The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment

Dorsal striatum coding for the timely execution of action sequences

The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore–exploit balance.

Dissociating the Impact of Movement Time and Energy Costs on Decision-Making and Action Initiation in Humans

Recent theories and data suggest that adapted behavior involves economic computations during which multiple trade-offs between reward value, accuracy requirement, energy expenditure, and elapsing time are solved so as to obtain rewards as soon as possible while spending the least possible amount of energy. However, the relative impact of movement energy and duration costs on perceptual decision-making and movement initiation is poorly understood. Here, we tested 31 healthy subjects on a perceptual decision-making task in which they executed reaching movements to report probabilistic choices. In distinct blocks of trials, the reaching duration (“Time” condition) and energy (“Effort” condition) costs were independently varied compared to a “Reference” block, while decision difficulty was maintained similar at the block level. Participants also performed a simple delayed-reaching (DR) task aimed at estimating movement initiation duration in each motor condition. Results in that DR task show that long duration movements extended reaction times (RTs) in most subjects, whereas energy-consuming movements led to mixed effects on RTs. In the decision task, about half of the subjects decreased their decision durations (DDs) in the Time condition, while the impact of energy on DDs were again mixed across subjects. Decision accuracy was overall similar across motor conditions. These results indicate that movement duration and, to a lesser extent, energy expenditure, idiosyncratically affect perceptual decision-making and action initiation. We propose that subjects who shortened their choices in the time-consuming condition of the decision task did so to limit a drop of reward rate.

Changes of cerebral network activity after invasive stimulation of the mesencephalic locomotor region in a rat stroke model

Motor deficits after stroke reflect both, focal lesion and network alterations in brain regions distant from infarction. This remote network dysfunction may be caused by aberrant signals from cortical motor regions travelling via mesencephalic locomotor region (MLR) to other locomotor circuits. A method for modulating disturbed network activity is deep brain stimulation. Recently, we have shown that high frequency stimulation (HFS) of the MLR in rats has restored gait impairment after photothrombotic stroke (PTS). However, it remains elusive which cerebral regions are involved by MLR-stimulation and contribute to the improvement of locomotion. Seventeen male Wistar rats underwent photothrombotic stroke of the right sensorimotor cortex and implantation of a microelectrode into the right MLR. 2-[¹⁸F]Fluoro-2-deoxyglucose ([¹⁸F]FDG)-positron emission tomography (PET) was conducted before stroke and thereafter, on day 2 and 3 after stroke, without and with MLR-HFS, respectively. [¹⁸F]FDG-PET imaging analyses yielded a reduced glucose metabolism in the right cortico-striatal thalamic loop after PTS compared to the state before intervention. When MLR-HFS was applied after PTS, animals exhibited a significantly higher uptake of [¹⁸F]FDG in the right but not in the left cortico-striatal thalamic loop. Furthermore, MLR-HFS resulted in an elevated glucose metabolism of right-sided association cortices related to the ipsilateral sensorimotor cortex. These data support the concept of diaschisis i.e., of dysfunctional brain areas distant to a focal lesion and suggests that MLR-HFS can reverse remote network effects following PTS in rats which otherwise may result in chronic motor symptoms.

The importance of urgency in decision making based on dynamic information

A standard view in the literature is that decisions are the result of a process that accumulates evidence in favor of each alternative until such accumulation reaches a threshold and a decision is made. However, this view has been recently questioned by an alternative proposal that suggests that, instead of accumulated, evidence is combined with an urgency signal. Both theories have been mathematically formalized and supported by a variety of decision-making tasks with constant information. However, recently, tasks with changing information have shown to be more effective to study the dynamics of decision making. Recent research using one of such tasks, the tokens task, has shown that decisions are better described by an urgency mechanism than by an accumulation one. However, the results of that study could depend on a task where all fundamental information was noiseless and always present, favoring a mechanism of non-integration, such as the urgency one. Here, we wanted to address whether the same conclusions were also supported by an experimental paradigm in which sensory evidence was removed shortly after it was provided, making working memory necessary to properly perform the task. Here, we show that, under such condition, participants' behavior could be explained by an urgency-gating mechanism that low-pass filters the mnemonic information and combines it with an urgency signal that grows with time but not by an accumulation process that integrates the same mnemonic information. Thus, our study supports the idea that, under certain situations with dynamic sensory information, decisions are better explained by an urgency-gating mechanism than by an accumulation one.

Reducing behavioral dimensions to study brain-environment interactions

Movement vigor provides a window on action valuation. But what is vigor, and how to measure it in the first place? Strikingly, many different co-varying vigor-related metrics can be found in the literature. I believe this is because vigor, just like the neural circuits that determine it, is an integrated, low-dimensional parameter. As such, it can only be roughly estimated.

The road towards understanding embodied decisions

Most current decision-making research focuses on classical economic scenarios, where choice offers are prespecified and where action dynamics play no role in the decision. However, our brains evolved to deal with different choice situations: "embodied decisions". As examples of embodied decisions, consider a lion that has to decide which gazelle to chase in the savannah or a person who has to select the next stone to jump on when crossing a river. Embodied decision settings raise novel questions, such as how people select from time-varying choice options and how they track the most relevant choice attributes; but they have long remained challenging to study empirically. Here, we summarize recent progress in the study of embodied decisions in sports analytics and experimental psychology. Furthermore, we introduce a formal methodology to identify the relevant dimensions of embodied choices (present and future affordances) and to map them into the attributes of classical economic decisions (probabilities and utilities), hence aligning them. Studying embodied decisions will greatly expand our understanding of what decision-making is.

Beyond information rate, the capacity of cognitive control predicts response criteria in perceptual decision-making

Recent studies indicate that higher capacity of cognitive control (CCC) represents higher processing efficiency (i.e., high accuracy with fast speed). However, the speed-accuracy tradeoff (SAT) exists ubiquitously in decision-making, and little is known about whether and how the CCC is associated with SAT and whether the CCC-SAT relationship would be affected by changes in information entropy. In this study, fifty-nine college students performed a majority function task in which accuracy and response speed were equally emphasized. A Bayesian-based hierarchical drift diffusion modeling method was used to estimate three parameters of boundary separation, drift rate, and nondecision time for each participant in this task. In addition, the CCC of each participant was estimated. The results showed that the CCC was positively correlated with the SAT represented by jointly increasing accuracy and reaction time (RT), which was modulated by the change in task-relevant information entropy. Multiple mediation analyses indicated that drift rate served as the key mediator in the positive CCC-accuracy relationship while boundary separation played the major mediating role in the positive CCC-RT relationship. These findings suggest that the CCC reflects not only the rate of information processing but also decision strategies for achieving current goals.

