On the neural implementation of the speed-accuracy trade-off

A multilayered bidirectional associative memory model for learning nonlinear tasks

A multilayered bidirectional associative memory neural network is proposed to account for learning nonlinear types of association. The model (denoted as the MF-BAM) is composed of two modules, the Multi-Feature extracting bidirectional associative memory (MF), which contains various unsupervised network layers, and a modified Bidirectional Associative Memory (BAM), which consists of a single supervised network layer. The MF generates successive feature patterns from the original inputs. These patterns change the relationship between the inputs and targets in a way that the BAM can learn. The model was tested on different nonlinear tasks, such as the N-bit, Double Moon and its variants, and the 3-class spiral task. Behaviors were reported through learning errors, decision zones, and recall performances. Results showed that it was possible to learn all tasks consistently. By manipulating the number of units per layer and the number of unsupervised network layers in the MF, it was possible to change the level of nonlinearity observed in the decision boundaries. Furthermore, results indicated that different behaviors were achieved from the same set of inputs by using the different generated patterns. These findings are significant as they showed how a BAM-inspired model could solve nonlinear tasks in a more cognitively plausible fashion.

A Randomized, Double-Blind, Placebo-Controlled, Parallel Study Investigating the Efficacy of a Whole Coffee Cherry Extract and Phosphatidylserine Formulation on Cognitive Performance of Healthy Adults with Self-Perceived Memory Problems

INTRODUCTION

Cognition refers to brain functions including memory, learning, and thought processing and is increasingly important to individuals. However, impairment of cognitive function is a concern among North American adults. Therefore, effective and reliable treatments are needed.

METHODS

This randomized, double-blind, placebo-controlled study examined the effects of 42 days of Neuriva® supplementation, a whole coffee cherry extract and phosphatidylserine supplement, on memory, accuracy, focus and concentration and learning among 138 healthy adults (40-65 years) with self-reported memory problems. Plasma brain-derived neurotrophic factor (BDNF) levels, Computerized Mental Performance Assessment System (COMPASS) tasks, the Everyday Memory Questionnaire (EMQ), and Go/No-Go tests were assessed at baseline and day 42.

RESULTS

As compared to placebo, Neuriva® supplementation elicited greater improvements at day 42 in numeric working memory COMPASS task accuracy outcomes (p ≤ 0.024) which assessed memory, accuracy, and focus and concentration, and reaction time outcomes (p ≤ 0.031) which assessed memory as well as focus and concentration. Neuriva® supplementation improved overall accuracy (p = 0.035) in the picture recognition task that assessed memory, accuracy, and learning compared to placebo. No significant differences between groups were observed for BDNF, the EMQ, or Go/No-Go tests.

CONCLUSION

Results suggest 42 days of Neuriva® supplementation was safe, well tolerated, and beneficial in improving memory, accuracy, focus and concentration, and learning in a healthy adult population with self-reported memory problems.

Investigating the involvement of cognitive control processes in innovative and adaptive creativity and their age-related changes

Introduction

Based on the two-factor model of creativity, two distinct types of creative problem solving can be differentiated: innovative ("do things differently") and adaptive ("do things better"). Flexible cognitive control is a crucial concept in connection with both general and specific styles of creativity: innovative problem-solving benefits from broader attention and flexible mental set shifting; while adaptive creativity relies on focused attention and persistent goal-oriented processes. We applied an informatively cued task-switching paradigm which is suitable for measuring different cognitive control processes and mechanisms like proactive and reactive control. We hypothesized that adaptive creativity is connected to effective proactive control processes, while innovative creativity is based on reactive task-execution. As we have found no previous evidence how age-related changes in cognitive control affects creative cognition; we also examined the effect of healthy aging on different problem-solving styles in an explorative way.

Methods

Our participants, 37 younger (18-30 years) and 37 older (60-75 years) adults, were divided into innovative and adaptive creative groups according to the Torrance Test of Creative Thinking's Figural Subtest (Hungarian version).

Results

Our results showed that among younger adults the adaptively creative group had larger cue-locked CNV component (effective preparatory activity connected to proactive control), while the innovatively creative group had a larger target-locked P3b component (effective target evaluation and categorization in line with reactive control) which supports a functional difference in the two creative styles. By contrast, in older adults innovative problem-solving showed larger mixing costs (less effective maintenance and selection of task sets), and the lack of trial type effect on target-locked N2b (target-induced goal reactivation and less effective conflict resolution); while adaptive problem-solving caused them to make fewer errors (accuracy-oriented behavior).

Discussion

All in all, innovative and adaptive creativity is based on distinct cognitive control mechanisms in both age-groups, but their processing level is affected by age-related changes.

