Proactive inhibitory control and attractor dynamics in countermanding action: a spiking neural circuit model

The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity

Cross-individual variability is considered the essence of biology, preventing precise mathematical descriptions of biological motion1-7 like the physics law of motion. Here we report that the cerebellum shapes motor kinematics by encoding dynamic motor frequencies with remarkable numerical precision and cross-individual uniformity. Using in-vivo electrophysiology and optogenetics in mice, we confirmed that deep cerebellar neurons encoded frequencies via populational tuning of neuronal firing probabilities, creating cerebellar oscillations and motions with matched frequencies. The mechanism was consistently presented in self-generated rhythmic and non-rhythmic motions triggered by a vibrational platform, or skilled tongue movements of licking in all tested mice with cross-individual uniformity. The precision and uniformity allowed us to engineer complex motor kinematics with designed frequencies. We further validated the frequency-coding function of the human cerebellum using cerebellar electroencephalography recordings and alternating-current stimulation during voluntary tapping tasks. Our findings reveal a cerebellar algorithm for motor kinematics with precision and uniformity, the mathematical foundation for brain-computer interface for motor control.

Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network

Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.

Transcranial focused ultrasound to human rIFG improves response inhibition through modulation of the P300 onset latency

Response inhibition in humans is important to avoid undesirable behavioral action consequences. Neuroimaging and lesion studies point to a locus of inhibitory control in the right inferior frontal gyrus (rIFG). Electrophysiology studies have implicated a downstream event-related potential from rIFG, the fronto-central P300, as a putative neural marker of the success and timing of inhibition over behavioral responses. However, it remains to be established whether rIFG effectively drives inhibition and which aspect of P300 activity uniquely indexes inhibitory control-ERP timing or amplitude. Here, we dissect the connection between rIFG and P300 for inhibition by using transcranial-focused ultrasound (tFUS) to target rIFG of human subjects while they performed a Stop-Signal task. By applying tFUS simultaneously with different task events, we found behavioral inhibition was improved, but only when applied to rIFG simultaneously with a 'stop' signal. Improved inhibition through tFUS to rIFG was indexed by faster stopping times that aligned with significantly shorter N200/P300 onset latencies. In contrast, P300 amplitude was modulated during tFUS across all groups without a paired change in behavior. Using tFUS, we provide evidence for a causal connection between anatomy, behavior, and electrophysiology underlying response inhibition.

Functional architecture of executive control and associated event-related potentials in macaques

The medial frontal cortex (MFC) enables executive control by monitoring relevant information and using it to adapt behavior. In macaques performing a saccade countermanding (stop-signal) task, we simultaneously recorded electrical potentials over MFC and neural spiking across all layers of the supplementary eye field (SEF). We report the laminar organization of neurons enabling executive control by monitoring the conflict between incompatible responses, the timing of events, and sustaining goal maintenance. These neurons were a mix of narrow-spiking and broad-spiking found in all layers, but those predicting the duration of control and sustaining the task goal until the release of operant control were more commonly narrow-spiking neurons confined to layers 2 and 3 (L2/3). We complement these results with evidence for a monkey homolog of the N2/P3 event-related potential (ERP) complex associated with response inhibition. N2 polarization varied with error-likelihood and P3 polarization varied with the duration of expected control. The amplitude of the N2 and P3 were predicted by the spike rate of different classes of neurons located in L2/3 but not L5/6. These findings reveal features of the cortical microcircuitry supporting executive control and producing associated ERPs.

Neuronal population dynamics during motor plan cancellation in nonhuman primates

To understand the cortical neuronal dynamics behind movement generation and control, most studies have focused on tasks where actions were planned and then executed using different instances of visuomotor transformations. However, to fully understand the dynamics related to movement control, one must also study how movements are actively inhibited. Inhibition, indeed, represents the first level of control both when different alternatives are available and only one solution could be adopted and when it is necessary to maintain the current position. We recorded neuronal activity from a multielectrode array in the dorsal premotor cortex (PMd) of monkeys performing a countermanding reaching task that requires, in a subset of trials, them to cancel a planned movement before its onset. In the analysis of the neuronal state space of PMd, we found a subspace in which activities conveying temporal information were confined during active inhibition and position holding. Movement execution required activities to escape from this subspace toward an orthogonal subspace and, furthermore, surpass a threshold associated with the maturation of the motor plan. These results revealed further details in the neuronal dynamics underlying movement control, extending the hypothesis that neuronal computation confined in an "output-null" subspace does not produce movements.

The Human Basal Ganglia Mediate the Interplay between Reactive and Proactive Control of Response through Both Motor Inhibition and Sensory Modulation

The basal ganglia (BG) have long been known for contributing to the regulation of motor behaviour by means of a complex interplay between tonic and phasic inhibitory mechanisms. However, after having focused for a long time on phasic reactive mechanisms, it is only recently that psychological research in healthy humans has modelled tonic proactive mechanisms of control. Mutual calibration between anatomo-functional and psychological models is still needed to better understand the unclear role of the BG in the interplay between proactive and reactive mechanisms of control. Here, we implemented an event-related fMRI design allowing proper analysis of both the brain activity preceding the target-stimulus and the brain activity induced by the target-stimulus during a simple go/nogo task, with a particular interest in the ambiguous role of the basal ganglia. Post-stimulus activity was evoked in the left dorsal striatum, the subthalamus nucleus and internal globus pallidus by any stimulus when the situation was unpredictable, pinpointing its involvement in reactive, non-selective inhibitory mechanisms when action restraint is required. Pre-stimulus activity was detected in the ventral, not the dorsal, striatum, when the situation was unpredictable, and was associated with changes in functional connectivity with the early visual, not the motor, cortex. This suggests that the ventral striatum supports modulatory influence over sensory processing during proactive control.