Organization of Parieto-Prefrontal and Temporo-Prefrontal Networks in the Macaque

The connectivity among architectonically defined areas of the frontal, parietal, and temporal cortex of the macaque has been extensively mapped through tract tracing methods. To investigate the statistical organization underlying this connectivity, and identify its underlying architecture, we performed a hierarchical cluster analysis on 69 cortical areas based on their anatomically defined inputs. We identified 10 frontal, 4 parietal, and 5 temporal hierarchically related sets of areas (clusters), defined by unique sets of inputs and typically composed of anatomically contiguous areas. Across cortex, clusters that share functional properties were linked by dominant information processing circuits in a topographically organized manner that reflects the organization of the main fiber bundles in the cortex. This led to a dorsal-ventral subdivision of the frontal cortex, where dorsal and ventral clusters showed privileged connectivity with parietal and temporal areas, respectively. Ventrally, temporo-frontal circuits encode information to discriminate objects in the environment, their value, emotional properties, and functions such as memory and spatial navigation. Dorsal parieto-frontal circuits encode information for selecting, generating, and monitoring appropriate actions based on visual-spatial and somatosensory information. This organization may reflect evolutionary antecedents, in which the vertebrate pallium, which is the ancestral cortex, was defined by a ventral and lateral olfactory region and a medial hippocampal region.

A cerebellar-thalamocortical pathway drives behavioral context-dependent movement initiation

Executing learned motor behaviors often requires the transformation of sensory cues into patterns of motor commands that generate appropriately timed actions. The cerebellum and thalamus are two key areas involved in shaping cortical output and movement, but the contribution of a cerebellar-thalamocortical pathway to voluntary movement initiation remains poorly understood. Here, we investigated how an auditory "go cue" transforms thalamocortical activity patterns and how these changes relate to movement initiation. Population responses in dentate/interpositus-recipient regions of motor thalamus reflect a time-locked increase in activity immediately prior to movement initiation that is temporally uncoupled from the go cue, indicative of a fixed-latency feedforward motor timing signal. Blocking cerebellar or motor thalamic output suppresses movement initiation, while stimulation triggers movements in a behavioral context-dependent manner. Our findings show how cerebellar output, via the thalamus, shapes cortical activity patterns necessary for learned context-dependent movement initiation.

Thalamic input to motor cortex facilitates goal-directed action initiation

Prompt execution of planned motor action is essential for survival. The interactions between frontal cortical circuits and the basal ganglia are central to goal-oriented action selection and initiation.^1-4 In rodents, the ventromedial thalamic nucleus (VM) is one of the critical nodes that conveys the output of the basal ganglia to the frontal cortical areas including the anterior lateral motor cortex (ALM).^5-9 Recent studies showed the critical role of ALM and its interplay with the motor thalamus in preparing sensory-cued rewarded movements, specifically licking.^10-12 Work in primates suggests that the basal ganglia output to the motor thalamus transmits an urgency or vigor signal,^13-15 which leads to shortened reaction times and faster movement initiation. As yet, little is known about what signals are transmitted from the motor thalamus to the cortex during cued movements and how these signals contribute to movement initiation. In the present study, we employed a tactile-cued licking task in mice while monitoring reaction times of the initial lick. We found that inactivation of ALM delayed the initiation of cued licking. Two-photon Ca²⁺ imaging of VM axons revealed that the majority of the axon terminals in ALM were transiently active during licking. Their activity was predictive of the time of the first lick. Chemogenetic and optogenetic manipulation of VM axons in ALM indicated that VM inputs facilitate the initiation of cue-triggered and impulsive licking in trained mice. Our results suggest that VM thalamocortical inputs increase the probability and vigor of initiating planned motor responses.

Coordinated increase of reliable cortical and striatal ensemble activations during recovery after stroke

Skilled movements rely on a coordinated cortical and subcortical network, but how this network supports motor recovery after stroke is unknown. Previous studies focused on the perilesional cortex (PLC), but precisely how connected subcortical areas reorganize and coordinate with PLC is unclear. The dorsolateral striatum (DLS) is of interest because it receives monosynaptic inputs from motor cortex and is important for learning and generation of fast reliable actions. Using a rat focal stroke model, we perform chronic electrophysiological recordings in motor PLC and DLS during long-term recovery of a dexterous skill. We find that recovery is associated with the simultaneous emergence of reliable movement-related single-trial ensemble spiking in both structures along with increased cross-area alignment of spiking. Our study highlights the importance of consistent neural activity patterns across brain structures during recovery and suggests that modulation of cross-area coordination can be a therapeutic target for enhancing motor function post-stroke.

Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans

A successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, called urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. Forty females and 34 males took part (mean age, 23.4 years). We find that an evoked potential time locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathologic decision-making such as in impulse control and addictive disorders.SIGNIFICANCE STATEMENT Perceptual decisions are often described by a class of models that assumes that sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.

Movement-related changes in pallidocortical synchrony differentiate action execution and observation in humans

OBJECTIVE

Suppression of local and network alpha and beta oscillations in the human basal ganglia-thalamocortical (BGTC) circuit is a prominent feature of movement, including suppression of local alpha/beta power, cross-region beta phase coupling, and cortical and subcortical phase-amplitude coupling (PAC). We hypothesized that network-level coupling is more directly related to movement execution than local power changes, given the role of pathological network hypersynchrony in movement disorders such as Parkinson disease (PD). Understanding the specificity of these movement-related signals is important for designing novel therapeutics.

METHODS

We recorded globus pallidus internus (GPi) and motor cortical local field potentials during movement execution, passive movement observation and rest in 12 patients with PD undergoing deep brain stimulator implantation.

RESULTS

Local alpha/beta power is suppressed in the globus pallidus and motor cortex during both action execution and action observation, although less so during action observation. In contrast, pallidocortical phase synchrony and GPi and motor cortical alpha/beta-gamma PAC are suppressed only during action execution.

CONCLUSIONS

The functional dissociation across tasks in pallidocortical network activity suggests a particularly important role of network coupling in motor execution.

