CLASSIFICATION OF UNIT RESPONSES IN THE AUDITORY CORTEX OF THE UNANAESTHETIZED AND UNRESTRAINED CAT

Cellular and Widefield Imaging of Sound Frequency Organization in Primary and Higher Order Fields of the Mouse Auditory Cortex

The mouse auditory cortex (ACtx) contains two core fields-primary auditory cortex (A1) and anterior auditory field (AAF)-arranged in a mirror reversal tonotopic gradient. The best frequency (BF) organization and naming scheme for additional higher order fields remain a matter of debate, as does the correspondence between smoothly varying global tonotopy and heterogeneity in local cellular tuning. Here, we performed chronic widefield and two-photon calcium imaging from the ACtx of awake Thy1-GCaMP6s reporter mice. Data-driven parcellation of widefield maps identified five fields, including a previously unidentified area at the ventral posterior extreme of the ACtx (VPAF) and a tonotopically organized suprarhinal auditory field (SRAF) that extended laterally as far as ectorhinal cortex. Widefield maps were stable over time, where single pixel BFs fluctuated by less than 0.5 octaves throughout a 1-month imaging period. After accounting for neuropil signal and frequency tuning strength, BF organization in neighboring layer 2/3 neurons was intermediate to the heterogeneous salt and pepper organization and the highly precise local organization that have each been described in prior studies. Multiscale imaging data suggest there is no ultrasonic field or secondary auditory cortex in the mouse. Instead, VPAF and a dorsal posterior (DP) field emerged as the strongest candidates for higher order auditory areas.

Sensory Island Task (SIT): A New Behavioral Paradigm to Study Sensory Perception and Neural Processing in Freely Moving Animals

A central function of sensory systems is the gathering of information about dynamic interactions with the environment during self-motion. To determine whether modulation of a sensory cue was externally caused or a result of self-motion is fundamental to perceptual invariance and requires the continuous update of sensory processing about recent movements. This process is highly context-dependent and crucial for perceptual performances such as decision-making and sensory object formation. Yet despite its fundamental ecological role, voluntary self-motion is rarely incorporated in perceptual or neurophysiological investigations of sensory processing in animals. Here, we present the Sensory Island Task (SIT), a new freely moving search paradigm to study sensory processing and perception. In SIT, animals explore an open-field arena to find a sensory target relying solely on changes in the presented stimulus, which is controlled by closed-loop position tracking in real-time. Within a few sessions, animals are trained via positive reinforcement to search for a particular area in the arena (“target island”), which triggers the presentation of the target stimulus. The location of the target island is randomized across trials, making the modulated stimulus feature the only informative cue for task completion. Animals report detection of the target stimulus by remaining within the island for a defined time (“sit-time”). Multiple “non-target” islands can be incorporated to test psychometric discrimination and identification performance. We exemplify the suitability of SIT for rodents (Mongolian gerbil, Meriones unguiculatus) and small primates (mouse lemur, Microcebus murinus) and for studying various sensory perceptual performances (auditory frequency discrimination, sound source localization, visual orientation discrimination). Furthermore, we show that pairing SIT with chronic electrophysiological recordings allows revealing neuronal signatures of sensory processing under ecologically relevant conditions during goal-oriented behavior. In conclusion, SIT represents a flexible and easily implementable behavioral paradigm for mammals that combines self-motion and natural exploratory behavior to study sensory sensitivity and decision-making and their underlying neuronal processing.

Anesthesia-induced loss of consciousness disrupts auditory responses beyond primary cortex

Despite its ubiquitous use in medicine, and extensive knowledge of its molecular and cellular effects, how anesthesia induces loss of consciousness (LOC) and affects sensory processing remains poorly understood. Specifically, it is unclear whether anesthesia primarily disrupts thalamocortical relay or intercortical signaling. Here we recorded intracranial electroencephalogram (iEEG), local field potentials (LFPs), and single-unit activity in patients during wakefulness and light anesthesia. Propofol infusion was gradually increased while auditory stimuli were presented and patients responded to a target stimulus until they became unresponsive. We found widespread iEEG responses in association cortices during wakefulness, which were attenuated and restricted to auditory regions upon LOC. Neuronal spiking and LFP responses in primary auditory cortex (PAC) persisted after LOC, while responses in higher-order auditory regions were variable, with neuronal spiking largely attenuated. Gamma power induced by word stimuli increased after LOC while its frequency profile slowed, thus differing from local spiking activity. In summary, anesthesia-induced LOC disrupts auditory processing in association cortices while relatively sparing responses in PAC, opening new avenues for future research into mechanisms of LOC and the design of anesthetic monitoring devices.

