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Daeyeol Lee

Publications and source records attributed to Daeyeol Lee.

18 recordsLinked to original sources
PubMed2006

Effects of reward expectancy on sequential eye movements in monkeys.

Desirability of an action, often referred to as utility or value, is determined by various factors, such as the probability and timing of expected reward. We investigated how performance of monkeys in an oculomotor serial reaction time task is influenced by multiple motivational factors. The animals produced a series of visually-guided eye movements, while the sequence of target locations and the location of the rewarded target were systematically manipulated. The results show that error rates as well as saccade latencies were consistently influenced by the number of remaining movements necessary to obtain a reward. In addition, when the animal produced multiple saccades before fixating a given target, the first saccade tended to be directed towards the rewarded location, suggesting that saccades to rewarded location and visual target might be programmed concurrently. These results show that monkeys can utilize information about the required sequence of movements to update their subjective values.

Animals↗
PubMed2006

Serial correlation in lateralized choices of hand and target.

We investigated how lateralized choices of hand and target are influenced by previous behavior. Three monkeys retrieved food pellets following cues indicating the location of available food pellet targets, and the hand that could be used to acquire a target. In pseudo-randomized trials, the monkeys could retrieve food pellet targets only on their right side, only on their left side, or their choice of either right or left side, using only their right hand, only their left hand, or their choice of either hand. We examined separately the patterns of serial correlation in target choices and hand choices. Although individual monkeys showed overall laterality preferences, instead of repeatedly using the preferred hand, we found that the monkeys tended to switch hands in successive trials. This serial correlation in hand choice was stronger and more robust than serial correlation in target choice. Furthermore, the pattern of serial correlation for target choice closely resembled that of serial correlation for hand choice when the animal was allowed to choose both target and hand, but only when the target cue was presented before the hand cue. These results suggest that when cued to choose a hand first, the monkeys tended to make a separate decision as to whether to switch their target choices or not, whereas their decisions to switch hands and targets were linked more tightly if the animal was cued to choose a target first.

Analysis of Variance↗
PubMed2006

Effects of noise correlations on information encoding and decoding.

Response variability is often correlated across populations of neurons, and these noise correlations may play a role in information coding. In previous studies, this possibility has been examined from the encoding and decoding perspectives. Here we used d prime and related information measures to examine how studies of noise correlations from these two perspectives are related. We found that for a pair of neurons, the effect of noise correlations on information decoding can be zero when the effect of noise correlations on the information encoded obtains its largest positive or negative values. Furthermore, there can be no effect of noise correlations on the information encoded when it has an effect on information decoding. We also measured the effect of noise correlations on information encoding and decoding in simultaneously recorded neurons in the supplementary motor area to see how well d prime accounted for the information actually present in the neural responses and to see how noise correlations affected encoding and decoding in real data. These analyses showed that d prime provides an accurate measure of information encoding and decoding in our population of neurons. We also found that the effect of noise correlations on information encoding was somewhat larger than the effect of noise correlations on information decoding, but both were relatively small. Finally, as predicted theoretically, the effects of correlations were slightly greater for larger ensembles (3-8 neurons) than for pairs of neurons.

Action Potentials↗
PubMed2006

Neural basis of quasi-rational decision making.

Standard economic theories conceive homo economicus as a rational decision maker capable of maximizing utility. In reality, however, people tend to approximate optimal decision-making strategies through a collection of heuristic routines. Some of these routines are driven by emotional processes, and others are adjusted iteratively through experience. In addition, routines specialized for social decision making, such as inference about the mental states of other decision makers, might share their origins and neural mechanisms with the ability to simulate or imagine outcomes expected from alternative actions that an individual can take. A recent surge of collaborations across economics, psychology and neuroscience has provided new insights into how such multiple elements of decision making interact in the brain.

Animals↗
PubMed2006

Activity in prefrontal cortex during dynamic selection of action sequences.

