scholarly journals Intracranial recordings from human auditory cortex reveal a neural population selective for song

2019 ◽  
Author(s):  
Sam V Norman-Haignere ◽  
Jenelle Feather ◽  
Dana Boebinger ◽  
Peter Brunner ◽  
Anthony Ritaccio ◽  
...  
Keyword(s):  
Human Brain ◽  
Superior Temporal Gyrus ◽  
Data Driven ◽  
Neural Population ◽  
Acoustic Features ◽  
Neural Representations ◽  
Cortical Responses ◽  
Different Types ◽  
Neural Selectivity ◽  
Intracranial Recordings

AbstractHow are neural representations of music organized in the human brain? While neuroimaging has suggested some segregation between responses to music and other sounds, it remains unclear whether finer-grained organization exists within the domain of music. To address this question, we measured cortical responses to natural sounds using intracranial recordings from human patients and inferred canonical response components using a data-driven decomposition algorithm. The inferred components replicated many prior findings including distinct neural selectivity for speech and music. Our key novel finding is that one component responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features and was co-located with speech- and music-selective responses in the middle and anterior superior temporal gyrus. These results suggest that neural representations of music are fractionated into subpopulations selective for different types of music, at least one of which is specialized for the analysis of song.

scholarly journals A speech envelope landmark for syllable encoding in human superior temporal gyrus

2019 ◽  
Vol 5 (11) ◽  
pp. eaay6279 ◽  
Author(s):  
Yulia Oganian ◽  
Edward F. Chang
Keyword(s):  
Temporal Structure ◽  
Superior Temporal Gyrus ◽  
Rate Of Change ◽  
Speech Comprehension ◽  
Acoustic Features ◽  
Local Maxima ◽  
Neural Computations ◽  
Absolute Amplitude ◽  
Speech Envelope ◽  
Intracranial Recordings

The most salient acoustic features in speech are the modulations in its intensity, captured by the amplitude envelope. Perceptually, the envelope is necessary for speech comprehension. Yet, the neural computations that represent the envelope and their linguistic implications are heavily debated. We used high-density intracranial recordings, while participants listened to speech, to determine how the envelope is represented in human speech cortical areas on the superior temporal gyrus (STG). We found that a well-defined zone in middle STG detects acoustic onset edges (local maxima in the envelope rate of change). Acoustic analyses demonstrated that timing of acoustic onset edges cues syllabic nucleus onsets, while their slope cues syllabic stress. Synthesized amplitude-modulated tone stimuli showed that steeper slopes elicited greater responses, confirming cortical encoding of amplitude change, not absolute amplitude. Overall, STG encoding of the timing and magnitude of acoustic onset edges underlies the perception of speech temporal structure.

scholarly journals Phase-amplitude coupling supports phase coding in human ECoG

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Andrew J Watrous ◽  
Lorena Deuker ◽  
Juergen Fell ◽  
Nikolai Axmacher
Keyword(s):  
Human Brain ◽  
High Frequency ◽  
Low Frequency ◽  
Phase Coding ◽  
Neural Representations ◽  
Simultaneous Acquisition ◽  
Categorical Information ◽  
High Frequency Activity ◽  
Phase Amplitude ◽  
Intracranial Recordings

Prior studies have shown that high-frequency activity (HFA) is modulated by the phase of low-frequency activity. This phenomenon of phase-amplitude coupling (PAC) is often interpreted as reflecting phase coding of neural representations, although evidence for this link is still lacking in humans. Here, we show that PAC indeed supports phase-dependent stimulus representations for categories. Six patients with medication-resistant epilepsy viewed images of faces, tools, houses, and scenes during simultaneous acquisition of intracranial recordings. Analyzing 167 electrodes, we observed PAC at 43% of electrodes. Further inspection of PAC revealed that category specific HFA modulations occurred at different phases and frequencies of the underlying low-frequency rhythm, permitting decoding of categorical information using the phase at which HFA events occurred. These results provide evidence for categorical phase-coded neural representations and are the first to show that PAC coincides with phase-dependent coding in the human brain.

