---
title: "Statistical Properties of the N-Back Sequences"
output: html_notebook
---

# Problems

Statistical properties of n-back sequences bias behaviors. These bias, under specified structure, allows multiple cognitive strategies, producing heterogeneous behavior in a "gold standard" cognitive task.

# Gaps

- Unclear how to parameterize interesting variations for sequence generation
- How do we model these multiple strategies (which requires identifying which sequence variations matter) 
    - local vs. global properties, which one matters the most?
    - Local:  lumpiness, short sequence patterns -> could be exploited by “reactive”/automaticity 
    - Global:  No lures, large vocabulary -> pattern repeats implies a target


```{r libraries, message=FALSE, include=FALSE, paged.print=FALSE}
library(ggplot2)
library(tidyverse)

```

```{r datasets}
load('./data/CL2015.RData')
```