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

2005 ◽  
Vol 94 (4) ◽  
pp. 2263-2274 ◽  
Author(s):  
Jiping Zhang ◽  
Kyle T. Nakamoto ◽  
Leonard M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Conditioning Stimulus ◽  
Primary Auditory Cortex ◽  
Response Magnitude ◽  
Absolute Level ◽  
Preceding Stimulus ◽  
Dynamic Modulation ◽  
Acoustic Stimuli ◽  
Static Level ◽  
Response Area

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 ≥50 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.

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

2006 ◽  
Vol 95 (3) ◽  
pp. 1897-1907 ◽  
Author(s):  
Kyle T. Nakamoto ◽  
Jiping Zhang ◽  
Leonard M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Recovery Rate ◽  
Primary Auditory Cortex ◽  
Auditory Stimuli ◽  
Time Interval ◽  
Large Set ◽  
Strong Response ◽  
Preceding Stimulus ◽  
Sequential Inhibition ◽  
Response Area

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.

Auditory Imagery Modulates Frequency-specific Areas in the Human Auditory Cortex

2013 ◽  
Vol 25 (2) ◽  
pp. 175-187 ◽  
Author(s):  
Jihoon Oh ◽  
Jae Hyung Kwon ◽  
Po Song Yang ◽  
Jaeseung Jeong
Keyword(s):  
Auditory Cortex ◽  
High Frequency ◽  
Low Frequency ◽  
Primary Auditory Cortex ◽  
Auditory Imagery ◽  
Neural Responses ◽  
Top Down ◽  
Visual Areas ◽  
Control Functional ◽  
Response Area

Neural responses in early sensory areas are influenced by top–down processing. In the visual system, early visual areas have been shown to actively participate in top–down processing based on their topographical properties. Although it has been suggested that the auditory cortex is involved in top–down control, functional evidence of topographic modulation is still lacking. Here, we show that mental auditory imagery for familiar melodies induces significant activation in the frequency-responsive areas of the primary auditory cortex (PAC). This activation is related to the characteristics of the imagery: when subjects were asked to imagine high-frequency melodies, we observed increased activation in the high- versus low-frequency response area; when the subjects were asked to imagine low-frequency melodies, the opposite was observed. Furthermore, we found that A1 is more closely related to the observed frequency-related modulation than R in tonotopic subfields of the PAC. Our findings suggest that top–down processing in the auditory cortex relies on a mechanism similar to that used in the perception of external auditory stimuli, which is comparable to early visual systems.

scholarly journals The Role of Adaptation in Generating Monotonic Rate Codes in Auditory Cortex

2019 ◽  
Author(s):  
Jong Hoon Lee ◽  
Xiaoqin Wang ◽  
Daniel Bendor
Keyword(s):  
Auditory Cortex ◽  
Single Unit ◽  
Discharge Rate ◽  
Primary Auditory Cortex ◽  
Stimulus Presentation ◽  
Single Neurons ◽  
Short Term ◽  
Acoustic Stimuli ◽  
Biophysical Mechanism

AbstractIn primary auditory cortex, slowly repeated acoustic events are represented temporally by phase-locked activity of single neurons. Single-unit studies in awake marmosets (Callithrix jacchus) have shown that a sub-population of these neurons also monotonically increase or decrease their average discharge rate during stimulus presentation for higher repetition rates. Building on a computational single-neuron model that generates phase-locked responses with stimulus evoked excitation followed by strong inhibition, we find that stimulus-evoked short-term depression is sufficient to produce synchronized monotonic positive and negative responses to slowly repeated stimuli. By exploring model robustness and comparing it to other models for adaptation to such stimuli, we conclude that short-term depression best explains our observations in single-unit recordings in awake marmosets. Using this model, we emulated how single neurons could encode and decode multiple aspects of an acoustic stimuli with the monotonic positive and negative encoding of a given stimulus feature. Together, our results show that a simple biophysical mechanism in single neurons can allow a more complex encoding and decoding of acoustic stimuli.

Time course of tonal frequency-response-area of primary auditory cortex neurons in alert cats

2003 ◽  
Vol 46 (2) ◽  
pp. 145-152 ◽  
Author(s):  
Ling Qin ◽  
Toshihiro Kitama ◽  
Sohei Chimoto ◽  
Shuichi Sakayori ◽  
Yu Sato
Keyword(s):  
Auditory Cortex ◽  
Frequency Response ◽  
Time Course ◽  
Primary Auditory Cortex ◽  
Tonal Frequency ◽  
Alert Cats ◽  
Response Area

scholarly journals Selective effects of arousal on population coding of natural sounds in auditory cortex

2020 ◽  
Author(s):  
Charles R. Heller ◽  
Zachary P. Schwartz ◽  
Daniela Saderi ◽  
Stephen V. David
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Population Coding ◽  
Response Magnitude ◽  
Correlated Noise ◽  
Natural Sounds ◽  
Dimensional Changes ◽  
Neural Populations ◽  
Evoked Activity ◽  
Low Dimensional

