The Experts below are selected from a list of 10296 Experts worldwide ranked by ideXlab platform

Christof Faller - One of the best experts on this subject based on the ideXlab platform.

  • Perceptual Coding of high quality digital audio
    Proceedings of the IEEE, 2013
    Co-Authors: Karlheinz Brandenburg, Christof Faller, James D Johnston, Jürgen Herre, W. Bastiaan Kleijn
    Abstract:

    This paper introduces high-quality audio Coding using psychoacoustic models. This technology is now abundant, with gadgets named after a standard (mp3 players) and the ability to play high-quality audio from literally billions of devices. The usual paradigm for these systems is based on filterbanks, followed by quantization and Coding, controlled by a model of human hearing. The paper describes the basic technology, theoretical framework to apply to check for optimality, and the most prominent standards built on the basic ideas and newer work.

  • best wavelet packet bases for audio Coding using Perceptual and rate distortion criteria
    International Conference on Acoustics Speech and Signal Processing, 1999
    Co-Authors: M Erne, G Moschytz, Christof Faller
    Abstract:

    This paper presents a new approach to the adaptation of a wavelet filterbank based on Perceptual and rate-distortion criteria. The system makes use of a wavelet-packet transform where each subband can have an individual time-segmentation. Boundary effects can be avoided by using overlapping blocks of samples and therefore switching bases is possible at every tree-level without affecting other subbands. A modified psychoacoustic model using Perceptual entropy can control the switching of the wavelet filterbank and the individual time-segmentation of every subband allows one to take advantage of temporal masking. Additionally a rate-distortion measure can control the filterbank for lossless audio Coding applications or in cases where large Coding gains can be achieved without using Perceptual criteria. The weight of the Perceptual measure as well as the weight of the rate-distortion measure can be selected individually, enabling to trade lossless Coding versus Perceptual Coding.

Todd S Braver - One of the best experts on this subject based on the ideXlab platform.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    Cerebral Cortex, 2020
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    : Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    bioRxiv, 2019
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task fMRI dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 MZ (monozygotic) twin, 78 DZ (dizygotic) twin, 99 non-twin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically-selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding, and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

Caitlin E Carey - One of the best experts on this subject based on the ideXlab platform.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    Cerebral Cortex, 2020
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    : Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    bioRxiv, 2019
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task fMRI dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 MZ (monozygotic) twin, 78 DZ (dizygotic) twin, 99 non-twin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically-selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding, and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

Yael Courtney - One of the best experts on this subject based on the ideXlab platform.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    Cerebral Cortex, 2020
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    : Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    bioRxiv, 2019
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task fMRI dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 MZ (monozygotic) twin, 78 DZ (dizygotic) twin, 99 non-twin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically-selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding, and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

Maria Z Gehred - One of the best experts on this subject based on the ideXlab platform.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    Cerebral Cortex, 2020
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    : Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.

  • pattern similarity analyses of frontoparietal task Coding individual variation and genetic influences
    bioRxiv, 2019
    Co-Authors: Joset A Etzel, Yael Courtney, Caitlin E Carey, Maria Z Gehred, Arpana Agrawal, Todd S Braver
    Abstract:

    Pattern similarity analyses are increasingly used to characterize Coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task fMRI dataset to examine individual differences and genetic influences on the Coding of working memory load (0-back, 2-back) and Perceptual category (Face, Place). Participants were grouped into 105 MZ (monozygotic) twin, 78 DZ (dizygotic) twin, 99 non-twin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same Perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural Coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically-selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load Coding, and in Visual only for Perceptual Coding. Further, in related pairs, the similarity of load Coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key Coding and heritability features of brain regions.