Decisions May Be an Illusion: Indiana University Professor Challenges Long-Held Beliefs About How the Brain Works

For generations, the human experience of decision-making has been understood as a clear, step-by-step assembly line. An individual perceives a stimulus in the environment, weighs options through cognitive processing, and finally executes a physical action. This linear framework—frequently dubbed the "sandwich model" by philosophers and neuroscientists alike—underpins centuries of everyday intuition, psychological theory, and modern computational models of the brain. However, recent theoretical work published in the Journal of Cognitive Neuroscience challenges this foundational paradigm, suggesting that the very way humans conceptualize decision-making may fundamentally misrepresent how the central nervous system actually operates.

Tom James, a professor in the Department of Psychological and Brain Sciences within the College of Arts and Sciences at Indiana University, argues that the traditional division between sensation, cognition, and motor activity is an analytical convenience rather than a biological reality. In his newly published paper, titled Sensorimotor Mechanisms of Decisions and Actions, James contends that the brain does not house a centralized executive committee or a "control center" responsible for issuing commands. Instead, human behavior emerges from simultaneous, distributed interactions among the brain, the body, and the physical environment, giving rise to what he terms "action selection."

Main Facts and the Theoretical Framework

At the heart of James’s proposition is a rigorous application of physicalism, a philosophical framework famously championed by thinkers such as Daniel Dennett. Physicalism posits that physical phenomena can cause both physical and nonphysical outcomes, but nonphysical phenomena—such as abstract thoughts, desires, or purely mental decisions—cannot independently exert causal force upon the physical world.

Within this framework, sensory inputs and motor outputs are entirely physical processes. If a decision is strictly treated as an abstract, nonphysical mental event, it cannot logically serve as the direct physical trigger for a muscular contraction or a behavioral output. To bridge this conceptual gap, James utilizes several robust analogies to explain how useful mental abstractions often mask the complex physical mechanisms underneath them.

One primary analogy draws upon Dennett’s concept of the center of mass (CoM), or center of gravity, in physics. A center of mass is an exceptionally useful mathematical tool; engineers and physicists rely on it daily to calculate trajectories, balance structures, and predict physical stability. Yet, a center of mass has no independent physical existence. An individual cannot physically move an object’s center of mass without moving the object itself.

Applying this logic to neuroscience, James suggests that "a decision" operates in much the exact same way. It is a highly compressed, abstract description of a complex physical process, rather than a distinct physical entity floating inside the cranial cavity that commands the body to move.

A second analogy examines institutional behavior. Society routinely uses shorthand phrases such as "the university decided to implement a new policy" or "the corporation shifted its market strategy." While these phrases effectively summarize macro-level outcomes, they tell an observer very little about the intricate micro-level events actually required to produce those outcomes—such as late-night administrative phone calls, heated committee meetings, or individual document signatures. Similarly, stating that a human "made a decision" provides a high-level narrative summary of behavior, but it fails to specify the distributed neural mechanisms that actually generated the physical movement.

Chronology and Background Context of the Shift in Cognitive Science

The publication of James’s paper arrives at a time of profound methodological and philosophical soul-searching within cognitive neuroscience. For decades, the dominant trajectory of brain research relied heavily on model-based cognitive neuroscience, an approach designed to isolate distinct mental functions into separate modules. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) were frequently deployed with the underlying assumption that researchers could map specific mental states—like "attention," "memory," or "decision-making"—to discrete geographic coordinates within the brain.

However, over the past fifteen years, the limits of localizationist models have become increasingly apparent. Advances in neuroimaging temporal resolution and large-scale neural recording have revealed that the brain operates less like a collection of isolated bureaucratic departments and more like a massively parallel, highly integrated dynamical system. Sensory and motor regions are now known to be deeply intertwined, with motor planning occurring simultaneously with sensory processing rather than strictly downstream from it.

By contributing Sensorimotor Mechanisms of Decisions and Actions to the Journal of Cognitive Neuroscience, James builds directly upon these modern empirical shifts. His work synthesizes decades of philosophical critiques regarding internal homunculi—the theoretical "little person inside the head" that watches sensory screens and pulls behavioral levers—with contemporary neuroscience’s growing appreciation for embodied cognition and dynamical systems theory.

The Homunculus Problem and the Cartesian Theater

The historical roots of James’s critique trace back to the seventeenth-century philosopher René Descartes and the enduring philosophical conundrum known as the "Cartesian Theater." Descartes proposed that sensory information converges in a central location within the brain where a non-material mind observes the data and issues commands to the body.