Age-Related Changes in Temporal Processing of Rapidly-Presented Sound Sequences in the Macaque Auditory Cortex

The mammalian auditory cortex is necessary to resolve temporal features in rapidly-changing sound streams. This capability is crucial for speech comprehension in humans and declines with normal aging. Nonhuman primate studies have revealed detrimental effects of normal aging on the auditory nervous system, and yet the underlying influence on temporal processing remains less well-defined. Therefore, we recorded from the core and lateral belt areas of auditory cortex when awake young and old monkeys listened to tone-pip and noise-burst sound sequences. Elevated spontaneous and stimulus-driven activity were the hallmark characteristics in old monkeys. These old neurons showed isomorphic-like discharge patterns to stimulus envelopes, though their phase-locking was less precise. Functional preference in temporal coding between the core and belt existed in the young monkeys but was mostly absent in the old monkeys, in which old belt neurons showed core-like response profiles. Finally, the analysis of population activity patterns indicated that the aged auditory cortex demonstrated a homogenous, distributed coding strategy, compared to the selective, sparse coding strategy observed in the young monkeys. Degraded temporal fidelity and highly-responsive, broadly-tuned cortical responses could underlie how aged humans have difficulties to resolve and track dynamic sounds leading to speech processing deficits.

State-dependent geometry of population activity in rat auditory cortex

The accuracy of the neural code depends on the relative embedding of signal and noise in the activity of neural populations. Despite a wealth of theoretical work on population codes, there are few empirical characterizations of the high-dimensional signal and noise subspaces. We studied the geometry of population codes in the rat auditory cortex across brain states along the activation-inactivation continuum, using sounds varying in difference and mean level across the ears. As the cortex becomes more activated, single-hemisphere populations go from preferring contralateral loud sounds to a symmetric preference across lateralizations and intensities, gain-modulation effectively disappears, and the signal and noise subspaces become approximately orthogonal to each other and to the direction corresponding to global activity modulations. Level-invariant decoding of sound lateralization also becomes possible in the active state. Our results provide an empirical foundation for the geometry and state-dependence of cortical population codes.

Are We Ready for Real-world Neuroscience?

Real-world environments are typically dynamic, complex, and multisensory in nature and require the support of top-down attention and memory mechanisms for us to be able to drive a car, make a shopping list, or pour a cup of coffee. Fundamental principles of perception and functional brain organization have been established by research utilizing well-controlled but simplified paradigms with basic stimuli. The last 30 years ushered a revolution in computational power, brain mapping, and signal processing techniques. Drawing on those theoretical and methodological advances, over the years, research has departed more and more from traditional, rigorous, and well-understood paradigms to directly investigate cognitive functions and their underlying brain mechanisms in real-world environments. These investigations typically address the role of one or, more recently, multiple attributes of real-world environments. Fundamental assumptions about perception, attention, or brain functional organization have been challenged-by studies adapting the traditional paradigms to emulate, for example, the multisensory nature or varying relevance of stimulation or dynamically changing task demands. Here, we present the state of the field within the emerging heterogeneous domain of real-world neuroscience. To be precise, the aim of this Special Focus is to bring together a variety of the emerging "real-world neuroscientific" approaches. These approaches differ in their principal aims, assumptions, or even definitions of "real-world neuroscience" research. Here, we showcase the commonalities and distinctive features of the different "real-world neuroscience" approaches. To do so, four early-career researchers and the speakers of the Cognitive Neuroscience Society 2017 Meeting symposium under the same title answer questions pertaining to the added value of such approaches in bringing us closer to accurate models of functional brain organization and cognitive functions.

