25 Can neural activity reveal syntactic structure building processes and their violations?26 To verify this, we recorded electroencephalographic and behavioral data as 27 participants discriminated concatenated isochronous sentence chains containing 28 only grammatical sentences (regular trials) from those containing ungrammatical 29 sentences (irregular trials). We found that the repetition of abstract syntactic 30 categories generates a harmonic structure of their period independently of stimulus 31 rate, thereby separating endogenous from exogenous neural rhythms. Behavioral 32 analyses confirmed this dissociation. Internal neural harmonics extracted from 33 regular trials predicted participants' grammatical sensitivity better than harmonics 34 extracted from irregular trials, suggesting a direct reflection of grammatical 35 sensitivity. Instead, entraining to external stimulus rate scaled with task sensitivity 36 only when extracted from irregular trials, reflecting attention-capture processing.37 Neural harmonics to repeated syntactic categories constitute the first behaviorally 38 relevant, purely internal index of syntactic competence. 39 40 42 43 Introduction 44 Speech and language are related but distinct dimensions of verbal communication 45 [1 -4]. While temporal regularities guide speech chunking in ways that are relevant 46 for language production and comprehension [3,[5][6][7][8][9][10][11][12][13]), the core of language 47 processing lies in the internal and tacit knowledge of syntactic rules, whose function 48 is to determine how words combine into meaningful utterances [14]. Isolating a direct 3 49 neural correlate of such linguistic competence has proven an extremely difficult task.50 A growing body of literature has linked brain rhythms to various aspects of language 51 comprehension. Recently, Ding and colleagues [15] tried to capture a neural 52 signature of structure building in the frequency domain by having native speakers of 53 English and Mandarin Chinese listen to continuous spoken sentences, concatenated 54 as continuous trains of monosyllabic words presented at a fixed rate of 4 Hz. They 55 tested sentences composed of two-word noun phrases (NP = a phrase headed by a 56 noun, such as "My shoe") followed by two-word verb phrases (VP = "is wet", see 57 Figure 1a). The lexical input therefore appeared at a rate of 4 Hz, phrasal units at 258 Hz, and sentences at 1 Hz. This design was selected to allow for 'frequency tagging' 59 of sentence building processes, such that the neural data could be decomposed into 60 linguistically relevant rhythmic response components. Remarkably, a Fast Fourier 61 Transform (FFT) analysis highlighted significant peaks of spectral energy emerging 62 not only at 4 Hz (word rate), but also at 2 Hz and 1 Hz. The authors deemed the 63 neural responses as a direct window into the linguistic hierarchy: 2 Hz rhythms (2-64 word units) tracked the phrases, and 1 Hz rhythms (4-word units) tracked the 65 sentences. Such linguistic rhythms emerged only if participants l...