Effects of stimulus-response compatibility on neural selection in frontal eye field

We investigated the neural basis of visual and saccade selection in the frontal eye field of macaque monkeys using a singleton search task with prosaccade or antisaccade responses. Two types of neurons were distinguished. The first initially selected the singleton even in antisaccade trials, although most subsequently selected the endpoint of the saccade. The time the singleton was located was not affected by stimulus-response compatibility and did not vary with reaction time across trials. The second type of neuron selected only the endpoint of the saccade. The time of endpoint selection by these neurons accounted for most of the effect of stimulus-response compatibility on reaction time. These results indicate that visual selection and saccade selection are different processes.     

Categorisation of three-dimensional stimuli by humans and baboons: search for prototype effects

A symbolic matching-to-sample procedure was adopted to investigate whether humans (n=2) and baboons (n=2) discriminate more accurately the prototypes of polymorphous categories than less typical exemplars. Subjects were initially trained to discriminate between two categories of stimuli defined by the possession of any two out of three possible binary features. In transfer, prototypes, which contained all the three feature values of their categories, and novel two-out-of-three feature exemplars were presented for discrimination. Humans solved the task in a propositional way, and showed no evidence for a better performance with the prototypes than with other exemplars. By contrast, monkeys classified the prototypes more accurately than the other exemplars. The analysis of training performance showed however, that their discriminations did not involve prototypical representations of the categories, but rather depended upon feature–and exemplar-response associations. It is argued that monkeys' better performance with the prototypes rested on peak shift and/or novelty effects.     

Functional connectivity between prefrontal cortex and striatum estimated by phase locking value

The interplay between the prefrontal cortex (PFC) and striatum has an important role in cognitive processes. To investigate interactive functions between the two areas in reward processing, we recorded local field potentials (LFPs) simultaneously from the two areas of two monkeys performing a reward prediction task (large reward vs small reward). The power of the LFPs was calculated in three frequency bands: the beta band (15–29 Hz), the low gamma band (30–49 Hz), and the high gamma band (50–100 Hz). We found that both the PFC and striatum encoded the reward information in the beta band. The reward information was also found in the high gamma band in the PFC, not in the striatum. We further calculated the phase-locking value (PLV) between two LFP signals to measure the phase synchrony between the PFC and striatum. It was found that significant differences occurred between PLVs in different task periods and in different frequency bands. The PLVs in small reward condition were significant higher than that in large reward condition in the beta band. In contrast, the PLVs in the high gamma band were stronger in large reward trials than in small trials. These results suggested that the functional connectivity between the PFC and striatum depended on the task periods and reward conditions. The beta synchrony between the PFC and striatum may regulate behavioral outputs of the monkeys in the small reward condition.     

Discrete or graded variation within rhesus monkey screams? Psychophysical experiments on classification

Gouzoules et al. (1984, Animal Behaviour,32, 182-193) presented evidence that semifree-ranging rhesus monkeys, Macaca mulatta, produce acoustically distinctive classes of scream vocalizations that carry different functional messages. To determine the perceptual validity of these vocal classes, we conducted psychophysical experiments on captive rhesus monkeys. We trained two monkeys to maintain contact with a metal response cylinder during presentation of nontarget stimuli, and to release the cylinder to report detection of target stimuli. For one subject, tonal screams served as nontarget stimuli and arched screams served as targets. These conditions were reversed for a second subject. Once natural exemplars were correctly discriminated, both subjects correctly generalized to synthetic targets. Variability in responses to nontarget stimuli, however, suggested that scream categories were not well defined following training. This result suggests that rhesus monkeys do not perceive categorical distinctions between arched and tonal screams, at least under the testing conditions implemented. Rather, our results provide evidence for a graded category. To explore which acoustic features are most important for classifying novel exemplars as tonal or arched screams, we ran several follow-up experiments with novel scream exemplars. Generalization trials suggested that variation in rate of frequency change, maximum frequency of the fundamental and harmonic structure may be important to the discrimination of screams.     