The unknown but knowable relationship between Presaccadic Accumulation of activity and Saccade initiation

The goal of this short review is to call attention to a yawning gap of knowledge that separates two processes essential for saccade production. On the one hand, knowledge about the saccade generation circuitry within the brainstem is detailed and precise - push-pull interactions between gaze-shifting and gaze-holding processes control the time of saccade initiation, which begins when omnipause neurons are inhibited and brainstem burst neurons are excited. On the other hand, knowledge about the cortical and subcortical premotor circuitry accomplishing saccade initiation has crystalized around the concept of stochastic accumulation - the accumulating activity of saccade neurons reaching a fixed value triggers a saccade. Here is the gap: we do not know how the reaching of a threshold by premotor neurons causes the critical pause and burst of brainstem neurons that initiates saccades. Why this problem matters and how it can be addressed will be discussed. Closing the gap would unify two rich but curiously disconnected empirical and theoretical domains.

Reduced Proactive Control Processes Associated With Behavioral Response Inhibition Deficits in Autism Spectrum Disorder

Impairments in inhibitory control are common in individuals with autism spectrum disorder (ASD) and associated with multiple clinical issues. Proactive (i.e., delaying response onset) and reactive control mechanisms (i.e., stopping quickly) contribute to successful inhibitory control in typically developing individuals and may be compromised in ASD. We assessed inhibitory control in 58 individuals with ASD and 63 typically developing controls aged 5-29 years using an oculomotor stop-signal task during which participants made rapid eye movements (i.e., saccades) toward peripheral targets (i.e., GO trials) or inhibited saccades (i.e., STOP trials). Individuals with ASD exhibited reduced ability to inhibit saccades, reduced reaction time slowing (GO RT slowing), and faster stop-signal reaction times (SSRT) compared to controls. Across participants, stopping accuracy was positively related to GO RT slowing, and increased age was associated with higher stopping accuracy and GO RT slowing. Our results indicate that failures to proactively delay prepotent responses in ASD underpin deficits of inhibitory control and may contribute to difficulties modifying their behavior according to changes in contextual demands. These findings implicate frontostriatal brain networks in inhibitory control and core symptoms of ASD. LAY SUMMARY: Difficulties stopping actions are common in individuals with autism spectrum disorder (ASD) and are related to repetitive behaviors. This study compared the ability to stop eye movements in individuals with ASD and healthy peers. We found that individuals with ASD were less able to stop eye movements and that this difficulty was related to a reduced ability to delay their eye movements before seeing the cue to stop, not their ability to react quickly to this cue.

Efficacy of inhibitory control depends on procrastination and deceleration in saccade planning

A goal-directed flexible behavior warrants our ability to timely inhibit impending movements deemed inappropriate due to an abrupt change in the context. Race model of countermanding rapid saccadic eye movement posits a competition between a preparatory GO process and an inhibitory STOP process rising to reach a fixed threshold. Stop-signal response time (SSRT), which is the average time STOP takes to rise to the threshold, is widely used as a metric to assess the ability to revoke a movement. A reliable estimation of SSRT critically depends on the assumption of independence between GO and STOP process, which has been violated in many studies. In addition, the physiological correlate of stochastic rise of STOP process to a threshold remains unsubstantiated thus far. Here, we introduce a method to estimate the efficacy of inhibitory control on the premise of an alternative model that assumes deceleration of GO process following the stop-signal onset. The average reaction time increased exponentially with the increase in the maximum duration available to attenuate GO process by the stop-signal. Our method estimates saccade procrastination in anticipation of the stop-signal, and the rate of increase in attenuation on GO process. Unlike SSRT, these new metrics are independent of how the stopping performance varies with the delay between go- and stop-signal onsets. We reckon that these metrics together qualify to be considered as an efficient alternative to SSRT for the estimation of individuals' ability to countermand saccades, especially in cases when the assumptions of race model are no longer valid.

Cognitive control and automatic interference in mind and brain: A unified model of saccadic inhibition and countermanding

Countermanding behavior has long been seen as a cornerstone of executive control-the human ability to selectively inhibit undesirable responses and change plans. However, scattered evidence implies that stopping behavior is entangled with simpler automatic stimulus-response mechanisms. Here we operationalize this idea by merging the latest conceptualization of saccadic countermanding with a neural network model of visuo-oculomotor behavior that integrates bottom-up and top-down drives. This model accounts for all fundamental qualitative and quantitative features of saccadic countermanding, including neuronal activity. Importantly, it does so by using the same architecture and parameters as basic visually guided behavior and automatic stimulus-driven interference. Using simulations and new data, we compare the temporal dynamics of saccade countermanding with that of saccadic inhibition (SI), a hallmark effect thought to reflect automatic competition within saccade planning areas. We demonstrate how SI accounts for a large proportion of the saccade countermanding process when using visual signals. We conclude that top-down inhibition acts later, piggy-backing on the quicker automatic inhibition. This conceptualization fully accounts for the known effects of signal features and response modalities traditionally used across the countermanding literature. Moreover, it casts different light on the concept of top-down inhibition, its timing and neural underpinning, as well as the interpretation of stop-signal reaction time (RT), the main behavioral measure in the countermanding literature. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Shaping the Cortical Landscape: Functions and Mechanisms of Top-Down Cortical Feedback Pathways

Cortical feedback pathways are proposed to guide cognition and behavior according to context and goal-direction. At the cellular level, cortical feedback pathways target multiple excitatory and inhibitory populations. However, we currently lack frameworks that link how the cellular mechanisms of cortical feedback pathways underlie their cognitive/behavioral functions. To establish this link, we expand on the framework of signal routing, the ability of cortical feedback pathways to proactively modulate how feedforward signals are propagated throughout the cortex. We propose that cortical feedback modulates routing through multiple mechanisms: preparing intended motor representations, setting the trigger conditions for evoking cortical outputs, altering coupling strengths between cortical regions, and suppressing expected sensory representations. In developing this framework, we first define the anatomy of cortical feedback pathways and identify recent advances in studying their functions at high specificity and resolution. Second, we review the diverse functions of cortical feedback pathways throughout the cortical hierarchy and evaluate these functions from the framework of signal routing. Third, we review the conserved cellular targets and circuit impacts of cortical feedback. Fourth, we introduce the concept of the “cortical landscape,” a graphical depiction of the routes through cortex that are favored at a specific moment in time. We propose that the cortical landscape, analogous to energy landscapes in physics and chemistry, can capture important features of signal routing including coupling strength, trigger conditions, and preparatory states. By resolving the cortical landscape, we may be able to quantify how the cellular processes of cortical feedback ultimately shape cognition and behavior.

Action processing in the motor system: Transcranial Magnetic Stimulation (TMS) evidence of shared mechanisms in the visual and linguistic modalities

In two experiments, we compared the dynamics of corticospinal excitability when processing visually or linguistically presented tool-oriented hand actions in native speakers and sequential bilinguals. In a third experiment we used the same procedure to test non-motor, low-level stimuli, i.e. scrambled images and pseudo-words. Stimuli were presented in sequence: pictures (tool + tool-oriented hand action or their scrambled counterpart) and words (tool noun + tool-action verb or pseudo-words). Experiment 1 presented German linguistic stimuli to native speakers, while Experiment 2 presented English stimuli to non-natives. Experiment 3 tested Italian native speakers. Single-pulse trascranial magnetic stimulation (spTMS) was applied to the left motor cortex at five different timings: baseline, 200 ms after tool/noun onset, 150, 350 and 500 ms after hand/verb onset with motor-evoked potentials (MEPs) recorded from the first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles. We report strong similarities in the dynamics of corticospinal excitability across the visual and linguistic modalities. MEPs' suppression started as early as 150 ms and lasted for the duration of stimulus presentation (500 ms). Moreover, we show that this modulation is absent for stimuli with no motor content. Overall, our study supports the notion of a core, overarching system of action semantics shared by different modalities.

Countermanding Perceptual Decision-Making

We investigated whether a task requiring concurrent perceptual decision-making and response control can be performed concurrently, whether evidence accumulation and response control are accomplished by the same neurons, and whether perceptual decision-making and countermanding can be unified computationally. Based on neural recordings in a prefrontal area of macaque monkeys, we present behavioral, neural, and computational results demonstrating that perceptual decision-making of varying difficulty can be countermanded efficiently, that single prefrontal neurons instantiate both evidence accumulation and response control, and that an interactive race between stochastic GO evidence accumulators for each alternative and a distinct STOP accumulator fits countermanding choice behavior and replicates neural trajectories. Thus, perceptual decision-making and response control, previously regarded as distinct mechanisms, are actually aspects of a common neuro-computational mechanism supporting flexible behavior.

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.

Detectability of stop-signal determines magnitude of deceleration in saccade planning

An inhibitory control is exerted when the context in which a movement has been planned changes abruptly making the impending movement inappropriate. Neurons in the frontal eye field and superior colliculus steadily increase activity before a saccadic eye movement, but cease the rise below a threshold when an impending saccade is withheld in response to an unexpected stop-signal. This type of neural modulation has been majorly considered as an outcome of a race between preparatory and inhibitory processes ramping up to reach a decision criterion. An alternative model claims that the rate of saccade planning is diminished exclusively when the stop-signal is detected within a stipulated period. However, due to a dearth of empirical evidence in support of the latter model, it remains unclear how the detectability of the stop-signal influences saccade inhibition. In our study, human participants selected a visual target to look at by discriminating a go-cue. Infrequently they cancelled saccade and reported whether they saw the stop-signal. The go-cue and stop-signal both were embedded in a stream of irrelevant stimuli presented in rapid succession. Participants exhibited difficulty in detection of the stop-signal when presented almost immediately after the go-cue. We found a robust relationship between the detectability of the stop-signal and the odds of saccade inhibition. Saccade latency increased exponentially with the maximum time available for processing the stop-signal before gaze shifted. A model in which the stop-signal onset spontaneously decelerated progressive saccade planning with the magnitude proportional to its detectability accounted for the data.

Behavioural and computational varieties of response inhibition in eye movements

Response inhibition is the ability to override a planned or an already initiated response. It is the hallmark of executive control as its deficits favour impulsive behaviours, which may be detrimental to an individual's life. This article reviews behavioural and computational guises of response inhibition. It focuses only on inhibition of oculomotor responses. It first reviews behavioural paradigms of response inhibition in eye movement research, namely the countermanding and antisaccade paradigms, both proven to be useful tools for the study of response inhibition in cognitive neuroscience and psychopathology. Then, it briefly reviews the neural mechanisms of response inhibition in these two behavioural paradigms. Computational models that embody a hypothesis and/or a theory of mechanisms underlying performance in both behavioural paradigms as well as provide a critical analysis of strengths and weaknesses of these models are discussed. All models assume the race of decision processes. The decision process in each paradigm that wins the race depends on different mechanisms. It has been shown that response latency is a stochastic process and has been proven to be an important measure of the cognitive control processes involved in response stopping in healthy and patient groups. Then, the inhibitory deficits in different brain diseases are reviewed, including schizophrenia and obsessive-compulsive disorder. Finally, new directions are suggested to improve the performance of models of response inhibition by drawing inspiration from successes of models in other domains.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'.

Testing the physiological plausibility of conflicting psychological models of response inhibition: A forward inference fMRI study

The neural mechanisms underlying response inhibition and related disorders are unclear and controversial for several reasons. First, it is a major challenge to assess the psychological bases of behaviour, and ultimately brain-behaviour relationships, of a function which is precisely intended to suppress overt measurable behaviours. Second, response inhibition is difficult to disentangle from other parallel processes involved in more general aspects of cognitive control. Consequently, different psychological and anatomo-functional models coexist, which often appear in conflict with each other even though they are not necessarily mutually exclusive. The standard model of response inhibition in go/no-go tasks assumes that inhibitory processes are reactively and selectively triggered by the stimulus that participants must refrain from reacting to. Recent alternative models suggest that action restraint could instead rely on reactive but non-selective mechanisms (all automatic responses are automatically inhibited in uncertain contexts) or on proactive and non-selective mechanisms (a gating function by which reaction to any stimulus is prevented in anticipation of stimulation when the situation is unpredictable). Here, we assessed the physiological plausibility of these different models by testing their respective predictions regarding event-related BOLD modulations (forward inference using fMRI). We set up a single fMRI design which allowed for us to record simultaneously the different possible forms of inhibition while limiting confounds between response inhibition and parallel cognitive processes. We found BOLD dynamics consistent with non-selective models. These results provide new theoretical and methodological lines of inquiry for the study of basic functions involved in behavioural control and related disorders.

