Miller’s Brain Waves’ Analog Organization of Cortex

Neuroscientist Earl K. Miller proposes that cognition and consciousness emerge from the fast and flexible dynamic organization of the cortex produced by traveling brain waves performing analog computations. Here’s how Miller gets to consciousness. He starts by recognizing that it’s no coincidence that the brain, where the coordinated electrical activity of many millions of neurons produces large-scale oscillations across a broad range of frequencies all the time, evolved to exploit the information-rich, fast-propagating, and reliable efficiency that its waves provide. (This can make sense in that analog computing is the classic way information in the real world is continuous, not discrete packets of digital binary bits, such that just two waves colliding with each other can smoothly represent any value from the negative to the positive sum of their amplitudes simply based on their phase, Picower Institute, 2025a; Miller, 2026).

Cognition, then, “relies on the flexible organization of neural activity,” where “many aspects of this organization can be described as emergent properties, not reducible to their constituent parts.” In particular, “electrical fields in the brain can serve as a medium for propagating activity nearly instantaneously,” and “population-level patterns of neural activity can organize computations through subspace coding” (Miller et al., 2024).

“What is needed for top-down executive control of the brain?” Miller asks and answers: “I propose it requires large-scale, dynamic neural-self organization. How can the activity of millions and millions of neurons be organized on the fly? Brain waves are organization. Networks of recurrent connections will naturally begin to oscillate and that’s an internal organization.” Miller maintains that numerous experiments in his lab and those of others “over decades provide evidence that brain waves sculpt the flow of information in the cortex and thereby enable volitional, goal-directed control of thought.” Whereas leading scientific theories of consciousness require communication and integration among at least several cortical regions (such as Global Neuronal Workspace Theory and Integrated Information Theory), Miller argues that his evidence augments such ideas in that brain waves not only unify the cortex but also organize it with analog computation to control and accomplish information processing (Picower Institute, 2025a; Miller, 2026).

Prefrontal Cortex and Neural Oscillations

Miller has been constructing his “Brain Waves’ Analog Organization of Cortex” theory of consciousness for over 25 years. His well-known 2001 paper, co-authored with Jonathan Cohen, “An Integrative Theory of Prefrontal Cortex Function,” positioned the prefrontal cortex as implementing executive control of the brain by actively maintaining goal-directed activity patterns that bias the functions of other regions around the brain. As they put it, “The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task” (Miller & Cohen, 2001). Moreover, many neurons in the prefrontal cortex are not dedicated to specific tasks but are multifunctional, participating in multiple networks at the same time (Picower Institute, 2025a).

A critical part of the long process was showing how these neural networks implement widespread, goal-directed functions via exquisite patterns of specific neural oscillations that communicate and integrate information across the cortex. In 2007, Buschman and Miller showed that attention “can be focused volitionally by ‘top-down’ signals derived from task demands and automatically by ‘bottom-up’ signals from salient stimuli.” Recording from frontal and parietal cortices simultaneously demonstrated that “prefrontal neurons reflected the target location first during top-down attention, whereas parietal neurons signaled it earlier during bottom-up attention. Synchrony between frontal and parietal areas was stronger in lower frequencies during top-down attention and in higher frequencies during bottom-up attention.” This data suggested that “top-down and bottom-up signals arise from the frontal and sensory cortex, respectively, and different modes of attention may emphasize synchrony at different frequencies” (Buschman & Miller, 2007).

“Top-down” goal-directed signals (which might be called “the brain’s internal sense of the rules”) are encoded in relatively slow alpha and beta frequency waves (15-35 Hz), while incoming sensory information is encoded in higher frequency gamma waves (35-60 Hz). “In cognitive functions such as working memory and making predictions, the beta waves constrain the power of the gamma waves, essentially imposing the brain’s goals on information processing.” This mechanism enables volitional control of thought: “When you want to retrieve information committed to working memory (like today’s specials at a restaurant), your cortex can relax beta power to let gamma fetch that for you” (Picower Institute, 2025a).

Brain waves physically travel within the cortex, either linearly or in rotations, and Miller has linked properties of those travels with specific functions, including working memory, because they may provide computational advantages such as constantly maintaining information and providing a clock for computation (Picower Institute, 2025a). “Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts of beta and gamma oscillations (Lundqvist et al., 2023).

Spatial Computing

In 2023, Lundqvist, Miller, and colleagues proposed “the novel concept of spatial computing, where beta and gamma interactions cause item-specific activity to flow spatially across the network during a task. This way, control-related information, such as item order, is stored in the spatial activity independent of the detailed recurrent connectivity supporting the item-specific activity itself. The spatial flow is, in turn, reflected in low-dimensional activity shared by many neurons.” The authors hypothesize that “spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension” (Lundqvist et al., 2023).

