Measuring the rarity of core-delta distances in fingerprint patterns in the Dutch population.

In latent print examination, a conclusion on an individualization is primarily based on the presence of corresponding minutiae. Depending on the level of correspondence between the minutiae on the fingermark and on the reference print, a match is concluded. However, a fingermark is analyzed on all three levels: general pattern combined with core-delta distance, minutiae, and third-level detail. In the opinion of the authors, next to the conclusion based on minutiae, all information should be included in the final assessment of the evidence if present. In this study, we present the results of frequency data on the combination of fingerprint patterns and their core-delta distances. The frequency data allow examiners to substantiate their subjective opinions on the strength of corresponding patterns and core-delta distances based on measurements. The frequencies of the core-delta distances in this study were obtained by encoding core-delta distances in a collection of more than 20,000 fingerprints containing either a loop or a whorl pattern. The frequencies for the core-delta distances of loop patterns were subsequently compared with data from the National Institute of Standards and Technology. This study will demonstrate that core-delta distances in loop and whorl patterns contribute significantly to the overall evidential strength of fingerprint evidence. By adding pattern and core-delta distance information to the evaluation of fingerprint evidence, more challenging fingermarks could be added to fingerprint case reports.

Measuring the Rarity of Fingerprint Patterns in the Dutch Population Using an Extended Classification Set.

Latent print examiners often use their experience and knowledge to reach a conclusion on the identity of the source. Their conclusion is primarily based on their personal opinion on the rarity of the matching fingerprint features. Fingerprint patterns, if present, can play a significant role in the final assessment of a match. The authors believe that statistical data on the rarity of fingerprint patterns strengthens the subjective evaluation of the corresponding information. In order to provide fingerprint examiners with additional numerical support, fingerprint patterns were manually classified in a set of 24,104 fingerprints. In this study the frequencies of occurrence of 35 different fingerprint patterns have been obtained. The frequency data presented in this study can be used in the ACE-V process applied in forensic casework, allowing for the assessment of the evidential strength related to a specific fingerprint pattern type.

Numerical likelihood ratios outputted by LR systems are often based on extrapolation: When to stop extrapolating?

A recent trend in forensic science is the development of objective, automated systems for the comparison of trace and reference material that give as output numerical likelihood ratios (LRs). For well discriminating LR systems, often the probability of the evidence given one or the other hypothesis depends on the density from the tail of a probability distribution. The models for probability distributions are trained by data. Since there is no proof of the applicability of the models beyond the data range, LR systems are sensitive to extrapolation errors. Given the unknown behavior in the tail region one may define the problem as when to stop extrapolating. When applied to LR systems, this leads to limit values of the likelihood ratio (e.g. a minimum and a maximum value of the LR outputted by the LR system), depending on the sizes of the validation datasets used. The solution proposed in this paper to determine these limits is based on the normalized Bayes error-rate [1] in combination with the introduction of misleading LRs with increasing strength.

Fingermark evidence evaluation based on automated fingerprint identification system matching scores: the effect of different types of conditioning on likelihood ratios.

In recent studies, the evidential value of the similarity of minutiae configurations of fingermarks and fingerprints, for example expressed by automated fingerprint identification systems (AFIS), is determined by likelihood ratios (LRs). The paper explores whether there is an effect on LRs if conditioning takes place on specified fingers, fingerprints, or fingermarks under competing hypotheses: In addition, an approach is explored where conditioning is asymmetric. Comparisons between fingerprints and simulated fingermarks with eight minutiae are performed to produce similarity score distributions for each type of conditioning, given a fixed AFIS matching algorithm. Both similarity scores and LRs are significantly different if the conditioning changes. Given a common-source scenario, "LRs" resulting from asymmetric conditioning are on average higher. The difference may reach a factor of 2000. As conditioning on a suspect's finger(print) is labor-intensive and requires a cooperating suspect, it is recommended to just condition on the number of minutiae in the fingermark.

Performance evaluation of automated fingerprint identification systems for specific conditions observed in casework using simulated fingermarks.

