Tuning curves in the presence of a simultaneous noise masker

1982 ◽  
Vol 72 (S1) ◽  
pp. S67-S67
Author(s):  
Edward A. Cudahy ◽  
Daniel Geller
Keyword(s):  
Tuning Curves ◽  
Noise Masker

AP tuning curves from normal and pathological human and guinea pig cochleas

1981 ◽  
Vol 69 (5) ◽  
pp. 1374-1385 ◽  
Author(s):  
Robert V. Harrison ◽  
Jean–Marie Aran ◽  
Jean–Paul Erre
Keyword(s):  
Guinea Pig ◽  
Tuning Curves

Population Vectors Can Provide Near Optimal Integration of Information

2017 ◽  
Vol 29 (8) ◽  
pp. 2021-2029
Author(s):  
Josue Orellana ◽  
Jordan Rodu ◽  
Robert E. Kass
Keyword(s):  
Bayesian Inference ◽  
Point Process ◽  
Neural Mechanism ◽  
Input Neuron ◽  
Tuning Curves ◽  
Optimal Integration ◽  
Bayesian Integration ◽  
Combine Information ◽  
Input Spike ◽  
Combine Evidence

Much attention has been paid to the question of how Bayesian integration of information could be implemented by a simple neural mechanism. We show that population vectors based on point-process inputs combine evidence in a form that closely resembles Bayesian inference, with each input spike carrying information about the tuning of the input neuron. We also show that population vectors can combine information relatively accurately in the presence of noisy synaptic encoding of tuning curves.

Response Properties of Single Auditory Nerve Fibers in the Mouse

2005 ◽  
Vol 93 (1) ◽  
pp. 557-569 ◽  
Author(s):  
Annette M. Taberner ◽  
M. Charles Liberman
Keyword(s):  
Auditory Nerve ◽  
Dynamic Range ◽  
Phase Locking ◽  
Nerve Fibers ◽  
Cochlear Function ◽  
Response Properties ◽  
Tuning Curves ◽  
Rate Versus ◽  
Interstrain Difference ◽  
Mutant Lines

The availability of transgenic and mutant lines makes the mouse a valuable model for study of the inner ear, and a powerful window into cochlear function can be obtained by recordings from single auditory nerve (AN) fibers. This study provides the first systematic description of spontaneous and sound-evoked discharge properties of AN fibers in mouse, specifically in CBA/CaJ and C57BL/6 strains, both commonly used in auditory research. Response properties of 196 AN fibers from CBA/CaJ and 58 from C57BL/6 were analyzed, including spontaneous rates (SR), tuning curves, rate versus level functions, dynamic range, response adaptation, phase-locking, and the relation between SR and these response properties. The only significant interstrain difference was the elevation of high-frequency thresholds in C57BL/6. In general, mouse AN fibers showed similar responses to other mammals: sharpness of tuning increased with characteristic frequency, which ranged from 2.5 to 70 kHz; SRs ranged from 0 to 120 sp/s, and fibers with low SR (<1 sp/s) had higher thresholds, and wider dynamic ranges than fibers with high SR. Dynamic ranges for mouse high-SR fibers were smaller (<20 dB) than those seen in other mammals. Phase-locking was seen for tone frequencies <4 kHz. Maximum synchronization indices were lower than those in cat but similar to those found in guinea pig.

A comparison of AP and ABR tuning curves in the guinea pig

1987 ◽  
Vol 25 (2-3) ◽  
pp. 193-204 ◽  
Author(s):  
Carolyn J. Browri ◽  
Paul J. Abbas
Keyword(s):  
Guinea Pig ◽  
Tuning Curves

scholarly journals The Physiologic and Psychophysical Consequences of Severe-to-Profound Hearing Loss

2018 ◽  
Vol 39 (04) ◽  
pp. 349-363 ◽  
Author(s):  
Eric Hoover ◽  
Pamela Souza
Keyword(s):  
Hearing Loss ◽  
Speech Recognition ◽  
Treatment Options ◽  
Sufficient Information ◽  
Noisy Environments ◽  
Cochlear Function ◽  
Profound Hearing Loss ◽  
Sound Perception ◽  
Severe Hearing Loss ◽  
Tuning Curves

