Inhibitory Plasticity in Auditory Cortex

Arguably the most important property of neuronal circuits in general, and of cortical circuits in particular, is plasticity—the ability to change in response to past experience. While many studies of plasticity emphasize changes in excitatory transmission, in this issue of Neuron, Galindo-Leon et al. demonstrate the important role that increased inhibition may play in shaping cortical responses to behaviorally relevant stimuli

Music and the Auditory Brain: Where is the Connection?

Sound processing by the auditory system is understood in unprecedented details, even compared with sensory coding in the visual system. Nevertheless, we do not understand yet the way in which some of the simplest perceptual properties of sounds are coded in neuronal activity. This poses serious difficulties for linking neuronal responses in the auditory system and music processing, since music operates on abstract representations of sounds. Paradoxically, although perceptual representations of sounds most probably occur high in auditory system or even beyond it, neuronal responses are strongly affected by the temporal organization of sound streams even in subcortical stations. Thus, to the extent that music is organized sound, it is the organization, rather than the sound, which is represented first in the auditory brain

Neurons and Objects: The Case of Auditory Cortex

Sounds are encoded into electrical activity in the inner ear, where they are represented (roughly) as patterns of energy in narrow frequency bands. However, sounds are perceived in terms of their high-order properties. It is generally believed that this transformation is performed along the auditory hierarchy, with low-level physical cues computed at early stages of the auditory system and high-level abstract qualities at high-order cortical areas. The functional position of primary auditory cortex (A1) in this scheme is unclear – is it ‘early’, encoding physical cues, or is it ‘late’, already encoding abstract qualities? Here we argue that neurons in cat A1 show sensitivity to high-level features of sounds. In particular, these neurons may already show sensitivity to ‘auditory objects’. The evidence for this claim comes from studies in which individual sounds are presented singly and in mixtures. Many neurons in cat A1 respond to mixtures in the same way they respond to one of the individual components of the mixture, and in many cases neurons may respond to a low-level component of the mixture rather than to the acoustically dominant one, even though the same neurons respond to the acoustically-dominant component when presented alone

Processing of Sounds by Population Spikes in a Model of Primary Auditory Cortex

We propose a model of the primary auditory cortex (A1), in which each iso-frequency column is represented by a recurrent neural network with short-term synaptic depression. Such networks can emit Population Spikes, in which most of the neurons fire synchronously for a short time period. Different columns are interconnected in a way that reflects the tonotopic map in A1, and population spikes can propagate along the map from one column to the next, in a temporally precise manner that depends on the specific input presented to the network. The network, therefore, processes incoming sounds by precise sequences of population spikes that are embedded in a continuous asynchronous activity, with both of these response components carrying information about the inputs and interacting with each other. With these basic characteristics, the model can account for a wide range of experimental findings. We reproduce neuronal frequency tuning curves, whose width depends on the strength of the intracortical inhibitory and excitatory connections. Non-simultaneous two-tone stimuli show forward masking depending on their temporal separation, as well as on the duration of the first stimulus. The model also exhibits non-linear suppressive interactions between sub-threshold tones and broad-band noise inputs, similar to the hypersensitive locking suppression recently demonstrated in auditory cortex. We derive several predictions from the model. In particular, we predict that spontaneous activity in primary auditory cortex gates the temporally locked responses of A1 neurons to auditory stimuli. Spontaneous activity could, therefore, be a mechanism for rapid and reversible modulation of cortical processing

Stimulus uncertainty and perceptual learning: Similar principles govern auditory and visual learning

AbstractWe examined the impact of variability in speech stimuli on improvement of general performance and on accessibility to low-level information as a function of practice. Listeners had to discriminate between two similar words in noise in two configurations that differed only in their low-level binaural information, which was either null or maximal. The difference in performance quantifies the use of binaural low-level information. These configurations were presented in three training protocols: in separate blocks; in a consistently interleaved manner; and in a randomly mixed manner. The first protocol enabled optimal use of the low-level binaural cues already at the first training session. The second, consistently interleaved protocol required more than one training session to reach the same performance. The final, mixed protocol did not enable optimal use of the low-level cues even after multi-session training. Interestingly, training with the first two protocols transferred to the mixed one. These results are in line with recent findings in the visual modality. In both modalities, the effects of variability on learning can be explained by the introduction of obstructions to a search mechanism going down along the sensory processing hierarchy, as suggested by the Reverse Hierarchy Theory

