Dot Motion Task Research Articles

Population Representation of the Confidence in a Decision in the Lateral Intraparietal Area of the Macaque.

Confidence in a decision is the belief, prior to feedback, that one's choice is correct. In the brain, many decisions are implemented as a race between competing evidence-accumulation processes. We ask whether the neurons that represent evidence accumulation also carry information about whether the choice is correct (i.e., confidence). Monkeys performed a reaction time version of the random dot motion task. Neuropixels probes were used to record from neurons in the lateral intraparietal (LIP) area. LIP neurons with response fields that overlap the choice-target contralateral to the recording site (Tin neurons) represent the accumulation of evidence in favor of contralateral target selection. We demonstrate that shortly before a contralateral choice is reported, the population of Tin neurons contains information about the accuracy of the choice (i.e., whether the choice is correct or incorrect). This finding is unexpected because, on average, Tin neurons exhibit a level of activity before the report that is independent of reaction time and evidence strength-both strong predictors of accuracy. This apparent contradiction is resolved by examining the variability in neuronal responses across the population of Tin neurons. While on average, Tin neurons exhibit a stereotyped level of activity before a contralateral choice, many neurons depart from this average in a consistent manner. From these neurons, the accuracy of the choice can be predicted using a simple logistic decoder. The accuracy of the choice predicted from neural activity reproduces the hallmarks of confidence identified in human behavioral experiments. Therefore, neurons that represent evidence accumulation can also inform the monkey's confidence.

Clinically established early Parkinson's disease patients do not show impaired use of priors in conditions of perceptual uncertainty

The ability to use past learned experiences to guide decisions is an important component of adaptive behavior, especially when decision-making is performed under time pressure or when perceptual information is unreliable. Previous studies using visual discrimination tasks have shown that this prior-informed decision-making ability is impaired in Parkinson's disease (PD), but the mechanisms underlying this deficit and the precise impact of dopaminergic denervation within cortico-basal circuits remain unclear. To shed light on this problem, we evaluated prior-informed decision-making under various conditions of perceptual uncertainty in a sample of 13 clinically established early PD patients, and compared behavioral performance with healthy control (HC) subjects matched in age, sex and education. PD patients and HC subjects performed a random dot motion task in which they had to decide the net direction (leftward vs. rightward) of a field of moving dots and communicate their choices through manual button presses. We manipulated prior knowledge by modulating the probability of occurrence of leftward vs. rightward motion stimuli between blocks of trials, and by explicitly giving these probabilities to subjects at the beginning of each block. We further manipulated stimulus discriminability by varying the proportion of dots moving coherently in the signal direction and speed-accuracy instructions. PD patients used choice probabilities to guide perceptual decisions in both speed and accuracy conditions, and their performance did not significantly differ from that of HC subjects. An additional analysis of the data with the diffusion decision model confirmed this conclusion. These results suggest that the impaired use of priors during visual discrimination observed at more advanced stages of PD is independent of dopaminergic denervation, though additional studies with larger sample sizes are needed to more firmly establish this conclusion.

Adaptive P300-Based Brain-Computer Interface for Attention Training: Protocol for a Randomized Controlled Trial.

The number of people with cognitive deficits and diseases, such as stroke, dementia, or attention-deficit/hyperactivity disorder, is rising due to an aging, or in the case of attention-deficit/hyperactivity disorder, a growing population. Neurofeedback training using brain-computer interfaces is emerging as a means of easy-to-use and noninvasive cognitive training and rehabilitation. A novel application of neurofeedback training using a P300-based brain-computer interface has previously shown potential to improve attention in healthy adults. This study aims to accelerate attention training using iterative learning control to optimize the task difficulty in an adaptive P300 speller task. Furthermore, we hope to replicate the results of a previous study using a P300 speller for attention training, as a benchmark comparison. In addition, the effectiveness of personalizing the task difficulty during training will be compared to a nonpersonalized task difficulty adaptation. In this single-blind, parallel, 3-arm randomized controlled trial, 45 healthy adults will be recruited and randomly assigned to the experimental group or 1 of 2 control groups. This study involves a single training session, where participants receive neurofeedback training through a P300 speller task. During this training, the task's difficulty is progressively increased, which makes it more difficult for the participants to maintain their performance. This encourages the participants to improve their focus. Task difficulty is either adapted based on the participants' performance (in the experimental group and control group 1) or chosen randomly (in control group 2). Changes in brain patterns before and after training will be analyzed to study the effectiveness of the different approaches. Participants will complete a random dot motion task before and after the training so that any transfer effects of the training to other cognitive tasks can be evaluated. Questionnaires will be used to estimate the participants' fatigue and compare the perceived workload of the training between groups. This study has been approved by the Maynooth University Ethics Committee (BSRESC-2022-2474456) and is registered on ClinicalTrials.gov (NCT05576649). Participant recruitment and data collection began in October 2022, and we expect to publish the results in 2023. This study aims to accelerate attention training using iterative learning control in an adaptive P300 speller task, making it a more attractive training option for individuals with cognitive deficits due to its ease of use and speed. The successful replication of the results from the previous study, which used a P300 speller for attention training, would provide further evidence to support the effectiveness of this training tool. ClinicalTrials.gov NCT05576649; https://clinicaltrials.gov/ct2/show/NCT05576649. DERR1-10.2196/46135.

Enhanced Dorsal Attention Network to Salience Network Interaction in Video Gamers During Sensorimotor Decision-Making Tasks.

Introduction: Video game playing is most often a perceptually and cognitively engaging activity. Players enter into sensory-rich competitive environments, which require them to go from trivial tasks to making active decisions repeatedly and could lend themselves to improve sensorimotor decision-making capabilities. Since video game playing requires moment-to-moment switching of attention from one aspect of sensory information and task to another, enhanced attention control and attention-switching mechanism in the brain can be thought as the neural basis for such improvements. Previous studies have suggested that attention switching is mediated by the salience network (SN). However, how SN interacts with the dorsal attention network (DAN) in active decision-making tasks and whether video game playing modulates these networks remain to be investigated. Methods: Using a modified version of the left-right moving dot motion task in a functional magnetic resonance imaging experiment, we examined the decision response times (dRTs) and functional interactions within and between SN and DAN for video game players (VGPs) and nonvideo game players (NVGPs). Results: We found that VGPs had lower response times for all task conditions and higher decision accuracy for a medium speed setting of moving dots. Associated with this improved task performance in VGPs compared with NVGPs was an increase in DAN to SN connectivity. This SN-DAN connectivity was negatively correlated with dRT. Discussion: These results suggest that enhanced influence of DAN over SN is the brain basis for improved sensorimotor decision-making performance as a result of engaging long term in cognitively challenging and attention-demanding activities such as video game playing. Impact statement Being able to flexibly direct attention is a key factor in sensorimotor decision-making. Video game playing, an attentionally and cognitively engaging activity, can have a beneficial effect on attention and decision-making. Through this study, we examined whether video game players (VGPs) have improved decision-making skills and investigated the brain basis for improvements in a functional magnetic resonance imaging experiment. Brain connectivity from dorsal attention network regions to salience network regions was higher in VGPs and negatively correlated with decision response time for both groups. These results suggest that video game playing can enhance the top-down interaction to improve sensorimotor decision-making.

Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost.

Finding the right amount of deliberation, between insufficient and excessive, is a hard decision making problem that depends on the value we place on our time. Average-reward, putatively encoded by tonic dopamine, serves in existing reinforcement learning theory as the opportunity cost of time, including deliberation time. Importantly, this cost can itself vary with the environmental context and is not trivial to estimate. Here, we propose how the opportunity cost of deliberation can be estimated adaptively on multiple timescales to account for non-stationary contextual factors. We use it in a simple decision-making heuristic based on average-reward reinforcement learning (AR-RL) that we call Performance-Gated Deliberation (PGD). We propose PGD as a strategy used by animals wherein deliberation cost is implemented directly as urgency, a previously characterized neural signal effectively controlling the speed of the decision-making process. We show PGD outperforms AR-RL solutions in explaining behaviour and urgency of non-human primates in a context-varying random walk prediction task and is consistent with relative performance and urgency in a context-varying random dot motion task. We make readily testable predictions for both neural activity and behaviour.

