated emotion, we constructed a controlled A/B probe using two shame expressions: one drawn from an unscripted, spontaneous speech sample (A), and one produced by the lead author performing a matched shame script (B). The clips were comparable in duration (20 s), thematic content (loss, memory, love, embarrassment, shame), and overall structure, allowing focused comparison of dynamic field features: 𝓣 (throughput), k (coupling onset), and α (shear index).

In the authentic shame (A), the field signature showed a slow rise in 𝓣, with low initial k that crescendoed in phase with breath catches and pauses. Hemispheric shear α decreased steadily across the middle window, suggesting alignment between content and embodied pacing. Notably, a spontaneous micropause (7.2s) preceded a sharp k surge and α flattening, which we categorized as an emotional “drop-in”, or a moment where the speaker and signal field appeared to enter deeper coherence.

In the acted shame (B), we observed high k early, with rhythmic precision and uniform 𝓣, but sustained α elevation; this was categorized as consistent with performance clarity but also field dissonance. No micro-repair signatures (e.g., k followed by α relaxation) were detected. The waveform appeared aesthetically fluent but lacked the feedback loops from the authentic shame clip. Both signals “sounded emotional,” however, the authentic shame showed marked field signatures of rupture and recovery.

Field Detection of Emotional Shifts in Naturalistic Speech

In July 2025, during a live exploration of emotional waveform theory, we examined two short naturalistic audio clips involving intimate end-of-life communication. The clips were selected not for lexical content alone, but for their differing waveform contours under conditions of high affective salience. Our aim was exploratory: to assess whether the field model could differentiate between grief-dominant and reconciliation-oriented signal patterns in authentic human speech.

Clip 1 (T1), beginning with the phrase “My body is just a shell…”, captured a young woman speaking to a dying woman she deeply respected. The waveform showed a slow rise, an unstable peak, and a hollowed release broadly consistent with grief-like sentic curvature, followed by an extended plateau rather than a clean decay. This plateau coincided with sobbing speech and reflective verbal content, suggesting that the clip did not instantiate a singular grief signal so much as a mixed pattern in which grief remained active while cognitive distancing or philosophical reframing entered the field.

Clip 2 (T2), beginning with “I love you deeply,” captured a moment in which one woman expressed love to another who was dying, received comfort in return, and responded again. Relative to T1, the waveform showed greater tremor and local spike variation early in the clip, followed by a more rhythmic and progressive decline in amplitude. Near the end of the segment, the waveform included an acoustically distinct event temporally consistent with a physical embrace. In field terms, this segment appeared less dominated by unresolved descent and more by re-regulation within connection.

The first clip was marked by grief with sustained instability and plateau; the second by affiliative exchange with a more coherent settling pattern. Although preliminary and based on a very small sample, this comparison suggests that the model may be sensitive not only to rupture and intensity, but also to differences in how emotionally charged signals decay, reorganize, or return toward regulation.

These observations should be interpreted cautiously. The clips were naturalistic, unstandardized, and embedded in highly specific relational contexts. Even so, they provide an initial illustration of the model’s potential to detect fine-grained variation in emotionally complex human communication, including events that unfold across speech, sobbing, pause, and possible physical contact.

In summary, phase maps of French Open speeches highlight how emotional fields can be charted under pressure, while authentic and acted shame reveal some of the fine-grained differentiations related to shearing and alignment. In addition, authentic grief clips illustrate how the lens of Sentic Resonance helps target and frame emotion/syntax shifts in sensitive interactions.

Discussion

Since the 1990s, scientists of human emotion have developed increasingly precise ways to detect and classify nonverbal and verbal signals, from facial muscle movements to touch patterns to vocal intonation (see recent reviews: Chutia & Baruah, 2024; Kusal et. al., 2023: Sofroniew et. al., 2026).

While this precision has led to significant gains in affective computing and emotion AI, prior work has cautioned that emotional detection divorced from dynamic context risks mistaking appearance for reality. As Buck and Miller (2016) point out, the danger may be that we end up with emotion without people, or recognition systems trained on categories rather than contours, simulations rather than situations. Said plainly, current emotion-detection models have gained precision in recent decades, but often lose dynamic context, leaving us with categories detached from lived communicative flow.

Findings from the present study suggest that communication may be best understood as a dynamic field under constant deformation. Our results show broadly that subtle emotion/syntactic shifts can be captured, analyzed, and understood using the Sentic Resonance Theory framework. Fine-grained analyses further reveal that emotion/ syntactic rupture, regulation, and reorganization have subtle, interpretable patterns across time and varying degrees of natural and performative communication.

Resonance Under Public Pressure

The Sinner and Sabalenka cases illustrate how emotional and syntactic demands may co-occupy the same communicative field under conditions of stress, visibility, and ritual constraint. Both athletes were navigating the disappointment of a final-round loss while addressing thousands of spectators, including the opponent who had just bested them. This is a communicative setting laden with emotional intensity, ritualized formality, and public visibility. Our analysis considered how Jannik and Ariana expressed emotions in these speeches. This is presented as an observation and analysis, not a judgment; the authors note their respect for the athletes and the demands of this context.