Completing everyday tasks often requires the execution of action sequences matched to a particular problem. To study the neural processes underlying these behaviors, we trained monkeys to produce a series of eye movements according to a sequence that changed unpredictably from one block of trials to the next. We then applied a decoding algorithm to estimate which sequence was being represented by the ensemble activity in prefrontal cortex. We found that the sequence predicted by this analysis changed gradually from the sequence that had been correct in the previous block to the sequence that was correct in the current block, closely following the fraction of executed movements that were consistent with the corresponding sequence. Thus, the neural activity dynamically tracked the monkeys' uncertainty about the correct sequence of actions. These results are consistent with prefrontal involvement in representing subjective knowledge of the correct action sequence.

Algorithms↗
PubMed2006

Neural mechanism for stochastic behaviour during a competitive game.

Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another agent. To understand the neural mechanism of such dynamic choice behaviour, we propose a biologically plausible model of decision making endowed with synaptic plasticity that follows a reward-dependent stochastic Hebbian learning rule. This model constitutes a biophysical implementation of reinforcement learning, and it reproduces salient features of behavioural data from an experiment with monkeys playing a matching pennies game. Due to interaction with an opponent and learning dynamics, the model generates quasi-random behaviour robustly in spite of intrinsic biases. Furthermore, non-random choice behaviour can also emerge when the model plays against a non-interactive opponent, as observed in the monkey experiment. Finally, when combined with a meta-learning algorithm, our model accounts for the slow drift in the animal's strategy based on a process of reward maximization.

Algorithms↗
PubMed2005

Learning and decision making in monkeys during a rock-paper-scissors game.

Game theory provides a solution to the problem of finding a set of optimal decision-making strategies in a group. However, people seldom play such optimal strategies and adjust their strategies based on their experience. Accordingly, many theories postulate a set of variables related to the probabilities of choosing various strategies and describe how such variables are dynamically updated. In reinforcement learning, these value functions are updated based on the outcome of the player's choice, whereas belief learning allows the value functions of all available choices to be updated according to the choices of other players. We investigated the nature of learning process in monkeys playing a competitive game with ternary choices, using a rock-paper-scissors game. During the baseline condition in which the computer selected its targets randomly, each animal displayed biases towards some targets. When the computer exploited the pattern of animal's choice sequence but not its reward history, the animal's choice was still systematically biased by the previous choice of the computer. This bias was reduced when the computer exploited both the choice and reward histories of the animal. Compared to simple models of reinforcement learning or belief learning, these adaptive processes were better described by a model that incorporated the features of both models. These results suggest that stochastic decision-making strategies in primates during social interactions might be adjusted according to both actual and hypothetical payoffs.

Algorithms↗
PubMed2004

Behavioral context and coherent oscillations in the supplementary motor area.

Movements with similar physical characteristics can occur in various behavioral contexts, as when they are embedded in different sequences or when the expected outcomes of movements vary. Similarly, neurons in various sensory and motor structures in the brain commonly display modulations in their activity according to contextual factors, such as expected reward. Although these contextual signals must be combined with incoming sensory inputs to generate appropriate behaviors according to the animal's motivational state, the mechanisms by which these two signals are integrated remain poorly understood. The present study examined the effects of contextual factors on the magnitude of coherent oscillations in the activity of individual neurons recorded in the supplementary motor area (SMA) of monkeys during a serial reaction time task. In this task, the animal produced a predictable sequence of hand movements repeatedly according to visual instructions. The performance of the animal was influenced by the location of the rewarded target as well as the ordinal position of the movement. In contrast, the level of coherent oscillations in the activity of SMA neurons was affected only by the rewarded target location but not by the ordinal position of the movement sequence. In addition, changes in coherent oscillations were not accounted for by systematic changes in the mean firing rates. These results are consistent with the proposal that synchronous spikes might be used to control the flow of information and suggest that coherent oscillations in the SMA might encode contextual variables, such as expected reward.

Action Potentials↗
PubMed2004

Prefrontal cortex and decision making in a mixed-strategy game.

In a multi-agent environment, where the outcomes of one's actions change dynamically because they are related to the behavior of other beings, it becomes difficult to make an optimal decision about how to act. Although game theory provides normative solutions for decision making in groups, how such decision-making strategies are altered by experience is poorly understood. These adaptive processes might resemble reinforcement learning algorithms, which provide a general framework for finding optimal strategies in a dynamic environment. Here we investigated the role of prefrontal cortex (PFC) in dynamic decision making in monkeys. As in reinforcement learning, the animal's choice during a competitive game was biased by its choice and reward history, as well as by the strategies of its opponent. Furthermore, neurons in the dorsolateral prefrontal cortex (DLPFC) encoded the animal's past decisions and payoffs, as well as the conjunction between the two, providing signals necessary to update the estimates of expected reward. Thus, PFC might have a key role in optimizing decision-making strategies.

Animals↗
PubMed2004

Reinforcement learning and decision making in monkeys during a competitive game.

Animals living in a dynamic environment must adjust their decision-making strategies through experience. To gain insights into the neural basis of such adaptive decision-making processes, we trained monkeys to play a competitive game against a computer in an oculomotor free-choice task. The animal selected one of two visual targets in each trial and was rewarded only when it selected the same target as the computer opponent. To determine how the animal's decision-making strategy can be affected by the opponent's strategy, the computer opponent was programmed with three different algorithms that exploited different aspects of the animal's choice and reward history. When the computer selected its targets randomly with equal probabilities, animals selected one of the targets more often, violating the prediction of probability matching, and their choices were systematically influenced by the choice history of the two players. When the computer exploited only the animal's choice history but not its reward history, animal's choice became more independent of its own choice history but was still related to the choice history of the opponent. This bias was substantially reduced, but not completely eliminated, when the computer used the choice history of both players in making its predictions. These biases were consistent with the predictions of reinforcement learning, suggesting that the animals sought optimal decision-making strategies using reinforcement learning algorithms.

Algorithms↗
PubMed2004

Coding and transmission of information by neural ensembles.

The brain processes information about sensory stimuli and motor intentions using a massive ensemble of neurons arrayed in parallel. Individual neurons receive convergent inputs from thousands of other neurons, leading to the possibility that patterns of spikes across the input neurons might be crucial components of the neural code. Recently, advances in multielectrode recording techniques have allowed several laboratories to investigate the nature of the interactions between neurons, and their potential role in information coding. Several recent studies have found that the amount of information coded by correlated activity about sensory and motor variables is small, casting doubt on the hypothesis that correlations between pairs of neurons are important for information coding. However, other studies have documented the appearance of coherent oscillations, during particular task epochs and conditions that require selective processing of sensory information, supporting the hypothesis that coherent oscillations between neurons might reflect the dynamic flow of information in the brain.

Animals↗
PubMed2003

Neural noise and movement-related codes in the macaque supplementary motor area.

We analyzed the variability of spike counts and the coding capacity of simultaneously recorded pairs of neurons in the macaque supplementary motor area (SMA). We analyzed the mean-variance functions for single neurons, as well as signal and noise correlations between pairs of neurons. All three statistics showed a strong dependence on the bin width chosen for analysis. Changes in the correlation structure of single neuron spike trains over different bin sizes affected the mean-variance function, and signal and noise correlations between pairs of neurons were much smaller at small bin widths, increasing monotonically with the width of the bin. Analyses in the frequency domain showed that the noise between pairs of neurons, on average, was most strongly correlated at low frequencies, which explained the increase in noise correlation with increasing bin width. The coding performance was analyzed to determine whether the temporal precision of spike arrival times and the interactions within and between neurons could improve the prediction of the upcoming movement. We found that in approximately 62% of neuron pairs, the arrival times of spikes at a resolution between 66 and 40 msec carried more information than spike counts in a 200 msec bin. In addition, in 19% of neuron pairs, inclusion of within (11%)- or between-neuron (8%) correlations in spike trains improved decoding accuracy. These results suggest that in some SMA neurons elements of the spatiotemporal pattern of activity may be relevant for neural coding.

Action Potentials↗
PubMed2003

Coherent oscillations in neuronal activity of the supplementary motor area during a visuomotor task.

