Learning strategy trumps motivational level in determining learning-induced auditory cortical plasticity

Prior experience modifies acquisition trajectories via response-strategy sampling

Few studies have considered how signal detection parameters evolve during acquisition periods. We addressed this gap by training mice with differential prior experience in a conditional discrimination, auditory signal detection task. Naïve mice, mice given separate experience with each of the later correct choice options (Correct Choice Response Transfer, CCRT), and mice experienced in conditional discriminations (Conditional Discrimination Transfer, CDT) were trained to detect the presence or absence of a tone in white noise. We analyzed data assuming a two-period model of acquisition: a pre-solution and solution period (Heinemann EG (1983) in The Presolution period and the detection of statistical associations. In: Quantitative analyses of behavior: discrimination processes, vol. 4, pp. 21-36). Ballinger. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.536.1978andrep=rep1andtype=pdf ). The pre-solution period was characterized by a selective sampling of biased response strategies until adoption of a conditional responding strategy in the solution period. Correspondingly, discriminability remained low until the solution period; criterion took excursions reflecting response-strategy sampling. Prior experience affected the length and composition of the pre-solution period. Whereas CCRT and CDT mice had shorter pre-solution periods than naïve mice, CDT and Naïve mice developed substantial criterion biases and acquired asymptotic discriminability faster than CCRT mice. To explain these data, we propose a learning model in which mice selectively sample and test different response-strategies and corresponding task structures until they exit the pre-solution period. Upon exit, mice adopt the conditional responding strategy and task structure, with action values updated via inference and generalization from the other task structures. Simulations of representative mouse data illustrate the viability of this model.

What Is the Benefit of Ramped Pulse Shapes for Activating Auditory Cortex Neurons? An Electrophysiological Study in an Animal Model of Cochlear Implant

In all commercial cochlear implant (CI) devices, the activation of auditory nerve fibers is performed with rectangular pulses that have two phases of opposite polarity. Recently, several papers proposed that ramped pulse shapes could be an alternative shape for efficiently activating auditory nerve fibers. Here, we investigate whether ramped pulse shapes can activate auditory cortex (ACx) neurons in a more efficient way than the classical rectangular pulses. Guinea pigs were implanted with CI devices and responses of ACx neurons were tested with rectangular pulses and with four ramped pulse shapes, with a first-phase being either cathodic or anodic. The thresholds, i.e., the charge level necessary for obtaining significant cortical responses, were almost systematically lower with ramped pulses than with rectangular pulses. The maximal firing rate (FR) elicited by the ramped pulses was higher than with rectangular pulses. As the maximal FR occurred with lower charge levels, the dynamic range (between threshold and the maximal FR) was not modified. These effects were obtained with cathodic and anodic ramped pulses. By reducing the charge levels required to activate ACx neurons, the ramped pulse shapes should reduce charge consumption and should contribute to more battery-efficient CI devices in the future.

Music-selective neural populations arise without musical training

Recent work has shown that human auditory cortex contains neural populations anterior and posterior to primary auditory cortex that respond selectively to music. However, it is unknown how this selectivity for music arises. To test whether musical training is necessary, we measured fMRI responses to 192 natural sounds in 10 people with almost no musical training. When voxel responses were decomposed into underlying components, this group exhibited a music-selective component that was very similar in response profile and anatomical distribution to that previously seen in individuals with moderate musical training. We also found that musical genres that were less familiar to our participants (e.g., Balinese gamelan) produced strong responses within the music component, as did drum clips with rhythm but little melody, suggesting that these neural populations are broadly responsive to music as a whole. Our findings demonstrate that the signature properties of neural music selectivity do not require musical training to develop, showing that the music-selective neural populations are a fundamental and widespread property of the human brain.NEW & NOTEWORTHY We show that music-selective neural populations are clearly present in people without musical training, demonstrating that they are a fundamental and widespread property of the human brain. Additionally, we show music-selective neural populations respond strongly to music from unfamiliar genres as well as music with rhythm but little pitch information, suggesting that they are broadly responsive to music as a whole.

