Latent Markov Models to Test the Strategy Use of 3-Year-Olds in a Rule-Based Feedback-Learning Task.

This study is the first to investigate how 3-year-olds learn simple rules from feedback using the Toddler Card Sorting Task (TCST). To account for intra- and inter- individual differences in the learning process, latent Markov models were fitted to the time series of accuracy responses using maximum likelihood techniques (Visser et al., 2002). In a first, exploratory study (N = 110, 3- to 5-years olds) a considerable group of 3-year olds applied a hypothesis testing learning strategy. A second study confirmed these results with a preregistered study (3-years olds, N = 60). Under supportive learning conditions, a majority of 3-year- olds was capable of hypothesis testing. Furthermore, older children and those with bigger working memory capacities were more likely to use hypothesis testing, even though the latter group perseverated more than younger children or those with smaller working memory capacities. 3-year-olds are more advanced feedback-learners than assumed.

Do infants have the horizontal bias?

A robust set of studies show that adults make more horizontal than vertical and oblique saccades, while scanning real-world scenes. In this paper we study the horizontal bias in infants. The directions of eye movements were calculated for 41 infants (M=8.40 months, SD=3.74, range=3.48-15.47) and 47 adults (M=21.74 years, SD=4.54, range=17.89-39.84) while viewing 28 real-world scenes. Saccade directions were binned to study the proportion of saccades in the horizontal, vertical and oblique directions. In addition, saccade directions were also modeled using a mixture of Von Mises distributions, to account for the relatively large amount of variance in infants data. Horizontal bias was replicated in adults and also found in infants, using both the binning and Von Mises approach. Moreover, a developmental pattern was observed in which older infants are more precise in targeting their saccades than younger infants. That infants have a horizontal bias is important in understanding infants' eye movements. Future studies should account for the horizontal bias in their designs and analyses.

Decreased intracellular GABA levels contribute to spinal cord stimulation-induced analgesia in rats suffering from painful peripheral neuropathy: the role of KCC2 and GABA(A) receptor-mediated inhibition.

Elevated spinal extracellular γ-aminobutyric acid (GABA) levels have been described during spinal cord stimulation (SCS)-induced analgesia in experimental chronic peripheral neuropathy. Interestingly, these increased GABA levels strongly exceeded the time frame of SCS-induced analgesia. In line with the former, pharmacologically-enhanced extracellular GABA levels by GABA(B) receptor agonists in combination with SCS in non-responders to SCS solely could convert these non-responders into responders. However, similar treatment with GABA(A) receptor agonists and SCS is known to be less efficient. Since K⁺ Cl⁻ cotransporter 2 (KCC2) functionality strongly determines proper GABA(A) receptor-mediated inhibition, both decreased numbers of GABA(A) receptors as well as reduced KCC2 protein expression might play a pivotal role in this loss of GABA(A) receptor-mediated inhibition in non-responders. Here, we explored the mechanisms underlying both changes in extracellular GABA levels and impaired GABA(A) receptor-mediated inhibition after 30 min of SCS in rats suffering from partial sciatic nerve ligation (PSNL). Immediately after cessation of SCS, a decreased spinal intracellular dorsal horn GABA-immunoreactivity was observed in responders when compared to non-responders or sham SCS rats. One hour later however, GABA-immunoreactivity was already increased to similar levels as those observed in non-responder or sham SCS rats. These changes did not coincide with alterations in the number of GABA-immunoreactive cells. C-Fos/GABA double-fluorescence clearly confirmed a SCS-induced activation of GABA-immunoreactive cells in responders immediately after SCS. Differences in spinal dorsal horn GABA(A) receptor-immunoreactivity and KCC2 protein levels were absent between all SCS groups. However, KCC2 protein levels were significantly decreased compared to sham PSNL animals. In conclusion, reduced intracellular GABA levels are only present during the time frame of SCS in responders and strongly point to a SCS-mediated on/off GABAergic release mechanism. Furthermore, a KCC2-dependent impaired GABA(A) receptor-mediated inhibition seems to be present both in responders and non-responders to SCS due to similar KCC2 and GABA(A) receptor levels.

Finite mixture distribution models of simple discrimination learning.

Through the application of finite mixture distribution models, we investigated the existence of distinct modes of behavior in learning a simple discrimination. The data were obtained in a repeated measures study in which subjects aged 6 to 10 years carried out a simple discrimination learning task. In contrast to distribution models of exclusively rational learners or exclusively incremental learners, a mixture distribution model of rational learners and slow learners was found to fit the data of all measurement occasions and all age groups. Hence, the finite mixture distribution analysis provides strong support for the existence of distinct modes of learning behavior. The results of a second experiment support this conclusion by crossvalidation of the models that fit the data of the first experiment. The effect of verbally labeling the values on the relevant stimulus dimension and the consistency of behavior over measurement occasions are related to the mixture model estimates.

Confidence intervals for hidden Markov model parameters.

Three methods for computing confidence intervals (CIs) of hidden Markov model parameters are compared in the context of 'long' time series, T > 100, namely likelihood profiling, bootstrapping and CIs based on a finite-differences approximation to the Hessian. First it is shown that with 'long' time series computing the exact Hessian is not feasible. In simulation studies quadratic and cubic interpolation polynomials for the likelihood profiles are compared. Likelihood profiling and bootstrapping produce similar CIs, whereas the CIs from the finite-differences approximation of the Hessian are mostly too small.

Numerical bifurcation analysis of distance-dependent on-center off-surround shunting neural networks.

On-center off-surround shunting neural networks are often applied as models for content-address-able memory (CAM), the equilibria being the stored memories. One important demand of biological plausible CAMs is that they function under a broad range of parameters, since several parameters vary due to postnatal maturation or learning. Ellias, Cohen and Grossberg have put much effort into showing the stability properties of several configurations of on-center off-surround shunting neural networks. In this article we present numerical bifurcation analysis of distance-dependent on-center off-surround shunting neural networks with fixed external input. We varied four parameters that may be subject to postnatal maturation: the range of both excitatory and inhibitory connections and the strength of both inhibitory and excitatory connections. These analyses show that fold bifurcations occur in the equilibrium behavior of the network by variation of all four parameters. The most important result is that the number of activation peaks in the equilibrium behavior varies from one to many if the range of inhibitory connections is decreased. Moreover, under a broad range of the parameters the stability of the network is maintained. The examined network is implemented in an ART network, Exact ART, where it functions as the classification layer F2. The stability of the ART network with the F2-field in different dynamic regimes is maintained and the behavior is functional in Exact ART. Through a bifurcation the learning behavior of Exact ART may even change from forming local representations to forming distributed representations.