A meta-analysis showing improved cognitive performance in healthy young adults with transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation used for improving cognitive functions via delivering weak electrical stimulation with a certain frequency. This systematic review and meta-analysis investigated the effects of tACS protocols on cognitive functions in healthy young adults. We identified 56 qualified studies that compared cognitive functions between tACS and sham control groups, as indicated by cognitive performances and cognition-related reaction time. Moderator variable analyses specified effect size according to (a) timing of tACS, (b) frequency band of simulation, (c) targeted brain region, and (b) cognitive domain, respectively. Random-effects model meta-analysis revealed small positive effects of tACS protocols on cognitive performances. The moderator variable analyses found significant effects for online-tACS with theta frequency band, online-tACS with gamma frequency band, and offline-tACS with theta frequency band. Moreover, cognitive performances were improved in online- and offline-tACS with theta frequency band on either prefrontal and posterior parietal cortical regions, and further both online- and offline-tACS with theta frequency band enhanced executive function. Online-tACS with gamma frequency band on posterior parietal cortex was effective for improving cognitive performances, and the cognitive improvements appeared in executive function and perceptual-motor function. These findings suggested that tACS protocols with specific timing and frequency band may effectively improve cognitive performances.

Computational analysis of speed-accuracy tradeoff

Speed-accuracy tradeoff (SAT) in the decision making of humans and animals is a well-documented phenomenon, but its underlying neuronal mechanism remains unclear. Modeling approaches have conceptualized SAT through the threshold hypothesis as adjustments to the decision threshold. However, the leading neurophysiological view is the gain modulation hypothesis. This hypothesis postulates that the SAT mechanism is implemented through changes in the dynamics of the choice circuit, which increase the baseline firing rate and the speed of neuronal integration. In this paper, I investigated alternative computational mechanisms of SAT and showed that the threshold hypothesis was qualitatively consistent with the behavioral data, but the gain modulation hypothesis was not. In order to reconcile the threshold hypothesis with the neurophysiological evidence, I considered the interference of alpha oscillations with the decision process and showed that alpha oscillations could increase the discriminatory power of the decision system, although they slowed down the decision process. This suggests that the magnitude of alpha waves suppression during the event related desynchronization (ERD) of alpha oscillations depends on a SAT condition and the amplitude of alpha oscillations is lower in the speed condition. I also showed that the lower amplitude of alpha oscillations resulted in an increase in the baseline firing rate and the speed of neuronal intergration. Thus, the interference of the event related desynchronization of alpha oscillations with a SAT condition explains why an increase in the baseline firing rate and the speed of neuronal integration accompany the speed condition.

Motivation by reward jointly improves speed and accuracy, whereas task-relevance and meaningful images do not

Visual selection is characterized by a trade-off between speed and accuracy. Speed or accuracy of the selection process can be affected by higher level factors—for example, expecting a reward, obtaining task-relevant information, or seeing an intrinsically relevant target. Recently, motivation by reward has been shown to simultaneously increase speed and accuracy, thus going beyond the speed–accuracy-trade-off. Here, we compared the motivating abilities of monetary reward, task-relevance, and image content to simultaneously increase speed and accuracy. We used a saccadic distraction task that required suppressing a distractor and selecting a target. Across different blocks successful target selection was followed either by (i) a monetary reward, (ii) obtaining task-relevant information, or (iii) seeing the face of a famous person. Each block additionally contained the same number of irrelevant trials lacking these consequences, and participants were informed about the upcoming trial type. We found that postsaccadic vision of a face affected neither speed nor accuracy, suggesting that image content does not affect visual selection via motivational mechanisms. Task relevance increased speed but decreased selection accuracy, an observation compatible with a classical speed–accuracy trade-off. Motivation by reward, however, simultaneously increased response speed and accuracy. Saccades in all conditions deviated away from the distractor, suggesting that the distractor was suppressed, and this deviation was strongest in the reward block. Drift-diffusion modelling revealed that task-relevance affected behavior by affecting decision thresholds, whereas motivation by reward additionally increased the rate of information uptake. The present findings thus show that the three consequences differ in their motivational abilities.

