Search

A large body of work has identified value signals in a number of brain areas and explored their role in decision-making and learning (1⇓–3). However, what is currently not well understood is how these value signals originate and how they are related to the specific sensory experiences that generate them. Taste is famously subjective and is typically treated as a given variable beyond the scope of the experiment. However, in any decision maker, be it a human or an animal, a particular pattern of sensory inputs must directly generate specific value signals in the reward circuit of that subject. This is an objective process, and, in principle at least, we should be able to understand it. Is it possible in practice? In PNAS, Huang et al. (4) describes work that starts to answer some of these questions in the domain of food preferences. Value is a fundamental concept in the behavioral sciences. Humans and animals can select between options with very different attributes. For example, we can easily choose between buying a new computer or going on an expensive vacation, even though these options are very different in type (an object and an activity) and will evoke very different sensory experiences. The behavioral sciences explain this ability by postulating an internal unidimensional signal, called “value,” that can be attributed to any distinguishable option and that collapses all attributes of that option into a single variable. This internal value signal can then be easily compared across all available options, so that the one associated with the largest value signal is chosen. While economics treats value as just a hypothetical variable that explains pattern of preference, neuroscience has demonstrated that value is, in fact, encoded in specific brain circuits. Single-unit recordings have shown the existence of neuronal activity that … [↵][1]1Email: veit{at}jhu.edu. [1]: #xref-corresp-1-1

Traditional models of decision making under uncertainty explain human behavior in simple situations with a minimal set of alternatives and attributes. Some of them, such as prospect theory, have been proven successful and robust in such simple situations. Yet, less is known about the preference formation during decision making in more complex cases. Furthermore, it is generally accepted that attention plays a role in the decision process but most theories make simplifying assumptions about where attention is deployed. In this study, we replace these assumptions by measuring where humans deploy overt attention, i.e. where they fixate. To assess the influence of task complexity, participants perform two tasks. The simpler of the two requires participants to choose between two alternatives with two attributes each (four items to consider). The more complex one requires a choice between four alternatives with four attributes each (16 items to consider). We then compare a large set of model classes, of different levels of complexity, by considering the dynamic interactions between uncertainty, attention and pairwise comparisons between attribute values. The task of all models is to predict what choices humans make, using the sequence of observed eye movements for each participant as input to the model. We find that two models outperform all others. The first is the two-layer leaky accumulator which predicts human choices on the simpler task better than any other model. We call the second model, which is introduced in this study, TNPRO. It is modified from a previous model from management science and designed to deal with highly complex decision problems. Our results show that this model performs well in the simpler of our two tasks (second best, after the accumulator model) and best for the complex task. Our results suggest that, when faced with complex choice problems, people prefer to accumulate preference based on attention-guided pairwise comparisons.

In humans, risk attitude is highly context-dependent, varying with wealth levels or for different potential outcomes, such as gains or losses. These behavioral effects have been modelled using prospect theory, with the key assumption that humans represent the value of each available option asymmetrically as a gain or loss relative to a reference point. It remains unknown how these computations are implemented at the neuronal level. Here we show that macaques, like humans, change their risk attitude across wealth levels and gain/loss contexts using a token gambling task. Neurons in the anterior insular cortex (AIC) encode the ‘reference point’ (i.e., the current wealth level of the monkey) and reflect ‘loss aversion’ (i.e., option value signals are more sensitive to change in the loss than in the gain context) as postulated by prospect theory. In addition, changes in the activity of a subgroup of AIC neurons correlate with the inter-trial fluctuations in choice and risk attitude. Taken together, we show that the primate AIC in risky decision-making may be involved in monitoring contextual information used to guide the animal’s willingness to accept risk.

Classically, specific orbitofrontal cortex (OFC) neurons are thought to represent attributes of specific decision options. A new model proposes instead that OFC neurons represent whichever option is currently attended. A recent study, however, tests these two models and rules out the 'current-focus-of-attention' model.