Fixation target representation in prefrontal cortex during the antisaccade task

Neurons that discharge strongly during the time period of fixation of a visual target and cease to discharge before saccade initiation have been described in the brain stem, superior colliculus, and cortical areas. In subcortical structures, fixation neurons play a reciprocal role with saccadic neurons during the generation of eye movements. Their role in the dorsolateral prefrontal cortex is less obvious, and it is not known if they are activated by fixation, inhibit saccade generation, or play a role in more complex functions such as the inhibition of inappropriate responses. We examined the properties of prefrontal fixation neurons in the context of an antisaccade task, which requires an eye movement directed away from a prepotent visual stimulus. We tested monkeys with variants of the task, allowing us to dissociate activity synchronized on the fixation offset, presentation of the visual stimulus, and saccadic onset. Fixation neuron activity latency was most strongly tied to the offset of the fixation point across task variants. It was not well predicted by the appearance of the visual stimulus, which is essential for planning of the correct eye movement and inhibiting inappropriate ones. Activity of fixation neurons was generally negatively correlated with that of saccade neurons; however, critical differences in timing make it unlikely that they provide precisely timed signals for the generation of eye movements. These results demonstrate the role of fixation neurons in the prefrontal cortex during tasks requiring timing of appropriate eye movement and inhibition of inappropriate actions.NEW & NOTEWORTHY Properties of neurons that discharge during eye fixation and go silent before saccade initiation have been described in subcortical structures involved in eye movement generation, but their role in the dorsolateral prefrontal cortex presents a puzzle. Our results demonstrate the role of fixation neurons in the prefrontal cortex during tasks requiring precise timing of appropriate eye movement and inhibition of inappropriate actions.

Models of inhibitory control

We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'.

Physiological Markers of Motor Inhibition during Human Behavior

Transcranial magnetic stimulation (TMS) studies in humans have shown that many behaviors engage processes that suppress excitability within the corticospinal tract. Inhibition of the motor output pathway has been extensively studied in the context of action stopping, where a planned movement needs to be abruptly aborted. Recent TMS work has also revealed markers of motor inhibition during the preparation of movement. Here, we review the evidence for motor inhibition during action stopping and action preparation, focusing on studies that have used TMS to monitor changes in the excitability of the corticospinal pathway. We discuss how these physiological results have motivated theoretical models of how the brain selects actions, regulates movement initiation and execution, and switches from one state to another.

Speeded saccadic and manual visuo-motor decisions: Distinct processes but same principles

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Core architecture of visuo-motor selection model generalises across effectors.

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Hand and eyes show very different response times, but similar decision times.

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Longer non-decision time for visuo-manual responses accounts for longer response times.

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Stronger faster transient visual inputs for saccades account for different selection dynamics.

Action decisions are considered an emergent property of competitive response activations. As such, decision mechanisms are embedded in, and therefore may differ between, different response modalities. Despite this, the saccadic eye movement system is often promoted as a model for all decisions, especially in the fields of electrophysiology and modelling. Other research traditions predominantly use manual button presses, which have different response distribution profiles and are initiated by different brain areas. Here we tested whether core concepts of action selection models (decision and non-decision times, integration of automatic and selective inputs to threshold, interference across response options, noise, etc.) generalise from saccadic to manual domains. Using two diagnostic phenomena, the remote distractor effect (RDE) and ‘saccadic inhibition', we find that manual responses are also sensitive to the interference of visual distractors but to a lesser extent than saccades and during a shorter time window. A biologically-inspired model (DINASAUR, based on non-linear input dynamics) can account for both saccadic and manual response distributions and accuracy by simply adjusting the balance and relative timings of transient and sustained inputs, and increasing the mean and variance of non-decisional delays for manual responses. This is consistent with known neurophysiological and anatomical differences between saccadic and manual networks. Thus core decision principles appear to generalise across effectors, consistent with previous work, but we also conclude that key quantitative differences underlie apparent qualitative differences in the literature, such as effects being robustly reported in one modality and unreliable in another.

Of monkeys and men: Impatience in perceptual decision-making

For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set decision standard throughout the decision process. Based on the theoretical argument of reward rate maximization, some authors have recently suggested that decision makers become increasingly impatient as time passes and therefore lower their decision standard. Indeed, a number of studies show that computational models with an impatience component provide a good fit to human and monkey decision behavior. However, many of these studies lack quantitative model comparisons and systematic manipulations of rewards. Moreover, the often-cited evidence from single-cell recordings is not unequivocal and complimentary data from human subjects is largely missing. We conclude that, despite some enthusiastic calls for the abandonment of the standard model, the idea of an impatience component has yet to be fully established; we suggest a number of recently developed tools that will help bring the debate to a conclusive settlement.

Inhibitory Control in the Cortico-Basal Ganglia-Thalamocortical Loop: Complex Regulation and Interplay with Memory and Decision Processes

We developed a circuit model of spiking neurons that includes multiple pathways in the basal ganglia (BG) and is endowed with feedback mechanisms at three levels: cortical microcircuit, corticothalamic loop, and cortico-BG-thalamocortical system. We focused on executive control in a stop signal task, which is known to depend on BG across species. The model reproduces a range of experimental observations and shows that the newly discovered feedback projection from external globus pallidus to striatum is crucial for inhibitory control. Moreover, stopping process is enhanced by the cortico-subcortical reverberatory dynamics underlying persistent activity, establishing interdependence between working memory and inhibitory control. Surprisingly, the stop signal reaction time (SSRT) can be adjusted by weights of certain connections but is insensitive to other connections in this complex circuit, suggesting novel circuit-based intervention for inhibitory control deficits associated with mental illness. Our model provides a unified framework for inhibitory control, decision making, and working memory.

