Measured Path Length Research Articles

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructure and connectivity. Yet, quantitative analysis of DW-MRI data is hindered by inconsistencies stemming from varying acquisition protocols. Specifically, there is a pressing need to harmonize the preprocessing of DW-MRI datasets to ensure the derivation of robust quantitative diffusion metrics across acquisitions. In the MICCAI-CDMRI 2023 QuantConn challenge, participants were provided raw data from the same individuals collected on the same scanner but with two different acquisitions and tasked with preprocessing the DW-MRI to minimize acquisition differences while retaining biological variation. Harmonized submissions are evaluated on the reproducibility and comparability of cross-acquisition bundlewise microstructure measures, bundle shape features, and connectomics. The key innovations of the QuantConn challenge are that (1) we assess bundles and tractography in the context of harmonization for the first time, (2) we assess connectomics in the context of harmonization for the first time, and (3) we have 10x additional subjects over prior harmonization challenge, MUSHAC and 100x over SuperMUDI. We find that bundle surface area, fractional anisotropy, connectome assortativity, betweenness centrality, edge count, modularity, nodal strength, and participation coefficient measures are most biased by acquisition and that machine learning voxel-wise correction, RISH mapping, and NeSH methods effectively reduce these biases. In addition, microstructure measures AD, MD, RD, bundle length, connectome density, efficiency, and path length are least biased by these acquisition differences. A machine learning approach that learned voxelwise cross-acquisition relationships was the most effective at harmonizing connectomic, microstructure, and macrostructure features, but requires the same subject be scanned at each site co-registered. NeSH, a spatial and angular resampling method, was also effective and has generalizable framework not reliant co-registration. Our code is available at <a href='https://github.com/nancynewlin-masi/QuantConn/'>https://github.com/nancynewlin-masi/QuantConn/</a>

The usage of interference effects in single Guided Ultrasonic Wave time signals for damage identification

Guided Ultrasonic Waves (GUW) interact with structural inhomogenities in multiple ways, e.g. mode conversions, mode scattering, oscillation phase shifts and reflections. These effects do occur at specimen edges and at damage on and in the specimen’s area. These effects at structural boundaries make the signal interpretation more complex. On the other hand they can lead to additional information in recorded time signals when caused by damage. This study aims at the usage of interference effects in single time signals caused by damage in the structure. This is investigated changing the location of the measurements points in relation to the damage position. Two cases are taken into account: once the damage lies in the direct measurement patch between actuator and measurement point and once the damage lies outside the measurement path and its effect on the recorded time signal is investigated. In the experimental setup, a rectangular Aluminum plate is used. Its dimension is chosen to make sure that edge reflections do not superimpose with the regarded wave packages within the time signals. A Laser-Doppler-Vibrometer allows the non-contact recording of several measurement points and is not wavelength-dependent as e.g. PZT-transducers. This allows the measurement to be unaffected by the transfer behavior of the transducers. The relationship between the specific mode wavelength reflected by the damage and the measurement path length provides information about the expected level of interference at the considered measurement point. The anticipation includes the indirect identification of damage off the direct measurement path through the observed interference effects, as well as variations in interference caused by the shift of the measurement point locations. The amplitude and phase changes serve as a measure of the interference and are obtained using the Hilbert transform.

Digital Measures of Postural Sway Quantify Balance Deficits in Spinocerebellar Ataxia.

Maintaining balance is crucial for independence and quality of life. Loss of balance is a hallmark of spinocerebellar ataxia (SCA). The aim of this study was to identify which standing balance conditions and digital measures of body sway were most discriminative, reliable, and valid for quantifying balance in SCA. Fifty-three people with SCA (13 SCA1, 13 SCA2, 14 SCA3, and 13 SCA6) and Scale for Assessment and Rating of Ataxia (SARA) scores 9.28 ± 4.36 and 31 healthy controls were recruited. Subjects stood in six test conditions (natural stance, feet together and tandem, each with eyes open [EO] and eyes closed [EC]) with an inertial sensor on their lower back for 30 seconds (×2). We compared test completion rate, test-retest reliability, and areas under the receiver operating characteristic curve (AUC) for seven digital sway measures. Pearson's correlations related sway with the SARA and the Patient-Reported Outcome Measure of Ataxia (PROM ataxia). Most individuals with SCA (85%-100%) could stand for 30 seconds with natural stance EO or EC, and with feet together EO. The most discriminative digital sway measures (path length, range, area, and root mean square) from the two most reliable and discriminative conditions (natural stance EC and feet together EO) showed intraclass correlation coefficients from 0.70 to 0.91 and AUCs from 0.83 to 0.93. Correlations of sway with SARA were significant (maximum r = 0.65 and 0.73). Correlations with PROM ataxia were mild to moderate (maximum r = 0.56 and 0.34). Inertial sensor measures of extent of postural sway in conditions of natural stance EC and feet together stance EO were discriminative, reliable, and valid for monitoring SCA. © 2024 International Parkinson and Movement Disorder Society.