AbstractSubstantial loss of cochlear function is required to elevate pure-tone thresholds to the severe hearing loss range; yet, individuals with severe or profound hearing loss continue to rely on hearing for communication. Despite the impairment, sufficient information is encoded at the periphery to make acoustic hearing a viable option. However, the probability of significant cochlear and/or neural damage associated with the loss has consequences for sound perception and speech recognition. These consequences include degraded frequency selectivity, which can be assessed with tests including psychoacoustic tuning curves and broadband rippled stimuli. Because speech recognition depends on the ability to resolve frequency detail, a listener with severe hearing loss is likely to have impaired communication in both quiet and noisy environments. However, the extent of the impairment varies widely among individuals. A better understanding of the fundamental abilities of listeners with severe and profound hearing loss and the consequences of those abilities for communication can support directed treatment options in this population.

scholarly journals Statistical assessment of the stability of neural movement representations

2011 ◽  
Vol 106 (2) ◽  
pp. 764-774 ◽  
Author(s):  
Ian H. Stevenson ◽  
Anil Cherian ◽  
Brian M. London ◽  
Nicholas A. Sachs ◽  
Eric Lindberg ◽  
...  
Keyword(s):  
Primary Motor Cortex ◽  
Tuning Curve ◽  
Modulation Depth ◽  
Measurement Noise ◽  
Neural Representation ◽  
Experimental Conditions ◽  
Sensory Stimuli ◽  
Tuning Curves ◽  
Dynamic Tuning ◽  
Preferred Direction

In systems neuroscience, neural activity that represents movements or sensory stimuli is often characterized by spatial tuning curves that may change in response to training, attention, altered mechanics, or the passage of time. A vital step in determining whether tuning curves change is accounting for estimation uncertainty due to measurement noise. In this study, we address the issue of tuning curve stability using methods that take uncertainty directly into account. We analyze data recorded from neurons in primary motor cortex using chronically implanted, multielectrode arrays in four monkeys performing center-out reaching. With the use of simulations, we demonstrate that under typical experimental conditions, the effect of neuronal noise on estimated preferred direction can be quite large and is affected by both the amount of data and the modulation depth of the neurons. In experimental data, we find that after taking uncertainty into account using bootstrapping techniques, the majority of neurons appears to be very stable on a timescale of minutes to hours. Lastly, we introduce adaptive filtering methods to explicitly model dynamic tuning curves. In contrast to several previous findings suggesting that tuning curves may be in constant flux, we conclude that the neural representation of limb movement is, on average, quite stable and that impressions to the contrary may be largely the result of measurement noise.

Psychophysical tuning curves in forward masking

1975 ◽  
Vol 58 (S1) ◽  
pp. S34-S34 ◽  
Author(s):  
F. L. Wightman ◽  
M. B. Kramer ◽  
T. McGee
Keyword(s):  
Forward Masking ◽  
Tuning Curves

A model for the estimate of local image velocity by cells in the visual cortex

1990 ◽  
Vol 239 (1295) ◽  
pp. 129-161 ◽  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Spatial Integration ◽  
Temporal Area ◽  
Image Velocity ◽  
Tuning Curves ◽  
Spatio Temporal ◽  
Local Image

Some computational theories of motion perception assume that the first stage en route to this perception is the local estimate of image velocity. However, this assumption is not supported by data from the primary visual cortex. Its motion sensitive cells are not selective to velocity, but rather are directionally selective and tuned to spatio-temporal frequen­cies. Accordingly, physiologically based theories start with filters selec­tive to oriented spatio-temporal frequencies. This paper shows that computational and physiological theories do not necessarily conflict, because such filters may, as a population, compute velocity locally. To prove this point, we show how to combine the outputs of a class of frequency tuned filters to detect local image velocity. Furthermore, we show that the combination of filters may simulate ‘Pattern’ cells in the middle temporal area (MT), whereas each filter simulates primary visual cortex cells. These simulations include three properties of the primary cortex. First, the spatio-temporal frequency tuning curves of the in­dividual filters display approximate space-time separability. Secondly, their direction-of-motion tuning curves depend on the distribution of orientations of the components of the Fourier decomposition and speed of the stimulus. Thirdly, the filters show facilitation and suppression for responses to apparent motions in the preferred and null directions, respect­ively. It is suggested that the MT’s role is not to solve the aperture problem, but to estimate velocities from primary cortex information. The spatial integration that accounts for motion coherence may be postponed to a later cortical stage.

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