Simulating Cortical Feedback Modulation as Changes in Excitation and Inhibition in a Cortical Circuit Model

Cortical feedback pathways are hypothesized to distribute context-dependent signals during flexible behavior. Recent experimental work has attempted to understand the mechanisms by which cortical feedback inputs modulate their target regions. Within the mouse whisker sensorimotor system, cortical feedback stimulation modulates spontaneous activity and sensory responsiveness, leading to enhanced sensory representations. However, the cellular mechanisms underlying these effects are currently unknown. In this study we use a simplified neural circuit model, which includes two recurrent excitatory populations and global inhibition, to simulate cortical modulation. First, we demonstrate how changes in the strengths of excitation and inhibition alter the input-output processing responses of our model. Second, we compare these responses with experimental findings from cortical feedback stimulation. Our analyses predict that enhanced inhibition underlies the changes in spontaneous and sensory evoked activity observed experimentally. More generally, these analyses provide a framework for relating cellular and synaptic properties to emergent circuit function and dynamic modulation.

Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a “Stop” process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.

We propose a novel neural circuit mechanism and construct a spiking neural network model for resolving conflict between an automatic response and a volitional one. In this mechanism the two types of responses compete against each other under the modulation of top-down control via multiple neural pathways. The model is able to reproduce a wide range of neuronal and behavioral features observed in various studies and provides insights into not just how subjects make correct responses and fast errors, but also why they make slow errors, a type of error often overlooked by previous modeling studies. The model suggests critical roles of tonic (non-racing) top-down inhibition and near-threshold decision-making in neural competition.

A neural model of the frontal eye fields with reward-based learning

Decision-making is a flexible process dependent on the accumulation of various kinds of information; however, the corresponding neural mechanisms are far from clear. We extended a layered model of the frontal eye field to a learning-based model, using computational simulations to explain the cognitive process of choice tasks. The core of this extended model has three aspects: direction-preferred populations that cluster together the neurons with the same orientation preference, rule modules that control different rule-dependent activities, and reward-based synaptic plasticity that modulates connections to flexibly change the decision according to task demands. After repeated attempts in a number of trials, the network successfully simulated three decision choice tasks: an anti-saccade task, a no-go task, and an associative task. We found that synaptic plasticity could modulate the competition of choices by suppressing erroneous choices while enhancing the correct (rewarding) choice. In addition, the trained model captured some properties exhibited in animal and human experiments, such as the latency of the reaction time distribution of anti-saccades, the stop signal mechanism for canceling a reflexive saccade, and the variation of latency to half-max selectivity. Furthermore, the trained model was capable of reproducing the re-learning procedures when switching tasks and reversing the cue-saccade association.

Proactive inhibitory control: A general biasing account

Flexible behavior requires a control system that can inhibit actions in response to changes in the environment. Recent studies suggest that people proactively adjust response parameters in anticipation of a stop signal. In three experiments, we tested the hypothesis that proactive inhibitory control involves adjusting both attentional and response settings, and we explored the relationship with other forms of proactive and anticipatory control. Subjects responded to the color of a stimulus. On some trials, an extra signal occurred. The response to this signal depended on the task context subjects were in: in the 'ignore' context, they ignored it; in the 'stop' context, they had to withhold their response; and in the 'double-response' context, they had to execute a secondary response. An analysis of event-related brain potentials for no-signal trials in the stop context revealed that proactive inhibitory control works by biasing the settings of lower-level systems that are involved in stimulus detection, action selection, and action execution. Furthermore, subjects made similar adjustments in the double-response and stop-signal contexts, indicating an overlap between various forms of proactive action control. The results of Experiment 1 also suggest an overlap between proactive inhibitory control and preparatory control in task-switching studies: both require reconfiguration of task-set parameters to bias or alter subordinate processes. We conclude that much of the top-down control in response inhibition tasks takes place before the inhibition signal is presented.

Evidence for spatial tuning of movement inhibition

The time to initiate a movement can, even implicitly, be influenced by the environment. All primates, including humans, respond faster and with greater accuracy to stimuli that are brighter, louder or associated with larger reward, than to neutral stimuli. Whether this environment also modulates the executive functions which allow ongoing actions to be suppressed remains an issue of debate. In this study, we investigated the implicit learning of spatial selectivity of movement inhibition in humans and macaque monkeys performing a saccade-countermanding task. The occurrence of stop trials, in which subjects were visually instructed to cancel a prepared movement, was manipulated according to the target location. One visual target was associated with higher probability of stop signal appearance (e.g., 80 %), while the second target was associated with low fraction of stop (e.g., 20 %). The absolute occurrence of stop trials across the two targets (50 %) remains constant. The results show that human and macaque monkeys can selectively adapt their behaviors according to the implicit probability of stopping. Behavioral adjustments were larger when targets were in different hemifields and for larger distances between targets. Reduced selective inhibitory behaviors were observed when 15° of visual angle separated the targets, and this effect vanished when targets were separated by only 2°. Overall, our study shows that both response and inhibition times can be modulated by the relative spatial occurrence of stop signals. We speculate that beyond the particular effect we observed in the context of the saccade paradigm, selective motor execution may imply a disinhibitory mechanism that modulates the motor pathways associated with the fronto-median cortex and basal ganglia circuits.

Neural control of visual search by frontal eye field: chronometry of neural events and race model processes

We investigated the chronometry of neural processes in frontal eye fields of macaques performing double-step saccade visual search in which a conspicuous target changes location in the array on a random fraction of trials. Durations of computational processes producing a saccade to original and final target locations (GO1 and GO2, respectively) are derived from response times (RT) on different types of trials. In these data, GO2 tended to be faster than GO1, demonstrating that inhibition of the initial saccade did not delay production of the compensated saccade. Here, we measured the dynamics of visual, visuomovement, and movement neuron activity in relation to these processes by examining trials when neurons instantiated either process. First, we verified that saccades were initiated when the discharge rate of movement neurons reached a threshold that was invariant across RT and trial type. Second, the time when visual and visuomovement neurons selected the target and when movement neuron activity began to accumulate were not significantly different across trial type. Third, the interval from the beginning of accumulation to threshold of movement-related activity was significantly shorter when instantiating the GO2 relative to the GO1 process. Differences observed between monkeys are discussed. Fourth, random variation of RT was accounted for to some extent by random variation in both the onset and duration of selective activity of each neuron type but mostly by variation of movement neuron accumulation duration. These findings offer new insights into the sources of control of target selection and saccade production in dynamic environments.

