When fMRI studies are designed to uncover the existence of discrete representations of features in language cortex, or MEG data interpreted by turning to underspecification notions of featural representations, we fall into the isomorphism fallacy— “to take the products of description and assign them explanatory, causal status” (Bellugi & Studdert-Kennedy, 1980, p. 92). Real explanations must come from “principles that are independent of the domain of the observations themselves (Lindblom, 1980, p. 18).”
The linguistically-driven search for memory structures in the human brain mapping featural-based entities could be compared to neuroethologists investigating echo location processing in the bat and claiming to find areas showing [+fast/-fast] or [+far/-far] ‘features’ in auditory areas of the bat’s brain. Such descriptive labels do not substitute for real time explanations such as auditory neurons sensitive to the various doppler shifts in the returning second harmonic (60kHz) echo, or the time delay of the echo signal relative to the emitting pulse. Acoustic signals shaped by the laws of physics is what the brain listens to and what underlies the perception and ultimate representations of sounds, whether they be contrastive segments of a human language, or species-specific sounds heard by bats. Admittedly, such sounds are arranged along a continuum, and do not lend themselves to binary classifications, but the analogy should hit home. Ultimately, the physical signals that shape the information-bearing parameters of speech segments is all we need to concern ourselves with. Combination-sensitive auditory neurons do not care about featural labels. Taxonomic classifications of sound systems are meant for textbooks and box and arrow functional models of language structure, not biological tissue.
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