HD-tDCS of primary and higher-order motor cortex affects action word processing

The contribution of action-perception systems of the brain to lexical semantics remains controversial. Here, we used high-definition transcranial direct current stimulation (HD-tDCS) in healthy adults to examine the role of primary (left hand motor area; HMA) and higher-order (left anterior inferior parietal lobe; aIPL) action areas in action-related word processing (action verbs and manipulable nouns) compared to non-action-related control words (non-action verbs and non-manipulable nouns). We investigated stimulation-related effects at three levels of semantic processing: subliminal, implicit, and explicit. Broadly, we found that stimulation of HMA and aIPL resulted in relative facilitation of action-related language processing compared to non-action. HMA stimulation facilitated action verb processing in subliminal and implicit task contexts, suggesting that HMA helps represent action verbs even in semantically shallow tasks. HMA stimulation also facilitated manipulable noun comprehension in an explicit semantic task, suggesting that HMA contributes to manipulable noun comprehension when semantic demands are high. aIPL stimulation facilitated both manipulable noun and action verb processing during an implicit task. We suggest that both HMA and aIPL play a functional role in action semantics. HMA plays a general role in the semantics of actions and manipulable objects, while aIPL is important only when visuo-motor coordination is required for the action.

Degenerate boundaries for multiple-alternative decisions

Integration-to-threshold models of two-choice perceptual decision making have guided our understanding of human and animal behavior and neural processing. Although such models seem to extend naturally to multiple-choice decision making, consensus on a normative framework has yet to emerge, and hence the implications of threshold characteristics for multiple choices have only been partially explored. Here we consider sequential Bayesian inference and a conceptualisation of decision making as a particle diffusing in n-dimensions. We show by simulation that, within a parameterised subset of time-independent boundaries, the optimal decision boundaries comprise a degenerate family of nonlinear structures that jointly depend on the state of multiple accumulators and speed-accuracy trade-offs. This degeneracy is contrary to current 2-choice results where there is a single optimal threshold. Such boundaries support both stationary and collapsing thresholds as optimal strategies for decision-making, both of which result from stationary representations of nonlinear boundaries. Our findings point towards a normative theory of multiple-choice decision making, provide a characterisation of optimal decision thresholds under this framework, and inform the debate between stationary and dynamic decision boundaries for optimal decision making.

Effector-dependent stochastic reference frame transformations alter decision-making

Psychophysical, motor control, and modeling studies have revealed that sensorimotor reference frame transformations (RFTs) add variability to transformed signals. For perceptual decision-making, this phenomenon could decrease the fidelity of a decision signal's representation or alternatively improve its processing through stochastic facilitation. We investigated these two hypotheses under various sensorimotor RFT constraints. Participants performed a time-limited, forced-choice motion discrimination task under eight combinations of head roll and/or stimulus rotation while responding either with a saccade or button press. This paradigm, together with the use of a decision model, allowed us to parameterize and correlate perceptual decision behavior with eye-, head-, and shoulder-centered sensory and motor reference frames. Misalignments between sensory and motor reference frames produced systematic changes in reaction time and response accuracy. For some conditions, these changes were consistent with a degradation of motion evidence commensurate with a decrease in stimulus strength in our model framework. Differences in participant performance were explained by a continuum of eye–head–shoulder representations of accumulated motion evidence, with an eye-centered bias during saccades and a shoulder-centered bias during button presses. In addition, we observed evidence for stochastic facilitation during head-rolled conditions (i.e., head roll resulted in faster, more accurate decisions in oblique motion for a given stimulus–response misalignment). We show that perceptual decision-making and stochastic RFTs are inseparable within the present context. We show that by simply rolling one's head, perceptual decision-making is altered in a way that is predicted by stochastic RFTs.

Imperfect integration: Congruency between multiple sensory sources modulates decision-making processes

Decision-making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. We combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying perceptual decision-making with single or double information sources. Ninety-four human participants performed binary decisions to discriminate the coherent motion direction averaged across two independent apertures. Regardless of the angular distance of the apertures, separating motion information into two apertures resulted in a reduction in accuracy. Our cognitive and neural-mass modelling results are consistent with the hypotheses that the addition of the second information source led to a lower signal-to-noise ratio of evidence accumulation with two congruent information sources, and a change in the decision strategy of speed–accuracy trade-off with two incongruent sources. Thus, our findings support a robust behavioural change in relation to multiple information sources, which have congruency-dependent impacts on selective decision-making subcomponents.

Hasty sensorimotor decisions rely on an overlap of broad and selective changes in motor activity

Humans and other animals are able to adjust their speed–accuracy trade-off (SAT) at will depending on the urge to act, favoring either cautious or hasty decision policies in different contexts. An emerging view is that SAT regulation relies on influences exerting broad changes on the motor system, tuning its activity up globally when hastiness is at premium. The present study aimed to test this hypothesis. A total of 50 participants performed a task involving choices between left and right index fingers, in which incorrect choices led either to a high or to a low penalty in 2 contexts, inciting them to emphasize either cautious or hasty policies. We applied transcranial magnetic stimulation (TMS) on multiple motor representations, eliciting motor-evoked potentials (MEPs) in 9 finger and leg muscles. MEP amplitudes allowed us to probe activity changes in the corresponding finger and leg representations, while participants were deliberating about which index to choose. Our data indicate that hastiness entails a broad amplification of motor activity, although this amplification was limited to the chosen side. On top of this effect, we identified a local suppression of motor activity, surrounding the chosen index representation. Hence, a decision policy favoring speed over accuracy appears to rely on overlapping processes producing a broad (but not global) amplification and a surround suppression of motor activity. The latter effect may help to increase the signal-to-noise ratio of the chosen representation, as supported by single-trial correlation analyses indicating a stronger differentiation of activity changes in finger representations in the hasty context.

