FUNCTIONAL SPECIALIZATION OF HUMAN AUDITORY CORTICAL FIELDS
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FUNCTIONAL SPECIALIZATION OF HUMAN AUDITORY CORTICAL FIELDS G. C. Stecker 1,2 , I. Liao 1 , T.J.Herron 1 , X.Kang 1 , E.W.Yund 1 , T. J. Rinne 1,3 , D.L.Woods 1 * 1. HCNLAB, Neurology, UC Davis and VANCHCS, Martínez, CA. 2. Speech and Hearing Sciences, Univ. of Washington, Seattle, WA, 3. Dept. of Psychology, Univ. of Helsinki, Helsinki, Finland 282.14 INTRODUCTION. We examined fMRI BOLD activations in auditory cortex using cortical surface mapping techniques to examine the influence of sound frequency, location, and intensity and attention on activation maps. • Identical experiments were performed using continuous an sparse sampling imaging parameters to examine the effects of scanner-generated masking noise. • Alterations in activation patterns as a consequence of tone frequency, location, and intensity were examined during difficult visual attention conditions to control for the potential differences in the attention-attracting properties of different stimuli. • Repeated studies were performed in each subject with the goal of visualizing the individual patterns of auditory cortical fields (ACF) organization. • The results were analyzed using surface- based tools that provide improved precision in comparing with 3D analyses and that permit the visualization of activation patterns References. Fischl, B., Sereno, M. I., Tootell, R. B., and Dale, A. M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Map., 1999, 8: 272-84. Kang, X., Bertrand., 0., Alho, K., Herron, T., Yund, E. W., and Woods, D. L. Local landmark-based mapping of human auditory cortex. NeuroImage, 2004. 22(4): p. 1657-1670. Kaas, J. H. and T. A. Hackett (2000). "Subdivisions of auditory cortex and processing streams in primates." Proc Natl Acad Sci U S A 97(22): 11793-9. Petkov, C.I., Kang, X.J., Alho, K., Bertrand, O. Yund, E.W. and Woods, D.L. Attentional modulation of human auditory SEMI-RANDOM BLOCK DESIGN. Stimuli were presented in 23.2s blocks. On 25% of the visual attention blocks, visual stimuli were presented alone and on 25% of the auditory attention blocks, auditory stimuli were presented alone. On the remaining blocks, visual and auditory stimuli were presented concurrently and subjects attended to either the visual stimuli or the tones. Auditory and visual conditions were randomly selected (with the constraint that auditory and visual attention conditions alternated) and paired for each experiment using Presentation™. IMAGING. Whole brain (29-slices, 92x92 voxels, 4-mm thickness, 1-mm gap) echo-planar images (TR=2.9s or 11.6s, TE = 40 ms) were obtained. Seven subjects were studied. Each participated on six experiments on separate days three with sparse and three with continuous sampling. Each experiment lasted approximately 75 min. BEHAVIOR. Hits rates averaged 54.7% (mean RT 670 ms) CONCLUSIONS. 1. Different features are differentially processed in different regions of auditory cortex. 2. Multiple tonotopic regions are evident in population averages, but smaller discrete regions seen in individual subjects. 3. Individual subjects show reliable but distinct activation patterns with incomplete sampling of the auditory cortical surface. This differences likely reflect variations in venous anatomy, and complicate inferences about ACF organization. 4. Attention does not merely enhance responses similar to increase loudness but recruits processing in additional cortical regions. STIMULI AND TASKS. Subjects performed a one-back matching task, attending to the auditory or visual modality in alternating 23.2s blocks. Auditory stimuli were three-tone patterns (tone durations 250 ms, 10 ms rise/fall, total duration 750 ms) presented once every 1.5 s. Tone intensities were set at 70 or 90 dB SPL in different blocks and tones were presented over broadband masking noise (70 dB SPL). Each tone pattern contained three tones different equally spaced over a one- half octave range that was centered at 225, 900 or 3600 Hz in different blocks. Visual stimuli were faces or words in different blocks. Visual stimuli were presented at central fixation for 700 ms every 1.5 s. During visual attention conditions subjects performed a one-back matching task, identifying facial identity (across expressions) or word category. Mollweide Projection of Cortical structure. Averaged over 62 subjects (124 hemispheres). Hemisphere alignment based on surface structure is more precise than volumetric co- registration (Kang et al, 2004). Here, the precision of alignment is reflected in the clarity of sulcal