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Carta, S.

Publications and source records attributed to Carta, S..

6 recordsLinked to original sources

Simultaneous cortical tracking of competing speech streams during attention switching

Successful speech communication in multi-talker scenarios requires a skilful combination of sustained attention and rapid attention switching. While the neurophysiology literature offers detailed insights into the neural underpinnings of sustained attention, there remains considerable uncertainty on how attention switching takes place. In this study, using EEG recordings from normal-hearing adults in an immersive multi-talker environment, we measured the neural encoding of two competing speech streams amid background babble. Participants were cued to switch attention between streams every 15-30 seconds. Neural tracking was assessed via Temporal Response Functions (TRF), confirming reliable decoding of attentional focus. Our results indicate asymmetric disengagement and engagement processes during attention switches, where the neural tracking of the new target stream emerges before disengaging from the previous target, revealing a transient simultaneous encoding of two speech streams. That transition was closely mirrored by a reduction in EEG alpha power, informing on the cognitive effort during different phases of the attention switch. We then isolated cortical activity reflecting lexical prediction mechanisms to determine how lexical context is updated after an attention switch, comparing four numerical hypotheses that were constructed using Large Language Models. Our findings elucidate both the temporal and contextual mechanisms underlying auditory attention shifts, pointing to the possibility that listeners carry out a reset in lexical context after switching attention. By focusing on dynamic attentional reallocation, this study offers insights into the brains capacity for flexible speech processing in complex listening environments.

neuroscience↗

Are you talking to me? How the choice of speech register impacts listeners' hierarchical encoding of speech.

Speakers accommodate their speech to meet the needs of their listeners, producing different speech registers. One such register is Foreigner-Directed Speech (FDS), which is the way native speakers address non-native listeners, typically characterized by features such as slow speech rate and phonetic exaggeration. Here, we investigated how register impacts the cortical encoding of speech at different levels of language integration. Specifically, we tested the hypothesis that enhanced comprehension of FDS compared with Native-Directed Speech (NDS) involves more than just a slower speech rate, influencing speech processing from acoustic to semantic levels. Electroencephalography (EEG) signals were recorded from Spanish native listeners, who were learning English (L2 learners), and English native listeners (L1 listeners) as they were presented with audio-stories. Speech was presented in English in three different speech registers: FDS, NDS and a control register (Slow-NDS) which is slowed down version of NDS. We measured the cortical tracking of acoustic, phonological, and semantic information with a multivariate temporal response function analysis (TRF) on the EEG signals. We found that FDS promoted L2 learners cortical encoding at all the levels of speech and language processing considered. First, FDS led to a more pronounced encoding of the speech envelope. Second, phonological encoding was more refined when listening to FDS, with phoneme perception getting closer to that of L1 listeners. Finally, FDS also enhanced the TRF- N400, a neural signature of lexical expectations. Conversely FDS impacted acoustic but not linguistic speech encoding in L1 listeners. Taken together, these results support our hypothesis that FDS accommodates speech processing in L2 listeners beyond what can be achieved by simply speaking slowly, impacting the cortical encoding of sound and language at different abstraction levels. In turn, this study provides objective metrics that are sensitive to the impact of register on the hierarchical encoding of speech, which could be extended to other registers and cohorts.

neuroscience↗

Cortical over-representation of phonetic onsets of ignored speech in hearing impaired individuals

Hearing impairment alters the sound input received by the human auditory system, reducing speech comprehension in noisy multi-talker auditory scenes. Despite such challenges, attentional modulation on the envelope tracking in multi-talker scenarios is comparable between normal hearing (NH) and hearing impaired (HI) participants, with previous research suggesting an over-representation of the speech envelopes in HI individuals (see, e.g., Fuglsang et al. 2020 and Presacco et al. 2019), even though HI participants reported difficulties in performing the task. This result raises an important question: What speech-processing stage could reflect the difficulty in attentional selection, if not envelope tracking? Here, we use scalp electroencephalography (EEG) to test the hypothesis that such difficulties are underpinned by an over-representation of phonological-level information of the ignored speech sounds. To do so, we carried out a re-analysis of an EEG dataset where EEG signals were recorded as HI participants fitted with hearing aids attended to one speaker (target) while ignoring a competing speaker (masker) and spatialised multi-talker background noise. Multivariate temporal response function analyses revealed that EEG signals reflect stronger phonetic-feature encoding for target than masker speech streams. Interestingly, robust EEG encoding of phoneme onsets emerged for both target and masker streams, in contrast with previous work on NH participants and in line with our hypothesis of an over-representation of the masker. Stronger phoneme-onset encoding emerged for the masker, pointing to a possible neural basis for the higher distractibility experienced by HI individuals. Significance StatementThis study investigated the neural underpinnings of attentional selection in multi-talker scenarios in hearing-impaired participants. The impact of attentional selection on phonological encoding was assessed with electroencephalography (EEG) in an immersive multi-talker scenario. EEG signals encoded the phonetic features of the target (attended) speech more strongly than those of the masker (ignored) speech; but interestingly, they encoded the phoneme onsets of both target and masker speech. This suggests that the cortex of hearing-impaired individuals may over-represent higher-level features of ignored speech sounds, which could contribute to their higher distractibility in noisy environments. These findings provide insight into the neural mechanisms underlying speech comprehension in hearing-impaired individuals and could inform the development of novel approaches to improve speech perception in noisy environments.

