Synaptic mechanisms underlying auditory processing

https://doi.org/10.1016/j.conb.2006.06.015Get rights and content

In vivo voltage clamp recordings have provided new insights into the synaptic mechanisms that underlie processing in the primary auditory cortex. Of particular importance are the discoveries that excitatory and inhibitory inputs have similar frequency and intensity tuning, that excitation is followed by inhibition with a short delay, and that the duration of inhibition is briefer than expected. These findings challenge existing models of auditory processing in which broadly tuned lateral inhibition is used to limit excitatory receptive fields and suggest new mechanisms by which inhibition and short term plasticity shape neural responses.

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

References (46)

  • P.H. Jen et al.

    Interaction between excitation and inhibition affects frequency tuning curve, response size and latency of neurons in the auditory cortex of the big brown bat, eptesicus fuscus

    Hear Res

    (2002)
  • L. Qin et al.

    Suppression of auditory cortical activities in awake cats by pure tone stimuli

    Neurosci Lett

    (2004)
  • M. Brosch et al.

    Sequence sensitivity of neurons in cat primary auditory cortex

    Cereb Cortex

    (2000)
  • M. Brosch et al.

    Processing of sound sequences in macaque auditory cortex: response enhancement

    J Neurophysiol

    (1999)
  • D.L. Barbour et al.

    Auditory cortical responses elicited in awake primates by random spectral stimuli

    J Neurosci

    (2003)
  • O. Creutzfeldt et al.

    Thalamocortical transformation of responses to complex auditory stimuli

    Exp. Brain Res

    (1980)
  • H. Ojima et al.

    Intracellular characterization of suppressive responses in supragranular pyramidal neurons of cat primary auditory cortex in vivo

    Cereb Cortex

    (2002)
  • J.F. Linden et al.

    Columnar transformations in auditory cortex? A comparison to visual and somatosensory cortices

    Cereb Cortex

    (2003)
  • C.L. Huang et al.

    Auditory thalamocortical projections in the cat: laminar and areal patterns of input

    J Comp Neurol

    (2000)
  • H.J. Rose et al.

    Auditory thalamocortical transmission is reliable and temporally precise

    J Neurophysiol

    (2005)
  • S.J. Cruikshank et al.

    Auditory thalamocortical synaptic transmission in vitro

    J Neurophysiol

    (2002)
  • R.S. Zucker et al.

    Short term synaptic plasticity

    Annu Rev Physiol

    (2002)
  • M. Atzori et al.

    Differential synaptic processing separates stationary from transient inputs to the auditory cortex

    Nat Neurosci

    (2001)
  • Cited by (73)

    • Precise Synaptic Balance in the Zebrafish Homolog of Olfactory Cortex

      2018, Neuron
      Citation Excerpt :

      Strong excitation and inhibition consistent with a balanced state has been observed in multiple brain areas (Denève and Machens, 2016; Poo and Isaacson, 2009; Shu et al., 2003; Xue et al., 2014). Furthermore, in visual, auditory, and somatosensory cortices, excitatory and inhibitory synaptic currents can be co-tuned to basic stimulus features and co-vary in time (Anderson et al., 2000; Okun and Lampl, 2008; Oswald et al., 2006; Tan et al., 2004, 2011; Wehr and Zador, 2003; Wilent and Contreras, 2005). As these brain areas are topographically organized, co-tuning may be a result of local connectivity because nearby neurons are expected to receive similar sensory input.

    • Cortical inhibitory interneurons control sensory processing

      2017, Current Opinion in Neurobiology
      Citation Excerpt :

      These models were previously supported by results from studies measuring relative contribution of excitatory and inhibitory currents to receptive fields of excitatory neurons or using pharmacological tools to suppress inhibition. For example, in the auditory cortex, experimental evidence from pharmacological experiments and intra-cellular recordings has supported either of these schemes [29,32–37] providing a contradictory view of the function of inhibition in sensory tuning. However, given the wide range of inhibitory neuron subtypes, an emerging possibility is that the different types of inhibitory neurons differentially shape the tuning properties of excitatory neurons.

    View all citing articles on Scopus
    View full text