SIGNIFICANCE

Network level recordings provide important specificity in differentiating motor behavior and may provide significant value for future closed loop therapies.

The Self-Prioritization Effect: Self-referential processing in movement highlights modulation at multiple stages

A wealth of recent research supports the validity of the Self-Prioritization Effect (SPE)—the performance advantage for responses to self-associated as compared with other-person-associated stimuli in a shape–label matching task. However, inconsistent findings have been reported regarding the particular stage(s) of information processing that are influenced. In one account, self-prioritization modulates multiple stages of processing, whereas according to a competing account, self-prioritization is driven solely by a modulation in central-stage information-processing. To decide between these two possibilities, the present study tested whether the self-advantage in arm movements previously reported could reflect a response bias using visual feedback (Experiment 1), or approach motivation processes (Experiments 1 and 2). In Experiment 1, visual feedback was occluded in a ballistic movement-time variant of the matching task, whereas in Experiment 2, task responses were directed away from the stimuli and the participant’s body. The advantage for self in arm-movement responses emerged in both experiments. The findings indicate that the self-advantage in arm-movement responses does not depend on the use of visual feedback or on a self/stimuli-directed response. They further indicate that self-relevance can modulate movement responses (predominantly) using proprioceptive, kinaesthetic, and tactile information. These findings support the view that self-relevance modulates arm-movement responses, countering the suggestion that self-prioritization only influences central-stage processes, and consistent with a multiple-stage influence instead.

Premotor Ramping of Thalamic Neuronal Activity Is Modulated by Nigral Inputs and Contributes to Control the Timing of Action Release

The ventromedial (VM)/ventro-anterior-lateral (VAL) motor thalamus is a key junction within the brain circuits sustaining normal and pathologic motor control functions and decision-making. In this area of thalamus, on one hand, the inhibitory nigro-thalamic pathway provides a main output from the basal ganglia, and, on the other hand, motor thalamo-cortical loops are involved in the maintenance of ramping preparatory activity before goal-directed movements. To better understand the nigral impact on thalamic activity, we recorded electrophysiological responses from VM/VAL neurons while male and female mice were performing a delayed right/left decision licking task. Analysis of correct (corr) and error trials revealed that thalamic ramping activity was stronger for premature licks (impulsive action) and weaker for trials with no licks [omission (omi)] compared with correct trials. Suppressing ramping activity through optogenetic activation of nigral terminals in the motor thalamus during the delay epoch of the task led to a reduced probability of impulsive action and an increased amount of omissions trials. We propose a parsimonious model explaining our data and conclude that a thalamic ramping mechanism contributes to the control of proper timing of action release and that inhibitory nigral inputs are sufficient to interrupt this mechanism and modulate the amount of motor impulsivity in this task.SIGNIFICANCE STATEMENT Coordinated neural activity in motor circuits is essential for correct movement preparation and execution, and even slight imbalances in neural processing can lead to failure in behavioral tasks or motor disorders. Here we focused on how failure to regulate the control of activity balance in the motor thalamus can be implicated in impulsive action release or omissions to act, through an activity ramping mechanism that is required for proper action release. Using optogenetic activation of inhibitory basal ganglia terminals in motor thalamus we show that basal ganglia input is well positioned to control this ramping activity and determine the timing of action initiation.

Evidence accumulation under uncertainty - a neural marker of emerging choice and urgency

To interact meaningfully with its environment, an agent must integrate external information with its own internal states. However, information about the environment is often noisy. In this study, we identify a neural correlate that tracks how asymmetries between competing alternatives evolve over the course of a decision. In our task participants had to monitor a stream of discrete visual stimuli over time and decide whether or not to act, on the basis of either strong or ambiguous evidence. We found that the classic P3 event-related potential evoked by sequential evidence items tracked decision-making processes and predicted participants' categorical choices on a single trial level, both when evidence was strong and when it was ambiguous. The P3 amplitudes in response to evidence supporting the eventually selected option increased over trial time as decisions evolved, being maximally different from the P3 amplitudes evoked by competing evidence at the time of decision. Computational modelling showed that both the neural dynamics and behavioural primacy and recency effects can be explained by a combination of (a) competition between mutually inhibiting accumulators for the two categorical choice outcomes, and (b) a context-dependant urgency signal. In conditions where evidence was presented at a low rate, urgency increased faster than in conditions when evidence was very frequent. We also found that the readiness potential, a classic marker of endogenously initiated actions, was observed preceding movements in all conditions - even when those were strongly driven by external evidence.

Prolonged response time helps eliminate residual errors in visuomotor adaptation

One persistent curiosity in visuomotor adaptation tasks is that participants often do not reach maximal performance. This incomplete asymptote has been explained as a consequence of obligatory computations within the implicit adaptation system, such as an equilibrium between learning and forgetting. A body of recent work has shown that in standard adaptation tasks, cognitive strategies operate alongside implicit learning. We reasoned that incomplete learning in adaptation tasks may primarily reflect a speed-accuracy tradeoff on time-consuming motor planning. Across three experiments, we find evidence supporting this hypothesis, showing that hastened motor planning may primarily lead to under-compensation. When an obligatory waiting period was administered before movement start, participants were able to fully counteract imposed perturbations (Experiment 1). Inserting the same delay between trials – rather than during movement planning – did not induce full compensation, suggesting that the motor planning interval influences the learning asymptote (Experiment 2). In the last experiment (Experiment 3), we asked participants to continuously report their movement intent. We show that emphasizing explicit re-aiming strategies (and concomitantly increasing planning time) also lead to complete asymptotic learning. Findings from all experiments support the hypothesis that incomplete adaptation is, in part, the result of an intrinsic speed-accuracy tradeoff, perhaps related to cognitive strategies that require parametric attentional reorienting from the visual target to the goal.

