Sound frequency representation in primary auditory cortex is level tolerant for moderately loud, complex sounds

Three dimensional rendering of auditory neuronal responses: A novel illustration of receptive field across frequency, intensity & time domains

BACKGROUND

Neural coding of sound information is often studied through frequency tuning curve (FTC), spectro-temporal receptive field (STRF), post-stimulus time histogram (PSTH), and other methods such as rate functions. These methods, despite providing a robust characterization of auditory responses in their specific domains, lack a complete description in terms of three sound fundamentals: frequency, amplitude, and time.

NEW METHOD

Using the techniques of electrophysiology, neural signal processing and medical image processing, a standalone method is created to illustrate the neural processing of three sound fundamentals in one representation.

RESULTS

The new method comprehensively showed frequency tuning, intensity tuning, time tuning as well as a novel representation of frequency and time dependent intensity coding. It provides most of the necessary parameters that are used to quantify neural response properties, such as minimum threshold (MT), frequency tuning, latency, best frequency (BF), characteristic frequency (CF), bandwidth (BW), etc. COMPARISON WITH EXISTING METHODS: Our method shows neural responses as a function of all three sound fundamentals in a single representation that was not possible in previous methods. It covers many functions of conventional methods and allow extracting novel information such as the intensity coding as the function of the spectrotemporal response area of auditory neurons.

CONCLUSION

This method can be used as a standalone package to study auditory neural responses and evaluate the performance of different hearing related devices such as cochlear implants and hearing aids in animal models as well as study and compare auditory processing in aged and hearing impaired animal models.

Compensating Level-Dependent Frequency Representation in Auditory Cortex by Synaptic Integration of Corticocortical Input

Robust perception of auditory objects over a large range of sound intensities is a fundamental feature of the auditory system. However, firing characteristics of single neurons across the entire auditory system, like the frequency tuning, can change significantly with stimulus intensity. Physiological correlates of level-constancy of auditory representations hence should be manifested on the level of larger neuronal assemblies or population patterns. In this study we have investigated how information of frequency and sound level is integrated on the circuit-level in the primary auditory cortex (AI) of the Mongolian gerbil. We used a combination of pharmacological silencing of corticocortically relayed activity and laminar current source density (CSD) analysis. Our data demonstrate that with increasing stimulus intensities progressively lower frequencies lead to the maximal impulse response within cortical input layers at a given cortical site inherited from thalamocortical synaptic inputs. We further identified a temporally precise intercolumnar synaptic convergence of early thalamocortical and horizontal corticocortical inputs. Later tone-evoked activity in upper layers showed a preservation of broad tonotopic tuning across sound levels without shifts towards lower frequencies. Synaptic integration within corticocortical circuits may hence contribute to a level-robust representation of auditory information on a neuronal population level in the auditory cortex.

Cochlear injury and adaptive plasticity of the auditory cortex

Growing evidence suggests that cochlear stressors as noise exposure and aging can induce homeostatic/maladaptive changes in the central auditory system from the brainstem to the cortex. Studies centered on such changes have revealed several mechanisms that operate in the context of sensory disruption after insult (noise trauma, drug-, or age-related injury). The oxidative stress is central to current theories of induced sensory-neural hearing loss and aging, and interventions to attenuate the hearing loss are based on antioxidant agent. The present review addresses the recent literature on the alterations in hair cells and spiral ganglion neurons due to noise-induced oxidative stress in the cochlea, as well on the impact of cochlear damage on the auditory cortex neurons. The emerging image emphasizes that noise-induced deafferentation and upward spread of cochlear damage is associated with the altered dendritic architecture of auditory pyramidal neurons. The cortical modifications may be reversed by treatment with antioxidants counteracting the cochlear redox imbalance. These findings open new therapeutic approaches to treat the functional consequences of the cortical reorganization following cochlear damage.

A review of hyperacusis and future directions: part II. Measurement, mechanisms, and treatment

PURPOSE

Hyperacusis can be extremely debilitating, and at present, there is no cure. In this detailed review of the field, we consolidate present knowledge in the hope of facilitating future research.

