A Model for the Study of the Increase in Stimulus and Change Point Detection with Small and Variable Spiking Delays.

Precise timing of spikes between different neurons has been found to convey reliable information beyond the spike count. In contrast, the role of small and variable spiking delays, as reported, for example, in the visual cortex, remains largely unclear. This issue becomes particularly important considering the high speed of neuronal information processing, which is assumed to be based on only a few milliseconds within each processing step. We investigate the role of small and variable spiking delays with a parsimonious stochastic spiking model that is strongly motivated by experimental observations. The model contains only two parameters for the response of a neuron to one stimulus, describing directly the rate and the delay, or phase. Within the theoretical model, we specifically investigate two quantities, the probability of correct stimulus detection and the probability of correct change point detection, as a function of these parameters and within short periods of time. Optimal combinations of the two parameters across stimuli are derived that maximize these probabilities and enable comparison of pure rate, pure phase, and combined codes. In particular, the gain in correct detection probability when adding small and variable spiking delays to pure rate coding increases with the number of stimuli. More interesting, small and variable spiking delays can considerably improve the process of detecting changes in the stimulus, while also decreasing the probability of false alarms and thus increasing robustness and speed of change point detection. The results are compared to empirical spike train recordings of neurons in the visual cortex reported earlier in response to a number of visual stimuli. The results suggest that near-optimal combinations of rate and phase parameters may be implemented in the brain and that adding phase information could particularly increase the quality of change point detection in cases of highly similar stimuli.

A hierarchical stochastic model for bistable perception.

Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to potential underlying mechanisms.

Increased dopamine D2 receptor activity in the striatum alters the firing pattern of dopamine neurons in the ventral tegmental area.

There is strong evidence that the core deficits of schizophrenia result from dysfunction of the dopamine (DA) system, but details of this dysfunction remain unclear. We previously reported a model of transgenic mice that selectively and reversibly overexpress DA D2 receptors (D2Rs) in the striatum (D2R-OE mice). D2R-OE mice display deficits in cognition and motivation that are strikingly similar to the deficits in cognition and motivation observed in patients with schizophrenia. Here, we show that in vivo, both the firing rate (tonic activity) and burst firing (phasic activity) of identified midbrain DA neurons are impaired in the ventral tegmental area (VTA), but not in the substantia nigra (SN), of D2R-OE mice. Normalizing striatal D2R activity by switching off the transgene in adulthood recovered the reduction in tonic activity of VTA DA neurons, which is concordant with the rescue in motivation that we previously reported in our model. On the other hand, the reduction in burst activity was not rescued, which may be reflected in the observed persistence of cognitive deficits in D2R-OE mice. We have identified a potential molecular mechanism for the altered activity of DA VTA neurons in D2R-OE mice: a reduction in the expression of distinct NMDA receptor subunits selectively in identified mesolimbic DA VTA, but not nigrostriatal DA SN, neurons. These results suggest that functional deficits relevant for schizophrenia symptoms may involve differential regulation of selective DA pathways.

Multi-scale detection of rate changes in spike trains with weak dependencies.

The statistical analysis of neuronal spike trains by models of point processes often relies on the assumption of constant process parameters. However, it is a well-known problem that the parameters of empirical spike trains can be highly variable, such as for example the firing rate. In order to test the null hypothesis of a constant rate and to estimate the change points, a Multiple Filter Test (MFT) and a corresponding algorithm (MFA) have been proposed that can be applied under the assumption of independent inter spike intervals (ISIs). As empirical spike trains often show weak dependencies in the correlation structure of ISIs, we extend the MFT here to point processes associated with short range dependencies. By specifically estimating serial dependencies in the test statistic, we show that the new MFT can be applied to a variety of empirical firing patterns, including positive and negative serial correlations as well as tonic and bursty firing. The new MFT is applied to a data set of empirical spike trains with serial correlations, and simulations show improved performance against methods that assume independence. In case of positive correlations, our new MFT is necessary to reduce the number of false positives, which can be highly enhanced when falsely assuming independence. For the frequent case of negative correlations, the new MFT shows an improved detection probability of change points and thus, also a higher potential of signal extraction from noisy spike trains.

A stochastic model for EEG microstate sequence analysis.

The analysis of spontaneous resting state neuronal activity is assumed to give insight into the brain function. One noninvasive technique to study resting state activity is electroencephalography (EEG) with a subsequent microstate analysis. This technique reduces the recorded EEG signal to a sequence of prototypical topographical maps, which is hypothesized to capture important spatio-temporal properties of the signal. In a statistical EEG microstate analysis of healthy subjects in wakefulness and three stages of sleep, we observed a simple structure in the microstate transition matrix. It can be described with a first order Markov chain in which the transition probability from the current state (i.e., map) to a different map does not depend on the current map. The resulting transition matrix shows a high agreement with the observed transition matrix, requiring only about 2% of mass transport (1/2 L1-distance). In the second part, we introduce an extended framework in which the simple Markov chain is used to make inferences on a potential underlying time continuous process. This process cannot be directly observed and is therefore usually estimated from discrete sampling points of the EEG signal given by the local maxima of the global field power. Therefore, we propose a simple stochastic model called sampled marked intervals (SMI) model that relates the observed sequence of microstates to an assumed underlying process of background intervals and thus, complements approaches that focus on the analysis of observable microstate sequences.

Selective increase of in vivo firing frequencies in DA SN neurons after proteasome inhibition in the ventral midbrain.

The impairment of protein degradation via the ubiquitin-proteasome system (UPS) is present in sporadic Parkinson's disease (PD), and might play a key role in selective degeneration of vulnerable dopamine (DA) neurons in the substantia nigra pars compacta (SN). Further evidence for a causal role of dysfunctional UPS in familial PD comes from mutations in parkin, which results in a loss of function of an E3-ubiquitin-ligase. In a mouse model, genetic inactivation of an essential component of the 26S proteasome lead to widespread neuronal degeneration including DA midbrain neurons and the formation of alpha-synuclein-positive inclusion bodies, another hallmark of PD. Studies using pharmacological UPS inhibition in vivo had more mixed results, varying from extensive degeneration to no loss of DA SN neurons. However, it is currently unknown whether UPS impairment will affect the neurophysiological functions of DA midbrain neurons. To answer this question, we infused a selective proteasome inhibitor into the ventral midbrain in vivo and recorded single DA midbrain neurons 2 weeks after the proteasome challenge. We found a selective increase in the mean in vivo firing frequencies of identified DA SN neurons in anesthetized mice, while those in the ventral tegmental area (VTA) were unaffected. Our results demonstrate that a single-hit UPS inhibition is sufficient to induce a stable and selective hyperexcitability phenotype in surviving DA SN neurons in vivo. This might imply that UPS dysfunction sensitizes DA SN neurons by enhancing 'stressful pacemaking'.

Nocturnal behavioral patterns of African ungulates in zoos.

Currently, most studies on ungulates' behavior are conducted during the daylight hours, but their nocturnal behavior patterns differ from those shown during day. Therefore, it is necessary to observe ungulates' behavior also overnight. Detailed analyses of nocturnal behavior have only been conducted for very prominent ungulates such as Giraffes (Giraffa camelopardalis), African Elephants (Loxodonta africana), or livestock (e.g., domesticated cattle, sheep, or pigs), and the nocturnal rhythms exhibited by many ungulates remain unknown. In the present study, the nocturnal rhythms of 192 individuals of 18 ungulate species from 20 European zoos are studied with respect to the behavioral positions standing, lying-head up, and lying-head down (the typical REM sleep position). Differences between individuals of different age were found, but no differences with respect to the sex were seen. Most species showed a significant increase in the proportion of lying during the night. In addition, the time between two events of "lying down" was studied in detail. A high degree of rhythmicity with respect to this quantity was found in all species. The proportion of lying in such a period was greater in Artiodactyla than in Perissodactyla, and greater in juveniles than in adults.

Predictive Power of Interictal Epileptiform Discharges in Fitness-to-Drive Evaluation.