Summary Real-world value often depends on subtle, continuously variable visual cues specific to particular object categories, like the tailoring of a suit, the condition of an automobile, or the construction of a house. Here, we used microelectrode recording in behaving monkeys to test two possible mechanisms for category-specific value-cue processing: (1) previous findings suggest that prefrontal cortex (PFC) identifies object categories, and based on category identity, PFC could use top-down attentional modulation to enhance visual processing of category-specific value cues, providing signals to PFC for calculating value, and (2) a faster mechanism would be first-pass visual processing of category-specific value cues, immediately providing the necessary visual information to PFC. This, however, would require learned mechanisms for processing the appropriate cues in a given object category. To test these hypotheses, we trained monkeys to discriminate value in four letter-like stimulus categories. Each category had a different, continuously variable shape cue that signified value (liquid reward amount) as well as other cues that were irrelevant. Monkeys chose between stimuli of different reward values. Consistent with the first-pass hypothesis, we found early signals for category-specific value cues in area TE (the final stage in monkey ventral visual pathway) beginning 81 ms after stimulus onset—essentially at the start of TE responses. Task-related activity emerged in lateral PFC approximately 40 ms later and consisted mainly of category-invariant value tuning. Our results show that, for familiar, behaviorally relevant object categories, high-level ventral pathway cortex can implement rapid, first-pass processing of category-specific value cues.

Response inhibition is the most basic form of behavioral control, which can occur either proactively to anticipate known task requirements, or reactively in response to sudden changes in the environment. This review will highlight some of the recent progress that has been made in understanding the mechanisms of response inhibition. Neurophysiological experiments in primates and rodents have uncovered a common neural network underlying reactive motor control. However, important questions regarding the exact locus of inhibitory control are still open. Other experiments have begun to investigate proactive control mechanisms in the medial frontal cortex. Proactive control might have a more general function in behavioral control by regulating speed-accuracy tradeoffs and the urgency to make a decision.

Voluntary behaviour requires control mechanisms that ensure our ability to act independently of habitual and innate response tendencies. Electrophysiological experiments, using the stop-signal task in humans, monkeys and rats, have uncovered a core network of brain structures that is essential for response inhibition. This network is shared across mammals and seems to be conserved throughout their evolution. Recently, new research building on these earlier findings has started to investigate the interaction between response inhibition and other control mechanisms in the brain. Here we describe recent progress in three different areas: selectivity of movement inhibition across different motor systems, re-orientation of motor actions and action evaluation. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’.

A key component of executive control and decision making is the ability to use the consequences of chosen actions to update and inform the process of future action selection. Evaluative signals, which monitor the outcomes of actions, are critical for this ability. Signals related to the evaluation of actions have been identified in eye movement-related areas of the medial frontal cortex. Here we examined whether such evaluative signals are also present in areas of the medial frontal cortex related to arm movements. To answer this question, we recorded from cells in the supplementary motor area (SMA) and pre-SMA, while monkeys performed an arm movement version of the countermanding paradigm. SMA and pre-SMA have been implicated in the higher-order control of movement selection and execution, although their precise role within the skeletomotor control circuit is unclear. We found evaluative signals that encode information about the expected outcome of the reward, the actual outcome, and the mismatch between actual and intended outcome. These findings suggest that signals that monitor and evaluate movement outcomes are represented throughout the medial frontal cortex, playing a general role across effector systems. These evaluation signals supervise the relationship between intentional motor behavior and reward expectation and could be used to adaptively shape future goal-directed behavior.

The role of top-down control in visual search has been a subject of much debate. Recent research has focused on whether attentional and oculomotor capture by irrelevant salient distractors can be modulated through top-down control, and if so, whether top-down control can be rapidly initiated based on current task goals. In the present study, participants searched for a unique shape in an array containing otherwise homogeneous shapes. A cue prior to each trial indicated the probability that an irrelevant color singleton distractor would appear on that trial. Initial saccades were less likely to land on the target and participants took longer to initiate a saccade to the target when a color distractor was present than when it was absent; this cost was greatly reduced on trials in which the probability that a distractor would appear was high, as compared to when the probability was low. These results suggest that top-down control can modulate oculomotor capture in visual search, even in a singleton search task in which distractors are known to readily capture both attention and the eyes. Furthermore, the results show that top-down distractor suppression mechanisms can be initiated quickly in anticipation of irrelevant salient distractors and can be adjusted on a trial-by-trial basis.

