Biology subjects

Cappotto, D.

Publications and source records attributed to Cappotto, D..

6 recordsLinked to original sources

bioRxiv2024

Assessing Behavioral and Neural Correlates of Change Detection in Spatialized Acoustic Scenes

The ability to detect changes in complex auditory scenes is crucial for human survival, yet the neural mechanisms underlying this process remain elusive. This study investigates how the presence and location of sound sources impacts active auditory change detection as well as neural correlates of passive change detection. We employed stimuli designed to minimize semantic associations while preserving naturalistic temporal envelopes and broadband spectra, presented in a spatial loudspeaker array. Behavioral change detection experiments tasked participants with detecting new sources added to spatialized and non-spatialized multi-source auditory scenes. In a passive listening experiment, participants were given a visual decoy task while neural data were collected via electroencephalography (EEG) during exposure to unattended spatialized scenes and added sources. Our behavioral experiments (N = 21 and 21) demonstrated that spatializing sounds facilitated change detection compared to non-spatialized presentation, but that performance declined with increasing number of sound sources and higher hearing thresholds at high frequencies, exclusively in spatialized conditions. Slower reaction times were also observed when changes occurred from above or behind the listener, exacerbated by a higher number of sources. EEG experiments (N = 32 and 30), using the same stimuli, showed robust change-evoked responses. However, no significant differences were detected in our analysis as a function of spatial location of the appearing source.

neuroscience↗

bioRxiv2024

Failed Double-Blind Replication of Offline 5Hz-rTUS-Induced Corticospinal Excitability

IntroductionTranscranial ultrasound stimulation (TUS) is a promising new form of non-invasive neuromodulation. As a nascent technique, replication of its effects on brain function is important. Of particular interest is offline 5Hz repetitive TUS (5Hz-rTUS), originally reported by Zeng and colleagues [1] to elicit lasting corticospinal excitability increases, with large effect sizes. Material and methodHere, we conducted a pre-registered (https://osf.io/p5n4q) replication of this protocol that benefitted from three additional features: double-blind application of TUS, neuronavigation for consistent TMS positioning, and acoustic simulations to assess M1 target exposure to TUS. Changes in resting motor thresholds (rMT), motor-evoked potential (MEP) amplitude, short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) in response to TUS (5Hz-rTUS vs. sham) were measured in the right first dorsal interosseous (FDI), abductor digiti minimi (ADM) and abductor pollicis brevis (APB) muscles, with unbiased selection of participants. Transducer location was determined by the TMS-hotspot for motor representations of the right FDI, as in the original work. ResultsNo significant effects of 5Hz-TUS (vs sham) were observed. Post-hoc simulations showed considerable variability of the acoustic focus, which was outside the anatomical M1-hand area in 67% of participants - in line with the known poor correspondence of TMS-hotspot location and M1-hand area. ConclusionOur results indicate that the effect sizes of the neuromodulatory effects of 5Hz-rTUS on M1 may be more variable than previously appreciated. We suggest that double-blinding, neuronavigated TMS, individualised acoustic simulations for TUS targeting and pre-registration will aid reproducibility across studies.

neuroscience↗

bioRxiv2024

"What" and "when" predictions jointly modulate speech processing

Adaptive behavior rests on forming predictions based on previous statistical regularities encountered in the environment. Such regularities pertain not only to the contents of the stimuli ("what") but also their timing ("when"), and both interactively modulate sensory processing. In speech streams, predictions can be formed at multiple hierarchical levels, both in terms of contents (e.g. single syllables vs. words) and timing (e.g., faster vs. slower time scales). Whether and how these hierarchies map onto each other in terms of integrating "what" and "when" predictions remains unknown. Under one hypothesis neural hierarchies may link "what" and "when" predictions within sensory processing areas: with lower cortical regions mediating interactions for smaller units e.g., syllables, and higher cortical areas mediating interactions for larger units e.g., words. Alternatively, interactions between "what" and "when" predictions might rest on a generic, sensory-independent mechanism, mediated by common attention-related (e.g., frontoparietal) networks. To address those questions, we manipulated "what" and "when" predictions at two levels - single syllables and disyllabic pseudowords - while recording neural activity using magnetoencephalography (MEG) in healthy volunteers (N=22). We studied how syllable and/or word deviants are modulated by "when" predictability, both analyzing event-related fields and using source reconstruction and dynamic causal modeling to explain the observed effects in terms of the underlying effective connectivity. "When" predictions modulated "what" mismatch responses in a specific way with regards to speech hierarchy, such that mismatch responses to deviant words (vs. syllables) were amplified by temporal predictions at a slower (vs. faster) time scale. However, these modulations were source-localized to a shared network of cortical regions, including frontal and parietal sources. Effective connectivity analysis showed that, while mismatch responses to violations of "what" predictions modulated connectivity between regions, the integration of "what" and "when" predictions selectively modulated connectivity within regions, consistent with gain effects. These results suggest that the brain integrates "what" and "when" predictions that are congruent with respect to their hierarchical level, but this integration is mediated by a shared and distributed cortical network. This contrasts with recent studies indicating separable networks for different levels of hierarchical speech processing.

neuroscience↗

bioRxiv2022

"What" and "When" Predictions Modulate Auditory Processing in a Contextually Specific Manner

Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli (i.e., "what" it is) and their timing (i.e., "when" it will occur), both of which are known to interactively modulate sensory processing. In real-world stimulus streams, regularities also occur contextually - e.g. predictions of individual notes vs. melodic contour in music. However, it is unknown whether the brain integrates predictions in a contextually congruent manner (e.g., if slower "when" predictions selectively interact with complex "what" predictions), and whether integrating predictions of simple vs. complex features rely on dissociable neural correlates. To address these questions, our study employed "what" and "when" violations at different levels - single tones (elements) vs. tone pairs (chunks) - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N=20) performing a repetition detection task. Our results reveal that "what" and "when" predictions interactively modulated stimulus-evoked response amplitude in a contextually congruent manner, but that these modulations were shared between contexts in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" prediction selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network. Taken together, these results suggest that the brain integrates different predictions with a high degree of contextual specificity, but in a shared and distributed cortical network. Significance statementPredictions of stimulus features, present in different statistically-regular contexts in the environment, are crucial to forming adaptive behavior. However, it is unknown if the brain integrates predictions selectively according to such contextual differences. By recording human electroencephalography during experimental manipulations of time-based and content-based predictions, we found that those predictions interactively modulated neural activity in a contextually congruent manner, such that local (vs. global) time-based predictions modulated content-based predictions of sequence elements (vs. chunks). These modulations were shared between contextual levels in terms of the spatiotemporal distribution of neural activity. This suggests that the brain integrates different predictions with a high degree of contextual specificity, but in a shared and distributed cortical network.

neuroscience↗

bioRxiv2021

Simultaneous Mnemonic and Predictive Representations in the Auditory Cortex

Recent studies have shown that stimulus history can be decoded via the use of broadband sensory impulses to reactivate mnemonic representations. It has also been shown that predictive mechanisms in the auditory system demonstrate similar tonotopic organization of neural activity as that elicited by the perceived stimuli. However, it remains unclear if the mnemonic and predictive information can be decoded from cortical activity simultaneously and from overlapping neural populations. Here, we recorded neural activity using electrocorticography (ECoG) in the auditory cortex of anesthetized rats while exposed to repeated stimulus sequences, where events within the sequence were occasionally replaced with a broadband noise burst or omitted entirely. We show that both stimulus history and predicted stimuli can be decoded from neural responses to broadband impulse at overlapping latencies but linked to largely independent neural populations. We also demonstrate that predictive representations are learned over the course of stimulation at two distinct time scales, reflected in two dissociable time windows of neural activity. These results establish a valuable tool for investigating the neural mechanisms of passive sequence learning, memory encoding, and prediction mechanisms within a single paradigm, and provide novel evidence for learning predictive representations even under anaesthesia.

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bioRxiv2020

Memory Transfer of Random Time Patterns Across Modalities

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, temporal patterns implicitly learned within one modality can also be recognised in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers (N=24, 12 females, 12 males) using electroencephalography (EEG), while participants were exposed to brief sequences of randomly-timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment, enabling implicit learning. Replicating previous behavioural findings, we showed that participants benefit from temporal information learned in audition, and that they can apply this information to stimuli presented in vision. Such memory transfer was not observed from vision to audition. However, using an analysis of EEG response learning curves, we showed that learning temporal structures both within and across modalities modulates single-trial EEG response amplitudes in both conditions (audition to vision and vision to audition). Interestingly, the neural correlates of temporal learning within modalities relied on modality-specific brain regions, while learning transfer affected activity in frontal regions, suggesting distinct mechanisms. The cross-modal effect could be linked to frontal beta-band activity. The neural effects of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. Thus, both modality-specific mechanisms for learning of temporal information, and general mechanisms which mediate learning transfer across modalities, have distinct physiological signatures that are observable in the EEG.

neuroscience↗