On the Timing of Signals in Multisensory Integration and Crossmodal Interactions: a Scoping Review

A scoping review was undertaken to explore research investigating early interactions and integration of auditory and visual stimuli in the human brain. The focus was on methods used to study low-level multisensory temporal processing using simple stimuli in humans, and how this research has informed our understanding of multisensory perception. The study of multisensory temporal processing probes how the relative timing between signals affects perception. Several tasks, illusions, computational models, and neuroimaging techniques were identified in the literature search. Research into early audiovisual temporal processing in special populations was also reviewed. Recent research has continued to provide support for early integration of crossmodal information. These early interactions can influence higher-level factors, and vice versa. Temporal relationships between auditory and visual stimuli influence multisensory perception, and likely play a substantial role in solving the 'correspondence problem' (how the brain determines which sensory signals belong together, and which should be segregated).

Muscarinic receptors regulate auditory and prefrontal cortical communication during auditory processing

Much of our understanding about how acetylcholine modulates prefrontal cortical (PFC) networks comes from behavioral experiments that examine cortical dynamics during highly attentive states. However, much less is known about how PFC is recruited during passive sensory processing and how acetylcholine may regulate connectivity between cortical areas outside of task performance. To investigate the involvement of PFC and cholinergic neuromodulation in passive auditory processing, we performed simultaneous recordings in the auditory cortex (AC) and PFC in awake head fixed mice presented with a white noise auditory stimulus in the presence or absence of local cholinergic antagonists in AC. We found that a subset of PFC neurons were strongly driven by auditory stimuli even when the stimulus had no associative meaning, suggesting PFC monitors stimuli under passive conditions. We also found that cholinergic signaling in AC shapes the strength of auditory driven responses in PFC, by modulating the intra-cortical sensory response through muscarinic interactions in AC. Taken together, these findings provide novel evidence that cholinergic mechanisms have a continuous role in cortical gating through muscarinic receptors during passive processing and expand traditional views of prefrontal cortical function and the contributions of cholinergic modulation in cortical communication.

Cortical Coding of Auditory Features

How the cerebral cortex encodes auditory features of biologically important sounds, including speech and music, is one of the most important questions in auditory neuroscience. The pursuit to understand related neural coding mechanisms in the mammalian auditory cortex can be traced back several decades to the early exploration of the cerebral cortex. Significant progress in this field has been made in the past two decades with new technical and conceptual advances. This article reviews the progress and challenges in this area of research.

Rate, not selectivity, determines neuronal population coding accuracy in auditory cortex

The notion that neurons with higher selectivity carry more information about external sensory inputs is widely accepted in neuroscience. High-selectivity neurons respond to a narrow range of sensory inputs, and thus would be considered highly informative by rejecting a large proportion of possible inputs. In auditory cortex, neuronal responses are less selective immediately after the onset of a sound and then become highly selective in the following sustained response epoch. These 2 temporal response epochs have thus been interpreted to encode first the presence and then the content of a sound input. Contrary to predictions from that prevailing theory, however, we found that the neural population conveys similar information about sound input across the 2 epochs in spite of the neuronal selectivity differences. The amount of information encoded turns out to be almost completely dependent upon the total number of population spikes in the read-out window for this system. Moreover, inhomogeneous Poisson spiking behavior is sufficient to account for this property. These results imply a novel principle of sensory encoding that is potentially shared widely among multiple sensory systems.

Limitations of Neural Map Topography for Decoding Spatial Information

Topographic maps are common throughout the nervous system, yet their functional role is still unclear. In particular, whether they are necessary for decoding sensory stimuli is unknown. Here we examined this question by recording population activity at the cellular level from the larval zebrafish tectum in response to visual stimuli at three closely spaced locations in the visual field. Due to map imprecision, nearby stimulus locations produced intermingled tectal responses, and decoding based on map topography yielded an accuracy of only 64%. In contrast, maximum likelihood decoding of stimulus location based on the statistics of the evoked activity, while ignoring any information about the locations of neurons in the map, yielded an accuracy close to 100%. A simple computational model of the zebrafish visual system reproduced these results. Although topography is a useful initial decoding strategy, we suggest it may be replaced by better methods following visual experience.

