Biology subjects

Tavano, A.

Publications and source records attributed to Tavano, A..

6 recordsLinked to original sources

bioRxiv2026

Prior knowledge reveals two computational regimes for syntactic processing in the human brain

The human brain rapidly transforms continuous speech into structured, meaningful linguistic representations, yet how prior knowledge constrains this process remains unclear. To characterize this influence, we combined MEG recordings acquired during audiobook listening with corpus-derived transition probabilities over syntactic features defined within both phrase-structure and dependency-based grammars. Across grammatical formalisms, prior knowledge selectively sharpened the neural representation of memory-related features indexing syntactic structures that must remain open for future completion. This enhancement was strictly local: immediately preceding contexts improved neural decoding at both word onset and offset, whereas longer histories produced either a return to baseline at the word level or a deterioration in decoding performance. By contrast, integration-related features indexing the completion of syntactic operations showed no benefit from prior knowledge and were represented most strongly at word offset, consistent with their dependence on word-level structural resolution. These dissociable dynamics reveal two concurrent neural computational regimes for syntactic processing: a forward-looking, locally maintained predictive code for pending structure and an integrative code engaged when structure is resolved. More broadly, our findings impose a mechanistic constraint on neural theories of language processing and on accounts that equate prediction in human language comprehension with the comparatively unconstrained operations of large language models (LLMs).

neuroscience↗

bioRxiv2022

A scalable and robust system for Audience EEG recordings

The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences. HighlightsA scalable EEG hyper-scanning system for recording audiences and large groups is presented with the following characteristics. O_LIOff-the-shelve, low cost components, namely a MUSE EEG headset, a Raspberry Pi computer and Photodiode. C_LIO_LIA Python library, available to the public, has been specifically developed from first principles, optimized for facilitating robust recording over Bluetooth even when multiple EEG headsets are in close proximity. C_LIO_LIThe use of photodiodes provides unambiguous data alignment between the different systems. C_LIO_LIA proof-of-concept system with 10 EEG headsets has been tested in the lab but also in naturalistic conditions, recording members of the audience in four different long movie screenings in the cinema of the German Film Museum. C_LI

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bioRxiv2021

A bias generating temporal distortions in serial perception

Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, relative duration and relative distance in time of two sequentially-organized events --standard S, with constant duration, and comparison C, varying trial-by-trial-- are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer ISI helps counteracting such serial distortion effect only the constant S is in first position, but not if the unpredictable C is in first position. These results suggest the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanics generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones.

neuroscience↗

bioRxiv2021

Rapid neural encoding of the contrast between native and nonnative speech in the alpha band

More than half of the worlds population is multilingual, yet it is not known how the human brain encodes the perception of native vs. nonnative speech. To find out, we asked German native speakers to detect the onset of native and nonnative (English and Turkish) vowels in a roving standard stimulation. Using EEG, we show that nonnativeness is robustly registered by an increase in phase coherence in the alpha band (8-12 Hz), beginning as early as [~]100 ms after stimulus onset and lasting more than 200 ms. The alpha band effect is speech-specific, successfully predicts the response speed advantage of nonnative speech, and grants [~]90% decoding accuracy in distinguishing native vs. nonnative speech irrespective of language familiarity. We propose alpha phase coherence as a candidate neural channel for the online resolution of the native-nonnative contrast in the adult brain. Significance StatementWe show that the human brain takes only [~] 100 ms to distinguish native vs. nonnative speech. This difference is neurally encoded in the alpha band in a reliable and specific way, supporting a processing model in which the mixture of top-down and bottom-up information represented in the speech signal is concurrently partitioned into different frequency channels.

neuroscience↗

bioRxiv2020

Neural harmonics reflect grammaticality

Can neural rhythms reflect purely internal syntactic processes in multi-word constructions? To test this controversial conjecture - relevant to language in particular and cognition more broadly - we recorded electroencephalographic and behavioural data as participants listened to isochronously presented sentences of varying in syntactic complexity. Each trial comprised ten concatenated sentences and was either fully grammatical (regular) or rendered ungrammatical via randomly distributed word order violations. We found that attending the regular repetition of abstract syntactic categories (phrases and sentences) generates neural rhythms whose harmonics are mathematically independent of word rate. This permits to clearly separate endogenous syntactic rhythms from exogenous speech rhythms. We demonstrate that endogenous but not exogenous rhythms predict participants grammaticality judgements, and allow for the neural decoding of regular vs. irregular trials. Neural harmonic series constitute a new form of behaviourally relevant evidence for syntactic competence.

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bioRxiv2017

Low beta power reflects perceived temporal probabilities for uncertain future events

Humans tend to use elapsed time to increase the perceived probability that an impending event - e.g., the Go sign at a traffic light - will occur soon. This prompts faster reactions for longer waiting times (hazard rate effect). Which neural processes reflect instead the perceived probability of uncertain future events? We recorded behavioral and electroencephalographic (EEG) data while participants detected a target tone, rarely appearing at one of three successive positions of a repeating five-tone sequence with equal probability. Pre-stimulus oscillatory power in the low betaband range (Beta 1: 15-19 Hz) predicted the hazard rate of response times to the uncertain target, suggesting it encodes abstract estimates of a potential event onset. Informing participants about the targets equiprobable distribution endogenously suppressed the hazard rate of response times. Beta 1 power still predicted behavior, validating its role in contextually estimating temporal probabilities for uncertain future events.\n\nHighlightsO_LIElapsed time to an uncertain future target increases response speed (Hazard rate).\nC_LIO_LIPre-stimulus low beta-band (Beta 1: 15-19 Hz) power predicts the hazard rate to uncertain targets.\nC_LIO_LIBeta 1 power predicts response times even when elapsed time is factored out.\nC_LI\n\neTOC BlurbTavano et al. show that pre-stimulus low beta band (15-19 Hz) power predicts response times to an uncertain future target, even before its occurrence and under different prior knowledge conditions, suggesting it reflects contextual, subjective estimates of potential future events.

neuroscience↗