Microsaccade production during saccade cancelation in a stop-signal task

We obtained behavioral data to evaluate two alternative hypotheses about the neural mechanisms of gaze control. The "fixation" hypothesis states that neurons in rostral superior colliculus (SC) enforce fixation of gaze. The "microsaccade" hypothesis states that neurons in rostral SC encode microsaccades rather than fixation per se. Previously reported neuronal activity in monkey SC during the saccade stop-signal task leads to specific, dissociable behavioral predictions of these two hypotheses. When subjects are required to cancel partially-prepared saccades, imbalanced activity spreads across rostral and caudal SC with a reliable temporal profile. The microsaccade hypothesis predicts that this imbalance will lead to elevated microsaccade production biased toward the target location, while the fixation hypothesis predicts reduced microsaccade production. We tested these predictions by analyzing the microsaccades produced by 4 monkeys while they voluntarily canceled partially prepared eye movements in response to explicit stop signals. Consistent with the fixation hypothesis and contradicting the microsaccade hypothesis, we found that each subject produced significantly fewer microsaccades when normal saccades were successfully canceled. The few microsaccades escaping this inhibition tended to be directed toward the target location. We additionally investigated interactions between initiating microsaccades and inhibiting normal saccades. Reaction times were longer when microsaccades immediately preceded target presentation. However, pre-target microsaccade production did not affect stop-signal reaction time or alter the probability of canceling saccades following stop signals. These findings demonstrate that imbalanced activity within SC does not necessarily produce microsaccades and add to evidence that saccade preparation and cancelation are separate processes.

The importance of decision onset

The neural mechanisms of decision making are thought to require the integration of evidence over time until a response threshold is reached. Much work suggests that response threshold can be adjusted via top-down control as a function of speed or accuracy requirements. In contrast, the time of integration onset has received less attention and is believed to be determined mostly by afferent or preprocessing delays. However, a number of influential studies over the past decade challenge this assumption and begin to paint a multifaceted view of the phenomenology of decision onset. This review highlights the challenges involved in initiating the integration of evidence at the optimal time and the potential benefits of adjusting integration onset to task demands. The review outlines behavioral and electrophysiolgical studies suggesting that the onset of the integration process may depend on properties of the stimulus, the task, attention, and response strategy. Most importantly, the aggregate findings in the literature suggest that integration onset may be amenable to top-down regulation, and may be adjusted much like response threshold to exert cognitive control and strategically optimize the decision process to fit immediate behavioral requirements.

Competing Neural Ensembles in Motor Cortex Gate Goal-Directed Motor Output

Unit recordings in behaving animals have revealed the transformation of sensory to motor representations in cortical neurons. However, we still lack basic insights into the mechanisms by which neurons interact to generate such transformations. Here, we study cortical circuits related to behavioral control in mice engaged in a sensory detection task. We recorded neural activity using extracellular and intracellular techniques and analyzed the task-related neural dynamics to reveal underlying circuit processes. Within motor cortex, we find two populations of neurons that have opposing spiking patterns in anticipation of movement. From correlation analyses and circuit modeling, we suggest that these dynamics reflect neural ensembles engaged in a competition. Furthermore, we demonstrate how this competitive circuit may convert a transient, sensory stimulus into a motor command. Together, these data reveal cellular and circuit processes underlying behavioral control and establish an essential framework for future studies linking cellular activity to behavior.

Limitations of short range Mexican hat connection for driving target selection in a 2D neural field: activity suppression and deviation from input stimuli

Dynamic Neural Field models (DNF) often use a kernel of connection with short range excitation and long range inhibition. This organization has been suggested as a model for brain structures or for artificial systems involved in winner-take-all processes such as saliency localization, perceptual decision or target/action selection. A good example of such a DNF is the superior colliculus (SC), a key structure for eye movements. Recent results suggest that the superficial layers of the SC (SCs) exhibit relatively short range inhibition with a longer time constant than excitation. The aim of the present study was to further examine the properties of a DNF with such an inhibition pattern in the context of target selection. First we tested the effects of stimulus size and shape on when and where self-maintained clusters of firing neurons appeared, using three variants of the model. In each model variant, small stimuli led to rapid formation of a spiking cluster, a range of medium sizes led to the suppression of any activity on the network and hence to no target selection, while larger sizes led to delayed selection of multiple loci. Second, we tested the model with two stimuli separated by a varying distance. Again single, none, or multiple spiking clusters could occur, depending on distance and relative stimulus strength. For short distances, activity attracted toward the strongest stimulus, reminiscent of well-known behavioral data for saccadic eye movements, while for larger distances repulsion away from the second stimulus occurred. All these properties predicted by the model suggest that the SCs, or any other neural structure thought to implement a short range MH, is an imperfect winner-take-all system. Although, those properties call for systematic testing, the discussion gathers neurophysiological and behavioral data suggesting that such properties are indeed present in target selection for saccadic eye movements.

Anticipating conflict: Neural correlates of a Bayesian belief and its motor consequence

Previous studies have examined the neural correlates of proactive control using a variety of behavioral paradigms; however, the neural network relating the control process to its behavioral consequence remains unclear. Here, we applied a dynamic Bayesian model to a large fMRI data set of the stop signal task to address this issue. By estimating the probability of the stop signal - p(Stop) - trial by trial, we showed that higher p(Stop) is associated with prolonged go trial reaction time (RT), indicating proactive control of motor response. In modeling fMRI signals at trial and target onsets, we distinguished activities of proactive control, prediction error, and RT slowing. We showed that the anterior pre-supplementary motor area (pre-SMA) responds specifically to increased stop signal likelihood, and its activity is correlated with activations of the posterior pre-SMA and bilateral anterior insula during prolonged response times. This directional link is also supported by Granger causality analysis. Furthermore, proactive control, prediction error, and time-on-task are each mapped to distinct areas in the medial prefrontal cortex. Together, these findings dissect regional functions of the medial prefrontal cortex in cognitive control and provide system level evidence associating conflict anticipation with its motor consequence.

