Responsive deep brain stimulation guided by ventral striatal electrophysiology of obsession durably ameliorates compulsion.

Treatment-resistant obsessive-compulsive disorder (OCD) occurs in approximately one-third of OCD patients. Obsessions may fluctuate over time but often occur or worsen in the presence of internal (emotional state and thoughts) and external (visual and tactile) triggering stimuli. Obsessive thoughts and related compulsive urges fluctuate (are episodic) and so may respond well to a time-locked brain stimulation strategy sensitive and responsive to these symptom fluctuations. Early evidence suggests that neural activity can be captured from ventral striatal regions implicated in OCD to guide such a closed-loop approach. Here, we report on a first-in-human application of responsive deep brain stimulation (rDBS) of the ventral striatum for a treatment-refractory OCD individual who also had comorbid epilepsy. Self-reported obsessive symptoms and provoked OCD-related distress correlated with ventral striatal electrophysiology. rDBS detected the time-domain area-based feature from invasive electroencephalography low-frequency oscillatory power fluctuations that triggered bursts of stimulation to ameliorate OCD symptoms in a closed-loop fashion. rDBS provided rapid, robust, and durable improvement in obsessions and compulsions. These results provide proof of concept for a personalized, physiologically guided DBS strategy for OCD.

Accumbens connectivity during deep-brain stimulation differentiates loss of control from physiologic behavioral states.

BACKGROUND: Loss of control (LOC) eating, the subjective sense that one cannot control what or how much one eats, characterizes binge-eating behaviors pervasive in obesity and related eating disorders. Closed-loop deep-brain stimulation (DBS) for binge eating should predict LOC and trigger an appropriately timed intervention. OBJECTIVE/HYPOTHESIS: This study aimed to identify a sensitive and specific biomarker to detect LOC onset for DBS. We hypothesized that changes in phase-locking value (PLV) predict the onset of LOC-associated cravings and distinguish them from potential confounding states. METHODS: Using DBS data recorded from the nucleus accumbens (NAc) of two patients with binge eating disorder (BED) and severe obesity, we compared PLV between inter- and intra-hemispheric NAc subregions for three behavioral conditions: craving (associated with LOC eating), hunger (not associated with LOC), and sleep. RESULTS: In both patients, PLV in the high gamma frequency band was significantly higher for craving compared to sleep and significantly higher for hunger compared to craving. Maximum likelihood classifiers achieved accuracies above 88% when differentiating between the three conditions. CONCLUSIONS: High-frequency inter- and intra-hemispheric PLV in the NAc is a promising biomarker for closed-loop DBS that differentiates LOC-associated cravings from physiologic states such as hunger and sleep. Future trials should assess PLV as a LOC biomarker across a larger cohort and a wider patient population transdiagnostically.

Neurocognitive markers of passive suicidal ideation in late-life depression.

OBJECTIVES: (1) To delineate whether cognitive flexibility and inhibitory ability are neurocognitive markers of passive suicidal ideation (PSI), an early stage of suicide risk in depression and (2) to determine whether PSI is associated with volumetric differences in regions of the prefrontal cortex (PFC) in middle-aged and older adults with depression. DESIGN: Cross-sectional study. SETTING: University medical school. PARTICIPANTS: Forty community-dwelling middle-aged and older adults with depression from a larger study of depression and anxiety (NIMH R01 MH091342-05 PI: O'Hara). MEASUREMENTS: Psychiatric measures were assessed for the presence of a DSM-5 depressive disorder and PSI. A neurocognitive battery assessed cognitive flexibility, inhibitory ability, as well as other neurocognitive domains. RESULTS: The PSI group (n = 18) performed significantly worse on cognitive flexibility and inhibitory ability, but not on other neurocognitive tasks, compared to the group without PSI (n = 22). The group with PSI had larger left mid-frontal gyri (MFG) than the no-PSI group. There was no association between cognitive flexibility/inhibitory ability and left MFG volume. CONCLUSIONS: Findings implicate a neurocognitive signature of PSI: poorer cognitive flexibility and poor inhibitory ability not better accounted for by other domains of cognitive dysfunction and not associated with volumetric differences in the left MFG. This suggests that there are two specific but independent risk factors of PSI in middle- and older-aged adults.

Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating.

Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.

Integrated cognitive and physical fitness training enhances attention abilities in older adults.