According to Miller and colleagues, by combining these mechanisms of cortical geographic interplay of different wave frequencies that represent different kinds of information, “spatial computing” becomes the new theory of cognition in the cortex. It proposes that brain waves modify or modulate neural networks by influencing or impacting cortical neurons (Picower Institute, 2025a). Spatial Computing theory explains how neurons in the prefrontal cortex can be organized dynamically into different functional groups capable of carrying out the information processing required by different cognitive tasks. “The basic idea of the theory is that the brain recruits and organizes ad hoc 'task forces' of neurons by using 'alpha' and 'beta' frequency brain waves (about 10-30 Hz) to apply control signals to physical patches of the prefrontal cortex. Rather than having to rewire themselves into new physical circuits every time a new task must be done, the neurons in the patch instead process information by following the patterns of excitation and inhibition imposed by the waves. Think of the alpha and beta frequency waves as stencils that shape when and where in the prefrontal cortex groups of neurons can take in or express information from the senses, Miller said. In that way, the waves represent the rules of the task and can organize how the neurons electrically “spike” to process the information content needed for the task. ‘Cognition is all about large-scale neural self-organization,’ said Miller” (Picower Institute, 2025b).

Spatial computing is said to enable “flexible cognition” by its “ability to represent and apply relevant information to the current task at hand. This allows the brain to interpret sensory input and guide behavior in a context-dependent manner… suggesting that task-related signals organize information processing through spatial patterns of oscillatory activity across the cortical surface. These patterns are proposed to act as ‘inhibitory stencils’ that constrain where sensory-related information (the ‘content’ of cognition) can be expressed in spiking activity.” Indeed, alpha/beta oscillations, which were organized into spatial patterns that changed with task conditions, were found to encode task-related information and were inversely correlated with the spatial expression of sensory-related spiking activity. Furthermore, “alpha/beta oscillations reflected misattributions of task conditions and correlated with subjects’ trial-by-trial decisions.” According to Miller and colleagues, “These findings validate core predictions of spatial computing, suggesting that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented. This framework offers a unifying principle for understanding how the brain flexibly coordinates cognition through structured population dynamics” (Zhen Chen et al., 2025). Additional confirmation is said to come from the ability of cortical activity to recover from distractions: “After distraction, there were state–space rotational dynamics that returned spiking to population patterns similar to those pre-disruption. In fact, rotations were fuller when the task was performed correctly versus when errors were made.” A correspondence between state–space rotations and traveling waves across the surface of the prefrontal cortex “suggests a role for emergent dynamics like state–space rotations and traveling waves in recovery from distractions” (Batabyal et al., 2025).

Other advantages of waves, Miller notes, include their speed. Neurons are known to rewire their network connections, or synapses, all the time, but that process is much too slow to enable cognitive tasks, he said. Waves and underlying electric fields can propagate across long distances of cortex much faster. Furthermore, Miller claims evidence that “electric fields representing whole ensembles of neurons also represent information more reliably than individual neurons do. Electric fields can directly unify neurons into information-representing ensembles via ‘ephatic coupling,’ he said, and there is even evidence that electric fields can modify physical properties of cells via ‘cytoelectric coupling’” (Picower Institute, 2025a).

Brain Waves and Consciousness

Coming to consciousness, Miller muses, “consciousness is the tip of the iceberg of cognition,” noting that brain waves and their analog computations do a lot of cognitive work without your explicit intervention, but they also enable volitional control. “Consciousness may be a natural outcome of analog computation,” Miller says. “Consciousness is good for flexibility and planning and the kind of big picture stuff that needs a unified representation. When the analog computations create wave patterns that are large enough to unify cortex, you get consciousness” (Picower Institute, 2025a).

In studies with colleagues, Miller has connected consciousness to brain wave dynamics by examining how general anesthesia affects both. Anesthesia, to be sure, provides a clean dividing line between consciousness and unconsciousness, and anesthesia disrupts the power of waves in different frequencies, knocking them out of the normal beta-gamma balance needed to organize cognition. Anesthesia disrupts the propagation or travels of waves linking sensory and higher-order regions of the cortex, which provides the unification and organization required for consciousness. Moreover, distinct anesthetic drugs push brain waves out of phase with one another, disrupting their ability to engage in analog computations (Picower Institute, 2025a).

In one particular study, Miller and colleagues showed that different anesthetic drugs (ketamine and dexmedetomidine) induce a shared pattern of changes in brain wave phase alignment associated with loss of consciousness, despite distinct molecular mechanisms. Homologous regions across the two hemispheres become more phase-aligned during unconsciousness. This is the opposite of the typical awake pattern, where hemispheres show relatively desynchronized activity during cognition. This reversal may indicate a shift to a passive, globally synchronized state that lacks the local differentiation necessary for consciousness. This suggests that phase relationships among brain oscillations may be a universal neural marker of unconsciousness and, by extension, a foundational element of conscious brain function (Bardon et al., 2025).

In other words, in Miller’s “Brain Waves’ Analog Organization of Cortex” theory, consciousness likely depends on precisely timed coordination of brain regions, maintained through specific phase alignments of brain oscillations. Disrupting this temporal coordination, as anesthetics do, may lead to unconsciousness regardless of the chemical pathway, pointing to electromagnetic synchrony (phase alignment)—electromagnetic fields—as a functional substrate of consciousness (Miller, 2026).