Prediction of Muscle Activities from Electrocorticograms in Primary Motor Cortex of Primates

Electrocorticography (ECoG) has drawn attention as an effective recording approach for brain-machine interfaces (BMI). Previous studies have succeeded in classifying movement intention and predicting hand trajectories from ECoG. Despite such successes, however, there still remains considerable work for the realization of ECoG-based BMIs as neuroprosthetics. We developed a method to predict multiple muscle activities from ECoG measurements. We also verified that ECoG signals are effective for predicting muscle activities in time varying series when performing sequential movements. ECoG signals were band-pass filtered into separate sensorimotor rhythm bands, z-score normalized, and smoothed with a Gaussian filter. We used sparse linear regression to find the best fit between frequency bands of ECoG and electromyographic activity. The best average correlation coefficient and the normalized root-mean-square error were 0.92±0.06 and 0.06±0.10, respectively, in the flexor digitorum profundus finger muscle. The δ (1.5∼4Hz) and γ2 (50∼90Hz) bands contributed significantly more strongly than other frequency bands (P<0.001). These results demonstrate the feasibility of predicting muscle activity from ECoG signals in an online fashion.     

Prediction of Hand Trajectory from Electrocorticography Signals in Primary Motor Cortex

Due to their potential as a control modality in brain-machine interfaces, electrocorticography (ECoG) has received much focus in recent years. Studies using ECoG have come out with success in such endeavors as classification of arm movements and natural grasp types, regression of arm trajectories in two and three dimensions, estimation of muscle activity time series and so on. However, there still remains considerable work to be done before a high performance ECoG-based neural prosthetic can be realized. In this study, we proposed an algorithm to decode hand trajectory from 15 and 32 channel ECoG signals recorded from primary motor cortex (M1) in two primates. To determine the most effective areas for prediction, we applied two electrode selection methods, one based on position relative to the central sulcus (CS) and another based on the electrodes'' individual prediction performance. The best coefficients of determination for decoding hand trajectory in the two monkeys were 0.4815±0.0167 and 0.7780±0.0164. Performance results from individual ECoG electrodes showed that those with higher performance were concentrated at the lateral areas and areas close to the CS. The results of prediction according with different numbers of electrodes based on proposed methods were also shown and discussed. These results also suggest that superior decoding performance can be achieved from a group of effective ECoG signals rather than an entire ECoG array.     

Correcting for Strong Eddy Current Induced B0 Modulation Enables Two-Spoke RF Pulse Design with Parallel Transmission: Demonstration at 9.4T in the Human Brain

Successful implementation of homogeneous slice-selective RF excitation in the human brain at 9.4T using 16-channel parallel transmission (pTX) is demonstrated. A novel three-step pulse design method incorporating fast real-time measurement of eddy current induced B0 variations as well as correction of resulting phase errors during excitation is described. To demonstrate the utility of the proposed method, phantom and in-vivo experiments targeting a uniform excitation in an axial slice were conducted using two-spoke pTX pulses. Even with the pre-emphasis activated, eddy current induced B0 variations with peak-to-peak values greater than 4 kHz were observed on our system during the rapid switches of slice selective gradients. This large B0 variation, when not corrected, resulted in drastically degraded excitation fidelity with the coefficient of variation (CV) of the flip angle calculated for the region of interest being large (∼12% in the phantom and ∼35% in the brain). By comparison, excitation fidelity was effectively restored, and satisfactory flip angle uniformity was achieved when using the proposed method, with the CV value reduced to ∼3% in the phantom and ∼8% in the brain. Additionally, experimental results were in good agreement with the numerical predictions obtained from Bloch simulations. Slice-selective flip angle homogenization in the human brain at 9.4T using 16-channel 3D spoke pTX pulses is achievable despite of large eddy current induced excitation phase errors; correcting for the latter was critical in this success.     