Independent component analysis of functional networks for response inhibition: Inter-subject variation in stop signal reaction time

Cognitive control is a critical executive function. Many studies have combined general linear modeling and the stop signal task (SST) to delineate the component processes of cognitive control. For instance, by contrasting stop success (SS) and stop error (SE) trials in the SST, investigators examined regional responses to stop signal inhibition. In contrast to this parameterized approach, independent component analysis (ICA) elucidates brain networks subserving cognitive control. In our earlier work of 59 adults performing the SST during fMRI, we characterized six independent components (ICs). However, none of these ICs correlated with stop signal performance, raising questions about their behavioral validity. Here, in a larger sample (n = 100), we identified and explored 23 ICs for correlation with the stop signal reaction time (SSRT), a measure of the efficiency of response inhibition. At a corrected threshold (P < 0.0005), a paracentral lobule-midcingulate network and a left inferior parietal-supplementary motor-somatomotor network showed a positive correlation between SE beta weight and SSRT. In contrast, a midline cerebellum-thalamus-pallidum network showed a negative correlation between SE beta weight and SSRT. These findings suggest that motor preparation and execution prolongs the SSRT, likely via an interaction between the go and stop processes as suggested by the race model. Behaviorally, consistent with this hypothesis, the difference in G and SE reaction times is positively correlated with SSRT across subjects. These new results highlight the importance of cognitive motor regions in response inhibition and support the utility of ICA in uncovering functional networks for cognitive control in the SST.

Speed-accuracy tradeoff by a control signal with balanced excitation and inhibition

A hallmark of flexible behavior is the brain's ability to dynamically adjust speed and accuracy in decision-making. Recent studies suggested that such adjustments modulate not only the decision threshold, but also the rate of evidence accumulation. However, the underlying neuronal-level mechanism of the rate change remains unclear. In this work, using a spiking neural network model of perceptual decision, we demonstrate that speed and accuracy of a decision process can be effectively adjusted by manipulating a top-down control signal with balanced excitation and inhibition [balanced synaptic input (BSI)]. Our model predicts that emphasizing accuracy over speed leads to reduced rate of ramping activity and reduced baseline activity of decision neurons, which have been observed recently at the level of single neurons recorded from behaving monkeys in speed-accuracy tradeoff tasks. Moreover, we found that an increased inhibitory component of BSI skews the decision time distribution and produces a pronounced exponential tail, which is commonly observed in human studies. Our findings suggest that BSI can serve as a top-down control mechanism to rapidly and parametrically trade between speed and accuracy, and such a cognitive control signal presents both when the subjects emphasize accuracy or speed in perceptual decisions.

Ocular motor measures of cognitive dysfunction in multiple sclerosis I: inhibitory control

Our ability to control and inhibit behaviours that are inappropriate, unsafe, or no longer required is crucial for functioning successfully in complex environments. Here, we investigated whether a series of ocular motor (OM) inhibition tasks could dissociate deficits in patients with multiple sclerosis (MS), including patients with only a probable diagnosis (clinically isolated syndrome: CIS), from healthy individuals as well as a function of increasing disease duration. 25 patients with CIS, 25 early clinically definite MS patients (CDMS: ≤7 years of diagnosis), 24 late CDMS patients (>7 years from diagnosis), and 25 healthy controls participated. All participants completed a series of classic OM inhibition tasks [antisaccade (AS) task, memory-guided (MG) task, endogenous cue task], and a neuropsychological inhibition task [paced auditory serial addition test (PASAT)]. Clinical disability was characterised in CDMS patients using the Expanded Disability Severity Scale (EDSS). OM (latency and error) and PASAT performance were compared between patient groups and controls, as well as a function of disease duration. For CDMS patients only, results were correlated with EDSS score. All patient groups made more errors than controls on all OM tasks; error rate did not increase with increasing disease duration. In contrast, saccade latency (MG and endogenous cue tasks) was found to worsen with increasing disease duration. PASAT performance did not discriminate patient groups or disease duration. The EDSS did not correlate with any measure. These OM measures appear to dissociate deficit between patients at different disease durations. This suggests their utility as a measure of progression from the earliest inception of the disease.

Inhibitory control in mind and brain 2.0: blocked-input models of saccadic countermanding

The interactive race model of saccadic countermanding assumes that response inhibition results from an interaction between a go unit, identified with gaze-shifting neurons, and a stop unit, identified with gaze-holding neurons, in which activation of the stop unit inhibits the growth of activation in the go unit to prevent it from reaching threshold. The interactive race model accounts for behavioral data and predicts physiological data in monkeys performing the stop-signal task. We propose an alternative model that assumes that response inhibition results from blocking the input to the go unit. We show that the blocked-input model accounts for behavioral data as accurately as the original interactive race model and predicts aspects of the physiological data more accurately. We extend the models to address the steady-state fixation period before the go stimulus is presented and find that the blocked-input model fits better than the interactive race model. We consider a model in which fixation activity is boosted when a stop signal occurs and find that it fits as well as the blocked input model but predicts very high steady-state fixation activity after the response is inhibited. We discuss the alternative linking propositions that connect computational models to neural mechanisms, the lessons to be learned from model mimicry, and generalization from countermanding saccades to countermanding other kinds of responses.

How does response inhibition influence decision making when gambling?

Recent research suggests that response inhibition training can alter impulsive and compulsive behavior. When stop signals are introduced in a gambling task, people not only become more cautious when executing their choice responses, they also prefer lower bets when gambling. Here, we examined how stopping motor responses influences gambling. Experiment 1 showed that the reduced betting in stop-signal blocks was not caused by changes in information sampling styles or changes in arousal. In Experiments 2a and 2b, people preferred lower bets when they occasionally had to stop their response in a secondary decision-making task but not when they were instructed to respond as accurately as possible. Experiment 3 showed that merely introducing trials on which subjects could not gamble did not influence gambling preferences. Experiment 4 demonstrated that the effect of stopping on gambling generalized to different populations. Further, 2 combined analyses suggested that the effect of stopping on gambling preferences was reliable but small. Finally, Experiment 5 showed that the effect of stopping on gambling generalized to a different task. On the basis of our findings and earlier research, we propose that the presence of stop signals influences gambling by reducing approach behavior and altering the motivational value of the gambling outcome.

Computational psychiatry

Psychiatric disorders such as autism and schizophrenia, arise from abnormalities in brain systems that underlie cognitive, emotional, and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically realistic modeling bridging cellular and synaptic mechanisms with behavior, and model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field.

