Transfer of learning: Analysis of dose-response functions from a large-scale, online, cognitive training dataset.

Fundamental to the efficacy of cognitive training (CT) is its dose. Here we used the power and breadth afforded by a large dataset to measure precisely dose-response (D-R) functions for CT and to examine the generality of their magnitude and form. The present observational study involved 107,000 users of Lumosity, a commercial program comprising computer games designed to provide CT over the internet. In addition to training with Lumosity games, these users took an online battery of cognitive assessments (NeuroCognitive Performance Test, NCPT) on two or more occasions separated by at least 10 weeks. Changes in performance on the NCPT between the first and second assessments were examined as a function of the amount of intervening gameplay. The resulting D-R functions were obtained both for overall performance on the NCPT and performance on its eight subtests. Also examined were differences between D-R functions from demographic groups defined by age, gender, and education. Monotonically increasing D-R functions, well fit by an exponential approach to an asymptote, were found consistently for overall performance on the NCPT, performance on seven of the eight subtests, and at each level of age, education, and gender. By examining how individual parameters of the D-R functions varied across subtests and groups, it was possible to measure separately changes in the effects on NCPT performance of 1) transfer from CT and 2) direct practice due to repeated testing. The impact of both transfer and direct practice varied across subtests. In contrast, while the effects of direct practice diminished with age, those of transfer remained constant. Besides its implications for CT by older adults, this latter finding suggests that direct practice and transfer do not involve identical learning processes, with transfer being limited to learning processes that remain constant across the adult lifespan.

Modelling human behaviour in cognitive tasks with latent dynamical systems.

Response time data collected from cognitive tasks are a cornerstone of psychology and neuroscience research, yet existing models of these data either make strong assumptions about the data-generating process or are limited to modelling single trials. We introduce task-DyVA, a deep learning framework in which expressive dynamical systems are trained to reproduce sequences of response times observed in data from individual human subjects. Models fitted to a large task-switching dataset captured subject-specific behavioural differences with high temporal precision, including task-switching costs. Through perturbation experiments and analyses of the models' latent dynamics, we find support for a rational account of switch costs in terms of a stability-flexibility trade-off. Thus, our framework can be used to discover interpretable cognitive theories that explain how the brain dynamically gives rise to behaviour.

A massive dataset of the NeuroCognitive Performance Test, a web-based cognitive assessment.

We present a dataset of approximately 5.5 million subtest scores from over 750,000 adults who completed the NeuroCognitive Performance Test (NCPT; Lumos Labs, Inc.), a validated, self-administered cognitive test accessed via web browser. The dataset includes assessment scores from eight test batteries consisting of 5-11 subtests that collectively span several cognitive domains including working memory, visual attention, and abstract reasoning. In addition to the raw scores and normative data from each subtest, the dataset includes basic demographic information from each participant (age, gender, and educational background). The scale and diversity of the dataset provides an unprecedented opportunity for researchers to investigate population-level variability in cognitive abilities and their relation to demographic factors. To facilitate reuse of this dataset by other researchers, we provide a Python module that supports several common preprocessing steps.

Separable Influences of Reward on Visual Processing and Choice.

Primate vision is characterized by constant, sequential processing and selection of visual targets to fixate. Although expected reward is known to influence both processing and selection of visual targets, similarities and differences between these effects remain unclear mainly because they have been measured in separate tasks. Using a novel paradigm, we simultaneously measured the effects of reward outcomes and expected reward on target selection and sensitivity to visual motion in monkeys. Monkeys freely chose between two visual targets and received a juice reward with varying probability for eye movements made to either of them. Targets were stationary apertures of drifting gratings, causing the end points of eye movements to these targets to be systematically biased in the direction of motion. We used this motion-induced bias as a measure of sensitivity to visual motion on each trial. We then performed different analyses to explore effects of objective and subjective reward values on choice and sensitivity to visual motion to find similarities and differences between reward effects on these two processes. Specifically, we used different reinforcement learning models to fit choice behavior and estimate subjective reward values based on the integration of reward outcomes over multiple trials. Moreover, to compare the effects of subjective reward value on choice and sensitivity to motion directly, we considered correlations between each of these variables and integrated reward outcomes on a wide range of timescales. We found that, in addition to choice, sensitivity to visual motion was also influenced by subjective reward value, although the motion was irrelevant for receiving reward. Unlike choice, however, sensitivity to visual motion was not affected by objective measures of reward value. Moreover, choice was determined by the difference in subjective reward values of the two options, whereas sensitivity to motion was influenced by the sum of values. Finally, models that best predicted visual processing and choice used sets of estimated reward values based on different types of reward integration and timescales. Together, our results demonstrate separable influences of reward on visual processing and choice, and point to the presence of multiple brain circuits for the integration of reward outcomes.