SIGNIFICANCE STATEMENT

A very common feature of brain wiring is that neighboring points on a sensory surface (eg, the retina) are connected to neighboring points in the brain. It is often assumed that this "topography" of wiring is essential for decoding sensory stimuli. However, here we show in the developing zebrafish that topographic decoding performs very poorly compared with methods that do not rely on topography. This suggests that, although wiring topography could provide a starting point for decoding at a very early stage in development, it may be replaced by more accurate methods as the animal gains experience of the world.

Local versus global scales of organization in auditory cortex

Topographic organization is a hallmark of sensory cortical organization. Topography is robust at spatial scales ranging from hundreds of microns to centimeters, but can dissolve at the level of neighboring neurons or subcellular compartments within a neuron. This dichotomous spatial organization is especially pronounced in the mouse auditory cortex, where an orderly tonotopic map can arise from heterogeneous frequency tuning between local neurons. Here, we address a debate surrounding the robustness of tonotopic organization in the auditory cortex that has persisted in some form for over 40 years. Drawing from various cortical areas, cortical layers, recording methodologies, and species, we describe how auditory cortical circuitry can simultaneously support a globally systematic, yet locally heterogeneous representation of this fundamental sound property.

Blurry topography for precise target-distance computations in the auditory cortex of echolocating bats

Echolocating bats use the time from biosonar pulse emission to the arrival of echo (defined as echo delay) to calculate the space depth of targets. In the dorsal auditory cortex of several species, neurons that encode increasing echo delays are organized rostrocaudally in a topographic arrangement defined as chronotopy. Precise chronotopy could be important for precise target-distance computations. Here we show that in the cortex of three echolocating bat species (Pteronotus quadridens, Pteronotus parnellii and Carollia perspicillata), chronotopy is not precise but blurry. In all three species, neurons throughout the chronotopic map are driven by short echo delays that indicate the presence of close targets and the robustness of map organization depends on the parameter of the receptive field used to characterize neuronal tuning. The timing of cortical responses (latency and duration) provides a binding code that could be important for assembling acoustic scenes using echo delay information from objects with different space depths.

Generation of intensity selectivity by differential synaptic tuning: fast-saturating excitation but slow-saturating inhibition

Intensity defines one fundamental aspect of sensory information and is specifically represented in each sensory modality. Interestingly, only in the central auditory system are intensity-selective neurons evolved. These neurons are characterized by nonmonotonic response-level functions. The synaptic circuitry mechanisms underlying the generation of intensity selectivity from nonselective auditory nerve inputs remain largely unclear. Here, we performed in vivo whole-cell recordings from pyramidal neurons in the rat dorsal cochlear nucleus (DCN), where intensity selectivity first emerges along the auditory neuraxis. Our results revealed that intensity-selective cells received fast-saturating excitation but slow-saturating inhibition with intensity increments, whereas in intensity-nonselective cells excitation and inhibition were similarly slow-saturating. The differential intensity tuning profiles of the monotonic excitation and inhibition qualitatively determined the intensity selectivity of output responses. In addition, the selectivity was further strengthened by significantly lower excitation/inhibition ratios at high-intensity levels compared with intensity-nonselective neurons. Our results demonstrate that intensity selectivity in the DCN is generated by extracting the difference between tuning profiles of nonselective excitatory and inhibitory inputs, which we propose can be achieved through a differential circuit mediated by feedforward inhibition.

Does a pitch center exist in auditory cortex?

Pitch perception is an important component of hearing, allowing us to appreciate melodies and harmonies as well as recognize prosodic cues in speech. Multiple studies over the last decade have suggested that pitch is represented by a pitch-processing center in auditory cortex. However, recent data (Barker D, Plack CJ, Hall DA. Cereb Cortex. In press; Hall DA, Plack CJ. Cereb Cortex 19: 576-585, 2009) now challenge these previous claims of a human "pitch center."