Involvement of Striatal Direct Pathway in Visual Spatial Attention in Mice

The basal ganglia are implicated in a range of perceptual functions [1], in addition to their well-known role in the regulation of movement [2]. One unifying explanation for these diverse roles is that the basal ganglia control the level of commitment to particular motor or cognitive outcomes based on the behavioral context [3, 4]. If this explanation is applicable to the allocation of visual spatial attention, then the involvement of basal ganglia circuits should incorporate the subject's expectations about the spatial location of upcoming events as well as the routing of visual signals that guide the response. From the viewpoint of signal detection theory, these changes in the level of commitment might correspond to shifts in the subject's decision criterion, one of two distinct components recently ascribed to visual selective attention [5]. We tested this idea using unilateral optogenetic activation of neurons in the dorsal striatum of mice during a visual spatial attention task [6], taking advantage of the ability to specifically target medium spiny neurons in the "direct" pathway associated with promoting responses [7, 8]. By comparing results across attention task conditions, we found that direct-pathway activation caused changes in performance determined by the spatial probability and location of the visual event. Moreover, across conditions with identical visual stimulation, activation shifted the decision criterion selectively when attention was directed to the contralateral visual field. These results demonstrate that activity through the basal ganglia may play an important and distinct role among the multifarious mechanisms that accomplish visual spatial attention.

Cortico-cerebellar interactions during goal-directed behavior

Preparatory activity is observed across multiple interconnected brain regions before goal-directed movement. Preparatory activity reflects discrete activity states representing specific future actions. It is unclear how this activity is mediated by multi-regional interactions. Recent evidence suggests that the cerebellum, classically associated with fine motor control, contributes to preparatory activity in the neocortex. We review recent advances and offer perspective on the function of cortico-cerebellar interactions during goal-directed behavior. We propose that the cerebellum learns to facilitate transitions between neocortical activity states. Transitions between activity states enable flexible and appropriately timed behavioral responses.

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning

The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. This is analogous to the statistical inference that has been extensively studied in the natural language processing field, where recent developments of recurrent neural networks have found many successes. We wonder whether these neural networks, the gated recurrent unit (GRU) networks in particular, reflect how the brain solves the contingency problem. Therefore, we build a GRU network framework inspired by the statistical learning approach of NLP and test it with four exemplar behavior tasks previously used in empirical studies. The network models are trained to predict future events based on past events, both comprising sensory, action, and reward events. We show the networks can successfully reproduce animal and human behavior. The networks generalize the training, perform Bayesian inference in novel conditions, and adapt their choices when event contingencies vary. Importantly, units in the network encode task variables and exhibit activity patterns that match previous neurophysiology findings. Our results suggest that the neural network approach based on statistical sequence learning may reflect the brain's computational principle underlying flexible and adaptive behaviors and serve as a useful approach to understand the brain.

Robust parallel decision-making in neural circuits with nonlinear inhibition

Animals frequently need to choose the best alternative from a set of possibilities, whether it is which direction to swim in or which food source to favor. How long should a network of neurons take to choose the best of N options? Theoretical results suggest that the optimal time grows as log(N), if the values of each option are imperfectly perceived. However, standard self-terminating neural network models of decision-making cannot achieve this optimal behavior. We show how using certain additional nonlinear response properties in neurons, which are ignored in standard models, results in a decision-making architecture that both achieves the optimal scaling of decision time and accounts for multiple experimentally observed features of neural decision-making.

An elemental computation in the brain is to identify the best in a set of options and report its value. It is required for inference, decision-making, optimization, action selection, consensus, and foraging. Neural computing is considered powerful because of its parallelism; however, it is unclear whether neurons can perform this max-finding operation in a way that improves upon the prohibitively slow optimal serial max-finding computation (which takes ∼N⁡log(N) time for N noisy candidate options) by a factor of N, the benchmark for parallel computation. Biologically plausible architectures for this task are winner-take-all (WTA) networks, where individual neurons inhibit each other so only those with the largest input remain active. We show that conventional WTA networks fail the parallelism benchmark and, worse, in the presence of noise, altogether fail to produce a winner when N is large. We introduce the nWTA network, in which neurons are equipped with a second nonlinearity that prevents weakly active neurons from contributing inhibition. Without parameter fine-tuning or rescaling as N varies, the nWTA network achieves the parallelism benchmark. The network reproduces experimentally observed phenomena like Hick’s law without needing an additional readout stage or adaptive N-dependent thresholds. Our work bridges scales by linking cellular nonlinearities to circuit-level decision-making, establishes that distributed computation saturating the parallelism benchmark is possible in networks of noisy, finite-memory neurons, and shows that Hick’s law may be a symptom of near-optimal parallel decision-making with noisy input.

Neural activity during a simple reaching task in macaques is counter to gating and rebound in basal ganglia-thalamic communication

Task-related activity in the ventral thalamus, a major target of basal ganglia output, is often assumed to be permitted or triggered by changes in basal ganglia activity through gating- or rebound-like mechanisms. To test those hypotheses, we sampled single-unit activity from connected basal ganglia output and thalamic nuclei (globus pallidus-internus [GPi] and ventrolateral anterior nucleus [VLa]) in monkeys performing a reaching task. Rate increases were the most common peri-movement change in both nuclei. Moreover, peri-movement changes generally began earlier in VLa than in GPi. Simultaneously recorded GPi-VLa pairs rarely showed short-time-scale spike-to-spike correlations or slow across-trials covariations, and both were equally positive and negative. Finally, spontaneous GPi bursts and pauses were both followed by small, slow reductions in VLa rate. These results appear incompatible with standard gating and rebound models. Still, gating or rebound may be possible in other physiological situations: simulations show how GPi-VLa communication can scale with GPi synchrony and GPi-to-VLa convergence, illuminating how synchrony of basal ganglia output during motor learning or in pathological conditions may render this pathway effective. Thus, in the healthy state, basal ganglia-thalamic communication during learned movement is more subtle than expected, with changes in firing rates possibly being dominated by a common external source.

The Dorsal Striatum Energizes Motor Routines

The dorsal striatum (dS) has been implicated in storing procedural memories and controlling movement kinematics. Since procedural memories are expressed through movements, the exact nature of the dS function has proven difficult to delineate. Here, we challenged rats in complementary locomotion-based tasks designed to alleviate this confound. Surprisingly, dS lesions did not impair the rats' ability to remember the procedure for the successful completion of motor routines. However, the speed and initiation of the reward-oriented phase of the routines were irreversibly altered by the dS lesion. Further behavioral analyses, combined with modeling in the optimal control framework, indicated that these kinematic alterations were well explained by an increased sensitivity to effort. Our work provides evidence supporting a primary role of the dS in modulating the kinematics of reward-oriented actions, a function that may be related to the optimization of the energetic costs of moving.

Confluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics

Although the decisions of our daily lives often occur in the context of temporal and reward structures, the impact of such regularities on decision-making strategy is poorly understood. Here, to explore how temporal and reward context modulate strategy, we trained 2 male rhesus monkeys to perform a novel perceptual decision-making task with asymmetric rewards and time-varying evidence reliability. To model the choice and response time patterns, we developed a computational framework for fitting generalized drift-diffusion models, which flexibly accommodate diverse evidence accumulation strategies. We found that a dynamic urgency signal and leaky integration, in combination with two independent forms of reward biases, best capture behavior. We also tested how temporal structure influences urgency by systematically manipulating the temporal structure of sensory evidence, and found that the time course of urgency was affected by temporal context. Overall, our approach identified key components of cognitive mechanisms for incorporating temporal and reward structure into decisions.SIGNIFICANCE STATEMENT In everyday life, decisions are influenced by many factors, including reward structures and stimulus timing. While reward and timing have been characterized in isolation, ecologically valid decision-making involves a multiplicity of factors acting simultaneously. This raises questions about whether the same decision-making strategy is used when these two factors are concurrently manipulated. To address these questions, we trained rhesus monkeys to perform a novel decision-making task with both reward asymmetry and temporal uncertainty. In order to understand their strategy and hint at its neural mechanisms, we used the new generalized drift diffusion modeling framework to model both reward and timing mechanisms. We found two of each reward and timing mechanisms are necessary to explain our data.

Humans sacrifice decision-making for action execution when a demanding control of movement is required

A growing body of evidence suggests that decision-making and action execution are governed by partly overlapping operating principles. Especially, previous work proposed that a shared decision urgency/movement vigor signal, possibly computed in the basal ganglia, coordinates both deliberation and movement durations in a way that maximizes the reward rate. Recent data support one aspect of this hypothesis, indicating that the urgency level at which a decision is made influences the vigor of the movement produced to express this choice. Here we investigated whether, conversely, the motor context in which a movement is executed determines decision speed and accuracy. Twenty human subjects performed a probabilistic decision task in which perceptual choices were expressed by reaching movements toward targets whose size and distance from a starting position varied in distinct blocks of trials. We found strong evidence for an influence of the motor context on most of the subjects' decision policy, but contrary to the predictions of the "shared regulation" hypothesis, we observed that slow movements executed in the most demanding motor blocks in terms of accuracy were often preceded by faster and less accurate decisions compared with blocks of trials in which big targets allowed expression of choices with fast and inaccurate movements. These results suggest that decision-making and motor control are not regulated by one unique "invigoration" signal determining both decision urgency and action vigor, but more likely by independent, yet interacting, decision urgency and movement vigor signals.NEW & NOTEWORTHY Recent hypotheses propose that choices and movements share optimization principles derived from economy, possibly implemented by one unique context-dependent regulation signal determining both processes' speed. In the present behavioral study conducted on human subjects, we demonstrate that action properties indeed influence perceptual decision-making, but that decision duration and action vigor are actually independently set depending on the difficulty of the movement executed to report a choice.

A neural network model of basal ganglia's decision-making circuitry

The basal ganglia have been increasingly recognized as an important structure involved in decision making. Neurons in the basal ganglia were found to reflect the evidence accumulation process during decision making. However, it is not well understood how the direct and indirect pathways of the basal ganglia work together for decision making. Here, we create a recurrent neural network model that is composed of the direct and indirect pathways and test it with the classic random dot motion discrimination task. The direct pathway drives the outputs, which are modulated through a gating mechanism controlled by the indirect pathway. We train the network to learn the task and find that the network reproduces the accuracy and reaction time patterns of previous animal studies. Units in the model exhibit ramping activities that reflect evidence accumulation. Finally, we simulate manipulations of the direct and indirect pathways and find that the manipulations of the direct pathway mainly affect the choice while the manipulations of the indirect pathway affect the model's reaction time. These results suggest a potential circuitry mechanism of the basal ganglia's role in decision making with predictions that can be tested experimentally in the future.

Globus pallidus dynamics reveal covert strategies for behavioral inhibition

Flexible behavior requires restraint of actions that are no longer appropriate. This behavioral inhibition critically relies on frontal cortex - basal ganglia circuits. Within the basal ganglia, the globus pallidus pars externa (GPe) has been hypothesized to mediate selective proactive inhibition: being prepared to stop a specific action, if needed. Here we investigate population dynamics of rat GPe neurons during preparation-to-stop, stopping, and going. Rats selectively engaged proactive inhibition towards specific actions, as shown by slowed reaction times (RTs). Under proactive inhibition, GPe population activity occupied state-space locations farther from the trajectory followed during normal movement initiation. Furthermore, the state-space locations were predictive of distinct types of errors: failures-to-stop, failures-to-go, and incorrect choices. Slowed RTs on correct proactive trials reflected starting bias towards the alternative action, which was overcome before progressing towards action initiation. Our results demonstrate that rats can exert cognitive control via strategic adjustments to their GPe network state.

Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions

Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

Contribution of the Entopeduncular Nucleus and the Globus Pallidus to the Control of Locomotion and Visually Guided Gait Modifications in the Cat

We tested the hypothesis that the entopeduncular (EP) nucleus (feline equivalent of the primate GPi) and the globus pallidus (GPe) contribute to both the planning and execution of locomotion and voluntary gait modifications in the cat. We recorded from 414 cells distributed throughout these two nuclei (referred to together as the pallidum) while cats walked on a treadmill and stepped over an obstacle that advanced towards them. Neuronal activity in many cells in both structures was modulated on a step-by-step basis during unobstructed locomotion and was modified in the step over the obstacle. On a population basis, the most frequently observed change, in both the EP and the GPe, was an increase in activity prior to and/or during the swing phase of the step over the obstacle by the contralateral forelimb, when it was the first limb to pass over the obstacle. Our results support a contribution of the pallidum, in concert with cortical structures, to the control of both the planning and the execution of the gait modifications. We discuss the results in the context of current models of pallidal action on thalamic activity, including the possibility that cells in the EP with increased activity may sculpt thalamo-cortical activity.