Perceptual classification in a rapidly changing environment

Humans and monkeys can learn to classify perceptual information in a statistically optimal fashion if the functional groupings remain stable over many hundreds of trials, but little is known about categorization when the environment changes rapidly. Here, we used a combination of computational modeling and functional neuroimaging to understand how humans classify visual stimuli drawn from categories whose mean and variance jumped unpredictably. Models based on optimal learning (Bayesian model) and a cognitive strategy (working memory model) both explained unique variance in choice, reaction time, and brain activity. However, the working memory model was the best predictor of performance in volatile environments, whereas statistically optimal performance emerged in periods of relative stability. Bayesian and working memory models predicted decision-related activity in distinct regions of the prefrontal cortex and midbrain. These findings suggest that perceptual category judgments, like value-guided choices, may be guided by multiple controllers.     

The role of prefrontal dopamine D1 receptors in the neural mechanisms of associative learning

Dopamine is thought to play a major role in learning. However, while dopamine D1 receptors (D1Rs) in the prefrontal cortex (PFC) have been shown to modulate working memory-related neural activity, their role in the cellular basis of learning is unknown. We recorded activity from multiple electrodes while injecting the D1R antagonist SCH23390 in the lateral PFC as monkeys learned visuomotor associations. Blocking D1Rs impaired learning of novel associations and decreased cognitive flexibility but spared performance of already familiar associations. This suggests a greater role for prefrontal D1Rs in learning new, rather than performing familiar, associations. There was a corresponding greater decrease in neural selectivity and increase in alpha and beta oscillations in local field potentials for novel than for familiar associations. Our results suggest that weak stimulation of D1Rs observed in aging and psychiatric disorders may impair learning and PFC function by reducing neural selectivity and exacerbating neural oscillations associated with inattention and cognitive deficits.     

Population-Vector Analysis by Primate Prefrontal Neuron Activities

The population-vector analysis was applied to visualize neuronal processes of sensory-to-motor transformation in the prefrontal cortex while two monkeys performed two types of oculomotor delayed-response (ODR) tasks. In a standard ODR task, monkeys were required to make a quick eye movement to where thevisual cue had been presented 3 s before, whereas in R-ODR task, monkeys wererequired to make an eye movement 90^°clockwise to the direction that the visual cue had been presented. In both tasks, directions of population vectors calculated from cue- and response-period activity were almost the same as cue directions and saccade directions, respectively, indicating that population vectors of cue- and response-period activity represent information of visual inputs and motor outputs, respectively. To visualize neuronal processes of information transformation, population vectors were calculated every 250 ms during a whole trial. In ODR task, population vectors weredirected the same direction as the cue direction during the delay period. However, in R-ODR task, population vector rotated gradually from the direction similar to the cue direction to the saccade direction during the delay period. These results indicate that visual-to-motor transformation occurs during the delay period and that this process can be visualized by the population-vectoranalysis.     

Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning

 A novel neural network model is presented that learns by trial-and-error to reproduce complex sensory-motor sequences. One subnetwork, corresponding to the prefrontal cortex (PFC), is responsible for generating unique patterns of activity that represent the continuous state of sequence execution. A second subnetwork, corresponding to the striatum, associates these state-encoding patterns with the correct response at each point in the sequence execution. From a neuroscience perspective, the model is based on the known cortical and subcortical anatomy of the primate oculomotor system. From a theoretical perspective, the architecture is similar to that of a finite automaton in which outputs and state transitions are generated as a function of inputs and the current state. Simulation results for complex sequence reproduction and sequence discrimination are presented. Received: 21 July 1994/Accepted in revised form: 21 March 1995     

Good Exemplars of Natural Scene Categories Elicit Clearer Patterns than Bad Exemplars but Not Greater BOLD Activity

