Response-stop decision-making and the NO-GO potential latency in a GO/NO-GO task

Modeling Response Times in the Go/No-Go Discrimination Task

The work presented here uses a simple stochastic model as a cognitive psychometric tool for analyzing response time data in the Go/No-Go Discrimination task with motivationally distinct conditions. The parameters of the model inform us of underlying cognitive mechanisms because they have an established psychological meaning and allow us to quantify a subjects ability and response caution. Using...

The Go/no-go Association Task

Theory i s constrained by the quality and versatility of measurement tools. As such, the development of techniques for measurement is critical to the successful development of theory. This paper presents a technique -the GoINo-go Association Task (GNAT) that joins a family of existing techniques for measuring implicit social cognition generally, with a focus on attitude (evaluation). To expand ...

Automatic and controlled response inhibition: associative learning in the go/no-go and stop-signal paradigms.

In 5 experiments, the authors examined the development of automatic response inhibition in the go/no-go paradigm and a modified version of the stop-signal paradigm. They hypothesized that automatic response inhibition may develop over practice when stimuli are consistently associated with stopping. All 5 experiments consisted of a training phase and a test phase in which the stimulus mapping wa...

Is the go/no-go lexical decision task an alternative to the yes/no lexical decision task?

In the go/no-go lexical decision task (LDT), participants are instructed to respond as quickly as they can when a word is presented and not to respond if a nonword is presented. By minimizing part of the response selection process in the experimental task, the impact of response decision time on the obtained lexical decision time is probably reduced relative to the standard yes/no LDT (Gordon, ...

Decision Modeling Individual Differences in the Go/No-Go Task With a Diffusion Model