Many have argued that the regulation of the speed-accuracy tradeoff relies on an urgency signal, which implements "collapsing decision thresholds" by tuning neural activity in a global manner in decision-related structures. This study indicates that the reality is more subtle, with several aspects of "urgency" being specifically targeted to particular corticospinal populations within the motor system.

Different strategies in pointing tasks and their impact on clinical bedside tests of spatial orientation

Deficits in spatial memory, orientation, and navigation are often early or neglected signs of degenerative and vestibular neurological disorders. A simple and reliable bedside test of these functions would be extremely relevant for diagnostic routine. Pointing at targets in the 3D environment is a basic well-trained common sensorimotor ability that provides a suitable measure. We here describe a smartphone-based pointing device using the built-in inertial sensors for analysis of pointing performance in azimuth and polar spatial coordinates. Interpretation of the vectors measured in this way is not trivial, since the individuals tested may use at least two different strategies: first, they may perform the task in an egocentric eye-based reference system by aligning the fingertip with the target retinotopically or second, by aligning the stretched arm and the index finger with the visual line of sight in allocentric world-based coordinates similar to using a rifle. The two strategies result in considerable differences of target coordinates. A pilot test with a further developed design of the device and an app for a standardized bedside utilization in five healthy volunteers revealed an overall mean deviation of less than 5° between the measured and the true coordinates. Future investigations of neurological patients comparing their performance before and after changes in body position (chair rotation) may allow differentiation of distinct orientational deficits in peripheral (vestibulopathy) or central (hippocampal or cortical) disorders.

Weighted neurofeedback facilitates greater self-regulation of functional connectivity between the primary motor area and cerebellum

Objective.Brain-computer interface (BCI) is a tool that can be used to train brain self-regulation and influence specific activity patterns, including functional connectivity, through neurofeedback. The functional connectivity of the primary motor area (M1) and cerebellum play a critical role in motor recovery after a brain injury, such as stroke. The objective of this study was to determine the feasibility of achieving control of the functional connectivity between M1 and the cerebellum in healthy subjects. Additionally, we aimed to compare the brain self-regulation of two different feedback modalities and their effects on motor performance.Approach.Nine subjects were trained with a real-time functional magnetic resonance imaging BCI system. Two groups were conformed: equal feedback group (EFG), which received neurofeedback that weighted the contribution of both regions of interest (ROIs) equally, and weighted feedback group (WFG) that weighted each ROI differentially (30% cerebellum; 70% M1). The magnitude of the brain activity induced by self-regulation was evaluated with the blood-oxygen-level-dependent (BOLD) percent change (BPC). Functional connectivity was assessed using temporal correlations between the BOLD signal of both ROIs. A finger-tapping task was included to evaluate the effect of brain self-regulation on motor performance.Main results.A comparison between the feedback modalities showed that WFG achieved significantly higher BPC in M1 than EFG. The functional connectivity between ROIs during up-regulation in WFG was significantly higher than EFG. In general, both groups showed better tapping speed in the third session compared to the first. For WFG, there were significant correlations between functional connectivity and tapping speed.Significance.The results show that it is possible to train healthy individuals to control M1-cerebellum functional connectivity with rtfMRI-BCI. Besides, it is also possible to use a weighted feedback approach to facilitate a higher activity of one region over another.

Pushing to the Limits: What Processes during Cognitive Control are Enhanced by Reaction-Time Feedback?

To respond as quickly as possible in a given task is a widely used instruction in cognitive neuroscience; however, the neural processes modulated by this common experimental procedure remain largely elusive. We investigated the underlying neurophysiological processes combining electroencephalography (EEG) signal decomposition (residue iteration decomposition, RIDE) and source localization. We show that trial-based response speed instructions enhance behavioral performance in conflicting trials, but slightly impair performance in nonconflicting trials. The modulation seen in conflicting trials was found at several coding levels in EEG data using RIDE. In the S-cluster N2 time window, this modulation was associated with modulated activation in the posterior cingulate cortex and the superior frontal gyrus. Furthermore, in the C-cluster P3 time window, this modulation was associated with modulated activation in the middle frontal gyrus. Interestingly, in the R-cluster P3 time window, this modulation was strongest according to statistical effect sizes, associated with modulated activity in the primary motor cortex. Reaction-time feedback mainly modulates response motor execution processes, whereas attentional and response selection processes are less affected. The study underlines the importance of being aware of how experimental instructions influence the behavior and neurophysiological processes.

