How task format affects cognitive performance: a memory test with two species of New World monkeys

In cognitive tests, animals are often given a choice between two options and obtain a reward if they choose correctly. We investigated whether task format affects subjects' performance in a physical cognition test. In experiment 1, a two-choice memory test, 15 marmosets, Callithrix jacchus, had to remember the location of a food reward over time delays of increasing duration. We predicted that their performance would decline with increasing delay, but this was not found. One possible explanation was that the subjects were not sufficiently motivated to choose correctly when presented with only two options because in each trial they had a 50% chance of being rewarded. In experiment 2, we explored this possibility by testing eight naïve marmosets and seven squirrel monkeys, Saimiri sciureus, with both the traditional two-choice and a new nine-choice version of the memory test that increased the cost of a wrong choice. We found that task format affected the monkeys' performance. When choosing between nine options, both species performed better and their performance declined as delays became longer. Our results suggest that the two-choice format compromises the assessment of physical cognition, at least in memory tests with these New World monkeys, whereas providing more options, which decreases the probability of obtaining a reward when making a random guess, improves both performance and measurement validity of memory. Our findings suggest that two-choice tasks should be used with caution in comparisons within and across species because they are prone to motivational biases.

Using multiple GPUs to accelerate string searching for digital forensic analysis

String searching within a large corpus of data is an important component of digital forensic (DF) analysis techniques such as file carving. The continuing increase in capacity of consumer storage devices requires corresponding im-provements to the performance of string searching techniques. As string search-ing is a trivially-parallelisable problem, GPGPU approaches are a natural fit – but previous studies have found that local storage presents an insurmountable performance bottleneck. We show that this need not be the case with modern hardware, and demonstrate substantial performance improvements from the use of single and multiple GPUs when searching for strings within a typical forensic disk image.