From elementary synaptic circuits to information processing in primary auditory cortex

A key for understanding how information is processed in the cortex is to unravel the dauntingly complex cortical neural circuitry. Recent technical innovations, in particular the in vivo whole-cell voltage-clamp recording techniques, make it possible to directly dissect the excitatory and inhibitory inputs underlying an individual cortical neuron's processing function. This method provides an essential complement to conventional approaches, with which the transfer functions of the neural system are derived by correlating neuronal spike outputs to sensory inputs. Here, we intend to introduce a potentially systematic strategy for resolving the structure of functional synaptic circuits. As complex circuits can be built upon elementary modules, the primary focus of this strategy is to identify elementary synaptic circuits and determine how these circuit units contribute to specific processing functions. This review will summarize recent studies on functional synaptic circuits in the primary auditory cortex, comment on existing experimental techniques for in vivo circuitry studies, and provide a perspective on immediate future directions.

Evaluation of techniques used to estimate cortical feature maps

Functional properties of neurons are often distributed nonrandomly within a cortical area and form topographic maps that reveal insights into neuronal organization and interconnection. Some functional maps, such as in visual cortex, are fairly straightforward to discern with a variety of techniques, while other maps, such as in auditory cortex, have resisted easy characterization. In order to determine appropriate protocols for establishing accurate functional maps in auditory cortex, artificial topographic maps were probed under various conditions, and the accuracy of estimates formed from the actual maps was quantified. Under these conditions, low-complexity maps such as sound frequency can be estimated accurately with as few as 25 total samples (e.g., electrode penetrations or imaging pixels) if neural responses are averaged together. More samples are required to achieve the highest estimation accuracy for higher complexity maps, and averaging improves map estimate accuracy even more than increasing sampling density. Undersampling without averaging can result in misleading map estimates, while undersampling with averaging can lead to the false conclusion of no map when one actually exists. Uniform sample spacing only slightly improves map estimation over nonuniform sample spacing typical of serial electrode penetrations. Tessellation plots commonly used to visualize maps estimated using nonuniform sampling are always inferior to linearly interpolated estimates, although differences are slight at higher sampling densities. Within primary auditory cortex, then, multiunit sampling with at least 100 samples would likely result in reasonable feature map estimates for all but the highest complexity maps and the highest variability that might be expected.

The role of attention in auditory information processing as revealed by event-related potentials and other brain measures of cognitive function

This article examines the role of attention and automaticity in auditory processing as revealed by event-related potential (ERP) research. An ERP component called the mismatch negativity, generated by the brain's automatic response to changes in repetitive auditory input, reveals that physical features of auditory stimuli are fully processed whether or not they are attended. It also suggests that there exist precise neuronal representations of the physical features of recent auditory stimuli, perhaps the traces underlying acoustic sensory (“echoic”) memory. A mechanism of passive attention switching in response to changes in repetitive input is also implicated.

Conscious perception of discrete acoustic stimuli might be mediated by some of the mechanisms underlying another ERP component (NI), one sensitive to stimulus onset and offset. Frequent passive attentional shifts might accountforthe effect cognitive psychologists describe as “the breakthrough of the unattended” (Broadbent 1982), that is, that even unattended stimuli may be semantically processed, without assuming automatic semantic processing or late selection in selective attention.

The processing negativity supports the early-selection theory and may arise from a mechanism for selectively attending to stimuli defined by certain features. This stimulus selection occurs in the form ofa matching process in which each input is compared with the “attentional trace,” a voluntarily maintained representation of the task-relevant features of the stimulus to be attended. The attentional mechanism described might underlie the stimulus-set mode of attention proposed by Broadbent. Finally, a model of automatic and attentional processing in audition is proposed that is based mainly on the aforementioned ERP components and some other physiological measures.

Linking topography to tonotopy in the mouse auditory thalamocortical circuit

The mouse sensory neocortex is reported to lack several hallmark features of topographic organization such as ocular dominance and orientation columns in primary visual cortex or fine-scale tonotopy in primary auditory cortex (AI). Here, we re-examined the question of auditory functional topography by aligning ultra-dense receptive field maps from the auditory cortex and thalamus of the mouse in vivo with the neural circuitry contained in the auditory thalamocortical slice in vitro. We observed precisely organized tonotopic maps of best frequency (BF) in the middle layers of AI and the anterior auditory field as well as in the ventral and medial divisions of the medial geniculate body (MGBv and MGBm, respectively). Tracer injections into distinct zones of the BF map in AI retrogradely labeled topographically organized MGBv projections and weaker, mixed projections from MGBm. Stimulating MGBv along the tonotopic axis in the slice produced an orderly shift of voltage-sensitive dye (VSD) signals along the AI tonotopic axis, demonstrating topography in the mouse thalamocortical circuit that is preserved in the slice. However, compared with BF maps of neuronal spiking activity, the topographic order of subthreshold VSD maps was reduced in layer IV and even further degraded in layer II/III. Therefore, the precision of AI topography varies according to the source and layer of the mapping signal. Our findings further bridge the gap between in vivo and in vitro approaches for the detailed cellular study of auditory thalamocortical circuit organization and plasticity in the genetically tractable mouse model.