We describe intracranial local field potentials (LFP) recorded in the anterior cingulate cortex (ACC) of macaque monkeys performing a saccade countermanding task. The most prominent feature at ∼70% of sites was greater negative polarity after errors than after rewarded correct trials. This negative polarity was also evoked in unrewarded correct trials. The LFP evoked by the visual target was much less polarized, and the weak presaccadic modulation was insufficient to control the initiation of saccades. When saccades were cancelled, LFP modulation decreased slightly with the magnitude of response conflict that corresponds to the coactivation of gaze-shifting and -holding neurons estimated from the probability of canceling. However, response time adjustments on subsequent trials were not correlated with LFP polarity on individual trials. The results provide clear evidence that error- and feedback-related, but not conflict-related, signals are carried by the LFP in the macaque ACC. Finding performance monitoring field potentials in the ACC of macaque monkeys establishes a bridge between event-related potential and functional brain-imaging studies in humans and neurophysiology studies in non-human primates.

Imagine you are at an intersection, waiting for the traffic lights. They turn green, and you are about to press the gas pedal, when suddenly a cyclist swerves into your lane. Before your foot has actually moved, you have to rapidly prevent it from moving as planned. This example highlights the

To explore how eye and hand movements are controlled in a stop task, we introduced effector uncertainty by instructing subjects to initiate and occasionally inhibit eye, hand, or eye + hand movements in response to a color-coded foveal or tone-coded auditory stop signal. Regardless of stop signal modality, stop signal reaction time was shorter for eye movements than for hand movements, but notably did not vary with knowledge about which movement to cancel. Most errors on eye + hand stopping trials were combined eye + hand movements. The probability and latency of signal respond eye and hand movements corresponded to predictions of Logan and Cowan's (1984) race model applied to each effector independently.

Real-life decisions often involve multiple intermediate choices among competing, interdependent options. Lorteije et al. (2015) introduce a new paradigm for dissecting the neural strategies underlying such decisions.

Choices are made with varying degrees of confidence, a cognitive signal representing the subjective belief in the optimality of the choice. Confidence has been mostly studied in the context of perceptual judgments, in which choice accuracy can be measured using objective criteria. Here, we study confidence in subjective value-based decisions. We recorded in the supplementary eye field (SEF) of monkeys performing a gambling task, where they had to use subjective criteria for placing bets. We found neural signals in the SEF that explicitly represent choice confidence independent from reward expectation. This confidence signal appeared after the choice and diminished before the choice outcome. Most of this neuronal activity was negatively correlated with confidence, and was strongest in trials on which the monkey spontaneously withdrew his choice. Such confidence-related activity indicates that the SEF not only guides saccade selection, but also evaluates the likelihood that the choice was optimal. This internal evaluation influences decisions concerning the willingness to bear later costs that follow from the choice or to avoid them. More generally, our findings indicate that choice confidence is an integral component of all forms of decision-making, whether they are based on perceptual evidence or on value estimations.

This chapter describes the role of single-cell recordings in understanding the mechanisms underlying human cognition. Cognition is a function of the brain, a complex computational network, whose most elementary nodes are made up out of individual neurons. These neurons encode information and influence each other through a dynamically changing pattern of action potentials. For this reason, the activity of neurons in the awake, behaving brain constitutes the most fundamental form of neural data for cognitive neuroscience. This chapter discusses a number of technical issues and challenges of single-cell neurophysiology using a recent project of the authors as an example. We discuss issues such as the choice of an appropriate animal model, the role of psychophysics, technical challenges surrounding the simultaneous recording of multiple neurons, and various methods for perturbation experiments. The chapter closes with a consideration of the challenge that the brain’s complexity poses for fully understanding any realistic nervous circuit, and of the importance of conceptual insights and mathematical models in the interpretation of single-cell recordings.