Precise memory for pure tones is predicted by measures of learning-induced sensory system neurophysiological plasticity at cortical and subcortical levels

Despite identical learning experiences, individuals differ in the memory formed of those experiences. Molecular mechanisms that control the neurophysiological bases of long-term memory formation might control how precisely the memory formed reflects the actually perceived experience. Memory formed with sensory specificity determines its utility for selectively cueing subsequent behavior, even in novel situations. Here, a rodent model of auditory learning capitalized on individual differences in learning-induced auditory neuroplasticity to identify and characterize neural substrates for sound-specific (vs. general) memory of the training signal's acoustic frequency. Animals that behaviorally revealed a naturally induced signal-"specific" memory exhibited long-lasting signal-specific neurophysiological plasticity in auditory cortical and subcortical evoked responses. Animals with "general" memories did not exhibit learning-induced changes in these same measures. Manipulating a histone deacetylase during memory consolidation biased animals to have more signal-specific memory. Individual differences validated this brain-behavior relationship in both natural and manipulated memory formation, such that the degree of change in sensory cortical and subcortical neurophysiological responses could be used to predict the behavioral precision of memory.

Plasticity in the auditory system

Over the last 30 years a wide range of manipulations of auditory input and experience have been shown to result in plasticity in auditory cortical and subcortical structures. The time course of plasticity ranges from very rapid stimulus-specific adaptation to longer-term changes associated with, for example, partial hearing loss or perceptual learning. Evidence for plasticity as a consequence of these and a range of other manipulations of auditory input and/or its significance is reviewed, with an emphasis on plasticity in adults and in the auditory cortex. The nature of the changes in auditory cortex associated with attention, memory and perceptual learning depend critically on task structure, reward contingencies, and learning strategy. Most forms of auditory system plasticity are adaptive, in that they serve to optimize auditory performance, prompting attempts to harness this plasticity for therapeutic purposes. However, plasticity associated with cochlear trauma and partial hearing loss appears to be maladaptive, and has been linked to tinnitus. Three important forms of human learning-related auditory system plasticity are those associated with language development, musical training, and improvement in performance with a cochlear implant. Almost all forms of plasticity involve changes in synaptic excitatory - inhibitory balance within existing patterns of connectivity. An attractive model applicable to a number of forms of learning-related plasticity is dynamic multiplexing by individual neurons, such that learning involving a particular stimulus attribute reflects a particular subset of the diverse inputs to a given neuron being gated by top-down influences. The plasticity evidence indicates that auditory cortex is a component of complex distributed networks that integrate the representation of auditory stimuli with attention, decision and reward processes.

Contrast Enhancement without Transient Map Expansion for Species-Specific Vocalizations in Core Auditory Cortex during Learning

Tonotopic map plasticity in the adult auditory cortex (AC) is a well established and oft-cited measure of auditory associative learning in classical conditioning paradigms. However, its necessity as an enduring memory trace has been debated, especially given a recent finding that the areal expansion of core AC tuned to a newly relevant frequency range may arise only transiently to support auditory learning. This has been reinforced by an ethological paradigm showing that map expansion is not observed for ultrasonic vocalizations (USVs) or for ultrasound frequencies in postweaning dams for whom USVs emitted by pups acquire behavioral relevance. However, whether transient expansion occurs during maternal experience is not known, and could help to reveal the generality of cortical map expansion as a correlate for auditory learning. We thus mapped the auditory cortices of maternal mice at postnatal time points surrounding the peak in pup USV emission, but found no evidence of frequency map expansion for the behaviorally relevant high ultrasound range in AC. Instead, regions tuned to low frequencies outside of the ultrasound range show progressively greater suppression of activity in response to the playback of ultrasounds or pup USVs for maternally experienced animals assessed at their pups’ postnatal day 9 (P9) to P10, or postweaning. This provides new evidence for a lateral-band suppression mechanism elicited by behaviorally meaningful USVs, likely enhancing their population-level signal-to-noise ratio. These results demonstrate that tonotopic map enlargement has limits as a construct for conceptualizing how experience leaves neural memory traces within sensory cortex in the context of ethological auditory learning.

Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded.

Learning strategy refinement reverses early sensory cortical map expansion but not behavior: Support for a theory of directed cortical substrates of learning and memory

Primary sensory cortical fields develop highly specific associative representational plasticity, notably enlarged area of representation of reinforced signal stimuli within their topographic maps. However, overtraining subjects after they have solved an instrumental task can reduce or eliminate the expansion while the successful behavior remains. As the development of this plasticity depends on the learning strategy used to solve a task, we asked whether the loss of expansion is due to the strategy used during overtraining. Adult male rats were trained in a three-tone auditory discrimination task to bar-press to the CS+ for water reward and refrain from doing so during the CS- tones and silent intertrial intervals; errors were punished by a flashing light and time-out penalty. Groups acquired this task to a criterion within seven training sessions by relying on a strategy that was "bar-press from tone-onset-to-error signal" ("TOTE"). Three groups then received different levels of overtraining: Group ST, none; Group RT, one week; Group OT, three weeks. Post-training mapping of their primary auditory fields (A1) showed that Groups ST and RT had developed significantly expanded representational areas, specifically restricted to the frequency band of the CS+ tone. In contrast, the A1 of Group OT was no different from naïve controls. Analysis of learning strategy revealed this group had shifted strategy to a refinement of TOTE in which they self-terminated bar-presses before making an error ("iTOTE"). Across all animals, the greater the use of iTOTE, the smaller was the representation of the CS+ in A1. Thus, the loss of cortical expansion is attributable to a shift or refinement in strategy. This reversal of expansion was considered in light of a novel theoretical framework (CONCERTO) highlighting four basic principles of brain function that resolve anomalous findings and explaining why even a minor change in strategy would involve concomitant shifts of involved brain sites, including reversal of cortical expansion.

Associative learning and sensory neuroplasticity: how does it happen and what is it good for?

Historically, the body's sensory systems have been presumed to provide the brain with raw information about the external environment, which the brain must interpret to select a behavioral response. Consequently, studies of the neurobiology of learning and memory have focused on circuitry that interfaces between sensory inputs and behavioral outputs, such as the amygdala and cerebellum. However, evidence is accumulating that some forms of learning can in fact drive stimulus-specific changes very early in sensory systems, including not only primary sensory cortices but also precortical structures and even the peripheral sensory organs themselves. This review synthesizes evidence across sensory modalities to report emerging themes, including the systems’ flexibility to emphasize different aspects of a sensory stimulus depending on its predictive features and ability of different forms of learning to produce similar plasticity in sensory structures. Potential functions of this learning-induced neuroplasticity are discussed in relation to the challenges faced by sensory systems in changing environments, and evidence for absolute changes in sensory ability is considered. We also emphasize that this plasticity may serve important nonsensory functions, including balancing metabolic load, regulating attentional focus, and facilitating downstream neuroplasticity.

New perspectives on the auditory cortex: learning and memory

Primary ("early") sensory cortices have been viewed as stimulus analyzers devoid of function in learning, memory, and cognition. However, studies combining sensory neurophysiology and learning protocols have revealed that associative learning systematically modifies the encoding of stimulus dimensions in the primary auditory cortex (A1) to accentuate behaviorally important sounds. This "representational plasticity" (RP) is manifest at different levels. The sensitivity and selectivity of signal tones increase near threshold, tuning above threshold shifts toward the frequency of acoustic signals, and their area of representation can increase within the tonotopic map of A1. The magnitude of area gain encodes the level of behavioral stimulus importance and serves as a substrate of memory strength. RP has the same characteristics as behavioral memory: it is associative, specific, develops rapidly, consolidates, and can last indefinitely. Pairing tone with stimulation of the cholinergic nucleus basalis induces RP and implants specific behavioral memory, while directly increasing the representational area of a tone in A1 produces matching behavioral memory. Thus, RP satisfies key criteria for serving as a substrate of auditory memory. The findings suggest a basis for posttraumatic stress disorder in abnormally augmented cortical representations and emphasize the need for a new model of the cerebral cortex.

