Binaural Interaction Revisited in the Cat Primary Auditory Cortex

Jones HG, Brown AD, Koka K, Thornton JL, Tollin DJ. Sound frequency-invariant neural coding of a frequency-dependent cue to sound source location. J Neurophysiol 114: 531-539, 2015. First published May 13, 2015; doi:10.1152/jn.00062.2015.-The centuryold duplex theory of sound localization posits that low-and highfrequency sounds are localized with two different acoustical cues, interaural time and level differences (ITDs and ILDs), respectively. While behavioral studies in humans and behavioral and neurophysiological studies in a variety of animal models have largely supported the duplex theory, behavioral sensitivity to ILD is curiously invariant across the audible spectrum. Here we demonstrate that auditory midbrain neurons in the chinchilla (Chinchilla lanigera) also encode ILDs in a frequency-invariant manner, efficiently representing the full range of acoustical ILDs experienced as a joint function of sound source frequency, azimuth, and distance. We further show, using Fisher information, that nominal "low-frequency" and "high-frequency" ILD-sensitive neural populations can discriminate ILD with similar acuity, yielding neural ILD discrimination thresholds for near-midline sources comparable to behavioral discrimination thresholds estimated for chinchillas. These findings thus suggest a revision to the duplex theory and reinforce ecological and efficiency principles that hold that neural systems have evolved to encode the spectrum of biologically relevant sensory signals to which they are naturally exposed. sound localization; interaural level difference; inferior colliculus; low-frequency neurons THE CAPACITY FOR SOUND LOCALIZATION is phylogenetically ubiquitous and basic to communication and environmental awareness in many species including humans. The century-old duplex theory of sound localization holds that low-frequency signals are localized on the basis of submillisecond interaural time differences (ITDs) whereas high-frequency signals are localized on the basis of interaural level differences (ILDs) attributable primarily to acoustic "shadowing" of the ear farther from the sound source by the head (Strutt 1907). While the magnitude of ITD cues depends almost exclusively on source azimuth and only slightly on frequency (e.g., Kuhn 1977;Kuwada et al. 2010), ILD cues (measured in the acoustic free field) are heavily frequency dependent (e.g., Feddersen et al. 1957;Koka et al. 2011). At low frequencies, for which ITD cues are most useful (Ͻ1-2 kHz, depending on species), ILDs (as measured in anechoic space) are generally small. ILDs gradually increase with frequency up to ϳ3-4 kHz (again depending on species), beyond which ILD magnitudes increase rapidly and are dramatically affected by source azimuth. Two parallel and anatomically separate neural pathways have evolved in the mammalian brain stem to encode ITD and ILD cues, with the neurons that comprise the associated nuclei (the medial and lateral superior olive, respectively) exhibiting lowand high-frequency biases consistent with the duplex theory...

Section: Comparison To Earlier Studies Of Neural Ild Codingmentioning

confidence: 62%

Sound frequency-invariant neural coding of a frequency-dependent cue to sound source location

Jones

Brown

Koka

et al. 2015

“…More than 90% of AI cells are sensitive to the interaction of level at the two ears (Kelly and Judge 1994;Semple and Kitzes 1993a;Zhang et al 2004). AI neurons respond to a wide range of binaural stimuli presented in isolation (Clarey et al 1994;Imig et al 1990;Irvine et al 1996;Nakamoto et al 2004;Semple and Kitzes 1993a,b;Zhang et al 2004).…”

Section: Introductionmentioning

confidence: 99%

“…AI neurons respond to a wide range of binaural stimuli presented in isolation (Clarey et al 1994;Imig et al 1990;Irvine et al 1996;Nakamoto et al 2004;Semple and Kitzes 1993a,b;Zhang et al 2004). Stimuli at either ear can be excitatory, inhibitory, or evoke a leveldependent combination of excitation and inhibition.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Temporal Nonlinearity During Recovery From Sequential Inhibition by Neurons in the Cat Primary Auditory Cortex