structure. Lobes are coded by color. Anatomical Structures (white labels): AG, angular gyrus; CC, corpus callosum; CG, cingulate gyrus; CalcS, calcarine sulcus; ColS, collateral sulcus; Cun, cuneate; CS, central sulcus; FG, fusiform gyrus; HG, Heschl’s gyrus, IFG, inferior frontal gyrus; IPL, inferior parietal lobule; IPS, intraparietal sulcus; ITG, inferior temporal gyrus; ITS, inferior temporal sulcus; LG, lingual gyrus; LGofin, long gyrus of the insula; LOS, lateral occipital sulcus; MedFG, medial frontal gyrus; MidFG, mid-frontal gyrus, MidTP, middle temporal gyrus; PCL, paracentral lobule; PHG, parahippocampal gyrus; POS, parieto- occipital sulcus; PoCG, postcentral gyrus, PoCS, postcentral sulcus; PreCG, precentral gyrus; PreCun, precuneus; PTO, parietal/temporal/occipital point; SF, Sylvian fissure; SFG, superior frontal gyrus; SMG, supramarginal gyrus; SPL, superior parietal lobule; TOS, transverse occipital sulcus. See http:// www.ebire.org/hcnlab/cortical -mapping for details. AC LO MT V3a IP L LO MT V3a IP L Methods. The cortex was segmented with FreeSurfer (Fischl, Sereno, Tootell and Dale, 1999) to obtain the gray/white boundary (left, yellow). The cortex was then inflated (shown for the left hemisphere of one subject) and colored to show local curvature values (green = gyrus, red = sulcus) at each point. Each hemisphere was further inflated into a sphere and aligned with anatomical templates of the same hemisphere using FreeSurfer and projected using a Mollweide equal-area projection. Because we were primarily interested in auditory cortex (dashed box) we chose a projection where Heschl’s gyrus lay near the equator to minimize distortion. CORTICAL INFLATION AND ALIGNMENT 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 V isual A ttention V isualonly Tim e (s) V isual A ttention Bim odal A uditory A ttention Bim odal A uditoryA ttention A uditory only Interm odalA ttention B lock D esign 225 900 3600 H z LEFT BINAURAL R IGH T 90 dB 70 dB Modeling human auditory cortical fields (ACFs). Kaas et al’s (2000) model of primate ACFs can projected onto areas showing auditory activations in the human brain. Apparent tonotopic extrema (e.g., mesial-lateral HG) may reflect summed activations from adjacent ACFs with similar frequency sensitivity. Regional differences in feature processing are evident in population responses from different cortical regions. High Intensit y Attentio n AC AC Contra Binaur al Ipsi All SPARSE CONT SOUND LOCATION EFFECTS Activations elicited by nonattended tone patterns presented contralaterally (red), binaurally (green) and ipsilaterally (blue) to the hemisphere shown. Scale proportional to response magnitude in each images (range (0.2-0.5%, minimum, 0.6-1.2% maximum). LEFT RIGHT Attenti on Intens ity SPARSE CONT Differences between 90 dB and 70 dB SPL signals (green) and between auditory and visual attention conditions (red). ATTENTION AND INTENSITY EFFECTS LEFT RIGHT LEFT RIGHT 225Hz 900 Hz 3600 Hz TONE FREQUENCY Activations to nonattended tones elicited by the three different tone frequencies during sparse sampling experiments. The results have been averaged over subjects (7), replications (3), location (left, right, binaural) and intensities (70 or 90 dB SPL). INTERSUBJECT VARIABILITY S2 S3 S13 S10 S12 S14 HG HG HG HG HG HG Intersubject variability in sound-evoked activations (scale 0.2-1.0%) elicited by nonattended sounds imaged with sparse sampling. Activations reproduced precisely over different days. In some subjects, high-amplitude “hot spots” (e.g., S3, S10) are likely to reflect venous anatomy and show limited feature specificity. 225 Hz 900 Hz 3.6 kHz All MT SPARSE CONT LEFT HEMISPHERE RIGHT HEMISPHERE FREQUENCY Auditory Cortex Heschl’s gyrus Heschl’s gyrus
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FUNCTIONAL SPECIALIZATION OF HUMAN AUDITORY CORTICAL FIELDS G. C. Stecker 1,2 , I. Liao 1 , T.J.Herron 1 , X.Kang 1 , E.W.Yund 1 , T. J. Rinne 1,3 , D.L.Woods 1 * - PowerPoint PPT Presentation
Transcript of FUNCTIONAL SPECIALIZATION OF HUMAN AUDITORY CORTICAL FIELDS
FUNCTIONAL SPECIALIZATION OF HUMAN AUDITORY CORTICAL FIELDS
G. C. Stecker1,2, I. Liao1, T.J.Herron1, X.Kang1, E.W.Yund1, T. J. Rinne1,3, D.L.Woods1* 1. HCNLAB, Neurology, UC Davis and VANCHCS, Martínez, CA. 2. Speech and Hearing Sciences, Univ. of Washington,
Seattle, WA, 3. Dept. of Psychology, Univ. of Helsinki, Helsinki, Finland 282.14
INTRODUCTION. We examined fMRI BOLD activations in auditory cortex using cortical surface mapping techniques to examine the influence of sound frequency, location, and intensity and attention on activation maps.
