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Noble Mind

An Exploration of Human Nature.

Consciousness, Intellect, and our Mind.

Our Noble Mind

Appendix H

The HI Theory of Variable Consciousness

Caveat

These theoretical papers have been produced to try and describe the fundamental concepts present in the Hemispheric Intelligence Mind Model in the more formal language used in the professional/practitioner world.
Citations are also included to attempt to indicate links and comparisons to existing knowledge and prior theories.
As a layman, I do not have direct access to prior knowledge nor the work of professionals, so I have used ChatGPT to try and compensate for my lacks. I have checked these texts as best I can but please be aware that the quality of these papers may be variable.
I also apologise for my typographical blunders. Constructive feedback is welcome!!

John Cochrane, 6 February 2026

Abstract

The HI Mind Theory of Variable Consciousness proposes an integrative framework for understanding the variability of conscious experience as an emergent property of distributed neural processing. The theory synthesises insights from contemporary neuroscience and cognitive science, including Global Workspace Theory (Baars, 1988; Dehaene and Changeux, 2011), predictive processing and active inference (Friston, 2010, 2018), distributed executive control (Miller and Cohen, 2001), and the Thousand Brains Model of intelligence (Hawkins and Blakeslee, 2021).
The HI Mind Model conceptualises the mind as a collection of semi-autonomous functional systems, referred to as Focuses. This abstraction reflects the widely supported view that the neocortex is not a single unified processor, but a distributed network of specialised systems operating in parallel (Fodor, 1983; Sporns, 2011). At any given moment, neural systems are concurrently engaged in activities such as:
• Interpreting sensory input
• Generating predictions about future states
• Retrieving and recombining memory
• Producing affective and motivational signals
• Proposing candidate actions
• Evaluating social and contextual outcomes
These processes unfold continuously, often at different temporal scales and with competing priorities (Cisek and Kalaska, 2010). Rather than producing disorganisation, this architecture gives rise to a dynamic and continuously shifting conscious experience.

Coherence Over Time

The multiplicity of parallel neural processes necessitates mechanisms that maintain coherence across time. Research in executive function and cognitive control suggests that coherence depends on integrative processes capable of:
• Establishing and revising priorities
• Maintaining competing representations
• Delaying or inhibiting actions
• Resolving goal conflicts
• Preserving continuity of self-related information
• Allocating attention toward salient stimuli
Within the HI Mind Model, these coordinating functions are attributed to the Planning Focus. This Focus is functionally analogous to frontoparietal control networks and prefrontal executive systems implicated in goal maintenance, conflict resolution, and temporal integration (Miller and Cohen, 2001; Dosenbach et al., 2008).
The Planning Focus is proposed to support Core Consciousness: a minimal, ongoing sense of subjective continuity. This proposal aligns with theories that associate consciousness with globally accessible, integrated representations rather than with any specific sensory or cognitive module (Baars, 1988; Dehaene et al., 2014). Core Consciousness, in this sense, reflects the brain’s capacity to maintain a coherent experiential narrative across fluctuating internal states.

Variability in Conscious Experience

The differentiation between Core Consciousness, specialised Focuses, and non-conscious processing offers a tractable simplification of the brain’s underlying complexity. Contemporary research demonstrates that much cognitive and affective processing occurs outside conscious awareness, including action selection, valuation, and perceptual inference (Nisbett and Wilson, 1977; Kahneman, 2011).
Although individuals are aware of emotions, urges, beliefs, and internal motivations, introspective access is necessarily limited. This limitation is adaptive: unrestricted access to the full volume of neural activity would overwhelm attentional and working memory capacities, undermining clarity and decision-making (Baddeley, 2007).
The HI Mind Model portrays the mind as an evolutionarily shaped system optimised for parallel processing. A person’s experienced state of mind depends on which Focuses are most active, their relative intensity, and how their outputs are integrated by the Planning Focus.
Beyond perception and reasoning, the brain continuously regulates energy balance, social positioning, affective stability, and exploratory behaviour (Sterling, 2012; Barrett, 2017). These regulatory processes generate fluctuations in mood, attention, and ideation, which are experienced phenomenologically as relaxation, excitement, inspiration, or emotional tension.

