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Mohammadi, Y.

Publications and source records attributed to Mohammadi, Y..

5 recordsLinked to original sources

An integrated virtual reality platform for naturalistic neuroimaging with magnetoencephalography

Studying the brain in motion promises deep insights into the neural circuits that support complex, real-world behaviour. In humans, wearable optically pumped magnetometers (OPMs) enable magnetoencephalography (MEG) with millisecond temporal resolution and millimetre spatial precision during movement. Integrating this technology with virtual reality (VR) could enable fully naturalistic experimental paradigms, but magnetic interference from existing head-mounted displays (HMDs) prevents reliable whole-brain MEG recordings. Here, we present and validate a VR system that integrates with wearable, OPM-based MEG. At its core is a purpose-designed HMD with minimal ferromagnetic material, resulting in magnetic flux density two orders of magnitude lower than consumer-grade alternatives at comparable resolution and weight. Using phantom measurements and established perceptual and cognitive benchmark tasks across participants, we demonstrate robust stimulus-induced neuronal activity at both sensor and source level. Crucially, these sources span the entire brain, including visual, motor and prefrontal cortices, as well as hippocampus. Our proposed VR system is straightforward to produce, readily extendable, and enables whole-brain MEG during immersive, naturalistic behaviours.

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Brain Representations of Natural Sound Statistics

Natural sound textures (e.g., rain, crackling fire) are perceptually defined by time-averaged summary statistics. While previous studies have examined neural responses to natural sounds, little is known regarding the neural processing of the statistics underlying these sounds. To study neuronal correlates of these statistics, we measured brain responses to synthetic sound textures in which statistical structure was systematically varied while preserving the texture category. Using two fMRI experiments (males and females), we examined neural responses along the ascending auditory pathway, within auditory cortex and medial temporal lobe (MTL) regions implicated in pattern analysis. In Experiment 1, we parametrically varied the full set of texture statistics, creating sounds with different levels of naturalness. In Experiment 2, we selectively manipulated high-level statistics (cochlear skewness and kurtosis, cochlear and modulation correlations) while holding low-level statistics (cochlear mean and modulation power) constant. Increasing texture naturalness produced graded increases in BOLD responses across bilateral primary and nonprimary auditory cortex in both experiments, although overall responses were weaker in Experiment 2. This reduction suggests that low-level statistics contribute substantially to response magnitude, even though higher-order statistics are sufficient to elicit graded responses. We also observed modulation in MTL regions, including entorhinal cortex, in Experiment 1. Moreover, functional connectivity between hippocampus and auditory cortex increased for more degraded (less natural) textures, suggesting a modulatory rather than representational role for MTL in texture processing. Together, these findings show that sensitivity to texture statistics is distributed across the auditory cortex and highlight MTL-auditory interactions when texture structure is ambiguous. Significant StatementNatural sound textures such as rain or crackling fire are perceptually defined by time-averaged summary statistics that support efficient auditory perception, yet how the human brain represents these statistics remains unclear. Using fMRI and synthetic sound textures in which statistical structure was systematically manipulated, we found that both primary and nonprimary auditory cortex were sensitive to texture statistics, exhibiting a graded and distributed representation of these acoustic features. We also observed increased functional connectivity between the hippocampus and auditory regions when texture structure was degraded or the sounds were unnatural. Together, these results indicate that sound texture statistics are encoded across multiple levels of auditory cortex and further suggest a modulatory role for hippocampus under conditions of heightened perceptual uncertainty.