scholarly journals Neural representations of own-voice in the human auditory cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Taishi Hosaka ◽  
Marino Kimura ◽  
Yuko Yotsumoto
Keyword(s):  
Auditory Cortex ◽  
Superior Temporal Gyrus ◽  
Neural Correlates ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen ◽  
Oxygen Level ◽  
Blood Oxygen Level ◽  
Neural Representations ◽  
Human Auditory Cortex ◽  
The Voice

AbstractWe have a keen sensitivity when it comes to the perception of our own voices. We can detect not only the differences between ourselves and others, but also slight modifications of our own voices. Here, we examined the neural correlates underlying such sensitive perception of one’s own voice. In the experiments, we modified the subjects’ own voices by using five types of filters. The subjects rated the similarity of the presented voices to their own. We compared BOLD (Blood Oxygen Level Dependent) signals between the voices that subjects rated as least similar to their own voice and those they rated as most similar. The contrast revealed that the bilateral superior temporal gyrus exhibited greater activities while listening to the voice least similar to their own voice and lesser activation while listening to the voice most similar to their own. Our results suggest that the superior temporal gyrus is involved in neural sharpening for the own-voice. The lesser degree of activations observed by the voices that were similar to the own-voice indicates that these areas not only respond to the differences between self and others, but also respond to the finer details of own-voices.

scholarly journals Adaptive data-driven age and patch mixing in contact networks with recurrent mobility

2021 ◽  
Author(s):  
Jesse Knight ◽  
Huiting Ma ◽  
Amir Ghasemi ◽  
Mackenzie Hamilton ◽  
Kevin Brown ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Age Distribution ◽  
Age Groups ◽  
Data Driven ◽  
Infectious Disease Transmission ◽  
Mobility Data ◽  
Contact Patterns ◽  
Different Types ◽  
Mixing Patterns ◽  
Transmission Models

AbstractInfectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form a contact if they meet in patch C. We build upon their approach to address three potential gaps that remain. First, our approach includes a distribution of contacts by age that is responsive to underlying age distribution of the mixing pool. Second, different age distributions by contact type are also maintained in our approach, such that changes to the numbers of different types of contacts are appropriately reflected in changes to the overall age mixing patterns. Finally, we introduce and distinguish between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch; and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch. We describe in detail the steps required to implement our approach, and present results of an example application.Graphical Abstract

scholarly journals Corpus linguistics and its aplications in higher education

2010 ◽  
pp. 51 ◽  
Author(s):  
Miguel Fuster Márquez ◽  
Begoña Clavel Arroitia
Keyword(s):  
Higher Education ◽  
Corpus Linguistics ◽  
Teaching Practices ◽  
Language Teaching ◽  
Applied Linguistics ◽  
Data Driven ◽  
Future Success ◽  
Different Types ◽  
Theoretical Linguistics ◽  
Relevant Factors

The aim of this paper is to review and analyse relevant factors related to the implementation of corpus linguistics (CL) in higher education. First we set out to describe underlying principles of CL and its developments in relation to theoretical linguistics and its applications in modern teaching practices. Then we attempt to establish how different types of corpora have contributed to the development of direct and indirect approaches in language teaching. We single out Data Driven Learning (DDL) due to its relevance in applied linguistics literature, and examine in detail advantages and drawbacks. Finally, we outline problems concerning the implementation of CL in the classroom since awareness of the limitations of CL is vital for its future success.

scholarly journals Low Frequency Noise Remove from EEG Signal

2020 ◽  
Vol 9 (1) ◽  
pp. 1510-1513
Keyword(s):  
Human Brain ◽  
Random Noise ◽  
Low Frequency ◽  
Frequency Noise ◽  
Eeg Signal ◽  
Low Frequency Noise ◽  
Frequency Range ◽  
Average Value ◽  
Different Types ◽  
The Brain

The electrical activity of the brain recorded by EEG which used to detect different types of diseases and disorders of the human brain. There is contained a large amount of random noise present during EEG recording, such as artifacts and baseline changes. These noises affect the low -frequency range of the EEG signal. These artifacts hiding some valuable information during analyzing of the EEG signal. In this paper we used the FIR filter for removing low -frequency noise(<1Hz) from the EEG signal. The performance is measured by calculating the SNR and the RMSE. We obtained RMSE average value from the test is 0.08 and the SNR value at frequency(<1Hz) is 0.0190.