Success requires deciding among alternatives, controlling the initiation of movements, and judging the consequences of actions. When alternatives are difficult to distinguish, habitual responses must be overcome, or consequences are uncertain, deliberation is necessary and a supervisory system exerts control over the processes that produce sensory-guided movements. We have investigated these processes by recording neural activity in the frontal lobe of macaque monkeys performing a countermanding task. Distinct neurons in the frontal eye field respond to visual stimuli or control the production of the movements. In the supplementary eye field and anterior cingulate cortex, neurons appear not to control directly movement initiation but instead signal the production of errors, the anticipation and delivery of reinforcement, and the presence of processing conflict. These signals form the core of current models of supervisory control of sensorimotor processes.

Executive control involves the ability to flexibly inhibit or change an action when it is contextually inappropriate. Using the complimentary techniques of human fMRI and monkey electrophysiology in a context-dependent stop signal task, we found a functional double dissociation between the right ventrolateral prefrontal cortex (rVLPFC) and the bi-lateral frontal eye field (FEF). Different regions of rVLPFC were associated with context-based signal meaning versus intention to inhibit a response, while FEF activity corresponded to success or failure of the response inhibition regardless of the stimulus response mapping or the context. These results were validated by electrophysiological recordings in rVLPFC and FEF from one monkey. Inhibition of a planned behavior is therefore likely not governed by a single brain system as had been previously proposed, but instead depends on two distinct neural processes involving different sub-regions of the rVLPFC and their interactions with other motor-related brain regions.

Intelligent behaviour requires self-control based on the consequences of actions. The countermanding task is designed to study self-control; it requires subjects to withhold planned movements in response to an imperative stop signal, which they can do with varying success. In humans, the medial frontal cortex has been implicated in the supervisory control of action1,2,3. In monkeys, the supplementary eye field in the dorsomedial frontal cortex is involved in producing eye movements, but its precise function has not been clarified4. To investigate the role of the supplementary eye field in the control of eye movements, we recorded neural activity in macaque monkeys trained to perform an eye movement countermanding task. Distinct groups of neurons were active after errors, after successful withholding of a partially prepared movement, or in association with reinforcement. These three forms of activation could not be explained by sensory or motor factors. Our results lead us to put forward the hypothesis that the supplementary eye field contributes to monitoring the context and consequences of eye movements.

Objects in the environment differ in their low-level perceptual properties (e.g., how easily a fruit can be recognized) as well as in their subjective value (how tasty it is). We studied the influence of visual salience on value-based decisions using a two alternative forced choice task, in which human subjects rapidly chose items from a visual display. All targets were equally easy to detect. Nevertheless, both value and salience strongly affected choices made and reaction times. We analyzed the neuronal mechanisms underlying these behavioral effects using stochastic accumulator models, allowing us to characterize not only the averages of reaction times but their full distributions. Independent models without interaction between the possible choices failed to reproduce the observed choice behavior, while models with mutual inhibition between alternative choices produced much better results. Mutual inhibition thus is an important feature of the decision mechanism. Value influenced the amount of accumulation in all models. In contrast, increased salience could either lead to an earlier start (onset model) or to a higher rate (speed model) of accumulation. Both models explained the data from the choice trials equally well. However, salience also affected reaction times in no-choice trials in which only one item was present, as well as error trials. Only the onset model could explain the observed reaction time distributions of error trials and no-choice trials. In contrast, the speed model could not, irrespective of whether the rate increase resulted from more frequent accumulated quanta or from larger quanta. Visual salience thus likely provides an advantage in the onset, not in the processing speed, of value-based decision making.

Consensus is emerging that the medial frontal lobe of the brain is involved in monitoring performance, but precisely what is monitored remains unclear. A saccade-countermanding task affords an experimental dissociation of neural signals of error, reinforcement, and conflict. Single-unit activity was monitored in the anterior cingulate cortex of monkeys performing this task. Neurons that signaled errors were found, half of which responded to the omission of earned reinforcement. A further diversity of neurons signaled earned or unexpected reinforcement. No neurons signaled the form of conflict engendered by interruption of saccade preparation produced in this task. These results are consistent with the hypothesis that the anterior cingulate cortex monitors the consequences of actions.