BACKGROUND AND OBJECTIVES: This study aimed to evaluate and predict the effects of interictal epileptiform discharges (IEDs) on driving ability using simple reaction tests and a driving simulator. METHODS: Patients with various epilepsies were evaluated with simultaneous EEGs during their response to visual stimuli in a single-flash test, a car-driving video game, and a realistic driving simulator. Reaction times (RTs) and missed reactions or crashes (miss/crash) during normal EEG and IEDs were measured. IEDs, as considered in this study, were a series of epileptiform potentials (>1 potential) and were classified as generalized typical, generalized atypical, or focal. RT and miss/crash in relation to IED type, duration, and test type were analyzed. RT prolongation, miss/crash probability, and odds ratio (OR) of miss/crash due to IEDs were calculated. RESULTS: Generalized typical IEDs prolonged RT by 164 ms, compared with generalized atypical IEDs (77.0 ms) and focal IEDs (48.0 ms) (p < 0.01). Generalized typical IEDs had a session miss/crash probability of 14.7% compared with a zero median for focal and generalized atypical IEDs (p < 0.01). Long repetitive bursts of focal IEDs lasting >2 seconds had a 2.6% miss/crash probabilityIED. Cumulated miss/crash probability could be predicted from RT prolongation: 90.3 ms yielded a 20% miss/crash probability. All tests were nonsuperior to each other in detecting miss/crash probabilitiesIED (zero median for all 3 tests) or RT prolongations (flash test: 56.4 ms, car-driving video game: 75.5 ms, simulator 86.6 ms). IEDs increased the OR of miss/crash in the simulator by 4.9-fold compared with normal EEG. A table of expected RT prolongations and miss/crash probabilities for IEDs of a given type and duration was created. DISCUSSION: IED-associated miss/crash probability and RT prolongation were comparably well detected by all tests. Long focal IED bursts carry a low risk, while generalized typical IEDs are the primary cause of miss/crash. We propose a cumulative 20% miss/crash risk at an RT prolongation of 90.3 ms as a clinically relevant IED effect. The IED-associated OR in the simulator approximates the effects of sleepiness or low blood alcohol level while driving on real roads. A decision aid for fitness-to-drive evaluation was created by providing the expected RT prolongations and misses/crashes when IEDs of a certain type and duration are detected in routine EEG.

A new concept for the cephalometric evaluation of craniofacial patterns (multiharmony).

Orthodontists commonly specify the alignment of the teeth and jaws by means of a set of k angles and their relationship with each other. Each individual can thus be visualized as a point in k-dimensional space. Individuals regarded as having an ideal occlusion and well-balanced face, form a cloud of points that is termed the 'norm' population. Individuals far from the cloud require orthodontic intervention. In this study, a method is presented--the multiharmony method (MHM), which assists in treatment planning. With multiple regression analysis, the expected value that each angle should take in a norm individual when the remaining angles are given is estimated. The residual difference between the measured angle and its expected value then indicates the deviation from a harmonic appearance in the respective angle. The MHM was applied to a data set of 134 Korean individuals identified as the norm population (Class I, mean age: 19.6 years) and to 87 patients (Class III, mean age: 21.2 years). From the number and size of the residuals, the two populations could be separated almost completely. Almost all patients showed residuals larger than any residual in the norm population (sensitivity: 99 per cent), whereas 90 per cent of all norm individuals showed no extreme residuals. The MHM can also be used to assist in visualizing different treatment effects, thereby assisting the orthodontist in choosing the best course of treatment for each patient.

In vivo functional diversity of midbrain dopamine neurons within identified axonal projections.

Functional diversity of midbrain dopamine (DA) neurons ranges across multiple scales, from differences in intrinsic properties and connectivity to selective task engagement in behaving animals. Distinct in vitro biophysical features of DA neurons have been associated with different axonal projection targets. However, it is unknown how this translates to different firing patterns of projection-defined DA subpopulations in the intact brain. We combined retrograde tracing with single-unit recording and labelling in mouse brain to create an in vivo functional topography of the midbrain DA system. We identified differences in burst firing among DA neurons projecting to dorsolateral striatum. Bursting also differentiated DA neurons in the medial substantia nigra (SN) projecting either to dorsal or ventral striatum. We found differences in mean firing rates and pause durations among ventral tegmental area (VTA) DA neurons projecting to lateral or medial shell of nucleus accumbens. Our data establishes a high-resolution functional in vivo landscape of midbrain DA neurons.

Impaired recruitment of dopamine neurons during working memory in mice with striatal D2 receptor overexpression.

