| 1. |
- Roland, P, et al.
(författare)
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A database generator for human brain imaging
- 2001
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Ingår i: TINS - Trends in Neurosciences. - 0166-2236 .- 1878-108X. ; 24:10, s. 562-564
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Tidskriftsartikel (refereegranskat)abstract
- Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogenous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.
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| 2. |
- Rosbacke, M., et al.
(författare)
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Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch
- 2001
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Ingår i: Medical Image Analysis. - 1361-8415 .- 1361-8423. ; 5:2, s. 89-110
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Tidskriftsartikel (refereegranskat)abstract
- A dominant approach to brain mapping is to define functional regions in the brain by analyzing images of brain activation obtained from positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). This paper presents an evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis. A comparison is made concerning two possible definitions of a significance measure of blob structures in scale-space, where local contrast is measured either relative to a local or global reference level. Experiments on real brain data show that (i) the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level, and that (ii) the global approach with absolute base level gives a higher significance to small blobs that are superimposed on larger scale structures, whereas the significance of isolated blobs largely remains unaffected. Relative to previously reported works, the following two technical improvements are also presented. (i) A post-processing tool is introduced for merging blobs that are multiple responses to image structures. This simplifies automated analysis from the scale-space primal sketch. (ii) A new approach is introduced for scale-space normalization of the significance measure, by collecting reference statistics of residual noise images obtained from the general Linear model.
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| 3. |
- Zagal, Juan Cristobal, et al.
(författare)
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Signficance determination for the scale-space primal sketch by comparison of statistics of scale-space blob volumes computed from PET signals vs. residual noise
- 2000
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Konferensbidrag (refereegranskat)abstract
- A dominant approach to brain mapping is to define functional regions in the brain by analyzing brain activation images obtained by PET or fMRI. In [1], it has been shown that the scale-space primal sketch provides a useful tool for such analysis. Some attractive properties of this method are that it only makes few assumptions about the data and the process for extracting activations is fully automatic.In the present version of the scale-space primal sketch, however, there is no method for determining p-values. The purpose here is to present a new methodology for addressing this question, by introducing a descriptor referred to as the -curve, which serves as a first step towards determining the probability of false positives, i.e. alpha.
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| 4. |
- Narayanan, Ajit, et al.
(författare)
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Artificial intelligence techniques for bioinformatics
- 2002
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Ingår i: Applied Bioinformatics. - 1175-5636. ; 1:4, s. 191-222
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Forskningsöversikt (refereegranskat)abstract
- This review provides an overview of the ways in which techniques from artificial intelligence (AI) can be usefully employed in bioinformatics, both for modelling biological data and for making new discoveries. The paper covers three techniques: symbolic machine learning approaches (nearest neighbour and identification tree techniques), artificial neural networks and genetic algorithms. Each technique is introduced and supported with examples taken from the bioinformatics literature. These examples include folding prediction, viral protease cleavage prediction, classification, multiple sequence alignment and microarray gene expression analysis.
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| 5. |
- Rahpeymai, Neda, et al.
(författare)
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Microarray-based diagnosis of breast cancer using decision trees
- 2003
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Konferensbidrag (refereegranskat)abstract
- We apply the decision tree algorithm C4.5 to gene expression data in order to induce decision trees for identification of breast cancer patients. Using expression data from 108 known breast cancer-related genes for 75 patients with various diseases of the breast, we are able to induce decision trees with 89% accuracy in separating cancer from non-cancer patients in a cross-validation test. We also show that by inducing a separate decision tree for each cancer-related gene, and using the expression level of the individual gene as the decision variable, it is possible to obtain decision trees which aid the understanding of signaling pathways involved in breast cancer. In addition, we also show that the C4.5 algorithm is able to identify key breast cancer genes when decision trees are induced on expression data sets containing randomly selected genes. This result indicates that it is possible to make biological discoveries when applying decision tree algorithms to large sets of gene expression data in diseases where the genetic basis is not well characterised.
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| 6. |
- Kozlov, Alexander, et al.