Few studies have been reported on the performance evaluation of automated fingerprint identification systems (AFIS) for fingermark-to-fingerprint comparisons. This paper aims to illustrate to fingerprint examiners the relevance of evaluating the AFIS performance under specific conditions by carrying out five types of performance tests. The conditions addressed are the number of minutiae assigned to a fingermark, manual and automatic assignment of the minutiae, the finger region from which the fingermark originates, the degree of distortion in the fingermark, and the difference in orientation between fingermarks and fingerprints. In these tests, the magnitude of the influence for each condition was quantified. The comparisons were performed using a research AFIS technology with simulated fingermarks. Simulated fingermarks provide a practical way to create fingermarks for specific conditions in large quantities. The results showed that each condition influences the performance significantly, emphasizing the relevance of developing, and applying performance tests for specific conditions.

Introducing a semi-automatic method to simulate large numbers of forensic fingermarks for research on fingerprint identification.

Statistical research on fingerprint identification and the testing of automated fingerprint identification system (AFIS) performances require large numbers of forensic fingermarks. These fingermarks are rarely available. This study presents a semi-automatic method to create simulated fingermarks in large quantities that model minutiae features or images of forensic fingermarks. This method takes into account several aspects contributing to the variability of forensic fingermarks such as the number of minutiae, the finger region, and the elastic deformation of the skin. To investigate the applicability of the simulated fingermarks, fingermarks have been simulated with 5-12 minutiae originating from different finger regions for six fingers. An AFIS matching algorithm was used to obtain similarity scores for comparisons between the minutiae configurations of fingerprints and the minutiae configurations of simulated and forensic fingermarks. The results showed similar scores for both types of fingermarks suggesting that the simulated fingermarks are good substitutes for forensic fingermarks.

Disturbed functional connectivity in brain tumour patients: evaluation by graph analysis of synchronization matrices.

OBJECTIVE: Cerebral functions are based on the functional interactions between multiple distinct specialized regions of the brain. Functional interactions require anatomical connections as well as the synchronization of brain oscillations. The present work aims at evaluating the impact of brain tumours on spatial patterns of functional connectivity of the brain measured at rest by MEG. METHODS: We analyzed the statistical dependency (by computing the synchronization likelihood (SL, a measure of generalized synchronization)) between MEG signals at rest, in 17 patients with a brain tumour and in 15 healthy controls. Following an approach that derives from graph theory, we also analyzed the architectural properties of the networks by computing two parameters from the SL matrix, the cluster coefficient C and the characteristic path length L. RESULTS: Alterations in synchronization levels were found in the patients and were not focal but involved intra-hemispheric connectivity. Effects were different considering the frequencies sub-bands, predominating in a decrease in high frequencies bands for long-distance connections and an increase in slower bands for local connectivity. In addition, graph analysis reveals changes in the normal "small-world" network architecture in addition to changes in synchronization levels with some differences according to the studied frequency sub-bands. CONCLUSIONS: Brain tumours alter the functional connectivity and the "network" architecture of the brain. These alterations are not focal and effects are different considering the frequencies sub-bands. SIGNIFICANCE: These neurophysiological changes may contribute to the cognitive alterations observed in patients with brain tumours.

How do brain tumors alter functional connectivity? A magnetoencephalography study.

OBJECTIVE: This study was undertaken to test the hypothesis that brain tumors interfere with normal brain function by disrupting functional connectivity of brain networks. METHODS: Functional connectivity was assessed by computing the synchronization likelihood in a broad band (0.5-60Hz) or in the gamma band (30-60Hz) between all pairwise combinations of magnetoencephalography signals. Magnetoencephalography recordings were made at rest in 17 brain tumor patients and 15 healthy control subjects. For a given threshold of synchronization likelihood values, graphs of the suprathreshold connections between each magnetoencephalography channel and the others channels were built. RESULTS: In some regions, a variable number of channels without connectivity (missing connective points) at this threshold was found. The number of missing connective points was higher in patients with brain tumors than in control subjects (p < 0.0001, broad and gamma band) and was higher for left-sided than right-sided tumors (p = 0.008, broad band; p < 0.0001, gamma band). Individual results analysis indicates that the majority of brain tumor patients display several regions with missing connective point alterations in the affected and in the contralateral hemisphere. INTERPRETATION: Our findings suggest that brain tumors induce a loss of functional connectivity that affects multiple brain regions, and that left side brain tumors have the more severe consequences in this respect.