Within the range of images that we might categorize as a “beach”, for example, some will be more representative of that category than others. Here we first confirmed that humans could categorize “good” exemplars better than “bad” exemplars of six scene categories and then explored whether brain regions previously implicated in natural scene categorization showed a similar sensitivity to how well an image exemplifies a category. In a behavioral experiment participants were more accurate and faster at categorizing good than bad exemplars of natural scenes. In an fMRI experiment participants passively viewed blocks of good or bad exemplars from the same six categories. A multi-voxel pattern classifier trained to discriminate among category blocks showed higher decoding accuracy for good than bad exemplars in the PPA, RSC and V1. This difference in decoding accuracy cannot be explained by differences in overall BOLD signal, as average BOLD activity was either equivalent or higher for bad than good scenes in these areas. These results provide further evidence that V1, RSC and the PPA not only contain information relevant for natural scene categorization, but their activity patterns mirror the fundamentally graded nature of human categories. Analysis of the image statistics of our good and bad exemplars shows that variability in low-level features and image structure is higher among bad than good exemplars. A simulation of our neuroimaging experiment suggests that such a difference in variance could account for the observed differences in decoding accuracy. These results are consistent with both low-level models of scene categorization and models that build categories around a prototype.     

The Prefrontal Cortex Regulates the Basal Release of Dopamine in the Limbic Striatum: An Effect Mediated by Ventral Tegmental Area

Abstract: The present study examined whether the prefrontal cortex (PFC) exerts a tonic control over the basal release of dopamine in the limbic striatum and whether this control is mediated by glutamatergic afferents to the dopamine cell body or terminal regions. Using intracerebral microdialysis in freely moving rats, it was demonstrated that application of tetrodotoxin in the contralateral PFC significantly decreased the release of dopamine in the medial striatum. Conversely, blockade of the tonic inhibitory GABAergic input in the PFC with bicuculline increased the release of dopamine in the medial striatum. Application of excitatory amino acid receptor antagonists into the striatum, while bicuculline was perfused in the PFC, did not affect the bicuculline-evoked dopamine increase in the striatum. However, infusion of tetrodotoxin or excitatory amino acid receptor antagonists into the ventral tegmental area, a region containing dopamine cell bodies that project to the medial striatum, blocked the stimulation of striatal dopamine release induced by infusion of bicuculline into the PFC. These data demonstrate that the basal output of dopamine terminals in the medial striatum is under a tonic excitatory control of the PFC. Furthermore, this control occurs primarily through glutamatergic projections to the dopamine cell body area rather than the terminal regions.     

Feature-based anticipation of cues that predict reward in monkey caudate nucleus

A subset of caudate neurons fires before cues that instruct the monkey what he should do. To test the hypothesis that the anticipatory activity of such neurons depends on the context of stimulus-reward mapping, we examined their activity while the monkeys performed a memory-guided saccade task in which either the position or the color of a cue indicated presence or absence of reward. Some neurons showed anticipatory activity only when a particular position was associated with reward, while others fired selectively for color-reward associations. The functional segregation suggests that caudate neurons participate in feature-based anticipation of visual information that predicts reward. This neuronal code influences the general activity level in response to visual features without improving the quality of visual discrimination.     

On predicting medulloblastoma metastasis by gene expression profiling

Accurately predicting clinical outcome or metastatic status from gene expression profiles remains one of the biggest hurdles facing the adoption of predictive medicine. Recently, MacDonald et al. (Nat. Genet. 2001, 29, 143-152) used gene expression profiles, from samples taken at diagnosis, to distinguish between clinically designated metastatic and nonmetastatic primary medulloblastomas, helping to elucidate the genetic mechanisms underlying metastasis and suggesting novel therapeutic targets. The obtained accuracy of predicting metastatic status does not, however, reach statistical significance on Fisher's exact test, although 22 training samples were used to make each prediction via leave-one-out testing. This paper introduces readily implemented nonlinear filters to transform sequences of gene expression levels into output signals that are significantly easier to classify and predict metastasis. It is shown that when only 3 exemplars each from the metastatic and nonmetastatic classes were assumed known, a predictor was constructed whose accuracy is statistically significant over the remaining profiles set aside as a test set. The predictor was as effective in recognizing metastatic as nonmetastatic medulloblastomas, and may be helpful in deciding which patients require more aggressive therapy. The same predictor was similarly effective on an independent set of 5 nonmetastatic tumors and 3 metastatic cell lines also used by MacDonald et al.     