neuroscience↗

Neural entrainment to pitch changes of auditory targets in noise

Neural entrainment to certain acoustic features can predict speech-in-noise perception, but these features are difficult to separate. We measured neural responses to both natural speech-in-noise and stimuli (auditory figure-ground) that simulate speech-in-noise without any acoustic or linguistic confound such as stress contour and semantics. The figure-ground stimulus is formed by multiple temporally coherent pure-tone components embedded in a random tone cloud. Previous work has shown that discrimination of dynamic figure-ground based on the fundamental frequency (F0) of natural speech predicts speech-in-noise recognition independent of hearing and age. In this study, we compared the brain substrate for the figure-ground analysis based on the F0 contour and a statistically similar 1/f contour with speech-in-noise. We used the temporal response function to predict the electroencephalography responses to the frequency trajectories of the auditory targets. We demonstrate that the brain significantly tracked the pitch changes in both AFG conditions (F0 and 1/F tracking) and a sentence-in-noise condition (F0 tracking) at similar latencies, but at similar magnitudes only when tracking the F0 contour. The pitch-tracking accuracy was consistently high across the delta and theta bands for the AFG condition but not for speech. Sensor-space analysis revealed that speech-in-noise performance correlated with the positive peak amplitude of the F0 figure-ground at 100 ms. Source-space analysis revealed bilateral temporal lobe and hippocampal generators, and strong tracking in the superior parietal lobe for auditory figures and natural speech. In conclusion, our findings demonstrate that the human brain reliably tracks the F0 trajectory of both speech and a non-linguistic figure in noise, with speech tracking showing reduced accuracy in the theta band compared to figure-ground tracking. Despite the difference in prediction accuracy, we reveal striking similarities in neural entrainment patterns and source locations between the two paradigms. These results suggest that neural entrainment engages high-level cortical mechanisms independent of linguistic content. Furthermore, we show that TRF peak amplitude serves as a potential biomarker for speech-in-noise ability, highlighting possible clinical applications.

neuroscience↗

Brain bases for navigating acoustic features

Whether physical navigation shares neural substrates with mental travel in other behaviourally relevant domains is debated. With respect to sound, pure-tone working memory in humans elicits hippocampal as well as auditory cortical and inferior frontal activity, and rodent work suggests that hippocampal cells that usually track an animals physical location can also map to tone frequency when task-relevant. We generated a sound dimension based on the density of random-frequency tones in a stack, resulting in a percept ranging from low- ("beepy") to high-density ("noisy"). We established that unlike tone frequency, which listeners automatically associate with vertical position, this density dimension elicited no consistent spatial mapping. During functional magnetic resonance imaging, human participants held in mind the density of a series of tone stacks and, after a short maintenance period, adjusted further stacks to match the target ("navigation"). Density of the currently heard sound was represented most strongly in bilateral non-primary auditory cortex, specifically bilateral planum polare, while density of the maintained target was represented in right anterior hippocampus and left inferior temporal gyrus. Encoding and maintenance activity in bilateral hippocampus, inferior frontal gyrus, planum polare and posterior cingulate was positively associated with subsequent navigation success. Bilateral inferior frontal gyrus and hippocampus were among regions with elevated activity during adjustment, compared to a parity-judgment condition with closely matched acoustics and motor demands. Bilateral orbitofrontal cortex was more active when navigation was toward a target density than when participants adjusted density in a control condition with no particular target. We find that self-initiated travel along a non-spatial auditory dimension engages a brain system overlapping with that supporting physical navigation. Key PointsO_LIWork in rodents suggests that navigation in physical space and the active analysis of sounds share a neural substrate in the hippocampus, supporting the use of common computational mechanisms. C_LIO_LIWe examined the human brain system for navigation through an acoustic environment to a remembered target. C_LIO_LIIn addition to high-level auditory cortex we demonstrate involvement of the hippocampus in acoustic navigation along with other sites in frontal and cingulate cortex that also support physical navigation. C_LI

neuroscience↗

Phase-locking of neural activity to the envelope of speech in the delta frequency band reflects differences between word lists and sentences

The envelope of a speech signal is tracked by neural activity in the cerebral cortex. The cortical tracking occurs mainly in two frequency bands, theta (4 - 8 Hz) and delta band (1 - 4 Hz). Tracking in the faster theta band has been mostly associated with lower-level acoustic processing, such as the parsing of syllables, whereas the slower tracking in the delta band relates to higher-level linguistic information of words and word sequences. However, much regarding the more specific association between cortical tracking and acoustic as well as linguistic processing remains to be uncovered. Here we recorded electroencephalographic (EEG) responses to both meaningful sentences as well as random word lists in different levels of signal-to-noise ratios (SNRs) that lead to different levels of speech comprehension as well as listening effort. We then related the neural signals to the acoustic stimuli by computing the phase-locking value (PLV) between the EEG recordings and the speech envelope. We found that the PLV in the delta band increases with increasing SNR for sentences but not for the random word lists, showing that the PLV in this frequency band reflects linguistic information. When attempting to disentangle the effects of SNR, speech comprehension, and listening effort, we observed a trend that the PLV in the delta band might reflect listening effort rather than the other two variables, although the effect was not statistically significant. In summary, our study shows that the PLV in the delta band reflects linguistic information and might be related to listening effort.

neuroscience↗