Biology subjects

Szewczyk, J.

Publications and source records attributed to Szewczyk, J..

6 recordsLinked to original sources

bioRxiv2026

Exploring Neural Mechanisms of Language Switching: An fMRI Study Using a Functional Localizer Approach

When bilinguals frequently switch between their first (L1) and second (L2) languages during speech production, we usually observe two phenomena: (i) language switch cost, where switching to a different language is more difficult than staying in the same one, and (ii) reversed language dominance, where L1 production becomes slower than L2 production. These effects are thought to reflect language control mechanisms, yet the underlying neural bases remain debated. In this study, we addressed this question by using the precision functional magnetic resonance imaging (fMRI) based on functional localization. Forty-one Polish-English bilinguals performed a language switching task (LST), in which they named pictures in L1 or L2 based on color cues. We investigated mechanisms behind two indices of language control commonly observed in the LST. First, we asked whether the domain-general resources supporting language switch cost overlap with nonverbal task switch cost. Second, we asked whether reversed language dominance reflects changes in language activation in the language-specific system, or whether it is related to increased engagement of domain-general control mechanisms. Results indicated that the language switch cost and nonverbal task switch cost share overlapping domain-general neural mechanisms. Similar to the language switch cost, reversed language dominance primarily engages domain-general processes rather than language-specific resources. HighlightsO_LIfMRI combined with functional localization approach is implemented to examine the neural mechanisms underlying language switch cost and reversed language dominance. C_LIO_LILanguage switch cost relies on neural mechanisms shared with nonverbal switch cost within the Multiple Demand network. C_LIO_LIReversed language dominance is primarily supported by the domain-general rather than the language-specific mechanisms. C_LIO_LIDomain-general neural mechanisms play a pivotal role in bilingual language switching in speech production. C_LI

neuroscience↗

bioRxiv2025

Predictive Neural Signals during Natural Mandarin Speech Comprehension

Language comprehension requires the continuous transformation of speech into a hierarchy of linguistic units, from phonemes to syllables to words. Because speech unfolds rapidly, listeners are thought to predict upcoming content to keep pace. Previous research has provided empirical evidence for predictive processes operating at multiple linguistic levels during naturalistic listening, including words and phonemes. However, it remains unclear whether prediction also operates concurrently at other levels, such as syllabic and phrasal representation. Here we use Mandarin Chinese to examine the neural signatures of predictive processing across multiple levels of linguistic granularity during natural speech comprehension. Mandarin comprises four representational levels: phoneme, sub-syllabic, character and word, and its lexical identity is largely constrained at the sub-syllabic level, potentially redistributing predictive weight across linguistic representations. We recorded magnetoencephalography (MEG) data while 34 native Mandarin speakers (21 females) listened to a naturalistic audiobook and applied linear regression modeling to examine how linguistic features modulated neural activity. We found that the brain activity of listeners segmented speech into hierarchical units, and that surprisal modulated responses simultaneously across sub-syllabic, character and word levels. In contrast to findings from Indo-European languages, however, we did not observe unique surprisal effects at the lowest, phonemic level. Furthermore, the surprisal of lexical tone in Mandarin modulated brain activity only when integrated with its phonological components. These findings suggest that predictive processing during Mandarin speech comprehension operates concurrently across multiple (though not necessarily all) levels of linguistic granularity, with its implementation shaped by language-specific structural properties. Significance statementLanguage comprehension involves segmenting a continuous acoustic stream into multiple linguistic units, from phonemes to words, and generating predictions at these levels. However, direct neural evidence remains limited regarding how segmentation and prediction operate simultaneously across levels of linguistic granularity, particularly outside Indo-European languages. Using temporal response function analysis of magnetoencephalography data recorded during naturalistic Mandarin listening, we show that predictive processing occurs across multiple levels of linguistic granularity. Specifically, we find evidence for prediction-related neural responses at sub-syllabic, character, and word levels, but not a reliable unique effect at the phonemic level. These results indicate that predictive processing also operates during Mandarin speech comprehension, and its neural implementation is shaped by language-specific structural properties.

neuroscience↗

bioRxiv2025

Stimulus dependencies---rather than next-word prediction---can explain pre-onset brain encoding during natural listening

