Dissociable Neural Correlates of Multisensory Coherence and Selective Attention.

Previous work has demonstrated that performance in an auditory selective attention task can be enhanced or impaired, depending on whether a task-irrelevant visual stimulus is temporally coherent with a target auditory stream or with a competing distractor. However, it remains unclear how audiovisual (AV) temporal coherence and auditory selective attention interact at the neurophysiological level. Here, we measured neural activity using EEG while human participants (men and women) performed an auditory selective attention task, detecting deviants in a target audio stream.

Interaural time difference sensitivity under binaural cochlear implant stimulation persists at high pulse rates up to 900 pps.

Spatial hearing remains one of the major challenges for bilateral cochlear implant (biCI) users, and early deaf patients in particular are often completely insensitive to interaural time differences (ITDs) delivered through biCIs. One popular hypothesis is that this may be due to a lack of early binaural experience. However, we have recently shown that neonatally deafened rats fitted with biCIs in adulthood quickly learn to discriminate ITDs as well as their normal hearing litter mates, and perform an order of magnitude better than human biCI users.

Hierarchical Deviant Processing in Auditory Cortex of Awake Mice.

Detecting patterns, and noticing unexpected pattern changes, in the environment is a vital aspect of sensory processing. Adaptation and prediction error responses are two components of neural processing related to these tasks, and previous studies in the auditory system in rodents show that these two components are partially dissociable in terms of the topography and latency of neural responses to sensory deviants. However, many previous studies have focused on repetitions of single stimuli, such as pure tones, which have limited ecological validity.

Sensitivity to interaural time differences in the inferior colliculus of cochlear implanted rats with or without hearing experience.

For deaf patients cochlear implants (CIs) can restore substantial amounts of functional hearing. However, binaural hearing, and in particular, the perception of interaural time differences (ITDs) with current CIs has been found to be notoriously poor, especially in the event of early hearing loss. One popular hypothesis for these deficits posits that a lack of early binaural experience may be a principal cause of poor ITD perception in pre-lingually deaf CI patients.

Learning boosts the decoding of sound sequences in rat auditory cortex.

Continuous acoustic streams, such as speech signals, can be chunked into segments containing reoccurring patterns (e.g., words).

Microsecond interaural time difference discrimination restored by cochlear implants after neonatal deafness.

Spatial hearing in cochlear implant (CI) patients remains a major challenge, with many early deaf users reported to have no measurable sensitivity to interaural time differences (ITDs). Deprivation of binaural experience during an early critical period is often hypothesized to be the cause of this shortcoming. However, we show that neonatally deafened (ND) rats provided with precisely synchronized CI stimulation in adulthood can be trained to lateralize ITDs with essentially normal behavioral thresholds near 50 μs.

Rhythmic Temporal Expectation Boosts Neural Activity by Increasing Neural Gain.

Temporal orienting improves sensory processing, akin to other top-down biases. However, it is unknown whether these improvements reflect increased neural gain to any stimuli presented at expected time points, or specific tuning to task-relevant stimulus aspects. Furthermore, while other top-down biases are selective, the extent of trade-offs across time is less well characterized.

Sensory cortex is optimized for prediction of future input.

Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory past that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few moments of video or audio in clips of natural scenes.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded.

Measuring the Performance of Neural Models.

Good metrics of the performance of a statistical or computational model are essential for model comparison and selection. Here, we address the design of performance metrics for models that aim to predict neural responses to sensory inputs. This is particularly difficult because the responses of sensory neurons are inherently variable, even in response to repeated presentations of identical stimuli.

Rhythm Facilitates the Detection of Repeating Sound Patterns.

This study investigates the influence of temporal regularity on human listeners' ability to detect a repeating noise pattern embedded in statistically identical non-repeating noise. Human listeners were presented with white noise stimuli that either contained a frozen segment of noise that repeated in a temporally regular or irregular manner, or did not contain any repetition at all. Subjects were instructed to respond as soon as they detected any repetition in the stimulus.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing.

Unlabelled: Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation.

Periodotopy in the gerbil inferior colliculus: local clustering rather than a gradient map.

Periodicities in sound waveforms are widespread, and shape important perceptual attributes of sound including rhythm and pitch. Previous studies have indicated that, in the inferior colliculus (IC), a key processing stage in the auditory midbrain, neurons tuned to different periodicities might be arranged along a periodotopic axis which runs approximately orthogonal to the tonotopic axis. Here we map out the topography of frequency and periodicity tuning in the IC of gerbils in unprecedented detail, using pure tones and different periodic sounds, including click trains, sinusoidally amplitude modulated (SAM) noise and iterated rippled noise.

Temporal predictability enhances auditory detection.

Periodic stimuli are common in natural environments and are ecologically relevant, for example, footsteps and vocalizations. This study reports a detectability enhancement for temporally cued, periodic sequences. Target noise bursts (embedded in background noise) arriving at the time points which followed on from an introductory, periodic "cue" sequence were more easily detected (by ∼1.

Constructing noise-invariant representations of sound in the auditory pathway.

Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics.

Temporal predictability as a grouping cue in the perception of auditory streams.

