Single trial Bayesian inference by population vector readout in the barn owl's sound localization system.

Bayesian models have proven effective in characterizing perception, behavior, and neural encoding across diverse species and systems. The neural implementation of Bayesian inference in the barn owl's sound localization system and behavior has been previously explained by a non-uniform population code model. This model specifies the neural population activity pattern required for a population vector readout to match the optimal Bayesian estimate. While prior analyses focused on trial-averaged comparisons of model predictions with behavior and single-neuron responses, it remains unknown whether this model can accurately approximate Bayesian inference on single trials under varying sensory reliability, a fundamental condition for natural perception and behavior. In this study, we utilized mathematical analysis and simulations to demonstrate that decoding a non-uniform population code via a population vector readout approximates the Bayesian estimate on single trials for varying sensory reliabilities. Our findings provide additional support for the non-uniform population code model as a viable explanation for the barn owl's sound localization pathway and behavior.

Diverse processing underlying frequency integration in midbrain neurons of barn owls.

Emergent response properties of sensory neurons depend on circuit connectivity and somatodendritic processing. Neurons of the barn owl's external nucleus of the inferior colliculus (ICx) display emergence of spatial selectivity. These neurons use interaural time difference (ITD) as a cue for the horizontal direction of sound sources. ITD is detected by upstream brainstem neurons with narrow frequency tuning, resulting in spatially ambiguous responses. This spatial ambiguity is resolved by ICx neurons integrating inputs over frequency, a relevant processing in sound localization across species. Previous models have predicted that ICx neurons function as point neurons that linearly integrate inputs across frequency. However, the complex dendritic trees and spines of ICx neurons raises the question of whether this prediction is accurate. Data from in vivo intracellular recordings of ICx neurons were used to address this question. Results revealed diverse frequency integration properties, where some ICx neurons showed responses consistent with the point neuron hypothesis and others with nonlinear dendritic integration. Modeling showed that varied connectivity patterns and forms of dendritic processing may underlie observed ICx neurons' frequency integration processing. These results corroborate the ability of neurons with complex dendritic trees to implement diverse linear and nonlinear integration of synaptic inputs, of relevance for adaptive coding and learning, and supporting a fundamental mechanism in sound localization.

Barn Owl's Auditory Space Map Activity Matching Conditions for a Population Vector Readout to Drive Adaptive Sound-Localizing Behavior.

Space-specific neurons in the owl's midbrain form a neural map of auditory space, which supports sound-orienting behavior. Previous work proposed that a population vector (PV) readout of this map, implementing statistical inference, predicts the owl's sound localization behavior. This model also predicts the frontal localization bias normally observed and how sound-localizing behavior changes when the signal-to-noise ratio varies, based on the spread of activity across the map. However, the actual distribution of population activity and whether this pattern is consistent with premises of the PV readout model on a trial-by-trial basis remains unknown. To answer these questions, we investigated whether the population response profile across the midbrain map in the optic tectum of the barn owl matches these predictions using in vivo multielectrode array recordings. We found that response profiles of recorded subpopulations are sufficient for estimating the stimulus interaural time difference using responses from single trials. Furthermore, this decoder matches the expected differences in trial-by-trial variability and frontal bias between stimulus conditions of low and high signal-to-noise ratio. These results support the hypothesis that a PV readout of the midbrain map can mediate statistical inference in sound-localizing behavior of barn owls.SIGNIFICANCE STATEMENT While the tuning of single neurons in the owl's midbrain map of auditory space has been considered predictive of the highly specialized sound-localizing behavior of this species, response properties across the population remain largely unknown. For the first time, this study analyzed the spread of population responses across the map using multielectrode recordings and how it changes with signal-to-noise ratio. The observed responses support the hypothesis concerning the ability of a population vector readout to predict biases in orienting behaviors and mediate uncertainty-dependent behavioral commands. The results are of significance for understanding potential mechanisms for the implementation of optimal behavioral commands across species.

School-based gardening, cooking and nutrition intervention increased vegetable intake but did not reduce BMI: Texas sprouts - a cluster randomized controlled trial.

BACKGROUND: Although school garden programs have been shown to improve dietary behaviors, there has not been a cluster-randomized controlled trial (RCT) conducted to examine the effects of school garden programs on obesity or other health outcomes. The goal of this study was to evaluate the effects of a one-year school-based gardening, nutrition, and cooking intervention (called Texas Sprouts) on dietary intake, obesity outcomes, and blood pressure in elementary school children. METHODS: This study was a school-based cluster RCT with 16 elementary schools that were randomly assigned to either the Texas Sprouts intervention (n = 8 schools) or to control (delayed intervention, n = 8 schools). The intervention was one school year long (9 months) and consisted of: a) Garden Leadership Committee formation; b) a 0.25-acre outdoor teaching garden; c) 18 student gardening, nutrition, and cooking lessons taught by trained educators throughout the school-year; and d) nine monthly parent lessons. The delayed intervention was implemented the following academic year and received the same protocol as the intervention arm. Child outcomes measured were anthropometrics (i.e., BMI parameters, waist circumference, and body fat percentage via bioelectrical impedance), blood pressure, and dietary intake (i.e., vegetable, fruit, and sugar sweetened beverages) via survey. Data were analyzed with complete cases and with imputations at random. Generalized weighted linear mixed models were used to test the intervention effects and to account for clustering effect of sampling by school. RESULTS: A total of 3135 children were enrolled in the study (intervention n = 1412, 45%). Average age was 9.2 years, 64% Hispanic, 47% male, and 69% eligible for free and reduced lunch. The intervention compared to control resulted in increased vegetable intake (+ 0.48 vs. + 0.04 frequency/day, p = 0.02). There were no effects of the intervention compared to control on fruit intake, sugar sweetened beverages, any of the obesity measures or blood pressure. CONCLUSION: While this school-based gardening, nutrition, and cooking program did not reduce obesity markers or blood pressure, it did result in increased vegetable intake. It is possible that a longer and more sustained effect of increased vegetable intake is needed to lead to reductions in obesity markers and blood pressure. CLINICAL TRIALS NUMBER: NCT02668744 .

Natural ITD statistics predict human auditory spatial perception.

A neural code adapted to the statistical structure of sensory cues may optimize perception. We investigated whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are parameters determining spatial discriminability. The natural ITD rate of change across azimuth (ITDrc) and ITD variability over time (ITDv) were combined in a Fisher information statistic to assess the amount of azimuthal information conveyed by this sensory cue. We hypothesized that natural ITD statistics underlie the neural code for ITD and thus influence spatial perception. To test this hypothesis, sounds with invariant statistics were presented to measure human spatial discriminability and spatial novelty detection. Human auditory spatial perception showed correlation with natural ITD statistics, supporting our hypothesis. Further analysis showed that these results are consistent with classic models of ITD coding and can explain the ITD tuning distribution observed in the mammalian brainstem.

When a person hears a sound, how do they work out where it is coming from? A sound coming from your right will reach your right ear a few fractions of a millisecond earlier than your left. The brain uses this difference, known as the interaural time difference or ITD, to locate the sound. But humans are also much better at localizing sounds that come from sources in front of them than from sources by their sides. This may be due in part to differences in the number of neurons available to detect sounds from these different locations. It may also reflect differences in the rates at which those neurons fire in response to sounds. But these factors alone cannot explain why humans are so much better at localizing sounds in front of them. Pavão et al. showed that the brain has evolved the ability to detect natural patterns that exist in sounds as a result of their location, and to use those patterns to optimize the spatial perception of sounds. Pavão et al. showed that the way in which the head and inner ear filter incoming sounds has two consequences for how we perceive them. Firstly, the change in ITD for sounds coming from different sources in front of a person is greater than for sounds coming from their sides. And secondly, the ITD for sounds that originate in front of a person varies more over time than the ITD for sounds coming from the periphery. By playing sounds to healthy volunteers while removing these differences, Pavão et al. found that natural ITD statistics were correlated with a person's ability to tell where a sound was coming from. By revealing the features the brain uses to determine the location of sounds, the work of Pavão et al. could ultimately lead to the development of more effective hearing aids. The results also provide clues to how other senses, including vision, may have evolved to respond optimally to the environment.

Synthesis of Hemispheric ITD Tuning from the Readout of a Neural Map: Commonalities of Proposed Coding Schemes in Birds and Mammals.

