The ascending and descending projections of the central auditory system form multiple tonotopic loops. This study specifically examines the tonotopic pathway from the auditory thalamus to the auditory cortex and then to the auditory midbrain in mice. We observed the changes of receptive fields in the central nucleus of the inferior colliculus of the midbrain evoked by focal electrical stimulation of the ventral division of the medial geniculate body of the thalamus. The receptive field of an auditory neuron was characterized by five parameters: the best frequency, minimum threshold, bandwidth, size of receptive field, and average spike number. We found that focal thalamic stimulation changed the parametric values characterizing the recorded collicular receptive fields toward those characterizing the stimulated thalamic receptive fields. Cortical inactivation with muscimol prevented the development of the collicular plasticity induced by focal thalamic stimulation. Our data suggest that the intact colliculo-thalamo-cortico-collicular loops are important for the coordination of sound-guided plasticity in the central auditory system.

Historically, the study of multisensory processing has examined the function of the definitive neuron type, the bimodal neuron. These neurons are excited by inputs from more than one sensory modality and, when multisensory stimuli are present, they can integrate their responses in a predictable manner. However, recent studies have revealed that multisensory processing in the cortex is not restricted to bimodal neurons. The present investigation sought to examine the potential for multisensory processing in non-bimodal ('unimodal') neurons in the retinotopically-organized posterolateral lateral suprasylvian (PLLS) area of the cat. Standard extracellular recordings were used to measure responses of all neurons encountered to both separate- and combined-modality stimulation. While bimodal neurons behaved as predicted, the surprising result was that 16% of 'unimodal' visual neurons encountered were significantly facilitated by auditory stimuli. Because these 'unimodal' visual neurons did not respond to an auditory stimulus presented alone, but had their visual responses modulated by concurrent auditory stimulation, they represent a new form of multisensory neuron: the subthreshold multisensory neuron. These data also demonstrate that bimodal neurons can no longer be regarded as the exclusive basis for multisensory processing.

People with sensorineural hearing loss have difficulty understanding speech, especially when background sounds are present. A reduction in the ability to resolve the frequency components of complex sounds is one factor contributing to this difficulty. Here, we show that a reduced ability to process the temporal fine structure of sounds plays an important role. Speech sounds were processed by filtering them into 16 adjacent frequency bands. The signal in each band was processed by using the Hilbert transform so as to preserve either the envelope (E, the relatively slow variations in amplitude over time) or the temporal fine structure (TFS, the rapid oscillations with rate close to the center frequency of the band). The band signals were then recombined and the stimuli were presented to subjects for identification. After training, normal-hearing subjects scored perfectly with unprocessed speech, and were approximately 90% correct with E and TFS speech. Both young and elderly subjects with moderate flat hearing loss performed almost as well as normal with unprocessed and E speech but performed very poorly with TFS speech, indicating a greatly reduced ability to use TFS. For the younger hearing-impaired group, TFS scores were highly correlated with the ability to take advantage of temporal dips in a background noise when identifying unprocessed speech. The results suggest that the ability to use TFS may be critical for "listening in the background dips." TFS stimuli may be useful in evaluating impaired hearing and in guiding the design of hearing aids and cochlear implants.

It is still a popular view that primary sensory cortices are unimodal, but recent physiological studies have shown that under certain behavioral conditions primary sensory cortices can also be activated by multiple other modalities. Here, we investigate the anatomical substrate, which may underlie multisensory processes at the level of the primary auditory cortex (field AI), and which may, in turn, enable AI to influence other sensory systems. We approached this issue by means of the axonal transport of the sensitive bidirectional neuronal tracer fluorescein-labeled dextran which was injected into AI of Mongolian gerbils (Meriones unguiculatus). Of the total number of retrogradely labeled cell bodies (i.e. cells of origin of direct projections to AI) found in non-auditory sensory and multisensory brain areas, approximately 40% were in cortical areas and 60% in subcortical structures. Of the cell bodies in the cortical areas about 82% were located in multisensory cortex, viz., the dorsoposterior and ventroposterior, posterior parietal cortex, the claustrum, and the endopiriform nucleus, 10% were located in the primary somatosensory cortex (hindlimb and trunk region), and 8% in secondary visual cortex. The cortical regions with retrogradely labeled cells also contained anterogradely labeled axons and their terminations, i.e. they are also target areas of direct projections from AI. In addition, the primary olfactory cortex was identified as a target area of projections from AI. The laminar pattern of corticocortical connections suggests that AI receives primarily cortical feedback-type inputs and projects in a feedforward manner to its target areas. Of the labeled cell bodies in the subcortical structures, approximately 90% were located in multisensory thalamic, 4% in visual thalamic, and 6% in multisensory lower brainstem structures. At subcortical levels, we observed a similar correspondence of retrogradely labeled cells and anterogradely labeled axons and terminals in visual (posterior limitans thalamic nucleus) and multisensory thalamic nuclei (dorsal and medial division of the medial geniculate body, suprageniculate nucleus, posterior thalamic cell group, zona incerta), and in the multisensory nucleus of the brachium of the inferior colliculus. Retrograde, but not anterograde, labeling was found in the multisensory pontine reticular formation, particularly in the reticulotegmental nucleus of the pons. Conversely, anterograde, but no retrograde, labeling was found in the visual laterodorsal and lateroposterior thalamic nuclei, in the multisensory peripeduncular, posterior intralaminar, and reticular thalamic nuclei, as well as in the multisensory superior and pericentral inferior colliculi (including cuneiform and sagulum nucleus), pontine nuclei, and periaqueductal gray. Our study supports the notion that AI is not merely involved in the analysis of auditory stimulus properties but also in processing of other sensory and multisensory information. Since AI is directly connected to other primary sensory cortices (viz. the somatosensory and olfactory ones) multisensory information is probably also processed in these cortices. This suggests more generally, that primary sensory cortices may not be unimodal.