Nakamoto

Zhang²,

Kitzes³

2006

Self Cite

Nakamoto, Kyle T., Jiping Zhang, and Leonard M. Kitzes. Temporal nonlinearity during recovery from sequential inhibition by neurons in the cat primary auditory cortex. J Neurophysiol 95: 1897-1907, 2006. First published December 7, 2005 doi:10.1152/jn.00625.2005. Auditory stimuli occur most often in sequences rather than in isolation. It is therefore necessary to understand how responses to sounds occurring in sequences differ from responses to isolated sounds. Cells in primary auditory cortex (AI) respond to a large set of binaural stimuli when presented in isolation. The set of responses to such stimuli presented at one frequency comprises a level response area. A preceding binaural stimulus can reduce the size and magnitude of level response areas of AI cells. The present study focuses on the effects of the time interval between a preceding stimulus and the stimuli of a level response area in pentobarbital-anesthetized cats. After the offset of a preceding stimulus, the ability of AI cells to respond to succeeding stimuli varies dynamically in time. At short interstimulus intervals (ISI), a preceding stimulus can completely inhibit responses to succeeding stimuli. With increasing ISIs, AI cells respond first to binaural stimuli that evoke the largest responses in the control condition, i.e., not preceded by a stimulus. Recovery rate is nonlinear across the level response area; responses to these most-effective stimuli recover to 70% of control on average 187 ms before responses to other stimuli recover to 70% of their control sizes. During the tens to hundreds of milliseconds that a level response area is reduced in size and magnitude, the selectivity of AI cells is increased for stimuli that evoke the largest responses. This increased selectivity results from a temporal nonlinearity in the recovery of the level response area which protects responses to the most effective binaural stimuli. Thus in a sequence of effective stimuli, a given cell will respond selectively to only those stimuli that evoke a strong response when presented alone.

“…Although almost all previous studies regarding the influence of a preceding or ongoing stimulus used monaural stimulus parameters, the present study focused on binaural stimuli because the response of neurons in the primary auditory cortex (AI) are almost always (Ͼ90%) influenced by stimulation of both ears (Kelly and Judge 1994;Semple and Kitzes 1993a;Zhang et al 2004). Responses of cortical neurons to binaural stimuli (Reale and Brugge 2000), as well as neurons throughout most of the auditory neuroaxis (Faure et al 2003;Finlayson 1999;Finlayson and Adam 1997;Fitzpatrick et al 1999;Litovsky and Yin 1998b;Yin 1994), can be altered by a preceding sound in a frequency-, level-, and time-dependent manner.…”

Section: Introductionmentioning

confidence: 99%

Modulation of Level Response Areas and Stimulus Selectivity of Neurons in Cat Primary Auditory Cortex

Zhang

Nakamoto²,

Kitzes³

2005

Self Cite

Zhang, Jiping, Kyle T. Nakamoto, and Leonard M. Kitzes. Modulation of level response areas and stimulus selectivity of neurons in cat primary auditory cortex. J Neurophysiol 94: 2263-2274, 2005. First published May 25, 2005 10.1152/jn.01207.2004. Sounds commonly occur in sequences, such as in speech. It is therefore important to understand how the occurrence of one sound affects the response to a subsequent sound. We approached this question by determining how a conditioning stimulus alters the response areas of single neurons in the primary auditory cortex (AI) of barbiturate-anesthetized cats. The response areas consisted of responses to stimuli that varied in level at the two ears and delivered at the characteristic frequency of each cell. A binaural conditioning stimulus was then presented Ն50 ms before each of the stimuli comprising the level response area. An effective preceding stimulus alters the shape and severely reduces the size and response magnitude of the level response area. This ability of the preceding stimulus depends on its proximity in the level domain to the level response area, not on its absolute level or on the size of the response it evokes. Preceding stimuli evoke a nonlinear inhibition across the level response area that results in an increased selectivity of a cortical neuron for its preferred binaural stimuli. The selectivity of AI neurons during the processing of a stream of acoustic stimuli is likely to be restricted to a portion of their level response areas apparent in the tone-alone condition. Thus rather than being static, level response areas are fluid; they can vary greatly in extent, shape and response magnitude. The dynamic modulation of the level response area and level selectivity of AI neurons might be related to several tasks confronting the central auditory system. I N T R O D U C T I O NAs acoustic stimuli commonly occur in a temporal relation to other acoustic stimuli, it is important to understand how responses of cortical neurons vary during the processing of a stream of acoustic signals. Throughout the auditory neuroaxis, discharge rate as a function of monaural stimulus level (so called rate-level functions) have been shown to be displaced to higher stimulus levels when stimuli are presented either during or after a conditioning stimulus (Boettcher et