Modern philosophers of mind, including Dennett, have repeatedly dismantled this notion, pointing out the logical fallacy of infinite regress. If a central controller inside the brain is required to interpret data and make choices, one must logically ask who or what is inside that controller’s brain doing the interpreting and choosing, leading to an endless chain of nested observers that explains nothing.

James argues that modern cognitive neuroscience often slips back into this Cartesian trap, even if dressed up in modern computational language. When researchers speak of "executive control networks" or "decision-making centers" as if they are independent entities orchestrating behavior from a control tower, they are merely passing the explanatory burden down the line without solving it.

"Explaining that the brain works by way of a central controller suggests that you haven’t figured out how the brain works, because you’ve just put a person inside your brain," James notes.

Supporting Data and Behavioral Simulations

To demonstrate how complex, goal-directed behavior can emerge without a central decision-making apparatus, James points to principles derived from robotics and cybernetics. He highlights a well-known thought experiment involving a simple, minimalist robot constructed with only a handful of basic sensory, motor, and sensorimotor modules.

Engineered with no central processor dedicated to strategic planning, this robot can exhibit sophisticated "wall-following" behavior when placed in a structured room. To an external human observer, the machine appears remarkably purposeful. It seems to have a clear goal (maintaining a steady distance from the wall), a strategy (navigating around obstacles), and an underlying intention.

Yet, the robot possesses no internal representation of a wall, no algorithmic decision tree, and no central controller.

"The robot does not have decisions built into it," James explains. "It just senses its environment and moves around accordingly. And based on the environment, wall-following turns out to be a good thing. It looks intentional. It looks strategic. It looks like the robot is making decisions. And yet, it is not. The reason we know it is not is that there are no systems built into it to do that."

This demonstration raises a startlingly parsimonious implication for human biology: if a basic electromechanical device can generate purposeful, highly adaptive behavior entirely through local, decentralized interactions with its environment, human behavior may be generated in an identical fashion. Assuming the existence of a higher-level, central monitoring controller in the human brain may be an unnecessary theoretical complication.

Implications for Future Research and Methodology

The theoretical shift advocated by James carries profound implications for experimental design within psychological and brain sciences. If decision-making is not a discrete event occurring at a specific moment in time, but rather an ongoing, emergent property of continuous brain-body-environment interactions, traditional laboratory paradigms must evolve.

Standard cognitive psychology experiments often rely on discrete trial structures—flashing a stimulus on a screen, forcing a participant to press a button after a specific delay, and measuring reaction times. While these methods have yielded valuable data, they inherently reinforce a linear, compartmentalized view of cognition.

To capture the complexity of action selection, researchers will need to embrace more dynamic, continuous, and ecologically valid methodologies. Laboratories inspired by embodied cognition, ecological psychology, and dynamical systems theory are already beginning to pioneer tracking systems that monitor continuous motor output, physiological states, and environmental changes simultaneously.

Broader Impact on Mental Health and Society

Beyond academic laboratories, reframing how humanity understands decisions could eventually ripple across multiple applied fields, including artificial intelligence, psychiatry, and law.

In artificial intelligence and robotics, moving away from centralized decision architectures toward decentralized, sensorimotor-driven models has already sparked major advancements in autonomous navigation and adaptive machine learning. Understanding that intelligence and purposeful behavior do not require a central "mind" provides engineers with leaner, more robust blueprints for artificial systems.

In psychiatry and clinical psychology, a non-linear, emergent view of brain function may alter how clinicians conceptualize disorders of volition, impulse control, and decision-making. Conditions such as addiction, obsessive-compulsive disorder, and attention-deficit hyperactivity disorder are frequently framed as deficits of a central "executive control network." Viewing these conditions through James’s physicalist, sensorimotor framework could encourage therapeutic interventions that focus more heavily on altering bodily interactions, environmental loops, and continuous sensorimotor dynamics rather than attempting to "repair" a broken central controller.

Meanwhile, human society will undoubtedly continue to use the language of choice and intentionality. As James readily acknowledges, describing human behavior through the lens of conscious decisions, desires, and beliefs is not only natural but profoundly useful for navigating daily social life, moral accountability, and legal frameworks. The conceptual leap, he cautions, is mistaking a remarkably effective linguistic and descriptive shorthand for the literal neurobiological machinery humming beneath the surface.