Inferring latent learning factors in large-scale cognitive training data.

The flexibility to learn diverse tasks is a hallmark of human cognition. To improve our understanding of individual differences and dynamics of learning across tasks, we analyse the latent structure of learning trajectories from 36,297 individuals as they learned 51 different tasks on the Lumosity online cognitive training platform. Through a data-driven modelling approach using probabilistic dimensionality reduction, we investigate covariation across learning trajectories with few assumptions about learning curve form or relationships between tasks. Modelling results show substantial covariation across tasks, such that an entirely unobserved learning trajectory can be predicted by observing trajectories on other tasks. The latent learning factors from the model include a general ability factor that is expressed mostly at later stages of practice and additional task-specific factors that carry information capable of accounting for manually defined task features and task domains such as attention, spatial processing, language and math.

Perceptions of Brain Training: Public Expectations of Cognitive Benefits From Popular Activities.

Many popular activities are thought by the general public to improve cognitive function. Such expectations can influence how often people engage in these activities, as well as the scientific evaluation of their putative cognitive benefits, e.g., via placebo effects. Here, we gathered survey data about the public's perceptions of nine different activities commonly thought to be cognitively stimulating, including "brain-training" games. Information was collected about the degree to which participants thought each activity was beneficial for improving cognitive function and how often they engaged in each activity. The patterns of correlation between ratings reveal details about the perception of cognitive benefits and its relation to engagement. They suggest that participants varied with respect to an overarching perception of the entire set of activities, which were perceived also as divided into three clusters. Frequency of engagement and perceived cognitive benefits were positively correlated across participants for each activity considered individually. But, when the activities were compared, the magnitude of their perceived benefits was not a good predictor of their frequency of engagement (and vice versa). Though small, there were systematic demographic differences. Women were more optimistic than men about cognitive benefits. Individual participants differed in the range of their ratings of benefit across activities, and these ranges were greater for younger than older participants, suggesting that perceptions of benefit are more differentiated among the young. Besides contributing to a better understanding of public expectations of cognitive benefits, the findings of this study are relevant to the critical evaluation of such benefits. Our survey can be viewed as providing an interface between expectations held by the general public and the design of studies examining the efficacy of cognitive training. The type of information it provides could be used in the selection of activities performed by an active control group, so that control activities match the treatment intervention as closely as possible with respect to such expectations.

Computerized Cognitive Training by Healthy Older and Younger Adults: Age Comparisons of Overall Efficacy and Selective Effects on Cognition.

Among the non-pharmacological methods under development for maintaining cognitive function across the lifespan is computerized cognitive training (CCT). There has been considerable interest in using CCT to slow or remediate age-related cognitive decline, both normal and pathological. Toward these ends, it would be useful to know how the effects of CCT on cognitive function vary over the course of normal cognitive aging. Are there changes in either 1) the overall efficacy of CCT or 2) which cognitive faculties are affected? To address these two questions, we reanalyzed results from a large online study by Hardy et al. (1) of 4,715 adults between 18 and 80 that examined effects of CCT on both a neuropsychological test battery and self-reported ratings of cognition and affect in daily living. Combined across all participants, Hardy et al. found greater improvement on both types of assessment following 10 weeks of CCT with the commercial program Lumosity, as compared to practice with a control activity involving computerized crossword puzzles. The present study compared the size of these effects on the older (50-80) and younger (18-49) participants. To address the question of overall efficacy, we examined CCT effects (treatment minus control) on overall performance of the test battery and mean rating. No significant difference on either measure was found between the two age cohorts. To address the question of whether the same magnitude of overall effects on both age cohorts was due to equivalent effects on the same set of underlying cognitive functions, we examined the patterns of CCT effects across individual subtests and rated items. These patterns did not differ significantly between the two age cohorts. Our findings suggest that benefits from CCT can occur to a similar degree and in a similar way across an extended part of the adult lifespan. Moreover, the overall effects of CCT delivered over the internet were of the same small to medium size as those typically found in the lab or clinic. Besides improving access and reducing the cost of CCT for older adults, delivery over the internet makes long-term training more practicable, which could potentially yield larger benefits.

Prefrontal contributions to visual selective attention.

The faculty of attention endows us with the capacity to process important sensory information selectively while disregarding information that is potentially distracting. Much of our understanding of the neural circuitry underlying this fundamental cognitive function comes from neurophysiological studies within the visual modality. Past evidence suggests that a principal function of the prefrontal cortex (PFC) is selective attention and that this function involves the modulation of sensory signals within posterior cortices. In this review, we discuss recent progress in identifying the specific prefrontal circuits controlling visual attention and its neural correlates within the primate visual system. In addition, we examine the persisting challenge of precisely defining how behavior should be affected when attentional function is lost.