Preserving attention abilities is of great concern to older adults who are motivated to maintain their quality of life. Both cognitive and physical fitness interventions have been utilized in intervention studies to assess maintenance and enhancement of attention abilities in seniors, and a coupling of these approaches is a compelling strategy to buttress both cognitive and physical health in a time- and resource-effective manner. With this perspective, we created a closed-loop, motion-capture video game (Body-Brain Trainer: BBT) that adapts a player's cognitive and physical demands in an integrated approach, thus creating a personalized and cohesive experience across both domains. Older adults who engaged in two months of BBT improved on both physical fitness (measures of blood pressure and balance) and attention (behavioral and neural metrics of attention on a continuous performance task) outcome measures beyond that of an expectancy matched, active, placebo control group, with maintenance of improved attention performance evidenced 1 year later. Following training, the BBT group's improvement on the attention outcome measure exceeded performance levels attained by an untrained group of 20-year olds, and showed age-equilibration of a neural signature of attention shown to decline with age: midline frontal theta power. These findings highlight the potential benefits of an integrated, cognitive-physical, closed-loop training platform as a powerful tool for both cognitive and physical enhancement in older adults.

The Role of the Dorsal-Lateral Prefrontal Cortex in Reward Sensitivity During Approach-Avoidance Conflict.

Approach-Avoidance conflict (AAC) arises from decisions with embedded positive and negative outcomes, such that approaching leads to reward and punishment and avoiding to neither. Despite its importance, the field lacks a mechanistic understanding of which regions are driving avoidance behavior during conflict. In the current task, we utilized transcranial magnetic stimulation (TMS) and drift-diffusion modeling to investigate the role of one of the most prominent regions relevant to AAC-the dorsolateral prefrontal cortex (dlPFC). The first experiment uses in-task disruption to examine the right dlPFC's (r-dlPFC) causal role in avoidance behavior. The second uses single TMS pulses to probe the excitability of the r-dlPFC, and downstream cortical activations, during avoidance behavior. Disrupting r-dlPFC during conflict decision-making reduced reward sensitivity. Further, r-dlPFC was engaged with a network of regions within the lateral and medial prefrontal, cingulate, and temporal cortices that associate with behavior during conflict. Together, these studies use TMS to demonstrate a role for the dlPFC in reward sensitivity during conflict and elucidate the r-dlPFC's network of cortical regions associated with avoidance behavior. By identifying r-dlPFC's mechanistic role in AAC behavior, contextualized within its conflict-specific downstream neural connectivity, we advance dlPFC as a potential neural target for psychiatric therapeutics.

Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions.

BACKGROUND: Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric. NEW METHODS: We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity. RESULTS: Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals. CONCLUSIONS: The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.

Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation.

BACKGROUND: Motor impairment after stroke is due not only to direct tissue loss but also to disrupted connectivity within the motor network. Mixed results from studies attempting to enhance motor recovery with Transcranial Magnetic Stimulation (TMS) highlight the need for a better understanding of both connectivity after stroke and the impact of TMS on this connectivity. This study used TMS-EEG to map the causal information flow in the motor network of healthy adult subjects and define how stroke alters these circuits. METHODS: Fourteen stroke patients and 12 controls received TMS to two sites (bilateral primary motor cortices) during two motor tasks (paretic/dominant hand movement vs. rest) while EEG measured the cortical response to TMS pulses. TMS-EEG based connectivity measurements were derived for each hemisphere and the change in connectivity (ΔC) between the two motor tasks was calculated. We analyzed if ΔC for each hemisphere differed between the stroke and control groups or across TMS sites, and whether ΔC correlated with arm function in stroke patients. RESULTS: Right hand movement increased connectivity in the left compared to the right hemisphere in controls, while hand movement did not significantly change connectivity in either hemisphere in stroke. Stroke patients with the largest increase in healthy hemisphere connectivity during paretic hand movement had the best arm function. CONCLUSIONS: TMS-EEG measurements are sensitive to movement-induced changes in brain connectivity. These measurements may characterize clinically meaningful changes in circuit dynamics after stroke, thus providing specific targets for trials of TMS in post-stroke rehabilitation.

Linked Sources of Neural Noise Contribute to Age-related Cognitive Decline.

Healthy aging is associated with a multitude of structural changes in the brain. These physical age-related changes are accompanied by increased variability in neural activity of all kinds, and this increased variability, collectively referred to as "neural noise," is argued to contribute to age-related cognitive decline. In this study, we examine the relationship between two particular types of neural noise in aging. We recorded scalp EEG from younger (20-30 years old) and older (60-70 years old) adults performing a spatial visual discrimination task. First, we used the 1/f-like exponent of the EEG power spectrum, a putative marker of neural noise, to assess baseline shifts toward a noisier state in aging. Next, we examined age-related decreases in the trial-by-trial consistency of visual stimulus processing. Finally, we examined to what extent these two age-related noise markers are related, hypothesizing that greater baseline noise would increase the variability of stimulus-evoked responses. We found that visual cortical baseline noise was higher in older adults, and the consistency of older adults' oscillatory alpha (8-12 Hz) phase responses to visual targets was also lower than that of younger adults. Crucially, older adults with the highest levels of baseline noise also had the least consistent alpha phase responses, whereas younger adults with more consistent phase responses achieved better behavioral performance. These results establish a link between tonic neural noise and stimulus-associated neural variability in aging. Moreover, they suggest that tonic age-related increases in baseline noise might diminish sensory processing and, as a result, subsequent cognitive performance.

