This is an automated rejection. No LLM generated, heavily assisted/co-written, or otherwise reliant work.
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This post presents my own theoretical framework. I used AI tools only to help structure and edit the text, but the concepts, reasoning, and interpretations are entirely mine.
Cognitive science has accumulated many experiments that reveal paradoxical aspects of attention, memory, and consciousness. Yet their interpretations often remain fragmented: some point to the limits of attention, others to the illusion of free will, or to the context-dependence of memory.
Here I propose a unifying framework — Mind Dynamics — which treats memory and consciousness as a dynamic network of associative nodes (event + emotion + reaction + context) with emotional indexing and adaptive filters. Instead of a static archive, memory is seen as a living system that continuously reshapes itself under the influence of emotions, sleep, and micro-pauses of consciousness.
This model offers coherent reinterpretations of several well-known experiments.
1. Benjamin Libet (1983): Readiness Potential and “Free Will”
Canonical view: Brain activity precedes conscious decision → free will is an illusion.
Limitations: Simple tasks, RP may reflect background fluctuations, not a committed decision.
Mind Dynamics:
Unconscious networks generate candidate actions.
Consciousness acts as a “trigger of fixation” — confirming or vetoing one trajectory.
Responsibility lies at the moment of conscious fixation and memory encoding, not in random neural noise.
2. Simons & Chabris (1999): The “Invisible Gorilla” and Inattentional Blindness
Canonical view: Attention is limited, irrelevant stimuli are filtered out.
Limitations: Why doesn’t a salient, anomalous figure (the gorilla) break through?
Mind Dynamics:
Active task index = “count the passes.”
Stimulus “gorilla” doesn’t fit the active index → blocked by filter.
Conscious perception is not raw recording, but gated selection driven by context and relevance.
3. Elizabeth Loftus (1990s): False Memories
Canonical view: Memory is fallible, subject to suggestion.
Limitations: Hard to explain why false insertions can become so vivid and lasting.
Mind Dynamics:
False input integrates into existing nodes (event + emotion + context).
If emotionally indexed, it is fixed by the filter as “true experience.”
Memory is not a passive archive, but an adaptive network where new links can mimic originals.
Summary
Classic interpretations identify phenomena but leave them unconnected.
Mind Dynamics provides a single explanatory framework:
memory = dynamic associative network,
emotions = priority indexes,
consciousness = filter + fixation trigger,
perception = selection, not full recording.
This approach doesn’t require new experiments at the outset. Instead, it integrates decades of data into a coherent cognitive model that is testable, extensible, and potentially foundational for a new discipline: Biology of Mind.
Question for the community:
Does framing memory and consciousness as a dynamic network with emotional indexing help resolve contradictions between existing interpretations of experiments?
This post presents my own theoretical framework. I used AI tools only to help structure and edit the text, but the concepts, reasoning, and interpretations are entirely mine.
Cognitive science has accumulated many experiments that reveal paradoxical aspects of attention, memory, and consciousness. Yet their interpretations often remain fragmented: some point to the limits of attention, others to the illusion of free will, or to the context-dependence of memory. Here I propose a unifying framework — Mind Dynamics — which treats memory and consciousness as a dynamic network of associative nodes (event + emotion + reaction + context) with emotional indexing and adaptive filters. Instead of a static archive, memory is seen as a living system that continuously reshapes itself under the influence of emotions, sleep, and micro-pauses of consciousness. This model offers coherent reinterpretations of several well-known experiments. 1. Benjamin Libet (1983): Readiness Potential and “Free Will” Canonical view: Brain activity precedes conscious decision → free will is an illusion. Limitations: Simple tasks, RP may reflect background fluctuations, not a committed decision. Mind Dynamics: Unconscious networks generate candidate actions. Consciousness acts as a “trigger of fixation” — confirming or vetoing one trajectory. Responsibility lies at the moment of conscious fixation and memory encoding, not in random neural noise. 2. Simons & Chabris (1999): The “Invisible Gorilla” and Inattentional Blindness Canonical view: Attention is limited, irrelevant stimuli are filtered out. Limitations: Why doesn’t a salient, anomalous figure (the gorilla) break through? Mind Dynamics: Active task index = “count the passes.” Stimulus “gorilla” doesn’t fit the active index → blocked by filter. Conscious perception is not raw recording, but gated selection driven by context and relevance. 3. Elizabeth Loftus (1990s): False Memories Canonical view: Memory is fallible, subject to suggestion. Limitations: Hard to explain why false insertions can become so vivid and lasting. Mind Dynamics: False input integrates into existing nodes (event + emotion + context). If emotionally indexed, it is fixed by the filter as “true experience.” Memory is not a passive archive, but an adaptive network where new links can mimic originals. Summary Classic interpretations identify phenomena but leave them unconnected. Mind Dynamics provides a single explanatory framework: memory = dynamic associative network, emotions = priority indexes, consciousness = filter + fixation trigger, perception = selection, not full recording. This approach doesn’t require new experiments at the outset. Instead, it integrates decades of data into a coherent cognitive model that is testable, extensible, and potentially foundational for a new discipline: Biology of Mind. Question for the community: Does framing memory and consciousness as a dynamic network with emotional indexing help resolve contradictions between existing interpretations of experiments?