A major cue to infer sound direction is the difference in arrival time of the sound at the left and right ears, called interaural time difference (ITD). The neural coding of ITD and its similarity across species have been strongly debated. In the barn owl, an auditory specialist relying on sound localization to capture prey, ITDs within the physiological range determined by the head width are topographically represented at each frequency. The topographic representation suggests that sound direction may be inferred from the location of maximal neural activity within the map. Such topographical representation of ITD, however, is not evident in mammals. Instead, the preferred ITD of neurons in the mammalian brainstem often lies outside the physiological range and depends on the neuron's best frequency. Because of these disparities, it has been assumed that how spatial hearing is achieved in birds and mammals is fundamentally different. However, recent studies reveal ITD responses in the owl's forebrain and midbrain premotor area that are consistent with coding schemes proposed in mammals. Particularly, sound location in owls could be decoded from the relative firing rates of two broadly and inversely ITD-tuned channels. This evidence suggests that, at downstream stages, the code for ITD may not be qualitatively different across species. Thus, while experimental evidence continues to support the notion of differences in ITD representation across species and brain regions, the latest results indicate notable commonalities, suggesting that codes driving orienting behavior in mammals and birds may be comparable.

Successful Extracorporeal Membrane Oxygenation (ECMO) Use without Systemic Anticoagulation for Acute Respiratory Distress Syndrome in a Patient with Aneurysmal Subarachnoid Hemorrhage.

Extracorporeal membrane oxygenation (ECMO) is an important life-saving technology for patients with severe acute respiratory distress syndrome (ARDS). Unfortunately, ECMO has been traditionally contraindicated in patients with hemorrhagic neurologic diseases. The recent improvement in ECMO devices, increased utilization and experience with venovenous ECMO technologies among healthcare teams, and the use of ECMO without anticoagulation has expanded the potential populations that may benefit from ECMO. We present a case of successful utilization of venovenous ECMO for severe respiratory failure secondary to ARDS in a patient with aneurysmal subarachnoid hemorrhage and severe, episodic cerebral vasospasm. We also discuss important limitations and considerations for future successful use of ECMO in hemorrhagic stroke. This case report highlights the potential for this life-saving technology in patients with hemorrhagic stroke.

Multidimensional stimulus encoding in the auditory nerve of the barn owl.

Auditory perception depends on multi-dimensional information in acoustic signals that must be encoded by auditory nerve fibers (ANF). These dimensions are represented by filters with different frequency selectivities. Multiple models have been suggested; however, the identification of relevant filters and type of interactions has been elusive, limiting progress in modeling the cochlear output. Spike-triggered covariance analysis of barn owl ANF responses was used to determine the number of relevant stimulus filters and estimate the nonlinearity that produces responses from filter outputs. This confirmed that ANF responses depend on multiple filters. The first, most dominant filter was the spike-triggered average, which was excitatory for all neurons. The second and third filters could be either suppressive or excitatory with center frequencies above or below that of the first filter. The nonlinear function mapping the first two filter outputs to the spiking probability ranged from restricted to nearly circular-symmetric, reflecting different modes of interaction between stimulus dimensions across the sample. This shows that stimulus encoding in ANFs of the barn owl is multidimensional and exhibits diversity over the population, suggesting that models must allow for variable numbers of filters and types of interactions between filters to describe how sound is encoded in ANFs.

Emergence of an Adaptive Command for Orienting Behavior in Premotor Brainstem Neurons of Barn Owls.