An integrated theory of deciding and acting.

This article presents a theory in which motor execution in perceptual decision-making tasks is determined by the same evolving decision variable that drives response time. The theory builds upon recent insights from the neuroscience of decision-making and motor control. It is formalized as an extension of Ratcliff's diffusion model, and assumes that two thresholds operate on the evidence accumulation decision variable. The first threshold, referred to as electromyographic (EMG) threshold, marks the onset of electrical activity in the response-relevant muscle and the beginning of force production. The second threshold corresponds to the response. The theory makes several benchmark predictions. Notably, the mean duration of motor execution, as quantified by the mean latency between EMG onset and the response, should depend on the rate of evidence accumulation, and should thus increase as the perceptual difficulty of the task increases. We tested these predictions in a paradigmatic perceptual decision-making task, the random dot motion task, and recorded the EMG activity of response-relevant muscles. The behavioral and EMG data provide very strong evidence for each prediction. A final quantitative evaluation of the model showed good fits to these data. The theory resolves conflicting findings in the fields of mathematical psychology, motor control, and decision neurosciences. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A neural index of inefficient evidence accumulation in dyslexia underlying slow perceptual decision making

Visual processing deficits have been widely reported in developmental dyslexia however the locus of cognitive dysfunction remains unclear. Here, we examined the neural correlates of perceptual decision-making using a dot-motion task and electroencephalography (EEG) and investigated whether presenting deficits were unique to children with dyslexia or if they were also evident in other, typically developing children with equally immature reading systems. Sixty-eight children participated: 32 with dyslexia (DD; 16 females); 21 age-matched controls (AM; 11 females) and 15 reading-matched controls (RM; 9 females). All participants completed a bilaterally presented random-dot-motion task while EEG was recorded. Neural signatures of low level sensory processing (steady state visual evoked potentials; SSVEPs), pre-target attentional bias (posterior α power), attentional orienting (N2), evidence accumulation (centro-parietal positive decision signal; CPP) and execution of a motor response (β) were obtained to dissect the temporal sequence of perceptual decision-making. Reading profile provided a score of relative lexical and sublexical skills for each participant. Although all groups performed comparably in terms of task accuracy and false alarm rate, the DD group were slower and demonstrated an earlier peak latency, reduced slope and lower amplitude of the CPP compared with both AM and RM controls. Reading profile was found to moderate the relationship between word reading ability, reaction time as well as CPP indices showing that lexical dyslexics responded more slowly and had a shallower slope, reduced amplitude and earlier latency of CPP waveforms than sublexical dyslexics. These findings suggest that children with dyslexia, particularly those with relatively poorer lexical abilities, have a reduced rate and peak of evidence accumulation as denoted by CPP markers yet remain slow in their overt response. This is in keeping with hypotheses that children with dyslexia have impairment in effectively sampling and processing evidence about visual motion stimuli.

"They don't Know Better than I do": People Prefer Seeing for Themselves Over Using the Wisdom of Crowds in Perceptual Decision Making.

Establishing the way people decide to use or avoid information when making a decision is of great theoretical and applied interest. In particular, the “big data revolution” enables decision-makers to harness the wisdom of crowds (WoC) toward reaching better decisions. The WoC is a well-documented phenomenon that highlights the potential superiority of collective wisdom over that of an individual. However, individuals may fail to utilize the power of collective wisdom as a means for optimizing decision outcomes. Using a random dot motion task, the present study examined situations in which decision-makers must choose between relying on their personal information or relying on the WoC in their decision. Although the latter was always the reward-maximizing choice, a substantial part of the participants chose to rely on their own observation and also advised others to do so. This choice tendency was associated with higher confidence, but not with better task performance, and hence reflects overconfidence. Acknowledging and understanding this decision bias may help mitigating it in applied settings.