Alpha- and beta-band oscillations subserve different processes in reactive control of limb movements

The capacity to rapidly suppress a behavioral act in response to sudden instruction to stop is a key cognitive function. This function, called reactive control, is tested in experimental settings using the stop signal task, which requires subjects to generate a movement in response to a go signal or suppress it when a stop signal appears. The ability to inhibit this movement fluctuates over time: sometimes, subjects can stop their response, and at other times, they can not. To determine the neural basis of this fluctuation, we recorded local field potentials (LFPs) in the alpha (6–12 Hz) and beta (13–35 Hz) bands from the dorsal premotor cortex of two nonhuman primates that were performing the task. The ability to countermand a movement after a stop signal was predicted by the activity of both bands, each purportedly representing a distinct neural process. The beta band represents the level of movement preparation; higher beta power corresponds to a lower level of movement preparation, whereas the alpha band supports a proper phasic, reactive inhibitory response: movements are inhibited when alpha band power increases immediately after a stop signal. Our findings support the function of LFP bands in generating the signatures of various neural computations that are multiplexed in the brain.

Banishing the Control Homunculi in Studies of Action Control and Behavior Change

For centuries, human self-control has fascinated scientists and nonscientists alike. Current theories often attribute it to an executive control system. But even though executive control receives a great deal of attention across disciplines, most aspects of it are still poorly understood. Many theories rely on an ill-defined set of "homunculi" doing jobs like "response inhibition" or "updating" without explaining how they do so. Furthermore, it is not always appreciated that control takes place across different timescales. These two issues hamper major advances. Here we focus on the mechanistic basis for the executive control of actions. We propose that at the most basic level, action control depends on three cognitive processes: signal detection, action selection, and action execution. These processes are modulated via error-correction or outcome-evaluation mechanisms, preparation, and task rules maintained in working and long-term memory. We also consider how executive control of actions becomes automatized with practice and how people develop a control network. Finally, we discuss how the application of this unified framework in clinical domains can increase our understanding of control deficits and provide a theoretical basis for the development of novel behavioral change interventions.

The dorsal medial frontal cortex mediates automatic motor inhibition in uncertain contexts: evidence from combined fMRI and EEG studies

Response inhibition is commonly thought to rely on voluntary, reactive, selective, and relatively slow prefrontal mechanisms. In contrast, we suggest here that response inhibition is achieved automatically, nonselectively, within very short delays in uncertain environments. We modified a classical go/nogo protocol to probe context-dependent inhibitory mechanisms. Because no single neuroimaging method can definitely disentangle neural excitation and inhibition, we combined fMRI and EEG recordings in healthy humans. Any stimulus (go or nogo) presented in an uncertain context requiring action restraint was found to evoke activity changes in the supplementary motor complex (SMC) with respect to a control condition in which no response inhibition was required. These changes included: (1) An increase in event-related BOLD activity, (2) an attenuation of the early (170 ms) event related potential generated by a single, consistent source isolated by advanced blind source separation, and (3) an increase in the evoked-EEG Alpha power of this source. Considered together, these results suggest that the BOLD signal evoked by any stimulus in the SMC when the situation is unpredictable can be driven by automatic, nonselective, context-dependent inhibitory activities. This finding reveals the paradoxical mechanisms by which voluntary control of action may be achieved. The ability to provide controlled responses in unpredictable environments would require setting-up the automatic self-inhibitory circuitry within the SMC. Conversely, enabling automatic behavior when the environment becomes predictable would require top-down control to deactivate anticipatorily and temporarily the inhibitory set.

A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution

A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.

Frontostriatal activity and connectivity increase during proactive inhibition across adolescence and early adulthood

During adolescence, functional and structural changes in the brain facilitate the transition from childhood to adulthood. Because the cortex and the striatum mature at different rates, temporary imbalances in the frontostriatal network occur. Here, we investigate the development of the subcortical and cortical components of the frontostriatal network from early adolescence to early adulthood in 60 subjects in a cross-sectional design, using functional MRI and a stop-signal task measuring two forms of inhibitory control: reactive inhibition (outright stopping) and proactive inhibition (anticipation of stopping). During development, reactive inhibition improved: older subjects were faster in reactive inhibition. In the brain, this was paralleled by an increase in motor cortex suppression. The level of proactive inhibition increased, with older subjects slowing down responding more than younger subjects when anticipating a stop-signal. Activation increased in the right striatum, right ventral and dorsal inferior frontal gyrus, and supplementary motor area. Moreover, functional connectivity during proactive inhibition increased between striatum and frontal regions with age. In conclusion, we demonstrate that developmental improvements in proactive inhibition are paralleled by increases in activation and functional connectivity of the frontostriatal network. These data serve as a stepping stone to investigate abnormal development of the frontostriatal network in disorders such as schizophrenia and attention-deficit hyperactivity disorder.

Response times from ensembles of accumulators

Decision-making is explained by psychologists through stochastic accumulator models and by neurophysiologists through the activity of neurons believed to instantiate these models. We investigated an overlooked scaling problem: How does a response time (RT) that can be explained by a single model accumulator arise from numerous, redundant accumulator neurons, each of which individually appears to explain the variability of RT? We explored this scaling problem by developing a unique ensemble model of RT, called e pluribus unum, which embodies the well-known dictum "out of many, one." We used the e pluribus unum model to analyze the RTs produced by ensembles of redundant, idiosyncratic stochastic accumulators under various termination mechanisms and accumulation rate correlations in computer simulations of ensembles of varying size. We found that predicted RT distributions are largely invariant to ensemble size if the accumulators share at least modestly correlated accumulation rates and RT is not governed by the most extreme accumulators. Under these regimes the termination times of individual accumulators was predictive of ensemble RT. We also found that the threshold measured on individual accumulators, corresponding to the firing rate of neurons measured at RT, can be invariant with RT but is equivalent to the specified model threshold only when the rate correlation is very high.

Production, control, and visual guidance of saccadic eye movements

Primate vision is served by rapid shifts of gaze called saccades. This review will survey current knowledge and particular problems concerning the neural control and guidance of gaze shifts.