The present study used a P300‐based Concealed Information Test (CIT) to detect individual and collaborative crimes and to explore whether or not the P300 index is effective in identifying collaborative crime members. Participants were divided into two groups to either steal a ring alone (individual group) or collaboratively with another companion participant (collaborative group) before taking the Complex Trial Protocol test that is regarded as an accurate version of the P300‐based CIT. The ERP results revealed that both groups showed significantly larger P300s to probe (the ring) than to all irrelevant stimuli (other jewelery), but the P300 amplitude difference of probe stimulus versus irrelevant stimuli in the collaborative group was significantly less than that in the individual group. For the individual diagnosis, using P300 index, the detection rate was significantly inferior for collaborative crime than individual crime, probably related to weakness of collaborative encoding. The ROC curve comparisons showed the individual guilty was effectively discriminated from the simulated‐innocent (AUC = .84) and from the collaborative guilty (AUC = .83), but the collaborative guilty was not discriminable from the simulated‐innocent (AUC = .66). These findings suggest that collaborative encoding of crime‐related information impacts the efficiency of the P300 index, and that the P300‐based CIT is not applicable when used to identify collaborative crime perpetrators.
Psychophysiology – Wiley
Published: Jan 1, 2018
Keywords: ; ; ; ;
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera