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.

Distinct Manifestations of Cooperative, Multidimensional Stimulus Representations in Different Auditory Forebrain Stations.

Classic spectrotemporal receptive fields (STRFs) for auditory neurons are usually expressed as a single linear filter representing a single encoded stimulus feature. Multifilter STRF models represent the stimulus-response relationship of primary auditory cortex (A1) neurons more accurately because they can capture multiple stimulus features. To determine whether multifilter processing is unique to A1, we compared the utility of single-filter versus multifilter STRF models in the medial geniculate body (MGB), anterior auditory field (AAF), and A1 of ketamine-anesthetized cats. We estimated STRFs using both spike-triggered average (STA) and maximally informative dimension (MID) methods. Comparison of basic filter properties of first maximally informative dimension (MID1) and second maximally informative dimension (MID2) in the 3 stations revealed broader spectral integration of MID2s in MGBv and A1 as opposed to AAF. MID2 peak latency was substantially longer than for STAs and MID1s in all 3 stations. The 2-filter MID model captured more information and yielded better predictions in many neurons from all 3 areas but disproportionately more so in AAF and A1 compared with MGBv. Significantly, information-enhancing cooperation between the 2 MIDs was largely restricted to A1 neurons. This demonstrates significant differences in how these 3 forebrain stations process auditory information, as expressed in effective and synergistic multifilter processing.

Anisomorphic cortical reorganization in asymmetric sensorineural hearing loss.

Acoustic trauma or inner ear disease may predominantly injure one ear, causing asymmetric sensorineural hearing loss (SNHL). While characteristic frequency (CF) map plasticity of primary auditory cortex (AI) contralateral to the injured ear has been detailed, there is no study that also evaluates ipsilateral AI to compare cortical reorganization across both hemispheres. We assess whether the normal isomorphic mirror-image relationship between the two hemispheres is maintained or disrupted in mild-to-moderate asymmetric SNHL of adult squirrel monkeys. At week 24 after induction of acoustic injury to the right ear, functional organization of the two hemispheres differs in direction and magnitude of interaural CF difference, percentage of recording sites with spectrally nonoverlapping binaural activation, and the concurrence of peripheral and central activation thresholds. The emergence of this anisomorphic cortical reorganization of the two hemispheres is replicated by simulation based on spike timing-dependent plasticity, where 1) AI input from the contralateral ear is dominant, 2) reestablishment of relatively shorter contralateral ear input timing drives reorganization, and 3) only AI contralateral to the injured ear undergoes major realignment of interaural frequency maps that evolve over months. Asymmetric SNHL disrupts isomorphic organization between the two hemispheres and results in relative local hemispheric autonomy, potentially impairing performance of tasks that require binaural input alignment or interhemispheric processing.NEW & NOTEWORTHY Mild-to-moderate hearing loss in one ear and essentially normal hearing in the other triggers cortical reorganization that is different in the two hemispheres. Asymmetry of cochlea sensitivities does not simply propagate to the two auditory cortices in mirror-image fashion. The resulting anisomorphic cortical reorganization may be a neurophysiological basis of clinical deficits in asymmetric hearing loss, such as difficulty with hearing in noise, impaired spatial hearing, and accelerated decline of the poorer ear.

Auditory cortical local subnetworks are characterized by sharply synchronous activity.

In primary auditory cortex (AI), broadly correlated firing has been commonly observed. In contrast, sharply synchronous firing has rarely been seen and has not been well characterized. Therefore, we examined cat AI local subnetworks using cross-correlation and spectrotemporal receptive field (STRF) analysis for neighboring neurons. Sharply synchronous firing responses were observed predominantly for neurons separated by <150 µm. This high synchrony was independent of layers and was present between all distinguishable cell types. The sharpest synchrony was seen in supragranular layers and between regular spiking units. Synchronous spikes conveyed more stimulus information than nonsynchronous spikes. Neighboring neurons in all layers had similar best frequencies and similar STRFs, with the highest similarity in supragranular and granular layers. Spectral tuning selectivity and latency were only moderately conserved in these local, high-synchrony AI subnetworks. Overall, sharp synchrony is a specific characteristic of fine-scale networks within the AI and local functional processing is well ordered and similar, but not identical, for neighboring neurons of all cell types.

Primary auditory cortical responses to electrical stimulation of the thalamus.

Cochlear implant electrical stimulation of the auditory system to rehabilitate deafness has been remarkably successful. Its deployment requires both an intact auditory nerve and a suitably patent cochlear lumen. When disease renders prerequisite conditions impassable, such as in neurofibromatosis type II and cochlear obliterans, alternative treatment targets are considered. Electrical stimulation of the cochlear nucleus and midbrain in humans has delivered encouraging clinical outcomes, buttressing the promise of central auditory prostheses to mitigate deafness in those who are not candidates for cochlear implantation. In this study we explored another possible implant target: the auditory thalamus. In anesthetized cats, we first presented pure tones to determine frequency preferences of thalamic and cortical sites. We then electrically stimulated tonotopically organized thalamic sites while recording from primary auditory cortical sites using a multichannel recording probe. Cathode-leading biphasic thalamic stimulation thresholds that evoked cortical responses were much lower than published accounts of cochlear and midbrain stimulation. Cortical activation dynamic ranges were similar to those reported for cochlear stimulation, but they were narrower than those found through midbrain stimulation. Our results imply that thalamic stimulation can activate auditory cortex at low electrical current levels and suggest an auditory thalamic implant may be a viable central auditory prosthesis.

Receptive field dimensionality increases from the auditory midbrain to cortex.

In the primary auditory cortex, spectrotemporal receptive fields (STRFs) are composed of multiple independent components that capture the processing of disparate stimulus aspects by any given neuron. The origin of these multidimensional stimulus filters in the central auditory system is unknown. To determine whether multicomponent STRFs emerge prior to the forebrain, we recorded from single neurons in the main obligatory station of the auditory midbrain, the inferior colliculus. By comparing results of different spike-triggered techniques, we found that the neural responses in the inferior colliculus can be accounted for by a single stimulus filter. This was observed for all temporal response patterns, from strongly phasic to tonic. Our results reveal that spectrotemporal stimulus encoding undergoes a fundamental transformation along the auditory neuraxis, with the emergence of multidimensional receptive fields beyond the auditory midbrain.

Hierarchical computation in the canonical auditory cortical circuit.

Sensory cortical anatomy has identified a canonical microcircuit underlying computations between and within layers. This feed-forward circuit processes information serially from granular to supragranular and to infragranular layers. How this substrate correlates with an auditory cortical processing hierarchy is unclear. We recorded simultaneously from all layers in cat primary auditory cortex (AI) and estimated spectrotemporal receptive fields (STRFs) and associated nonlinearities. Spike-triggered averaged STRFs revealed that temporal precision, spectrotemporal separability, and feature selectivity varied with layer according to a hierarchical processing model. STRFs from maximally informative dimension (MID) analysis confirmed hierarchical processing. Of two cooperative MIDs identified for each neuron, the first comprised the majority of stimulus information in granular layers. Second MID contributions and nonlinear cooperativity increased in supragranular and infragranular layers. The AI microcircuit provides a valid template for three independent hierarchical computation principles. Increases in processing complexity, STRF cooperativity, and nonlinearity correlate with the synaptic distance from granular layers.

Improved stimulus representation by short interspike intervals in primary auditory cortex.

We analyzed the receptive field information conveyed by interspike intervals (ISIs) in the auditory cortex. In the visual system, different ISIs may both code for different visual features and convey differing amounts of stimulus information. To determine their potential role in auditory signal processing, we obtained extracellular recordings in the primary auditory cortex (AI) of the cat while presenting a dynamic moving ripple stimulus and then used the responses to construct spectrotemporal receptive fields (STRFs). For each neuron, we constructed three STRFs, one for short-ISI events (ISI < 15 ms); one for isolated, long-ISI events (ISI > 15 ms); and one including all events. To characterize stimulus encoding, we calculated the feature selectivity and event information for each of the STRFs. Short-ISI spikes were more feature selective and conveyed information more efficiently. The different ISI regimens of AI neurons did not represent different stimulus features, but short-ISI spike events did contribute over-proportionately to the full spike train STRF information. Thus short-ISIs constitute a robust representation of auditory features, and they are particularly effective at driving postsynaptic activity. This suggests that short-ISI events are especially suited to provide noise immunity and high-fidelity information transmission in AI.

Plasticity of Multidimensional Receptive Fields in Core Rat Auditory Cortex Directed by Sound Statistics.

