Source Localizations Research Articles

A novel, robust, and portable platform for magnetoencephalography using optically-pumped magnetometers.

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of "OPM-MEG" systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG is in its infancy with existing limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range. We show that this system produces equivalent measures compared with an established OPM-MEG instrument; specifically, when measuring task-induced beta-band, gamma-band, and evoked neuro-electrical responses, source localisations from the two systems were comparable and temporal correlation of measured brain responses was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG and offers an attractive platform for next generation functional medical imaging.

Closely related species differ in their traits, but competition induces high intra-specific variability.

Theories explaining community assembly assume that biotic and abiotic filters sort species into communities based on the values of their traits and are thus based on between-species trait variability (BTV). Nevertheless, these filters act on individuals rather than on species. Consequently, the selection is also influenced by intraspecific trait variability (ITV) and its drivers. These drivers may be abiotic (e.g., water availability) or biotic (e.g., competition). Although closely related species should have similar traits, many of them coexist. We investigated the relative magnitudes of BTV and ITV in coexisting closely related species and how their individual traits differ under different drivers of ITV. We manipulated conditions in a greenhouse pot experiment with four common Carex species, where individuals of each species originated from four source localities. Individuals were grown in factorial combinations of two moisture levels, with and without a competitor (grass species Holcus lanatus, a frequent competitor). We analyzed the variability of six morphological traits on individuals in the greenhouse and three morphological traits in the source localities. Species identity was the main determinant of differences in most traits. Competition exerted a greater effect than water availability. For leaf dry matter content (LDMC) and vegetative height, competition's effect even exceeded the variability among species. On the contrary, for specific leaf area (SLA) and clonal spread, the interspecific differences exceeded ITV induced by experimental treatments. SLA measured in the greenhouse closely correlated with values measured in field populations, while LDMC did not. The variability caused by source locality of ramets in the greenhouse was small, although sometimes significant. Closely related species differ in their traits, but for some traits, ITV can exceed BTV. We can expect that ITV can modify the processes of community assembly, particularly among coexisting closely related species.

Gridless mixed-field sources localisation algorithm based on covariance matrix reconstruction

Gridless mixed-field sources localisation algorithm based on covariance matrix reconstruction

P.050 Spike source localizations between the three non-REM sleep stages: resemblances to wakefulness and distinctions from REM sleep

Background: Sleep-wake states (SWS) affect the expression of interictal epileptiform discharges (“spikes”), which affects resultant source localization calculations used in epilepsy evaluation. We hypothesize that spike localizations from non-REM sleep 1-3 are most concordant with one another. Methods: We used Standardized low-resolution brain electromagnetic tomography (sLORETA) in Curry 8 software to calculate source localization voxels of spikes in N1-3, REM, or wakefulness (W). We assessed voxel concordance between N1-N2-N3/N1-N2-W/N1-N3-W/N2-N3-W/REM-N1-N2/REM-N1-N3/REM-N2-N3/REM-N1-W/REM-N2-W/REM-N3-W. We classified concordances into those containing and not containing a SWS (e.g. N1 vs. not-N1 = N1-N2-N3/N1-N2-W/N1-N3-W/REM-N1-N2/REM-N1-N3/REM-N1-W vs. REM-N2-W/REM-N3-W/REM-N2-N3/N2-N3-W) for comparison. Results: Concordances did not differ for N1-3 or W. However, concordances with REM were lower than those without REM as a fraction of source localization space (median 32.1% vs. 56.1%, p<0.001) and cortical grey matter (median 20.4% vs. 27.3%, p=0.003). Conclusions: As expected, source localizations from spikes in N1, N2, and N3 did not significantly differ from one another because these three states are constituent members of non-REM sleep. Surprisingly, however, source localizations derived from awake spikes – not a constituent of non-REM sleep – also did not differ. In contrast, REM was most different by reproducibly exhibiting the least three-way concordance. These findings reinforce the unique localizing ability of REM sleep.

Classification of motor imagery using chaotic entropy based on sub-band EEG source localization

Objective. Electroencephalography (EEG) has been widely used in motor imagery (MI) research by virtue of its high temporal resolution and low cost, but its low spatial resolution is still a major criticism. The EEG source localization (ESL) algorithm effectively improves the spatial resolution of the signal by inverting the scalp EEG to extrapolate the cortical source signal, thus enhancing the classification accuracy. Approach. To address the problem of poor spatial resolution of EEG signals, this paper proposed a sub-band source chaotic entropy feature extraction method based on sub-band ESL. Firstly, the preprocessed EEG signals were filtered into 8 sub-bands. Each sub-band signal was source localized respectively to reveal the activation patterns of specific frequency bands of the EEG signals and the activities of specific brain regions in the MI task. Then, approximate entropy, fuzzy entropy and permutation entropy were extracted from the source signal as features to quantify the complexity and randomness of the signal. Finally, the classification of different MI tasks was achieved using support vector machine. Main result. The proposed method was validated on two MI public datasets (brain–computer interface (BCI) competition III IVa, BCI competition IV 2a) and the results showed that the classification accuracies were higher than the existing methods. Significance. The spatial resolution of the signal was improved by sub-band EEG localization in the paper, which provided a new idea for EEG MI research.

Electrocortical correlates of attention differentiate individual capacity in associative learning

Associative learning abilities vary considerably among individuals, with attentional processes suggested to play a role in these variations. However, the relationship between attentional processes and individual differences in associative learning remains unclear, and whether these variations reflect in event-related potentials (ERPs) is unknown. This study aimed to investigate the relationship between attentional processes and associative learning by recording electrocortical activity of 38 young adults (18–32 years) during an associative learning task. Learning performance was assessed using the signal detection index d’. EEG topographic analyses and source localizations were applied to examine the neural correlates of attention and associative learning. Results revealed that better learning scores are associated with (1) topographic differences during early (126–148 ms) processing of the stimulus, coinciding with a P1 ERP component, which corresponded to a participation of the precuneus (BA 7), (2) topographic differences at 573–638 ms, overlapping with an increase of global field power at 530–600 ms, coinciding with a P3b ERP component and localized within the superior frontal gyrus (BA11) and (3) an increase of global field power at 322–507 ms, underlay by a stronger participation of the middle occipital gyrus (BA 19). These insights into the neural mechanisms underlying individual differences in associative learning suggest that better learners engage attentional processes more efficiently than weaker learners, making more resources available and displaying increased functional activity in areas involved in early attentional processes (BA7) and decision-making processes (BA11) during an associative learning task. This highlights the crucial role of attentional mechanisms in individual learning variability.

Global sensitivity of EEG source analysis to tissue conductivity uncertainties.

To reliably solve the EEG inverse problem, accurate EEG forward solutions based on a detailed, individual volume conductor model of the head are essential. A crucial-but often neglected-aspect in generating a volume conductor model is the choice of the tissue conductivities, as these may vary from subject to subject. In this study, we investigate the sensitivity of EEG forward and inverse solutions to tissue conductivity uncertainties for sources distributed over the whole cortex surface. We employ a detailed five-compartment head model distinguishing skin, skull, cerebrospinal fluid, gray matter, and white matter, where we consider uncertainties of skin, skull, gray matter, and white matter conductivities. We use the finite element method (FEM) to calculate EEG forward solutions and goal function scans (GFS) as inverse approach. To be able to generate the large number of EEG forward solutions, we employ generalized polynomial chaos (gPC) expansions. For sources up to a depth of 4 cm, we find the strongest influence on the signal topography of EEG forward solutions for the skull conductivity and a notable effect for the skin conductivity. For even deeper sources, e.g., located deep in the longitudinal fissure, we find an increasing influence of the white matter conductivity. The conductivity variations translate to varying source localizations particularly for quasi-tangential sources on sulcal walls, whereas source localizations of quasi-radial sources on the top of gyri are less affected. We find a strong correlation between skull conductivity and the variation of source localizations and especially the depth of the reconstructed source for quasi-tangential sources. We furthermore find a clear but weaker correlation between depth of the reconstructed source and the skin conductivity. Our results clearly show the influence of tissue conductivity uncertainties on EEG source analysis. We find a particularly strong influence of skull and skin conductivity uncertainties.

