A groundbreaking study reveals that artificial languages, such as Esperanto and Klingon, engage the same neural networks in the brain as natural languages. Researchers conducted fMRI scans on 44 speakers of constructed languages while they listened to sentences in their respective conlangs. The results indicate that the brain's language-processing regions respond similarly to both natural and artificial languages when these systems can express real-world meanings. This contrasts with computer programming languages, which rely on areas associated with logical reasoning rather than linguistic processing. The findings deepen our understanding of what defines a system as a language in the human brain and suggest that neither the age of the language nor its number of speakers determines its neural engagement.
In recent years, the intersection of neuroscience and linguistics has shed light on how the brain processes different forms of communication. This particular study, led by MIT researchers, delves into the neurological response to constructed languages, or "conlangs," which differ significantly from naturally evolving tongues. Conlangs are typically created by individuals for specific purposes, such as promoting international communication (Esperanto) or enhancing fictional universes ("Star Trek"’s Klingon). Despite their artificial origins, these languages activate the same brain regions as those used for native speech. The research involved gathering nearly 50 proficient speakers of various conlangs over a single weekend, an unprecedented effort in the field.
To better understand this phenomenon, the scientists utilized functional magnetic resonance imaging (fMRI) to observe participants' brain activity. During the experiment, subjects listened to sentences in their chosen conlang and their native language. Results showed consistent activation in the language-processing regions regardless of whether the input was natural or constructed. Furthermore, unlike coding languages like Python, which stimulate the brain's multiple demand network tied to complex problem-solving, conlangs align more closely with natural language patterns. This distinction highlights the importance of expressing real-world concepts in engaging the brain’s linguistic mechanisms.
The implications of this study extend beyond mere curiosity about artificial languages. By identifying shared features between natural and constructed languages, researchers gain insight into the fundamental properties required to define a system as a language within the human brain. For instance, High Valyrian—a language developed for "Game of Thrones"—despite being less than a decade old, activates the same neural circuits as centuries-old natural languages. Such findings challenge traditional notions that only long-evolved languages with vast speaker bases can stimulate these areas. Instead, it seems the ability to convey meaningful information about external realities or internal states is key.
This investigation underscores the flexibility of the human brain in adapting to diverse linguistic systems. Whether crafted for practicality or entertainment, conlangs demonstrate remarkable similarities to natural languages in terms of neural engagement. As researchers continue exploring lesser-known conlangs, such as Lojban, designed to minimize ambiguity, further insights into the essence of language may emerge. Ultimately, these discoveries refine our comprehension of what constitutes a language and why certain systems resonate so deeply within us.