Sensory cortical neurons can nonlinearly integrate a wide range of inputs. The outcome of this nonlinear process can be approximated by more than one receptive field component or filter to characterize the ensuing stimulus preference. The functional properties of multidimensional filters are, however, not well understood. Here we estimated two spectrotemporal receptive fields (STRFs) per neuron using maximally informative dimension analysis. We compared their temporal and spectral modulation properties and determined the stimulus information captured by the two STRFs in core rat auditory cortical fields, primary auditory cortex (A1) and ventral auditory field (VAF). The first STRF is the dominant filter and acts as a sound feature detector in both fields. The second STRF is less feature specific, preferred lower modulations, and had less spike information compared to the first STRF. The information jointly captured by the two STRFs was larger than that captured by the sum of the individual STRFs, reflecting nonlinear interactions of two filters. This information gain was larger in A1. We next determined how the acoustic environment affects the structure and relationship of these two STRFs. Rats were exposed to moderate levels of spectrotemporally modulated noise during development. Noise exposure strongly altered the spectrotemporal preference of the first STRF in both cortical fields. The interaction between the two STRFs was reduced by noise exposure in A1 but not in VAF. The results reveal new functional distinctions between A1 and VAF indicating that (i) A1 has stronger interactions of the two STRFs than VAF, (ii) noise exposure diminishes modulation parameter representation contained in the noise more strongly for the first STRF in both fields, and (iii) plasticity induced by noise exposure can affect the strength of filter interactions in A1. Taken together, ascertaining two STRFs per neuron enhances the understanding of cortical information processing and plasticity effects in core auditory cortex.

Information diversity in individual auditory cortical neurons is associated with functionally distinct coordinated neuronal ensembles.

Neuronal activity in auditory cortex is often highly synchronous between neighboring neurons. Such coordinated activity is thought to be crucial for information processing. We determined the functional properties of coordinated neuronal ensembles (cNEs) within primary auditory cortical (AI) columns relative to the contributing neurons. Nearly half of AI cNEs showed robust spectro-temporal receptive fields whereas the remaining cNEs showed little or no acoustic feature selectivity. cNEs can therefore capture either specific, time-locked information of spectro-temporal stimulus features or reflect stimulus-unspecific, less-time specific processing aspects. By contrast, we show that individual neurons can represent both of those aspects through membership in multiple cNEs with either high or absent feature selectivity. These associations produce functionally heterogeneous spikes identifiable by instantaneous association with different cNEs. This demonstrates that single neuron spike trains can sequentially convey multiple aspects that contribute to cortical processing, including stimulus-specific and unspecific information.

Laminar diversity of dynamic sound processing in cat primary auditory cortex.

For primary auditory cortex (AI) laminae, there is little evidence of functional specificity despite clearly expressed cellular and connectional differences. Natural sounds are dominated by dynamic temporal and spectral modulations and we used these properties to evaluate local functional differences or constancies across laminae. To examine the layer-specific processing of acoustic modulation information, we simultaneously recorded from multiple AI laminae in the anesthetized cat. Neurons were challenged with dynamic moving ripple stimuli and we subsequently computed spectrotemporal receptive fields (STRFs). From the STRFs, temporal and spectral modulation transfer functions (tMTFs, sMTFs) were calculated and compared across layers. Temporal and spectral modulation properties often differed between layers. On average, layer II/III and VI neurons responded to lower temporal modulations than those in layer IV. tMTFs were mainly band-pass in granular layer IV and became more low-pass in infragranular layers. Compared with layer IV, spectral MTFs were broader and their upper cutoff frequencies higher in layers V and VI. In individual penetrations, temporal modulation preference was similar across layers for roughly 70% of the penetrations, suggesting a common, columnar functional characteristic. By contrast, only about 30% of penetrations showed consistent spectral modulation preferences across layers, indicative of functional laminar diversity or specialization. Since local laminar differences in stimulus preference do not always parallel the main flow of information in the columnar cortical microcircuit, this indicates the influence of additional horizontal or thalamocortical inputs. AI layers that express differing modulation properties may serve distinct roles in the extraction of dynamic sound information, with the differing information specific to the targeted stations of each layer.

Stimulus dependent transformations between synaptic and spiking receptive fields in auditory cortex.

Auditory cortex neurons nonlinearly integrate synaptic inputs from the thalamus and cortex, and generate spiking outputs for simple and complex sounds. Directly comparing synaptic and spiking activity can determine whether this input-output transformation is stimulus-dependent. We employ in vivo whole-cell recordings in the mouse primary auditory cortex, using pure tones and broadband dynamic moving ripple stimuli, to examine properties of functional integration in tonal (TRFs) and spectrotemporal (STRFs) receptive fields. Spectral tuning in STRFs derived from synaptic, subthreshold and spiking responses proves to be substantially more selective than for TRFs. We describe diverse spectral and temporal modulation preferences and distinct nonlinearities, and their modifications between the input and output stages of neural processing. These results characterize specific processing differences at the level of synaptic convergence, integration and spike generation resulting in stimulus-dependent transformation patterns in the primary auditory cortex.

