For decades, the standard scientific narrative regarding human behavior has followed a comfortable, linear path: we perceive the world, we deliberate on that information, and then we act. This "sandwich model"—sensory input followed by cognitive processing, ending in motor output—has served as the bedrock for countless studies in cognitive neuroscience. However, according to Tom James, a professor in the Department of Psychological and Brain Sciences at Indiana University, this intuitive framework may be fundamentally misaligned with the biological reality of the human brain.
In a new paper published in the Journal of Cognitive Neuroscience, titled "Sensorimotor Mechanisms of Decisions and Actions," James challenges the long-held assumption that the brain contains a dedicated, centralized "decision-making" module. Instead, he proposes that what we perceive as a calculated choice is actually an emergent property of complex, simultaneous interactions between the brain, the body, and the environment.
Rethinking the Brain’s Decision-Making Process
The "sandwich model" is more than just a scientific framework; it mirrors our own internal experience. "Our actions feel like they are caused by decisions based on desires, beliefs, and intentions," James observes. This subjective feeling of agency is so powerful that it has shaped the development of model-based cognitive neuroscience, which often assigns distinct neural processes to perception, cognition, and motor activity.
James, however, argues that this model is a convenient fiction. While neuroscience has successfully mapped specific mechanisms for sensory input and motor output, the "cognitive stage" tucked between them remains elusive. There is no clear evidence of a neural hub that functions as a distinct decision-maker.
Instead of a centralized command center, James advocates for a model of "action selection." In this view, behavior is not the result of a linear chain of events but emerges from ongoing, bidirectional feedback loops. Sensory and motor processes do not wait for a cognitive "green light" to occur; they are constantly interacting, adjusting, and feeding back into one another in real-time. By moving away from the sequential model, James suggests that we can begin to understand behavior as a continuous, dynamic process rather than a series of discrete, compartmentalized events.
Crucially, James is not suggesting that decisions are "unreal" in the sense that they don’t occur. He acknowledges that the language of desire and intent is highly functional for navigating daily life. "Of course they do," James says, referring to the reality of decisions as a descriptive tool. "We use this language all the time and it’s very helpful in terms of describing behavior. The leap, I think, is to say that the brain works by having decision-making or control processes. It produces behavior that is well described in that way. But it doesn’t need a process that does that to make it look that way."
Decisions as Abstract Descriptions
To bridge the gap between our experience of choosing and the physical reality of the brain, James employs a "physicalist" framework, a philosophical approach championed by thinkers like Daniel Dennett. The core of this argument is that physical phenomena can cause other physical events, but nonphysical phenomena—such as a "decision" as we traditionally define it—cannot exert force on the physical world. If a decision is an abstract, nonphysical mental state, it cannot, by definition, pull the physical levers of the brain to trigger a muscle movement.
To illustrate this, James draws a parallel to the concept of a "center of mass" in physics. A center of mass is an incredibly useful mathematical concept used to describe the stability and movement of an object. However, the center of mass is not a physical object itself; you cannot move an object’s center of mass without moving the object itself. It is a description, not a cause. James argues that our concept of a "decision" may be exactly the same: an abstract description we use to summarize complex, lower-level physical processes.
He extends this analogy to how we describe institutional behavior. When we say, "The university took certain actions during a campus protest," we are using a convenient shorthand to describe a vast, chaotic web of individual meetings, administrative directives, police interactions, and student movements. While the statement is useful for communication, it is practically useless for a researcher trying to understand the specific, granular events that caused the situation.
Similarly, James argues that neuroscience often falls into the trap of using "decision" as a high-level label that obscures the actual biological mechanisms. "As mental phenomena, they are defined on too abstract a level for the goals of cognitive neuroscience," James explains. By labeling a behavior as a "decision," we may be satisfied with the explanation, but we have failed to describe what is actually occurring within the neurons and synapses of the brain.
A Simple Robot Raises a Bigger Question
To push his argument further, James points to a thought experiment involving a simple robot. Imagine a machine programmed with only basic sensorimotor modules that allow it to navigate its environment. When placed near a wall, the robot exhibits "wall-following" behavior. To an outside observer, the robot appears to be acting with clear intent, goal-oriented strategy, and purpose.
Yet, the robot contains no "decision-making" software. It is simply reacting to sensory feedback and adjusting its motor output in a continuous loop. "The robot does not have decisions built into it," says James. "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."
This leads to a provocative question for human neuroscience: if a simple robot can produce behavior that appears to be the result of a high-level, centralized controller when no such controller exists, why do we assume the human brain must have one? James argues that his model—where behavior emerges from the bottom up—is far more parsimonious, or simpler, than the alternative. It eliminates the need for a mysterious "central controller" that magically regulates sensory and motor processes.
The Problem With a Central Controller
The reliance on a central controller creates a profound philosophical dilemma that has haunted science since René Descartes. If there is a "higher-level" entity inside the brain that monitors information and makes choices, we are forced to ask how that controller itself operates.
"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. This concept, dubbed the "Cartesian Theater" by Daniel Dennett, inevitably leads to an infinite regress. If there is a "person" or "controller" inside the brain making decisions, that controller would theoretically need its own smaller controller to process information, and so on, ad infinitum. By moving away from the internal decision-maker, James hopes to resolve this philosophical knot and focus instead on the tangible, interacting systems that generate behavior.
An Experimental Path Forward
Shifting the scientific perspective toward a model of continuous interaction poses significant methodological challenges. If decision-making is not a discrete event but an emergent property of a dynamic system, researchers can no longer rely on strictly linear models. They must develop experimental methods capable of capturing processes that happen simultaneously, influence one another in real-time, and shift constantly as an individual engages with their environment.
James and his laboratory are currently exploring these possibilities, drawing on concepts from embodied cognition and ecological psychology. By viewing the brain as an integral part of the body’s interaction with the world—rather than a separate entity observing the world—they hope to uncover the true mechanisms that produce what we describe as "decisions."
While this shift requires a move away from decades of established, linear cognitive models, James remains optimistic. He believes this approach will not only clarify how the brain produces behavior but will also offer a more accurate framework for investigating other mental phenomena that have long been incorrectly classified as distinct, isolated processes within the brain. For cognitive neuroscience, the goal is to look past the convenient labels of our inner life and begin to map the intricate, interconnected reality that actually drives our actions.