Experimental and numerical comparison of multiple passive beamformers for separating intra- and extra-canal cavitation activity during transvertebral spinal cord therapy

Distinguishing intra-canal cavitation activity during transvertebral focused ultrasound sonication of the spinal cord is a challenge due to the strong prefocal cavitation emissions in the spinalis musculature overwhelming emissions originating in the canal. To achieve mapping of all cavitation sources simultaneously, two methods for enhancing detection sensitivity are investigated: (1) multiple dynamic ranges within a reconstructed volume and (2) utilizing alternative beamformers to delay-and-sum (DAS) during map reconstruction. The performance of DAS beamforming is compared to a delay-multiply and-sum beamformer (DMAS), with and without a paired multiplicative compounding method (pDMAS). Experiments and simulations were performed on a 128-element, dual-aperture transvertebral array, through stacks of ex vivo human vertebra. Numerically and experimentally obtained point spread functions were compared in 3D, producing voxel-wise cross correlation values of 0.84, 0.89, 0.97 (N = 1) for the beamformers listed above, respectively, in water. Experimental, transvertebral localizations of canal sources in isolation produced localization error of 2.8 ± 1.2, 2.9 ± 1.4, 2.7 ± 1.3 mm for a single vertebral target (N = 30 sonications), respectively. A large numerical data set investigating the prefocal cavitation problem (N > 160) is presented and compared with (N = 9) experimental data demonstrating enhancement of intracanal sensitivity in cavitation maps.

High-density electric source imaging patterns and outcomes following temporal lobectomy in patients with hippocampal sclerosis.

The objective of this study was to ascertain specific patterns of electrical source imaging (ESI) that are associated with a good surgical outcome (no seizure recurrence) using 256-channel high-density (HD) electroencephalography (EEG) in patients with temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) who underwent temporal lobectomy. Adult patients (age ≥ 18 years) were prospectively recruited from September 2016 to May 2020 at the authors' center. All patients underwent phase I presurgical evaluation and were subsequently advised to proceed with surgery based on consensus from a multidisciplinary epilepsy conference, without knowing HD-ESI results. All recruited patients were followed for at least 12 months after surgery. The outcome of interest was a status of no seizure recurrence, which was assessed at the end of the study. The association between ESI patterns and outcome was assessed using the chi-square or Fisher exact test. Associated p values as well as odds ratios and 95% CIs were reported. The diagnostic performance of the significant pattern associated with the outcome was also evaluated. Fifty-eight patients with known predictors for either good or worse surgical outcomes were recruited. The mean postoperative follow-up period was 33.34 (SD 13.88) months. Forty-seven patients had sufficient interictal epileptiform discharges for HD-ESI analysis. Thirteen of these 47 patients experienced seizure recurrence. The most common source localizations were at Brodmann area (BA) 20 (inferior temporal area) and BA 21 (middle temporal area). A specific ESI pattern of BA 21 without extratemporal sources was significantly associated with no seizure recurrence (p = 0.047). This pattern had a high positive predictive value of 100% and false-positive rate of 0% associated with no seizure recurrence following the surgery. A specific ESI pattern that was highly associated with no seizure recurrence following surgery was demonstrated by a 256-channel HD-EEG. If this pattern can be reproducibly proven in further studies, some TLE-HS patients may be able to proceed with surgery without further investigations.

