More Like this

1. Linking cognitive and neural models of audiovisual processing to explore speech perception in autism

   Brown, Grace C.; Feldman, Naomi H. (July 2024, Proceedings of the Annual Conference of the Cognitive Science Society)

   Autistic and neurotypical children do not handle audiovisual speech in the same manner. Current evidence suggests that this difference occurs at the level of cue combination. Here, we test whether differences in autistic and neurotypical audiovisual speech perception can be explained by a neural theory of sensory perception in autism, which proposes that heightened levels of neural excitation can account for sensory differences in autism. Through a linking hypothesis that integrates a standard probabilistic cognitive model of cue integration with representations of neural activity, we derive a model that can simulate audio-visual speech perception at a neural population level. Simulations of an audiovisual lexical identification task demonstrate that heightened levels of neural excitation at the level of cue combination cannot account for the observed differences in autistic and neurotypical children's audiovisual speech perception. 

   more » « less
2. Cortical responses time-locked to continuous speech in the high-gamma band depend on selective attention

   https://doi.org/10.3389/fnins.2023.1264453  

   Commuri, Vrishab; Kulasingham, Joshua P.; Simon, Jonathan Z. (December 2023, Frontiers in Neuroscience)

   Auditory cortical responses to speech obtained by magnetoencephalography (MEG) show robust speech tracking to the speaker's fundamental frequency in the high-gamma band (70–200 Hz), but little is currently known about whether such responses depend on the focus of selective attention. In this study 22 human subjects listened to concurrent, fixed-rate, speech from male and female speakers, and were asked to selectively attend to one speaker at a time, while their neural responses were recorded with MEG. The male speaker's pitch range coincided with the lower range of the high-gamma band, whereas the female speaker's higher pitch range had much less overlap, and only at the upper end of the high-gamma band. Neural responses were analyzed using the temporal response function (TRF) framework. As expected, the responses demonstrate robust speech tracking of the fundamental frequency in the high-gamma band, but only to the male's speech, with a peak latency of ~40 ms. Critically, the response magnitude depends on selective attention: the response to the male speech is significantly greater when male speech is attended than when it is not attended, under acoustically identical conditions. This is a clear demonstration that even very early cortical auditory responses are influenced by top-down, cognitive, neural processing mechanisms. 

   more » « less
3. Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior

   https://doi.org/10.1007/978-3-031-16431-6_34  

   Zhao, Chongyue; Zhan, Liang; Thompson, Paul M; Huang, Heng. (September 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. Lecture Notes in Computer Science.)

   Understanding the intrinsic patterns of human brain is important to make inferences about the mind and brain-behavior association. Electrophysiological methods (i.e. MEG/EEG) provide direct measures of neural activity without the effect of vascular confounds. The blood oxygenated level-dependent (BOLD) signal of functional MRI (fMRI) reveals the spatial and temporal brain activity across different brain regions. However, it is unclear how to associate the high temporal resolution Electrophysiological measures with high spatial resolution fMRI signals. Here, we present a novel interpretable model for coupling the structure and function activity of brain based on heterogeneous contrastive graph representation. The proposed method is able to link manifest variables of the brain (i.e. MEG, MRI, fMRI and behavior performance) and quantify the intrinsic coupling strength of different modal signals. The proposed method learns the heterogeneous node and graph representations by contrasting the structural and temporal views through the mind to multimodal brain data. The first experiment with 1200 subjects from Human connectome Project (HCP) shows that the proposed method outperforms the existing approaches in predicting individual gender and enabling the location of the importance of brain regions with sex difference. The second experiment associates the structure and temporal views between the low-level sensory regions and high-level cognitive ones. The experimental results demonstrate that the dependence of structural and temporal views varied spatially through different modal variants. The proposed method enables the heterogeneous biomarkers explanation for different brain measurements. 

   more » « less
4. Organization of distributed cortical connections underlying the processing of auditory information in dogs assessed by diffusion MRI

   https://doi.org/10.1162/IMAG.a.16  

   Cordeau, Mélina; Barton, Sophie A; Hecht, Erin E (January 2025, Imaging Neuroscience)

   Abstract Dogs and humans have co-evolved for millennia. This provides an opportunity to examine neural adaptations supporting cross-species communication. Previous canine fMRI studies have identified functional activations in response to human voice perception. However, the specific neural pathways involved in dogs’ ability to process and respond to human language remain unknown. This study takes a data-driven approach to examine the brain connectivity supporting bidirectional communication in a large sample of dogs. We examine white matter pathways linking temporal regions, involved in the perception of communicative signals, and frontal regions, responsible for generating communicative responses. Using cortical regions with known axonal connectivity from tract tracing studies as a foundation, we applied probabilistic tractography to measure connectivity patterns in a diverse cohort of dogs (n = 110, 16 breeds). Our findings reveal that, beyond short-range intra-regional connections, consistent large-scale tracts connect the prefrontal, somatosensory, premotor, motor, and temporal lobes across subjects. Hierarchical clustering analysis revealed distinct structural organization, with sylvian regions strongly connected to motor regions and ectosylvian regions linked to higher-order frontal and prefrontal regions. This organization may suggest that the ectosylvian gyrus plays a key role in integrating auditory input with complex cognitive functions, potentially underlying cross-species communication and language processing in dogs. This study elucidates cortico-cortical communication pathways in dogs and contributes to our understanding of the neural basis of lexical processing in the canine brain. 

   more » « less
5. Algorithms for Estimating Time-Locked Neural Response Components in Cortical Processing of Continuous Speech

   https://doi.org/10.1109/TBME.2022.3185005  

   Kulasingham, Joshua P.; Simon, Jonathan Z. (June 2022, IEEE Transactions on Biomedical Engineering)

   Objective: The Temporal Response Function (TRF) is a linear model of neural activity time-locked to continuous stimuli, including continuous speech. TRFs based on speech envelopes typically have distinct components that have provided remarkable insights into the cortical processing of speech. However, current methods may lead to less than reliable estimates of single-subject TRF components. Here, we compare two established methods, in TRF component estimation, and also propose novel algorithms that utilize prior knowledge of these components, bypassing the full TRF estimation. Methods: We compared two established algorithms, ridge and boosting, and two novel algorithms based on Subspace Pursuit (SP) and Expectation Maximization (EM), which directly estimate TRF components given plausible assumptions regarding component characteristics. Single-channel, multi-channel, and source-localized TRFs were fit on simulations and real magnetoencephalographic data. Performance metrics included model fit and component estimation accuracy. Results: Boosting and ridge have comparable performance in component estimation. The novel algorithms outperformed the others in simulations, but not on real data, possibly due to the plausible assumptions not actually being met. Ridge had slightly better model fits on real data compared to boosting, but also more spurious TRF activity. Conclusion: Results indicate that both smooth (ridge) and sparse (boosting) algorithms perform comparably at TRF component estimation. The SP and EM algorithms may be accurate, but rely on assumptions of component characteristics. Significance: This systematic comparison establishes the suitability of widely used and novel algorithms for estimating robust TRF components, which is essential for improved subject-specific investigations into the cortical processing of speech. 

   more » « less