AbstractThe ability to discriminate between complex natural sounds is critical for survival. Changes in arousal and other aspects of behavioral state can impact the accuracy of sensory coding, affecting both the reliability of single neuron responses and the degree of correlated noise between neurons. However, it is unclear how these effects interact to influence coding of diverse natural stimuli. We recorded the spiking activity of neural populations in primary auditory cortex (A1) evoked by a large library of natural sounds while monitoring changes in pupil size as an index of arousal. Heightened arousal increased response magnitude and reduced noise correlations between neurons, improving coding accuracy on average. Rather than suppressing shared noise along all dimensions of neural activity, the change in noise correlations occurred via coherent, low-dimensional modulation of response variability in A1. The modulation targeted a different group of neurons from those undergoing changes in response magnitude. Thus, changes in response magnitude and correlation are mediated by distinct mechanisms. The degree to which these low-dimensional changes were aligned with the high-dimensional natural sound-evoked activity was variable, resulting in stimulus-dependent improvements in coding accuracy.

Functional topography of cat primary auditory cortex: distribution of integrated excitation

1990 ◽  
Vol 64 (5) ◽  
pp. 1442-1459 ◽  
Author(s):  
C. E. Schreiner ◽  
J. R. Mendelson
Keyword(s):  
Spatial Distribution ◽  
Auditory Cortex ◽  
Functional Organization ◽  
Primary Auditory Cortex ◽  
Response Magnitude ◽  
Response Threshold ◽  
Step Response ◽  
Frequency Independent ◽  
Multiple Unit ◽  
Excitatory Responses

1. Neuronal responses to tones and transient stimuli were mapped with microelectrodes in the primary auditory cortex (AI) of barbiturate anesthetized cats. Most of the dorsoventral extent of AI was mapped with multiple-unit recordings in the high-frequency domain (between 5.8 and 26.3 kHz) of all six studied cases. The spatial distributions of 1) sharpness of tuning measured with pure tones and 2) response magnitudes to a broadband transient were determined in each of three intensively studied cases. 2. The sharpness of tuning of integrated cluster responses was defined 10 dB above threshold (Q10 dB, integrated excitatory bandwidth). The spatial reconstructions revealed a frequency-independent maximum located near the center of the dorsoventral extent of AI. The sharpness of tuning gradually decreased toward the dorsal and ventral border of AI in all three cases. 3. The sharpness of tuning 40 dB above response threshold was also analyzed (Q40 dB). The Q40 dB values were less than one-half of the corresponding Q10 dB value. The spatial distribution showed a maximum in the center of AI, similar to the Q10 dB distribution. In two out of three cases, restricted additional maxima were recorded dorsal to the main maximum. Overall, Q10 dB and Q40 dB were only moderately correlated, indicating that the integrated excitatory bandwidth at higher stimulus levels can be influenced by additional mechanisms that are not active at lower levels. 4. The magnitude of excitatory responses to a broadband transient (frequency-step response) was determined. The normalized response magnitude varied between less than 1% and up to 100% relative to a characteristic frequency (CF) tone response. The step-response magnitude showed a systematic spatial distribution. An area dorsal to the Q10 dB maximum consistently showed the largest response magnitude surrounded by areas of lower responsivity. A second spatially more restricted maximum was recorded in the ventral-third of each map. Areas with high-transient responsiveness coincided with areas of broad integrated excitatory bandwidth at comparable stimulus levels. 5. The distribution of excitation produced by narrowband and broadband signals suggest that there exists a clear functional organization in the isofrequency domain of AI that is orthogonal to the main cochleotopic organization of the AI. Systematic spatial variations of the integrated excitatory bandwidth reflect underlying cortical processing capacities that may contribute to a parallel analysis of spectral complexity, e.g., spectral shape and contrast, at any given frequency.(ABSTRACT TRUNCATED AT 400 WORDS)

Speaker Verification via Modeling Kurtosis Using Sparse Coding

2016 ◽  
Vol 30 (03) ◽  
pp. 1659008 ◽  
Author(s):  
Wei Wang ◽  
Jiqing Han ◽  
Tieran Zheng ◽  
Guibin Zheng ◽  
Xingyu Zhou
Keyword(s):  
Auditory Cortex ◽  
Statistical Method ◽  
Auditory System ◽  
Sparse Coding ◽  
Speaker Verification ◽  
Primary Auditory Cortex ◽  
Acoustic Signals ◽  
Acoustic Stimuli ◽  
Independent Events ◽  
Individual Speaker

This paper proposes a new model for speaker verification by employing kurtosis statistical method based on sparse coding of human auditory system. Since only a small number of neurons in primary auditory cortex are activated in encoding acoustic stimuli and sparse independent events are used to represent the characteristics of the neurons. Each individual dictionary is learned from individual speaker samples where dictionary atoms correspond to the cortex neurons. The neuron responses possess statistical properties of acoustic signals in auditory cortex so that the activation distribution of individual speaker’s neurons is approximated as the characteristics of the speaker. Kurtosis is an efficient approach to measure the sparsity of the neuron from its activation distribution, and the vector composed of the kurtosis of every neuron is obtained as the model to characterize the speaker’s voice. The experimental results demonstrate that the kurtosis model outperforms the baseline systems and an effective identity validation function is achieved desirably.