Characterizing and Predicting Submovements during Human Three-Dimensional Arm Reaches

We have demonstrated that 3D target-oriented human arm reaches can be represented as linear combinations of discrete submovements, where the submovements are a set of minimum-jerk basis functions for the reaches. We have also demonstrated the ability of deterministic feed-forward Artificial Neural Networks (ANNs) to predict the parameters of the submovements. ANNs were trained using kinematic data obtained experimentally from five human participants making target-directed movements that were decomposed offline into minimum-jerk submovements using an optimization algorithm. Under cross-validation, the ANNs were able to accurately predict the parameters (initiation-time, amplitude, and duration) of the individual submovements. We also demonstrated that the ANNs can together form a closed-loop model of human reaching capable of predicting 3D trajectories with VAF >95.9% and RMSE ≤4.32 cm relative to the actual recorded trajectories. This closed-loop model is a step towards a practical arm trajectory generator based on submovements, and should be useful for the development of future arm prosthetic devices that are controlled by brain computer interfaces or other user interfaces.     

Giga-Pixel Lensfree Holographic Microscopy and Tomography Using Color Image Sensors

We report Giga-pixel lensfree holographic microscopy and tomography using color sensor-arrays such as CMOS imagers that exhibit Bayer color filter patterns. Without physically removing these color filters coated on the sensor chip, we synthesize pixel super-resolved lensfree holograms, which are then reconstructed to achieve ∼350 nm lateral resolution, corresponding to a numerical aperture of ∼0.8, across a field-of-view of ∼20.5 mm². This constitutes a digital image with ∼0.7 Billion effective pixels in both amplitude and phase channels (i.e., ∼1.4 Giga-pixels total). Furthermore, by changing the illumination angle (e.g., ±50°) and scanning a partially-coherent light source across two orthogonal axes, super-resolved images of the same specimen from different viewing angles are created, which are then digitally combined to synthesize tomographic images of the object. Using this dual-axis lensfree tomographic imager running on a color sensor-chip, we achieve a 3D spatial resolution of ∼0.35 µm×0.35 µm×∼2 µm, in x, y and z, respectively, creating an effective voxel size of ∼0.03 µm³ across a sample volume of ∼5 mm³, which is equivalent to >150 Billion voxels. We demonstrate the proof-of-concept of this lensfree optical tomographic microscopy platform on a color CMOS image sensor by creating tomograms of micro-particles as well as a wild-type C. elegans nematode.     

Autosomal Resequence Data Reveal Late Stone Age Signals of Population Expansion in Sub-Saharan African Foraging and Farming Populations

Background

A major unanswered question in the evolution of Homo sapiens is when anatomically modern human populations began to expand: was demographic growth associated with the invention of particular technologies or behavioral innovations by hunter-gatherers in the Late Pleistocene, or with the acquisition of farming in the Neolithic?

Methodology/Principal Findings

We investigate the timing of human population expansion by performing a multilocus analysis of≥20 unlinked autosomal noncoding regions, each consisting of ∼6 kilobases, resequenced in ∼184 individuals from 7 human populations. We test the hypothesis that the autosomal polymorphism data fit a simple two-phase growth model, and when the hypothesis is not rejected, we fit parameters of this model to our data using approximate Bayesian computation.

Conclusions/Significance

The data from the three surveyed non-African populations (French Basque, Chinese Han, and Melanesians) are inconsistent with the simple growth model, presumably because they reflect more complex demographic histories. In contrast, data from all four sub-Saharan African populations fit the two-phase growth model, and a range of onset times and growth rates is inferred for each population. Interestingly, both hunter-gatherers (San and Biaka) and food-producers (Mandenka and Yorubans) best fit models with population growth beginning in the Late Pleistocene. Moreover, our hunter-gatherer populations show a tendency towards slightly older and stronger growth (∼41 thousand years ago, ∼13-fold) than our food-producing populations (∼31 thousand years ago, ∼7-fold). These dates are concurrent with the appearance of the Late Stone Age in Africa, supporting the hypothesis that population growth played a significant role in the evolution of Late Pleistocene human cultures.     