Learning-stage-dependent plasticity of temporal coherence in the auditory cortex of rats

Temporal coherence among neural populations may contribute importantly to signal encoding, specifically by providing an optimal tradeoff between encoding reliability and efficiency. Here, we considered the possibility that learning modulates the temporal coherence among neural populations in association with well-characterized map plasticity. We previously demonstrated that, in appetitive operant conditioning tasks, the tone-responsive area globally expanded during the early stage of learning, but shrank during the late stage. The present study further showed that phase locking of the first spike to band-specific oscillations of local field potentials (LFPs) significantly increased during the early stage of learning but decreased during the late stage, suggesting that neurons in A1 were more synchronously activated during early learning, whereas they were more asynchronously activated once learning was completed. Furthermore, LFP amplitudes increased during early learning but decreased during later learning. These results suggest that, compared to naïve encoding, early-stage encoding is more reliable but energy-consumptive, whereas late-stage encoding is more energetically efficient. Such a learning-stage-dependent encoding strategy may underlie learning-induced, non-monotonic map plasticity. Accumulating evidence indicates that the cholinergic system is likely to be a shared neural substrate of the processes for perceptual learning and attention, both of which modulate neural encoding in an adaptive manner. Thus, a better understanding of the links between map plasticity and modulation of temporal coherence will likely lead to a more integrated view of learning and attention.

Understanding the neurophysiological basis of auditory abilities for social communication: a perspective on the value of ethological paradigms

Acoustic communication between animals requires them to detect, discriminate, and categorize conspecific or heterospecific vocalizations in their natural environment. Laboratory studies of the auditory-processing abilities that facilitate these tasks have typically employed a broad range of acoustic stimuli, ranging from natural sounds like vocalizations to "artificial" sounds like pure tones and noise bursts. However, even when using vocalizations, laboratory studies often test abilities like categorization in relatively artificial contexts. Consequently, it is not clear whether neural and behavioral correlates of these tasks (1) reflect extensive operant training, which drives plastic changes in auditory pathways, or (2) the innate capacity of the animal and its auditory system. Here, we review a number of recent studies, which suggest that adopting more ethological paradigms utilizing natural communication contexts are scientifically important for elucidating how the auditory system normally processes and learns communication sounds. Additionally, since learning the meaning of communication sounds generally involves social interactions that engage neuromodulatory systems differently than laboratory-based conditioning paradigms, we argue that scientists need to pursue more ethological approaches to more fully inform our understanding of how the auditory system is engaged during acoustic communication. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives".

Gamma band plasticity in sensory cortex is a signature of the strongest memory rather than memory of the training stimulus

Gamma oscillations (∼30-120Hz) are considered to be a reflection of coordinated neuronal activity, linked to processes underlying synaptic integration and plasticity. Increases in gamma power within the cerebral cortex have been found during many cognitive processes such as attention, learning, memory and problem solving in both humans and animals. However, the specificity of gamma to the detailed contents of memory remains largely unknown. We investigated the relationship between learning-induced increased gamma power in the primary auditory cortex (A1) and the strength of memory for acoustic frequency. Adult male rats (n=16) received three days (200 trials each) of pairing a tone (3.66 kHz) with stimulation of the nucleus basalis, which implanted a memory for acoustic frequency as assessed by associatively-induced disruption of ongoing behavior, viz., respiration. Post-training frequency generalization gradients (FGGs) revealed peaks at non-CS frequencies in 11/16 cases, likely reflecting normal variation in pre-training acoustic experiences. A stronger relationship was found between increased gamma power and the frequency with the strongest memory (peak of the difference between individual post- and pre-training FGGs) vs. behavioral responses to the CS training frequency. No such relationship was found for the theta/alpha band (4-15 Hz). These findings indicate that the strength of specific increased neuronal synchronization within primary sensory cortical fields can determine the specific contents of memory.

