CNN Architectures for Large-Scale Audio Classification

Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNNs), AlexNet [1], VGG [2], Inception [3], and ResNet [4]. We investigate varying the size of both training set and label vocabulary, finding that analogs of the CNNs used in image classification do well on our audio classification task, and larger training and label sets help up to a point. A model using embeddings from these classifiers does much better than raw features on the Audio Set [5] Acoustic Event Detection (AED) classification task.Comment: Accepted for publication at ICASSP 2017 Changes: Added definitions of mAP, AUC, and d-prime. Updated mAP/AUC/d-prime numbers for Audio Set based on changes of latest Audio Set revision. Changed wording to fit 4 page limit with new addition

Long-term modification of cortical synapses improves sensory perception

Synapses and receptive fields of the cerebral cortex are plastic. However, changes to specific inputs must be coordinated within neural networks to ensure that excitability and feature selectivity are appropriately configured for perception of the sensory environment. Long-lasting enhancements and decrements to rat primary auditory cortical excitatory synaptic strength were induced by pairing acoustic stimuli with activation of the nucleus basalis neuromodulatory system. Here we report that these synaptic modifications were approximately balanced across individual receptive fields, conserving mean excitation while reducing overall response variability. Decreased response variability should increase detection and recognition of near-threshold or previously imperceptible stimuli, as we found in behaving animals. Thus, modification of cortical inputs leads to wide-scale synaptic changes, which are related to improved sensory perception and enhanced behavioral performance

Inhibitory Actions Unified by Network Integration

Cortical function is regulated by a strikingly diverse array of local-circuit inhibitory neurons. We evaluated how optogenetically activating somatostatin- and parvalbumin-positive interneurons subtractively or divisively suppressed auditory cortical cells' responses to tones. In both awake and anesthetized animals, we found that activating either family of interneurons produced mixtures of divisive and subtractive effects and that simultaneously recorded neurons were often suppressed in qualitatively different ways. A simple network model shows that threshold nonlinearities can interact with network activity to transform subtractive inhibition of neurons into divisive inhibition of networks, or vice versa. Varying threshold and the strength of suppression of a model neuron could determine whether the effect of inhibition appeared divisive, subtractive, or both. We conclude that the characteristics of response inhibition specific to a single interneuron type can be "masked" by the network configuration and cellular properties of the network in which they are embedded

Chronic reduction in inhibition reduces receptive field size in mouse auditory cortex.

Inhibitory interneurons regulate the responses of cortical circuits. In auditory cortical areas, inhibition from these neurons narrows spectral tuning and shapes response dynamics. Acute disruptions of inhibition expand spectral receptive fields. However, the effects of long-term perturbations of inhibitory circuitry on auditory cortical responses are unknown. We ablated ~30% of dendrite-targeting cortical inhibitory interneurons after the critical period by studying mice with a conditional deletion of Dlx1. Following the loss of interneurons, baseline firing rates rose and tone-evoked responses became less sparse in auditory cortex. However, contrary to acute blockades of inhibition, the sizes of spectral receptive fields were reduced, demonstrating both higher thresholds and narrower bandwidths. Furthermore, long-latency responses at the edge of the receptive field were absent. On the basis of changes in response dynamics, the mechanism for the reduction in receptive field size appears to be a compensatory loss of cortico-cortically (CC) driven responses. Our findings suggest chronic conditions that feature changes in inhibitory circuitry are not likely to be well modeled by acute network manipulations, and compensation may be a critical component of chronic neuronal conditions

Chronic reduction in inhibition reduces receptive field size in mouse auditory cortex.

Inhibitory interneurons regulate the responses of cortical circuits. In auditory cortical areas, inhibition from these neurons narrows spectral tuning and shapes response dynamics. Acute disruptions of inhibition expand spectral receptive fields. However, the effects of long-term perturbations of inhibitory circuitry on auditory cortical responses are unknown. We ablated ~30% of dendrite-targeting cortical inhibitory interneurons after the critical period by studying mice with a conditional deletion of Dlx1. Following the loss of interneurons, baseline firing rates rose and tone-evoked responses became less sparse in auditory cortex. However, contrary to acute blockades of inhibition, the sizes of spectral receptive fields were reduced, demonstrating both higher thresholds and narrower bandwidths. Furthermore, long-latency responses at the edge of the receptive field were absent. On the basis of changes in response dynamics, the mechanism for the reduction in receptive field size appears to be a compensatory loss of cortico-cortically (CC) driven responses. Our findings suggest chronic conditions that feature changes in inhibitory circuitry are not likely to be well modeled by acute network manipulations, and compensation may be a critical component of chronic neuronal conditions

Long-term modification of cortical synapses improves sensory perception.

Synapses and receptive fields of the cerebral cortex are plastic. However, changes to specific inputs must be coordinated within neural networks to ensure that excitability and feature selectivity are appropriately configured for perception of the sensory environment. We induced long-lasting enhancements and decrements to excitatory synaptic strength in rat primary auditory cortex by pairing acoustic stimuli with activation of the nucleus basalis neuromodulatory system. Here we report that these synaptic modifications were approximately balanced across individual receptive fields, conserving mean excitation while reducing overall response variability. Decreased response variability should increase detection and recognition of near-threshold or previously imperceptible stimuli. We confirmed both of these hypotheses in behaving animals. Thus, modification of cortical inputs leads to wide-scale synaptic changes, which are related to improved sensory perception and enhanced behavioral performance