Automatic digital optical heterodyne phase locking loop in the milliradian domain for spaceborne laser interferometry.

We developed a digital optical phase locking loop (OPLL) with three advantages, including high precision of phase locking, high control bandwidth up to 2.8 MHz, and automatic laser locking strategy. Spaceborne laser interferometers will be used to measure tiny displacements caused by gravitational waves in millions of kilometers range. A slave laser will be heterodyne phase locked to the incoming weak light at the end of an arm, emitting a higher power light back to the other satellite to measure pathlength variations at the picometer level. Such accuracy requires extremely precise OPLL. We report an experiment to demonstrate a digital OPLL that can automatically lock two independent free-running Nd:YAG lasers with residual phase error below 1mrad/Hz above 0.01 Hz, which is the best performance recorded for digital servos, to our knowledge. Such performance tested under a normal laboratory environment will be highly improved in a vacuum environment with temperature and vibration well controlled. Both the digital OPLL and the automatic strategy were implemented on a field programmable gate array that could be potentially used for future gravitational-wave detection. Our experiment might change the thinking of scientists who study phasemeters of gravitational-wave detection because we are aware that the digital phase locking loop used for "optical phase tracking" is differently designed from "optical phase locking."

Analysis of ionospheric Total Electron Content variability determined from Global Navigation Satellite System data

Free electrons refract signals transmitted from satellites mainly during their trans-ionospheric propagation. The side-effect is the measured path length travelled by a signal is about five to fifteen meters longer than the actual path covered. Moreover, magnitudes of signal delays are directly proportional to the Total Electron Content (TEC). TEC is an ionospheric parameter indicating the total amount of electrons along a signal path between satellites and ground based receivers. This study was conducted because the TEC-induced ionospheric delay is themain error source in single frequency receivers. Hence, this study involved the extraction of TEC values from GNSS data with the Global Positioning System (GPS) TEC software to observe diurnal and seasonal variations of GNSS-TEC. Additionally, the study compared TEC plots of Windhoek(22.5741⁰S; 17.0894⁰E), Hermanus(South Africa, -34.42463056⁰S; 19.22306111⁰E), and Dakar(Senegal, 14.720903⁰N; -17.439503⁰W) to validate whether the ionospheric delay varies in accordance with the geographic location or not.Comparisons of observational GNSS-TEC and IRI-TEC derived from the IRI model were made to determine the accuracy of the IRI-model in the southern hemisphere. GNSS data were derived from a dual-frequency receiver installed at Windhoek (22.5741⁰S; 17.0894⁰E), Namibia. Results show that maximum TEC was prevalent in spring while minimum TEC generally occurred throughout winter. Moreover, results revealed that the International Reference Ionosphere (IRI) model overestimated GNSS-TEC in winter but underestimatedduring summer, autumn and spring.

Dispersion scanning beam medium infra-red interferometry for divertor plasma density measurement in DTT

Dispersion Interferometers (DI) present the fundamental advantage over conventional ones to be insensitive to mechanical vibrations without requiring a second wavelength interferometer to measure path length variations. On the other hand, their optical setup requires duplication of nearly all optical components for any measuring chord. This makes the realization of a multi-channel interferometer that is needed to obtain density profiles via Abel inversion of line integral measurements more complicated. To overcome such drawback of the DI, in this work we propose to join the dispersion technique to the beam scanning one, which has been already successfully implemented in the conventional mid-infrared two-colour interferometer. In particular, we present a preliminary design of a DI scanning interferometer for the new Divertor Test Tokamak (DTT) facility, presently in construction. DTT is designed to study a large suite of alternative divertor magnetic configurations in order to ensure acceptable conditions at the walls while maintaining sufficient core performance. In this contest, measuring plasma parameters in the divertor region is very important though it often presents various difficulties. To improve divertor measurements the proposed interferometer will measure the density along the divertor legs from the strike points up the X-point. The interferometer will use a CO2 laser (λ =10.6 μm) and a double pass optical scheme. Phase modulation method will be used to improve the resolution of the measurement and to extend the measuring range above the 1020 m−2 line integral limitation of the standard homodyne implementation. Both improvements are important in this application, considering the wide density range expected in the DTT divertor region. Comparing to shorter wavelengths, more commonly used in the DI interferometers, the CO2 wavelength improves density resolution while providing good immunity to the diffraction effect due to the expected high density gradient.