scholarly journals Spectral and spatial tuning of onset and offset response functions in auditory cortical fields A1 and CL of rhesus macaques

2017 ◽  
Vol 117 (3) ◽  
pp. 966-986 ◽  
Author(s):  
Deepa L. Ramamurthy ◽  
Gregg H. Recanzone
Keyword(s):  
Auditory Cortex ◽  
Rhesus Macaques ◽  
Primary Auditory Cortex ◽  
Evoked Responses ◽  
Neural Responses ◽  
Complex Cells ◽  
Acoustic Stimuli ◽  
Spatial Tuning ◽  
Response Profiles ◽  
The Relationship

The mammalian auditory cortex is necessary for spectral and spatial processing of acoustic stimuli. Most physiological studies of single neurons in the auditory cortex have focused on the onset and sustained portions of evoked responses, but there have been far fewer studies on the relationship between onset and offset responses. In the current study, we compared spectral and spatial tuning of onset and offset responses of neurons in primary auditory cortex (A1) and the caudolateral (CL) belt area of awake macaque monkeys. Several different metrics were used to determine the relationship between onset and offset response profiles in both frequency and space domains. In the frequency domain, a substantial proportion of neurons in A1 and CL displayed highly dissimilar best stimuli for onset- and offset-evoked responses, although even for these neurons, there was usually a large overlap in the range of frequencies that elicited onset, and offset responses and distributions of tuning overlap metrics were mostly unimodal. In the spatial domain, the vast majority of neurons displayed very similar best locations for onset- and offset-evoked responses, along with unimodal distributions of all tuning overlap metrics considered. Finally, for both spectral and spatial tuning, a slightly larger fraction of neurons in A1 displayed nonoverlapping onset and offset response profiles, relative to CL, which supports hierarchical differences in the processing of sounds in the two areas. However, these differences are small compared with differences in proportions of simple cells (low overlap) and complex cells (high overlap) in primary and secondary visual areas. NEW & NOTEWORTHY In the current study, we examine the relationship between the tuning of neural responses evoked by the onset and offset of acoustic stimuli in the primary auditory cortex, as well as a higher-order auditory area—the caudolateral belt field—in awake rhesus macaques. In these areas, the relationship between onset and offset response profiles in frequency and space domains formed a continuum, ranging from highly overlapping to highly nonoverlapping.

Focal selectivity for binaural sound pressure level in cat primary auditory cortex: two-way intensity network tuning

1993 ◽  
Vol 69 (2) ◽  
pp. 462-473 ◽  
Author(s):  
M. N. Semple ◽  
L. M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Preceding Paper ◽  
Primary Auditory Cortex ◽  
Pressure Level ◽  
Response Magnitude ◽  
Interaural Level Difference ◽  
Single Class ◽  
Effective Combination

1. The influence of sound pressure level (SPL) at the two ears was studied in single-neuron responses recorded in high-frequency regions of primary auditory cortex (AI) of anesthetized cats. For each unit, many binaural combinations of SPL were tested by using best-frequency tone pips presented to each ear independently via sealed stimulus delivery systems. In the preceding paper, we illustrated the different forms of response observed in our sample of units. Here we explore in more detail the mechanisms underlying the properties of the largest single class of binaural response, characterized by joint nonmonotonic tuning to the SPLs at the two ears. We have described such units as being influenced by a Two-Way Intensity Network (TWIN). 2. Under binaural conditions, 62% of our sample of well documented neurons (81/130) exhibited a nonmonotonic relation between response magnitude and the SPL at one or the other ear. Of these units, 47 displayed clear bilateral nonmonotonicity (TWIN tuning), 17 units displayed only unilateral nonmonotonicity, and an additional 17 units showed intermediate (or transitional) characteristics between unilateral and bilateral nonmonotonicity. These characteristics can also be described in terms of average binaural level (ABL) and interaural level difference (ILD). Thus there is commonly a nonmonotonic relation between response magnitude and ABL and sometimes a TWIN tuning to ABL and ILD. The distribution of best frequencies for TWIN neurons is broad. 3. Under monaural conditions, TWIN neurons exhibit diverse properties. Some are responsive only under binaural conditions [i.e., predominantly binaural (PB)]. Some monaurally responsive TWINs are contralaterally excitable and ipsilaterally unresponsive (EO), some are ipsilaterally excitable and contralaterally unresponsive (OE), and a few are bilaterally excitable (EE). Monaural rate/level functions are monotonic for some of these neurons and nonmonotonic for others. Neurons of the PB class have previously been found to have nonmonotonic selectivity for ILDs near zero. In this study we have found that virtually all PB neurons are also nonmonotonically selective for ABL with different PB neurons having different best ABLs. 4. For TWIN neurons that respond monaurally, it is possible to demonstrate a mixed binaural influence. The optimal stimulus (or best binaural combination) for a TWIN neuron is associated with binaural facilitation. Flanking the most effective combination of ABL and ILD are less effective combinations that generate lower response magnitudes, either through threshold effects (at low SPLs) or through binaural suppression (at higher SPLs).(ABSTRACT TRUNCATED AT 400 WORDS)

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