Neural activity recorded in behaving animals is nonstationary, making it difficult to determine factors influencing its temporal patterns. In the present study, rhesus monkeys were trained to produce a series of visually guided hand movements according to the changes in target locations, and multichannel single-neuron activity was recorded from the caudal supplementary motor area. Coherent oscillations in neural activity were analyzed using the wavelet cross-spectrum, and its statistical significance was evaluated using various methods based on surrogate spike trains and trial shuffling. A population-averaged wavelet cross-spectrum displayed a strong tendency for oscillatory activity in the gamma frequency range (30 approximately 50 Hz) to synchronize immediately before and after the onset of movement target. The duration of synchronized oscillations in the gamma frequency range increased when the onset of the next target was delayed. In addition, analysis of individual neuron pairs revealed that many neuron pairs also displayed coherent oscillations in the beta frequency range (15-30 Hz). Coherent beta frequency oscillations were less likely to be synchronized than gamma frequency oscillations, consistent with the fact that coherent beta frequency oscillations were not clearly seen in the population-averaged cross-spectrum. For a given neuron pair, the time course and phase of coherent oscillations were often similar across different movements. These results are consistent with the proposal that synchronized oscillations in the gamma frequency range might be related to the anticipation of behaviorally relevant events and the contextual control of cortical information flow.

Action Potentials↗
PubMed2003

Visual search is facilitated by scene and sequence familiarity in rhesus monkeys.

Whether searching for targets in a familiar scene leads to improved performance was tested in monkeys. We found that search performance improved for a familiar scene when target locations were always randomized. However, when target locations repeatedly followed a predictable sequence, performance improvement for a familiar scene was manifested only for targets presented in a familiar sequence, suggesting that scene memory might be masked by the learning of target sequences. These results suggest that information about a visual scene can facilitate the performance of visual search, and that this memory is coupled to the learned sequence of target locations.

Animals↗
PubMed2003

Activity in the supplementary motor area related to learning and performance during a sequential visuomotor task.

Monkeys were trained in a serial reaction time task to produce hand movements according to changing locations of visual targets. In most trials, targets followed the same sequence repeatedly, whereas in other trials targets were presented in random locations or switched unpredictably between two alternative sequences. Single-unit activity was recorded from the caudal supplementary motor area (SMA-proper). Based on the activity associated with random movement sequences, effects of hand position and movement direction were evaluated. Activity was influenced by the hand position in ~60% of the neurons, and the movement direction influenced the activity of 51% of the neurons. In addition, 37 and 71% of SMA neurons displayed nonstationarity in their activity across successive movements within a given trial and across trials, respectively. Such nonstationarity in the ongoing neural activity and the effects of performance-related variables were evaluated using a regression model and separated from learning-related activity changes. About a third of SMA neurons displayed gradual changes in neural activity related to experience with a movement sequence across trials. Furthermore, about a quarter of SMA neurons showed similar changes within individual trials. When the individual movements included in the frequently repeated movement sequences were introduced unexpectedly, learning-related changes in neural activity were reduced, indicating that many SMA neurons changed their activity in relation to the learning of particular movement sequences. These results suggest that the pattern of neural activity in the cortical network involved in the control of movement sequences can be modified continuously by experience.

Animals↗
PubMed2002

Analysis of phase-locked oscillations in multi-channel single-unit spike activity with wavelet cross-spectrum.

Electrophysiological measures of neural activity frequently display oscillatory patterns at various frequencies. Furthermore, these oscillatory patterns can become dynamically synchronized across a wide region of the brain in a task-dependent manner. In this study, phase-locked oscillations in simultaneously recorded spike trains were analyzed using the wavelet cross-spectrum. Adaptation of the existent methods of calculating wavelet cross-spectrum to spike train data was straightforward. In contrast, new methods were needed for evaluating the statistical significance of the cross-spectrum. Although a permutation test based on a large number of re-sampled cross-spectra can provide a reliable estimate of statistical significance, this was quite time-consuming. As an alternative, statistical significance was determined with a normal probability density function estimated from a small number of re-sampled cross-spectra. When applied to neuron pairs recorded in the primate supplementary motor area, the re-sampling procedure produced a reliable outcome even when it was based on as few as ten re-sampled cross-spectra. These results suggest that the wavelet analysis in combination with a re-sampling procedure provides a useful tool to examine the dynamic patterns of temporal correlation in cortical spike trains.

Action Potentials↗