Microstimulation of dorsal premotor and primary motor cortex delays the volitional commitment to an action choice

Humans and other animals are faced with decisions about actions on a daily basis. These typically include a period of deliberation that ends with the commitment to a choice, which then leads to the overt expression of that choice through action. Previous studies with monkeys have demonstrated that neural activity in sensorimotor areas correlates with the deliberation process and reflects the moment of commitment before movement initiation, but the causal roles of these regions are challenging to establish. Here, we tested whether dorsal premotor (PMd) and primary motor cortex (M1) are causally involved in the volitional commitment to a reaching choice. We found that brief subthreshold microstimulation in PMd or M1 delayed commitment to an action but not the initiation of the action itself. Importantly, microstimulation only had a significant effect when it was delivered close to and before commitment time. These results are consistent with the proposal that PMd and M1 participate in the commitment process, which occurs when a critical firing rate difference is reached between cells voting for the selected option and those voting for the competing one.NEW & NOTEWORTHY The neural substrates of decisions between actions are typically investigated by correlating neural activity and subjects' decision behavior, but this does not establish causality. In a reaching decision task, we demonstrate that subthreshold microstimulation of the monkey dorsal premotor cortex or primary motor cortex delays the deliberation duration if applied shortly before choice commitment. This result suggests a causal role of the sensorimotor cortex in the determination of decisions between actions.

Chemogenetic inhibition in the dorsal striatum reveals regional specificity of direct and indirect pathway control of action sequencing

Animals engage in intricate action sequences that are constructed during instrumental learning. There is broad consensus that the basal ganglia play a crucial role in the formation and fluid performance of action sequences. To investigate the role of the basal ganglia direct and indirect pathways in action sequencing, we virally expressed Cre-dependent Gi-DREADDs in either the dorsomedial (DMS) or dorsolateral (DLS) striatum during and/or after action sequence learning in D1 and D2 Cre rats. Action sequence performance in D1 Cre rats was slowed down early in training when DREADDs were activated in the DMS, but sped up when activated in the DLS. Acquisition of the reinforced sequence was hindered when DREADDs were activated in the DLS of D2 Cre rats. Outcome devaluation tests conducted after training revealed that the goal-directed control of action sequence rates was immune to chemogenetic inhibition-rats suppressed the rate of sequence performance when rewards were devalued. Sequence initiation latencies were generally sensitive to outcome devaluation, except in the case where DREADD activation was removed in D2 Cre rats that previously experienced DREADD activation in the DMS during training. Sequence completion latencies were generally not sensitive to outcome devaluation, except in the case where D1 Cre rats experienced DREADD activation in the DMS during training and test. Collectively, these results suggest that the indirect pathway originating from the DLS is part of a circuit involved in the effective reinforcement of action sequences, while the direct and indirect pathways originating from the DMS contribute to the goal-directed control of sequence completion and initiation, respectively.

Accumulators, Neurons, and Response Time

The marriage of cognitive neurophysiology and mathematical psychology to understand decision-making has been exceptionally productive. This interdisciplinary area is based on the proposition that particular neurons or circuits instantiate the accumulation of evidence specified by mathematical models of sequential sampling and stochastic accumulation. This linking proposition has earned widespread endorsement. Here, a brief survey of the history of the proposition precedes a review of multiple conundrums and paradoxes concerning the accuracy, precision, and transparency of that linking proposition. Correctly establishing how abstract models of decision-making are instantiated by particular neural circuits would represent a remarkable accomplishment in mapping mind to brain. Failing would reveal challenging limits for cognitive neuroscience. This is such a vigorous area of research because so much is at stake.

Mouse movement measures enhance the stop-signal task in adult ADHD assessment

The accurate detection of attention-deficit/hyperactivity disorder (ADHD) symptoms, such as inattentiveness and behavioral disinhibition, is crucial for delivering timely assistance and treatment. ADHD is commonly diagnosed and studied with specialized questionnaires and behavioral tests such as the stop-signal task. However, in cases of late-onset or mild forms of ADHD, behavioral measures often fail to gauge the deficiencies well-highlighted by questionnaires. To improve the sensitivity of behavioral tests, we propose a novel version of the stop-signal task (SST), which integrates mouse cursor tracking. In two studies, we investigated whether introducing mouse movement measures to the stop-signal task improves associations with questionnaire-based measures, as compared to the traditional (keypress-based) version of SST. We also scrutinized the influence of different parameters of stop-signal tasks, such as the method of stop-signal delay setting or definition of response inhibition failure, on these associations. Our results show that a) SSRT has weak association with impulsivity, while mouse movement measures have strong and significant association with impulsivity; b) machine learning models trained on the mouse movement data from "known" participants using nested cross-validation procedure can accurately predict impulsivity ratings of "unknown" participants; c) mouse movement features such as maximum acceleration and maximum velocity are among the most important predictors for impulsivity; d) using preset stop-signal delays prompts behavior that is more indicative of impulsivity.

Resynthesizing behavior through phylogenetic refinement

This article proposes that biologically plausible theories of behavior can be constructed by following a method of "phylogenetic refinement," whereby they are progressively elaborated from simple to complex according to phylogenetic data on the sequence of changes that occurred over the course of evolution. It is argued that sufficient data exist to make this approach possible, and that the result can more effectively delineate the true biological categories of neurophysiological mechanisms than do approaches based on definitions of putative functions inherited from psychological traditions. As an example, the approach is used to sketch a theoretical framework of how basic feedback control of interaction with the world was elaborated during vertebrate evolution, to give rise to the functional architecture of the mammalian brain. The results provide a conceptual taxonomy of mechanisms that naturally map to neurophysiological and neuroanatomical data and that offer a context for defining putative functions that, it is argued, are better grounded in biology than are some of the traditional concepts of cognitive science.

Optimal models of decision-making in dynamic environments

Nature is in constant flux, so animals must account for changes in their environment when making decisions. How animals learn the timescale of such changes and adapt their decision strategies accordingly is not well understood. Recent psychophysical experiments have shown humans and other animals can achieve near-optimal performance at two alternative forced choice (2AFC) tasks in dynamically changing environments. Characterization of performance requires the derivation and analysis of computational models of optimal decision-making policies on such tasks. We review recent theoretical work in this area, and discuss how models compare with subjects' behavior in tasks where the correct choice or evidence quality changes in dynamic, but predictable, ways.