How Much of What We Learn in Virtual Reality Transfers to Real-World Navigation?

Past studies suggest that learning a spatial environment by navigating on a desktop computer can lead to significant acquisition of spatial knowledge, although typically less than navigating in the real world. Exactly how this might differ when learning in immersive virtual interfaces that offer a rich set of multisensory cues remains to be fully explored. In this study, participants learned a campus building environment by navigating (1)the real-world version, (2)an immersive version involving an omnidirectional treadmill and head-mounted display, or (3)a version navigated on a desktop computer with a mouse and a keyboard. Participants first navigated the building in one of the three different interfaces and, afterward, navigated the real-world building to assess information transfer. To determine how well they learned the spatial layout, we measured path length, visitation errors, and pointing errors. Both virtual conditions resulted in significant learning and transfer to the real world, suggesting their efficacy in mimicking some aspects of real-world navigation. Overall, real-world navigation outperformed both immersive and desktop navigation, effects particularly pronounced early in learning. This was also suggested in a second experiment involving transfer from the real world to immersive virtual reality (VR). Analysis of effect sizes of going from virtual conditions to the real world suggested a slight advantage for immersive VR compared to desktop in terms of transfer, although at the cost of increased likelihood of dropout. Our findings suggest that virtual navigation results in significant learning, regardless of the interface, with immersive VR providing some advantage when transferring to the real world.

Path Planning Algorithm for Unmanned Ground Vehicles (UGVs) in Known Static Environments

Unmanned ground vehicles (UGVs) have been utilized in many civilian fields in addition to the traditional military field. This is due to their increasing capabilities in terms of performance, power, and tackling risky missions. Many applications require the UGV to autonomously navigate static environments while taking into consideration obstacle avoidance. Autonomous path planning is one of the key challenges and issues related to UGVs. Generally, robotic path planning is an optimization search problem that comes in different forms. Some of its forms have been solved by different classical algorithms such as A*, but these algorithms are computationally inefficient. In contrast, the emerging nature-inspired algorithms outperform the classical ones since the computational overhead is reduced. Nature-inspired algorithms are among the most common heuristic algorithms. This paper proposes a near-optimal algorithm to find a feasible path for UGV in a static environment. The performance of the proposed algorithm was compared with other well-established algorithms in path planning literature such as A* using a simulator developed for this purpose. The simulator tests three performance measures path length, farness from obstacles, and running time. The simulator results revealed that the length of the path generated by this algorithm is near-optimal, however, the generated path is kept far from obstacles.

Stability of graph theoretical measures in structural brain networks in Alzheimer\u2019s disease

Graph analysis has become a popular approach to study structural brain networks in neurodegenerative disorders such as Alzheimer’s disease (AD). However, reported results across similar studies are often not consistent. In this paper we investigated the stability of the graph analysis measures clustering, path length, global efficiency and transitivity in a cohort of AD (N = 293) and control subjects (N = 293). More specifically, we studied the effect that group size and composition, choice of neuroanatomical atlas, and choice of cortical measure (thickness or volume) have on binary and weighted network properties and relate them to the magnitude of the differences between groups of AD and control subjects. Our results showed that specific group composition heavily influenced the network properties, particularly for groups with less than 150 subjects. Weighted measures generally required fewer subjects to stabilize and all assessed measures showed robust significant differences, consistent across atlases and cortical measures. However, all these measures were driven by the average correlation strength, which implies a limitation of capturing more complex features in weighted networks. In binary graphs, significant differences were only found in the global efficiency and transitivity measures when using cortical thickness measures to define edges. The findings were consistent across the two atlases, but no differences were found when using cortical volumes. Our findings merits future investigations of weighted brain networks and suggest that cortical thickness measures should be preferred in future AD studies if using binary networks. Further, studying cortical networks in small cohorts should be complemented by analyzing smaller, subsampled groups to reduce the risk that findings are spurious.

