Challenging Paradigms Through Ecological Neuroscience: Lessons From Visual Models

Abstract

Perhaps the ultimate goal of neuroscience is to generate models and theories to explain how our nervous system works in its natural environment. To a large extent, this goal has been pursued with experimental approaches that have a high degree of control of experimental variables, isolating the one of interest while trying to keep all others constant. In the field of perceptual neuroscience, this approach has made it possible to study the brain's responses to specific stimuli in a precise manner, leading to the development of explanatory models. However, a high degree of variable control is not without its drawbacks. It has been proposed that when experimental control is taken to an extreme level, it is possible to generate conditions so specific that experiments cannot be replicated by other researchers (Voelkl et al., 2020), generating a kind of experimental endemism. And even when they are replicable, it is difficult to draw conclusions that can be extrapolated to behavior and brain function in nature. In fact, we believe that the greatest risk lies in that evidence obtained under high variable control may lead to models that do not reflect natural brain functioning. This is how the significance of ecological validity becomes evident. Ecological validity aims to generalize the findings outside the laboratory by designing experiments that resemble the natural conditions where the organism develops and behaves (Shamay-Tsoory and Mendelsohn, 2019). But this statement leaves considerable room for interpretation (Holleman et al., 2020). Therefore, it is important to emphasize that for an experiment to be ecologically valid, it is not necessary to recreate “real life” in the laboratory, but rather capture the necessary features for the conclusions of the experiment to be extrapolated to the phenomenon studied. These features depend on each question and should represent the essential elements that the phenomenon has in the real world. Therefore, it is relevant to ask how many of our current models have been generated with experiments that are not capturing these necessary features. We suspect that ideas deeply embedded in everyday discourse in neuroscience, such as the neural code, have been established with evidence obtained mostly under highly controlled conditions and low ecological validity. For that reason, it is necessary to challenge them in new, more ecological experimental contexts.