The Discovery and Interpretation of Evidence Accumulation Stages

To improve the understanding of cognitive processing stages, we combined two prominent traditions in cognitive science: evidence accumulation models and stage discovery methods. While evidence accumulation models have been applied to a wide variety of tasks, they are limited to tasks in which decision-making effects can be attributed to a single processing stage. Here, we propose a new method that first uses machine learning to discover processing stages in EEG data and then applies evidence accumulation models to characterize the duration effects in the identified stages. To evaluate this method, we applied it to a previously published associative recognition task (Application 1) and a previously published random dot motion task with a speed-accuracy trade-off manipulation (Application 2). In both applications, the evidence accumulation models accounted better for the data when we first applied the stage-discovery method, and the resulting parameter estimates where generally in line with psychological theories. In addition, in Application 1 the results shed new light on target-foil effects in associative recognition, while in Application 2 the stage discovery method identified an additional stage in the accuracy-focused condition — challenging standard evidence accumulation accounts. We conclude that the new framework provides a powerful new tool to investigate processing stages.

Causal evidence for dissociable roles of the prefrontal and superior medial frontal cortices in decision strategies.

The speed-accuracy trade-off (SAT) is arguably the most robust finding in cognitive psychology. This simple and intuitive effect (the faster subjects respond, the more likely they are to make an error) has been the subject of extensive empirical and modeling work to ascertain the underlying latent process(es). One such process is response caution-the amount of evidence to be acquired before a decision is reached-with debate regarding the involvement of another latent variable, the rate of evidence accumulation. Neuroimaging has implicated two frontal regions as neural substrates of the SAT: the posterior lateral prefrontal cortex and the pre-supplementary motor area (preSMA; part of the superior medial frontal cortex; SMFC). However, there is no causal evidence for these regions' involvement in the SAT, nor is it clear what role each plays in the underlying processes. In a double-blind, preregistered study, we applied cathodal transcranial direct current stimulation (offline) to the prefrontal and SMFC. The SAT was measured using a dot-motion task, with differing response instructions (focus on accuracy, speed, or both). The linear ballistic accumulator model indicated performance modulations were driven by response caution. Moreover, both target regions modulated caution but in opposing directions: Prefrontal stimulation increased, and SMFC stimulation decreased, caution. Discriminability (difference between correct and error evidence accumulation rates) was predominantly affected by stimulation targeting the SMFC and did not vary with response instructions. Overall, the findings indicate that while both the SMFC and the prefrontal cortex are causally involved in the SAT, they play distinct roles in this phenomenon. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Exploring the Moderation Effect of Educational Stage on Visual Magnocellular Functioning Linked to Reading: A Study in French Primary School Children.

Many studies have investigated the visual magnocellular system functioning in dyslexia. However, very little is known on the relationship between the visual magnocellular system functioning and reading abilities in typical developing readers. In this study, we aimed at studying this relationship and more specifically the moderation effect of educational stage on this link. We thus tested 82 French typical developing readers (40 beginning readers—Grade 1 and 42 advanced readers—Grade 5) with reading tests and a coherent dot motion task measuring the visual magnocellular functioning. Results indicate positive correlations between visual magnocellular functioning and reading for beginning readers but not for advanced readers. Moreover, moderation analyses confirm that reading proficiency moderates the relationship between magnocellular system functioning and reading outcomes. We concluded that the relationship between visual magnocellular pathway functioning and reading abilities in typical developing readers could depend on reading proficiency.

Validating a dimension of doubt in decision-making: A proposed endophenotype for obsessive-compulsive disorder.