neuroscience↗

Task-dependent and automatic tracking of hierarchical linguistic structure

Linguistic phrases are tracked in sentences even though there is no clear acoustic phrasal marker in the physical signal. This phenomenon suggests an automatic tracking of abstract linguistic structure that is endogenously generated by the brain. However, all studies investigating linguistic tracking compare conditions where either relevant information at linguistic timescales is available, or where this information is absent altogether (e.g., sentences versus word lists during passive listening). It is therefore unclear whether tracking at these phrasal timescales is related to the content of language, or rather, is a consequence of attending to the timescales that happen to match behaviourally-relevant information. To investigate this question, we presented participants with sentences and word lists while recording their brain activity with MEG. Participants performed passive, syllable, word, and word-combination tasks corresponding to attending to rates they would naturally attend to, syllable-rates, word-rates, and phrasal-rates, respectively. We replicated overall findings of stronger phrasal-rate tracking measured with mutual information (MI) for sentences compared to word lists across the classical language network. However, in the inferior frontal gyrus (IFG) we found a task-effect suggesting stronger phrasal-rate tracking during the word-combination task independent of the presence of linguistic structure, as well as stronger delta-band connectivity during this task. These results suggest that extracting linguistic information at phrasal-rates occurs automatically with or without the presence of an additional task, but also that that IFG might be important for temporal integration across various perceptual domains.

neuroscience↗

In vivo calcium imaging of CA3 pyramidal neuron populations in adult mouse hippocampus

Neuronal population activity in the hippocampal CA3 subfield is implicated in cognitive brain functions such as memory processing and spatial navigation. However, because of its deep location in the brain, the CA3 area has been difficult to target with modern calcium imaging approaches. Here, we achieved chronic two-photon calcium imaging of CA3 pyramidal neurons with the red fluorescent calcium indicator R-CaMP1.07 in anesthetized and awake mice. We characterize CA3 neuronal activity at both the single-cell and population level and assess its stability across multiple imaging days. During both anesthesia and wakefulness, nearly all CA3 pyramidal neurons displayed calcium transients. Most of the calcium transients were consistent with a high incidence of bursts of action potentials, based on calibration measurements using simultaneous juxtacellular recordings and calcium imaging. In awake mice, we found state-dependent differences with striking large and prolonged calcium transients during locomotion. We estimate that trains of >30 action potentials over 3 s underlie these salient events. Their abundance in particular subsets of neurons was relatively stable across days. At the population level, we found that coactivity within the CA3 network was above chance level and that co-active neuron pairs maintained their correlated activity over days. Our results corroborate the notion of state-dependent spatiotemporal activity patterns in the recurrent network of CA3 and demonstrate that at least some features of population activity, namely coactivity of cell pairs and likelihood to engage in prolonged high activity, are maintained over days.

neuroscience↗

A deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging data

Calcium imaging is a key method to record patterns of neuronal activity across populations of identified neurons. Inference of temporal patterns of action potentials ( spikes) from calcium signals is, however, challenging and often limited by the scarcity of ground truth data containing simultaneous measurements of action potentials and calcium signals. To overcome this problem, we compiled a large and diverse ground truth database from publicly available and newly performed recordings. This database covers various types of calcium indicators, cell types, and signal-to-noise ratios and comprises a total of >35 hours from 298 neurons. We then developed a novel algorithm for spike inference (CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates, and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level. As a consequence, no parameters need to be adjusted by the user. To facilitate routine application of CASCADE we developed systematic performance assessments for unseen data, we openly release all resources, and we provide a user-friendly cloud-based implementation.

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