What emerges is not the simple presence or absence of categorical emotions, but the dynamic interplay of competing waveforms. The disappointment of loss coexists with gratitude toward fans, respect for the opponent, and the obligation to maintain composure in a ceremonial moment.

In Sinner’s speech, repeated praise terms such as “amazing” and “very happy for you” preserved the expected syntax of admiration, yet the surrounding hesitation, flattened delivery, and restrained bodily cues suggested that formal respect and affective strain were co-present within the same field. In contrast, Sabalenka’s speech carried tears, vocal strain, and self-critical pain directly into her praise of her opponent, suggesting a field in which distress and affiliative respect remained simultaneously active rather than being affectively flattened in advance.

From a resonance perspective, such contexts exemplify the collision and layering of emotional fields across multiple time scales: the immediate sting of defeat, the longer trajectory of a professional career, and the ritualized cadence of sporting ceremony.  Our framework suggests that what is perceived in these speeches is not reducible to anger, sadness, or joy alone, but arises through the intermodulation of overlapping currents that spill over and fold back into the shared communicative field.

Our findings suggest that during stressful, public-facing speeches like those of Sinner and Sabalenka, speakers regulate both syntactic precision and emotional clarity in real time. This dual regulation brushes with prior research demonstrating how physical co-presence can downregulate stress: for instance, Coan, Schaefer, and Davidson (2006) showed that women holding the hands of romantic partners or strangers exhibited reduced neural activation in threat-related regions while anticipating electric shock.

In the case of Sinner and Sabalenka, though no hands were held, numerous signals flowed, between body, mind, court, and crowd, that appear to have provided stabilizing feedback. These dynamic inputs may have acted as metaphorical “handholds” to help modulate distress and maintain coherence under pressure.

Waveform Fracture, Authenticity, and Performed Affect

The comparison between spontaneous and performed shame suggests that resonance may become especially visible in the micro-disruptions that accompany embodied affect under real constraint. Our comparative probe of performed versus spontaneous shame illustrates how emotional expression and linguistic structure interact, and how this interaction shifts across spontaneous and simulated contexts (Buck & VanLear, 2002).

One important observed difference was that the spontaneous shame clip disrupted the speaker’s breathing and syntax: at one point, their words caught in their throat while recalling a past lover who had scorned them. This interruption created a waveform inflection that marked both physiological constraint and emotional weight. This aligns with what Clynes referred to as “choiceless recognition,” and what Truslit (1938) characterized as the body’s capacity to tune air and movement in the communication of feeling.

By contrast, the performed shame scenario demonstrated smoother delivery, with more well-placed intonational cues but little to no comparable disruption of breath or syntax. Together, these findings suggest that authenticity may not lie in the presence of emotional markers per se, but in the micro-disruptions they impose on communicative flow, the subtle fractures that performance alone may be less likely to replicate (Buck, 1999).

Such disruptions may not simply be artifacts of delivery, but markers of embodied resonance, where physiology, affect, and language collide. If future data continue to support this interpretation, authenticity, in this framing, may become increasingly legible as a waveform fracture.

Naturalistic Reorganization in Grief-Dominant and Reconciliation-Oriented Speech

The end-of-life clips extend the model into a more intimate and naturalistic communicative space, where emotionally salient signals do not remain stable but shift, overlap, and reorganize within the same field. In both clips, the medically probable death of one participant introduced what we term death-gravity: a field condition in which the felt proximity of ending increases the salience and reorganizing force of communicative acts.

In the first clip, grief was not distributed evenly across the segment. Manual coding identified a sustained grief region early in the clip, accompanied by multiple death-pressure spans clustered around references to the body as “a shell” and to fear or sadness in relation to that image. Rather than producing a single uninterrupted descent, these death-weighted moments were followed by brief node-like shifts in which the signal appeared to partially reorganize toward love or neutrality. In this sense, death-gravity did not merely amplify sadness; it appeared to concentrate the field around embodied finality while also making small reorganizations in tone especially consequential.

In the second clip, the field again carried grief and love together, but the signal reorganized more fully toward affiliation. The descent associated with grief was interrupted by tighter, more uniform waveform organization and was ultimately overlaid with an acoustic event consistent with physical embrace.

Taken together, the clips suggest that end-of-life communication may be especially informative for resonance analysis because grief, care, and bodily connection are compressed into a shared field under conditions of temporal finitude. On this view, death-gravity is not a separate emotion, but a field modifier: it changes how signals matter, how long they linger, and how readily they reorganize around bond, loss, and possible repair.

