Associative representational plasticity in the auditory cortex: a synthesis of two disciplines

Historically, sensory systems have been largely ignored as potential loci of information storage in the neurobiology of learning and memory. They continued to be relegated to the role of "sensory analyzers" despite consistent findings of associatively induced enhancement of responses in primary sensory cortices to behaviorally important signal stimuli, such as conditioned stimuli (CS), during classical conditioning. This disregard may have been promoted by the fact that the brain was interrogated using only one or two stimuli, e.g., a CS(+) sometimes with a CS(-), providing little insight into the specificity of neural plasticity. This review describes a novel approach that synthesizes the basic experimental designs of the experimental psychology of learning with that of sensory neurophysiology. By probing the brain with a large stimulus set before and after learning, this unified method has revealed that associative processes produce highly specific changes in the receptive fields of cells in the primary auditory cortex (A1). This associative representational plasticity (ARP) selectively facilitates responses to tonal CSs at the expense of other frequencies, producing tuning shifts toward and to the CS and expanded representation of CS frequencies in the tonotopic map of A1. ARPs have the major characteristics of associative memory: They are highly specific, discriminative, rapidly acquired, exhibit consolidation over hours and days, and can be retained indefinitely. Evidence to date suggests that ARPs encode the level of acquired behavioral importance of stimuli. The nucleus basalis cholinergic system is sufficient both for the induction of ARPs and the induction of specific auditory memory. Investigation of ARPs has attracted workers with diverse backgrounds, often resulting in behavioral approaches that yield data that are difficult to interpret. The advantages of studying associative representational plasticity are emphasized, as is the need for greater behavioral sophistication.     

A computational model of fractionated conflict-control mechanisms in task-switching

A feature of human cognition is the ability to monitor and adjust one's own behavior under changing circumstances. A dynamic balance between controlled and rapid responding is needed to adapt to a fluctuating environment. We suggest that cognitive control may include, among other things, two distinct processes. Incongruent stimuli may drive top-down facilitation of task-relevant responses to bias performance toward exploitation vs. exploration. Task or response switches may generally slow responses to bias toward accuracy vs. speed and exploration vs. exploitation. Behavioral results from a task switching study demonstrate these two distinct processes as revealed by higher-order sequential effects. A computational model implements the two conflict-control mechanisms, which allow it to capture many complex and novel sequential effects. Lesion studies with the model demonstrate that the model is unable to capture these effects without the conflict-control loops and show how each monitoring component modulates cognitive control. The results suggest numerous testable predictions regarding the neural substrates of cognitive control.     

A comparison of visual and auditory representational momentum in spatial tasks

Similarities have been observed in the localization of the final position of moving visual and moving auditory stimuli: Perceived endpoints that are judged to be farther in the direction of motion in both modalities likely reflect extrapolation of the trajectory, mediated by predictive mechanisms at higher cognitive levels. However, actual comparisons of the magnitudes of displacement between visual tasks and auditory tasks using the same experimental setup are rare. As such, the purpose of the present free-field study was to investigate the influences of the spatial location of motion offset, stimulus velocity, and motion direction on the localization of the final positions of moving auditory stimuli (Experiment 1 and 2) and moving visual stimuli (Experiment 3). To assess whether auditory performance is affected by dynamically changing binaural cues that are used for the localization of moving auditory stimuli (interaural time differences for low-frequency sounds and interaural intensity differences for high-frequency sounds), two distinct noise bands were employed in Experiments 1 and 2. In all three experiments, less precise encoding of spatial coordinates in paralateral space resulted in larger forward displacements, but this effect was drowned out by the underestimation of target eccentricity in the extreme periphery. Furthermore, our results revealed clear differences between visual and auditory tasks. Displacements in the visual task were dependent on velocity and the spatial location of the final position, but an additional influence of motion direction was observed in the auditory tasks. Together, these findings indicate that the modality-specific processing of motion parameters affects the extrapolation of the trajectory.     

Self-organized formation of colour maps in a model cortex

A report is presented of computer simulations which demonstrate the applicability of self-organization principles to the formation of a cortical colour map. A two-dimensional array of cortical units can be shown to become selectively sensitive to different colour stimuli in an orderly fashion. The precortical part of the simulation model contains three wavelength-sensitive receptors with overlapping sensitivity distributions, and a simple opponent processing stage. Each cortical unit receives the same activity from the precortical stage by adaptive connections. Initially the connections are arbitrary; during self-organization they are changed so that different way. Self-organization of the connections can be shown to take place even when the stimulation of the receptors is totally random, ie the wavelength and purity (and in some simulations the distribution) of each stimulus are selected randomly.     

A computational model of human parsing

This report describeslicensing-structure parsing (LS-parsing), a computational model of human parsing. LS-parsing corresponds to human parsing at three points: (1) the order in which the LS parser builds nodes is psychologically more accurate than the orders in which either LL or LR parsers build nodes, (2) the LS parser's preferences in resolving local ambiguities are preferable to Frazier's strategies on both empirical and theoretical grounds, and (3) the backtracking strategies the parser uses when it has made an error at an earlier choice point model the distinction betweenweak andstrong garden paths-strong garden paths being irrecoverable, weak garden paths causing psychological difficulty, but not preventing recovery of the correct structure.     