Auditory Cortical Plasticity Dependent on Environmental Noise Statistics.

During critical periods, neural circuits develop to form receptive fields that adapt to the sensory environment and enable optimal performance of relevant tasks. We hypothesized that early exposure to background noise can improve signal-in-noise processing, and the resulting receptive field plasticity in the primary auditory cortex can reveal functional principles guiding that important task. We raised rat pups in different spectro-temporal noise statistics during their auditory critical period. As adults, they showed enhanced behavioral performance in detecting vocalizations in noise. Concomitantly, encoding of vocalizations in noise in the primary auditory cortex improves with noise-rearing. Significantly, spectro-temporal modulation plasticity shifts cortical preferences away from the exposed noise statistics, thus reducing noise interference with the foreground sound representation. Auditory cortical plasticity shapes receptive field preferences to optimally extract foreground information in noisy environments during noise-rearing. Early noise exposure induces cortical circuits to implement efficient coding in the joint spectral and temporal modulation domain.

Spectrotemporal processing differences between auditory cortical fast-spiking and regular-spiking neurons.

Excitatory pyramidal neurons and inhibitory interneurons constitute the main elements of cortical circuitry and have distinctive morphologic and electrophysiological properties. Here, we differentiate them by analyzing the time course of their action potentials (APs) and characterizing their receptive field properties in auditory cortex. Pyramidal neurons have longer APs and discharge as regular-spiking units (RSUs), whereas basket and chandelier cells, which are inhibitory interneurons, have shorter APs and are fast-spiking units (FSUs). To compare these neuronal classes, we stimulated cat primary auditory cortex neurons with a dynamic moving ripple stimulus and constructed single-unit spectrotemporal receptive fields (STRFs) and their associated nonlinearities. FSUs had shorter latencies, broader spectral tuning, greater stimulus specificity, and higher temporal precision than RSUs. The STRF structure of FSUs was more separable, suggesting more independence between spectral and temporal processing regimens. The nonlinearities associated with the two cell classes were indicative of higher feature selectivity for FSUs. These global functional differences between RSUs and FSUs suggest fundamental distinctions between putative excitatory and inhibitory interneurons that shape auditory cortical processing.

Coordinated neuronal ensembles in primary auditory cortical columns.

The synchronous activity of groups of neurons is increasingly thought to be important in cortical information processing and transmission. However, most studies of processing in the primary auditory cortex (AI) have viewed neurons as independent filters; little is known about how coordinated AI neuronal activity is expressed throughout cortical columns and how it might enhance the processing of auditory information. To address this, we recorded from populations of neurons in AI cortical columns of anesthetized rats and, using dimensionality reduction techniques, identified multiple coordinated neuronal ensembles (cNEs), which are groups of neurons with reliable synchronous activity. We show that cNEs reflect local network configurations with enhanced information encoding properties that cannot be accounted for by stimulus-driven synchronization alone. Furthermore, similar cNEs were identified in both spontaneous and evoked activity, indicating that columnar cNEs are stable functional constructs that may represent principal units of information processing in AI.

Multidimensional receptive field processing by cat primary auditory cortical neurons.

The receptive fields of many auditory cortical neurons are multidimensional and are best represented by more than one stimulus feature. The number of these dimensions, their characteristics, and how they differ with stimulus context have been relatively unexplored. Standard methods that are often used to characterize multidimensional stimulus selectivity, such as spike-triggered covariance (STC) or maximally informative dimensions (MIDs), are either limited to Gaussian stimuli or are only able to recover a small number of stimulus features due to data limitations. An information theoretic extension of STC, the maximum noise entropy (MNE) model, can be used with non-Gaussian stimulus distributions to find an arbitrary number of stimulus dimensions. When we applied the MNE model to auditory cortical neurons, we often found more than two stimulus features that influenced neuronal firing. Excitatory and suppressive features coded different acoustic contexts: excitatory features encoded higher temporal and spectral modulations, while suppressive features had lower modulation frequency preferences. We found that the excitatory and suppressive features themselves were sensitive to stimulus context when we employed two stimuli that differed only in their short-term correlation structure: while the linear features were similar, the secondary features were strongly affected by stimulus statistics. These results show that multidimensional receptive field processing is influenced by feature type and stimulus context.

Synchrony, connectivity, and functional similarity in auditory midbrain local circuits.