This study reports a role of temporal regularity on the perception of auditory streams. Listeners were presented with two-tone sequences in an A-B-A-B rhythm that was either regular or had a controlled amount of temporal jitter added independently to each of the B tones. Subjects were asked to report whether they perceived one or two streams.

Auditory cortex represents both pitch judgments and the corresponding acoustic cues.

The neural processing of sensory stimuli involves a transformation of physical stimulus parameters into perceptual features, and elucidating where and how this transformation occurs is one of the ultimate aims of sensory neurophysiology. Recent studies have shown that the firing of neurons in early sensory cortex can be modulated by multisensory interactions [1-5], motor behavior [1, 3, 6, 7], and reward feedback [1, 8, 9], but it remains unclear whether neural activity is more closely tied to perception, as indicated by behavioral choice, or to the physical properties of the stimulus. We investigated which of these properties are predominantly represented in auditory cortex by recording local field potentials (LFPs) and multiunit spiking activity in ferrets while they discriminated the pitch of artificial vowels.

Spectral timbre perception in ferrets: discrimination of artificial vowels under different listening conditions.

Spectral timbre is an acoustic feature that enables human listeners to determine the identity of a spoken vowel. Despite its importance to sound perception, little is known about the neural representation of sound timbre and few psychophysical studies have investigated timbre discrimination in non-human species. In this study, ferrets were positively conditioned to discriminate artificial vowel sounds in a two-alternative-forced-choice paradigm.

Spectrotemporal contrast kernels for neurons in primary auditory cortex.

Auditory neurons are often described in terms of their spectrotemporal receptive fields (STRFs). These map the relationship between features of the sound spectrogram and firing rates of neurons. Recently, we showed that neurons in the primary fields of the ferret auditory cortex are also subject to gain control: when sounds undergo smaller fluctuations in their level over time, the neurons become more sensitive to small-level changes (Rabinowitz et al.

Tell me something interesting: context dependent adaptation in somatosensory cortex.

It is widely accepted that through a process of adaptation cells adjust their sensitivity in accordance with prevailing stimulus conditions. However, in two recent studies exploring adaptation in the rodent inferior colliculus and somatosensory cortex, neurons did not adapt towards global mean, but rather became most sensitive to inputs that were located towards the edge of the stimulus distribution with greater intensity than the mean. We re-examined electrophysiological data from the somatosensory study with the purpose of exploring the underlying encoding strategies.

The laminar and temporal structure of stimulus information in the phase of field potentials of auditory cortex.

Recent studies have shown that the phase of low-frequency local field potentials (LFPs) in sensory cortices carries a significant amount of information about complex naturalistic stimuli, yet the laminar circuit mechanisms and the aspects of stimulus dynamics responsible for generating this phase information remain essentially unknown. Here we investigated these issues by means of an information theoretic analysis of LFPs and current source densities (CSDs) recorded with laminar multi-electrode arrays in the primary auditory area of anesthetized rats during complex acoustic stimulation (music and broadband 1/f stimuli). We found that most LFP phase information originated from discrete "CSD events" consisting of granular-superficial layer dipoles of short duration and large amplitude, which we hypothesize to be triggered by transient thalamocortical activation.

Multiplexed and robust representations of sound features in auditory cortex.

We can recognize the melody of a familiar song when it is played on different musical instruments. Similarly, an animal must be able to recognize a warning call whether the caller has a high-pitched female or a lower-pitched male voice, and whether they are sitting in a tree to the left or right. This type of perceptual invariance to "nuisance" parameters comes easily to listeners, but it is unknown whether or how such robust representations of sounds are formed at the level of sensory cortex.

Emergence of tuning to natural stimulus statistics along the central auditory pathway.

We have previously shown that neurons in primary auditory cortex (A1) of anaesthetized (ketamine/medetomidine) ferrets respond more strongly and reliably to dynamic stimuli whose statistics follow "natural" 1/f dynamics than to stimuli exhibiting pitch and amplitude modulations that are faster (1/f(0.5)) or slower (1/f(2)) than 1/f. To investigate where along the central auditory pathway this 1/f-modulation tuning arises, we have now characterized responses of neurons in the central nucleus of the inferior colliculus (ICC) and the ventral division of the mediate geniculate nucleus of the thalamus (MGV) to 1/f(γ) distributed stimuli with γ varying between 0.

Contrast gain control in auditory cortex.

The auditory system must represent sounds with a wide range of statistical properties. One important property is the spectrotemporal contrast in the acoustic environment: the variation in sound pressure in each frequency band, relative to the mean pressure. We show that neurons in ferret auditory cortex rescale their gain to partially compensate for the spectrotemporal contrast of recent stimulation.

Binaural sensitivity changes between cortical on and off responses.

Neurons exhibiting on and off responses with different frequency tuning have previously been described in the primary auditory cortex (A1) of anesthetized and awake animals, but it is unknown whether other tuning properties, including sensitivity to binaural localization cues, also differ between on and off responses. We measured the sensitivity of A1 neurons in anesthetized ferrets to 1) interaural level differences (ILDs), using unmodulated broadband noise with varying ILDs and average binaural levels, and 2) interaural time delays (ITDs), using sinusoidally amplitude-modulated broadband noise with varying envelope ITDs. We also assessed fine-structure ITD sensitivity and frequency tuning, using pure-tone stimuli.