Interpretive monitoring in the caudate nucleus.

In a dynamic environment an organism has to constantly adjust ongoing behavior to adapt to a given context. This process requires continuous monitoring of ongoing behavior to provide its meaningful interpretation. The caudate nucleus is known to have a role in behavioral monitoring, but the nature of these signals during dynamic behavior is still unclear.

Representation of outcome risk and action in the anterior caudate nucleus.

The anterior caudate nucleus is essential for goal-directed behavior because it links outcome information to actions. It is well known that caudate neurons provide a variety of reward-related and action signals. However, it is still unclear how the two signals are integrated.

State-space algorithms for estimating spike rate functions.

The accurate characterization of spike firing rates including the determination of when changes in activity occur is a fundamental issue in the analysis of neurophysiological data. Here we describe a state-space model for estimating the spike rate function that provides a maximum likelihood estimate of the spike rate, model goodness-of-fit assessments, as well as confidence intervals for the spike rate function and any other associated quantities of interest. Using simulated spike data, we first compare the performance of the state-space approach with that of Bayesian adaptive regression splines (BARS) and a simple cubic spline smoothing algorithm.

Frontal eye field neurons signal changes in decision criteria.

Flexible links between sensory stimuli and behavioral responses underlie many cognitive processes. One process that contributes to flexible decision-making is categorization. Some categories are innate or overlearned, but, in many cases, category boundaries represent flexible decision criteria that can shift on the fly to adapt to changes in the environment.

Comparison of associative learning-related signals in the macaque perirhinal cortex and hippocampus.

Strong evidence suggests that the macaque monkey perirhinal cortex is involved in both the initial formation as well as the long-term storage of associative memory. To examine the neurophysiological basis of associative memory formation in this area, we recorded neural activity in this region as monkeys learned new conditional-motor associations. We report that a population of perirhinal neurons signal newly learned associations by changing their firing rate correlated with the animal's behavioral learning curve.

Analysis of between-trial and within-trial neural spiking dynamics.

Recording single-neuron activity from a specific brain region across multiple trials in response to the same stimulus or execution of the same behavioral task is a common neurophysiology protocol. The raster plots of the spike trains often show strong between-trial and within-trial dynamics, yet the standard analysis of these data with the peristimulus time histogram (PSTH) and ANOVA do not consider between-trial dynamics. By itself, the PSTH does not provide a framework for statistical inference.

Functional magnetic resonance imaging activity during the gradual acquisition and expression of paired-associate memory.

Recent neurophysiological findings from the monkey hippocampus showed dramatic changes in the firing rate of individual hippocampal cells as a function of learning new associations. To extend these findings to humans, we used blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to examine the patterns of brain activity during learning of an analogous associative task. We observed bilateral, monotonic increases in activity during learning not only in the hippocampus but also in the parahippocampal and right perirhinal cortices.

Representation of well-learned information in the monkey hippocampus.

In the neocortex, extensive training results in enhanced neuronal selectivity for learned stimuli relative to novel stimuli. This enhanced selectivity has been taken as evidence for learning-related plasticity. Much less is known, in contrast, about the representation of well-learned information in the hippocampus.

Dynamic analysis of learning in behavioral experiments.

Understanding how an animal's ability to learn relates to neural activity or is altered by lesions, different attentional states, pharmacological interventions, or genetic manipulations are central questions in neuroscience. Although learning is a dynamic process, current analyses do not use dynamic estimation methods, require many trials across many animals to establish the occurrence of learning, and provide no consensus as how best to identify when learning has occurred. We develop a state-space model paradigm to characterize learning as the probability of a correct response as a function of trial number (learning curve).

Single neurons in the monkey hippocampus and learning of new associations.

The medial temporal lobe is crucial for the ability to learn and retain new declarative memories. This form of memory includes the ability to quickly establish novel associations between unrelated items. To better understand the patterns of neural activity during associative memory formation, we recorded the activity of hippocampal neurons of macaque monkeys as they learned new associations.