The Induction of Religious Experiences and Temporal Lobe Activation: Neuronal Source Localization Using EEG Inverse Solutions

Knowledge about brain source localizations for religious states of mind is still limited. Previous studies have usually not set a direct emphasis on experience. The present study investigated the phenomenon of religious experience using inverse solution calculations, and it is one of the first to measure the dimension of experience directly. A total of 60 evangelical Christians participated in an experiment where they were asked to engage in worship and try to connect with God. Using a bar slider, the participants continuously rated how strongly they sensed God’s presence at any given moment. A selection of songs helped to induce the desired experience. Measurements were made using EEG with 64 electrodes and inverse solutions were calculated with sLORETA. We appropriated two mutually compatible hypotheses from the literature pertaining to religious experiences: the executive inhibition hypothesis (reformulated as the frontal relaxation hypothesis) and the temporal involvement hypothesis. Our results did not yield any information about the frontal areas; however, they indicated that the right temporal cortex appeared to be involved during the experience.

A review of Graph Neural Networks for Electroencephalography data analysis

Electroencephalography (EEG) sensors are flexible and non-invasive sensoring devices for the measurement of electrical brain activity which is extensively used in some areas of clinical practice and psychological/psychiatric research, such as epilepsy, sleep, emotion, and brain computer interfaces. Although EEG sensor do not provide actual brain localizations of the activity sources, they allow to study brain functional connectivity. In this paper we review current application of a specific family of computational methods, the Graph Neural Networks (GNN) to the analysis of EEG data. GNNs appear to be well suited to EEG data modeling as they deal with signals whose domain is defined by a graph instead of a regular lattice in Euclidean space. Readings of EEG electrodes fall in this category, hence the increasing research activity on the application of GNNs to EEG data.

Climate suitability analyses compare the distributions of invasive knotweeds in Europe and North America with the source localities of their introduced biological control agents.

Climate suitability analyses based on ecological niche modeling provide a powerful tool for biological control practitioners to assess the likelihood of establishment of different candidate agents prior to their introduction in the field. These same analyses could also be performed to understand why some agents establish more easily than others. The release of three strains of Aphalara itadori (Shinji) (Hemiptera: Pysllidae), each from a different source locality in Japan, for the biological control of invasive knotweed species, Reynoutria spp. Houtt. (Caryophyllales: Polygonaceae), provides an important opportunity to compare the utility of climate suitability analyses for identifying potential climate-based limitations for successful biological control introductions. Here, we predict climate suitability envelopes for three target species of knotweed in Europe and two target species of knotweed in North America and compare these suitability estimates for each of these species to the source localities of each A. itadori strain. We find that source locality of one strain, the Kyushu strain, has little-to-no suitability compared to other locations in Japan based on knotweed records from Europe, supporting an earlier study based on North American Japanese knotweed records. The source locality of a second strain, the Murakami strain, was predicted to have medium-to-high suitability based on records of knotweeds from North America. In contrast, European records of Reynoutria × bohemica Chrtek & Chrtková and Reynoutria sachalinensis (F. Schmidt) Nakai predicted no suitability for this locality compared to other locations in Japan, while European records for Reynoutria japonica Houtt. predicted low suitability. The source locality of the final strain, the Hokkaido strain, was predicted as having medium-to-high suitability based on knotweed records of all examined species from both North America and Europe.

Особенности биоэлектрической активности ретросплениальной коры головного мозга

Human brain is one of the most difficult organs to study. The possibility of developing the technologies that have sufficient scientific accuracy and economic accessibility and never violate the moral and ethical standards of human society is of great interest. The study was aimed to study the possibility of assessing the retrosplenial cortex (RSC) structures’ activity based on the EEG analysis of brain activity in the alpha frequency range in 36 healthy volunteers with an average age of 29.1 years, no acute central nervous system disorders or exacerbation of chronic central nervous system disorders, severe traumatic brain injuries, mental disorders or epilepsy. Significant source localizations were obtained by solving the EEG inverse problem that could be used for identification of the cerebral retrosplenial cortex structures’ bioelectric activity. The use of such technology will allow us to expand the scope of the research focused on assessing the brain functional activity in both research and clinical centers, thereby paving the way for understanding the features of the brain structures’ activity in physiologically normal conditions and in individuals with mental disorders caused by various functional alterations in the brain.