Focuses and the Construction of Conscious Experience

Some Focuses, such as the Aspirational and Noble Focuses, are characterised by intuitive, associative processing. Research on creativity and insight supports the view that novel ideas often emerge from non-linear, non-conscious mechanisms rather than from deliberate, stepwise reasoning (Kounios and Beeman, 2014).
By contrast, knowledge-based Focuses—such as Social and Cultural Focuses—support habitual, context-sensitive behaviour and social norm compliance, contributing to a subjective sense of confidence or automaticity in action (Bourdieu, 1990; Barrett et al., 2019). Activation of the Aspirational Focus may bias behaviour toward exploration and impulsivity, whereas the Noble Focus may prioritise long-term, prosocial, or value-driven goals.
The Planning Focus integrates these diverse influences, resolving conflicts and producing a coherent conscious narrative. In this view, conscious thought is not a transparent reflection of underlying cognition, but a constructed summary that enables coordination, prediction, and communication (Dennett, 1991).
Consistent with findings in cognitive psychology, this narrative conceals the parallel, automatic, and sometimes contradictory processes that shape behaviour. Experimental methods allow researchers to infer these hidden influences by revealing systematic biases, heuristics, and non-conscious drivers of decision-making (Kahneman and Tversky, 1979).

Compulsions, Emotions, and Imperatives

The HI Mind Model accounts for motivational conflict by distinguishing three interacting layers of motivation:
1. Compulsions, arising from subcortical and subconscious systems associated with habit formation, reward learning, and survival (Berridge and Kringelbach, 2015).
2. Emotions, which mediate between subconscious processes and conscious Focuses, shaping attention, valuation, and action readiness (Damasio, 1999; Barrett, 2017).
3. Imperatives, which bias long-term goal selection and behavioural tendencies across multiple Focuses, often without entering conscious awareness.
This layered structure is consistent with dual- and multi-system models of cognition, which distinguish fast, automatic motivational systems from slower, deliberative control processes (Evans and Stanovich, 2013).

Intelligence and the Thousand Brains Framework

The Thousand Brains Model provides a structural account of distributed intelligence that complements the HI Mind framework. According to this model, the neocortex consists of many semi-independent cortical columns, each capable of learning predictive models of the world and proposing actions in parallel (Hawkins and Blakeslee, 2021).
Within the HI Mind Theory, imperatives may be embedded within or emerge from this distributed architecture, shaping which internal models gain influence and which predictions guide behaviour. Although these imperatives are not directly accessible to introspection, their effects are evident in systematic patterns of attention, preference, and goal pursuit.From this perspective, intelligence is not a unitary faculty but an emergent property of coordinated distributed systems shaped by evolutionary pressures and individual learning. Consciousness, rather than being the origin of cognition, functions as an integrative interface that supports flexible adaptation across a complex internal landscape.

References

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Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., and Pollak, S. D. (2019). Emotional expressions reconsidered. Psychological Science in the Public Interest, 20(1), 1–68.
Berridge, K. C., and Kringelbach, M. L. (2015). Pleasure systems in the brain. Neuron, 86(3), 646–664.
Bourdieu, P. (1990). The logic of practice. Stanford University Press.
Cisek, P., and Kalaska, J. F. (2010). Neural mechanisms for interacting with a world full of action choices. Annual Review of Neuroscience, 33, 269–298.
Damasio, A. (1999). The feeling of what happens. Harcourt Brace.
Dehaene, S., and Changeux, J.-P. (2011). Experimental and theoretical approaches to conscious processing. Neuron, 70(2), 200–227.
Dehaene, S., Charles, L., King, J.-R., and Marti, S. (2014). Toward a computational theory of conscious processing. Current Opinion in Neurobiology, 25, 76–84.
Dennett, D. C. (1991). Consciousness explained. Little, Brown and Company.
Dosenbach, N. U. F., Fair, D. A., Cohen, A. L., Schlaggar, B. L., and Petersen, S. E. (2008). A dual-networks architecture of top-down control. Trends in Cognitive Sciences, 12(3), 99–105.
Evans, J. St. B. T., and Stanovich, K. E. (2013). Dual-process theories of higher cognition. Perspectives on Psychological Science, 8(3), 223–241.
Fodor, J. A. (1983). The modularity of mind. MIT Press.
Friston, K. (2010). The free-energy principle. Nature Reviews Neuroscience, 11(2), 127–138.
Friston, K. (2018). Does predictive coding have a future? Nature Neuroscience, 21(8), 1019–1021.
Hawkins, J., and Blakeslee, S. (2021). A thousand brains. Basic Books.
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Kahneman, D., and Tversky, A. (1979). Prospect theory. Econometrica, 47(2), 263–291.
Kounios, J., and Beeman, M. (2014). The cognitive neuroscience of insight. MIT Press.
Miller, E. K., and Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.
Nisbett, R. E., and Wilson, T. D. (1977). Telling more than we can know. Psychological Review, 84(3), 231–259.
Sporns, O. (2011). Networks of the brain. MIT Press.
Sterling, P. (2012). Allostasis. In Encyclopedia of behavioral medicine. Springer.