The midbrain map of auditory space commands sound-orienting responses in barn owls. Owls precisely localize sounds in frontal space but underestimate the direction of peripheral sound sources. This bias for central locations was proposed to be adaptive to the decreased reliability in the periphery of sensory cues used for sound localization by the owl. Understanding the neural pathway supporting this biased behavior provides a means to address how adaptive motor commands are implemented by neurons. Here we find that the sensory input for sound direction is weighted by its reliability in premotor neurons of the midbrain tegmentum of owls (male and female), such that the mean population firing rate approximates the head-orienting behavior. We provide evidence that this coding may emerge through convergence of upstream projections from the midbrain map of auditory space. We further show that manipulating the sensory input yields changes predicted by the convergent network in both premotor neural responses and behavior. This work demonstrates how a topographic sensory representation can be linearly read out to adjust behavioral responses by the reliability of the sensory input.SIGNIFICANCE STATEMENT This research shows how statistics of the sensory input can be integrated into a behavioral command by readout of a sensory representation. The firing rate of midbrain premotor neurons receiving sensory information from a topographic representation of auditory space is weighted by the reliability of sensory cues. We show that these premotor responses are consistent with a weighted convergence from the topographic sensory representation. This convergence was also tested behaviorally, where manipulation of stimulus properties led to bidirectional changes in sound localization errors. Thus a topographic representation of auditory space is translated into a premotor command for sound localization that is modulated by sensory reliability.

Fixation Strength of Polyetheretherketone Sheath-and-Bullet Device for Soft Tissue Repair in the Foot and Ankle.

Tendon transfers are often performed in the foot and ankle. Recently, interference screws have been a popular choice owing to their ease of use and fixation strength. Considering the benefits, one disadvantage of such devices is laceration of the soft tissues by the implant threads during placement that potentially weaken the structural integrity of the grafts. A shape memory polyetheretherketone bullet-in-sheath tenodesis device uses circumferential compression, eliminating potential damage from thread rotation and maintaining the soft tissue orientation of the graft. The aim of this study was to determine the pullout strength and failure mode for this device in both a synthetic bone analogue and porcine bone models. Thirteen mature bovine extensor tendons were secured into ten 4.0 × 4.0 × 4.0-cm cubes of 15-pound per cubic foot solid rigid polyurethane foam bone analogue models or 3 porcine femoral condyles using the 5 × 20-mm polyetheretherketone soft tissue anchor. The bullet-in-sheath device demonstrated a mean pullout of 280.84 N in the bone analog models and 419.47 N in the porcine bone models. (p = .001). The bullet-in-sheath design preserved the integrity of the tendon graft, and none of the implants dislodged from their original position.

Optimal nonlinear cue integration for sound localization.

Integration of multiple sensory cues can improve performance in detection and estimation tasks. There is an open theoretical question of the conditions under which linear or nonlinear cue combination is Bayes-optimal. We demonstrate that a neural population decoded by a population vector requires nonlinear cue combination to approximate Bayesian inference. Specifically, if cues are conditionally independent, multiplicative cue combination is optimal for the population vector. The model was tested on neural and behavioral responses in the barn owl's sound localization system where space-specific neurons owe their selectivity to multiplicative tuning to sound localization cues interaural phase (IPD) and level (ILD) differences. We found that IPD and ILD cues are approximately conditionally independent. As a result, the multiplicative combination selectivity to IPD and ILD of midbrain space-specific neurons permits a population vector to perform Bayesian cue combination. We further show that this model describes the owl's localization behavior in azimuth and elevation. This work provides theoretical justification and experimental evidence supporting the optimality of nonlinear cue combination.

Cue Reliability Represented in the Shape of Tuning Curves in the Owl's Sound Localization System.

Optimal use of sensory information requires that the brain estimates the reliability of sensory cues, but the neural correlate of cue reliability relevant for behavior is not well defined. Here, we addressed this issue by examining how the reliability of spatial cue influences neuronal responses and behavior in the owl's auditory system. We show that the firing rate and spatial selectivity changed with cue reliability due to the mechanisms generating the tuning to the sound localization cue. We found that the correlated variability among neurons strongly depended on the shape of the tuning curves. Finally, we demonstrated that the change in the neurons' selectivity was necessary and sufficient for a network of stochastic neurons to predict behavior when sensory cues were corrupted with noise. This study demonstrates that the shape of tuning curves can stand alone as a coding dimension of environmental statistics. SIGNIFICANCE STATEMENT: In natural environments, sensory cues are often corrupted by noise and are therefore unreliable. To make the best decisions, the brain must estimate the degree to which a cue can be trusted. The behaviorally relevant neural correlates of cue reliability are debated. In this study, we used the barn owl's sound localization system to address this question. We demonstrated that the mechanisms that account for spatial selectivity also explained how neural responses changed with degraded signals. This allowed for the neurons' selectivity to capture cue reliability, influencing the population readout commanding the owl's sound-orienting behavior.