Cortical Excitability, Synaptic Plasticity, and Cognition in Benign Epilepsy With Centrotemporal Spikes: A Pilot TMS-EMG-EEG Study.

PURPOSE: Children with benign epilepsy with centrotemporal spikes have rare seizures emerging from the motor cortex, which they outgrow in adolescence, and additionally may have language deficits of unclear etiology. We piloted the use of transcranial magnetic stimulation paired with EMG and EEG (TMS-EMG, TMS-EEG) to test the hypotheses that net cortical excitability decreases with age and that use-dependent plasticity predicts learning. METHODS: We assessed language and motor learning in 14 right-handed children with benign epilepsy with centrotemporal spikes. We quantified two TMS metrics of left motor cortex excitability: the resting motor threshold (measure of neuronal membrane excitability) and amplitude of the N100-evoked potential (an EEG measure of GABAergic tone). To test plasticity, we applied 1 Hz repetitive TMS to the motor cortex to induce long-term depression-like changes in EMG- and EEG-evoked potentials. RESULTS: Children with benign epilepsy with centrotemporal spikes tolerate TMS; no seizures were provoked. Resting motor threshold decreases with age but is elevated above maximal stimulator output for half the group. N100 amplitude decreases with age after controlling for resting motor threshold. Motor cortex plasticity correlates significantly with language learning and at a trend level with motor learning. CONCLUSIONS: Transcranial magnetic stimulation is safe and feasible for children with benign epilepsy with centrotemporal spikes, and TMS-EEG provides more reliable outcome measures than TMS-EMG in this group because many children have unmeasurably high resting motor thresholds. Net cortical excitability decreases with age, and motor cortex plasticity predicts not only motor learning but also language learning, suggesting a mechanism by which motor cortex seizures may interact with language development.

An electroencephalographic signature predicts antidepressant response in major depression.

Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n = 309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial.

Importance: Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice. Objective: To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment. Design, Setting, and Participants: In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019. Interventions: Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks. Main Outcomes and Measures: Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit. Results: Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points. Conclusions and Relevance: These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials. Trial Registration: ClinicalTrials.gov identifier: NCT01407094.

Closed-loop digital meditation improves sustained attention in young adults.

Attention is a fundamental cognitive process that is critical for essentially all aspects of higher-order cognition and real-world activities. Younger generations have deeply embraced information technology and multitasking in their personal lives, school and the workplace, creating myriad challenges to their attention. While improving sustained attention in healthy young adults would be beneficial, enhancing this ability has proven notoriously difficult in this age group. Here we show that 6 weeks of engagement with a meditation-inspired, closed-loop software program (MediTrain) delivered on mobile devices led to gains in both sustained attention and working memory in healthy young adults. These improvements were associated with positive changes in key neural signatures of attentional control (frontal theta inter-trial coherence and parietal P3b latency), as measured by electroencephalography. Our findings suggest the utility of delivering aspects of the ancient practice of focused-attention meditation in a modern, technology-based approach and its benefits on enhancing sustained attention.

ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.

Characterizing cognitive and visuomotor control in children with sensory processing dysfunction and autism spectrum disorders.

OBJECTIVE: Children with autism spectrum disorders (ASD) and sensory processing dysfunction (SPD) are reported to show difficulties involving cognitive and visuomotor control. We sought to determine whether performance on computerized, behavioral measures of cognitive control aimed at assessing selective attention, as well as visuomotor abilities differentiated children with ASD (n = 14), SPD (n = 14) and typically developing controls (TDC; n = 28). METHOD: Cognitive control differences were measured by assessing selective attention-based abilities both with and without distracting stimuli, and visuomotor differences were measured by characterizing visuomotor tracking and tracing skills. Performance in cognitive control and visuomotor domains were investigated globally as composite scores, and specifically within each task. RESULTS: Our results indicated that though the ASD group showed the most impaired selective attention performance, the SPD group had intermediate abilities-performing above the ASD group but below the TDC group. Furthermore, both the SPD and ASD groups demonstrated equally impaired visuomotor abilities relative to the TDC group. A correlational analysis between cognitive and visuomotor control suggest a relationship between these overlapping control networks. CONCLUSIONS: This study supports the importance of direct, phenotypic characterizations of control-based abilities in children with ASD and SPD to personalize characterization and treatment interventions for at-risk children. (PsycINFO Database Record

Enhancing Spatial Attention and Working Memory in Younger and Older Adults.