An optical method for the measurement of combustion gas temperature in particle laden flows

Temperature measurements in combustion systems are challenging due to the physical limitations of measurement devices and the complexity of combustion flows. The objective of this work is to investigate the Integrated Spectral Band Ratio (ISBR) method for measuring the temperature of combustion product gases surrounded by radiating walls or within a mixture of gas and particles. Five conditions in a multi-fuel reactor were investigated using an optical probe. A Fourier Transform Infrared spectrometer provided detailed spectral measurements of hot gas and particle emissions at wavelengths of 1.69–2.15 μm, focusing on a spectral region where H2O is the dominant participating gas. These measurements were used to infer the gas temperature of the flows. It was found that the measurement path length needed to be at least 0.25 m in order to obtain a signal large enough to infer temperature accurately. For four of the five operating conditions tested, optically measured gas temperatures were found to be in good agreement with the average temperature along the measured path as taken with a suction pyrometer (aspirated thermocouple). For these four operating conditions the particle media were optically thin. Temperatures for the in-flame fine wood particle condition did not exhibit as good of agreement due to high particle loading causing optically thick zones along the line of sight. Modeling experiments showed that when particles and gasses are optically thin, the optical gas temperature measured with this technique will be near the arithmetic mean of the line of sight temperature.

Estimating the impact of structural directionality: How reliable are undirected connectomes?

Directionality is a fundamental feature of network connections. Most structural brain networks are intrinsically directed because of the nature of chemical synapses, which comprise most neuronal connections. Because of the limitations of noninvasive imaging techniques, the directionality of connections between structurally connected regions of the human brain cannot be confirmed. Hence, connections are represented as undirected, and it is still unknown how this lack of directionality affects brain network topology. Using six directed brain networks from different species and parcellations (cat, mouse, C. elegans, and three macaque networks), we estimate the inaccuracies in network measures (degree, betweenness, clustering coefficient, path length, global efficiency, participation index, and small-worldness) associated with the removal of the directionality of connections. We employ three different methods to render directed brain networks undirected: (a) remove unidirectional connections, (b) add reciprocal connections, and (c) combine equal numbers of removed and added unidirectional connections. We quantify the extent of inaccuracy in network measures introduced through neglecting connection directionality for individual nodes and across the network. We find that the coarse division between core and peripheral nodes remains accurate for undirected networks. However, hub nodes differ considerably when directionality is neglected. Comparing the different methods to generate undirected networks from directed ones, we generally find that the addition of reciprocal connections (false positives) causes larger errors in graph-theoretic measures than the removal of the same number of directed connections (false negatives). These findings suggest that directionality plays an essential role in shaping brain networks and highlight some limitations of undirected connectomes.

Two-color heterodyne laser interferometry for long-distance stage measurement with correction of uncertainties in measured optical distances

We designed a new system that eliminates deviations by correcting uncertainty in optical distance measurements in the laser two-color heterodyne interferometer. In simulations, eliminating the uncertainty from the atmosphere, the deviation in the uncertainty of the optical distance was 50 times greater with the two-color method than with the one-color method. Adding a correction arm reduces the deviation caused by the uncertainties in measured optical distances. The uncertainty in the measured path length is reduced to 20 nm over a path length of 1500 mm, giving a relative uncertainty of 1.34 × 10−8.

Novel utilisation of a circular multi-reflection cell applied to materials ageing experiments

We report on the novel utilisation of a circular multi-reflection (CMR) cell applied to materials ageing experiments. This enabled trace gas detection within a narrow interfacial region located between two sample materials and remotely interrogated with near-infrared sources combined with fibre-optic coupling. Tunable diode laser absorption spectroscopy was used to detect water vapour and carbon dioxide at wavelengths near 1,358 and 2,004 nm, respectively, with corresponding detection limits of 7 and 1,139 ppm m Hz−0.5. The minimum detectable absorption was estimated to be 2.82 × 10−3 over a 1-s average. In addition, broadband absorption spectroscopy was carried out for the detection of acetic acid, using a super-luminescent light emitting diode centred around 1,430 nm. The 69 cm measurement pathlength was limited by poor manufacturing tolerances of the spherical CMR mirrors and the consequent difficulty of collecting all the cell output light.

Analyzing water contents in unexposed glass inclusions in quartz crystals

Fourier-transform infrared (FTIR) spectroscopy is commonly used to measure volatile contents dissolved in glass inclusions in minerals. The standard method is to doubly polish the crystal to fully expose the inclusion to allow infrared light to pass through the inclusion only. Glass inclusions are often a few tens of micrometers thick, which can limit the usefulness of FTIR because of how fragile samples become when thinned enough to doubly expose inclusions. Here, we test whether unexposed inclusions can be feasibly analyzed by measuring the dissolved volatile contents of a population of rehomogenized quartz-hosted glass inclusions at variable exposure levels. We analyzed 118 unexposed inclusions in 46 crystals. Of those, we analyzed the 74 inclusions in 38 crystals that survived being singly exposed. Of those, only 24 inclusions in 18 crystals remained to be analyzed when doubly exposed. Measuring the path length of light through the inclusion is critical to FTIR analyses. That length can be measured directly for doubly exposed inclusions. For those inclusions we find that water contents vary from 1.6 to 2.6 wt%, averaging 2.2 ± 0.3 wt%. Path length is difficult to measure, however, in singly exposed or unexposed inclusions. Indeed, we find that path length is variably underestimated when measured using a well-calibrated optical method. Despite that difficulty, the average water contents for the populations at each exposure level are statistically the same. But, on an inclusion-by-inclusion basis volatile contents at various exposure levels are highly discrepant because the typically underestimated thicknesses for non-doubly exposed inclusions result in anomalously high volatile contents. One way to measure path length in those inclusions is to reorient the host crystal to align the path length horizontally so it can be measured with the eyepiece reticle. Often, however, that technique proves impractical because small samples are difficult to handle. When path length cannot be measured directly, we find that using the average of the dimensions of the inclusion orthogonal to the path length can be used as a proxy for path length. That proxy allows volatile contents in unexposed inclusions to be analyzed accurately, which significantly reduces difficulties of sample preparation and can dramatically increase the number of potential target inclusions.

Classroom measurements of sound speed in fresh/saline water

A tabletop apparatus permitting demonstrations and hands-on student exercises in the measurement of sound speed in water as a function of both temperature and salinity, at atmospheric pressure, is described. By measuring sound speed using a differential technique with a precisely measured path length difference Δx, errors due to uncertainty in original path length are minimized. The apparatus can be used to measure sound speed in freshwater baths of varying temperature and room temperature baths of varying salinities to provide the student a clear picture of sound speed variation along two axes.

Measurement and analysis of sarcomere length in rat cardiomyocytes in situ and in vitro

Sarcomere length (SL) is an important determinant and indicator of cardiac mechanical function; however, techniques for measuring SL in living, intact tissue are limited. Here, we present a technique that uses two-photon microscopy to directly image striations of living cells in cardioplegic conditions, both in situ (Langendorff-perfused rat hearts and ventricular tissue slices, stained with the fluorescent marker di-4-ANEPPS) and in vitro (acutely isolated rat ventricular myocytes). Software was developed to extract SL from two-photon fluorescence image sets while accounting for measurement errors associated with motion artifact in raster-scanned images and uncertainty of the cell angle relative to the imaging plane. Monte-Carlo simulations were used to guide analysis of SL measurements by determining error bounds as a function of measurement path length. The mode of the distribution of SL measurements in resting Langendorff-perfused heart is 1.95 mum (n = 167 measurements from N = 11 hearts) after correction for tissue orientation, which was significantly greater than that in isolated cells (1.71 mum, n = 346, N = 9 isolations) or ventricular slice preparations (1.79 mum, n = 79, N = 3 hearts) under our experimental conditions. Furthermore, we find that edema in arrested Langendorff-perfused heart is associated with a mean SL increase; this occurs as a function of time ex vivo and correlates with tissue volume changes determined by magnetic resonance imaging. Our results highlight that the proposed method can be used to monitor SL in living cells and that different experimental models from the same species may display significantly different SL values under otherwise comparable conditions, which has implications for experiment design, as well as comparison and interpretation of data.