Doubt is subjective uncertainty about one’s perceptions and recall. It can impair decision-making and is a prominent feature of obsessive-compulsive disorder (OCD). We propose that evaluation of doubt during decision-making provides a useful endophenotype with which to study the underlying pathophysiology of OCD and potentially other psychopathologies. For the current study, we developed a new instrument, the Doubt Questionnaire, to clinically assess doubt. The random dot motion task was used to measure reaction time and subjective certainty, at varying levels of perceptual difficulty, in individuals who scored high and low on doubt, and in individuals with and without OCD. We found that doubt scores were significantly higher in OCD cases than controls. Drift diffusion modeling revealed that high doubt scores predicted slower evidence accumulation than did low doubt scores; and OCD diagnosis lower than controls. At higher levels of dot coherence, OCD participants exhibited significantly slower drift rates than did controls (q<0.05 for 30%, and 45% coherence; q<0.01 for 70% coherence). In addition, at higher levels of coherence, high doubt subjects exhibited even slower drift rates and reaction times than low doubt subjects (q<0.01 for 70% coherence). Moreover, under high coherence conditions, individuals with high doubt scores reported lower certainty in their decisions than did those with low doubt scores. We conclude that the Doubt Questionnaire is a useful instrument for measuring doubt. Compared to those with low doubt, those with high doubt accumulate evidence more slowly and report lower certainty when making decisions under conditions of low uncertainty. High doubt may affect the decision-making process in individuals with OCD. The dimensional doubt measure is a useful endophenotype for OCD research and could enable computationally rigorous and neurally valid understanding of decision-making and its pathological expression in OCD and other disorders.

Confidence Representation of Perceptual Decision by EEG and Eye Data in a Random Dot Motion Task

The Confidence of a decision could be considered as the internal estimate of decision accuracy. This variable has been studied extensively by different types of recording data such as behavioral, electroencephalography (EEG), eye and electrophysiology data. Although the value of the reported confidence is considered as one of the most important parameters in decision making, the confidence reporting phase might be considered as a restrictive element in investigating the decision process. Thus, decision confidence should be extracted by means of other provided types of information. Here, we proposed eight confidence related properties in EEG and eye data which are significantly descriptive of the defined confidence levels in a random dot motion (RDM) task. As a matter of fact, our proposed EEG and eye data properties are capable of recognizing more than nine distinct levels of confidence. Among our proposed features, the latency of the pupil maximum diameter through the stimulus presentation was established to be the most associated one to the confidence levels. Through the time-dependent analysis of these features, we recognized the time interval of 500–600 ms after the stimulus onset as an important time in correlating features to the confidence levels.

Some task demands induce collapsing bounds: Evidence from a behavioral analysis.

Traditional models of choice-response time assume that sensory evidence accumulates for choice alternatives until a threshold amount of evidence has been obtained. Although some researchers have characterized the threshold as varying randomly from trial to trial, these investigations have all assumed that the threshold remains fixed across time within a trial. Despite decades of successful applications of these models to a variety of experimental manipulations, the time-invariance assumption has recently been called into question, and a time-variant alternative implementing collapsing decision thresholds has been proposed instead. Here, we investigated the fidelity of the collapsing threshold assumption by assessing relative model fit to data from a highly constrained experimental design that coupled a within-subject mixture of two classic response time paradigms-interrogation and free response-within a random dot motion (RDM) task. Overall, we identified strong evidence in favor of collapsing decision thresholds, suggesting that subjects may adopt a dynamic decision policy due to task characteristics, specifically to account for the mixture of response time paradigms and motion strengths across trials in the mixed response signal task. We conclude that time-variant mechanisms may serve as a viable explanation for the strategy used by human subjects in our task.