The dopamine (DA) system plays a major role in cognitive functions through its interactions with several brain regions including the prefrontal cortex (PFC). Conversely, disturbances in the DA system contribute to cognitive deficits in psychiatric diseases, yet exactly how they do so remains poorly understood. Here we show, using mice with disease-relevant alterations in DA signaling (D2R-OE mice), that deficits in working memory (WM) are associated with impairments in the WM-dependent firing patterns of DA neurons in the ventral tegmental area (VTA). The WM-dependent phase-locking of DA neurons to 4 Hz VTA-PFC oscillations is absent in D2R-OE mice and VTA-PFC synchrony deficits scale with their WM impairments. We also find reduced 4 Hz synchrony between VTA DA neurons and selective impairments in their representation of WM demand. These results identify how altered DA neuron activity-at the level of long-range network activity and task-related firing patterns-may underlie cognitive impairments.

Detecting joint pausiness in parallel spike trains.

BACKGROUND: Transient periods with reduced neuronal discharge - called 'pauses' - have recently gained increasing attention. In dopamine neurons, pauses are considered important teaching signals, encoding negative reward prediction errors. Particularly simultaneous pauses are likely to have increased impact on information processing. COMPARISON WITH EXISTING METHODS: Available methods for detecting joint pausing analyze temporal overlap of pauses across spike trains. Such techniques are threshold dependent and can fail to identify joint pauses that are easily detectable by eye, particularly in spike trains with different firing rates. NEW METHOD: We introduce a new statistic called pausiness that measures the degree of synchronous pausing in spike train pairs and avoids threshold-dependent identification of specific pauses. A new graphic termed the cross-pauseogram compares the joint pausiness of two spike trains with its time shifted analogue, such that a (pausiness) peak indicates joint pausing. When assessing significance of pausiness peaks, we use a stochastic model with synchronous spikes to disentangle joint pausiness arising from synchronous spikes from additional 'joint excess pausiness' (JEP). Parameter estimates are obtained from auto- and cross-correlograms, and statistical significance is assessed by comparison to simulated cross-pauseograms. RESULTS: Our new method was applied to dopamine neuron pairs recorded in the ventral tegmental area of awake behaving mice. Significant JEP was detected in about 20% of the pairs. CONCLUSION: Given the neurophysiological importance of pauses and the fact that neurons integrate multiple inputs, our findings suggest that the analysis of JEP can reveal interesting aspects in the activity of simultaneously recorded neurons.

The role of soft-tissue traction forces in bone segment transport for callus distraction : A force measurement cadaver study on eight human femora using a novel intramedullary callus distraction system.

Callus distraction using bone segment transport systems is an applied process in the treatment of bone defects. However, complications such as muscle contractures, axial deviation and pin track infections occur in the treatment process using the currently available devices. Since successful treatment is influenced by the applied distraction force, knowledge of the biomechanical properties of the involved soft tissues is essential to improve clinical outcome and treatment strategies. To date, little data on distraction forces and the role of soft-tissue traction forces are available. The aim of this study was to assess traction forces generated by soft tissues during bone segment transport using a novel intramedullary callus distraction system on eight human femora. For traction force measurements, bone segment transport over 60-mm femoral defects was conducted under constant load measurement using 40- and 60-mm bone segments. The required traction forces for 60-mm bone segments were higher than forces for 40-mm bone segments. This study demonstrates that soft tissues are of relevance biomechanically in bone segment transport. The size of the bone segment and the selection of the region for osteotomy are of utmost importance in defining the treatment procedure.

Time-lapse imaging of granule cells in mouse entorhino-hippocampal slice cultures reveals changes in spine stability after entorhinal denervation.

Principal neurons that are partially denervated after brain injury remodel their synaptic connections and show biphasic changes in their dendritic spine density: during an early phase after denervation spine density decreases and during a late phase spine density recovers again. It has been hypothesized that these changes in spine density are caused by a period of increased spine loss followed by a period of increased spine formation. We have tested this hypothesis, which is based on data from fixed tissues, by using time-lapse imaging of denervated dentate granule cells in organotypic entorhino-hippocampal slice cultures of Thy1-GFP mice. Our data show that nondenervated granule cells turn over spines spontaneously while keeping their spine density constant. Denervation influenced this equilibrium and induced biphasic changes in the spine loss rate but not in the rate of spine formation: during the early phase after denervation the spine loss rate was increased and during the late phase after denervation the spine loss rate was decreased compared with nondenervated control cultures. In line with these observations, time-lapse imaging of identified spines formed after the lesion revealed that the stability of these spines was decreased during the early phase and increased during the late phase after the lesion. We conclude that biphasic changes in spine loss rate and spine stability but not in the rate of spine formation play a central role in the reorganization of dentate granule cells after entorhinal denervation in vitro.