An Electrocorticographic Brain Interface in an Individual with Tetraplegia

Brain-computer interface (BCI) technology aims to help individuals with disability to control assistive devices and reanimate paralyzed limbs. Our study investigated the feasibility of an electrocorticography (ECoG)-based BCI system in an individual with tetraplegia caused by C4 level spinal cord injury. ECoG signals were recorded with a high-density 32-electrode grid over the hand and arm area of the left sensorimotor cortex. The participant was able to voluntarily activate his sensorimotor cortex using attempted movements, with distinct cortical activity patterns for different segments of the upper limb. Using only brain activity, the participant achieved robust control of 3D cursor movement. The ECoG grid was explanted 28 days post-implantation with no adverse effect. This study demonstrates that ECoG signals recorded from the sensorimotor cortex can be used for real-time device control in paralyzed individuals.     

Comprehensive Characterization of Human Genome Variation by High Coverage Whole-Genome Sequencing of Forty Four Caucasians

Whole genome sequencing studies are essential to obtain a comprehensive understanding of the vast pattern of human genomic variations. Here we report the results of a high-coverage whole genome sequencing study for 44 unrelated healthy Caucasian adults, each sequenced to over 50-fold coverage (averaging 65.8×). We identified approximately 11 million single nucleotide polymorphisms (SNPs), 2.8 million short insertions and deletions, and over 500,000 block substitutions. We showed that, although previous studies, including the 1000 Genomes Project Phase 1 study, have catalogued the vast majority of common SNPs, many of the low-frequency and rare variants remain undiscovered. For instance, approximately 1.4 million SNPs and 1.3 million short indels that we found were novel to both the dbSNP and the 1000 Genomes Project Phase 1 data sets, and the majority of which (∼96%) have a minor allele frequency less than 5%. On average, each individual genome carried ∼3.3 million SNPs and ∼492,000 indels/block substitutions, including approximately 179 variants that were predicted to cause loss of function of the gene products. Moreover, each individual genome carried an average of 44 such loss-of-function variants in a homozygous state, which would completely “knock out” the corresponding genes. Across all the 44 genomes, a total of 182 genes were “knocked-out” in at least one individual genome, among which 46 genes were “knocked out” in over 30% of our samples, suggesting that a number of genes are commonly “knocked-out” in general populations. Gene ontology analysis suggested that these commonly “knocked-out” genes are enriched in biological process related to antigen processing and immune response. Our results contribute towards a comprehensive characterization of human genomic variation, especially for less-common and rare variants, and provide an invaluable resource for future genetic studies of human variation and diseases.     

Ion-Abrasion Scanning Electron Microscopy Reveals Surface-Connected Tubular Conduits in HIV-Infected Macrophages

HIV-1-containing internal compartments are readily detected in images of thin sections from infected cells using conventional transmission electron microscopy, but the origin, connectivity, and 3D distribution of these compartments has remained controversial. Here, we report the 3D distribution of viruses in HIV-1-infected primary human macrophages using cryo-electron tomography and ion-abrasion scanning electron microscopy (IA-SEM), a recently developed approach for nanoscale 3D imaging of whole cells. Using IA-SEM, we show the presence of an extensive network of HIV-1-containing tubular compartments in infected macrophages, with diameters of ∼150–200 nm, and lengths of up to ∼5 µm that extend to the cell surface from vesicular compartments that contain assembling HIV-1 virions. These types of surface-connected tubular compartments are not observed in T cells infected with the 29/31 KE Gag-matrix mutant where the virus is targeted to multi-vesicular bodies and released into the extracellular medium. IA-SEM imaging also allows visualization of large sheet-like structures that extend outward from the surfaces of macrophages, which may bend and fold back to allow continual creation of viral compartments and virion-lined channels. This potential mechanism for efficient virus trafficking between the cell surface and interior may represent a subversion of pre-existing vesicular machinery for antigen capture, processing, sequestration, and presentation.     

A Transport Model for Estimating the Time Course of ERK Activation in the C.?elegans Germline

The Caenorhabditis elegans germline is a well-studied model system for investigating the control of cell fate by signaling pathways. Cell signals at the distal tip of the germline promote cell proliferation; just before the loop, signals couple cell maturation to organism-level nutrient status; at the proximal end of the germline, signals coordinate oocyte maturation and fertilization in the presence of sperm. The latter two events require dual phosphorylation and activation of ERK, the effector molecule of the Ras/MAPK cascade. In C. elegans, ERK is known as MPK-1. At this point, none of today’s methods for real-time monitoring of dually phosphorylated MPK-1 are working in the germline. Consequently, quantitative understanding of the MPK-1-dependent processes during germline development is limited. Here, we make a step toward advancing this understanding using a model-based framework that reconstructs the time course of MPK-1 activation from a snapshot of a fixed germline. Our approach builds on a number of recent studies for estimating temporal dynamics from fixed organisms, but takes advantage of the anatomy of the germline to simplify the analysis. Our model predicts that the MPK-1 signal turns on ∼30 h into germ cell progression and peaks ∼7 h later.     