A computational model of visual analogies in design

We present an analysis of the work of human participants in addressing design problems by analogy. We describe a computer program, called Galatea, that simulates the visual input and output of four experimental participants. Since Galatea is an operational computer program, it makes specific commitments about the visual representations and reasoning it uses for analogical transfer. In particular, Galatea provides a computational model of how human designers might be generating new designs by incremental transfer of the problem-solving procedure used in previous design cases.     

Interactions between frontal cortex and basal ganglia in working memory: a computational model

The frontal cortex and the basal ganglia interact via a relatively well understood and elaborate system of interconnections. In the context of motor function, these interconnections can be understood as disinhibiting, or “releasing the brakes,” on frontal motor action plans: The basal ganglia detect appropriate contexts for performing motor actions and enable the frontal cortex to execute such actions at the appropriate time. We build on this idea in the domain of working memory through the use of computational neural network models of this circuit. In our model, the frontal cortex exhibits robust active maintenance, whereas the basal ganglia contribute a selective, dynamic gating function that enables frontal memory representations to be rapidly updated in a task-relevant manner. We apply the model to a novel version of the continuous performance task that requires subroutine-like selective working memory updating and compare and contrast our model with other existing models and theories of frontal-cortex-basal-ganglia interactions.     

Absolute pitch in infant auditory learning: evidence for developmental reorganization

To what extent do infants represent the absolute pitches of complex auditory stimuli? Two experiments with 8-month-old infants examined the use of absolute and relative pitch cues in a tone-sequence statistical learning task. The results suggest that, given unsegmented stimuli that do not conform to the rules of musical composition, infants are more likely to track patterns of absolute pitches than of relative pitches. A 3rd experiment tested adults with or without musical training on the same statistical learning tasks used in the infant experiments. Unlike the infants, adult listeners relied primarily on relative pitch cues. These results suggest a shift from an initial focus on absolute pitch to the eventual dominance of relative pitch, which, it is argued, is more useful for both music and speech processing.     

A computational cognitive model of syntactic priming

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of modeling studies, we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads.     

A computational model of spatial visualization capacity

Visualizing spatial material is a cornerstone of human problem solving, but human visualization capacity is sharply limited. To investigate the sources of this limit, we developed a new task to measure visualization accuracy for verbally-described spatial paths (similar to street directions), and implemented a computational process model to perform it. In this model, developed within the Adaptive Control of Thought-Rational (ACT-R) architecture, visualization capacity is limited by three mechanisms. Two of these (associative interference and decay) are longstanding characteristics of ACT-R’s declarative memory. A third (spatial interference) is a new mechanism motivated by spatial proximity effects in our data. We tested the model in two experiments, one with parameter-value fitting, and a replication without further fitting. Correspondence between model and data was close in both experiments, suggesting that the model may be useful for understanding why visualizing new, complex spatial material is so difficult.     

A uniform model of computational conceptual blending

We present a mathematical model for the cognitive operation of conceptual blending that aims at being uniform across different representation formalisms, while capturing the relevant structure of this operation. The model takes its inspiration from amalgams as applied in case-based reasoning, but lifts them into category theory so as to follow Joseph Goguen’s intuition for a mathematically precise characterisation of conceptual blending at a representation-independent level of abstraction. We prove that our amalgam-based category-theoretical model of conceptual blending is essentially equivalent to the pushout model in the ordered category of partial maps as put forward by Goguen. But unlike Goguen’s approach, our model is more suitable to capture computational realisations of conceptual blending, and we exemplify this by concretising our model to computational conceptual blends for various representation formalisms and application domains.     

A computational model of the Simon effect

Even though stimulus location is task irrelevant, reaction times are faster when the location of the stimulus corresponds with the location of the response than when it does not. This phenomenon is called the Simon effect. Most accounts of the Simon effect are based on the assumption that it arises from a conflict between the spatial code of the stimulus and that of the response. In this paper a computational model of this hypothesis is presented. It provides a computationally explicit mechanism of the Simon effect. Consistent with human performance, the model provides reaction times that indicate both an advantage for the ipsilateral, corresponding response (i.e., facilitation) and a disadvantage of the contralateral, noncorresponding response (i.e., inhibition). In addition, the model accounts for the fact that the size for the effect depends on task difficulty.     

A computational model of retrospective time estimation

Retrospective time estimation is an important aspect of dynamic systems and needs to be integrated in cognitive architectures. This article gives an overview of theoretical accounts of retrospective and prospective time estimation. Assumptions based on an experiment investigating retrospective time estimation conducted in our research group are presented. Integrating both we introduce a retrospective timer-module for ACT-R 6.0 and the corresponding estimation algorithm. The successful validation of the module is shown and further implications are discussed.