K-ATP channels in dopamine substantia nigra neurons control bursting and novelty-induced exploration.

Phasic activation of the dopamine (DA) midbrain system in response to unexpected reward or novelty is critical for adaptive behavioral strategies. This activation of DA midbrain neurons occurs via a synaptically triggered switch from low-frequency background spiking to transient high-frequency burst firing. We found that, in medial DA neurons of the substantia nigra (SN), activity of ATP-sensitive potassium (K-ATP) channels enabled NMDA-mediated bursting in vitro as well as spontaneous in vivo burst firing in anesthetized mice. Cell-selective silencing of K-ATP channel activity in medial SN DA neurons revealed that their K-ATP channel-gated burst firing was crucial for novelty-dependent exploratory behavior. We also detected a transcriptional upregulation of K-ATP channel and NMDA receptor subunits, as well as high in vivo burst firing, in surviving SN DA neurons from Parkinson's disease patients, suggesting that burst-gating K-ATP channel function in DA neurons affects phenotypes in both disease and health.

Measuring burstiness and regularity in oscillatory spike trains.

The ability of neurons to emit different firing patterns such as bursts or oscillations is important for information processing in the brain. In dopaminergic neurons, prominent patterns include repetitive, oscillatory bursts, regular pacemakers, and irregular spike trains with nonstationary properties. In order to describe and measure the variability of these patterns, we describe burstiness and regularity in a single model framework. We present a doubly stochastic spike train model in which a background oscillation with independent and normally distributed intervals gives rise to either single spikes or bursty spike events with Gaussian firing intensities. Five easily interpretable parameters allow a classification into bursty or single spike and irregularly or regularly oscillating firing patterns. This classification is based primarily on features of the autocorrelation histogram which are usually studied qualitatively by visual inspection. The present model provides a quantitative and objective classification scheme and relates these features directly to the underlying processes. In addition, confidence intervals visualize the uncertainty of parameter estimation and classification precision. We apply the model to a data set obtained from single dopaminergic substantia nigra neurons recorded extracellularly in vivo. The model is able to represent a high variety of discharge patterns observed empirically, and the classification agrees closely with visual inspection. In addition, changes in the parameters can be studied quantitatively, including also the properties related to bursting behavior. Thus, the proposed model can be used for the description of neuronal firing patterns and the investigation of their dynamical changes with cellular and experimental conditions.

Effect sizes in experimental pain produced by gender, genetic variants and sensitization procedures.

BACKGROUND: Various effects on pain have been reported with respect to their statistical significance, but a standardized measure of effect size has been rarely added. Such a measure would ease comparison of the magnitude of the effects across studies, for example the effect of gender on heat pain with the effect of a genetic variant on pressure pain. METHODOLOGY/PRINCIPAL FINDINGS: Effect sizes on pain thresholds to stimuli consisting of heat, cold, blunt pressure, punctuate pressure and electrical current, administered to 125 subjects, were analyzed for 29 common variants in eight human genes reportedly modulating pain, gender and sensitization procedures using capsaicin or menthol. The genotype explained 0-5.9% of the total interindividual variance in pain thresholds to various stimuli and produced mainly small effects (Cohen's d 0-1.8). The largest effect had the TRPA1 rs13255063T/rs11988795G haplotype explaining >5% of the variance in electrical pain thresholds and conferring lower pain sensitivity to homozygous carriers. Gender produced larger effect sizes than most variant alleles (1-14.8% explained variance, Cohen's d 0.2-0.8), with higher pain sensitivity in women than in men. Sensitization by capsaicin or menthol explained up to 63% of the total variance (4.7-62.8%) and produced largest effects according to Cohen's d (0.4-2.6), especially heat sensitization by capsaicin (Cohen's d = 2.6). CONCLUSIONS: Sensitization, gender and genetic variants produce effects on pain in the mentioned order of effect sizes. The present report may provide a basis for comparative discussions of factors influencing pain.