The modulatory role of pre-SMA in speed-accuracy tradeoff: A bi-directional TMS study

Many perceptual decisions are inevitably subject to the tradeoff between speed and accuracy of choices (SAT). Sequential sampling models attribute this ubiquitous relation to random noise in the sensory evidence accumulation process, and assume that SAT is adaptively modulated by altering the decision thresholds at which the level of integrated evidence should reach for making a choice. Although, neuroimaging studies have shown a relationship between right presupplementary motor area (pre-SMA) activity and threshold setting, only a limited number of brain stimulation studies aimed at establishing the causal link, results of which were inconsistent. Additionally, these studies were limited in scope as they only examined the effect of pre-SMA activity unidirectionally through experimentally inhibiting the neural activity in this region. The current study aims to investigate the predictions of the striatal theory of SAT by experimentally assessing the modulatory effect of right pre-SMA on threshold setting bi-directionally. To this end, we applied both offline inhibition and excitation to the right pre-SMA utilizing transcranial magnetic stimulation in a within-subjects design and tested participants on a Random Dot Motion Task. Decision thresholds were estimated using the Hierarchical Drift Diffusion Model. Findings of our planned comparisons showed that right pre-SMA inhibition leads to significantly higher, whereas right pre-SMA excitation leads to significantly lower thresholds without showing any effects on the evidence integration process itself.

Decisions Made with Less Evidence Involve Higher Levels of Corticosubthalamic Nucleus Theta Band Synchrony.

The switch between automatic action selection and more controlled forms of decision-making is a dynamic process thought to involve both cortical and subcortical structures. During sensory conflict, medial pFC oscillations in the theta band (<8 Hz) drive those of the subthalamic nucleus (STN), and this is thought to increase the threshold of evidence needed for one competing response to be selected over another. Here, we were interested in testing whether STN activity is also altered by the rate at which evidence is presented during a congruent dot motion task absent of any explicit sensory conflict. By having a series of randomly moving dots gradually transform to congruent motion at three different rates (slow, medium, fast), we were able to show that a slower rate increased the time it took participants to make a response but did not alter the total amount of evidence that was integrated before the response. Notably, this resulted in a decision being made with a lower amount of instantaneous evidence during the slow and medium trials. Consistent with the idea that medial pFC–STN activity is involved in executing cognitive control, the higher levels of ambiguity during these trials were associated with increased theta band synchrony between the cortex and the STN, with the cortical oscillations Granger-causal to those of the STN. These results further confirm the involvement of the STN in decision-making and suggest that the disruption of this network may underlie some of the unwanted cognitive deficits associated with STN deep brain stimulation.

TOO MUCH DELIBERATION? CAUTIOUS DECISION-MAKING IN OCD

abstract Introduction Compulsive behaviours are typical symptoms of Obsessive-Compulsive Disorder (OCD) which may reflect difficulties to commit to ultimate decisions and may be conceptualized as a means to accumulate sufficient evidence prior to a decision. Here we investigate the process of evidence accumulation in OCD in perceptual discrimination, hypothesizing greater evidence accumulation in OCD patients. Methods Twenty-eight OCD patients (16 F/12 M) and 35 healthy control (20 F/15 M) subjects were tested with a low-level visual perceptual task (random dot motion task), whereby different coherent levels for motion were defined to measure high and low uncertainty along with two response conflict tasks as control tasks (Flanker task and reinforcement learning conflict task). Regression analysis across all coherence levels (which accounted for visual detection threshold) and hierarchical drift diffusion modeling (HDDM) [1] were used to characterize response strategies between patients with OCD and healthy controls in the random dot motion task. Results Behavioural and computational modelling approaches show that patients required more evidence under high uncertainty perceptual contexts, as indexed by longer response time intercepts and higher decision boundaries. HDDM, which defines a decision when accumulated noisy evidence reaches a criterion level (a decision boundary) [2] , further showed slower drift rate towards the decision boundary reflecting poorer quality of evidence entering the decision process in patients under low uncertainty. With incentives to emphasize speed, OCD patients lost the previous effect of uncertainty on reaction time and reversed the difference in decision boundaries, accumulating less evidence in low uncertainty trials compared to healthy volunteers, without compromising accuracy. There were no significant differences between groups in the confidence ratings and in reaction time after receiving positive or negative feedback in the random dots task. There were also no significant differences between groups on accuracy and reaction time measured by the control tasks. Our findings in the perceptual task were unrelated to high-level visual perceptual deficits and response conflict. Conclusions This study extends the literature of evidence gathering in OCD from probabilistic to perceptual decisions. We provide evidence for impaired decision-formation processes in OCD, with a differential influence of high and low uncertainty contexts on evidence accumulation (decision threshold) and on the quality of evidence gathered (drift rates). We further emphasize that OCD patients are sensitive to monetary incentives in heightening speed in the speed-accuracy tradeoff, improving evidence accumulation and shifting away from pathological internal monitoring. Finally, our lack of sensitivity to external feedback in OCD subjects highlights the differential role of implicit cost and external feedback in decision formation in OCD. These findings may have relevance for therapeutic approaches.

