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

Receptive-field nonlinearities in primary auditory cortex: a comparative perspective

Cortical processing of auditory information can be affected by interspecies differences as well as brain states. Here we compare multifeature spectro-temporal receptive fields (STRFs) and associated input/output functions or nonlinearities (NLs) of neurons in primary auditory cortex (AC) of four mammalian species. Single-unit recordings were performed in awake animals (female squirrel monkeys, female, and male mice) and anesthetized animals (female squirrel monkeys, rats, and cats). Neuronal responses were modeled as consisting of two STRFs and their associated NLs. The NLs for the STRF with the highest information content show a broad distribution between linear and quadratic forms. In awake animals, we find a higher percentage of quadratic-like NLs as opposed to more linear NLs in anesthetized animals. Moderate sex differences of the shape of NLs were observed between male and female unanesthetized mice. This indicates that the core AC possesses a rich variety of potential computations, particularly in awake animals, suggesting that multiple computational algorithms are at play to enable the auditory system's robust recognition of auditory events.

Roles of temporal proximity between sound edges in the perceptual organization of veridical and illusory auditory events

The gap transfer illusion is an auditory illusion in which a temporal gap in a long glide is perceived as if it had transferred to a physically continuous shorter glide. The illusion typically occurs when the long and the shorter glide cross each other at their temporal midpoints, where the long glide is physically divided by the gap. The occurrence of the gap transfer illusion was investigated in stimuli in which the duration and the slope of the long glide were 5000 ms and ∼0.8 oct/s. The shorter glide was given different frequency ranges and different temporal ranges, and thus its time-frequency slope was also varied. The overlap configuration of these crossing glides was varied as well. As control stimuli, we used stimuli in which a continuous long glide crossed a shorter glide with a gap, i.e., the opposite configuration of the gap-transfer stimuli as above, as well as stimuli in which both crossing glides were continuous. The perception of two crossing tones tended to be facilitated when the glides differed in duration and/or slope. When the glides were relatively similar in duration and slope, however, bouncing percepts appeared more often. Similarity between the crossing tones thus promoted auditory bouncing, while dissimilarity between them facilitated the crossing percept. If the crossing percept dominated in gap-transfer stimuli, the gap transfer illusion took place in a typical manner, but the illusory transfer of the gap could occur even when the crossing percept was not dominant. When the shorter glide was as short as 500 ms, the crossing percept and the gap transfer illusion were robust. The mechanism of the illusion was examined in terms of factors that can influence the perceptual integration of auditory stimulus edges, i.e., onsets and offsets, of physically different sounds. Much like the perceptual construction of speech units, we suggest that the auditory system utilizes a rough time window of several hundreds of milliseconds to construct an initial skeleton percept of auditory events. The present data indicated the importance of the temporal proximity, rather than the frequency proximity, between sound edges in the illusory tone construction.

Temporally precise population coding of dynamic sounds by auditory cortex

Fluctuations in the amplitude envelope of complex sounds provide critical cues for hearing, particularly for speech and animal vocalizations. Responses to amplitude modulation (AM) in the ascending auditory pathway have chiefly been described for single neurons. How neural populations might collectively encode and represent information about AM remains poorly characterized, even in primary auditory cortex (A1). We modeled population responses to AM based on data recorded from A1 neurons in awake squirrel monkeys and evaluated how accurately single trial responses to modulation frequencies from 4 to 512 Hz could be decoded as functions of population size, composition, and correlation structure. We found that a population-based decoding model that simulated convergent, equally weighted inputs was highly accurate and remarkably robust to the inclusion of neurons that were individually poor decoders. By contrast, average rate codes based on convergence performed poorly; effective decoding using average rates was only possible when the responses of individual neurons were segregated, as in classical population decoding models using labeled lines. The relative effectiveness of dynamic rate coding in auditory cortex was explained by shared modulation phase preferences among cortical neurons, despite heterogeneity in rate-based modulation frequency tuning. Our results indicate significant population-based synchrony in primary auditory cortex and suggest that robust population coding of the sound envelope information present in animal vocalizations and speech can be reliably achieved even with indiscriminate pooling of cortical responses. These findings highlight the importance of firing rate dynamics in population-based sensory coding.NEW & NOTEWORTHY Fundamental questions remain about population coding in primary auditory cortex (A1). In particular, issues of spike timing in models of neural populations have been largely ignored. We find that spike-timing in response to sound envelope fluctuations is highly similar across neuron populations in A1. This property of shared envelope phase preference allows for a simple population model involving unweighted convergence of neuronal responses to classify amplitude modulation frequencies with high accuracy.