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.

Characterizing the role of the pre-SMA in the control of speed/accuracy trade-off with directed functional connectivity mapping and multiple solution reduction

Several plausible theories of the neural implementation of speed/accuracy trade-off (SAT), the phenomenon in which individuals may alternately emphasize speed or accuracy during the performance of cognitive tasks, have been proposed, and multiple lines of evidence point to the involvement of the pre-supplemental motor area (pre-SMA). However, as the nature and directionality of the pre-SMA's functional connections to other regions involved in cognitive control and task processing are not known, its precise role in the top-down control of SAT remains unclear. Although recent advances in cross-sectional path modeling provide a promising way of characterizing these connections, such models are limited by their tendency to produce multiple equivalent solutions. In a sample of healthy adults (N = 18), the current study uses the novel approach of Group Iterative Multiple Model Estimation for Multiple Solutions (GIMME-MS) to assess directed functional connections between the pre-SMA, other regions previously linked to control of SAT, and regions putatively involved in evidence accumulation for the decision task. Results reveal a primary role of the pre-SMA for modulating activity in regions involved in the decision process but suggest that this region receives top-down input from the DLPFC. Findings also demonstrate the utility of GIMME-MS and solution-reduction methods for obtaining valid directional inferences from connectivity path models.

Bumblebees Express Consistent, but Flexible, Speed-Accuracy Tactics Under Different Levels of Predation Threat

A speed-accuracy trade-off (SAT) in behavioural decisions is known to occur in a wide range of vertebrate and invertebrate taxa. Accurate decisions often take longer for a given condition, while fast decisions can be inaccurate in some tasks. Speed-accuracy tactics are known to vary consistently among individuals, and show a degree of flexibility during colour discrimination tasks in bees. Such individual flexibility in speed-accuracy tactics is likely to be advantageous for animals exposed to fluctuating environments, such as changes in predation threat. We therefore test whether individual speed-accuracy tactics are fixed or flexible under different levels of predation threat in a model invertebrate, the bumblebee Bombus terrestris. The flexibility of speed-accuracy tactics in a foraging context was tested in the laboratory using a “meadow” of artificial flowers harbouring “robotic” crab spider predators. We found that while the ranking of bees along the speed and accuracy continuums was consistent across two levels of predation threat, there was some flexibility in the tactics used by individual bees – most bees became less accurate at colour discrimination when exposed to predation threat when flower types were rewarding. The relationship between decision speed and accuracy was influenced by predator detectability and the risk associated with making incorrect choices during the colour discrimination task. Predator crypsis resulted in a breakdown in the relationship between speed and accuracy, especially when making an incorrect floral choice incurred a distasteful quinine punishment. No single speed-accuracy tactic was found to be optimal in terms of foraging efficiency under either predation threat situation. However, bees that made faster decisions achieved higher nectar collection rates in predator free situations, while accurate bees achieved higher foraging rates under predation threat. Our findings show that while individual bees remain relatively consistent in terms of whether they place greater emphasis on speed or accuracy under predation threat, they can respond flexibly to the additional time costs of detecting predators.

Slot-like capacity and resource-like coding in a neural model of multiple-item working memory

For the past decade, research on the storage limitations of working memory has been dominated by two fundamentally different hypotheses. On the one hand, the contents of working memory may be stored in a limited number of "slots," each with a fixed resolution. On the other hand, any number of items may be stored but with decreasing resolution. These two hypotheses have been invaluable in characterizing the computational structure of working memory, but neither provides a complete account of the available experimental data or speaks to the neural basis of the limitations it characterizes. To address these shortcomings, we simulated a multiple-item working memory task with a cortical network model, the cellular resolution of which allowed us to quantify the coding fidelity of memoranda as a function of memory load, as measured by the discriminability, regularity, and reliability of simulated neural spiking. Our simulations account for a wealth of neural and behavioral data from human and nonhuman primate studies, and they demonstrate that feedback inhibition lowers both capacity and coding fidelity. Because the strength of inhibition scales with the number of items stored by the network, increasing this number progressively lowers fidelity until capacity is reached. Crucially, the model makes specific, testable predictions for neural activity on multiple-item working memory tasks. NEW & NOTEWORTHY Working memory is the ability to keep information in mind and is fundamental to cognition. It is actively debated whether the storage limitations of working memory reflect a small number of storage units (slots) or a decrease in coding resolution as a limited resource is allocated to more items. In a cortical model, we found that slot-like capacity and resource-like neural coding resulted from the same mechanism, offering an integrated explanation for storage limitations.

