The most important source of information of other states of mind is the semantic content of language. However, previous quantitative research has largely ignored this information, possibly because it is difficult to quantify.
I have been fascinated by the possibility quantifying semantics by computational modelling of human learning of semantics. By applying these models to large text corpora, it is possible to quantify the semantic content of all words in a language. Currently I am applying this method to a large number of projects including:
- eyewitness memory
- evaluation and evolution of social groups
- semantic representation in the brain
- views of god, etc.
Computational modelling of memory
The brain consists of a large number of cells, or processing units, which together form cognitive functioning as memory and consciousness. My research has focused on computational models aimed at understanding memory and cognition in the brain. Several of these models are based on neural network theories. I have published computational models on forgetting, the mirror effect, reaction times, serial position effect, frequency effects, successive tests, etc. related to episodic and semantic memory.
Noise improves cognitive performance
Irrelevant stimuli are typically seen as distractive and remove attention from the relevant task. We have shown that irrelevant stimuli, in the form of audible noise, can actually improve cognitive performance, and that this effect is particular strong for people with poor attentive skills.
That people make every-day choices based on accessible intentions is often taken for granted, yet our research indicates that this may not be the case. We let subjects choose which of two faces they found most attractive, and immediately asked them to motivate their choice. Through a “magical” trick, we replaced the face they had actually chosen with the the face they did not choose. Subjects failed to detect this mismatch between their own choice and the outcome of their choice, and were willing to make elaborate motivations for their decision. These results question whether people have access to the underlying reason for their choices.
Head of division
Department of Psychology
+46 46 222 87 55
Sverker [dot] Sikstrom [at] psy [dot] lu [dot] se