Invasion potential of hornets (Hymenoptera: Vespidae: Vespa spp.).

Hornets are large, predatory wasps that have the potential to alter biotic communities and harm honey bee colonies once established in non-native locations. Mated, diapausing females (gynes) can easily be transported to new habitats, where their behavioral flexibility allows them to found colonies using local food and nest materials. Of the 22 species in the genus Vespa, five species are now naturalized far from their endemic populations and another four have been detected either in nature or during inspections at borders of other countries. By far the most likely pathway of long-distance dispersal is the transport of gynes in transoceanic shipments of goods. Thereafter, natural dispersal of gynes in spring and accidental local transport by humans cause shorter-range expansions and contribute to the invasion process. Propagule pressure of hornets is unquantified, although it is likely low but unrelenting. The success of introduced populations is limited by low propagule size and the consequences of genetic founder effects, including the extinction vortex linked to single-locus, complementary sex determination of most hymenopterans. Invasion success is enhanced by climatic similarity between source locality and introduction site, as well as genetic diversity conferred by polyandry in some species. These and other factors that may have influenced the successful establishment of invasive populations of V. velutina, V. tropica, V. bicolor, V. orientalis, and V. crabro are discussed. The highly publicized detections of V. mandarinia in North America and research into its status provide a real-time example of an unfolding hornet invasion.

Application of Classified Elastic Waves for AE Source Localization Based on Self-Organizing Map

Acoustic emission (AE) source localization has been used to visualize progress failures generated in a wide variety of materials. In the conventional approaches, AE source localization algorithms assume that the AE signal is propagated as a straight line. However, it is supposed that progress failures form heterogeneity of elastic wave velocity distributions. Hence, with the conventional source localization, it is expected that the localization accuracy is reduced in heterogeneous materials since diffraction and refraction waves are generated. Thus, if the straight propagation waves are classified, conventional source localizations are performed in the heterogeneous materials. The self-organizing map (SOM) is one of the unsupervised learning methods, and the SOM has potential to classify straight propagation waves for the source localizations. However, the application of classified AE signals in source localization is not popular. If classified AE signals are applied to the time difference of arrival (TDOA) method, which is the popular localization method, it is expected that number of visualized sources are decreased because the algorithm does not consider the selection of the propagated wave. Although ray tracing has potential to localize a larger number of sources than the TDOA method, it is expected that the localized sources are less accurate in comparison with results of the TDOA method. In this study, classified waves were applied to two of the source localizations, and model tests based on pencil-lead breaks (PLBs) generating artificial AE sources were conducted to validate the performance of the source localizations with classified waves. The results of the validation confirmed that the maximum error in the TDOA method is larger in comparison with ray tracing conducted with 20 mm intervals of source candidates. Moreover, ray tracing localizes the same number of sources as the number of PLB tests. Therefore, ray tracing is expected to more practically localize AE sources than the TDOA method if classified waves are applied.