Unilateral entorhinal denervation leads to long-lasting dendritic alterations of mouse hippocampal granule cells.

Following brain injury, neurons efferently connected from the lesion site are denervated and remodel their dendritic tree. Denervation-induced dendritic reorganization of granule cells was investigated in the dentate gyrus of the Thy1-GFP mouse. After mechanical transection of the perforant path, single granule cells were 3D-reconstructed at different time points post-lesion (3d, 7d, 10d, 30 d, 90 d and 180 d) and their soma size, total dendritic length, number of dendritic segments and dendritic branch orders were studied. Changes in spine densities were determined using 3D-analysis of individual dendritic segments. Following entorhinal denervation the granule cell arbor progressively atrophied until 90 d post-lesion (reduction of total dendritic length to ~50% of control). Dendritic alterations occurred selectively in the denervated outer molecular layer, where a loss of distal dendritic segments and a reduction of mean segment length were seen. At 180 d post-lesion total dendritic length partially recovered (~70% of control). This recovery appeared to be the result of a re-elongation of surviving dendrites rather than dendritic re-branching, since the number of dendritic segments did not recover. In contrast to the protracted dendritic changes, spine density changes followed a faster time course. In the denervated layer spine densities dropped to ~65% of control values and fully recovered by 30 d post-lesion. We conclude that entorhinal denervation in mouse causes protracted and long-term structural alterations of the granule cell dendritic tree. Spontaneously occurring reinnervation processes, such as the sprouting of surviving afferent fibers, are insufficient to maintain the granule cell dendritic arbor.

Messages of oscillatory correlograms: a spike train model.

Oscillatory correlograms are widely used to study neuronal activity that shows a joint periodic rhythm. In most cases, the statistical analysis of cross-correlation histograms (CCH) features is based on the null model of independent processes, and the resulting conclusions about the underlying processes remain qualitative. Therefore, we propose a spike train model for synchronous oscillatory firing activity that directly links characteristics of the CCH to parameters of the underlying processes. The model focuses particularly on asymmetric central peaks, which differ in slope and width on the two sides. Asymmetric peaks can be associated with phase offsets in the (sub-) millisecond range. These spatiotemporal firing patterns can be highly consistent across units yet invisible in the underlying processes. The proposed model includes a single temporal parameter that accounts for this peak asymmetry. The model provides approaches for the analysis of oscillatory correlograms, taking into account dependencies and nonstationarities in the underlying processes. In particular, the auto- and the cross-correlogram can be investigated in a joint analysis because they depend on the same spike train parameters. Particular temporal interactions such as the degree to which different units synchronize in a common oscillatory rhythm can also be investigated. The analysis is demonstrated by application to a simulated data set.

Sequence polymorphism systems for quantitative real-time polymerase chain reaction to characterize hematopoietic chimerism-high informativity and sensitivity as well as excellent reproducibility and precision of measurement.

Sequence polymorphisms (SPs) can serve as genetic markers for quantitative polymerase chain reactions (qPCR) for chimerism analysis, providing a significantly higher sensitivity compared to short tandem repeat PCR. In this study, a panel of 29 selected markers was evaluated in 317 patients with leukemia and myelodysplastic syndrome, who received allogeneic stem cell transplantation. In total, 5415 posttransplantation samples were analyzed. Recipient genotype discrimination was possible in 96% with a mean number of 2.5 (1-7) informative markers per recipient/donor pair. Marker specific standard dilution series from volunteers' DNA served as standard for quantification of chimerism. Sensitivity of the method was < or =1 x 10-3 (0.1% of recipient cells) in 83.3% of the assays. By this method, it was possible to very accurately detect autologous signals in the range from 0% to 0.5% (95% confidence interval [CI] +/-0.2), from 0.5% to 1% (95% CI +/-0.4), from 1% to 2% (95% CI +/-0.6) and from 2% to 5% (95% CI +/-1.2). Reproducibility of the quantified autologous signals was independent from the amount of DNA. This is the first report on a SP-based chimerism system allowing for the performance of chimerism analyses for virtually all patients with high sensitivity, excellent reproducibility, and precision of measurement.