Multisensory Integration during Short-term Music Reading Training Enhances Both Uni- and Multisensory Cortical Processing

2014 ◽  
Vol 26 (10) ◽  
pp. 2224-2238 ◽  
Author(s):  
Evangelos Paraskevopoulos ◽  
Anja Kuchenbuch ◽  
Sibylle C. Herholz ◽  
Christo Pantev
Keyword(s):  
Multisensory Integration ◽  
Superior Temporal Gyrus ◽  
Music Reading ◽  
Short Term ◽  
Visual Elements ◽  
Human Ability ◽  
Cortical Responses ◽  
Anterior Prefrontal Cortex

The human ability to integrate the input of several sensory systems is essential for building a meaningful interpretation out of the complexity of the environment. Training studies have shown that the involvement of multiple senses during training enhances neuroplasticity, but it is not clear to what extent integration of the senses during training is required for the observed effects. This study intended to elucidate the differential contributions of uni- and multisensory elements of music reading training in the resulting plasticity of abstract audiovisual incongruency identification. We used magnetoencephalography to measure the pre- and posttraining cortical responses of two randomly assigned groups of participants that followed either an audiovisual music reading training that required multisensory integration (AV-Int group) or a unisensory training that had separate auditory and visual elements (AV-Sep group). Results revealed a network of frontal generators for the abstract audiovisual incongruency response, confirming previous findings, and indicated the central role of anterior prefrontal cortex in this process. Differential neuroplastic effects of the two types of training in frontal and temporal regions point to the crucial role of multisensory integration occurring during training. Moreover, a comparison of the posttraining cortical responses of both groups to a group of musicians that were tested using the same paradigm revealed that long-term music training leads to significantly greater responses than the short-term training of the AV-Int group in anterior prefrontal regions as well as to significantly greater responses than both short-term training protocols in the left superior temporal gyrus (STG).

scholarly journals Simple Acoustic Features Can Explain Phoneme-Based Predictions of Cortical Responses to Speech

2019 ◽  
Vol 29 (12) ◽  
pp. 1924-1937.e9 ◽  
Author(s):  
Christoph Daube ◽  
Robin A.A. Ince ◽  
Joachim Gross
Keyword(s):  
Acoustic Features ◽  
Cortical Responses

scholarly journals FusionDN: A Unified Densely Connected Network for Image Fusion

2020 ◽  
Vol 34 (07) ◽  
pp. 12484-12491 ◽  
Author(s):  
Han Xu ◽  
Jiayi Ma ◽  
Zhuliang Le ◽  
Junjun Jiang ◽  
Xiaojie Guo
Keyword(s):  
Image Fusion ◽  
State Of The Art ◽  
Data Driven ◽  
Single Model ◽  
Connected Network ◽  
Qualitative And Quantitative ◽  
Multiple Tasks ◽  
Different Types ◽  
Fused Image ◽  
Quantitative Results

In this paper, we present a new unsupervised and unified densely connected network for different types of image fusion tasks, termed as FusionDN. In our method, the densely connected network is trained to generate the fused image conditioned on source images. Meanwhile, a weight block is applied to obtain two data-driven weights as the retention degrees of features in different source images, which are the measurement of the quality and the amount of information in them. Losses of similarities based on these weights are applied for unsupervised learning. In addition, we obtain a single model applicable to multiple fusion tasks by applying elastic weight consolidation to avoid forgetting what has been learned from previous tasks when training multiple tasks sequentially, rather than train individual models for every fusion task or jointly train tasks roughly. Qualitative and quantitative results demonstrate the advantages of FusionDN compared with state-of-the-art methods in different fusion tasks.

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