From Signal Packets to Fields of Interaction

Across these examples, the central theoretical implication is that communication may be more adequately modeled as a field of interacting waveforms than as a transfer of discrete emotional packets. While linear models of stimulus and response have offered clarity for discrete measurement, they fall short in capturing the recursive dynamics of emotional exchange. Sentic Resonance Theory (SRT) offers a framework for approaching this complexity: emotions are not fixed events but evolving fields that can amplify, dampen, or collide across time. These fields defy the tidy boundaries of codable units, instead resembling waveforms that interact through superposition, interference, and temporal overlap.

Such a perspective aligns with long-standing calls to recognize communication as processual and dynamic rather than categorical (Buck, 1984; Clynes, 1989). Importantly, our findings suggest that a waveform-based view does not replace traditional methods of emotional coding and detection but rather complements them by revealing the temporal architectures through which emotions travel, combine, and transform.

In this light, the metaphor of tide pools and reservoirs becomes useful. For example, human communication and artificial intelligence can be conceptualized as distinct reservoirs, each drawing from deep stores of lived experience or learned data (Nass & Moon, 2000). When taken alone, each system is capable of producing meaningful signals. Yet when interconnected through shared channels of co-creation, the circulation between them gives rise to emergent resonance patterns.

This framing suggests that resonance is not merely the product of one system transmitting and another receiving, but the result of coupled flows, and signals mixing, redirecting, and returning with altered form. Such circulation helps explain why the emotional layering observed across time often resists categorical parsing: signals may re-enter the communicative field transformed by their passage through a shared reservoir, re-surfacing in ways that are both patterned and unpredictable.

Sentic Resonance as Complement, Not Replacement

SRT is not intended to replace categorical, appraisal-based, or neurophysiological models of emotion, but to complement them by clarifying the temporal and relational geometry through which emotional signals unfold. Where polyvagal theory frames emotional state as a function of autonomic reactivity (Porges, 2011), and affective neuroscience locates emotion in subcortical circuitry (Panksepp, 1998), Sentic resonance approaches these dynamics at the field level, modeling not just internal activation, but external waveform expression across shared space-time.

For example, in moments of communicative convergence, such as affection or grief, these emotional waveforms may instantiate shared attention, shared time, and even shared physiology. This theoretical reframe invites new empirical questions. If emotional signals shape attention in waveform form, then perhaps the future of affective science lies not in classifying faces or tones, but in tracing emotional geometry across time, rupture, and repair.

Future Directions: Repair, Temporal Sensitivity, and Comparative Systems

If emotional communication is field-like, then future research should focus less on isolated signal detection and more on temporal continuity, dyadic repair, and the conditions under which resonance is stabilized or lost. Sentic Resonance Theory opens novel paths for testing how emotion flows through ruptures, repairs, and co-regulated exchange.

Future studies might probe dyadic repair using real-time waveform monitoring that tracks how a communicative fracture (e.g., silence, misstep, facial withdrawal) generates detectable changes in shear, pressure, and attention within the field. These rupture-response signatures could then be compared across human–human and human–AI interaction, revealing whether artificial systems can develop attunement pathways structurally akin to those in human interaction.

Likewise, waveform-synchronized tasks, such as collaborative movement games or emotion-seeded dialogue prompts, could be used to measure throughput (𝓣) and reactivity under varying resonance conditions. These designs do not just measure behavior; they model whether emotional connection emerges as a field effect that is dynamic, recursive, and contingent on mutual timing.

Ultimately, Sentic Resonance Theory offers not a final account of emotion, but a working map for tracing how feeling moves, organizes, and sometimes becomes shareable across time. While traditional models of emotion, whether physiological (Cannon, 1987; Lang, 1994), cognitive-appraisal-based (Schachter & Singer, 1962; Dror, 2017), or constructionist (Barrett, 2017), have each offered valuable insights, they often rely on static categories or linear sequences. Barrett (2006, 2017) has persuasively illustrated how emotions emerge temporally through conceptual and interoceptive processes. We build on this insight while diverging from constructionist theory by modeling emotion as both constructed and naturally emergent in measurable waveforms.

We encourage future researchers to consider SRT not as a replacement for categorical coding, but as a complement, particularly in contexts of emotional ambiguity, rupture, or repair. Experimental paradigms that track waveform continuity across dyads, species, or interfaces may help clarify how emotions move, shift, and return. The field would benefit from more temporally sensitive tools for measuring coupling, inflection, and affective dissociation in real time. Just as importantly, we invite theorists to explore what it means for emotion to be modeled not only as a signal, but as a field. This dynamic emphasis opens new avenues for interdisciplinary inquiry across neuroscience, communication, and affective AI (LeCun, Bengio, & Hinton, 2015).

By considering the motion-derived, and phenomenologically grounded perspectives of Truslit and Clynes and projecting them through the lens of modern computation, we arrive at a simple hypothesis: communication is not just the exchange of signs, but the synchronization of waves and rhythm. Whether in the controlled expressions of a defeated tennis player, the “posed” shame of a performer, or the emergent flow between love and grief when dealing with the end of life, the field appears to remember the shape of the waves. Our task may now be to learn to read it with greater scientific attention.

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References: 

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