Subset of thin spike cortical neurons preserve the peripheral encoding of stimulus onsets

An important question in auditory neuroscience concerns how the neural representation of sound features changes from the periphery to the cortex. Here we focused on the encoding of sound onsets and we used a modeling approach to explore the degree to which auditory cortical neurons follow a similar envelope integration mechanism found at the auditory periphery. Our "forward" model was able to predict relatively accurately the timing of first spikes evoked by natural communication calls in the auditory cortex of awake, head-restrained mice, but only for a subset of cortical neurons. These neurons were systematically different in their encoding of the calls, exhibiting less call selectivity, shorter latency, greater precision, and more transient spiking compared with the same factors of their poorly predicted counterparts. Importantly, neurons that fell into this best-predicted group all had thin spike waveforms, suggestive of suspected interneurons conveying feedforward inhibition. Indeed, our population of call-excited thin spike neurons had significantly higher spontaneous rates and larger frequency tuning bandwidths than those of thick spike neurons. Thus the fidelity of our model's first spike predictions segregated neurons into one earlier responding subset, potentially dominated by suspected interneurons, which preserved a peripheral mechanism for encoding sound onsets and another longer latency subset that reflected higher, likely centrally constructed nonlinearities. These results therefore provide support for the hypothesis that physiologically distinct subclasses of neurons in the auditory cortex may contribute hierarchically to the representation of natural stimuli.

Spontaneous activity resembling tone-evoked activity in the primary auditory cortex of guinea pigs

In the primary auditory cortex (AI), a pure tone evokes propagating activity along a strip of the cortex. We have previously shown that focal activation of AI triggers autonomously propagating activity that resembles tone-evoked activity (Song et al., 2006). Because a focal spontaneous activity is expected to trigger similar activity propagation, spontaneous activity resembling tone-evoked activity may exist in AI. Here we tested this possibility by optical imaging of AI in guinea pigs. After obtaining tone-evoked activities, we made long-duration optical recordings (9-40s) and isolated spontaneous activities from respiration and heartbeat noises using independent component analyses. Spontaneous activities were found all over AI, in all animals examined. Of all spontaneous events, 33.6% showed significant correlation in spatio-temporal pattern with tone-evoked activities. Simulation using a model that captures the temporal feature of spontaneous response in single channels but sets no constraint among channels, generated no spontaneous events that resembled tone-evoked activations. These results show the existence of spontaneous events similar in spatio-temporal pattern to tone-evoked activations in AI. Such spontaneous events are likely a manifestation of cortical structures that govern the pattern of distributed activation in AI.

Contribution of inhibition to stimulus selectivity in primary auditory cortex of awake primates

Recent studies have demonstrated the high selectivity of neurons in primary auditory cortex (A1) and a highly sparse representation of sounds by the population of A1 neurons in awake animals. However, the underlying receptive field structures that confer high selectivity on A1 neurons are poorly understood. The sharp tuning of A1 neurons' excitatory receptive fields (RFs) provides a partial explanation of the above properties. However, it remains unclear how inhibitory components of RFs contribute to the selectivity of A1 neurons observed in awake animals. To examine the role of the inhibition in sharpening stimulus selectivity, we have quantitatively analyzed stimulus-induced suppressive effects over populations of single neurons in frequency, amplitude, and time in A1 of awake marmosets. In addition to the well documented short-latency side-band suppression elicited by masking tones around the best frequency (BF) of a neuron, we uncovered long-latency suppressions caused by single-tone stimulation. Such long-latency suppressions also included monotonically increasing suppression with sound level both on-BF and off-BF, and persistent suppression lasting up to 100 ms after stimulus offset in a substantial proportion of A1 neurons. The extent of the suppression depended on the shape of a neuron's frequency-response area ("O" or "V" shaped). These findings suggest that the excitatory RF of A1 neurons is cocooned by wide-ranging inhibition that contributes to the high selectivity in A1 neurons' responses to complex stimuli. Population sparseness of the tone-responsive A1 neuron population may also be a consequence of this pervasive inhibition.