Optimal Prediction of Moving Sound Source Direction in the Owl.

Capturing nature's statistical structure in behavioral responses is at the core of the ability to function adaptively in the environment. Bayesian statistical inference describes how sensory and prior information can be combined optimally to guide behavior. An outstanding open question of how neural coding supports Bayesian inference includes how sensory cues are optimally integrated over time. Here we address what neural response properties allow a neural system to perform Bayesian prediction, i.e., predicting where a source will be in the near future given sensory information and prior assumptions. The work here shows that the population vector decoder will perform Bayesian prediction when the receptive fields of the neurons encode the target dynamics with shifting receptive fields. We test the model using the system that underlies sound localization in barn owls. Neurons in the owl's midbrain show shifting receptive fields for moving sources that are consistent with the predictions of the model. We predict that neural populations can be specialized to represent the statistics of dynamic stimuli to allow for a vector read-out of Bayes-optimal predictions.

Neural representation of probabilities for Bayesian inference.

Bayesian models are often successful in describing perception and behavior, but the neural representation of probabilities remains in question. There are several distinct proposals for the neural representation of probabilities, but they have not been directly compared in an example system. Here we consider three models: a non-uniform population code where the stimulus-driven activity and distribution of preferred stimuli in the population represent a likelihood function and a prior, respectively; the sampling hypothesis which proposes that the stimulus-driven activity over time represents a posterior probability and that the spontaneous activity represents a prior; and the class of models which propose that a population of neurons represents a posterior probability in a distributed code. It has been shown that the non-uniform population code model matches the representation of auditory space generated in the owl's external nucleus of the inferior colliculus (ICx). However, the alternative models have not been tested, nor have the three models been directly compared in any system. Here we tested the three models in the owl's ICx. We found that spontaneous firing rate and the average stimulus-driven response of these neurons were not consistent with predictions of the sampling hypothesis. We also found that neural activity in ICx under varying levels of sensory noise did not reflect a posterior probability. On the other hand, the responses of ICx neurons were consistent with the non-uniform population code model. We further show that Bayesian inference can be implemented in the non-uniform population code model using one spike per neuron when the population is large and is thus able to support the rapid inference that is necessary for sound localization.

Spatial cue reliability drives frequency tuning in the barn Owl's midbrain.

The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owl's midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owl's space-specific neurons reflects a higher-order feature of the code that captures cue reliability.

Resolution of interaural time differences in the avian sound localization circuit-a modeling study.

Interaural time differences (ITDs) are a main cue for sound localization and sound segregation. A dominant model to study ITD detection is the sound localization circuitry in the avian auditory brainstem. Neurons in nucleus laminaris (NL) receive auditory information from both ears via the avian cochlear nucleus magnocellularis (NM) and compare the relative timing of these inputs. Timing of these inputs is crucial, as ITDs in the microsecond range must be discriminated and encoded. We modeled ITD sensitivity of single NL neurons based on previously published data and determined the minimum resolvable ITD for neurons in NL. The minimum resolvable ITD is too large to allow for discrimination by single NL neurons of naturally occurring ITDs for very low frequencies. For high frequency NL neurons (>1 kHz) our calculated ITD resolutions fall well within the natural range of ITDs and approach values of below 10 µs. We show that different parts of the ITD tuning function offer different resolution in ITD coding, suggesting that information derived from both parts may be used for downstream processing. A place code may be used for sound location at frequencies above 500 Hz, but our data suggest the slope of the ITD tuning curve ought to be used for ITD discrimination by single NL neurons at the lowest frequencies. Our results provide an important measure of the necessary temporal window of binaural inputs for future studies on the mechanisms and development of neuronal computation of temporally precise information in this important system. In particular, our data establish the temporal precision needed for conduction time regulation along NM axons.

Binaural gain modulation of spectrotemporal tuning in the interaural level difference-coding pathway.

