Binaural Interaction Revisited in the Cat Primary Auditory Cortex

2004 ◽  
Vol 91 (1) ◽  
pp. 101-117 ◽  
Author(s):  
Jiping Zhang ◽  
Kyle T. Nakamoto ◽  
Leonard M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Large Population ◽  
Primary Auditory Cortex ◽  
Lower Proportion ◽  
Response Functions ◽  
Interaction Type ◽  
Binaural Interaction ◽  
The Matrix ◽  
Interaural Level Differences ◽  
Tonal Stimuli

The binaural interactions of neurons were studied in the primary auditory cortex (AI) of barbiturate-anesthetized cats with a matrix of binaural tonal stimuli varying in both interaural level differences (ILD) and average binaural level (ABL). The purpose of this study was to determine: 1) the distribution of preferred binaural combinations (PBCs) of a large population of neurons and its relationships with binaural interactions and binaural monotonicity; 2) whether monaural responses are predictive of binaural responses; and 3) whether there is a restricted set of representative binaural stimulus configurations that could effectively classify the binaural interactions. Binaural interactions were often diverse in the matrix and dependent on both ABL and ILD. Compared with previous studies, a higher proportion of mixed binaural interaction type and a lower proportion of EO/I type were found. No monaural neurons were found. Binaural responses often differed from monaural responses in the number of spikes and/or the form of the response functions. The PBCs of the majority of EO and PB neurons were in the contralateral field and midline, respectively. However, the PBCs of EE units were evenly distributed across the contralateral and ipsilateral fields. The majority of the nonmonotonic neurons responded most strongly to lower ABLs, whereas the majority of monotonic neurons responded most strongly to higher ABLs. This study demonstrated that in AI a restricted set of binaural stimulus configurations is not sufficient to reveal the binaural responses properties. Also, monaural responses are not predictive of binaural responses.

Representation of cochlea within primary auditory cortex in the cat

1975 ◽  
Vol 38 (2) ◽  
pp. 231-249 ◽  
Author(s):  
M. M. Merzenich ◽  
P. L. Knight ◽  
G. L. Roth
Keyword(s):  
Auditory Cortex ◽  
Frequency Band ◽  
Constant Width ◽  
Primary Auditory Cortex ◽  
Cortical Surface ◽  
Cortical Layers ◽  
Secondary Field ◽  
Mapping Techniques ◽  
Cochlear Partition ◽  
Tonal Stimuli

The representation of sound frequency (and of the cochlear partition) within primary auditory cortex has been investigated with use of microelectrode-mapping techniques in a series of 25 anesthetized cats. Among the results were the following: 1) Within vertical penetrations into AI, best frequency and remarkably constant for successively studied neurons across the active middle and deep cortical layers. 2) There is an orderly representation of frequency (and of represented cochlear place) within AI. Frequency is rerepresented across the mediolateral dimension of the field. On an axis perpendicular to this plane of rerepresentation, best-frequency (represented cochlear place) changes as a simple function of cortical location. 3) Any given frequency band (or sector of the cochlear partition) is represented across a belt of cortex of nearly constant width that runs on a nearly straight axis across AI. 4) There is a disproportionately large cortical surface representation of the highest-frequency octaves (basal cochlea) within AI. 5) The primary and secondary field locations were somewhat variable, when referenced to cortical surface landmarks. 6) Data from long penetrations passing down the rostral bank of the posterior ectosylvian sulcus were consistent with the existence of a vertical unit of organization in AI, akin to cortical columns described in primary visual and somatosensory cortex. 7) Responses to tonal stimuli were encountered in fields dorsocaudal, caudal, ventral, and rostral to AI. There is an orderly representation of the cochlea within the field rostal to AI, with a reversal in best frequencies across its border with AI. 8) Physiological definitions of AI boundaries are consistent with their cytoarchitectonic definition. Some of the implications of these findings are discussed.

