Biomedical subjects

Jukka Saarinen

Publications and source records attributed to Jukka Saarinen.

4 recordsLinked to original sources

PubMed2004

Shape perception in human vision: specialized detectors for concentric spatial structures?

It has been suggested that second-order shape integration mechanisms in human spatial vision (e.g. the neurons at V2 and V4 cortical areas) may contain specialized detectors for concentric shapes [Vision Res. 37 (1997) 2325; Vision Res. 38 (1998) 2933]. We tested this notion using psychophysical techniques in which the observers' task was to detect orientation noise (randomly oriented dot pairs) in concentric and linear Glass patterns. Our results showed that the detection of orientation noise was easier in concentric Glass patterns, thus supporting the notion of specialized detectors.

Analysis of Variance↗

PubMed2003

Spatial integration in Glass patterns.

The extraction of a global orientation structure presumably has a different neural mechanism from that of the analysis of its local features. We investigated spatial integration within these two mechanisms using stimulus patterns composed of dot pairs (dipoles). The stimuli targeted local feature detection, contained no global configuration, but rather contained randomly oriented dipoles of a fixed length (the distance between the dots in a pair). For the detection of a global orientation structure, local dipole orientations were arranged in a concentric Glass pattern. Thresholds as a function of a stimulus area were determined by measuring the minimum proportion of dipoles among random-dot noise (signal-to-noise ratio) required for the detection of dipoles (features), as well as for the detection of an orientation structure. Thresholds for feature detection were significantly higher than those for the detection of the global structure--regardless of the stimulus size. Spatial integration, however, did not differ between the two tasks: the exponents of the power functions fitted to data for six observers were -0.48 +/- 0.07 for random dipole orientations and -0.62 +/- 0.1 for Glass patterns.

Humans↗

PubMed2002

Fuzzy detection of EEG alpha without amplitude thresholding.

Intelligent automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested using a total of 32 recordings from seven different subjects. Intelligence of the method was distributed to features extracted and the way they were combined. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector was assessed with receiver operating characteristic (ROC) curves. When the true positive rate was 94.2%, the false positive rate was 9.2%, which indicates good performance in sleep EEG analysis.

Adult↗

PubMed2002

A study on gender and age differences in sleep spindles.

In the present work, gender differences in sleep spindle topography were examined in 40 subjects. Their median age was 32 years (range 22-49 years). Spindles were detected from 3,306,060 s of visually scored stage 2 sleep EEG by a previously validated automatic fuzzy detector at 1-second intervals. A total of 271,168 spindles were found from the six EEG channels analyzed. Females showed a significantly higher percentage of spindles in the left frontal channel than males (Fp1-A2; p = 0.026). To confirm that this difference was gender and not age related, the subjects were divided into two age groups. No significant differences in spindle activity of the frontal channels were found between the groups. However, the interindividual spindle variability seemed to be at least as large as that stemming from gender.

Adult↗