The outcomes of many decisions are uncertain and therefore need to be evaluated. We studied this evaluation process by recording neuronal activity in the supplementary eye field (SEF) during an oculomotor gambling task. While the monkeys awaited the outcome, SEF neurons represented attributes of the chosen option, namely, its expected value and the uncertainty of this value signal. After the gamble result was revealed, a number of neurons reflected the actual reward outcome. Other neurons evaluated the outcome by encoding the difference between the reward expectation represented during the delay period and the actual reward amount (i.e., the reward prediction error). Thus, SEF encodes not only reward prediction error but also all the components necessary for its computation: the expected and the actual outcome. This suggests that SEF might actively evaluate value-based decisions in the oculomotor domain, independent of other brain regions.

Adaptive behavior requires the ability to flexibly control actions. This can occur either proactively to anticipate task requirements, or reactively in response to sudden changes. Recent work in humans has identified a network of cortical and subcortical brain region that might have an important role in proactive and reactive control. However, due to technical limitations, such as the spatial and temporal resolution of the BOLD signal, human imaging experiments are not able to disambiguate the specific function(s) of these brain regions. These limitations can be overcome through single-unit recordings in non-human primates. In this article, we describe the behavioral and physiological evidence for dual mechanisms of control in response inhibition in the medial frontal cortex of monkeys performing the stop signal or countermanding task.

There have been conflicting reports on the chemical nature of the projection of the pretectal nuclei [nucleus of the optic tract and dorsal terminal nucleus of the accessory optic tract (NOT-DTN complex) and posterior pretectal nucleus] to the lateral geniculate nucleus and inferior olive. There is evidence that the pretecto-geniculate pathway is inhibitory. However, most attempts to verify the GABAergic nature of the projection neurons have failed. In order to answer this question, we employed a combination of retrograde transport and in situ hybridization. Rhodamine-labelled latex microspheres were injected into the electrophysiologically identified lateral geniculate nucleus. In addition, fluorescein-labelled latex microspheres were injected into the inferior olive. Retrograde axonal transport labelled large pretectal neurons. We then applied riboprobes specific for glutamic acid decarboxylase mRNA. We were able to demonstrate glutamic acid decarboxylase mRNA expression in up to 70% of lateral geniculate nucleus-projecting NOT-DTN and posterior pretectal nucleus neurons but in none of the pretecto-olivary projection neurons. The results suggest that the pretecto-geniculate projection is GABAergic in nature, which would confirm previous electrophysiological and morphological observations. The pretecto-olivary projection is not GABAergic.

Adaptive behavior requires the ability to flexibly control actions. This can occur either proactively to anticipate task requirements, or reactively in response to sudden changes. Here we report neuronal activity in the supplementary motor area (SMA) that is correlated with both forms of behavioral control. Single-unit and multiunit activity and intracranial local field potentials (LFPs) were recorded in macaque monkeys during a stop-signal task, which elicits both proactive and reactive behavioral control. The LFP power in high- (60–150 Hz) and low- (25–40 Hz) frequency bands was significantly correlated with arm movement reaction time, starting before target onset. Multiunit and single-unit activity also showed a significant regression with reaction time. In addition, LFPs and multiunit and single-unit activity changed their activity level depending on the trial history, mirroring adjustments on the behavioral level. Together, these findings indicate that neuronal activity in the SMA exerts proactive control of arm movements by adjusting the level of motor readiness. On trials when the monkeys successfully canceled arm movements in response to an unforeseen stop signal, the LFP power, particularly in a low (10–50 Hz) frequency range, increased early enough to be causally related to the inhibition of the arm movement on those trials. This indicated that neuronal activity in the SMA is also involved in response inhibition in reaction to sudden task changes. Our findings indicate, therefore, that SMA plays a role in the proactive control of motor readiness and the reactive inhibition of unwanted movements.