Daily experiences demand both focused and broad allocation of attention for us to interact efficiently with our complex environments. Many types of attention have shown age-related decline, although there is also evidence that such deficits may be remediated with cognitive training. However, spatial attention abilities have shown inconsistent age-related differences, and the extent of potential enhancement of these abilities remains unknown. Here, we assessed spatial attention in both healthy younger and older adults and trained this ability in both age groups for 5 hr over the course of 2 weeks using a custom-made, computerized mobile training application. We compared training-related gains on a spatial attention assessment and spatial working memory task to age-matched controls who engaged in expectancy-matched, active placebo computerized training. Age-related declines in spatial attention abilities were observed regardless of task difficulty. Spatial attention training led to improved focused and distributed attention abilities as well as improved spatial working memory in both younger and older participants. No such improvements were observed in either of the age-matched control groups. Note that these findings were not a function of improvements in simple response time, as basic motoric function did not change after training. Furthermore, when using change in simple response time as a covariate, all findings remained significant. These results suggest that spatial attention training can lead to enhancements in spatial working memory regardless of age.

A pilot study to determine the feasibility of enhancing cognitive abilities in children with sensory processing dysfunction.

Children with Sensory Processing Dysfunction (SPD) experience incoming information in atypical, distracting ways. Qualitative challenges with attention have been reported in these children, but such difficulties have not been quantified using either behavioral or functional neuroimaging methods. Furthermore, the efficacy of evidence-based cognitive control interventions aimed at enhancing attention in this group has not been tested. Here we present work aimed at characterizing and enhancing attentional abilities for children with SPD. A sample of 38 SPD and 25 typically developing children were tested on behavioral, neural, and parental measures of attention before and after a 4-week iPad-based at-home cognitive remediation program. At baseline, 54% of children with SPD met or exceeded criteria on a parent report measure for inattention/hyperactivity. Significant deficits involving sustained attention, selective attention and goal management were observed only in the subset of SPD children with parent-reported inattention. This subset of children also showed reduced midline frontal theta activity, an electroencephalographic measure of attention. Following the cognitive intervention, only the SPD children with inattention/hyperactivity showed both improvements in midline frontal theta activity and on a parental report of inattention. Notably, 33% of these individuals no longer met the clinical cut-off for inattention, with the parent-reported improvements persisting for 9 months. These findings support the benefit of a targeted attention intervention for a subset of children with SPD, while simultaneously highlighting the importance of having a multifaceted assessment for individuals with neurodevelopmental conditions to optimally personalize treatment.

Preparatory Encoding of the Fine Scale of Human Spatial Attention.

Our attentional focus is constantly shifting: In one moment, our attention may be intently concentrated on a specific spot, whereas in another moment we might spread our attention more broadly. Although much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is known about how we shift the aperture of attention from more narrowly to more broadly focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate-with varying degrees of certainty-approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that, with decreasing certainty regarding the precise location of the impending target, participant RTs increased whereas target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8-12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and RT nearly 1 sec later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution and how that influences behavior.

Exploring the Potential of the iPad and Xbox Kinect for Cognitive Science Research.

Many studies have validated consumer-facing hardware platforms as efficient, cost-effective, and accessible data collection instruments. However, there are few reports that have assessed the reliability of these platforms as assessment tools compared with traditional data collection platforms. Here we evaluated performance on a spatial attention paradigm obtained by our standard in-lab data collection platform, the personal computer (PC), and compared performance with that of two widely adopted, consumer technology devices: the Apple (Cupertino, CA) iPad(®) 2 and Microsoft (Redmond, WA) Xbox(®) Kinect(®). The task assessed spatial attention, a fundamental ability that we use to navigate the complex sensory input we face daily in order to effectively engage in goal-directed activities. Participants were presented with a central spatial cue indicating where on the screen a stimulus would appear. We manipulated spatial cueing such that, on a given trial, the cue presented one of four levels of information indicating the upcoming target location. Based on previous research, we hypothesized that as information of the cued spatial area decreased (i.e., larger area of possible target location) there would be a parametric decrease in performance, as revealed by slower response times and lower accuracies. Identical paradigm parameters were used for each of the three platforms, and testing was performed in a single session with a counterbalanced design. We found that performance on the Kinect and iPad showed a stronger parametric effect across the cued-information levels than that on the PC. Our results suggest that not only can the Kinect and iPad be reliably used as assessment tools to yield research-quality behavioral data, but that these platforms exploit mechanics that could be useful in building more interactive, and therefore effective, cognitive assessment and training designs. We include a discussion on the possible contributing factors to the differential effects between platforms, as well as potential confounds of the study.