Reading A Universe of Consciousness

I’ve just finished reading A Universe of Consciousness by Gerald Edelman and Giulio Tononi. Rather than focusing heavily on experimental data, the book offers a high-level conceptual framework for how the brain gives rise to consciousness. That approach resonates with me—once we understand the overarching structure, we can begin to interpret experimental findings as either supporting or challenging the theory.

Three Systems

One of the most valuable insights for me was the book’s description of the brain as comprising three main systems:

The thalamocortical system
The cortical appendages
The neuromodulatory value system

In short, the thalamocortical system acts as the primary input–processing–output network. Sensory signals arrive via the thalamus and are processed through the cerebral cortex, where consciousness emerges from this dynamic activity. The cortical appendages—structures like the cerebellum and basal ganglia—refine and modulate the outputs of the main system, often operating below the level of awareness. Finally, the neuromodulatory value system (e.g., dopaminergic or noradrenergic systems) diffuses chemicals throughout the brain, modulating global states such as mood. With these systems in mind, many pieces of neuroscientific evidence begin to make sense within a unified framework.

10Hz

The second major idea that struck me was the time scale of consciousness. Not long ago, I was playing a stopwatch game with my son to see who could tap the button with the shortest interval between presses. The best we managed was around 0.1 seconds. Reading the book, I was fascinated to learn that this aligns with a basic physiological constraint: we can’t consciously distinguish two stimuli unless one completes before the next begins—typically requiring 100–150 milliseconds. This creates a kind of fundamental “frame rate” for consciousness, around 10 Hz. That frequency aligns with the alpha rhythm (~10 Hz) observed in EEG recordings of calm, awake individuals.

This time scale seems to recur throughout the brain. For instance, saccadic eye movements occur at intervals of ~150–200 ms, and cognitive task switching also falls in the 150–300 ms range (more if context loading is required). Conscious processing, it appears, is inherently low-frequency compared to the speed of neurons or digital systems. That might be because, to discriminate between firing patterns—like different rates of neuronal activity—we need a minimum temporal window. If the brain operated at, say, 1 MHz, we couldn’t make meaningful sense of neuronal firing frequencies within the 10 ns measurement window. Consciousness seems to require a coarser temporal resolution to function.

Primary Consciousness

Another essential insight from the book is the distinction between primary and higher-order consciousness (though I think higher-order consciousness is not a single thing but consists of many facets). Primary consciousness refers to experiencing the “continuous present”—the stream of perceptual awareness without the need for language or reflection. Higher-order consciousness adds self-awareness, introspection, and symbolic thinking. Making this distinction allows for a more precise and less ambiguous discussion of consciousness. The book does a particularly good job exploring primary consciousness.

The authors argue—echoing William James—that consciousness is a process, not a static entity. Specifically, primary consciousness is a dynamic state running on the hardware of the thalamocortical system. What we experience at any given moment depends on the instantaneous activation pattern of this network. The process evolves through reentry—bidirectional signaling between interconnected neural regions—which leads to synchronization and the emergence of coherent, integrated experience. The system itself is a product of evolution, which tends to favor complex systems capable of producing a vast amount of candidates for nature to select.

Biological Realism vs. Formalism

One final takeaway from the book is the philosophical divergence between the two authors—Edelman and Tononi. While reading, I sensed a subtle tension—two voices pulling in different directions. Afterward, exploring Tononi’s Integrated Information Theory (IIT) made the contrast even clearer.

Edelman grounds consciousness firmly in biological realism, emphasizing natural selection and the anatomical details of real brains. Tononi, by contrast, leans toward formalism, suggesting that consciousness arises from intrinsic system properties—namely, the integration and differentiation of information—regardless of the physical substrate.

I find value in both perspectives, even though they might appear to conflict. While Tononi treats consciousness as a generalized mathematical property of systems with sufficient complexity. Edelman would likely reject the idea that arbitrary non-biological systems can possess even minimal consciousness without evolutionary grounding. To reconcile the two, we must acknowledge that our only known instance of consciousness is brain-based. Edelman focuses on the how does a brain-based consciouness work, grounded in biology. Tononi explores the what does it mean by being conscious, seeking a fundamental definition. The real difference lies in terminology—what we choose to call “consciousness.”

That said, to avoid philosophical confusion, perhaps we should reserve the term consciousness for brain-like systems, while using IIT as a powerful analytic tool for measuring integrated complexity in any system.

IIT for Complex Systems

As a student of complex systems science, I plan to explore IIT further. It deserves more attention in our field—not just as a theory of consciousness, but as a general framework for measuring structure, integration, and information flow in complex networks. It may yet prove to be a key tool in understanding not only minds, but also organizations, ecosystems, and artificial systems.

Sida Liu