We recorded neuronal activity in the supplementary eye field (SEF) while monkeys made saccades to targets that yielded rewards of variable amount and uncertainty of delivery. Some SEF cells (29%) represented the anticipated value of the saccade target. These neurons encoded the value of the reward option but did not reflect the action necessary to obtain the reward. A plurality of cells (45%) represented both saccade direction and value. These neurons reflect action value, i.e., the value that is expected to follow from a specific saccade. Other cells (13%) represented only saccade direction. The SEF neurons matched the monkey's risk-seeking behavior by responding more strongly to the uncertain reward options than would be expected based on their response to the sure options and the cued outcome probability. Thus SEF neurons represented subjective, not expected, value. Across the SEF population, option-value signals developed early, ∼120 ms prior to saccade execution. Action-value and saccade direction signals developed ∼60 ms later. These results suggest that the SEF is involved in transforming option-value signals into action-value signals. However, in contrast to other oculomotor neurons, SEF neurons did not reach a constant level of activity before saccade onset. Instead the activity level of many (52%) SEF neurons still reflected value at the time just before saccade initiation. This suggests that SEF neurons guide the selection of a saccade based on value information but do not participate in the initiation of that saccade.

Voluntary control of behavior implies the ability to select what action is performed. The supplementary motor area (SMA) and pre-SMA are widely considered to be of central importance for this ability because of their role in movement initiation and inhibition. To test this hypothesis, we recorded from neurons in SMA and pre-SMA of monkeys performing an arm countermanding task. Temporal analysis of neural activity and behavior in this task allowed us to test whether neural activity is sufficient to control movement initiation or inhibition. Surprisingly, 99% (242 of 243) of movement-related neurons in SMA and pre-SMA failed to exhibit time-locked activity changes predictive of movement initiation in this task. We also found a second group of neurons that was more active during successful response cancelation. Of these putative inhibitory cells, 18% (7 of 40) responded early enough to be able to influence the cancelation of the movement. Thus, when tested with the countermanding task, the SMA/pre-SMA region may play a role in movement inhibition but does not appear to control movement initiation. However, the activity of 76% (202 of 267) of movement-related neurons was contingent on the expectation of reward and 42% of them reflected the amount of expected reward. These findings suggest that the movement-related activity in pre-SMA and SMA might represent the motivation for a specific action but does not determine whether or not that action is performed. This motivational signal in pre-SMA and SMA could provide an essential link between reward expectation and motor execution.

The goal of this study was to determine whether the activity of neurons in the supplementary eye field (SEF) is sufficient to control saccade initiation in macaque monkeys performing a saccade countermanding (stop signal) task. As previously observed, many neurons in the SEF increase the discharge rate before saccade initiation. However, when saccades are canceled in response to a stop signal, effectively no neurons with presaccadic activity display discharge rate modulation early enough to contribute to saccade cancellation. Moreover, SEF neurons do not exhibit a specific threshold discharge rate that could trigger saccade initiation. Yet, we observed more subtle relations between SEF activation and saccade production. The activity of numerous SEF neurons was correlated with response time and varied with sequential adjustments in response latency. Trials in which monkeys canceled or produced a saccade in a stop signal trial were distinguished by a modest difference in discharge rate of these SEF neurons before stop signal or target presentation. These findings indicate that neurons in the SEF, in contrast to counterparts in the frontal eye field and superior colliculus, do not contribute directly and immediately to the initiation of visually guided saccades. However the SEF may proactively regulate saccade production by biasing the balance between gaze-holding and gaze-shifting based on prior performance and anticipated task requirements.

The countermanding (or stop signal) task probes the control of the initiation of a movement by measuring subjects' ability to withhold a movement in various degrees of preparation in response to an infrequent stop signal. Previous research found that saccades are initiated when the activity of movement-related neurons reaches a threshold, and saccades are withheld if the growth of activity is interrupted. To extend and evaluate this relationship of frontal eye field (FEF) activity to saccade initiation, two new analyses were performed. First, we fit a neurometric function that describes the proportion of trials with a stop signal in which neural activity exceeded a criterion discharge rate as a function of stop signal delay, to the inhibition function that describes the probability of producing a saccade as a function of stop signal delay. The activity of movement-related but not visual neurons provided the best correspondence between neurometric and inhibition functions. Second, we determined the criterion discharge rate that optimally discriminated between the distributions of discharge rates measured on trials when saccades were produced or withheld. Differential activity of movement-related but not visual neurons could distinguish whether a saccade occurred. The threshold discharge rates determined for individual neurons through these two methods agreed. To investigate how reliably movement-related activity predicted movement initiation; the analyses were carried out with samples of activity from increasing numbers of trials from the same or from different neurons. The reliability of both measures of initiation threshold improved with number of trials and neurons to an asymptote of between 10 and 20 movement-related neurons. Combining the activity of visual neurons did not improve the reliability of predicting saccade initiation. These results demonstrate how the activity of a population of movement-related but not visual neurons in the FEF contributes to the control of saccade initiation. The results also validate these analytical procedures for identifying signals that control saccade initiation in other brain structures.

