Reference no: EM131906626 , Length: word count:1000
Topic: Neuroscience/ Cognitive Psychology
Here is an overview about the idea.
Human sleep consists of cycles that last approximately 90 minutes. These cycles consist of REM (Rapid Eye Movement) sleep and 4 stages of non-REM sleep, with stages 3 and 4 being the deepest sleep known as slow-wave sleep (SWS). Most SWS sleep occurs in the 'early sleep' period, the first part of the night, whereas REM sleep occurs most of the later part of the night, the 'late sleep' period. SWS is thought of as being important for sleep-dependent memory processing. Previous research has suggested that SWS impairs declarative memory consolidation (of facts and events) and is therefore possibly linked to the consolidation of false memory. As SWS occurs mostly in the early period this perhaps points to some connection between this period and false memory. I want to use u the DRM paradigm (Deese,1959, Roediger & McDermott,1995). The DRM paradigm is used to present participants with lists of words (e.g bed, wake, dream..etc ) which create a false memory for non-presented words (e.g sleep). So, i am thinking of recruit self-identified early and late sleepers to see whether the same effects can be observed for sparser compared with denser semantically related lists. In other words, following the predictions from Sio et al's pilot analysis (they used easy and difficult problem and here will be denser and sparser lists), i would predict that early sleepers would show increased false memories for the more closely related (denser) DRM lists relative to the late sleepers, whilst both groups would show equivalent increases in false memory for the less closely related (sparser) DRM lists.
Would you please write me a report like literature review or background about this? Also the rational and which task is better to make this effect more pronounced? Recall or recognition? Regarding denser and sparser lists, you can use (interitem connectivity or association) to search about this topic.
800-1000 words.