Despite numerous studies of auditory cortical processing in the ferret (Mustela putorius), very little is known about the connections between the different regions of the auditory cortex that have been characterized cytoarchitectonically and physiologically. We examined the distribution of retrograde and anterograde labeling after injecting tracers into one or more regions of ferret auditory cortex. Injections of different tracers at frequency-matched locations in the core areas, the primary auditory cortex (A1) and anterior auditory field (AAF), of the same animal revealed the presence of reciprocal connections with overlapping projections to and from discrete regions within the posterior pseudosylvian and suprasylvian fields (PPF and PSF), suggesting that these connections are frequency specific. In contrast, projections from the primary areas to the anterior dorsal field (ADF) on the anterior ectosylvian gyrus were scattered and non-overlapping, consistent with the non-tonotopic organization of this field. The relative strength of the projections originating in each of the primary fields differed, with A1 predominantly targeting the posterior bank fields PPF and PSF, which in turn project to the ventral posterior field, whereas AAF projects more heavily to the ADF, which then projects to the anteroventral field and the pseudosylvian sulcal cortex. These findings suggest that parallel anterior and posterior processing networks may exist, although the connections between different areas often overlap and interactions were present at all levels.

Cholinergic inputs to the auditory cortex can modulate sensory processing and regulate stimulus-specific plasticity according to the behavioural state of the subject. In order to understand how acetylcholine achieves this, it is essential to elucidate the circuitry by which cholinergic inputs influence the cortex. In this study, we described the distribution of cholinergic neurons in the basal forebrain and their inputs to the auditory cortex of the ferret, a species used increasingly in studies of auditory learning and plasticity. Cholinergic neurons in the basal forebrain, visualized by choline acetyltransferase and p75 neurotrophin receptor immunocytochemistry, were distributed through the medial septum, diagonal band of Broca, and nucleus basalis magnocellularis. Epipial tracer deposits and injections of the immunotoxin ME20.4-SAP (monoclonal antibody specific for the p75 neurotrophin receptor conjugated to saporin) in the auditory cortex showed that cholinergic inputs originate almost exclusively in the ipsilateral nucleus basalis. Moreover, tracer injections in the nucleus basalis revealed a pattern of labelled fibres and terminal fields that resembled acetylcholinesterase fibre staining in the auditory cortex, with the heaviest labelling in layers II/III and in the infragranular layers. Labelled fibres with small en-passant varicosities and simple terminal swellings were observed throughout all auditory cortical regions. The widespread distribution of cholinergic inputs from the nucleus basalis to both primary and higher level areas of the auditory cortex suggests that acetylcholine is likely to be involved in modulating many aspects of auditory processing.

The cerebral cortex plays a critical role in perception and in learning-induced plasticity. We show that reversibly silencing any of the main regions of auditory cortex impairs the ability of adult ferrets to localize sound, with the largest deficit seen after deactivating the primary fields. Although these animals had no trouble localizing longer sound bursts, their performance dropped considerably when auditory spatial cues were altered by occluding one ear with an earplug. In contrast to control ferrets, which recovered their localization abilities with intensive training, adaptation to an earplug was impaired following cortical inactivation, with the greatest disruption in plasticity observed after silencing higher-level cortical areas. These findings imply regional differences in the processing of spatial information across the auditory cortex.

The brain has a remarkable capacity to adapt to changes in sensory inputs and to learn from experience. However, the neural circuits responsible for this flexible processing remain poorly understood. Using optogenetic silencing of ArchT-expressing neurons in adult ferrets, we show that within-trial activity in primary auditory cortex (A1) is required for training-dependent recovery in sound-localization accuracy following monaural deprivation. Because localization accuracy under normal-hearing conditions was unaffected, this highlights a specific role for cortical activity in learning. A1-dependent plasticity appears to leave a memory trace that can be retrieved, facilitating adaptation during a second period of monaural deprivation. However, in ferrets in which learning was initially disrupted by perturbing A1 activity, subsequent optogenetic suppression during training no longer affected localization accuracy when one ear was occluded. After the initial learning phase, the reweighting of spatial cues that primarily underpins this plasticity may therefore occur in A1 target neurons.

Neural adaptation enables sensory information to be represented optimally in the brain despite large fluctuations over time in the statistics of the environment. Auditory contrast gain control represents an important example, which is thought to arise primarily from cortical processing. Here we show that neurons in the auditory thalamus and midbrain of mice show robust contrast gain control, and that this is implemented independently of cortical activity. Although neurons at each level exhibit contrast gain control to similar degrees, adaptation time constants become longer at later stages of the processing hierarchy, resulting in progressively more stable representations. We also show that auditory discrimination thresholds in human listeners compensate for changes in contrast, and that the strength of this perceptual adaptation can be predicted from physiological measurements. Contrast adaptation is therefore a robust property of both the subcortical and cortical auditory system and accounts for the short-term adaptability of perceptual judgments.