Recent studies, conducted almost exclusively in primates, have shown that several cortical areas usually associated with modality-specific sensory processing are subject to influences from other senses. Here we demonstrate using single-unit recordings and estimates of mutual information that visual stimuli can influence the activity of units in the auditory cortex of anesthetized ferrets. In many cases, these units were also acoustically responsive and frequently transmitted more information in their spike discharge patterns in response to paired visual-auditory stimulation than when either modality was presented by itself. For each stimulus, this information was conveyed by a combination of spike count and spike timing. Even in primary auditory areas (primary auditory cortex [A1] and anterior auditory field [AAF]), approximately 15% of recorded units were found to have nonauditory input. This proportion increased in the higher level fields that lie ventral to A1/AAF and was highest in the anterior ventral field, where nearly 50% of the units were found to be responsive to visual stimuli only and a further quarter to both visual and auditory stimuli. Within each field, the pure-tone response properties of neurons sensitive to visual stimuli did not differ in any systematic way from those of visually unresponsive neurons. Neural tracer injections revealed direct inputs from visual cortex into auditory cortex, indicating a potential source of origin for the visual responses. Primary visual cortex projects sparsely to A1, whereas higher visual areas innervate auditory areas in a field-specific manner. These data indicate that multisensory convergence and integration are features common to all auditory cortical areas but are especially prevalent in higher areas.

Many models of cortical dynamics have focused on the high-firing regime, in which neurons are driven near their maximal rate. Here we consider the responses of neurons in auditory cortex under typical low-firing rate conditions, when stimuli have not been optimized to drive neurons maximally. We used whole-cell patch-clamp recording in vivo to measure subthreshold membrane potential fluctuations in rat primary auditory cortex in both the anesthetized and awake preparations. By analyzing the subthreshold membrane potential dynamics on single trials, we made inferences about the underlying population activity. We found that, during both spontaneous and evoked responses, membrane potential was highly non-Gaussian, with dynamics consisting of occasional large excursions (sometimes tens of millivolts), much larger than the small fluctuations predicted by most random walk models that predict a Gaussian distribution of membrane potential. Thus, presynaptic inputs under these conditions are organized into quiescent periods punctuated by brief highly synchronous volleys, or "bumps." These bumps were typically so brief that they could not be well characterized as "up states" or "down states." We estimate that hundreds, perhaps thousands, of presynaptic neurons participate in the largest volleys. These dynamics suggest a computational scheme in which spike timing is controlled by concerted firing among input neurons rather than by small fluctuations in a sea of background activity.

Previous studies have shown that processing information in one sensory modality can either be enhanced or attenuated by concurrent stimulation of another modality. Here, we reconcile these apparently contradictory results by showing that the sign of cross-modal interactions depends on whether the content of two modalities is associated or not. When concurrently presented auditory and visual stimuli are paired by chance, cue-induced preparatory neural activity is strongly enhanced in the task-relevant sensory system and suppressed in the irrelevant system. Conversely, when information in the two modalities is reliably associated, activity is enhanced in both systems regardless of which modality is task relevant. Our findings illustrate an ecologically optimal flexibility of the neural mechanisms that govern multisensory processing: facilitation occurs when integration is expected, and suppression occurs when distraction is expected. Because thalamic structures were more active when the senses needed to operate separately, we propose them to serve gatekeeper functions in early cross-modal interactions.

The status of the organization of the auditory corticofugal systems is summarized. These are among the largest pathways in the brain, with descending connections to auditory and non-auditory thalamic, midbrain, and medullary regions. Auditory corticofugal influence thus reaches sites immediately presynaptic to the cortex, sites remote from the cortex, as in periolivary regions that may have a centrifugal role, and to the cochlear nucleus, which could influence early central events in hearing. Other targets include the striatum (possible premotor functions), the amygdala and central gray (prospective limbic and motivational roles), and the pontine nuclei (for precerebellar control). The size, specificity, laminar origins, and morphologic diversity of auditory corticofugal axons is consonant with an interpretation of multiple roles in parallel descending systems.

We continually rely on our ability to segregate the myriad sounds in our environment—phones ringing, people talking—into separate “auditory streams,��? each originating from a different source. In this issue of Neuron, Micheyl et al. provide the most direct evidence to date linking single-unit spiking responses from auditory cortex to the perception of distinct auditory streams.

Sounds commonly occur in sequences, such as in speech. It is therefore important to understand how the occurrence of one sound affects the response to a subsequent sound. We approached this question by determining how a conditioning stimulus alters the response areas of single neurons in the primary auditory cortex (AI) of barbiturate-anesthetized cats. The response areas consisted of responses to stimuli that varied in level at the two ears and delivered at the characteristic frequency of each cell. A binaural conditioning stimulus was then presented >/=50 ms before each of the stimuli comprising the level response area. An effective preceding stimulus alters the shape and severely reduces the size and response magnitude of the level response area. This ability of the preceding stimulus depends on its proximity in the level domain to the level response area, not on its absolute level or on the size of the response it evokes. Preceding stimuli evoke a nonlinear inhibition across the level response area that results in an increased selectivity of a cortical neuron for its preferred binaural stimuli. The selectivity of AI neurons during the processing of a stream of acoustic stimuli is likely to be restricted to a portion of their level response areas apparent in the tone-alone condition. Thus rather than being static, level response areas are fluid; they can vary greatly in extent, shape and response magnitude. The dynamic modulation of the level response area and level selectivity of AI neurons might be related to several tasks confronting the central auditory system.