publication . Other literature type . Article . 2018

Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI

Ayan Sengupta; Stefan Pollmann; Michael Hanke;
  • Published: 04 Apr 2018
  • Publisher: (:unav)
  • Country: China (People's Republic of)
Abstract
<ns4:p>Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the...
Subjects
Medical Subject Headings: genetic structures
free text keywords: Research Note, Articles, musical-genre decoding, 7 Tesla fMRI, primary auditory cortex, spatial band-pass filtering, Spatial filter, Brain activity and meditation, Stimulus (physiology), Sensory stimulation therapy, Speech recognition, Auditory cortex, Decoding methods, Visual cortex, medicine.anatomical_structure, medicine, Bandpass filtering
Funded by
NSF| U.S.-German Collaboration: Building common high-dimensional models of neural representational spaces
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1129855
  • Funding stream: Directorate for Social, Behavioral & Economic Sciences | Division of Behavioral and Cognitive Sciences
19 references, page 1 of 2

Sengupta A, Yakupov R, Speck O, et al.: The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7T. Neuroimage. 2017; 148: 64-76.

PubMed Abstract | Publisher Full Text Hanke M, Dinga R, Häusler C, et al.: High-resolution 7-Tesla fMRI data on the perception of musical genres - an extension to the studyforrest dataset [version 1; referees: 2 approved with reservations]. F1000Res. 2015; 4: 174.

Publisher Full Text Hanke M, Baumgartner FJ, Ibe P, et al.: A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Sci Data. 2014; 1: 140003.

PubMed Abstract | Publisher Full Text | Free Full Text Güçlü U, Thielen J, Hanke M, et al.: Brains on beats. In Advances in Neural Information Processing Systems. 2016; 2101-2109.

Reference Source Casey MA: Music of the 7Ts: Predicting and Decoding Multivoxel fMRI Responses with Acoustic, Schematic, and Categorical Music Features. Front Psychol. 2017; 8: 1179.

PubMed Abstract | Publisher Full Text | Free Full Text In MH, Speck O: Highly accelerated PSF-mapping for EPI distortion correction with improved fidelity. MAGMA. 2012; 25(3): 183-192.

PubMed Abstract | Publisher Full Text Desikan RS, Ségonne F, Fischl B, et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006; 31(3): 968-980.

PubMed Abstract | Publisher Full Text Millman KJ, Brett M: Analysis of functional magnetic resonance imaging in Python. Comput Sci Eng. 2007; 9(3): 52-55.

Publisher Full Text Pernet CR: Misconceptions in the use of the General Linear Model applied to functional MRI: a tutorial for junior neuro-imagers. Front Neurosci. 2014; 8: 1.

PubMed Abstract | Publisher Full Text | Free Full Text Chang CC, Lin CJ: LIBSVM: A library for support vector machines. ACM Trans Intell Syst Technol. 2011; 2(3): 27.

Publisher Full Text Hanke M, Halchenko YO, Sederberg PB, et al.: PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data. Front Neuroinform. 2009; 3: 3.

PubMed Abstract | Publisher Full Text | Free Full Text Varoquaux G, Raamana PR, Engemann DA, et al.: Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines. Neuroimage. 2017; 17. Freeman J, Brouwer GJ, Heeger DJ, et al.: Orientation decoding depends on maps, not columns. J Neurosci. 2011; 31(13): 4792-804.

PubMed Abstract | Publisher Full Text | Free Full Text Alink A, Krugliak A, Walther A, et al.: fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli. Front Psychol.

PubMed Abstract | Publisher Full Text | Free Full Text 19. Freeman J, Heeger DJ, Merriam EP: Coarse-scale biases for spirals and orientation in human visual cortex. J Neurosci. 2013; 33(50): 19695-703.

PubMed Abstract | Publisher Full Text | Free Full Text 20. Linden JF, Schreiner CE: Columnar transformations in auditory cortex? A comparison to visual and somatosensory cortices. Cereb Cortex. 2003; 13(1): 83-89.