Motor cortex disruption delays motor processes but not deliberation about action choices

Decisions about actions typically involve a period of deliberation that ends with the commitment to a choice and the motor processes overtly expressing that choice. Previous studies have shown that neural activity in sensorimotor areas, including the primary motor cortex (M1), correlates with deliberation features during action selection. However, the causal contribution of these areas to the decision process remains unclear. Here, we investigated whether M1 determines choice commitment or whether it simply reflects decision signals coming from upstream structures and instead mainly contributes to the motor processes that follow commitment. To do so, we tested the impact of a disruption of M1 activity, induced by continuous theta burst stimulation (cTBS), on the behavior of human subjects in 1) a simple reaction time (SRT) task allowing us to estimate the duration of the motor processes and 2) a modified version of the tokens task (Cisek P, Puskas GA, El-Murr S. J Neurosci 29: 11560-11571, 2009), which allowed us to estimate subjects' time of commitment as well as accuracy criterion. The efficiency of cTBS was attested by a reduction in motor evoked potential amplitudes following M1 disruption compared with those following a sham stimulation. Furthermore, M1 cTBS lengthened SRTs, indicating that motor processes were perturbed by the intervention. Importantly, all of the behavioral results in the tokens task were similar following M1 disruption and sham stimulation, suggesting that the contribution of M1 to the deliberation process is potentially negligible. Taken together, these findings favor the view that M1 contribution is downstream of the decision process.NEW & NOTEWORTHY Decisions between actions are ubiquitous in the animal realm. Deliberation during action choices entails changes in the activity of the sensorimotor areas controlling those actions, but the causal role of these areas is still often debated. With the use of continuous theta burst stimulation, we show that disrupting the primary motor cortex (M1) delays the motor processes that follow instructed commitment but does not alter volitional deliberation, suggesting that M1 contribution may be downstream of the decision process.

Early Trajectory Prediction in Elite Athletes

Cerebellar plasticity is a critical mechanism for optimal feedback control. While Purkinje cell activity of the oculomotor vermis predicts eye movement speed and direction, more lateral areas of the cerebellum may play a role in more complex tasks, including decision-making. It is still under question how this motor-cognitive functional dichotomy between medial and lateral areas of the cerebellum plays a role in optimal feedback control. Here we show that elite athletes subjected to a trajectory prediction, go/no-go task manifest superior subsecond trajectory prediction accompanied by optimal eye movements and changes in cognitive load dynamics. Moreover, while interacting with the cerebral cortex, both the medial and lateral cerebellar networks are prominently activated during the fast feedback stage of the task, regardless of whether or not a motor response was required for the correct response. Our results show that cortico-cerebellar interactions are widespread during dynamic feedback and that experience can result in superior task-specific decision skills.

The Urge to Decide and Act: Implications for Brain Function and Dysfunction

Humans and other animals are motivated to act so as to maximize their subjective reward rate. Here, we propose that reward rate maximization is accomplished by adjusting a context-dependent “urgency signal,” which influences both the commitment to a developing action choice and the vigor with which the ensuing action is performed. We review behavioral and neurophysiological data suggesting that urgency is controlled by projections from the basal ganglia to cerebral cortical regions, influencing neural activity related to decision making as well as activity related to action execution. We also review evidence suggesting that different individuals possess specific policies for adjusting their urgency signal to particular contextual variables, such that urgency constitutes an individual trait which jointly influences a wide range of behavioral measures commonly related to the overall quality and hastiness of one’s decisions and actions. Consequently, we argue that a central mechanism for reward rate maximization provides a potential link between personality traits such as impulsivity, as well as some of the motivation-related symptomology of clinical disorders such as depression and Parkinson’s disease.

What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation

Deciding what to do and when to move is vital to our survival. Clinical and fundamental studies have identified basal ganglia circuits as critical for this process. The main input nucleus of the basal ganglia, the striatum, receives inputs from frontal, sensory, and motor cortices and interconnected thalamic areas that provide information about potential goals, context, and actions and directly or indirectly modulates basal ganglia outputs. The striatum also receives dopaminergic inputs that can signal reward prediction errors and also behavioral transitions and movement initiation. Here we review studies and models of how direct and indirect pathways can modulate basal ganglia outputs to facilitate movement initiation, and we discuss the role of cortical and dopaminergic inputs to the striatum in determining what to do and if and when to do it. Complex but exciting scenarios emerge that shed new light on how basal ganglia circuits modulate self-paced movement initiation.

Movement Vigor as a Reflection of Subjective Economic Utility

To understand subjective evaluation of an option, various disciplines have quantified the interaction between reward and effort during decision making, producing an estimate of economic utility, namely the subjective 'goodness' of an option. However, variables that affect utility of an option also influence the vigor of movements toward that option. For example, expectation of reward increases speed of saccadic eye movements, whereas expectation of effort decreases this speed. These results imply that vigor may serve as a new, real-time metric with which to quantify subjective utility, and that the control of movements may be an implicit reflection of the brain's economic evaluation of the expected outcome.

Sensorimotor subthalamic stimulation restores risk-reward trade-off in Parkinson's disease

BACKGROUND

STN-DBS effectively treats motor symptoms of advanced PD. Nonmotor cognitive symptoms, such as impaired impulse control or decision making, may either improve or worsen with DBS. A potential mediating factor of DBS-induced modulation of cognition is the electrode position within the STN with regard to functional subareas of parallel motor, cognitive, and affective basal ganglia loops. However, to date, the volume of tissue activated and weighted stimulation of STN motor versus nonmotor territories are yet to be linked to differential DBS effects on cognition.

OBJECTIVES

We aim to investigate whether STN-DBS influences risk-reward trade-off decisions and analyze its dependency on electrode placement.

METHODS

Seventeen PD patients ON and OFF STN-DBS and 17 age-matched healthy controls conducted a sequential decision-making task with escalating risk and reward. We computed the effect of STN-DBS on risk-reward trade-off decisions, localized patients' bilateral electrodes, and analyzed the predictive value of volume of tissue activated in STN motor and nonmotor territories on behavioral change.

RESULTS

We found that STN-DBS not only improves PD motor symptoms, but also normalizes overly risk-averse decision behavior in PD. Intersubject variance in electrode location could explain this behavioral change. Specifically, if STN-DBS activated preferentially STN motor territory, patients' risk-reward trade-off decisions more resembled those of healthy controls.

CONCLUSIONS

Our findings support the notion of convergence of different functional circuits within the STN and imply a positive effect of well-placed STN-DBS on nonmotor cognitive functioning in PD. © 2018 International Parkinson and Movement Disorder Society.

Bridging Neural and Computational Viewpoints on Perceptual Decision-Making

Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.