Age distribution of MEG spontaneous theta activity in healthy subjects.

This study investigates the possible relevance of distribution and age variation of spontaneous theta activity (4-8 Hz) in normal subjects using magnetoencephalography (MEG) recordings. Spontaneous theta was recorded with a 151-channel MEG in healthy subjects; moreover, in a group of 10 subjects, simultaneous MEG-EEG was recorded in order to compare the two methods. Theta was divided in two sub-bands: T(A) (4-6 Hz) and T(B) (6-8 Hz). The pre-processed data were transformed into the frequency domain by Fast Fourier Transform (FFT)-based software by subdividing the data in epochs of 5 sec, on which FFT amplitudes are computed. Moreover, on all trials a simple model of a single electric current embedded in a spherically symmetric conductor was fitted automatically to the magnetic fields and projected onto an averaged MRI. The results obtained show that FFT-based theta power spectrum was distributed in adults with the highest power over the posterior parietal and occipital areas with T(B) dominance. The dipole analysis resulted in a mid-sagittal distribution, though the youngest group displayed theta dipoles fitting more posteriorly respect to the adults and the elderly. These results suggest that spontaneous theta activity is a diffuse and pervasive rhythm which shows some different topographical distribution among the age groups. Whether the prevalent posterior distribution of theta is the expression of distinct networks or the outcome of complex dynamics are questions of possible relevance in the organization of higher order processes.

Differences in MEG/EEG epileptic spike yields explained by regional differences in signal-to-noise ratios.

Controversy remains regarding the preferred modality, magnetoencephalography (MEG) or EEG, for the presurgical evaluation of patients with epilepsy. In general, it appears that the spike yields for MEG and EEG are similar in patients with temporal lobe epilepsy, and that for neocortical epilepsy the MEG spike yields may be larger than for EEG. In general, MEG/EEG spike yields depend on factors such as (1) the number of sensors, (2) the source depth and orientation, (3) the background activity, and (4) the smearing of the potential fields due to variations in skull resistivity in EEG. Because the contribution of all these factors are of the same order of magnitude, the authors took them all into account to predict the signal-to-noise ratio (SNR) of hypothetical spikes in different brain areas. In this study, it was assumed that spike sensitivity (and therefore the spike yield) increases with SNR. The estimated SNR values at temporal areas were comparable for MEG and EEG, which is in agreement with clinical findings that spike yields in temporal lobe epilepsy are similar. Furthermore, the SNR of MEG was substantially higher in the frontal area, indicating that in frontal lobe epilepsy MEG may be highly relevant to prescreening of epilepsy patients. This model-based approach indicates that SNR mapping clarifies differences between MEG and EEG findings that are difficult to understand on the basis of patient studies only.

Localization of slow wave activity in patients with tumor-associated epilepsy.

OBJECTIVE: Brain tumors are frequently accompanied by abnormal low frequency magnetic activity (ALFMA). The prevalence and clinical meaning of ALFMA are not well known, although a relation with epileptic brain tissue has been suggested. We studied the prevalence, characteristics and clinical correlates of ALFMA in 20 patients with brain tumors. METHODS: In 20 patients with clinical seizures due to a supratentorial tumor, MEG was performed, followed by MR imaging. MEG signals were band pass-filtered (1-4 Hz); the sources of this activity were localized and projected onto the MRI of the patient. RESULTS: Peritumoral ALFMA could be detected in 13 of 20 patients. A pattern of ALFMA distribution around the tumor could be recognized. In eight cases ALFMA also appeared to be localized within the tumor. In three cases ALFMA was also detected in peritumoral white matter. CONCLUSIONS: Automatic detection of abnormal delta-activity in patients with a brain tumor and seizures can be performed in a clinical setting. When detected, ALFMA is mostly present in circumscribed regions around the tumor. Presence of ALFMA within the tumor might be an important warning signal for the neurosurgeon that the tumor area comprises functional brain tissue.