19 references, page 1 of 2
Abstract
<ns4:p>Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the...
Subjects
Medical Subject Headings: genetic structures
free text keywords: Research Note, Articles, musical-genre decoding, 7 Tesla fMRI, primary auditory cortex, spatial band-pass filtering, Spatial filter, Brain activity and meditation, Stimulus (physiology), Sensory stimulation therapy, Speech recognition, Auditory cortex, Decoding methods, Visual cortex, medicine.anatomical_structure, medicine, Bandpass filtering
Funded by
NSF| U.S.-German Collaboration: Building common high-dimensional models of neural representational spaces
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1129855
  • Funding stream: Directorate for Social, Behavioral & Economic Sciences | Division of Behavioral and Cognitive Sciences
19 references, page 1 of 2

Sengupta A, Yakupov R, Speck O, et al.: The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7T. Neuroimage. 2017; 148: 64-76.

PubMed Abstract | Publisher Full Text Hanke M, Dinga R, Häusler C, et al.: High-resolution 7-Tesla fMRI data on the perception of musical genres - an extension to the studyforrest dataset [version 1; referees: 2 approved with reservations]. F1000Res. 2015; 4: 174.

Publisher Full Text Hanke M, Baumgartner FJ, Ibe P, et al.: A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Sci Data. 2014; 1: 140003.

PubMed Abstract | Publisher Full Text | Free Full Text Güçlü U, Thielen J, Hanke M, et al.: Brains on beats. In Advances in Neural Information Processing Systems. 2016; 2101-2109.

Reference Source Casey MA: Music of the 7Ts: Predicting and Decoding Multivoxel fMRI Responses with Acoustic, Schematic, and Categorical Music Features. Front Psychol. 2017; 8: 1179.

PubMed Abstract | Publisher Full Text | Free Full Text In MH, Speck O: Highly accelerated PSF-mapping for EPI distortion correction with improved fidelity. MAGMA. 2012; 25(3): 183-192.

PubMed Abstract | Publisher Full Text Desikan RS, Ségonne F, Fischl B, et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006; 31(3): 968-980.

PubMed Abstract | Publisher Full Text Millman KJ, Brett M: Analysis of functional magnetic resonance imaging in Python. Comput Sci Eng. 2007; 9(3): 52-55.

Publisher Full Text Pernet CR: Misconceptions in the use of the General Linear Model applied to functional MRI: a tutorial for junior neuro-imagers. Front Neurosci. 2014; 8: 1.

PubMed Abstract | Publisher Full Text | Free Full Text Chang CC, Lin CJ: LIBSVM: A library for support vector machines. ACM Trans Intell Syst Technol. 2011; 2(3): 27.

Publisher Full Text Hanke M, Halchenko YO, Sederberg PB, et al.: PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data. Front Neuroinform. 2009; 3: 3.

PubMed Abstract | Publisher Full Text | Free Full Text Varoquaux G, Raamana PR, Engemann DA, et al.: Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines. Neuroimage. 2017; 17. Freeman J, Brouwer GJ, Heeger DJ, et al.: Orientation decoding depends on maps, not columns. J Neurosci. 2011; 31(13): 4792-804.

PubMed Abstract | Publisher Full Text | Free Full Text Alink A, Krugliak A, Walther A, et al.: fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli. Front Psychol.

PubMed Abstract | Publisher Full Text | Free Full Text 19. Freeman J, Heeger DJ, Merriam EP: Coarse-scale biases for spirals and orientation in human visual cortex. J Neurosci. 2013; 33(50): 19695-703.

PubMed Abstract | Publisher Full Text | Free Full Text 20. Linden JF, Schreiner CE: Columnar transformations in auditory cortex? A comparison to visual and somatosensory cortices. Cereb Cortex. 2003; 13(1): 83-89.

19 references, page 1 of 2
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publication . Other literature type . Article . 2018

Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI

Ayan Sengupta; Stefan Pollmann; Michael Hanke;