Functional properties of human auditory cortical fields

Abstract

While auditory cortex in non-human primates has been subdivided into multiple functionally specialized auditory cortical fields (ACFs), the boundaries and functional specialization of human ACFs have not been defined. In the current study, we evaluated whether a widely accepted primate model of auditory cortex could explain regional tuning properties of fMRI activations on the cortical surface to attended and non-attended tones of different frequency, location, and intensity. The limits of auditory cortex were defined by voxels that showed significant activations to non-attended sounds. Three centrally located fields with mirror-symmetric tonotopic organization were identified and assigned to the three core fields of the primate model while surrounding activations were assigned to belt fields following procedures similar to those used in macaque fMRI studies. The functional properties of core, medial belt, and lateral belt field groups were then analyzed. Field groups were distinguished by tonotopic organization, frequency selectivity, intensity sensitivity, contralaterality, binaural enhancement, attentional modulation, and hemispheric asymmetry. In general, core fields showed greater sensitivity to sound properties than did belt fields, while belt fields showed greater attentional modulation than core fields. Significant distinctions in intensity sensitivity and contralaterality were seen between adjacent core fields A1 and R, while multiple differences in tuning properties were evident at boundaries between adjacent core and belt fields. The reliable differences in functional properties between fields and field groups suggest that the basic primate pattern of auditory cortex organization is preserved in humans. A comparison of the sizes of functionally defined ACFs in humans and macaques reveals a significant relative expansion in human lateral belt fields implicated in the processing of speech.

Keywords: attention; cortical mapping; fMRI; primate; sound intensity; sound location; tones; tonotopy.

Figures

Figure 1

Stimuli were delivered in 23.2 s blocks according to a randomized factorial design with all factors in auditory blocks (bimodal and unimodal blocks, the modality attended, tone frequency, tone intensity, and tone location) varying in random order. UV = unimodal visual, BV = bimodal, visual attention, UA = unimodal auditory, BA = bimodal, auditory attention. Each subject received two counterbalanced sequences of 72 blocks during each of six functional imaging sessions performed on separate days, three with continuous image acquisition (TR = 2.9 s) and three with sparse image acquisition (TR = 10.6 s).

Figure 2

Cortical-surface analysis. The cortex from each hemisphere was segmented with FreeSurfer (Fischl et al., 1999), then inflated to a sphere, and aligned to a hemispherically unified coordinate system. The functional and anatomical data were then mapped onto a Mollweide equal-area projection after rotating the sphere so that the intersection of Heschls’ gyrus (HG) and the superior temporal gyrus (STG) lay at the map center with the STG aligned along the equator. Auditory activations during visual attention conditions are shown on the average cortical anatomy of the left hemispheres (gyri are light, sulci are dark). Activations to non-attended tones were largely restricted to the regions of auditory cortex surrounding HG while activations during auditory attention conditions had increased spatial extent. Activations within the rectangular grid were quantified. Color scale: F(1,8) = 4.5–28.0 (red to yellow).

Figure 3

Auditory cortical fields (ACFs). (A) Best-frequency map, showing best frequency at each voxel relative to the two other frequencies. Saturation codes the magnitude of frequency preference (range: 0.07–0.15% difference). Red = 3600 Hz, Green = 900 Hz., Blue = 225 Hz. ACFs (yellow lines) were assigned following the model of Kaas et al. (1999). Auditory core fields were identified by their mirror-symmetric tonotopic organization with surrounding belt fields divided at the boundaries between adjacent core ACFs. White lines indicate gyral boundaries. See text for ACF labels. (B) Model projected on average curvature map of the superior temporal plane (green = gyri, red = sulci), showing anatomical structures and grids used for quantification. CiS: circular sulcus; HG: Heschl's gyrus; HS: Heschl's sulcus; PT: planum temporale; STG: superior temporal gyrus; STS: superior temporal sulcus, LGI: long gyri of the insula.

Figure 4

Mean auditory activation magnitudes (averaged over all auditory conditions and both hemispheres) shown for each voxel in the grid. Color codes activation magnitude: Blue = 0.05–0.15%, Green = 0.15–0.40%, Red: 0.40–0.60%.

Figure 5

Tuning properties of human ACFs. (A) Frequency selectivity: best frequency vs. average of other two frequencies. Color codes bandwidth. Blue = 0.11–0.13, Green = 0.13–0.15, Red: 0.15–0.22. (B) Intensity sensitivity. Blue = 0.01–0.05, Green = 0.05–0.10, Red: 0.10–0.20. (C) Contralaterality. Blue = 0.01–0.05, Green = 0.05–0.10, Red: 0.10–0.20. (D) Binaurality tuning: Blue = 0.01–0.03, Green = 0.03–0.06, Red: 0.06–0.9. (E) Attention: Blue = 0.01–0.06, Green = 0.06–0.012, Red: 0.12–0.20. (F) Hemispheric asymmetry: Blue = 0.01–0.06, Green = 0.06–0.012, Red: 0.12–0.20. Black regions had values below the minimal threshold for each display. AI = anterior insula, PI = posterior insula.

Figure 6

Auditory cortical field functional gradients. Significant differences between adjacent fields are shown for T = tone-frequency selectivity, I = intensity sensitivity, C = contralaterality, B = binaural enhancement, A = attentional modulation, H = right-hemisphere asymmetry.