Study of speaker localization with binaural microphone array incorporating auditory filters and lateral angle estimation

Speaker localization for binaural microphone arrays has been widely studied for applications such as speech communication, video conferencing, and robot audition. Many methods developed for this task, including the direct path dominance (DPD) test, share common stages in their processing, which include transformation using the short-time Fourier transform (STFT), and a direction of arrival (DOA) search that is based on the head related transfer function (HRTF) set. In this paper, alternatives to these processing stages, motivated by human hearing, are proposed. These include incorporating an auditory filter bank to replace the STFT, and a new DOA search based on transformed HRTF as steering vectors. A simulation study and an experimental study are conducted to validate the proposed alternatives, and both are applied to two binaural DOA estimation methods; the results show that the proposed method compares favorably with current methods

Modeling the auditory scene: predictive regularity representations and perceptual objects

Predictive processing of information is essential for goal directed behavior. We offer an account of auditory perception suggesting that representations of predictable patterns, or ‘regularities’, extracted from the incoming sounds serve as auditory perceptual objects. The auditory system continuously searches for regularities within the acoustic signal. Primitive regularities may be encoded by neurons adapting their response to specific sounds. Such neurons have been observed in many parts of the auditory system. Representations of the detected regularities produce predictions of upcoming sounds as well as alternative solutions for parsing the composite input into coherent sequences potentially emitted by putative sound sources. Accuracy of the predictions can be utilized for selecting the most likely interpretation of the auditory input. Thus in our view, perception generates hypotheses about the causal structure of the world

Stimulus-Specific Adaptation in the Auditory Thalamus of the Anesthetized Rat

The specific adaptation of neuronal responses to a repeated stimulus (Stimulus-specific adaptation, SSA), which does not fully generalize to other stimuli, provides a mechanism for emphasizing rare and potentially interesting sensory events. Previous studies have demonstrated that neurons in the auditory cortex and inferior colliculus show SSA. However, the contribution of the medial geniculate body (MGB) and its main subdivisions to SSA and detection of rare sounds remains poorly characterized. We recorded from single neurons in the MGB of anaesthetized rats while presenting a sequence composed of a rare tone presented in the context of a common tone (oddball sequences). We demonstrate that a significant percentage of neurons in MGB adapt in a stimulus-specific manner. Neurons in the medial and dorsal subdivisions showed the strongest SSA, linking this property to the non-lemniscal pathway. Some neurons in the non-lemniscal regions showed strong SSA even under extreme testing conditions (e.g., a frequency interval of 0.14 octaves combined with a stimulus onset asynchrony of 2000 ms). Some of these neurons were able to discriminate between two very close frequencies (frequency interval of 0.057 octaves), revealing evidence of hyperacuity in neurons at a subcortical level. Thus, SSA is expressed strongly in the rat auditory thalamus and contribute significantly to auditory change detection

Frequency discrimination and stimulus deviance in the inferior colliculus and cochlear nucleus

[EN] Auditory neurons that exhibit stimulus-specific adaptation (SSA) decrease their response to common tones while retaining responsiveness to rare ones. We recorded single-unit responses from the inferior colliculus (IC) where SSA is known to occur and we explored for the first time SSA in the cochlear nucleus (CN) of rats. We assessed an important functional outcome of SSA, the extent to which frequency discriminability depends on sensory context. For this purpose, pure tones were presented in an oddball sequence as standard (high probability of occurrence) or deviant (low probability of occurrence) stimuli. To study frequency discriminability under different probability contexts, we varied the probability of occurrence and the frequency separation between tones. The neuronal sensitivity was estimated in terms of spike-count probability using signal detection theory. We reproduced the finding that many neurons in the IC exhibited SSA, but we did not observe significant SSA in our CN sample. We concluded that strong SSA is not a ubiquitous phenomenon in the CN. As predicted, frequency discriminability was enhanced in IC when stimuli were presented in an oddball context, and this enhancement was correlated with the degree of SSA shown by the neurons. In contrast, frequency discrimination by CN neurons was independent of stimulus context. Our results demonstrated that SSA is not widespread along the entire auditory pathway, and suggest that SSA increases frequency discriminability of single neurons beyond that expected from their tuning curves