(författare)
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Modeling of substance P and 5-HT induced synaptic plasticity in the lamprey spinal CPG : Consequences for network pattern generation
- 2001
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Ingår i: Journal of Computational Neuroscience. - 0929-5313 .- 1573-6873. ; 11:2, s. 183-200
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Tidskriftsartikel (refereegranskat)abstract
- Consequences of synaptic plasticity in the lamprey spinal CPG are analyzed by means of simulations. This is motivated by the effects substance P (a tachykinin) and serotonin (5-hydroxytryptamin; 5-HT) have on synaptic transmission in the locomotor network. Activity-dependent synaptic depression and potentiation have recently been shown experimentally using paired intracellular recordings. Although normally activity-dependent plasticity presumably does not contribute to the patterning of network activity, this changes in the presence of the neuromodulators substance P and 5-HT, which evoke significant plasticity. Substance P can induce a faster and larger depression of inhibitory connections but potentiation of excitatory inputs, whereas 5-HT induces facilitation of both inhibitory and excitatory inputs. Changes in the amplitude of the first postsynaptic potential are also seen. These changes could thus be a potential mechanism underlying the modulatory role these substances have on the rhythmic network activity. The aim of the present study has been to implement the activity dependent synaptic depression and facilitation induced by substance P and 5-HT into two alternative models of the lamprey spinal locomotor network, one relying on reciprocal inhibition for bursting and one in which each hemicord is capable of oscillations. The consequences of the plasticity of inhibitory and excitatory connections are then explored on the network level. In the intact spinal cord, tachykinins and 5-HT, which can be endogenously released, increase and decrease the frequency of the alternating left-right burst pattern, respectively. The frequency decreasing effect of 5-HT has previously been explained based on its conductance decreasing effect on K underlying the postspike afterhyperpolarization (AHP). The present simulations show that short-term synaptic plasticity may have strong effects on frequency regulation in the lamprey spinal CPG. In the network model relying on reciprocal inhibition, the observed effects substance P and 5-HT have on network behavior (i.e., a frequency increase and decrease respectively) can to a substantial part be explained by their effects on the total extent and time dynamics of synaptic depression and facilitation. The cellular effects of these substances will in the 5-HT case further contribute to its network effect.
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| 7. |
- Nilsson, Kenneth, 1951-, et al.
(författare)
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Complex Filters Applied to Fingerprint Images Detecting Prominent Symmetry Points Used for Alignment
- 2002
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Ingår i: Biometric Authentication. - Berlin : Springer Berlin/Heidelberg. - 9783540437239 ; , s. 39-47
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- For the alignment of two fingerprints position of certain landmarks are needed. These should be automatically extracted with low misidentification rate. As landmarks we suggest the prominent symmetry points (core-points) in the fingerprint. They are extracted from the complex orientation field estimated from the global structure of the fingerprint, i.e. the overall pattern of the ridges and valleys. Complex filters, applied to the orientation field in multiple resolution scales, are used to detect the symmetry and the type of symmetry. Experimental results are reported.
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| 8. |
- Björkman, Eva, et al.
(författare)
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Evaluation of design options for the scale-space primal sketch analysis of brain activation images
- 2000
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Konferensbidrag (refereegranskat)abstract
- A key issue in brain imaging concerns how to detect the functionally activated regions from PET and fMRI images. In earlier work, it has been shown that the scale-space primal sketch provides a useful tool for such analysis [1]. The method includes presmoothing with different filter widths and automatic estimation of the spatial extent of the activated regions (blobs).The purpose is to present two modifications of the scale-space primal sketch, as well as a quantitative evaluation which shows that these modifications improve the performance, measured as the separation between blob descriptors extracted from PET images and from noise images. This separation is essential for future work of associating a statistical p-value with the scale-space blob descriptors.
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| 9. |
- Kozlov, Alexander K., et al.
(författare)
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Mechanisms for lateral turns in lamprey in response to descending unilateral commands : a modeling study
- 2002
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Ingår i: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 86:1, s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- Straight locomotion in the lamprey is, at the segmental level, characterized by alternating bursts of motor activity with equal duration and spike frequency on the left and the right sides of the body. Lateral turns are characterized by three main changes in this pattern: (1) in the turn cycle, the spike frequency, burst duration, and burst proportion (burst duration/cycle duration) increase on the turning side; (2) the cycle duration increases in both the turn cycle and the succeeding cycle; and (3) in the cycle succeeding the turn cycle, the burst duration increases on the non-turning side (rebound). We investigated mechanisms for the generation of turns in single-segment models of the lamprey locomotor spinal network. Activation of crossing inhibitory neurons proved a sufficient mechanism to explain all three changes in the locomotor rhythm during a fictive turn. Increased activation of these cells inhibits the activity of the opposite side during the prolonged burst of the turn cycle, and slows down the locomotor rhythm. Secondly, this activation of the crossing inhibitory neurons is accompanied by an increased calcium influx into the cells. This gives a suppressed activity on the turning side and a contralateral rebound after the turn, through activation of calcium-dependent potassium channels.
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| 10. |
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