The central nucleus of the inferior colliculus (ICC) contains a laminar structure that functions as an organizing substrate of ascending inputs and local processing. While topographic distributions of ICC response parameters within and across laminae have been reported, the functional micro-organization of the ICC is less well understood. For pairs of neighboring ICC neurons, we examined the nature of functional connectivity and receptive field preferences to gain a better understanding of the structure and function of local circuits. By recording from pairs of adjacent neurons and presenting pure-tone and dynamic broad-band stimulation, we estimated functional connectivity and local differences in frequency response areas (FRAs), spectrotemporal receptive fields (STRFs), nonlinear input/output functions, and single-spike information. From the cross-covariance functions we identified putative unidirectional as well as bidirectional excitatory/inhibitory interactions. STRFs of neighboring neurons strongly conserve best frequency, and moderately agree in STRF similarity, bandwidth, temporal response type, best modulation frequency, nonlinearity structure, and degree of information processing. Excitatory connectivity was stronger and temporally more precise than for inhibitory connections. Neither connection strength nor degree of synchrony correlated with receptive field parameters. The functional similarity of local pairs of ICC neurons was substantially less than for local pairs in the granular layers of primary auditory cortex (AI). These results imply that while the ICC is an obligatory nexus of ascending information, local neurons are comparatively weakly connected and exhibit considerable receptive field variability, potentially reflecting the heterogeneity of converging inputs to ICC functional zones.

Spectrotemporal processing in spectral tuning modules of cat primary auditory cortex.

Spectral integration properties show topographical order in cat primary auditory cortex (AI). Along the iso-frequency domain, regions with predominantly narrowly tuned (NT) neurons are segregated from regions with more broadly tuned (BT) neurons, forming distinct processing modules. Despite their prominent spatial segregation, spectrotemporal processing has not been compared for these regions. We identified these NT and BT regions with broad-band ripple stimuli and characterized processing differences between them using both spectrotemporal receptive fields (STRFs) and nonlinear stimulus/firing rate transformations. The durations of STRF excitatory and inhibitory subfields were shorter and the best temporal modulation frequencies were higher for BT neurons than for NT neurons. For NT neurons, the bandwidth of excitatory and inhibitory subfields was matched, whereas for BT neurons it was not. Phase locking and feature selectivity were higher for NT neurons. Properties of the nonlinearities showed only slight differences across the bandwidth modules. These results indicate fundamental differences in spectrotemporal preferences--and thus distinct physiological functions--for neurons in BT and NT spectral integration modules. However, some global processing aspects, such as spectrotemporal interactions and nonlinear input/output behavior, appear to be similar for both neuronal subgroups. The findings suggest that spectral integration modules in AI differ in what specific stimulus aspects are processed, but they are similar in the manner in which stimulus information is processed.

Hierarchical representations in the auditory cortex.

Understanding the neural mechanisms of invariant object recognition remains one of the major unsolved problems in neuroscience. A common solution that is thought to be employed by diverse sensory systems is to create hierarchical representations of increasing complexity and tolerance. However, in the mammalian auditory system many aspects of this hierarchical organization remain undiscovered, including the prominent classes of high-level representations (that would be analogous to face selectivity in the visual system or selectivity to bird's own song in the bird) and the dominant types of invariant transformations. Here we review the recent progress that begins to probe the hierarchy of auditory representations, and the computational approaches that can be helpful in achieving this feat.

Columnar connectivity and laminar processing in cat primary auditory cortex.

BACKGROUND: Radial intra- and interlaminar connections form a basic microcircuit in primary auditory cortex (AI) that extracts acoustic information and distributes it to cortical and subcortical networks. Though the structure of this microcircuit is known, we do not know how the functional connectivity between layers relates to laminar processing. METHODOLOGY/PRINCIPAL FINDINGS: We studied the relationships between functional connectivity and receptive field properties in this columnar microcircuit by simultaneously recording from single neurons in cat AI in response to broadband dynamic moving ripple stimuli. We used spectrotemporal receptive fields (STRFs) to estimate the relationship between receptive field parameters and the functional connectivity between pairs of neurons. Interlaminar connectivity obtained through cross-covariance analysis reflected a consistent pattern of information flow from thalamic input layers to cortical output layers. Connection strength and STRF similarity were greatest for intralaminar neuron pairs and in supragranular layers and weaker for interlaminar projections. Interlaminar connection strength co-varied with several STRF parameters: feature selectivity, phase locking to the stimulus envelope, best temporal modulation frequency, and best spectral modulation frequency. Connectivity properties and receptive field relationships differed for vertical and horizontal connections. CONCLUSIONS/SIGNIFICANCE: Thus, the mode of local processing in supragranular layers differs from that in infragranular layers. Therefore, specific connectivity patterns in the auditory cortex shape the flow of information and constrain how spectrotemporal processing transformations progress in the canonical columnar auditory microcircuit.