Selective attention from voluntary control of neurons in prefrontal cortex.

Animals can learn to voluntarily control neuronal activity within various brain areas through operant conditioning, but the relevance of that control to cognitive functions is unknown. We found that rhesus monkeys can control the activity of neurons within the frontal eye field (FEF), an oculomotor area of the prefrontal cortex. However, operantly driven FEF activity was primarily associated with selective visual attention, and not oculomotor preparation. Attentional effects were untrained and were observed both behaviorally and neurophysiologically. Furthermore, selective attention correlated with voluntary, but not spontaneous, fluctuations in FEF activity. Our results reveal a specific association of voluntarily driven neuronal activity with "top-down" attention and suggest a basis for the use of neurofeedback training to treat disorders of attention.

Attention governs action in the primate frontal eye field.

While the motor and attentional roles of the frontal eye field (FEF) are well documented, the relationship between them is unknown. We exploited the known influence of visual motion on the apparent positions of targets, and measured how this illusion affects saccadic eye movements during FEF microstimulation. Without microstimulation, saccades to a moving grating are biased in the direction of motion, consistent with the apparent position illusion. Here we show that microstimulation of spatially aligned FEF representations increases the influence of this illusion on saccades. Rather than simply impose a fixed-vector signal, subthreshold stimulation directed saccades away from the FEF movement field, and instead more strongly in the direction of visual motion. These results demonstrate that the attentional effects of FEF stimulation govern visually guided saccades, and suggest that the two roles of the FEF work together to select both the features of a target and the appropriate movement to foveate it.

Cell membrane array fabrication and assay technology.

BACKGROUND: Microarray technology has been used extensively over the past 10 years for assessing gene expression, and has facilitated precise genetic profiling of everything from tumors to small molecule drugs. By contrast, arraying cell membranes in a manner which preserves their ability to mediate biochemical processes has been considerably more difficult. RESULTS: In this article, we describe a novel technology for generating cell membrane microarrays for performing high throughput biology. Our robotically-arrayed supported membranes are physiologically fluid, a critical property which differentiates this technology from other previous membrane systems and makes it useful for studying cellular processes on an industrialized scale. Membrane array elements consist of a solid substrate, above which resides a fluid supported lipid bilayer containing biologically-active molecules of interest. Incorporation of transmembrane proteins into the arrayed membranes enables the study of ligand/receptor binding, as well as interactions with live intact cells. The fluidity of these molecules in the planar lipid bilayer facilitates dimerization and other higher order interactions necessary for biological signaling events. In order to demonstrate the utility of our fluid membrane array technology to ligand/receptor studies, we investigated the multivalent binding of the cholera toxin B-subunit (CTB) to the membrane ganglioside GM1. We have also displayed a number of bona fide drug targets, including bacterial endotoxin (also referred to as lipopolysaccharide (LPS)) and membrane proteins important in T cell activation. CONCLUSION: We have demonstrated the applicability of our fluid cell membrane array technology to both academic research applications and industrial drug discovery. Our technology facilitates the study of ligand/receptor interactions and cell-cell signaling, providing rich qualitative and quantitative information.

Lipid mobility and molecular binding in fluid lipid membranes.

The lateral mobility of dilute concentrations of fluorescently labeled lipids doped into supported membranes is found to change upon receptor ligand binding at the membrane surface, even when the lipid is not directly involved in the binding event. Experiments using membrane microarrays are performed that illustrate the use of lipid mobility measurements as an effectively label-free strategy of detecting binding on membrane surfaces.

Reversal of motor learning in the vestibulo-ocular reflex in the absence of visual input.

Motor learning in the vestibulo-ocular reflex (VOR) and eyeblink conditioning use similar neural circuitry, and they may use similar cellular plasticity mechanisms. Classically conditioned eyeblink responses undergo extinction after prolonged exposure to the conditioned stimulus in the absence of the unconditioned stimulus. We investigated the possibility that a process similar to extinction may reverse learned changes in the VOR. We induced a learned alteration of the VOR response in rhesus monkeys using magnifying or miniaturizing goggles, which caused head movements to be accompanied by visual image motion. After learning, head movements in the absence of visual stimulation caused a loss of the learned eye movement response. When the learned gain was low, this reversal of learning occurred only when head movements were delivered, and not when the head was held stationary in the absence of visual input, suggesting that this reversal is mediated by an active, extinction-like process.