Remodeling sensory cortical maps implants specific behavioral memory

Neural mechanisms underlying the capacity of memory to be rich in sensory detail are largely unknown. A candidate mechanism is learning-induced plasticity that remodels the adult sensory cortex. Here, expansion in the primary auditory cortical (A1) tonotopic map of rats was induced by pairing a 3.66-kHz tone with activation of the nucleus basalis, mimicking the effects of natural associative learning. Remodeling of A1 produced de novo specific behavioral memory, but neither memory nor plasticity was consistently at the frequency of the paired tone, which typically decreased in A1 representation. Rather, there was a specific match between individual subjects' area of expansion and the tone that was strongest in each animal's memory, as determined by post-training frequency generalization gradients. These findings provide the first demonstration of a match between the artificial induction of specific neural representational plasticity and artificial induction of behavioral memory. As such, together with prior and present findings for detection, correlation and mimicry of plasticity with the acquisition of memory, they satisfy a key criterion for neural substrates of memory. This demonstrates that directly remodeling sensory cortical maps is sufficient for the specificity of memory formation.

Auditory Imagery Modulates Frequency-specific Areas in the Human Auditory Cortex

Neural responses in early sensory areas are influenced by top–down processing. In the visual system, early visual areas have been shown to actively participate in top–down processing based on their topographical properties. Although it has been suggested that the auditory cortex is involved in top–down control, functional evidence of topographic modulation is still lacking. Here, we show that mental auditory imagery for familiar melodies induces significant activation in the frequency-responsive areas of the primary auditory cortex (PAC). This activation is related to the characteristics of the imagery: when subjects were asked to imagine high-frequency melodies, we observed increased activation in the high- versus low-frequency response area; when the subjects were asked to imagine low-frequency melodies, the opposite was observed. Furthermore, we found that A1 is more closely related to the observed frequency-related modulation than R in tonotopic subfields of the PAC. Our findings suggest that top–down processing in the auditory cortex relies on a mechanism similar to that used in the perception of external auditory stimuli, which is comparable to early visual systems.

Tone-detection training enhances spectral integration mediated by intracortical pathways in primary auditory cortex

Auditory-cued behavioral training can alter neural circuits in primary auditory cortex (A1), but the mechanisms and consequences of experience-dependent cortical plasticity are not fully understood. To address this issue, we trained adult rats to detect a 5 kHz target in order to receive a food reward. After 14 days training we identified three locations within A1: (i) the region representing the characteristic frequency (CF) 5 kHz, (ii) a nearby region with CF ∼10 kHz, and (iii) a more distant region with CF ∼20 kHz. In order to compare functional connectivity in A1 near to, vs. far from, the representation of the target frequency, we placed a 16-channel multiprobe in middle- (∼10 kHz) and high- (∼20 kHz) CF regions and obtained current-source density (CSD) profiles evoked by a range of tone stimuli (CF±1-3 octaves in quarter-octave steps). Our aim was to construct "CSD receptive fields" (CSD RFs) in order to determine the laminar and spectral profile of tone-evoked current sinks, and infer changes to thalamocortical and intracortical inputs. Behavioral training altered CSD RFs at the 10 kHz, but not 20 kHz, site relative to CSD RFs in untrained control animals. At the 10 kHz site, current sinks evoked by the target frequency were enhanced in layer 2/3, but the initial current sink in layer 4 was not altered. The results imply training-induced plasticity along intracortical pathways connecting the target representation with nearby cortical regions. Finally, we related behavioral performance (sensitivity index, d') to CSD responses in individual animals, and found a significant correlation between the development of d' over training and the amplitude of the target-evoked current sink in layer 2/3. The results suggest that plasticity along intracortical pathways is important for auditory learning.