Age-related changes in sound onset and offset intensity coding in auditory cortical fields A1 and CL of rhesus macaques

Inhibition plays a key role in shaping sensory processing in the central auditory system and has been implicated in sculpting receptive field properties such as sound intensity coding and also in shaping temporal patterns of neuronal firing such as onset- or offset-evoked responses. There is substantial evidence supporting a decrease in inhibition throughout the ascending auditory pathway in geriatric animals. We therefore examined intensity coding of onset (ON) and offset (OFF) responses in auditory cortex of aged and young monkeys. A large proportion of cells in the primary auditory cortex (A1) and the caudolateral field (CL) displayed nonmonotonic rate-level functions for OFF responses in addition to nonmonotonic coding of ON responses. Aging differentially affected ON and OFF responses; the magnitude of effects was generally greater for ON responses. In addition to higher firing rates, neurons in old monkeys exhibited a significant increase in the proportion of monotonic rate-level functions and had higher best intensities than those in young monkeys. OFF responses in young monkeys displayed a range of intensity coding relationships with ON responses of the same cells, ranging from highly similar to highly dissimilar. Dissimilarity in ON/OFF coding was greater in CL and was reduced with aging, which was largely explained by a preferential decrease in the percentage of cells with nonmonotonic coding of ON and OFF responses. The changes we observed are consistent with previously demonstrated alterations in inhibition in the ascending auditory pathway of primates and could be involved in age-related deficits in the temporal processing of sounds.NEW & NOTEWORTHY Aging has a major impact on intensity coding of neurons in auditory cortex of rhesus macaques. Neural responses to sound onset and offset were affected to different extents, and their rate-level functions became more mutually similar, which could be accounted for by the loss of nonmonotonic intensity coding in geriatric monkeys. These findings were consistent with weakened inhibition in the central auditory system and could contribute to auditory processing deficits in elderly subjects.

Effects of Ketamine Administration on Auditory Information Processing in the Neocortex of Nonhuman Primates

Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, exerts broad effects on consciousness and perception. Since NMDA receptor antagonists induce cognitive impairments, ketamine has been used for translational research on several psychiatric diseases, such as schizophrenia. Whereas the effects of ketamine on cognitive functions have been extensively studied, studies on the effects of ketamine on simple sensory information processing remain limited. In this study, we investigated the cortex-wide effects of ketamine administration on auditory information processing in nonhuman primates using whole-cortical electrocorticography (ECoG). We first recorded ECoG from awake monkeys on presenting auditory stimuli of different frequencies or different durations. We observed auditory evoked responses (AERs) across the cortex, including in frontal, parietal, and temporal areas, while feature-specific responses were obtained around the temporal sulcus. Next, we examined the effects of ketamine on cortical auditory information processing. We conducted ECoG recordings from monkeys that had been administered anesthetic doses of ketamine from 10 to 180 min following administration. We observed significant changes in stimulus feature-specific responses. Electrodes showing a frequency preference or offset responses were altered following ketamine administration, while those of the AERs were not strongly influenced. However, the frequency preference of a selected electrode was not significantly altered by ketamine administration over time following administration, while the imbalances in the onset and offset persisted over the course of 150 min following ketamine administration in all three monkeys. These results suggest that ketamine affects the ability to distinguish between sound frequency and duration in different ways. In conclusion, future research on the NMDA sensitivity of cortical wide sensory information processing may provide a new perspective into the development of nonhuman primate models of psychiatric disorders.

Online Detection of Multiple Stimulus Changes Based on Single Neuron Interspike Intervals

Nervous systems need to detect stimulus changes based on their neuronal responses without using any additional information on the number, times, and types of stimulus changes. Here, two relatively simple, biologically realistic change point detection methods are compared with two common analysis methods. The four methods are applied to intra- and extracellularly recorded responses of a single cricket interneuron (AN2) to acoustic simulation. Solely based on these recorded responses, the methods should detect an unknown number of different types of sound intensity in- and decreases shortly after their occurrences. For this task, the methods rely on calculating an adjusting interspike interval (ISI). Both simple methods try to separate responses to intensity in- or decreases from activity during constant stimulation. The Pure-ISI method performs this task based on the distribution of the ISI, while the ISI-Ratio method uses the ratio of actual and previous ISI. These methods are compared to the frequently used Moving-Average method, which calculates mean and standard deviation of the instantaneous spike rate in a moving interval. Additionally, a classification method provides the upper limit of the change point detection performance that can be expected for the cricket interneuron responses. The classification learns the statistical properties of the actual and previous ISI during stimulus changes and constant stimulation from a training data set. The main results are: (1) The Moving-Average method requires a stable activity in a long interval to estimate the previous activity, which was not always given in our data set. (2) The Pure-ISI method can reliably detect stimulus intensity increases when the neuron bursts, but it fails to identify intensity decreases. (3) The ISI-Ratio method detects stimulus in- and decreases well, if the spike train is not too noisy. (4) The classification method shows good performance for the detection of stimulus in- and decreases. But due to the statistical learning, this method tends to confuse responses to constant stimulation with responses triggered by a stimulus change. Our results suggest that stimulus change detection does not require computationally costly mechanisms. Simple nervous systems like the cricket's could effectively apply ISI-Ratios to solve this fundamental task.