• Identical experiments were performed using continuous an
sparse sampling imaging parameters to examine the effects of scanner-generated masking noise.
• Alterations in activation patterns as a consequence of tone frequency, location, and intensity were examined during difficult visual attention conditions to control for the potential differences in the attention-attracting properties of different stimuli.
• Repeated studies were performed in each subject with the goal of visualizing the individual patterns of auditory cortical fields (ACF) organization.
• The results were analyzed using surface-based tools that provide improved precision in comparing with 3D analyses and that permit the visualization of activation patterns
References. Fischl, B., Sereno, M. I., Tootell, R. B., and Dale, A. M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Map., 1999, 8: 272-84.Kang, X., Bertrand., 0., Alho, K., Herron, T., Yund, E. W., and Woods, D. L. Local landmark-based mapping of human auditory cortex . NeuroImage, 2004. 22(4): p. 1657-1670.Kaas, J. H. and T. A. Hackett (2000). "Subdivisions of auditory cortex and processing streams in primates." Proc Natl Acad Sci U S A 97(22): 11793-9.Petkov, C.I., Kang, X.J., Alho, K., Bertrand, O. Yund, E.W. and Woods, D.L. Attentional modulation of human auditory cortex. Nature Neuroscience 2004. 7(6): p. 658-663.
SEMI-RANDOM BLOCK DESIGN. Stimuli were presented in 23.2s blocks. On 25% of the visual attention blocks, visual stimuli were presented alone and on 25% of the auditory attention blocks, auditory stimuli were presented alone. On the remaining blocks, visual and auditory stimuli were presented concurrently and subjects attended to either the visual stimuli or the tones. Auditory and visual conditions were randomly selected (with the constraint that auditory and visual attention conditions alternated) and paired for each experiment using Presentation™.
IMAGING. Whole brain (29-slices, 92x92 voxels, 4-mm thickness, 1-mm gap) echo-planar images (TR=2.9s or 11.6s, TE = 40 ms) were obtained. Seven subjects were studied. Each participated on six experiments on separate days three with sparse and three with continuous sampling. Each experiment lasted approximately 75 min.
BEHAVIOR. Hits rates averaged 54.7% (mean RT 670 ms) in visual attention conditions and 44.0/^% (mean RT 450 ms) in auditory attention conditions. Mean RTs to auditory targets slowed during continuous sampling, but no significant changes were seen in accuracy. Accuracy was enhanced and mean RTs shorter for louder targets.
CONCLUSIONS.1. Different features are differentially processed in different regions of auditory cortex.
2. Multiple tonotopic regions are evident in population averages, but smaller discrete regions seen in individual subjects.
3. Individual subjects show reliable but distinct activation patterns with incomplete sampling of the auditory cortical surface. This differences likely reflect variations in venous anatomy, and complicate inferences about ACF organization.
4. Attention does not merely enhance responses similar to increase loudness but recruits processing in additional cortical regions.
STIMULI AND TASKS. Subjects performed a one-back matching task, attending to the auditory or visual modality in alternating 23.2s blocks. Auditory stimuli were three-tone patterns (tone durations 250 ms, 10 ms rise/fall, total duration 750 ms) presented once every 1.5 s. Tone intensities were set at 70 or 90 dB SPL in different blocks and tones were presented over broadband masking noise (70 dB SPL). Each tone pattern contained three tones different equally spaced over a one-half octave range that was centered at 225, 900 or 3600 Hz in different blocks. Visual stimuli were faces or words in different blocks. Visual stimuli were presented at central fixation for 700 ms every 1.5 s. During visual attention conditions subjects performed a one-back matching task, identifying facial identity (across expressions) or word category.