A Threading-Based Method for the Prediction of DNA-Binding Proteins with Application to the Human Genome

Diverse mechanisms for DNA-protein recognition have been elucidated in numerous atomic complex structures from various protein families. These structural data provide an invaluable knowledge base not only for understanding DNA-protein interactions, but also for developing specialized methods that predict the DNA-binding function from protein structure. While such methods are useful, a major limitation is that they require an experimental structure of the target as input. To overcome this obstacle, we develop a threading-based method, DNA-Binding-Domain-Threader (DBD-Threader), for the prediction of DNA-binding domains and associated DNA-binding protein residues. Our method, which uses a template library composed of DNA-protein complex structures, requires only the target protein''s sequence. In our approach, fold similarity and DNA-binding propensity are employed as two functional discriminating properties. In benchmark tests on 179 DNA-binding and 3,797 non-DNA-binding proteins, using templates whose sequence identity is less than 30% to the target, DBD-Threader achieves a sensitivity/precision of 56%/86%. This performance is considerably better than the standard sequence comparison method PSI-BLAST and is comparable to DBD-Hunter, which requires an experimental structure as input. Moreover, for over 70% of predicted DNA-binding domains, the backbone Root Mean Square Deviations (RMSDs) of the top-ranked structural models are within 6.5 Å of their experimental structures, with their associated DNA-binding sites identified at satisfactory accuracy. Additionally, DBD-Threader correctly assigned the SCOP superfamily for most predicted domains. To demonstrate that DBD-Threader is useful for automatic function annotation on a large-scale, DBD-Threader was applied to 18,631 protein sequences from the human genome; 1,654 proteins are predicted to have DNA-binding function. Comparison with existing Gene Ontology (GO) annotations suggests that ∼30% of our predictions are new. Finally, we present some interesting predictions in detail. In particular, it is estimated that ∼20% of classic zinc finger domains play a functional role not related to direct DNA-binding.     

Decoding Individual Finger Movements from One Hand Using Human EEG Signals

Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (p<0.05). The present study suggests the similar movement-related spectral changes in EEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies.     

Increased Force Variability in Chronic Stroke: Contributions of Force Modulation below 1 Hz

Increased force variability constitutes a hallmark of arm disabilities following stroke. Force variability is related to the modulation of force below 1 Hz in healthy young and older adults. However, whether the increased force variability observed post stroke is related to the modulation of force below 1 Hz remains unknown. Thus, the purpose of this study was to compare force modulation below 1 Hz in chronic stroke and age-matched healthy individuals. Both stroke and control individuals (N = 26) performed an isometric grip task to submaximal force levels. Coefficient of variation quantified force variability, and power spectrum density of force quantified force modulation below 1 Hz with a high resolution (0.07 Hz). Analyses indicated that force variability was greater for the stroke group compared with to healthy controls and for the paretic hand compared with the non-paretic hand. Force modulation below 1 Hz differentiated the stroke individuals and healthy controls, as well as the paretic and non-paretic hands. Specifically, stroke individuals (paretic hand) exhibited greater power ∼0.2 Hz (0.07–0.35 Hz) and lesser power ∼0.6 Hz (0.49–0.77 Hz) compared to healthy controls (non-dominant hand). Similarly, the paretic hand exhibited greater power ∼0.2 Hz, and lesser power ∼0.6 Hz than the non-paretic hand. Moreover, variability of force was strongly predicted from the modulation of specific frequencies below 1 Hz (R ² = 0.80). Together, these findings indicate that the modulation of force below 1 Hz provides significant insight into changes in motor control after stroke.     