Effects of head modeling errors on the spatial frequency representation of MEG

Objectives. We aim to investigate the effects of head model inaccuracies on signal and source reconstruction accuracies for various sensor array distances to the head. This allows for the assessment of the importance of head modeling for next-generation magnetoencephalography (MEG) sensors, optically-pumped magnetometers (OPM). Approach. A 1-shell boundary element method (BEM) spherical head model with 642 vertices of radius 9 cm and conductivity of 0.33 S m−1 was defined. The vertices were then randomly perturbed radially up to 2%, 4%, 6%, 8% and 10% of the radius. For each head perturbation case, the forward signal was calculated for dipolar sources located at 2 cm, 4 cm, 6 cm and 8 cm from the origin (center of the sphere), and for a 324 sensor array located at 10 cm to 15 cm from the origin. Equivalent current dipole (ECD) source localization was performed for each of these forward signals. The signal for each perturbed spherical head case was then analyzed in the spatial frequency domain, and the signal and ECD errors were quantified relative to the unperturbed case. Main results. In the noiseless and high signal-to-noise ratio (SNR) case of approximately ≥6 dB, inaccuracies in our spherical BEM head conductor models lead to increased signal and ECD inaccuracies when sensor arrays are placed closer to the head. This is true especially in the case of deep and superficial sources. In the noisy case however, the higher SNR for closer sensor arrays allows for an improved ECD fit and outweighs the effects of head geometry inaccuracies. Significance. OPMs may be placed directly on the head, as opposed to the more commonly used superconducting quantum interference device sensors which must be placed a few centimeters away from the head. OPMs thus allow for signals of higher spatial resolution to be captured, resulting in potentially more accurate source localizations. Our results suggest that an increased emphasis on accurate head modeling for OPMs may be necessary to fully realize its improved source localization potential.

Brain Connectivity Signature Extractions from TMS Invoked EEGs.

(1) Background: The correlations between brain connectivity abnormality and psychiatric disorders have been continuously investigated and progressively recognized. Brain connectivity signatures are becoming exceedingly useful for identifying patients, monitoring mental health disorders, and treatment. By using electroencephalography (EEG)-based cortical source localization along with energy landscape analysis techniques, we can statistically analyze transcranial magnetic stimulation (TMS)-invoked EEG signals, for obtaining connectivity among different brain regions at a high spatiotemporal resolution. (2) Methods: In this study, we analyze EEG-based source localized alpha wave activity in response to TMS administered to three locations, namely, the left motor cortex (49 subjects), left prefrontal cortex (27 subjects), and the posterior cerebellum, or vermis (27 subjects) by using energy landscape analysis techniques to uncover connectivity signatures. We then perform two sample t-tests and use the (5 × 10-5) Bonferroni corrected p-valued cases for reporting six reliably stable signatures. (3) Results: Vermis stimulation invoked the highest number of connectivity signatures and the left motor cortex stimulation invoked a sensorimotor network state. In total, six out of 29 reliable, stable connectivity signatures are found and discussed. (4) Conclusions: We extend previous findings to localized cortical connectivity signatures for medical applications that serve as a baseline for future dense electrode studies.

An annotated checklist of Australian Mesozoic tetrapods

In 2020, the Australasian palaeontological association Australasian Palaeontologists (AAP) joined the Australian government-supported Australian National Species List (auNSL) initiative to compile the first Australian Fossil National Species List (auFNSL) for the region. The goal is to assemble comprehensive systematic data on all vertebrate, invertebrate and plant fossil taxa described to date, and to present the information both within a continuously updated open-access online framework, and as a series of primary reference articles in AAP’s flagship journal Alcheringa. This paper spearheads these auFNSL Alcheringa publications with an annotated checklist of Australian Mesozoic tetrapods. Complete synonymy, type material, source locality, geological age and bibliographical information are provided for 111 species formally named as of 2022. In addition, chronostratigraphically arranged inventories of all documented Australian Mesozoic tetrapod fossil occurrences are presented with illustrations of significant, exceptionally preserved and/or diagnostic specimens. The most diverse order-level clades include temnospondyl amphibians (34 species), saurischian (13 species) and ornithischian (12 species) dinosaurs (excluding ichnotaxa), and plesiosaurian marine reptiles (11 species). However, numerous other groups collectively span the earliest Triassic (earliest Induan) to Late Cretaceous (late Maastrichtian) and incorporate antecedents of modern Australian lineages, such as chelonioid and chelid turtles and monotreme mammals. Although scarce in comparison to records from other continents, Australia’s Mesozoic tetrapod assemblages are globally important because they constitute higher-palaeolatitude faunas that evince terrestrial and marine ecosystem evolution near the ancient South Pole. The pace of research on these assemblages has also accelerated substantially over the last 20 years, and serves to promote fossil geoheritage as an asset for scientific, cultural and economic development. The auFNSL augments the accessibility and utility of these palaeontological resources and provides a foundation for ongoing exploration into Australia’s unique natural history. Stephen F. Poropat [stephenfporopat@gmail.com], Western Australian Organic and Isotope Geochemistry Centre, School of Earth and Planetary Science, Curtin University, Bentley, Western Australia 6102, Australia, and Australian Age of Dinosaurs Museum of Natural History, Lot 1 Dinosaur Drive, Winton, Queensland 4735, Australia; Phil R. Bell [pbell23@une.edu.au], Palaeoscience Research Centre, School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia; Lachlan J. Hart [l.hart@unsw.edu.au], Earth and Sustainability Science Research Centre, School of Biological, Earth and Environmental Sciences (BEES), University of New South Wales, Kensington, New South Wales 2052, Australia, and Australian Museum Research Institute, 1 William Street, Sydney, New South Wales 2010, Australia; Steven W. Salisbury [s.salisbury@uq.edu.au] School of Biological Sciences, The University of Queensland, Brisbane, Queensland 4072, Australia; Benjamin P. Kear [benjamin.kear@em.uu.se] The Museum of Evolution, Uppsala University, Norbyvägen 16, Uppsala SE-752 36, Sweden.