Prefrontal cortex activity related to abstract response strategies

Many monkeys adopt abstract response strategies as they learn to map visual symbols to responses by trial and error. According to the repeat-stay strategy, if a symbol repeats from a previous, successful trial, the monkeys should stay with their most recent response choice. According to the change-shift strategy, if the symbol changes, the monkeys should shift to a different choice. We recorded the activity of prefrontal cortex neurons while monkeys chose responses according to these two strategies. Many neurons had activity selective for the strategy used. In a subsequent block of trials, the monkeys learned fixed stimulus-response mappings with the same stimuli. Some neurons had activity selective for choosing responses based on fixed mappings, others for choosing based on abstract strategies. These findings indicate that the prefrontal cortex contributes to the implementation of the abstract response strategies that monkeys use during trial-and-error learning.     

Control of the superior colliculus by the lateral prefrontal cortex

Several decades of patient, functional imaging and neurophysiological studies have supported a model in which the lateral prefrontal cortex (PFC) acts to suppress unwanted saccades by inhibiting activity in the oculomotor system. However, recent results from combined PFC deactivation and neural recordings of the superior colliculus in monkeys demonstrate that the primary influence of the PFC on the oculomotor system is excitatory, and stands in direct contradiction to the inhibitory model of PFC function. Although erroneous saccades towards a visual stimulus are commonly labelled reflexive in patients with PFC damage or dysfunction, the latencies of most of these saccades are outside of the range of express saccades, which are triggered directly by the visual stimulus. Deactivation and pharmacological manipulation studies in monkeys suggest that response errors following PFC damage or dysfunction are not the result of a failure in response suppression but can best be understood in the context of a failure to maintain and implement the proper task set.     

Electrical stimulation of the primate lateral habenula suppresses saccadic eye movement through a learning mechanism

The lateral habenula (LHb) is a brain structure which represents negative motivational value. Neurons in the LHb are excited by unpleasant events such as reward omission and aversive stimuli, and transmit these signals to midbrain dopamine neurons which are involved in learning and motivation. However, it remains unclear whether these phasic changes in LHb neuronal activity actually influence animal behavior. To answer this question, we artificially activated the LHb by electrical stimulation while monkeys were performing a visually guided saccade task. In one block of trials, saccades to one fixed direction (e.g., right direction) were followed by electrical stimulation of the LHb while saccades to the other direction (e.g., left direction) were not. The direction-stimulation contingency was reversed in the next block. We found that the post-saccadic stimulation of the LHb increased the latencies of saccades in subsequent trials. Notably, the increase of the latency occurred gradually as the saccade was repeatedly followed by the stimulation, suggesting that the effect of the post-saccadic stimulation was accumulated across trials. LHb stimulation starting before saccades, on the other hand, had no effect on saccade latency. Together with previous studies showing LHb activation by reward omission and aversive stimuli, the present stimulation experiment suggests that LHb activity contributes to learning to suppress actions which lead to unpleasant events.     

A Representational Similarity Analysis of the Dynamics of Object Processing Using Single-Trial EEG Classification

The recognition of object categories is effortlessly accomplished in everyday life, yet its neural underpinnings remain not fully understood. In this electroencephalography (EEG) study, we used single-trial classification to perform a Representational Similarity Analysis (RSA) of categorical representation of objects in human visual cortex. Brain responses were recorded while participants viewed a set of 72 photographs of objects with a planned category structure. The Representational Dissimilarity Matrix (RDM) used for RSA was derived from confusions of a linear classifier operating on single EEG trials. In contrast to past studies, which used pairwise correlation or classification to derive the RDM, we used confusion matrices from multi-class classifications, which provided novel self-similarity measures that were used to derive the overall size of the representational space. We additionally performed classifications on subsets of the brain response in order to identify spatial and temporal EEG components that best discriminated object categories and exemplars. Results from category-level classifications revealed that brain responses to images of human faces formed the most distinct category, while responses to images from the two inanimate categories formed a single category cluster. Exemplar-level classifications produced a broadly similar category structure, as well as sub-clusters corresponding to natural language categories. Spatiotemporal components of the brain response that differentiated exemplars within a category were found to differ from those implicated in differentiating between categories. Our results show that a classification approach can be successfully applied to single-trial scalp-recorded EEG to recover fine-grained object category structure, as well as to identify interpretable spatiotemporal components underlying object processing. Finally, object category can be decoded from purely temporal information recorded at single electrodes.     