One important behavioral role for head movements is to assist in the redirection of gaze. However, primates also frequently make head movements that do not involve changes in the line of sight. Virtually nothing is known about the neural basis of these head-only movements. In the present study, single-unit extracellular activity was recorded from the superior colliculus while monkeys performed behavioral tasks that permit the temporal dissociation of gaze shifts and head movements. We sought to determine whether superior colliculus contains neurons that modulate their activity in association with head movements in the absence of gaze shifts and whether classic gaze-related burst neurons also discharge for head-only movements. For 26% of the neurons in our sample, significant changes in average firing rate could be attributed to head-only movements. Most of these increased their firing rate immediately prior to the onset of a head movement and continued to discharge at elevated frequency until the offset of the movement. Others discharged at a tonic rate when the head was stable and decreased their activity, or paused, during head movements. For many putative head cells, average firing rate was found to be predictive of head displacement. Some neurons exhibited significant changes in activity associated with gaze, eye-only, and head-only movements, although none of the gaze-related burst neurons significantly modulated its activity in association with head-only movements. These results suggest the possibility that the superior colliculus plays a role in the control of head movements independent of gaze shifts.

The stop-signal or countermanding task probes the ability to control action by requiring subjects to withhold a planned movement in response to an infrequent stop signal which they do with variable success depending on the delay of the stop signal. We investigated whether performance of humans and macaque monkeys in a saccade countermanding task was influenced by stimulus and performance history. In spite of idiosyncrasies across subjects several trends were evident in both humans and monkeys. Response time decreased after successive trials with no stop signal. Response time increased after successive trials with a stop signal. However, post-error slowing was not observed. Increased response time was observed mainly or only after cancelled (signal inhibit) trials and not after noncancelled (signal respond) trials. These global trends were based on rapid adjustments of response time in response to momentary fluctuations in the fraction of stop signal trials. The effects of trial sequence on the probability of responding were weaker and more idiosyncratic across subjects when stop signal fraction was fixed. However, both response time and probability of responding were influenced strongly by variations in the fraction of stop signal trials. These results indicate that the race model of countermanding performance requires extension to account for these sequential dependencies and provide a basis for physiological studies of executive control of countermanding saccade performance.

Modern economics no longer uses the concept of cardinal utility, which describes the value of a good independently of a comparison with another good. New electrophysiological recordings in primates performing economic choices suggest a neurological substrate for cardinal utility, a finding that economists should perhaps take note of.

The supplementary eye field registers the occurrence of conflict, errors and reward in macaque monkeys performing a saccade-countermanding task. Using intracortical microstimulation, we determined whether the supplementary eye field only monitors or can actually influence performance. Weak microstimulation of many sites in the supplementary eye field improved monkeys' performance on a 'stop signal' task by delaying saccade initiation. This effect depended on the context of the task because simple visually guided saccades were not delayed by the same stimulation. These results demonstrate that the supplementary eye field can exert contextual executive control over saccade generation.

The latency and variability of latency of single-unit responses to identical visual stimulation were measured in the frontal eye field (FEF), supplementary eye field (SEF), and anterior cingulate cortex (ACC) of macaque monkeys performing visually guided saccades. The mean visual response latency was significantly shorter in FEF (64 ms) than in SEF (81 ms) or ACC (100 ms), and latency values determined by four methods agreed. The latency variability of the visual response was respectively less in FEF (21 ms) than in SEF (37 ms) or ACC (41 ms). Latency, variability of latency, and magnitude of the visual responses were correlated within FEF and SEF but not ACC. These characteristics of the visual response are consistent with the degree of convergence of visual afferents to these areas and constrain hypotheses about visual processing in the frontal lobe.