Mollweide Projection of Cortical structure. Averaged over 62 subjects (124 hemispheres). Hemisphere alignment based on surface structure is more precise than volumetric co-registration (Kang et al, 2004). Here, the precision of alignment is reflected in the clarity of sulcal structure. Lobes are coded by color.
Anatomical Structures (white labels): AG, angular gyrus; CC, corpus callosum; CG, cingulate gyrus; CalcS, calcarine sulcus; ColS, collateral sulcus; Cun, cuneate; CS, central sulcus; FG, fusiform gyrus; HG, Heschl’s gyrus, IFG, inferior frontal gyrus; IPL, inferior parietal lobule; IPS, intraparietal sulcus; ITG, inferior temporal gyrus; ITS, inferior temporal sulcus; LG, lingual gyrus; LGofin, long gyrus of the insula; LOS, lateral occipital sulcus; MedFG, medial frontal gyrus; MidFG, mid-frontal gyrus, MidTP, middle temporal gyrus; PCL, paracentral lobule; PHG, parahippocampal gyrus; POS, parieto-occipital sulcus; PoCG, postcentral gyrus, PoCS, postcentral sulcus; PreCG, precentral gyrus; PreCun, precuneus; PTO, parietal/temporal/occipital point; SF, Sylvian fissure; SFG, superior frontal gyrus; SMG, supramarginal gyrus; SPL, superior parietal lobule; TOS, transverse occipital sulcus. See http://www.ebire.org/hcnlab/cortical-mapping for details.
AC
LOMT
V3a
IPL
LOMT
V3a
IPL
Methods. The cortex was segmented with FreeSurfer (Fischl, Sereno, Tootell and Dale, 1999) to obtain the gray/white boundary (left, yellow). The cortex was then inflated (shown for the left hemisphere of one subject) and colored to show local curvature values (green = gyrus, red = sulcus) at each point. Each hemisphere was further inflated into a sphere and aligned with anatomical templates of the same hemisphere using FreeSurfer and projected using a Mollweide equal-area projection. Because we were primarily interested in auditory cortex (dashed box) we chose a projection where Heschl’s gyrus lay near the equator to minimize distortion.
CORTICAL INFLATION AND ALIGNMENT
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300
Visual AttentionVisual only
Time (s)Visual AttentionBimodal
Auditory AttentionBimodal
Auditory AttentionAuditory only
Intermodal Attention Block Design
225 900 3600 HzLEFT BINAURAL RIGHT 90 dB 70 dB
Modeling human auditory cortical fields (ACFs). Kaas et al’s (2000) model of primate ACFs can projected onto areas showing auditory activations in the human brain. Apparent tonotopic extrema (e.g., mesial-lateral HG) may reflect summed activations from adjacent ACFs with similar frequency sensitivity. Regional differences in feature processing are evident in population responses from different cortical regions.
High Intensity
Attention
AC AC
Contra
Binaural
Ipsi
All
SP
AR
SE
CO
NT
SOUND LOCATION EFFECTS
Activations elicited by nonattended tone patterns presented contralaterally (red), binaurally (green) and ipsilaterally (blue) to the hemisphere shown. Scale proportional to response magnitude in each images (range (0.2-0.5%, minimum, 0.6-1.2% maximum).
LEFT RIGHT
Attention
Intensity
SP
AR
SE
CO
NT
Differences between 90 dB and 70 dB SPL signals (green) and between auditory and visual attention conditions (red).
ATTENTION AND INTENSITY EFFECTSLEFT RIGHT
LE
FT
RIG
HT
225Hz 900 Hz 3600 Hz TONE FREQUENCY
Activations to nonattended tones elicited by the three different tone frequencies during sparse sampling experiments. The results have been averaged over subjects (7), replications (3), location (left, right, binaural) and intensities (70 or 90 dB SPL).
INTERSUBJECT VARIABILITY
S2 S3 S13
S10 S12 S14
HG
HGHG
HGHG
HG
Intersubject variability in sound-evoked activations (scale 0.2-1.0%) elicited by nonattended sounds imaged with sparse sampling. Activations reproduced precisely over different days. In some subjects, high-amplitude “hot spots” (e.g., S3, S10) are likely to reflect venous anatomy and show limited feature specificity.
225 Hz
900 Hz
3.6 kHz
All
MT
SP
AR
SE
CO
NT
LEFT HEMISPHERE RIGHT HEMISPHERE
FREQUENCY
Auditory Cortex
Heschl’s gyrusHeschl’s gyrus