Sensitivity to interaural intensity differences of neurons in primary auditory cortex of the cat. I. types of sensitivity and effects of variations in sound pressure level

1996 ◽  
Vol 75 (1) ◽  
pp. 75-96 ◽  
Author(s):  
D. R. Irvine ◽  
R. Rajan ◽  
L. M. Aitkin
Keyword(s):  
Auditory Cortex ◽  
High Frequency ◽  
Primary Auditory Cortex ◽  
Mirror Image ◽  
Sensitivity Function ◽  
Maximum Response ◽  
Binaural Interaction ◽  
Sensitivity Functions ◽  
Monaural Stimulation ◽  
Stimulation Of

1. Interaural intensity differences (IIDs) provide the major cue to the azimuthal location of high-frequency narrowband sounds. In recent studies of the azimuthal sensitivity of high-frequency neurons in the primary auditory cortex (field AI) of the cat, a number of different types of azimuthal sensitivity have been described and the azimuthal sensitivity of many neurons was found to vary as a function of changes in stimulus intensity. The extent to which the shape and the intensity dependence of the azimuthal sensitivity of AI neurons reflects features of their IID sensitivity was investigated by obtaining data on IID sensitivity from a large sample of neurons with a characteristic frequency (CF) > 5.5 kHz in AI of anesthetized cats. IID sensitivity functions were classified in a manner that facilitated comparison with previously obtained data on azimuthal sensitivity, and the effects of changes in the base intensity at which IIDs were introduced were examined. 2. IID sensitivity functions for CF tonal stimuli were obtained at one or more intensities for a total of 294 neurons, in most cases by a method of generating IIDs that kept the average binaural intensity (ABI) of the stimuli at the two ears constant. In the standard ABI range at which a function was obtained for each unit, five types of IID sensitivity were distinguished. Contra-max neurons (50% of the sample) had maximum response (a peak or a plateau) at IIDs corresponding to contralateral azimuths, whereas ipsi-max neurons (17%) had the mirror-image form of sensitivity. Near-zero-max neurons (18%) had a clearly defined maximum response (peak) in the range of +/- 10 dB IID, whereas a small group of tough neurons (2%) had a restricted range of minimal responsiveness with near-maximal responses at IIDs on either side. A final 18% of AI neurons were classified as insensitive to IIDs. The proportions of neurons exhibiting the various types of sensitivity corresponded closely to the proportions found to exhibit corresponding types of azimuthal sensitivity in a previous study. 3. There was a strong correlation between a neuron's binaural interaction characteristics and the form of its IID sensitivity function. Thus, neurons excited by monaural stimulation of only one ear but with either inhibitory, facilitatory, or mixed facilitatory-inhibitory effects of stimulation of the other ear had predominantly contra-max IID sensitivity (if contralateral monaural stimulation was excitatory) or ipsi-max sensitivity (if ipsilateral monaural stimulation was excitatory). Neurons driven weakly or not at all by monaural stimulation but facilitated binaurally almost all exhibited near-zero-max IID sensitivity. The exception to this tight association between binaural input and IID sensitivity was provided by neurons excited by monaural stimulation of either ear (EE neurons). Although EE neurons have frequently been considered to be insensitive to IIDs, our data were in agreement with two recent reports indicating that they can exhibit various forms of IID sensitivity: only 23 of 75 EE neurons were classified as insensitive and the remainder exhibited diverse types of sensitivity. 4. IID sensitivity was examined at two or more intensities (3-5 in most cases) for 84 neurons. The form of the IID sensitivity function (defined in terms of both shape and position along the IID axis) was invariant with changes in ABI for only a small proportion of IID-sensitive neurons (approximately 15% if a strict criterion of invariance was employed), and for many of these neurons the spike counts associated with a given IID varied with ABI, particularly at near-threshold levels. When the patterns of variation in the form of IID sensitivity produced by changes in ABI were classified in a manner equivalent to that used previously to classify the effects of intensity on azimuthal sensitivity, there was a close correspondence between the effects of intensity on corresponding types of azimuthal and IID sensitivity

Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex

2003 ◽  
Vol 90 (4) ◽  
pp. 2660-2675 ◽  
Author(s):  
Jennifer F. Linden ◽  
Robert C. Liu ◽  
Maneesh Sahani ◽  
Christoph E. Schreiner ◽  
Michael M. Merzenich
Keyword(s):  
Receptive Field ◽  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Dynamic Stimuli ◽  
Tuning Curves ◽  
Response Characteristics ◽  
Spectrotemporal Receptive Fields ◽  
Auditory Field ◽  
Tonal Stimuli