A fully automated and highly versatile system for testing multi-cognitive functions and recording neuronal activities in rodents

We have developed a fully automated system for operant behavior testing and neuronal activity recording by which multiple cognitive brain functions can be investigated in a single task sequence. The unique feature of this system is a custom-made, acoustically transparent chamber that eliminates many of the issues associated with auditory cue control in most commercially available chambers. The ease with which operant devices can be added or replaced makes this system quite versatile, allowing for the implementation of a variety of auditory, visual, and olfactory behavioral tasks. Automation of the system allows fine temporal (10 ms) control and precise time-stamping of each event in a predesigned behavioral sequence. When combined with a multi-channel electrophysiology recording system, multiple cognitive brain functions, such as motivation, attention, decision-making, patience, and rewards, can be examined sequentially or independently.

Extinction reveals that primary sensory cortex predicts reinforcement outcome

Primary sensory cortices are traditionally regarded as stimulus analysers. However, studies of associative learning-induced plasticity in the primary auditory cortex (A1) indicate involvement in learning, memory and other cognitive processes. For example, the area of representation of a tone becomes larger for stronger auditory memories and the magnitude of area gain is proportional to the degree that a tone becomes behaviorally important. Here, we used extinction to investigate whether 'behavioral importance' specifically reflects a sound's ability to predict reinforcement (reward or punishment) vs. to predict any significant change in the meaning of a sound. If the former, then extinction should reverse area gains as the signal no longer predicts reinforcement. Rats (n = 11) were trained to bar-press to a signal tone (5.0 kHz) for water-rewards, to induce signal-specific area gains in A1. After subsequent withdrawal of reward, A1 was mapped to determine representational areas. Signal-specific area gains, estimated from a previously established brain-behavior quantitative function, were reversed, supporting the 'reinforcement prediction' hypothesis. Area loss was specific to the signal tone vs. test tones, further indicating that withdrawal of reinforcement, rather than unreinforced tone presentation per se, was responsible for area loss. Importantly, the amount of area loss was correlated with the amount of extinction (r = 0.82, P < 0.01). These findings show that primary sensory cortical representation can encode behavioral importance as a signal's value to predict reinforcement, and that the number of cells tuned to a stimulus can dictate its ability to command behavior.

Task reward structure shapes rapid receptive field plasticity in auditory cortex

As sensory stimuli and behavioral demands change, the attentive brain quickly identifies task-relevant stimuli and associates them with appropriate motor responses. The effects of attention on sensory processing vary across task paradigms, suggesting that the brain may use multiple strategies and mechanisms to highlight attended stimuli and link them to motor action. To better understand factors that contribute to these variable effects, we studied sensory representations in primary auditory cortex (A1) during two instrumental tasks that shared the same auditory discrimination but required different behavioral responses, either approach or avoidance. In the approach task, ferrets were rewarded for licking a spout when they heard a target tone amid a sequence of reference noise sounds. In the avoidance task, they were punished unless they inhibited licking to the target. To explore how these changes in task reward structure influenced attention-driven rapid plasticity in A1, we measured changes in sensory neural responses during behavior. Responses to the target changed selectively during both tasks but did so with opposite sign. Despite the differences in sign, both effects were consistent with a general neural coding strategy that maximizes discriminability between sound classes. The dependence of the direction of plasticity on task suggests that representations in A1 change not only to sharpen representations of task-relevant stimuli but also to amplify responses to stimuli that signal aversive outcomes and lead to behavioral inhibition. Thus, top-down control of sensory processing can be shaped by task reward structure in addition to the required sensory discrimination.

Inverted-U function relating cortical plasticity and task difficulty

Many psychological and physiological studies with simple stimuli have suggested that perceptual learning specifically enhances the response of primary sensory cortex to task-relevant stimuli. The aim of this study was to determine whether auditory discrimination training on complex tasks enhances primary auditory cortex responses to a target sequence relative to non-target and novel sequences. We collected responses from more than 2000 sites in 31 rats trained on one of six discrimination tasks that differed primarily in the similarity of the target and distractor sequences. Unlike training with simple stimuli, long-term training with complex stimuli did not generate target-specific enhancement in any of the groups. Instead, cortical receptive field size decreased, latency decreased, and paired pulse depression decreased in rats trained on the tasks of intermediate difficulty, whereas tasks that were too easy or too difficult either did not alter or degraded cortical responses. These results suggest an inverted-U function relating neural plasticity and task difficulty.