METHOD

We review and reference the literature on hyperacusis and related areas. This is the 2nd of a 2-part review.

RESULTS

Hyperacusis encompasses a wide range of reactions to sounds, which can be grouped into the categories of excessive loudness, annoyance, fear, and pain. Reasonable approaches to assessing the different forms of hyperacusis are emerging, including brain-imaging studies. Researchers are only beginning to understand the many mechanisms at play, and valid animal models are still evolving. There are many counseling and sound-therapy approaches that some patients find helpful, but well-controlled studies are needed to measure their long-term efficacy and to test new approaches.

CONCLUSIONS

Hyperacusis can make life difficult in this increasingly noisy world, forcing sufferers to dramatically alter their work and social habits. We believe this is an opportune time to explore approaches to better understand and treat hyperacusis.

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings

Our understanding of the large-scale population dynamics of neural activity is limited, in part, by our inability to record simultaneously from large regions of the cortex. Here, we validated the use of a large-scale active microelectrode array that simultaneously records 196 multiplexed micro-electrocortigraphical (μECoG) signals from the cortical surface at a very high density (1,600 electrodes/cm(2)). We compared μECoG measurements in auditory cortex using a custom "active" electrode array to those recorded using a conventional "passive" μECoG array. Both of these array responses were also compared with data recorded via intrinsic optical imaging, which is a standard methodology for recording sound-evoked cortical activity. Custom active μECoG arrays generated more veridical representations of the tonotopic organization of the auditory cortex than current commercially available passive μECoG arrays. Furthermore, the cortical representation could be measured efficiently with the active arrays, requiring as little as 13.5 s of neural data acquisition. Next, we generated spectrotemporal receptive fields from the recorded neural activity on the active μECoG array and identified functional organizational principles comparable to those observed using intrinsic metabolic imaging and single-neuron recordings. This new electrode array technology has the potential for large-scale, temporally precise monitoring and mapping of the cortex, without the use of invasive penetrating electrodes.

Estimating the correlation between bursty spike trains and local field potentials

To further understand rhythmic neuronal synchronization, an increasingly useful method is to determine the relationship between the spiking activity of individual neurons and the local field potentials (LFPs) of neural ensembles. Spike field coherence (SFC) is a widely used method for measuring the synchronization between spike trains and LFPs. However, due to the strong dependency of SFC on the burst index, it is not suitable for analyzing the relationship between bursty spike trains and LFPs, particularly in high frequency bands. To address this issue, we developed a method called weighted spike field correlation (WSFC), which uses the first spike in each burst multiple times to estimate the relationship. In the calculation, the number of times that the first spike is used is equal to the spike count per burst. The performance of this method was demonstrated using simulated bursty spike trains and LFPs, which comprised sinusoids with different frequencies, amplitudes, and phases. This method was also used to estimate the correlation between pyramidal cells in the hippocampus and gamma oscillations in rats performing behaviors. Analyses using simulated and real data demonstrated that the WSFC method is a promising measure for estimating the correlation between bursty spike trains and high frequency LFPs.

A new and fast characterization of multiple encoding properties of auditory neurons

The functional properties of auditory cortex neurons are most often investigated separately, through spectrotemporal receptive fields (STRFs) for the frequency tuning and the use of frequency sweeps sounds for selectivity to velocity and direction. In fact, auditory neurons are sensitive to a multidimensional space of acoustic parameters where spectral, temporal and spatial dimensions interact. We designed a multi-parameter stimulus, the random double sweep (RDS), composed of two uncorrelated random sweeps, which gives an easy, fast and simultaneous access to frequency tuning as well as frequency modulation sweep direction and velocity selectivity, frequency interactions and temporal properties of neurons. Reverse correlation techniques applied to recordings from the primary auditory cortex of guinea pigs and rats in response to RDS stimulation revealed the variety of temporal dynamics of acoustic patterns evoking an enhanced or suppressed firing rate. Group results on these two species revealed less frequent suppression areas in frequency tuning STRFs, the absence of downward sweep selectivity, and lower phase locking abilities in the auditory cortex of rats compared to guinea pigs.