Neural Mechanisms Influencing Interlimb Coordination during Locomotion in Humans: Presynaptic Modulation of Forearm H-Reflexes during Leg Cycling

Presynaptic inhibition of transmission between Ia afferent terminals and alpha motoneurons (Ia PSI) is a major control mechanism associated with soleus H-reflex modulation during human locomotion. Rhythmic arm cycling suppresses soleus H-reflex amplitude by increasing segmental Ia PSI. There is a reciprocal organization in the human nervous system such that arm cycling modulates H-reflexes in leg muscles and leg cycling modulates H-reflexes in forearm muscles. However, comparatively little is known about mechanisms subserving the effects from leg to arm. Using a conditioning-test (C-T) stimulation paradigm, the purpose of this study was to test the hypothesis that changes in Ia PSI underlie the modulation of H-reflexes in forearm flexor muscles during leg cycling. Subjects performed leg cycling and static activation while H-reflexes were evoked in forearm flexor muscles. H-reflexes were conditioned with either electrical stimuli to the radial nerve (to increase Ia PSI; C-T interval  = 20 ms) or to the superficial radial (SR) nerve (to reduce Ia PSI; C-T interval  = 37–47 ms). While stationary, H-reflex amplitudes were significantly suppressed by radial nerve conditioning and facilitated by SR nerve conditioning. Leg cycling suppressed H-reflex amplitudes and the amount of this suppression was increased with radial nerve conditioning. SR conditioning stimulation removed the suppression of H-reflex amplitude resulting from leg cycling. Interestingly, these effects and interactions on H-reflex amplitudes were observed with subthreshold conditioning stimulus intensities (radial n., ∼0.6×MT; SR n., ∼ perceptual threshold) that did not have clear post synaptic effects. That is, did not evoke reflexes in the surface EMG of forearm flexor muscles. We conclude that the interaction between leg cycling and somatosensory conditioning of forearm H-reflex amplitudes is mediated by modulation of Ia PSI pathways. Overall our results support a conservation of neural control mechanisms between the arms and legs during locomotor behaviors in humans.     

Learning brain dynamics for decoding and predicting individual differences

Insights from functional Magnetic Resonance Imaging (fMRI), as well as recordings of large numbers of neurons, reveal that many cognitive, emotional, and motor functions depend on the multivariate interactions of brain signals. To decode brain dynamics, we propose an architecture based on recurrent neural networks to uncover distributed spatiotemporal signatures. We demonstrate the potential of the approach using human fMRI data during movie-watching data and a continuous experimental paradigm. The model was able to learn spatiotemporal patterns that supported 15-way movie-clip classification (∼90%) at the level of brain regions, and binary classification of experimental conditions (∼60%) at the level of voxels. The model was also able to learn individual differences in measures of fluid intelligence and verbal IQ at levels comparable to that of existing techniques. We propose a dimensionality reduction approach that uncovers low-dimensional trajectories and captures essential informational (i.e., classification related) properties of brain dynamics. Finally, saliency maps and lesion analysis were employed to characterize brain-region/voxel importance, and uncovered how dynamic but consistent changes in fMRI activation influenced decoding performance. When applied at the level of voxels, our framework implements a dynamic version of multivariate pattern analysis. Our approach provides a framework for visualizing, analyzing, and discovering dynamic spatially distributed brain representations during naturalistic conditions.     

Preservation of Differentiation and Clonogenic Potential of Human Hematopoietic Stem and Progenitor Cells during Lyophilization and Ambient Storage