Effect of dopamine deficiency on the preparation of visually guided saccadic eye movements

Parameters of saccadic eye movements were studied in patients with Parkinson's disease and control subjects. In parkinsonian patients, the number of slow regular saccades was shown to be increased, and the number of express saccades was shown to be decreased. As a result the mean of saccade latency in patients was longer than in the control group. Moreover, the percentage of multistep saccades in patients with Parkinson's disease. In this case, not one but two or three saccades were performed with smaller amplitude to the target. We point, that the multistep saccades occurred mainly among the express saccades. Obviously, the dopamine deficiency distinguishing parkinsonian patients takes the primary part in the development of saccadic disorders. Degeneration of the nigrostriatal dopamine pathway results in imbalance in activity of the direct and indirect output pathways of the striatum. We suppose that this leads to inhibition of neurons activity in the superior colliculus during the saccade performance, which results in the early saccade interruption. In support of this reasoning, the mean of saccade latency and the percentage of the multistep saccades decreased in patients with Parkinson's disease after dopamine D2/D3 agonist (piribedil) treatment, due to activity restoration of the indirect pathway.     

Integrating hippocampus and striatum in decision-making

Learning and memory and navigation literatures emphasize interactions between multiple memory systems: a flexible, planning-based system and a rigid, cached-value system. This has profound implications for decision-making. Recent conceptualizations of flexible decision-making employ prospection and projection arising from a network involving the hippocampus. Recent recordings from rodent hippocampus in decision-making situations have found transient forward-shifted representations. Evaluation of that prediction and subsequent action-selection probably occurs downstream (e.g. in orbitofrontal cortex, in ventral and dorsomedial striatum). Classically, striatum has been identified as a crucial component of the less-flexible, incremental system. Current evidence, however, suggests that striatum is involved in both flexible and stimulus-response decision-making, with dorsolateral striatum involved in stimulus-response strategies and ventral and dorsomedial striatum involved in goal-directed strategies.     

The learning skills of primates: The rhesus macaque in comparative perspective

Twenty-month-old rhesus monkeys were tested in a modified discrimination-reversal paradigm, which was designed to distinguish abstract learning from stimulus-response associational learning. Previous studies indicate that talapoin monkeys learn associationally and great apes via forming abstract concepts. Adult rhesus monkeys are apparently capable of forming simple abstractions, but learn primarily through associational process. The results of this study show the adolescent rhesus monkeys to be associational learners, with their response patterns indicating more complexity than the talapoins but less than the adult rhesus monkeys. The data suggest that rhesus monkeys develop their low-level capacity of abstract learning with maturation.     

A neural representation of categorization uncertainty in the human brain

The ability to classify visual objects into discrete categories ("friend" versus "foe"; "edible" versus "poisonous") is essential for survival and is a fundamental cognitive function. The cortical substrates that mediate this function, however, have not been identified in humans. To identify brain regions involved in stimulus categorization, we developed a task in which subjects classified stimuli according to a variable categorical boundary. Psychophysical functions were used to define a decision variable, categorization uncertainty, which was systematically manipulated. Using event-related functional MRI, we discovered that activity in a fronto-striatal-thalamic network, consisting of the medial frontal gyrus, anterior insula, ventral striatum, and dorsomedial thalamus, was modulated by categorization uncertainty. We found this network to be distinct from the frontoparietal attention network, consisting of the frontal and parietal eye fields, where activity was not correlated with categorization uncertainty.