Improving Dual-Task Control With a Posture-Second Strategy in Early-Stage Parkinson Disease

OBJECTIVE

To examine the task prioritization effects on postural-suprapostural dual-task performance in patients with early-stage Parkinson disease (PD) without clinically observed postural symptoms.

DESIGN

Cross-sectional study. Participants performed a force-matching task while standing on a mobile platform, and were instructed to focus their attention on either the postural task (posture-first strategy) or the force-matching task (posture-second strategy).

SETTING

University research laboratory.

PARTICIPANTS

Individuals (N=16) with early-stage PD who had no clinically observed postural symptoms.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Dual-task change (DTC; percent change between single-task and dual-task performance) of posture error, posture approximate entropy (ApEn), force error, and reaction time (RT). Positive DTC values indicate higher postural error, posture ApEn, force error, and force RT during dual-task conditions compared with single-task conditions.

RESULTS

Compared with the posture-first strategy, the posture-second strategy was associated with smaller DTC of posture error and force error, and greater DTC of posture ApEn. In contrast, greater DTC of force RT was observed under the posture-second strategy.

CONCLUSIONS

Contrary to typical recommendations, our results suggest that the posture-second strategy may be an effective dual-task strategy in patients with early-stage PD who have no clinically observed postural symptoms in order to reduce the negative effect of dual tasking on performance and facilitate postural automaticity.

One year after ischemic stroke: Changes in leg movement path stability in a speed-accuracy task but no major effects on the hands

First year after the stroke is essential for motor recovery. The main motor control strategy (i.e., faster movement production at the expense of lower movement accuracy and stability, or greater movement accuracy and stability at the expense of slower movement) selected by poststroke patients during a unilateral speed-accuracy task (SAT) remains unclear. We aimed to investigate the poststroke (12 months after stroke) effects on the trade-off between movement speed and accuracy, and intraindividual variability during a motor performance task. Healthy right-handed men (n = 20; age ∼ 66 years) and right-handed men after ischemic stroke during their post rehabilitation period (n = 20; age ∼ 69 years) were asked to perform a simple reaction task, a maximal velocity performance task and a SAT with the right and left hand, and with the right and left leg. In the hand movement trial, reaction time and movement velocity (V_max) in the SAT were slower and time to V_max in the SAT was longer in the poststroke group (P < .01). In the leg movement trial, poststroke participants reached a greater V_max in the SAT than the healthy participants (P < .01). The greatest poststroke effect on intraindividual variability in movements was found for movement path in the SAT, which was significantly greater in the legs than in the hands. Poststroke patients in the first year after stroke mainly selected an impulsive strategy for speed over hand and leg motor control, but at the expense of lower movement accuracy and greater variability in movement.

Working Memory and Decision-Making in a Frontoparietal Circuit Model

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models.SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks.

Optimal pseudorandom sequence selection for online c-VEP based BCI control applications

Background

In a c-VEP BCI setting, test subjects can have highly varying performances when different pseudorandom sequences are applied as stimulus, and ideally, multiple codes should be supported. On the other hand, repeating the experiment with many different pseudorandom sequences is a laborious process.

Aims

This study aimed to suggest an efficient method for choosing the optimal stimulus sequence based on a fast test and simple measures to increase the performance and minimize the time consumption for research trials.

Methods

A total of 21 healthy subjects were included in an online wheelchair control task and completed the same task using stimuli based on the m-code, the gold-code, and the Barker-code. Correct/incorrect identification and time consumption were obtained for each identification. Subject-specific templates were characterized and used in a forward-step first-order model to predict the chance of completion and accuracy score.

Results

No specific pseudorandom sequence showed superior accuracy on the group basis. When isolating the individual performances with the highest accuracy, time consumption per identification was not significantly increased. The Accuracy Score aids in predicting what pseudorandom sequence will lead to the best performance using only the templates. The Accuracy Score was higher when the template resembled a delta function the most and when repeated templates were consistent. For completion prediction, only the shape of the template was a significant predictor.

Conclusions

The simple and fast method presented in this study as the Accuracy Score, allows c-VEP based BCI systems to support multiple pseudorandom sequences without increase in trial length. This allows for more personalized BCI systems with better performance to be tested without increased costs.