Plasticity in the Primary Auditory Cortex, Not What You Think it is: Implications for Basic and Clinical Auditory Neuroscience

Standard beliefs that the function of the primary auditory cortex (A1) is the analysis of sound have proven to be incorrect. Its involvement in learning, memory and other complex processes in both animals and humans is now well-established, although often not appreciated. Auditory coding is strongly modifed by associative learning, evident as associative representational plasticity (ARP) in which the representation of an acoustic dimension, like frequency, is re-organized to emphasize a sound that has become behaviorally important. For example, the frequency tuning of a cortical neuron can be shifted to match that of a significant sound and the representational area of sounds that acquire behavioral importance can be increased. ARP depends on the learning strategy used to solve an auditory problem and the increased cortical area confers greater strength of auditory memory. Thus, primary auditory cortex is involved in cognitive processes, transcending its assumed function of auditory stimulus analysis. The implications for basic neuroscience and clinical auditory neuroscience are presented and suggestions for remediation of auditory processing disorders are introduced.

Remodeling the cortex in memory: Increased use of a learning strategy increases the representational area of relevant acoustic cues

Associative learning induces plasticity in the representation of sensory information in sensory cortices. Such high-order associative representational plasticity (HARP) in the primary auditory cortex (A1) is a likely substrate of auditory memory: it is specific, rapidly acquired, long-lasting and consolidates. Because HARP is likely to support the detailed content of memory, it is important to identify the necessary behavioral factors that dictate its induction. Learning strategy is a critical factor for the induction of plasticity (Bieszczad & Weinberger, 2010b). Specifically, use of a strategy that relies on tone onsets induces HARP in A1 in the form of signal-specific decreased threshold and bandwidth. The present study tested the hypothesis that the form and degree of HARP in A1 reflects the amount of use of an "onset strategy". Adult male rats (n=7) were trained in a protocol that increased the use of this strategy from approximately 20% in prior studies to approximately 80%. They developed signal-specific gains in representational area, transcending plasticity in the form of local changes in threshold and bandwidth. Furthermore, the degree of area gain was proportional to the amount of use of the onset strategy. A second complementary experiment demonstrated that use of a learning strategy that specifically did not rely on tone onsets did not produce gains in representational area; but rather produced area loss. Together, the findings indicate that the amount of strategy use is a dominant factor for the induction of learning-induced cortical plasticity along a continuum of both form and degree.

Song recognition learning and stimulus-specific weakening of neural responses in the avian auditory forebrain

Learning typically increases the strength of responses and the number of neurons that respond to training stimuli. Few studies have explored representational plasticity using natural stimuli, however, leaving unknown the changes that accompany learning under more realistic conditions. Here, we examine experience-dependent plasticity in European starlings, a songbird with rich acoustic communication signals tied to robust, natural recognition behaviors. We trained starlings to recognize conspecific songs and recorded the extracellular spiking activity of single neurons in the caudomedial nidopallium (NCM), a secondary auditory forebrain region analogous to mammalian auditory cortex. Training induced a stimulus-specific weakening of the neural responses (lower spike rates) to the learned songs, whereas the population continued to respond robustly to unfamiliar songs. Additional experiments rule out stimulus-specific adaptation and general biases for novel stimuli as explanations of these effects. Instead, the results indicate that associative learning leads to single neuron responses in which both irrelevant and unfamiliar stimuli elicit more robust responses than behaviorally relevant natural stimuli. Detailed analyses of these effects at a finer temporal scale point to changes in the number of motifs eliciting excitatory responses above a neuron's spontaneous discharge rate. These results show a novel form of experience-dependent plasticity in the auditory forebrain that is tied to associative learning and in which the overall strength of responses is inversely related to learned behavioral significance.