The mouse is a promising model system for auditory cortex research because of the powerful genetic tools available for manipulating its neural circuitry. Previous studies have identified two tonotopic auditory areas in the mouse—primary auditory cortex (AI) and anterior auditory field (AAF)— but auditory receptive fields in these areas have not yet been described. To establish a foundation for investigating auditory cortical circuitry and plasticity in the mouse, we characterized receptive-field structure in AI and AAF of anesthetized mice using spectrally complex and temporally dynamic stimuli as well as simple tonal stimuli. Spectrotemporal receptive fields (STRFs) were derived from extracellularly recorded responses to complex stimuli, and frequency-intensity tuning curves were constructed from responses to simple tonal stimuli. Both analyses revealed temporal differences between AI and AAF responses: peak latencies and receptive-field durations for STRFs and first-spike latencies for responses to tone bursts were significantly longer in AI than in AAF. Spectral properties of AI and AAF receptive fields were more similar, although STRF bandwidths were slightly broader in AI than in AAF. Finally, in both AI and AAF, a substantial minority of STRFs were spectrotemporally inseparable. The spectrotemporal interaction typically appeared in the form of clearly disjoint excitatory and inhibitory subfields or an obvious spectrotemporal slant in the STRF. These data provide the first detailed description of auditory receptive fields in the mouse and suggest that although neurons in areas AI and AAF share many response characteristics, area AAF may be specialized for faster temporal processing.

Response Patterns Along an Isofrequency Contour in Cat Primary Auditory Cortex (AI) to Stimuli Varying in Average and Interaural Levels

2004 ◽  
Vol 91 (1) ◽  
pp. 118-135 ◽  
Author(s):  
Kyle T. Nakamoto ◽  
Jiping Zhang ◽  
Leonard M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Characteristic Frequency ◽  
Primary Auditory Cortex ◽  
Sound Level ◽  
Response Patterns ◽  
Single Neurons ◽  
Sound Location ◽  
Interaural Level Differences

The topographical response of a portion of an isofrequency contour in primary cat auditory cortex (AI) to a series of monaural and binaural stimuli was studied. Responses of single neurons to monaural and a matrix of binaural characteristic frequency tones, varying in average binaural level (ABL) and interaural level differences (ILD), were recorded. The topography of responses to monaural and binaural stimuli was appreciably different. Patches of cells that responded monotonically to increments in ABL alternated with patches that responded nonmonotonically to ABL. The patches were between 0.4 and 1 mm in length along an isofrequency contour. Differences were found among monotonic patches and among nonmonotonic patches. Topographically, activated and silent populations of neurons varied with both changes in ILD and changes in ABL, suggesting that the area of responsive units may underlie the coding of sound level and sound location.

scholarly journals Comparison of responses in the anterior and primary auditory fields of the ferret cortex

1995 ◽  
Vol 73 (4) ◽  
pp. 1513-1523 ◽  
Author(s):  
N. Kowalski ◽  
H. Versnel ◽  
S. A. Shamma
Keyword(s):  
Auditory Cortex ◽  
Weighted Average ◽  
Primary Auditory Cortex ◽  
Directional Sensitivity ◽  
High Frequencies ◽  
Electrophysiological Responses ◽  
Range Rate ◽  
Auditory Field ◽  
The Relationship ◽  
Tonal Stimuli

1. Characteristics of an anterior auditory field (AAF) in the ferret auditory cortex are described in terms of its electrophysiological responses to tonal stimuli and compared with those of primary auditory cortex (AI). Ferrets were barbiturate-anesthetized and tungsten microelectrodes were used to record single-unit responses from both AI and AAF fields. Units in both areas were presented with the same stimulus paradigms and their responses analyzed in the same manner so that a direct comparison of responses was possible. 2. The AAF is located dorsal and rostral to AI on the ectosylvian gyrus and extends into the suprasylvian sulcus rostral to AI. The tonotopicity is organized with high frequencies at the top of the sulcus bordering the high-frequency area of AI, then reversing with lower BFs extending down into the sulcus. AAF contained single units that responded to a frequency range of 0.3-30 kHz. 3. Stimuli consisted of single-tone bursts, two-tone bursts and frequency-modulated (FM) stimuli swept in both directions at various rates. Best frequency (BF) range, rate-level functions at BF, FM directional sensitivity, and variation in asymmetries of response areas were all comparable characteristics between AAF and AI. Responses in both areas were primarily phasic. 4. The characteristics that were different between the two cortical areas were: latency to tone onset, excitatory bandwidth 20 dB above threshold (BW20), and preferred FM rate as parameterized with the centroid (a weighted average of spike counts). The mean latency of AAF units was shorter than in AI (AAF: 16.8 ms, AI: 19.4 ms). BW20 measurements in AAF were typically twice as large as those found in AI (AAF: 2.5 octaves, AI 1.3 octaves). The AI centroid population had a significantly larger standard deviation than the AAF centroid population. 5. We examined the relationship between centroid and BW20 to see whether wider bandwidths were a factor in a unit's ability to detect fast sweeps. There was significant (P < 0.05) linear correlation in AAF but not in AI. In both fields the variance of the centroid population decreased with increasing BW20. BW20 decreased as BF increased for units in both auditory fields.