Progenitor cell therapies show great promise, but their potential for clinical applications requires improved storage and transportation. Desiccated cells stored at ambient temperature would provide economic and practical advantages over approaches employing cell freezing and subzero temperature storage. The objectives of this study were to assess a method for loading the stabilizing sugar, trehalose, into hematopoietic stem and progenitor cells (HPC) and to evaluate the effects of subsequent freeze-drying and storage at ambient temperature on differentiation and clonogenic potential. HPC were isolated from human umbilical cord blood and loaded with trehalose using an endogenous cell surface receptor, termed P2Z. Solution containing trehalose-loaded HPC was placed into vials, which were transferred to a tray freeze-dryer and removed during each step of the freeze-drying process to assess differentiation and clonogenic potential. Control groups for these experiments were freshly isolated HPC. Control cells formed 1450±230 CFU-GM, 430±140 BFU-E, and 50±40 CFU-GEMM per 50 µL. Compared to the values for the control cells, there was no statistical difference observed for cells removed at the end of the freezing step or at the end of primary drying. There was a gradual decrease in the number of CFU-GM and BFU-E for cells removed at different temperatures during secondary drying; however, there were no significant differences in the number of CFU-GEMM. To determine storage stability of lyophilized HPC, cells were stored for 4 weeks at 25°C in the dark. Cells reconstituted immediately after lyophilization produced 580±90 CFU-GM (∼40%, relative to unprocessed controls p<0.0001), 170±70 BFU-E (∼40%, p<0.0001), and 41±22 CFU-GEMM (∼82%, p = 0.4171), and cells reconstituted after 28 days at room temperature produced 513±170 CFU-GM (∼35%, relative to unprocessed controls, p<0.0001), 112±68 BFU-E (∼26%, p<0.0001), and 36±17 CFU-GEMM (∼82%, p = 0.2164) These studies are the first to document high level retention of CFU-GEMM following lyophilization and storage for 4 weeks at 25°C. This type of flexible storage stability would potentially permit the ability to ship and store HPC without the need for refrigeration.     

Formulating a Historical and Demographic Model of Recent Human Evolution Based on Resequencing Data from Noncoding Regions

Background

Estimating the historical and demographic parameters that characterize modern human populations is a fundamental part of reconstructing the recent history of our species. In addition, the development of a model of human evolution that can best explain neutral genetic diversity is required to identify confidently regions of the human genome that have been targeted by natural selection.

Methodology/Principal Findings

We have resequenced 20 independent noncoding autosomal regions dispersed throughout the genome in 213 individuals from different continental populations, corresponding to a total of ∼6 Mb of diploid resequencing data. We used these data to explore and co-estimate an extensive range of historical and demographic parameters with a statistical framework that combines the evaluation of multiple models of human evolution via a best-fit approach, followed by an Approximate Bayesian Computation (ABC) analysis. From a methodological standpoint, evaluating the accuracy of the parameter co-estimation allowed us to identify the most accurate set of statistics to be used for the estimation of each of the different historical and demographic parameters characterizing recent human evolution.

Conclusions/Significance

Our results support a model in which modern humans left Africa through a single major dispersal event occurring ∼60,000 years ago, corresponding to a drastic reduction of ∼5 times the effective population size of the ancestral African population of ∼13,800 individuals. Subsequently, the ancestors of modern Europeans and East Asians diverged much later, ∼22,500 years ago, from the population of ancestral migrants. This late diversification of Eurasians after the African exodus points to the occurrence of a long maturation phase in which the ancestral Eurasian population was not yet diversified.     

Maturity Ogives for South Pacific Albacore Tuna (Thunnus alalunga) That Account for Spatial and Seasonal Variation in the Distributions of Mature and Immature Fish

Length and age at maturity are important life history parameters for estimating spawning stock biomass and reproductive potential of fish stocks. Bias in estimates of size and age at maturity can arise when disparate distributions of mature and immature fish within a population are not accounted for in the analysis. Here we investigate the spatial and temporal variability in observed size and age at maturity of female albacore tuna, Thunnus alalunga, using samples collected across the South Pacific. Maturity status was identified using consistent histological criteria that were precise enough to allow for mature but regenerating females to be distinguished from immature females during the non-spawning season, permitting year-round sampling for maturity estimation in albacore. Using generalised linear mixed models, we found that the proportion of mature females at length varied significantly with latitude and time of year. Specifically, females at northern latitudes (∼10–20°S, where spawning occurs) were mature at significantly smaller lengths and ages than females at southern latitudes (∼20–40°S), particularly during the spawning season (October–March). This variation was due to different geographic distributions of mature and immature fish during the year. We present a method for estimating an unbiased maturity ogive that takes into account the latitudinal variation in proportion mature at length during a given season (spawning or non-spawning). Applying this method to albacore samples from the western region of the South Pacific gave a predicted length at 50% mature of ∼87 cm fork length (4.5 years).