Nonoverlapping sets of synapses drive on responses and off responses in auditory cortex

Neurons in visual, somatosensory, and auditory cortex can respond to the termination as well as the onset of a sensory stimulus. In auditory cortex, these off responses may underlie the ability of the auditory system to use sound offsets as cues for perceptual grouping. Off responses have been widely proposed to arise from postinhibitory rebound, but this hypothesis has never been directly tested. We used in vivo whole-cell recordings to measure the synaptic inhibition evoked by sound onset. We find that inhibition is invariably transient, indicating that off responses are not caused by postinhibitory rebound in auditory cortical neurons. Instead, on and off responses appear to be driven by distinct sets of synapses, because they have distinct frequency tuning and different excitatory-inhibitory balance. Furthermore, an on-on sequence causes complete forward suppression, whereas an off-on sequence causes no suppression at all. We conclude that on and off responses are driven by largely nonoverlapping sets of synaptic inputs.

Dynamics of spectro-temporal tuning in primary auditory cortex of the awake ferret

We previously characterized the steady-state spectro-temporal tuning properties of cortical cells with respect to broadband sounds by using sounds with sinusoidal spectro-temporal modulation envelope where spectral density and temporal periodicity were constant over several seconds. However, since speech and other natural sounds have spectro-temporal features that change substantially over milliseconds, we study the dynamics of tuning by using stimuli of constant overall intensity, but alternating between a flat spectro-temporal envelope and a modulated envelope with well defined spectral density and temporal periodicity. This allows us to define the tuning of cortical cells to speech-like and other rapid transitions, on the order of milliseconds, as well as the time evolution of this tuning in response to the appearance of new features in a sound. Responses of 92 cells in AI were analyzed based on the temporal evolution of the following measures of tuning after a rapid transition in the stimulus: center of mass and breadth of tuning; separability and direction selectivity; temporal and spectral asymmetry. We find that tuning center of mass increased in 70% of cells for spectral density and in 68% of cells for temporal periodicity, while roughly half of cells (47%) broadened their tuning, with the other half (53%) sharpening tuning. The majority of cells (73%) were initially not direction selective, as measured by an inseparability index, which had an initial low value that then increased to a higher steady state value. Most cells were characterized by temporal symmetry, while spectral symmetry was initially high and then progressed to low steady-state values (61%). We demonstrate that cortical neurons can be characterized by a lag-dependent modulation transfer function. This characterization, when measured through to steady-state, becomes equivalent to the classical spectro-temporal receptive field.

Nonlinear spectrotemporal interactions underlying selectivity for complex sounds in auditory cortex

In the auditory cortex of awake animals, a substantial number of neurons do not respond to pure tones. These neurons have historically been classified as "unresponsive" and even been speculated as being nonauditory. We discovered, however, that many of these neurons in the primary auditory cortex (A1) of awake marmoset monkeys were in fact highly selective for complex sound features. We then investigated how such selectivity might arise from the tone-tuned inputs that these neurons likely receive. We found that these non-tone responsive neurons exhibited nonlinear combination-sensitive responses that require precise spectral and temporal combinations of two tone pips. The nonlinear spectrotemporal maps derived from these neurons were correlated with their selectivity for complex acoustic features. These non-tone responsive and nonlinear neurons were commonly encountered at superficial cortical depths in A1. Our findings demonstrate how temporally and spectrally specific nonlinear integration of putative tone-tuned inputs might underlie a diverse range of high selectivity of A1 neurons in awake animals. We propose that describing A1 neurons with complex response properties in terms of tone-tuned input channels can conceptually unify a wide variety of observed neural selectivity to complex sounds into a lower dimensional description.