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A neural implementation of Wald's sequential probability ratio test.

ABSTRACT: Difficult decisions often require evaluation of samples of evidence acquired sequentially. A sensible strategy is to accumulate evidence, weighted by its reliability, until sufficient support is attained. An optimal statistical approach would accumulate evidence in units of logarithms of likelihood ratios (logLR) to a desired level. Studies of perceptual decisions suggest that the brain approximates an analogous procedure, but a direct test of accumulation, in units of logLR, to a threshold in units of cumulative logLR is lacking. We trained rhesus monkeys to make decisions based on a sequence of evanescent, visual cues assigned different logLR, hence different reliability. Firing rates of neurons in the lateral intraparietal area (LIP) reflected the accumulation of logLR and reached a stereotyped level before the monkeys committed to a decision. The monkeys' choices and reaction times, including their variability, were explained by LIP activity in the context of accumulation of logLR to a threshold.

SUBMITTER: Kira S

PROVIDER: S-EPMC4365451 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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A neural implementation of Wald's sequential probability ratio test.

Kira Shinichiro S Yang Tianming T Shadlen Michael N MN

Neuron 20150205 4

Difficult decisions often require evaluation of samples of evidence acquired sequentially. A sensible strategy is to accumulate evidence, weighted by its reliability, until sufficient support is attained. An optimal statistical approach would accumulate evidence in units of logarithms of likelihood ratios (logLR) to a desired level. Studies of perceptual decisions suggest that the brain approximates an analogous procedure, but a direct test of accumulation, in units of logLR, to a threshold in u ...[more]

PMID: 25661183

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Project description:Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed. Methods: Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR). Results: Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters. Conclusion: A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.

Dataset Information

A neural implementation of Wald's sequential probability ratio test.

Publications

A neural implementation of Wald's sequential probability ratio test.

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