Israel Nelken

Stimulus-specific adaptation and deviance detection in the auditory system: experiments and models

Stimulus-specific adaptation (SSA) is the reduction in the response to a common stimulus that does not generalize, or only partially generalizes, to other, rare stimuli. SSA has been proposed to be a correlate of ‘deviance detection’, an important computational task of sensory systems. SSA is ubiquitous in the auditory system: It is found both in cortex and in subcortical stations, and it has been demonstrated in many mammalian species as well as in birds. A number of models have been suggested in the literature to account for SSA in the auditory domain. In this review, the experimental literature is critically examined in relationship to these models. While current models can all account for auditory SSA to some degree, none is fully compatible with the available findings.

Intracellular Correlates of Stimulus-Specific Adaptation

Stimulus-specific adaptation (SSA) is the reduction in response to a common stimulus that does not generalize, or only partially generalizes, to rare stimuli. SSA is strong and widespread in primary auditory cortex (A1) of rats, but is weak or absent in the main input station to A1, the ventral division of the medial geniculate body. To study SSA in A1, we recorded neural activity in A1 intracellularly using sharp electrodes. We studied the responses to tone pips of the same frequency in different contexts: as Standard and Deviants in Oddball sequences; in equiprobable sequences; in sequences consisting of rare tone presentations; and in sequences composed of many different frequencies, each of which was rare. SSA was found both in subthreshold membrane potential fluctuations and in spiking responses of A1 neurons. SSA for changes in frequency was large at a frequency difference of 44% between Standard and Deviant, and clearly present with tones separated by as little as 4%, near the behavioral frequency difference limen in rats. When using equivalent measures, SSA in spiking responses was generally larger than the SSA at the level of the membrane potential. This effect can be traced to the nonlinearity of the transformation between membrane potential to spikes. Using the responses to the same tone in different contexts made it possible to demonstrate that cortical SSA could not be fully explained by adaptation in narrow frequency channels, even at the level of the membrane potential. We conclude that local processing significantly contributes to the generation of cortical SSA.

Elevated Correlations in Neuronal Ensembles of Mouse Auditory Cortex Following Parturition

The auditory cortex is malleable by experience. Previous studies of auditory plasticity have described experience-dependent changes in response profiles of single neurons or changes in global tonotopic organization. However, experience-dependent changes in the dynamics of local neural populations have remained unexplored. In this study, we examined the influence of a dramatic yet natural experience in the life of female mice, giving birth and becoming a mother on single neurons and neuronal ensembles in the primary auditory cortex (A1). Using in vivo two-photon calcium imaging and electrophysiological recordings from layer 2/3 in A1 of mothers and age-matched virgin mice, we monitored changes in the responses to a set of artificial and natural sounds. Population dynamics underwent large changes as measured by pairwise and higher-order correlations, with noise correlations increasing as much as twofold in lactating mothers. Concomitantly, changes in response properties of single neurons were modest and selective. Remarkably, despite the large changes in correlations, information about stimulus identity remained essentially the same in the two groups. Our results demonstrate changes in the correlation structure of neuronal activity as a result of a natural life event.

Interplay between population firing stability and single neuron dynamics in hippocampal networks

Neuronal circuits ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001

Detecting the unexpected

Sensory input is inherently dynamic and redundant. Humans and animals alike show a remarkable ability to extract regularities from the sensory scene and dynamically update their responses to the environment. This type of short-term plasticity occurs on time scales ranging from seconds to minutes (and possibly longer). Mismatch Negativity (a component of the human event-related potentials, MMN) and Stimulus Specific Adaptation (a single-neuron analogue, SSA) are two examples of this form of short-term plasticity. Conceptually, both are thought to express a form of surprise and to represent predictive processing. MMN and SSA therefore provide us with handles for investigating this important time scale of short-term plasticity.

Single neuron and population coding of natural sounds in auditory cortex.

The auditory system drives behavior using information extracted from sounds. Early in the auditory hierarchy, circuits are highly specialized for detecting basic sound features. However, already at the level of the auditory cortex the functional organization of the circuits and the underlying coding principles become different. Here, we review some recent progress in our understanding of single neuron and population coding in primary auditory cortex, focusing on natural sounds. We discuss possible mechanisms explaining why single neuron responses to simple sounds cannot predict responses to natural stimuli. We describe recent work suggesting that structural features like local subnetworks rather than smoothly mapped tonotopy are essential components of population coding. Finally, we suggest a synthesis of how single neurons and subnetworks may be involved in coding natural sounds.

The Representation of Prediction Error in Auditory Cortex.

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence.

An ear for statistics

A study finds that sound textures are stored in auditory memory as summary statistics representing the sound over long time scales; specific events are superimposed, forming a skeleton of events on a bed of texture.

Early indices of deviance detection in humans and animal models

Detecting unexpected stimuli in the environment is a critical function of the auditory system. Responses to unexpected deviant sounds are enhanced compared to responses to expected stimuli. At the human scalp, deviance detection is reflected in the mismatch negativity (MMN) and in an enhancement of the middle-latency response (MLR). Single neurons often respond more strongly to a stimulus when rare than when common, a phenomenon termed stimulus-specific adaptation (SSA). Here we compare stimulus-specific adaptation with scalp-recorded deviance-related responses. We conclude that early markers of deviance detection in the time range of the MLR could be a direct correlate of cortical SSA. Both occur at an early level of cortical activation, both are robust findings with low-probability stimuli, and both show properties of genuine deviance detection. Their causal relation with the later scalp-recorded MMN is a key question in this field.

Frequency tuning in the behaving mouse: different bandwidths for discrimination and generalization

When faced with sensory stimuli, an organism may be required to detect very small differences in a physical parameter (discrimination), while in other situations it may have to generalize over many possible values of the same physical parameter. This decision may be based both on learned information and on sensory aspects of perception. In the present study we describe frequency processing in the behaving mouse using both discrimination and generalization as two key aspects of behaviour. We used a novel naturalistic behavioural apparatus designed for mice, the Audiobox, and paradigm contingencies that were identical for both auditory discrimination and generalization, the latter measured using latent inhibition. Mice learned to discriminate between frequencies that were an octave apart in a single trial. They showed significant discrimination between tone frequencies that were as close as 4–7%, and had d of about 1 for ΔF of around 10%. In contrast, pre-exposure frequencies that were half an octave or less below the conditioned tone elicited latent inhibition, showing a generalization bandwidth of at least half an octave. Thus, in the same apparatus and using the same general memory paradigm, mice showed generalization gradients that were considerably wider than their discrimination threshold, indicating that environmental requirements and previous experience can determine whether the same two frequencies will be considered same or different. Remarkably, generalization gradients paralleled the typical bandwidths established in the auditory periphery and midbrain, suggesting that frequencies may be considered similar when falling within the same critical band.