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Stimulus dependent transformations between synaptic and spiking receptive fields in auditory cortex.

ABSTRACT: Auditory cortex neurons nonlinearly integrate synaptic inputs from the thalamus and cortex, and generate spiking outputs for simple and complex sounds. Directly comparing synaptic and spiking activity can determine whether this input-output transformation is stimulus-dependent. We employ in vivo whole-cell recordings in the mouse primary auditory cortex, using pure tones and broadband dynamic moving ripple stimuli, to examine properties of functional integration in tonal (TRFs) and spectrotemporal (STRFs) receptive fields. Spectral tuning in STRFs derived from synaptic, subthreshold and spiking responses proves to be substantially more selective than for TRFs. We describe diverse spectral and temporal modulation preferences and distinct nonlinearities, and their modifications between the input and output stages of neural processing. These results characterize specific processing differences at the level of synaptic convergence, integration and spike generation resulting in stimulus-dependent transformation patterns in the primary auditory cortex.

SUBMITTER: Kim KX

PROVIDER: S-EPMC7046699 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Stimulus dependent transformations between synaptic and spiking receptive fields in auditory cortex.

Kim Kyunghee X KX Atencio Craig A CA Schreiner Christoph E CE

Nature communications 20200227 1

Auditory cortex neurons nonlinearly integrate synaptic inputs from the thalamus and cortex, and generate spiking outputs for simple and complex sounds. Directly comparing synaptic and spiking activity can determine whether this input-output transformation is stimulus-dependent. We employ in vivo whole-cell recordings in the mouse primary auditory cortex, using pure tones and broadband dynamic moving ripple stimuli, to examine properties of functional integration in tonal (TRFs) and spectrotempor ...[more]

PMID: 32107370

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Project description:Previous studies have shown that the auditory cortex can enhance the perception of behaviorally important sounds in the presence of background noise, but the mechanisms by which it does this are not yet elucidated. Rapid plasticity of spectrotemporal receptive fields (STRFs) in the primary (A1) cortical neurons is observed during behavioral tasks that require discrimination of particular sounds. This rapid task-related change is believed to be one of the processing strategies utilized by the auditory cortex to selectively attend to one stream of sound in the presence of mixed sounds. However, the mechanism by which the brain evokes this rapid plasticity in the auditory cortex remains unclear. This paper uses a neural network model to investigate how synaptic transmission within the cortical neuron network can change the receptive fields of individual neurons. A sound signal was used as input to a model of the cochlea and auditory periphery, which activated or inhibited integrate-and-fire neuron models to represent networks in the primary auditory cortex. Each neuron in the network was tuned to a different frequency. All neurons were interconnected with excitatory or inhibitory synapses of varying strengths. Action potentials in one of the model neurons were used to calculate the receptive field using reverse correlation. The results were directly compared to previously recorded electrophysiological data from ferrets performing behavioral tasks that require discrimination of particular sounds. The neural network model could reproduce complex STRFs observed experimentally through optimizing the synaptic weights in the model. The model predicts that altering synaptic drive between cortical neurons and/or bottom-up synaptic drive from the cochlear model to the cortical neurons can account for rapid task-related changes observed experimentally in A1 neurons. By identifying changes in the synaptic drive during behavioral tasks, the model provides insights into the neural mechanisms utilized by the auditory cortex to enhance the perception of behaviorally salient sounds.

Project description:To navigate complex acoustic environments, listeners adapt neural processes to focus on behaviorally relevant sounds in the acoustic foreground while minimizing the impact of distractors in the background, an ability referred to as top-down selective attention. Particularly striking examples of attention-driven plasticity have been reported in primary auditory cortex via dynamic reshaping of spectro-temporal receptive fields (STRFs). By enhancing the neural response to features of the foreground while suppressing those to the background, STRFs can act as adaptive contrast matched filters that directly contribute to an improved cognitive segregation between behaviorally relevant and irrelevant sounds. In this study, we propose a novel discriminative framework for modeling attention-driven plasticity of STRFs in primary auditory cortex. The model describes a general strategy for cortical plasticity via an optimization that maximizes discriminability between the foreground and distractors while maintaining a degree of stability in the cortical representation. The first instantiation of the model describes a form of feature-based attention and yields STRF adaptation patterns consistent with a contrast matched filter previously reported in neurophysiological studies. An extension of the model captures a form of object-based attention, where top-down signals act on an abstracted representation of the sensory input characterized in the modulation domain. The object-based model makes explicit predictions in line with limited neurophysiological data currently available but can be readily evaluated experimentally. Finally, we draw parallels between the model and anatomical circuits reported to be engaged during active attention. The proposed model strongly suggests an interpretation of attention-driven plasticity as a discriminative adaptation operating at the level of sensory cortex, in line with similar strategies previously described across different sensory modalities.

Dataset Information

Stimulus dependent transformations between synaptic and spiking receptive fields in auditory cortex.

Publications

Stimulus dependent transformations between synaptic and spiking receptive fields in auditory cortex.

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