The prerequisite for behavioral self-control is the ability to initiate actions and to cancel planned actions. A rational choice about which action to initiate or to withhold must be informed by the consequences of prior actions. The neuronal correlates of these processes have been studied with the countermanding paradigm. This task requires subjects to withhold planned movements in response to an imperative stop signal, which they can do with varying success. By recording the activity of single neurons in different parts of the frontal cortex of macaque monkeys performing this task, signals that are sufficient for controlling the initiation and inhibition of movements and other signals that evaluate the consequences of these movements have been identified.

Reaching with the arm to a newly appearing target is usually preceded by a saccadic eye movement. Neurons in the superior colliculus (SC) constitute one important brain structure controlling saccades. Yet, the SC also contains reach neurons activated during arm movements, whose location extends also deeper into the underlying mesencephalic reticular formation. Reach neurons can be divided into two classes based on their different modulation with respect to gaze position. For the first class, the gaze-independent reach neurons, the activity does not depend on which location is currently fixated, but solely on the position and movement of the (usually contralateral) arm. There is a correlation of the activity of these neurons with the activity of shoulder muscles. The second class, the gaze-related reach neurons, are active for reaches into a specific area relative to the current point of gaze. This means the target has to project on a certain part of the retina, while it is not important which arm is used or by which trajectory the target will be reached. Many fixation neurons in the rostral pole of the SC discharge tonically during fixation and pause during saccades. For some fixation neurons, the activity can be increased during simultaneous arm movements, for others decreased. Two psychophysical experiments with healthy human subjects show possible behavioral correlates of an interaction between these reach neurons and visuomotort neurons within the SC.

Correlation of primate superior colliculus and reticular formation discharge with proximal limb muscle activity. We studied the discharge of neurons from both the superior colliculus (SC) and the underlying mesencephalic reticular formation (MRF) and its relation to the simultaneously recorded activity of 11 arm muscles. The 242 neurons tested with a center-out reach task yielded 2,586 pairs of neuron/muscle cross-correlations (normalized, such that perfect correlations are ±1.0). Of these, 43% had peaks with magnitude as large as 0.15, a value that corresponds to the 5% level of significance, and 16% were as large as 0.25. The great majority of peaks in this latter group was positive. The median lag time within this group was 52 ms, indicating that the neuronal discharge tended to precede the correlated muscle activity. We found a small but significantly higher proportion of cells with these relatively strong correlations in the MRF than in the SC. For both areas, these occurred most frequently with muscles of the shoulder girdle and became less frequent for axial as well as for increasingly distal arm musculature. The results support a role for the SC and MRF in guiding the arm during reach movements via the control of proximal limb musculature.

Responses of relay cells in the A-laminae of the dorsal lateral geniculate nucleus (LGNd) during spontaneous saccades and saccade-like visual stimulation were extracellularly recorded in awake cats. Ninety-six out of 137 cells recorded (42 X and 54 Y cells) were responsive during spontaneous saccadic eye movements. All Y cells and 67% of the X cells responded with burst activity, i.e. with either one or two activity peaks during and after saccades. Thirty-three percent of the X cells were inhibited during saccades. Excitatory peaks occurred at mean latencies of 33 ms and 31 ms for X and Y cells, respectively. Comparable burst responses were obtained when retinal image shifts similar to those during saccades were induced by external saccade-like stimulus movements. However, the latencies of excitatory peak activity were significantly longer to external stimuli than to the onsets of saccades. This indicates the existence of an eye movement-related input which activates LGNd relay cells in addition to the visual input. We propose that the pretectogeniculate projection may contribute to the responses of LGNd relay cells following saccadic eye movements via a disinhibitory input and that this input could be involved in intra- and postsaccadic modulations of the transfer of visual signals to visual cortex.

Orienting movements in space are governed by information from different sensory modalities. Although the sensory signals from the eyes, the ears, or from the body surface are mapped in different reference frames, the neural motor system generates a motor program which is organized within a body-centered coordinate system. This implies that coordinate transformations are a necessary step in the sensorimotor signal processing [11, 19].