Sound source localization based on residual network and channel attention module

This paper presents a sound source localization (SSL) model based on residual network and channel attention mechanism. The method takes the combination of log-Mel spectrogram and generalized cross-correlation phase transform (GCC-PHAT) as the input features, and extracts the time–frequency information by using the residual structure and channel attention mechanism, thus obtaining a better localizing performance. The residual blocks are introduced to extract deeper features, which can stack more layers for high-level features and avoid gradient vanishing or exploding at the same time. The attention mechanism is taken into account for the feature extraction stage in the proposed SSL model, which can focus on the most important information on the input features. We use the signals collected by microphone array to explore the performance of the model under different features, and find the most suitable input features of the proposed method. We compare our method with other models on public dataset. Experience results show a quite substantial improvement of sound source localizing performance.

Where should they come from? Where should they go? Several measures of seed source locality fail to predict plant establishment in early prairie restorations

AbstractDuring the “decade on restoration,” we must understand how to reliably re‐establish native plant populations. When establishing populations through seed addition, practitioners often prioritize obtaining seed from locations geographically near the restoration site (i.e. “local seed sourcing”). They are assumed to be under similar environmental conditions to the restoration site and should establish more robust plant populations and preserve local biotic interactions better than seeds sourced from further away. However, this assumption remains virtually untested in realistic restoration settings and the importance of seed sourcing, relative to other factors such as seeding rate and management regimes, is unclear.To determine if seed sourcing decision impacts plant establishment, abundance and phenology, we developed a partnership between university‐researchers and a native seed producer that kept records on where their seed was sourced from and where it was planted. At each site, we recorded the abundance and phenological stage of five commonly used tallgrass prairie restoration species seeded at 24 sites undergoing restoration across Michigan. We considered two measures of seed source locality: geographic distance (seeds were sourced from locations 6–750 km away from their respective restoration sites) and environmental distance. We also obtained data on the seeding rate and post‐seeding management at each site.We found that no measure of seed source locality predicted the likelihood of plant establishment or abundance at restoration sites. However, sites sown with seed from further away, or from cooler and wetter climates, had a greater proportion of flowering individuals earlier in the season. Finally, sites with higher seeding rates had greater plant abundance, and post‐seeding management of the restoration site increased the likelihood a species would establish by 36%.Overall, these results support that seed sourcing decisions did not impact plant establishment or abundance in our system. However, using less‐local seed sources may alter flowering phenology.Our results suggest that tallgrass prairie restoration efforts should prioritize higher seeding rates, post‐seeding management, and might expand the region seed sources are considered “local”, though this may impact flowering phenology. Future research leveraging native seed producer records can help answer critical questions about restoration seed sourcing.