In the article, “Useful and Useless Misnomers in Motor Control,” Latash (2024) discusses nine terms commonly used in the field of human motor control. He evaluates these terms according to (a) how clearly they can be defined, and (b) whether they were imported from fields outside motor control. This topic resonated with us, as terminology is often a point of discussion in our lab meetings, given our diverse training backgrounds in areas like cognitive science, vision science, animal biology, occupational therapy, and neuroscience. Although we agreed with Latash on the importance of precise definitions for effective communication, we focused less on his specific nine terms, as their ambiguity was uncontentious. Instead, we discussed at length three terms that were not on his list, but that were often employed in his article: “Law of nature,” “model,” and “program.” We highlight the translation challenges these terms present for researchers from diverse backgrounds and disciplines, as they carry distinct meanings in different scientific contexts.

Latash asserts that motor control, as a natural science, must be analyzed using laws of nature and not principles arising from nonbiological fields such as control theory, for example, “If we want motor control to be a field of natural science, there is no way to ignore or bypass laws of nature. Laws of inanimate nature (physics) are clearly insufficient to describe biological movements. So, the task is to discover the missing biology-specific laws of nature. . . .” We find this perspective unclear. What specific laws of nature are being bypassed? What evidence is there for missing biology-specific laws of nature? Encyclopaedia Britannica defines a law of nature as a “stated regularity in the relations or order of phenomena in the world that holds, under a stipulated set of conditions, either universally or in a stated proportion of instances” (Britannica, The Editors of Encyclopaedia, 2017). Examples include the law of gravity and laws of thermodynamics.

It would be helpful if Latash could clarify what he means by a “law of nature” or provide an example, as he seems to use the term differently than is commonly understood. In the quotation above, he contrasts biological laws with “laws of inanimate nature (physics),” yet this distinction feels problematic, as all systems, living or nonliving, are governed by the same fundamental laws of matter and energy—laws of nature. As far as we are aware, there are no laws of nature that apply to biological systems but not to nonbiological systems. It might be more accurate to say that if we ask questions about living systems at a higher level than particles and energy—for example, a question about human motor behavior—the complexity involved requires that we turn to principles, theories, and frameworks beyond the natural laws to have any hope of understanding or predicting anything. We doubt that the study of motor control will yield new natural laws—after all, even evolution, the theory that underpins modern biology, does not have the status of a law of nature.

Another possible reading of Latash’s emphasis on natural law is that he may be primarily concerned with the use of concepts from control theory in understanding human behavior. We, however, see value in this cross-disciplinary approach. Many terms now common in the biological sciences have origins in the physical sciences—feedback is one such example (Feedback Noun, 2023). While we agree that precise definitions are essential for clear scientific communication, we believe that a term’s origin outside biology should not preclude its use if it is otherwise useful and can be defined in the context of human movement. Indeed, insights from fields like control theory can deepen our understanding of biological systems by providing frameworks that capture complex, dynamic interactions—an approach that aligns well with the multifaceted nature of motor control.

Our second area of confusion initially centered on the term “internal model,” but after further discussion, we realized the core issue was with the term “model” itself. We coauthors generally view an internal model as a representation or simplification. To elaborate, the best available explanation of the predictive qualities observed in human motor behavior, and the updating of predictions based on feedback in paradigms such as visuomotor adaptation, is that the brain has some representation (i.e., model) relating sensory inputs and motor outputs. In contrast to Latash’s perspective, we see this concept as neutral with respect to any particular computational method or implementation.

We agree that the computational details Latash outlines in relation to the “specific” version of the internal model assume a great degree of sophistication, which we have no evidence that the brain can implement. However, we disagree that the term “internal model” must necessarily imply that the brain implements a specific computation in a specific way. Neuroscientists often use models to fit data or predict experimental outcomes without implying that the brain performs the exact computations specified by the model. Instead, models serve to approximate, simplify, or represent complex neural processes whose precise computational details remain unknown. Philosophers of science have defined many types of models that are used for various purposes in science (Frigg & Hartmann, 2024). We might consider the internal model as a representational or analog model, whereas Latash’s interpretation may align more with a mathematical or mechanistic model. If internal models are representational or analog models as we suggest, then they are not “hypothetical neuronal mechanisms that can map any set of variables on any other set of variables.” They are not neuronal mechanisms at all, but rather analogical models that help us understand and predict motor behavior and learning in a way that can guide further systematic empirical inquiries.

Finally, when we discussed Latash’s criticism of the term “motor program,” we realized that we interpret “program” differently than he does. For example, he writes “...programming any of the mentioned variables is impossible given the unpredictable variations in external forces and intrinsic body states, including circuits mediating spinal reflex effects on muscle activation levels.” We were considering “program” in the context of a modern computer program, which can integrate sensor feedback to adapt dynamically to environmental and internal conditions (e.g., machine learning, neural networks). However, when we consider “motor program” in its original sense from early motor control theories over 50 years ago, we agree with Latash that this older concept falls short in not accounting for the complex interactions of the nervous system with musculoskeletal and environmental factors.

We believe the challenge lies in the evolution of language; “program” has come to mean something quite different today than when “motor program” was first defined. Many people may now associate “motor program” with modern computer programs, overlooking its original intent. But does it make sense to discard a term that has evolved with the science? Science has many terms that are now used very differently than when they were originally defined. For example, “virus” meant “poisonous substance” (Mammas et al., 2020) for centuries before attaining its modern biological meaning with connotations of nucleic acid surrounded by a protein coat (Modrow et al., 2013). Perhaps a century from now, “motor program” will be a very useful term because no one will remember the original meaning of “program.” In the meantime, when ambiguity arises between historical and modern interpretations of “motor program,” it is certainly essential to clarify the intended meaning for readers.

Clearly, we use some terms differently than Latash. If we disagree on the meanings of “law of nature,” “model,” or “program,” reaching consensus on the utility of the nine motor control terms he discusses seems unlikely. While we agree on the need for clear definitions, we face the same challenge: identifying the problem without a clear solution. Multiple meanings across disciplines may be inevitable, especially as scientific progress often stems from interdisciplinary work that adapts terms to new contexts. Furthermore, as language evolves over time, it may be inevitable that terms take on new meanings. Explicitly defining ambiguous terms in our writing, with consideration for the diverse backgrounds of our readers, may help clarify our intentions but is unlikely to result in total alignment of interpretation across the field. Ultimately, achieving universal consensus on terminology may be less important than fostering an openness to nuanced interpretations that reflect the diverse perspectives within our field.