The human brain is thought to constantly predict future words during language processing. Recently, a new approach emerged that aims to capture neural prediction directly by using vector representations of words (embeddings) to predict brain activity prior to word onset. Two findings have been proposed as hallmarks of neural next-word prediction: (i) significant encoding prior to word onset and (ii) its modulation by word predictability. However, natural language is rife with temporal correlations, where upcoming words share statistical information with preceding ones. This raises a critical question: do these these hallmarks emerge from the brain actively predicting future content, or might they be equally well explained by the regression model exploiting these inherent stimulus dependencies? To distinguish between these alternatives, we applied the same encoding analysis to passive control systems, i.e., representational systems that encode the stimulus but cannot predict upcoming words. We show that both hallmarks emerge in two such control systems, namely in word embeddings themselves and in speech acoustics. We further show that proposed methods to correct for these dependencies are insufficient, as the effects persist even after such corrections. Together, these results suggests that pre-onset prediction of brain activity might reflect dependencies in natural language rather than predictive computations. This questions the extent to which this new encoding-based method can be used to study prediction in the brain.

neuroscience↗

bioRxiv2023

Domain-general and language-specific contributions to speech production in L2: an fMRI study using functional localizers.

For bilinguals, speaking in a second language (L2) compared to the native language (L1) is usually more difficult. In this study we asked whether the difficulty in L2 production reflects increased demands imposed on domain-general or core language mechanisms. We compared the brain response to speech production in L1 and L2 within two functionally-defined networks in the brain: the Multiple Demand (MD) network and the language network. We found that speech production in L2 was linked to a widespread increase of brain activity in the domain-general MD network. The language network did not show a similarly robust differences in processing speech in the two languages, however, we found increased response to L2 production in the language-specific portion of the left inferior frontal gyrus (IFG). To further explore our results, we have looked at domain-general and language-specific response within the brain structures postulated to form a Bilingual Language Control (BLC) network. Within this network, we found a robust increase in response to L2 in the domain-general, but also in some language-specific voxels including in the left IFG. Our findings show that L2 production strongly engages domain-general mechanisms, but only affects language sensitive portions of the left IFG. These results put constraints on the current model of bilingual language control by precisely disentangling the domain-general and language-specific contributions to the difficulty in speech production in L2.

neuroscience↗

bioRxiv2023

Tracking components of bilingual language control in speech production: an fMRI study using functional localizers.

When bilingual speakers switch back to speaking in their native language (L1) after having used their second language (L2), they often experience difficulty in retrieving words in their L1: this phenomenon is referred to as the L2 after-effect. We used the L2 after-effect as a lens to explore the neural bases of bilingual language control mechanisms. Our goal was twofold: first, to explore whether bilingual language control draws on domain-general or language-specific mechanisms; second, to investigate the precise mechanism(s) that drive the L2 after-effect. We used a precision fMRI approach based on functional localizers to measure the extent to which the brain activity that reflects the L2 after-effect overlaps with the language network (Fedorenko et al., 2010) and the domain-general Multiple Demand network (Duncan et al., 2010), as well as three task-specific networks that tap into interference resolution, lexical retrieval, and articulation. Forty-two Polish-English bilinguals participated in the study. Our results show that the L2 after-effect reflects increased engagement of domain-general but not language-specific resources. Furthermore, contrary to previously proposed interpretations, we did not find evidence that the effect reflects increased difficulty related to lexical access, articulation, and the resolution of lexical interference. We propose that difficulty of speech production in the picture naming paradigm - manifested as the L2 after-effect - reflects interference at a non-linguistic level of task schemas or a general increase of cognitive control engagement during speech production in L1 after L2.

neuroscience↗

bioRxiv2021

Disorder is a critical component of lipoprotein sorting in Gram-negative bacteria

Gram-negative bacteria express structurally diverse lipoproteins in their envelope. Here we found that approximately half of lipoproteins destined to the Escherichia coli outer membrane display an intrinsically disordered linker at their N-terminus. Intrinsically disordered regions are common in proteins, but establishing their importance in vivo has remained challenging. Here, as we sought to unravel how lipoproteins mature, we discovered that unstructured linkers are required for optimal trafficking by the Lol lipoprotein sorting system: linker deletion re-routes three unrelated lipoproteins to the inner membrane. Focusing on the stress sensor RcsF, we found that replacing the linker with an artificial peptide restored normal outer membrane targeting only when the peptide was of similar length and disordered. Overall, this study reveals the role played by intrinsic disorder in lipoprotein sorting, providing mechanistic insight into the biogenesis of these proteins and suggesting that evolution can select for intrinsic disorder that supports protein function.

biochemistry↗