Self-reference in action: Arm-movement responses are enhanced in perceptual matching

Considerable evidence now shows that making a reference to the self in a task modulates attention, perception, memory, and decision-making. Furthermore, the self-reference effect (SRE) cannot be reduced to domain-general factors (e.g., reward value) and is supported by distinct neural circuitry. However, it remains unknown whether self-associations modulate response execution as well. This was tested in the present study. Participants carried out a perceptual-matching task, and movement time (MT) was measured separately from reaction-time (RT; drawing on methodology from the literature on intelligence). A response box recorded 'home'-button-releases (measuring RT from stimulus onset); and a target-key positioned 14 cm from the response box recorded MT (from 'home'-button-release to target-key depression). MTs of responses to self- as compared with other-person-associated stimuli were faster (with a higher proportion correct for self-related responses). We present a novel demonstration that the SRE can modulate the execution of rapid-aiming arm-movement responses. Implications of the findings are discussed, along with suggestions to guide and inspire future work in investigating how the SRE influences action.

Visual salience of the stop signal affects the neuronal dynamics of controlled inhibition

The voluntary control of movement is often tested by using the countermanding, or stop-signal task that sporadically requires the suppression of a movement in response to an incoming stop-signal. Neurophysiological recordings in monkeys engaged in the countermanding task have shown that dorsal premotor cortex (PMd) is implicated in movement control. An open question is whether and how the perceptual demands inherent the stop-signal affects inhibitory performance and their underlying neuronal correlates. To this aim we recorded multi-unit activity (MUA) from the PMd of two male monkeys performing a countermanding task in which the salience of the stop-signals was modulated. Consistently to what has been observed in humans, we found that less salient stimuli worsened the inhibitory performance. At the neuronal level, these behavioral results were subtended by the following modulations: when the stop-signal was not noticeable compared to the salient condition the preparatory neuronal activity in PMd started to be affected later and with a less sharp dynamic. This neuronal pattern is probably the consequence of a less efficient inhibitory command useful to interrupt the neural dynamic that supports movement generation in PMd.

Visuomotor Correlates of Conflict Expectation in the Context of Motor Decisions

Many behaviors require choosing between conflicting options competing against each other in visuomotor areas. Such choices can benefit from top-down control processes engaging frontal areas in advance of conflict when it is anticipated. Yet, very little is known about how this proactive control system shapes the visuomotor competition. Here, we used electroencephalography in human subjects (male and female) to identify the visual and motor correlates of conflict expectation in a version of the Eriksen Flanker task that required left or right responses according to the direction of a central target arrow surrounded by congruent or incongruent (conflicting) flankers. Visual conflict was either highly expected (it occurred in 80% of trials; mostly incongruent blocks) or very unlikely (20% of trials; mostly congruent blocks). We evaluated selective attention in the visual cortex by recording target- and flanker-related steady-state visual-evoked potentials (SSVEPs) and probed action selection by measuring response-locked potentials (RLPs) in the motor cortex. Conflict expectation enhanced accuracy in incongruent trials, but this improvement occurred at the cost of speed in congruent trials. Intriguingly, this behavioral adjustment occurred while visuomotor activity was less finely tuned: target-related SSVEPs were smaller while flanker-related SSVEPs were higher in mostly incongruent blocks than in mostly congruent blocks, and incongruent trials were associated with larger RLPs in the ipsilateral (nonselected) motor cortex. Hence, our data suggest that conflict expectation recruits control processes that augment the tolerance for inappropriate visuomotor activations (rather than processes that downregulate their amplitude), allowing for overflow activity to occur without having it turn into the selection of an incorrect response.SIGNIFICANCE STATEMENT Motor choices made in front of discordant visual information are more accurate when conflict can be anticipated, probably due to the engagement of top-down control from frontal areas. How this control system modulates activity within visual and motor areas is unknown. Here, we show that, when control processes are recruited in anticipation of conflict, as evidenced by higher midfrontal theta activity, visuomotor activity is less finely tuned: visual processing of the goal-relevant location was reduced and the motor cortex displayed more inappropriate activations, compared with when conflict was unlikely. We argue that conflict expectation is associated with an expansion of the distance-to-selection threshold, improving accuracy while the need for online control of visuomotor activity is reduced.

Paradoxical Decision-Making: A Framework for Understanding Cognition in Parkinson's Disease

People with Parkinson's disease (PD) show impaired decision-making when sensory and memory information must be combined. This recently identified impairment results from an inability to accumulate the proper amount of information needed to make a decision and appears to be independent of dopamine tone and reinforcement learning mechanisms. Although considerable work focuses on PD and decisions involving risk and reward, in this Opinion article we propose that the emerging findings in perceptual decision-making highlight the multisystem nature of PD, and that unraveling the neuronal circuits underlying perceptual decision-making impairment may help in understanding other cognitive impairments in people with PD. We also discuss how a decision-making framework may be extended to gain insights into mechanisms of motor impairments in PD.

Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions

Evolutionary pressures suggest that choices should be optimized to maximize rewards, by appropriately trading speed for accuracy. This speed-accuracy tradeoff (SAT) is commonly explained by variation in just the baseline-to-boundary distance, i.e., the excursion, of accumulation-to-bound models of perceptual decision-making. However, neural evidence is not consistent with this explanation. A compelling account of speeded choice should explain both overt behavior and the full range of associated brain signatures. Here, we reconcile seemingly contradictory behavioral and neural findings. In two variants of the same experiment, we triangulated upon the neural underpinnings of the SAT in the human brain using both EEG and transcranial magnetic stimulation (TMS). We found that distinct neural signals, namely the event-related potential (ERP) centroparietal positivity (CPP) and a smoothed motor-evoked potential (MEP) signal, which have both previously been shown to relate to decision-related accumulation, revealed qualitatively similar average neurodynamic profiles with only subtle differences between SAT conditions. These signals were then modelled from behavior by either incorporating traditional boundary variation or utilizing a forced excursion. These model variants are mathematically equivalent, in terms of their behavioral predictions, hence providing identical fits to correct and erroneous reaction time distributions. However, the forced-excursion version instantiates SAT via a more global change in parameters and implied neural activity, a process conceptually akin to, but mathematically distinct from, urgency. This variant better captured both ERP and MEP neural profiles, suggesting that the SAT may be implemented via neural gain modulation, and reconciling standard modelling approaches with human neural data.