Modulation of Premotor and Primary Motor Cortical Activity during Volitional Adjustments of Speed-Accuracy Trade-Offs

Recent work suggests that while animals decide between reaching actions, neurons in dorsal premotor (PMd) and primary motor (M1) cortex reflect a dynamic competition between motor plans and determine when commitment to a choice is made. This competition is biased by at least two sources of information: the changing sensory evidence for one choice versus another, and an urgency signal that grows over time. Here, we test the hypothesis that the urgency signal adjusts the trade-off between speed and accuracy during both decision-making and movement execution. Two monkeys performed a reaching decision task in which sensory evidence continuously evolves over the course of each trial. In different blocks, task timing parameters encouraged monkeys to voluntarily adapt their behavior to be either hasty or conservative. Consistent with our hypothesis, during the deliberation process the baseline and gain of neural activity in decision-related PMd (29%) and M1 cells (45%) was higher when monkeys applied a hasty policy than when they behaved conservatively, but at the time of commitment the population activity was similar across blocks. Other cells (30% in PMd, 30% in M1) showed activity that increased or decreased with elapsing time until the moment of commitment. Movement-related neurons were also more active after longer decisions, as if they were influenced by the same urgency signal controlling the gain of decision-related activity. Together, these results suggest that the arm motor system receives an urgency/vigor signal that adjusts the speed-accuracy trade-off for decision-making and movement execution. Significance statement: This work addresses the neural mechanisms that control the speed-accuracy trade-off in both decisions and movements, in the kinds of dynamic situations that are typical of natural animal behavior. We found that many "decision-related" premotor and motor neurons are modulated in a time-dependent manner compatible with an "urgency" signal that changes between hasty and conservative decision policies. We also found that such modulation influenced cells related to the speed of the reaching movements executed by the animals to report their decisions. These results suggest that a unified mechanism determines speed-accuracy trade-off adjustments during decision-making and movement execution, potentially influencing both the cognitive and motor aspects of reward-oriented behavior.

Continuous Theta Burst Stimulation Over the Dorsolateral Prefrontal Cortex and the Pre-SMA Alter Drift Rate and Response Thresholds Respectively During Perceptual Decision-Making

BACKGROUND

The speed-accuracy trade-off (SAT) refers to the balancing of speed versus accuracy during decision-making. SAT is very commonly investigated with perceptual decision-making tasks such as the moving dots task (MDT). The dorsolateral prefrontal cortex (DLPFC) and the pre-supplementary motor area (pre-SMA) are two brain regions considered to be involved in the control of SAT.

OBJECTIVES/HYPOTHESES

The study tested whether the DLPFC and the pre-SMA play an essential role in the control of SAT. We hypothesized that continuous theta burst stimulation (cTBS) over the right DLPFC would primarily alter the rate of accumulation of evidence, whereas stimulation of the pre-SMA would influence the threshold for reaching a decision.

METHODS

Fifteen (5 females; mean age = 30, SD =5.40) healthy volunteers participated in the study. We used two versions of the MDT and cTBS over the right DLPFC, pre-SMA and sham stimulation. The drift diffusion model was fit to the behavioural data (reaction time and error rate) in order to calculate the drift rate, boundary separation (threshold) and non-decision time.

RESULTS

cTBS over the right DLPFC decreased the rate of accumulation of evidence (i.e. the drift rate from the diffusion model) in high (0.35 and 0.5) but not in low coherence trials. cTBS over the pre-SMA changed the boundary separation/threshold required to reach a decision on accuracy, but not on speed trials.

CONCLUSIONS

The results suggest for the first time that both the DLPFC and the pre-SMA make essential but distinct contributions to the modulation of SAT.

Believer-Skeptic Meets Actor-Critic: Rethinking the Role of Basal Ganglia Pathways during Decision-Making and Reinforcement Learning

The flexibility of behavioral control is a testament to the brain's capacity for dynamically resolving uncertainty during goal-directed actions. This ability to select actions and learn from immediate feedback is driven by the dynamics of basal ganglia (BG) pathways. A growing body of empirical evidence conflicts with the traditional view that these pathways act as independent levers for facilitating (i.e., direct pathway) or suppressing (i.e., indirect pathway) motor output, suggesting instead that they engage in a dynamic competition during action decisions that computationally captures action uncertainty. Here we discuss the utility of encoding action uncertainty as a dynamic competition between opposing control pathways and provide evidence that this simple mechanism may have powerful implications for bridging neurocomputational theories of decision making and reinforcement learning.

