Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Jan 30;33(5):1858-63.
doi: 10.1523/JNEUROSCI.4405-12.2013.

Tuning in to sound: frequency-selective attentional filter in human primary auditory cortex

Affiliations

Tuning in to sound: frequency-selective attentional filter in human primary auditory cortex

Sandra Da Costa et al. J Neurosci. .

Abstract

Cocktail parties, busy streets, and other noisy environments pose a difficult challenge to the auditory system: how to focus attention on selected sounds while ignoring others? Neurons of primary auditory cortex, many of which are sharply tuned to sound frequency, could help solve this problem by filtering selected sound information based on frequency-content. To investigate whether this occurs, we used high-resolution fMRI at 7 tesla to map the fine-scale frequency-tuning (1.5 mm isotropic resolution) of primary auditory areas A1 and R in six human participants. Then, in a selective attention experiment, participants heard low (250 Hz)- and high (4000 Hz)-frequency streams of tones presented at the same time (dual-stream) and were instructed to focus attention onto one stream versus the other, switching back and forth every 30 s. Attention to low-frequency tones enhanced neural responses within low-frequency-tuned voxels relative to high, and when attention switched the pattern quickly reversed. Thus, like a radio, human primary auditory cortex is able to tune into attended frequency channels and can switch channels on demand.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
A, Tonotopic mapping was used to indentify primary auditory cortex in each subject individually (n = 6). In each hemisphere (n = 12), two mirror-symmetric gradients (high-to-low and low-to-high) corresponding the primary areas hA1 and hR were manually outlined on the medial two-thirds of Heschl's gyrus (one same right hemisphere shown). Each voxel within the selected region was labeled according to its preferred frequency between 88 and 8000 Hz in half-octave steps. B, Next, in the selective attention (dual-stream) experiment, low (250 Hz)- and high (4000 Hz)-frequency patterned tonal streams were presented concurrently to different ears. Subjects were cued to attend to only one stream at a time, alternating the attended stream every 30 s (blocks of attend high vs attend low). A 2-IFC experiment was used to focus attention on the cue stream (see Materials and Methods). The stimulus itself did not change across blocks, only the attentional state. Ear-side was counterbalanced across runs allowing the comparison of effects of frequency-specific attention (attend high vs attend low collapsed across sides) to effects of spatial-selective attention (attend contralateral vs attend ipsilateral collapsed across frequencies).
Figure 2.
Figure 2.
A, Mean fMRI time courses during the dual-stream selective attention experiment (across all subjects and hemispheres, n = 12) smoothed with a Gaussian (half-width = 8 s). Time courses were extracted from all voxels of primary auditory cortex labeled as preferring 250 Hz (light gray) and 4000 Hz (dark gray) in each subject and hemisphere based on individual subject tonotopic mappings. The responses of 4000 Hz-preferring voxels increased during attend high blocks and decreased during attend low blocks, and vice versa for 250 Hz-preferring voxels. B, Frequency attention. Bars show the mean difference in response between attend high and attend low blocks across all voxel bins in primary auditory cortex with all frequency preferences. C, Spatial attention. Bars show the mean difference in response between attend contralateral and attend ipsilateral blocks. D, Modulation in single-stream experiment. Bars show the mean difference in response between high and low blocks measured in separate scans in which the stimulus physically alternated between high-only and low-only streams. Note change in y-axis scale. Comparing the amplitudes in B and C, feature-selective attention outweighed effects of spatial attention by a factor of ∼5. Comparing the amplitudes of B and D, frequency attention modulation was 18.6% as large as stimulus-driven modulation in 250 Hz voxels and 56.2% as large in 4000 Hz voxels, a robust modulatory effect. Error bars show SEM across all subjects and hemispheres, n = 12.

Similar articles

Cited by

References

    1. Ahveninen J, Hämäläinen M, Jääskeläinen IP, Ahlfors SP, Huang S, Lin FH, Raij T, Sams M, Vasios CE, Belliveau JW. Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise. Proc Natl Acad Sci U S A. 2011;108:4182–4187. - PMC - PubMed
    1. Atiani S, Elhilali M, David SV, Fritz JB, Shamma SA. Task difficulty and performance induce diverse adaptive patterns in gain and shape of primary auditory cortical receptive field. Neuron. 2009;61:467–480. - PMC - PubMed
    1. Bartlett EL, Sadagopan S, Wang X. Fine frequency tuning in monkey auditory cortex and thalamus. J Neurophysiol. 2011;106:849–859. - PMC - PubMed
    1. Bidet-Caulet A, Fischer C, Besle J, Aguera PE, Giard MH, Bertrand O. Effects of selective attention on the electrophysiological representation of concurrent sounds in the human auditory cortex. J Neurosci. 2007;27:9252–9261. - PMC - PubMed
    1. Bitterman Y, Mukamel R, Malach R, Fried I, Nelken I. Ultra-fine frequency tuning revealed in single neurons of human auditory cortex. Nature. 2008;451:197–201. - PMC - PubMed

Publication types

LinkOut - more resources