In the brainstem, the auditory system diverges into two pathways that process different sound localization cues, interaural time differences (ITDs) and level differences (ILDs). We investigated the site where ILD is detected in the auditory system of barn owls, the posterior part of the lateral lemniscus (LLDp). This structure is equivalent to the lateral superior olive in mammals. The LLDp is unique in that it is the first place of binaural convergence in the brainstem where monaural excitatory and inhibitory inputs converge. Using binaurally uncorrelated noise and a generalized linear model, we were able to estimate the spectrotemporal tuning of excitatory and inhibitory inputs to these cells. We show that the response of LLDp neurons is highly locked to the stimulus envelope. Our data demonstrate that spectrotemporally tuned, temporally delayed inhibition enhances the reliability of envelope locking by modulating the gain of LLDp neurons' responses. The dependence of gain modulation on ILD shown here constitutes a means for space-dependent coding of stimulus identity by the initial stages of the auditory pathway.

Forced desynchrony reveals independent contributions of suprachiasmatic oscillators to the daily plasma corticosterone rhythm in male rats.

The suprachiasmatic nucleus (SCN) is required for the daily rhythm of plasma glucocorticoids; however, the independent contributions from oscillators within the different subregions of the SCN to the glucocorticoid rhythm remain unclear. Here, we use genetically and neurologically intact, forced desynchronized rats to test the hypothesis that the daily rhythm of the glucocorticoid, corticosterone, is regulated by both light responsive and light-dissociated circadian oscillators in the ventrolateral (vl-) and dorsomedial (dm-) SCN, respectively. We show that when the vlSCN and dmSCN are in maximum phase misalignment, the peak of the plasma corticosterone rhythm is shifted and the amplitude reduced; whereas, the peak of the plasma adrenocorticotropic hormone (ACTH) rhythm is also reduced, the phase is dissociated from that of the corticosterone rhythm. These data support previous studies suggesting an ACTH-independent pathway contributes to the corticosterone rhythm. To determine if either SCN subregion independently regulates corticosterone through the sympathetic nervous system, we compared unilateral adrenalectomized, desynchronized rats that had undergone either transection of the thoracic splanchnic nerve or sham transection to the remaining adrenal. Splanchnicectomy reduced and phase advanced the peak of both the corticosterone and ACTH rhythms. These data suggest that both the vlSCN and dmSCN contribute to the corticosterone rhythm by both reducing plasma ACTH and differentially regulating plasma corticosterone through an ACTH- and sympathetic nervous system-independent pathway.

Population-wide bias of surround suppression in auditory spatial receptive fields of the owl's midbrain.

The physical arrangement of receptive fields (RFs) within neural structures is important for local computations. Nonuniform distribution of tuning within populations of neurons can influence emergent tuning properties, causing bias in local processing. This issue was studied in the auditory system of barn owls. The owl's external nucleus of the inferior colliculus (ICx) contains a map of auditory space in which the frontal region is overrepresented. We measured spatiotemporal RFs of ICx neurons using spatial white noise. We found a population-wide bias in surround suppression such that suppression from frontal space was stronger. This asymmetry increased with laterality in spatial tuning. The bias could be explained by a model of lateral inhibition based on the overrepresentation of frontal space observed in ICx. The model predicted trends in surround suppression across ICx that matched the data. Thus, the uneven distribution of spatial tuning within the map could explain the topography of time-dependent tuning properties. This mechanism may have significant implications for the analysis of natural scenes by sensory systems.

Developmental validation of RSID™-Semen: a lateral flow immunochromatographic strip test for the forensic detection of human semen.

Tests for the identification of semen commonly involve the microscopic visualization of spermatozoa or assays for the presence of seminal markers such as acid phosphatase (AP) or prostate-specific antigen (PSA). Here, we describe the rapid stain identification kit for the identification of semen (RSID™-Semen), a lateral flow immunochromatographic strip test that uses two antihuman semenogelin monoclonal antibodies to detect the presence of semenogelin. The RSID™-Semen strip is specific for human semen, detecting <2.5 nL of semen, and does not cross-react with other human or nonhuman tissues tested. RSID™-Semen is more sensitive with certain forensic evidence samples containing mixtures of vaginal secretions and semen than either of the commercially available PSA-based forensic semen detection tests or tests that measure AP activity that were tested in parallel. The RSID™-Semen kit also allows sampling a fraction of a questioned stain while retaining the majority of the sample for further processing through short tandem repeat analysis.