Subthalamic nucleus deep brain stimulation induces impulsive action when patients with Parkinson's disease act under speed pressure

The subthalamic nucleus (STN) is proposed to modulate response thresholds and speed–accuracy trade-offs. In situations of conflict, the STN is considered to raise response thresholds, allowing time for the accumulation of information to occur before a response is selected. Conversely, speed pressure is thought to reduce the activity of the STN and lower response thresholds, resulting in fast, errorful responses. In Parkinson’s disease (PD), subthalamic nucleus deep brain stimulation (STN-DBS) reduces the activity of the nucleus and improves motor symptoms. We predicted that the combined effects of STN stimulation and speed pressure would lower STN activity and lead to fast, errorful responses, hence resulting in impulsive action. We used the motion discrimination ‘moving-dots’ task to assess speed–accuracy trade-offs, under both speed and accuracy instructions. We assessed 12 patients with PD and bilateral STN-DBS and 12 age-matched healthy controls. Participants completed the task twice, and the patients completed it once with STN-DBS on and once with STN-DBS off, with order counterbalanced. We found that STN stimulation was associated with significantly faster reaction times but more errors under speed instructions. Application of the drift diffusion model showed that stimulation resulted in lower response thresholds when acting under speed pressure. These findings support the involvement of the STN in the modulation of speed–accuracy trade-offs and establish for the first time that speed pressure alone, even in the absence of conflict, can result in STN stimulation inducing impulsive action in PD.

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.

Categorical evidence, confidence, and urgency during probabilistic categorization

We used a temporally extended categorization task to investigate the neural substrates underlying our ability to integrate information over time and across multiple stimulus features. Using model-based fMRI, we tracked the temporal evolution of two important variables as participants deliberated about impending choices: (1) categorical evidence, and (2) confidence (the total amount of evidence provided by the stimuli, irrespective of the particular category favored). Importantly, in each model, we also included a covariate that allowed us to differentiate signals related to information accumulation from other, evidence-independent functions that increased monotonically with time (such as urgency or cognitive load). We found that somatomotor regions tracked the temporal evolution of categorical evidence, while regions in both medial and lateral prefrontal cortex, inferior parietal cortex, and the striatum tracked decision confidence. As both theory and experimental work suggest that patterns of activity thought to be related to information-accumulation may reflect, in whole or in part, an interaction between sensory evidence and urgency, we additionally investigated whether urgency might modulate the slopes of the two evidence-dependent functions. We found that the slopes of both functions were likely modulated by urgency such that the difference between the high and low evidence states increased as the response deadline loomed.

Balloons and bavoons versus spikes and shikes: ERPs reveal shared neural processes for shape-sound-meaning congruence in words, and shape-sound congruence in pseudowords

There is something about the sound of a pseudoword like takete that goes better with a spiky, than a curvy shape (Köhler, 1929:1947). Yet despite decades of research into sound symbolism, the role of this effect on real words in the lexicons of natural languages remains controversial. We report one behavioural and one ERP study investigating whether sound symbolism is active during normal language processing for real words in a speaker's native language, in the same way as for novel word forms. The results indicate that sound-symbolic congruence has a number of influences on natural language processing: Written forms presented in a congruent visual context generate more errors during lexical access, as well as a chain of differences in the ERP. These effects have a very early onset (40-80 ms, 100-160 ms, 280-320 ms) and are later overshadowed by familiar types of semantic processing, indicating that sound symbolism represents an early sensory-co-activation effect.

Neural dynamics implement a flexible decision bound with a fixed firing rate for choice: a model-based hypothesis

Decisions are faster and less accurate when conditions favor speed, and are slower and more accurate when they favor accuracy. This speed-accuracy trade-off (SAT) can be explained by the principles of bounded integration, where noisy evidence is integrated until it reaches a bound. Higher bounds reduce the impact of noise by increasing integration times, supporting higher accuracy (vice versa for speed). These computations are hypothesized to be implemented by feedback inhibition between neural populations selective for the decision alternatives, each of which corresponds to an attractor in the space of network states. Since decision-correlated neural activity typically reaches a fixed rate at the time of commitment to a choice, it has been hypothesized that the neural implementation of the bound is fixed, and that the SAT is supported by a common input to the populations integrating evidence. According to this hypothesis, a stronger common input reduces the difference between a baseline firing rate and a threshold rate for enacting a choice. In simulations of a two-choice decision task, we use a reduced version of a biophysically-based network model (Wong and Wang, 2006) to show that a common input can control the SAT, but that changes to the threshold-baseline difference are epiphenomenal. Rather, the SAT is controlled by changes to network dynamics. A stronger common input decreases the model's effective time constant of integration and changes the shape of the attractor landscape, so the initial state is in a more error-prone position. Thus, a stronger common input reduces decision time and lowers accuracy. The change in dynamics also renders firing rates higher under speed conditions at the time that an ideal observer can make a decision from network activity. The difference between this rate and the baseline rate is actually greater under speed conditions than accuracy conditions, suggesting that the bound is not implemented by firing rates per se.