Synaptic mechanisms underlying auditory processing
Introduction
A central issue in auditory neuroscience is how the external acoustic environment is represented by neural activity in the primary auditory cortex (AI). AI plays a role in the perceptual processing of complex acoustic stimuli, contributing to a wide variety of processes including recognition of species-specific vocalizations, sound source localization, identification of auditory objects, stimulus-specific adaptation, and learning and memory [1, 2, 3, 4]. Although auditory signals undergo significant subcortical processing, in vivo recordings indicate that further refinement takes place in AI [5, 6, 7]. AI, in comparison to subcortical regions, has a higher incidence of neurons that exhibit non-monotonic rate-level functions, greater sensitivity to source location, and a decreased ability to phase-lock to high temporal modulation rates. The relationship between acoustic stimuli and cortical spiking patterns has traditionally been characterized using extracellular recordings. Because spikes result from the integration of numerous subthreshold events, the underlying cellular and network mechanisms can be more directly studied with intracellular recording techniques. Unfortunately, in vivo intracellular recording in AI is technically challenging and, to date, only a few successful experiments have been performed [8, 9, 10]. In this review, we highlight recent in vivo whole-cell recordings in AI and focus on two important factors that influence neuronal firing — the interaction of excitatory and inhibitory synaptic inputs and the dynamic properties of synaptic potentials. We discuss how these factors contribute to time-varying firing during tonal stimulation, receptive field properties, and other well-documented response characteristics of AI neurons. These new data narrow the gap between cellular and systems physiology and suggest how current models of auditory processing could be refined.
Section snippets
General synaptic features of primary auditory cortex
The basic organization of AI is generally similar to that of other primary sensory cortices (see [11] for review and notable exceptions). Neurons in AI are tonotopically organized according to the characteristic frequency (CF; see glossary) that evokes a response at the lowest stimulus intensity. The tuning properties of the neurons are inherited from the ventral division of the medial geniculate nucleus of the thalamus but are further refined in AI [5, 6, 7]. Thalamic afferents terminate on
Contribution of local inhibitory networks
During acoustic stimulation, some AI neurons fire only at the onset or offset of a stimulus (phasic), whereas others fire continuously throughout the stimulus (tonic, phasic–tonic) [8, 9, 19]. Intracellular recordings indicate that these responses are partly due to the interaction of excitatory (EPSPs) and inhibitory (IPSPs) postsynaptic potentials [8, 9, 10]. Neurons that fire phasically receive a barrage of EPSPs followed after a short delay by IPSPs. Tonically firing neurons also receive a
Contribution of short-term plasticity
Short-term plasticity also contributes to the time-varying firing patterns and receptive field properties of AI neurons. Phasic responses evoked with tonal stimulation can be attributed to synaptic depression: the EPSPs are initially suprathreshold but then taper off to become subthreshold (Figure 2ai). By contrast, tonic responses could be mediated by non-depressing or facilitating synapses (Figure 2aii). Auditory thalamocortical synapses on average depress, although there is substantial
Caveats
Some important caveats about in vivo intracellular recordings are worth noting. First, the studies have been performed entirely in anesthetized animals in order to maintain recording stability. However, cortical activity depends significantly on the type of anesthesia and the level of arousal [23••, 38, 39, 40••]. Second, for practical reasons, only brief and relatively simple stimuli were used to probe synaptic responses. There is strong evidence that neural responses, and by inference network
Conclusions
Decades of research in auditory physiology have yielded valuable insights into the mechanisms by which auditory stimuli are encoded and processed in the central nervous system. Recent in vivo intracellular studies have enhanced our understanding of cortical auditory processing by elucidating underlying synaptic mechanisms. These studies have challenged previous explanations of how inhibitory receptive fields and forward suppression arise. First, co-tuned excitation and inhibition does not
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
We would like to thank D Sanes and J de la Rocha for helpful comments. This work was supported by National Institute of Deafness and Communication Disorders Grants DC005787-01A1 to AD Reyes and DC007025-02 to ML Schiff.
Glossary
- Characteristic frequency
- The tone frequency that elicits a neural response at the lowest stimulus intensity.
- Click stimuli
- Brief (5 ms) white noise stimuli [23••].
- Frequency sweep
- Stimulus protocol in which progressively increasing or decreasing frequencies tones are presented sequentially and continuously.
- Tuning curve
- Plot of neural response versus tone frequency. Typically, there is an optimal stimulus frequency that evokes the maximal response.
- Two-tone stimulation
- Two brief tones, the probe and the
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