Auditory forebrain neurons track temporal features of time-warped natural stimuli

A fundamental challenge for sensory systems is to recognize natural stimuli despite stimulus variations. A compelling example occurs in speech, where the auditory system can recognize words spoken at a wide range of speeds. To date, there have been more computational models for time-warp invariance than experimental studies that investigate responses to time-warped stimuli at the neural level. Here, we address this problem in the model system of zebra finches anesthetized with urethane. In behavioral experiments, we found high discrimination accuracy well beyond the observed natural range of song variations. We artificially sped up or slowed down songs (preserving pitch) and recorded auditory responses from neurons in field L, the avian primary auditory cortex homolog. We found that field L neurons responded robustly to time-warped songs, tracking the temporal features of the stimuli over a broad range of warp factors. Time-warp invariance was not observed per se, but there was sufficient information in the neural responses to reliably classify which of two songs was presented. Furthermore, the average spike rate was close to constant over the range of time warps, contrary to recent modeling predictions. We discuss how this response pattern is surprising given current computational models of time-warp invariance and how such a response could be decoded downstream to achieve time-warp-invariant recognition of sounds.

Frequency response areas in the inferior colliculus: nonlinearity and binaural interaction

The tuning, binaural properties, and encoding characteristics of neurons in the central nucleus of the inferior colliculus (CNIC) were investigated to shed light on nonlinearities in the responses of these neurons. Results were analyzed for three types of neurons (I, O, and V) in the CNIC of decerebrate cats. Rate responses to binaural stimuli were characterized using a 1st- plus 2nd-order spectral integration model. Parameters of the model were derived using broadband stimuli with random spectral shapes (RSS). This method revealed four characteristics of CNIC neurons: (1) Tuning curves derived from broadband stimuli have fixed (i. e., level tolerant) bandwidths across a 50-60 dB range of sound levels; (2) 1st-order contralateral weights (particularly for type I and O neurons) were usually larger in magnitude than corresponding ipsilateral weights; (3) contralateral weights were more important than ipsilateral weights when using the model to predict responses to untrained noise stimuli; and (4) 2nd-order weight functions demonstrate frequency selectivity different from that of 1st-order weight functions. Furthermore, while the inclusion of 2nd-order terms in the model usually improved response predictions related to untrained RSS stimuli, they had limited impact on predictions related to other forms of filtered broadband noise [e. g., virtual-space stimuli (VS)]. The accuracy of the predictions varied considerably by response type. Predictions were most accurate for I neurons, and less accurate for O and V neurons, except at the lowest stimulus levels. These differences in prediction performance support the idea that type I, O, and V neurons encode different aspects of the stimulus: while type I neurons are most capable of producing linear representations of spectral shape, type O and V neurons may encode spectral features or temporal stimulus properties in a manner not easily explained with the low-order model. Supported by NIH grant DC00115.

Component analysis reveals sharp tuning of the local field potential in the guinea pig auditory cortex

Local field potentials (LFPs) recorded in the auditory cortex of mammals are known to reveal weakly selective and often multimodal spectrotemporal receptive fields in contrast to spiking activity. This may in part reflect the wider "listening sphere" of LFPs relative to spikes due to the greater current spread at low than high frequencies. We recorded LFPs and spikes from auditory cortex of guinea pigs using 16-channel electrode arrays. LFPs were processed by a component analysis technique that produces optimally tuned linear combinations of electrode signals. Linear combinations of LFPs were found to have sharply tuned responses, closer to spike-related tuning. The existence of a sharply tuned component implies that a cortical neuron (or group of neurons) capable of forming a linear combination of its inputs has access to that information. Linear combinations of signals from electrode arrays reveal information latent in the subspace spanned by multichannel LFP recordings and are justified by the fact that the observations themselves are linear combinations of neural sources.