Enhanced detection and discrimination, along with faster reaction times, are the most typical behavioural manifestations of the brain's capacity to integrate multisensory signals arising from the same object. In this study, we examined whether multisensory behavioural gains are observable across different components of the localization response that are potentially under the command of distinct brain regions. We measured the ability of ferrets to localize unisensory (auditory or visual) and spatiotemporally coincident auditory-visual stimuli of different durations that were presented from one of seven locations spanning the frontal hemifield. During the localization task, we recorded the head movements made following stimulus presentation, as a metric for assessing the initial orienting response of the ferrets, as well as the subsequent choice of which target location to approach to receive a reward. Head-orienting responses to auditory-visual stimuli were more accurate and faster than those made to visual but not auditory targets, suggesting that these movements were guided principally by sound alone. In contrast, approach-to-target localization responses were more accurate and faster to spatially congruent auditory-visual stimuli throughout the frontal hemifield than to either visual or auditory stimuli alone. Race model inequality analysis of head-orienting reaction times and approach-to-target response times indicates that different processes, probability summation and neural integration, respectively, are likely to be responsible for the effects of multisensory stimulation on these two measures of localization behaviour.

Descending cortical inputs to the superior colliculus (SC) contribute to the unisensory response properties of the neurons found there and are critical for multisensory integration. However, little is known about the relative contribution of different auditory cortical areas to this projection or the distribution of their terminals in the SC. We characterized this projection in the ferret by injecting tracers in the SC and auditory cortex. Large pyramidal neurons were labeled in layer V of different parts of the ectosylvian gyrus after tracer injections in the SC. Those cells were most numerous in the anterior ectosylvian gyrus (AEG), and particularly in the anterior ventral field, which receives both auditory and visual inputs. Labeling was also found in the posterior ectosylvian gyrus (PEG), predominantly in the tonotopically organized posterior suprasylvian field. Profuse anterograde labeling was present in the SC following tracer injections at the site of acoustically responsive neurons in the AEG or PEG, with terminal fields being both more prominent and clustered for inputs originating from the AEG. Terminals from both cortical areas were located throughout the intermediate and deep layers, but were most concentrated in the posterior half of the SC, where peripheral stimulus locations are represented. No inputs were identified from primary auditory cortical areas, although some labeling was found in the surrounding sulci. Our findings suggest that higher level auditory cortical areas, including those involved in multisensory processing, may modulate SC function via their projections into its deeper layers.

Integration of information across the senses is critical for perception and is a common property of neurons in the cerebral cortex, where it is thought to arise primarily from corticocortical connections. Much less is known about the role of subcortical circuits in shaping the multisensory properties of cortical neurons. We show that stimulation of the whiskers causes widespread suppression of sound-evoked activity in mouse primary auditory cortex (A1). This suppression depends on the primary somatosensory cortex (S1), and is implemented through a descending circuit that links S1, via the auditory midbrain, with thalamic neurons that project to A1. Furthermore, a direct pathway from S1 has a facilitatory effect on auditory responses in higher-order thalamic nuclei that project to other brain areas. Crossmodal corticofugal projections to the auditory midbrain and thalamus therefore play a pivotal role in integrating multisensory signals and in enabling communication between different sensory cortical areas.

The precise encoding of temporal features of auditory stimuli by the mammalian auditory system is critical to the perception of biologically important sounds, including vocalizations, speech, and music. In this study, auditory gap-detection behavior was evaluated in adult pigmented ferrets (Mustelid putorius furo) using bandpassed stimuli designed to widely sample the ferret's behavioral and physiological audiogram. Animals were tested under positive operant conditioning, with psychometric functions constructed in response to gap-in-noise lengths ranging from 3 to 270 ms. Using a modified version of this gap-detection task, with the same stimulus frequency parameters, we also tested a cohort of normal-hearing human subjects. Gap-detection thresholds were computed from psychometric curves transformed according to signal detection theory, revealing that for both ferrets and humans, detection sensitivity was worse for silent gaps embedded within low-frequency noise compared with high-frequency or broadband stimuli. Additional psychometric function analysis of ferret behavior indicated effects of stimulus spectral content on aspects of behavioral performance related to decision-making processes, with animals displaying improved sensitivity for broadband gap-in-noise detection. Reaction times derived from unconditioned head-orienting data and the time from stimulus onset to reward spout activation varied with the stimulus frequency content and gap length, as well as the approach-to-target choice and reward location. The present study represents a comprehensive evaluation of gap-detection behavior in ferrets, while similarities in performance with our human subjects confirm the use of the ferret as an appropriate model of temporal processing.