Effects of ear plugging on single-unit azimuth sensitivity in cat primary auditory cortex. II. Azimuth tuning dependent upon binaural stimulation

1994 ◽  
Vol 71 (6) ◽  
pp. 2194-2216 ◽  
Author(s):  
F. K. Samson ◽  
P. Barone ◽  
J. C. Clarey ◽  
T. J. Imig
Keyword(s):  
Auditory Cortex ◽  
Single Unit ◽  
Free Field ◽  
Primary Auditory Cortex ◽  
Excitatory Input ◽  
Spectral Cues ◽  
Binaural Stimulation ◽  
Monaural Stimulation ◽  
Monaural Spectral Cues ◽  
Interaural Level Differences

1. Single-unit recordings were carried out in primary auditory cortex (AI) of barbiturate-anesthetized cats. Observations were based on a sample of 131 high-best-frequency (> 5 kHz), azimuth-sensitive neurons. These were identified by their responses to a set of noise bursts, presented in the free field, that varied in azimuth and sound-pressure level (SPL). Each azimuth-sensitive neuron responded well to some levels at certain azimuths, but did not respond well to any level at other azimuths. 2. Unilateral ear plugging was used to infer each neuron's response to monaural stimulation. Ear plugs, produced by injecting a plastic ear mold compound into the external ear, attenuated sound reaching the tympanic membrane by 25–70 dB. The azimuth tuning of a large proportion of the sample (62/131), referred to as binaural directional (BD), was completely dependent upon binaural stimulation because with one ear plugged, these cells were insensitive to azimuth (either responded well at all azimuths or failed to respond at any azimuth) or in a few cases exhibited striking changes in location of azimuth function peaks. This report describes patterns of monaural responses and binaural interactions exhibited by BD neurons and relates them to each cell's azimuth and level tuning. The response of BD cells to ear plugging is consistent with the hypothesis that they derive azimuth tuning from interaural level differences present in noise bursts. Another component of the sample consisted of monaural directional (27/131) cells that derived azimuth tuning in part or entirely from monaural spectral cues. Cells in the remaining portion of the sample (42/131) responded too unreliably to permit specific conclusions. 3. Binaural interactions were inferred by statistical comparison of a cell's responses to monaural (unilateral plug) and binaural (no plug) stimulation. A larger binaural response than either monaural response was taken as evidence for binaural facilitation. A smaller binaural than monaural response was taken as evidence for binaural inhibition. Binaural facilitation was exhibited by 65% (40/62) of the BD sample (facilitatory cells). Many of these exhibited mixed interactions, i.e., binaural facilitation occurred in response to some azimuth-level combinations, and binaural inhibition to others. Binaural inhibition in the absence of binaural facilitation occurred in 35% (22/62) of the BD sample, a majority of which were EI cells, so called because they received excitatory (E) input from one ear (excitatory ear) and inhibitory (I) input from the other (inhibitory ear). One cell that exhibited binaural inhibition received excitatory input from each ear.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Analysis of dynamic spectra in ferret primary auditory cortex. I. Characteristics of single-unit responses to moving ripple spectra

1996 ◽  
Vol 76 (5) ◽  
pp. 3503-3523 ◽  
Author(s):  
N. Kowalski ◽  
D. A. Depireux ◽  
S. A. Shamma
Keyword(s):  
Auditory Cortex ◽  
Impulse Response ◽  
Transfer Functions ◽  
Primary Auditory Cortex ◽  
Angular Frequency ◽  
Spectral Envelope ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Cortical Cells ◽  
Complex Sounds