Liquid-Phase and Evanescent-Wave Cavity Ring-Down Spectroscopy in Analytical Chemistry

Due to its simplicity, versatility, and straightforward interpretation into absolute concentrations, molecular absorbance detection is widely used in liquid-phase analytical chemistry. Because this method is inherently less sensitive than zero-background techniques such as fluorescence detection, alternative, more sensitive measurement principles are being explored. This review discusses one of these: cavity ring-down spectroscopy (CRDS). Advantages of this technique include its long measurement pathlength and its insensitivity to light-source-intensity fluctuations. CRDS is already a well-established technique in the gas phase, so we focus on two new modes: liquid-phase CRDS and evanescent-wave (EW)-CRDS. Applications of liquid-phase CRDS in analytical chemistry focus on improving the sensitivity of absorbance detection in liquid chromatography. Currently, EW-CRDS is still in early stages: It is used to study basic interactions between molecules and silica surfaces. However, in the future this method may be used to develop, for instance, biosensors with high specificity.

Evaluation of a multimode fiber optic low coherence interferometer for path length resolved Doppler measurements of diffuse light

The performance of a graded index multimode fiber optic low coherence Mach-Zehnder interferometer with phase modulation is analyzed. Investigated aspects were its ability to measure path length distributions and to perform path length resolved Doppler measurements of multiple scattered photons in a turbid suspension of particles undergoing Brownian and translational motion. The path length resolution of this instrument is compared with a system using single mode fibers for illumination and detection. The optical path lengths are determined from the zero order moment of the phase modulation peak in the power spectrum. The weighted first moment, which is equal to the average Doppler shift, shows a linear response for different mean flow velocities within the physiological range.

Extrinsic Fabry−Perot Interferometry for Noncontact Temperature Control of Nanoliter-Volume Enzymatic Reactions in Glass Microchips

Optical fiber extrinsic Fabry-Perot interferometry (EFPI) was investigated as a noncontact temperature sensor and utilized for regulating the temperature of small-volume solutions in microchips. Interference pattern analysis determined the optical path lengths (OPL) associated with reflections from various surfaces on or in the microchip, in particular, from gold sputtered on the bottom of a microchannel. Since OPL is directly proportional to refractive index, which is dependent on solution temperature, the EFPI sensor was capable of noncontact monitoring of solution temperature simply from alterations in the measured path length. Calibration of the sensor against a thermocouple was performed while heating the microchip in a noncontact manner with an IR lamp. The combination of EFPI temperature sensor, IR-mediated heating, and air cooling allowed a fully noncontact system for small-volume temperature control in microchip structures, and its utility was illustrated by optimal digestion of DNA by a temperature-dependent restriction endonuclease in 320 nL. The functionality and simplicity of the microchip EFPI temperature sensor was enhanced by replacing the prebonding sputtered gold with a tunable, chemically plated semireflective silver coating created in situ after chip fabrication. This provided an 8-fold improvement in the lowest detectable temperature change (deltaT = 0.1 degrees C), facilitated primarily by enhanced reflection from both the bottom and top surfaces of the microchannel. This approach for controlling micro- and nanoscale reactions--with heating, cooling, and temperature control being carried out in a completely noncontact fashion--provides an accurate and sensitive method for executing chemical and biochemical reactions in microchips.

Particle path length distributions in meandering gravel‐bed streams: results from physical models

AbstractIn gravel‐bed rivers with well‐defined pool–bar morphology, the path length of transported bed particles must be, at least during ‘channel‐forming’ flows, equal to the length scale of the morphology. This is the basis for some methods for estimating bed material transport rates. However, previous data, especially from field tests, are often strongly positively skewed with mean much shorter than the pool–bar spacing. One possible explanation is that positively skewed distributions occur only in channels lacking distinct pool–bar topography or only at lower discharges in pool–bar channels. A series of flume experiments using fluorescent tracers was used to measure path length distributions in low‐sinuosity meandering channels to assess the relation with channel morphology and flow conditions. At channel‐forming flows, 55 to 75 per cent of the tracer grains were deposited on the first point bar downstream of the point of tracer input, with 15 per cent passing beyond the first bar. Path length distributions are symmetrical with mean equal to the pool–bar spacing and can be described with a Cauchy distribution. In some cases there was a secondary mode close to the point of tracer introduction; this bimodal distribution fits a combined gamma–Cauchy distribution. Only when discharge was reduced below the channel‐forming flow were frequency distributions unimodal and positively skewed with no relation to the pool–bar spacing. Thus, path length distributions become more symmetrical, and mean path length increases to coincide with pool–bar spacing, as flow approaches channel‐forming conditions. This is a substantial modification of existing models of particle transfer in gravel‐bed rivers. Copyright © 2003 John Wiley & Sons, Ltd.