CAUTIOUS DECISION MAKING IN OBSESSIVECOMPULSIVE DISORDER: THE ROLE OF PERCEPTUAL UNCERTAINTY AND IMPLICIT INCENTIVES

ObjectiveThe compulsive behaviour underlying Obsessive-Compulsive Disorder (OCD) may be related to abnormalities in decision-making. The inability to commit to ultimate decisions, e.g. patients unable to decide whether their hands are...

Long-Term Safety of Repeated Blood-Brain Barrier Opening via Focused Ultrasound with Microbubbles in Non-Human Primates Performing a Cognitive Task.

Focused Ultrasound (FUS) coupled with intravenous administration of microbubbles (MB) is a non-invasive technique that has been shown to reliably open (increase the permeability of) the blood-brain barrier (BBB) in multiple in vivo models including non-human primates (NHP). This procedure has shown promise for clinical and basic science applications, yet the safety and potential neurological effects of long term application in NHP requires further investigation under parameters shown to be efficacious in that species (500kHz, 200–400 kPa, 4–5μm MB, 2 minute sonication). In this study, we repeatedly opened the BBB in the caudate and putamen regions of the basal ganglia of 4 NHP using FUS with systemically-administered MB over 4–20 months. We assessed the safety of the FUS with MB procedure using MRI to detect edema or hemorrhaging in the brain. Contrast enhanced T1-weighted MRI sequences showed a 98% success rate for openings in the targeted regions. T2-weighted and SWI sequences indicated a lack edema in the majority of the cases. We investigated potential neurological effects of the FUS with MB procedure through quantitative cognitive testing of’ visual, cognitive, motivational, and motor function using a random dot motion task with reward magnitude bias presented on a touchpanel display. Reaction times during the task significantly increased on the day of the FUS with MB procedure. This increase returned to baseline within 4–5 days after the procedure. Visual motion discrimination thresholds were unaffected. Our results indicate FUS with MB can be a safe method for repeated opening of the BBB at the basal ganglia in NHP for up to 20 months without any long-term negative physiological or neurological effects with the parameters used.

Informing cognitive abstractions through neuroimaging: the neural drift diffusion model.

Trial-to-trial fluctuations in an observer's state of mind have a direct influence on their behavior. However, characterizing an observer's state of mind is difficult to do with behavioral data alone, particularly on a single-trial basis. In this article, we extend a recently developed hierarchical Bayesian framework for integrating neurophysiological information into cognitive models. In so doing, we develop a novel extension of the well-studied drift diffusion model (DDM) that uses single-trial brain activity patterns to inform the behavioral model parameters. We first show through simulation how the model outperforms the traditional DDM in a prediction task with sparse data. We then fit the model to experimental data consisting of a speed-accuracy manipulation on a random dot motion task. We use our cognitive modeling approach to show how prestimulus brain activity can be used to simultaneously predict response accuracy and response time. We use our model to provide an explanation for how activity in a brain region affects the dynamics of the underlying decision process through mechanisms assumed by the model. Finally, we show that our model performs better than the traditional DDM through a cross-validation test. By combining accuracy, response time, and the blood oxygen level-dependent response into a unified model, the link between cognitive abstraction and neuroimaging can be better understood.