1. Auditory stimuli referred to as moving ripples are used to characterize the responses of both single and multiple units in the ferret primary auditory cortex. Moving ripples are broadband complex sounds with a sinusoidal spectral profile that drift along the logarithmic frequency axis at a constant velocity. 2. Neuronal responses to moving ripples are locked to the phase of the ripple, i.e., they exhibit the same periodicity as that of the moving ripple profile. Neural responses are characterized as a function of ripple velocity (temporal property) and ripple frequency (spectral property). Transfer functions describing the response to these temporal and spectral modulations are constructed. Temporal transfer functions are inverse Fourier transformed to obtain impulse response functions that reflect the cell's temporal characteristics. Ripple transfer functions are inverse Fourier transformed to obtain the response field, a measure analogous to the cell's response area. These operations assume linearity in the cell's response to moving ripples. 3. Transfer functions and other response functions are shown to be fairly independent on the overall level or depth of modulation of the ripple stimuli. Only downward moving ripples were used in this study. 4. The temporal and ripple transfer functions are found to be separable, in that their shapes remain unchanged for different test parameters. Thus ripple transfer functions and response fields remain statistically similar in shape (to within an overall scale factor) regardless of the ripple velocity or whether stationary or moving ripples are used in the measurement. The same stability in shape holds for the temporal transfer functions and the impulse response functions measured with different ripple frequencies. Separability implies that the combined spectrotemporal transfer function of a cell can be written as the product of a purely ripple and a purely temporal transfer functions, and thus that the neuron can be computationally modeled as processing spectral and temporal information in two separate and successive stages. 5. The ripple parameters that characterize cortical cells are distributed somewhat evenly, with the characteristic ripple frequencies ranging from 0.2 to > 2 cycles/octave and the characteristic angular frequency typically ranging from 2 to 20 Hz. 6. Many responses exhibit periodicities in the spectral envelope of the stimulus. These periodicities are of two types. Slow rebounds, not found in the spectral envelope, and with a period of approximately 150 ms, appear with various strengths in approximately 30% of the cells. Fast regular firings with interspike intervals of approximately 10 ms are much less common and appear to correspond to interactions between the component tones that make up a ripple.

scholarly journals Binaural-Level Functions in Ferret Auditory Cortex: Evidence for a Continuous Distribution of Response Properties

2006 ◽  
Vol 95 (6) ◽  
pp. 3742-3755 ◽  
Author(s):  
Robert A. A. Campbell ◽  
Jan W. H. Schnupp ◽  
Akhil Shial ◽  
Andrew J. King
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Free Field ◽  
Continuous Distribution ◽  
Principal Component ◽  
Response Surfaces ◽  
Response Functions ◽  
Underlying Distribution ◽  
Response Properties ◽  
Interaural Level Differences

Many previous studies have subdivided auditory neurons into a number of physiological classes according to various criteria applied to their binaural response properties. However, it is often unclear whether such classifications represent discrete classes of neurons or whether they merely reflect a potentially convenient but ultimately arbitrary partitioning of a continuous underlying distribution of response properties. In this study we recorded the binaural response properties of 310 units in the auditory cortex of anesthetized ferrets, using an extensive range of interaural level differences (ILDs) and average binaural levels (ABLs). Most recordings were from primary auditory fields on the middle ectosylvian gyrus and from neurons with characteristic frequencies >5 kHz. We used simple multivariate statistics to quantify a fundamental coding feature: the shapes of the binaural response functions. The shapes of all 310 binaural response surfaces were represented as points in a five-dimensional principal component space. This space captured the underlying shape of all the binaural response surfaces. The distribution of binaural level functions was not homogeneous because some shapes were more common than others. Despite this, clustering validation techniques revealed no evidence for the existence of discrete, or partially overlapping, clusters that could serve as a basis for an objective classification of binaural-level functions. We also examined the gradients of the response functions for the population of units; these gradients were greatest near the midline, which is consistent with free-field data showing that cortical neurons are most sensitive to changes in stimulus location in this region of space.

Sign in / Sign up

Export Citation Format

Share Document