Research paperAuditory associative memory and representational plasticity in the primary auditory cortex
Introduction
This article provides a summary of our research on learning-related neurophysiological plasticity in the adult primary auditory cortex (A1). We refer to the systematic effects of associative learning on a dimension of neuronal processing, such as acoustic frequency, as “associative representational plasticity” (ARP) (Weinberger, 2007). This report begins with studies of the basic process of classical (Pavlovian) conditioning and then considers experiments on instrumental conditioning. However, the major goal of this paper is to highlight the importance of appropriate experimental designs and the objective measurement of behavior. Although central to the study of auditory memory and cortical plasticity, they have engendered controversy and confusion due to reliance on some questionable assumptions. Thus, the research reviewed here is intended to serve dual functions: (a) as findings in the search for a comprehensive understanding of the auditory cortex, and (b) as vehicles for the discussion of conceptual and methodological problems.
Before proceeding, it will be helpful to distinguish between associative learning and perceptual learning because they are often conflated. Associative learning simply refers to acquiring the knowledge that two events occur non-randomly, usually with one preceding the other. Classical conditioning is the most basic form of associative learning, in which a conditioned stimulus (CS, e.g., tone) is followed by an unconditioned stimulus (US, e.g., shock or food) without requiring any particular behavioral response. The learned association is that the CS predicts the US. Instrumental conditioning, which is based on prior classical conditioning, consists of learning to perform a particular behavioral response (e.g., key press) when presented with a CS, in order to obtain a reward or avoid a noxious stimulus. The learned association is that the instrumental response in the presence of the CS will produce a reinforcement (e.g., food). Such associations enable animals and humans to learn the “causal fabric” of their environments (Rescorla, 1988).
Perceptual learning is a particular form of instrumental conditioning. It consists of first learning to discriminate between two different signal stimuli (e.g., tones), one of which is designated as “correct” by the experimenter. After an easy discrimination has been achieved, increasingly difficult discrimination problems are used, until no further improvement. The result of perceptual learning is to improve perceptual abilities, such as the ability to better distinguish between two frequencies. Training often involves thousands of trials over many days. But while it can be rapid (Hawkey et al., 2004), nonetheless subjects must first learn basic associations, e.g., between an acoustic stimulus and a reinforcer (i.e., simple classical conditioning) and between a response contingent on an acoustic stimulus and a reinforcer (i.e., simple instrumental conditioning). Because basic associative learning and its correlated cortical plasticity develop very rapidly, understanding their substrates may help elucidate mechanisms of perceptual learning, further consideration of which is beyond the scope of this paper.
Section snippets
Why study the auditory cortex and conditioning?
As ablation of primary auditory cortex does not prevent classical conditioning to acoustic conditioned stimuli (CS) (e.g., Romanski and LeDoux, 1992), its study during conditioning has been questioned (Ohl and Scheich, 2004). However, even “simple” conditioning involves a widely distributed network of neural changes (Weinberger, 2004b). Even if sub-cortical circuitry can support simple associations in the absence of cortex, the auditory cortex stores information in parallel with the sub-cortex.
The “traditional approach”
Beginning in the mid-1950s, recordings were obtained during training trials. This very logical approach was applied to all sensory systems, in fact, to all brain structures. When acoustic training stimuli were used and recordings were obtained from A1, the findings consistently showed that associative plasticity develops in the primary auditory cortex (Weinberger and Diamond, 1987). These studies are foundational to contemporary research, so their value is not in question. However, restricting
Non-primary auditory cortex
The unified design was first used in the mid-1980s, but not in A1. The zeitgeist in sensory physiology at that time was that the primary auditory, somatosensory and visual cortices were not very plastic beyond a “critical period” of development. Rather, we decided to study two non-primary areas, secondary auditory cortex (A2) and the ventral ectosylvian (VE) field. They were selected because we wrongly assumed that A1 would be less plastic. Cats were trained in fear conditioning and developed
Controversies and assumptions
Currently, there are substantial controversies about associative representational plasticity. These include opposing claims regarding the form of receptive field plasticity, the interpretation of its functional significance and its underlying neural mechanisms. We will consider form and function first, and mechanisms next.
Auditory learning without frequency tuning shifts
We noted previously that Ohl and Scheich have proposed that the form of learning-induced plasticity is task dependent. Their formulation, as a subclass of the general expectation that cortical cells subserve whatever adaptive needs are present, is proving to be correct (see also Fritz et al., 2005). For example, while there is overwhelming evidence of tuning shifts caused by increased responses to the CS frequency and decreased responses to the pre-training BF in associative learning, this is
Conclusions and future directions
It is now well established that learning systematically modifies the processing and representation of acoustic information in the primary auditory cortex. Tuning shifts that favor the frequency of an important, signal stimulus are a consistent and dominant finding across types of training, types of reinforcement motivation and different laboratories. Moreover, the persistence of associative representational plasticity indicates that some of the substrates of auditory memory are probably stored
Acknowledgements
We thank Gabriel K. Hui and Jacquie Weinberger for assistance. This research was supported by research grants from the National Institutes of Health/National Institute on Deafness and Other Communication Disorders (NIDCD), DC-02938 and DC-05592.
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