Neural Modulation Tuning Characteristics Scale to Efficiently Encode Natural Sound Statistics

Overview

Journal J Neurosci

Specialty Neurology

Date 2010 Nov 26

PMID 21106835

Citations 47

Authors

Francisco A Rodriguez

Chen Chen

Heather L Read

Monty A Escabi

Affiliations

Soon will be listed here.

Abstract

The efficient-coding hypothesis asserts that neural and perceptual sensitivity evolved to faithfully represent biologically relevant sensory signals. Here we characterized the spectrotemporal modulation statistics of several natural sound ensembles and examined how neurons encode these statistics in the central nucleus of the inferior colliculus (CNIC) of cats. We report that modulation-tuning in the CNIC is matched to equalize the modulation power of natural sounds. Specifically, natural sounds exhibited a tradeoff between spectral and temporal modulations, which manifests as 1/f modulation power spectrum (MPS). Neural tuning was highly overlapped with the natural sound MPS and neurons approximated proportional resolution filters where modulation bandwidths scaled with characteristic modulation frequencies, a behavior previously described in human psychoacoustics. We demonstrate that this neural scaling opposes the 1/f scaling of natural sounds and enhances the natural sound representation by equalizing their MPS. Modulation tuning in the CNIC may thus have evolved to represent natural sound modulations in a manner consistent with efficiency principles and the resulting characteristics likely underlie perceptual resolution.

Citing Articles

Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function.

Vazquez-Guerrero P, Tuladhar R, Psychalinos C, Elwakil A, Chacron M, Santamaria F Sci Rep. 2024; 14(1):5817.

PMID: 38461365 PMC: 10925066. DOI: 10.1038/s41598-024-55784-1.

Interference of mid-level sound statistics underlie human speech recognition sensitivity in natural noise.

Clonan A, Zhai X, Stevenson I, Escabi M bioRxiv. 2024; .

PMID: 38405870 PMC: 10888804. DOI: 10.1101/2024.02.13.579526.

Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures.

Peng F, Harper N, Mishra A, Auksztulewicz R, Schnupp J J Neurosci. 2024; 44(10).

PMID: 38267259 PMC: 10919253. DOI: 10.1523/JNEUROSCI.1115-23.2023.

Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions.

Tuckute G, Feather J, Boebinger D, McDermott J PLoS Biol. 2023; 21(12):e3002366.

PMID: 38091351 PMC: 10718467. DOI: 10.1371/journal.pbio.3002366.

Spectral-temporal processing of naturalistic sounds in monkeys and humans.

van der Willigen R, Versnel H, Van Opstal A J Neurophysiol. 2023; 131(1):38-63.

PMID: 37965933 PMC: 11305640. DOI: 10.1152/jn.00129.2023.

References

Ewert S, Dau T . Characterizing frequency selectivity for envelope fluctuations. J Acoust Soc Am. 2000; 108(3 Pt 1):1181-96. DOI: 10.1121/1.1288665. View

Harris K, Henze D, Csicsvari J, Hirase H, Buzsaki G . Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements. J Neurophysiol. 2000; 84(1):401-14. DOI: 10.1152/jn.2000.84.1.401. View

Smith E, Lewicki M . Efficient auditory coding. Nature. 2006; 439(7079):978-82. DOI: 10.1038/nature04485. View

Escabi M, Schreiner C . Nonlinear spectrotemporal sound analysis by neurons in the auditory midbrain. J Neurosci. 2002; 22(10):4114-31. PMC: 6757655. DOI: 20026325. View

Merzenich M, Reid M . Representation of the cochlea within the inferior colliculus of the cat. Brain Res. 1974; 77(3):397-415. DOI: 10.1016/0006-8993(74)90630-1. View

Dau T, Kollmeier B, Kohlrausch A . Modeling auditory processing of amplitude modulation. II. Spectral and temporal integration. J Acoust Soc Am. 1997; 102(5 Pt 1):2906-19. DOI: 10.1121/1.420345. View

Zheng Y, Escabi M . Distinct roles for onset and sustained activity in the neuronal code for temporal periodicity and acoustic envelope shape. J Neurosci. 2008; 28(52):14230-44. PMC: 2636849. DOI: 10.1523/JNEUROSCI.2882-08.2008. View

Ruderman , Bialek . Statistics of natural images: Scaling in the woods. Phys Rev Lett. 1994; 73(6):814-817. DOI: 10.1103/PhysRevLett.73.814. View

Lewicki M . Efficient coding of natural sounds. Nat Neurosci. 2002; 5(4):356-63. DOI: 10.1038/nn831. View

10.

Laughlin M, Van de Sande B, van der Heijden M, Joris P . Comparison of bandwidths in the inferior colliculus and the auditory nerve. I. Measurement using a spectrally manipulated stimulus. J Neurophysiol. 2007; 98(5):2566-79. DOI: 10.1152/jn.00595.2007. View

11.

Olshausen B, Field D . Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 1996; 381(6583):607-9. DOI: 10.1038/381607a0. View

12.

Viemeister N . Temporal modulation transfer functions based upon modulation thresholds. J Acoust Soc Am. 1979; 66(5):1364-80. DOI: 10.1121/1.383531. View

13.

Nelken I, Rotman Y, Bar Yosef O . Responses of auditory-cortex neurons to structural features of natural sounds. Nature. 1999; 397(6715):154-7. DOI: 10.1038/16456. View

14.

Elliott T, Theunissen F . The modulation transfer function for speech intelligibility. PLoS Comput Biol. 2009; 5(3):e1000302. PMC: 2639724. DOI: 10.1371/journal.pcbi.1000302. View

15.

Andoni S, Li N, Pollak G . Spectrotemporal receptive fields in the inferior colliculus revealing selectivity for spectral motion in conspecific vocalizations. J Neurosci. 2007; 27(18):4882-93. PMC: 6672083. DOI: 10.1523/JNEUROSCI.4342-06.2007. View

16.

Woolley S, Fremouw T, Hsu A, Theunissen F . Tuning for spectro-temporal modulations as a mechanism for auditory discrimination of natural sounds. Nat Neurosci. 2005; 8(10):1371-9. DOI: 10.1038/nn1536. View

17.

Rieke F, Bodnar D, Bialek W . Naturalistic stimuli increase the rate and efficiency of information transmission by primary auditory afferents. Proc Biol Sci. 1995; 262(1365):259-65. DOI: 10.1098/rspb.1995.0204. View

18.

Holmstrom L, Eeuwes L, Roberts P, Portfors C . Efficient encoding of vocalizations in the auditory midbrain. J Neurosci. 2010; 30(3):802-19. PMC: 6633079. DOI: 10.1523/JNEUROSCI.1964-09.2010. View

19.

Theunissen F, Sen K, Doupe A . Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds. J Neurosci. 2000; 20(6):2315-31. PMC: 6772498. View

20.

Pickles J . Psychophysical frequency resolution in the cat as determined by simultaneous masking and its relation to auditory-nerve resolution. J Acoust Soc Am. 1979; 66(6):1725-32. DOI: 10.1121/1.383645. View