Biology subjects

Bush, A.

Publications and source records attributed to Bush, A..

At least 19 recordsLinked to original sources

bioRxiv2026

The role of the Angular Gyrus in the Elaboration of Specific and Categoric Memories

This study investigated the role of the angular gyrus (AG) and its subregions in the elaboration of specific and categoric autobiographical memories (AMs). Using a cue-word fMRI paradigm, thirty-nine participants retrieved and elaborated on episodic (specific) and semantic (categoric) memories, rating the amount of detail of each recollection. Parametric analyses revealed that AG activity, particularly in posterior AG, was positively associated with the amount of detail retrieved, regardless of memory type. Specific memories elicited greater activation in right AG subregions compared to categoric memories. These findings support the AGs involvement in both episodic and semantic memory retrieval and suggest functional differentiation between its subregions.

neuroscience↗

bioRxiv2026

Monosynaptic connections link functionally similar regions in human cortex

The functional organization of human cortex has been mapped in considerable detail1-5, yet the axonal connections linking these areas remain largely unknown. This gap precludes inferring either the computational pathways through cortical networks or the principles governing why each area connects to its particular target regions. Here, in patients undergoing intracranial monitoring for epilepsy, we used concurrent electrical stimulation and functional magnetic resonance imaging (es-fMRI), validated previously against tracer studies in nonhuman primates6, to map anatomical connectivity of cortical sites across the whole brain, and combined these maps with task and resting-state fMRI in the same individuals. Es-fMRI revealed four main findings. First, connectivity followed an asymmetric functional-similarity principle: connected sites tended to share similar functional profiles, but, because connectivity is sparse, most pairs of functionally similar sites were not connected. Second, although connectivity also declines with distance7, the functional profile explained three times as much variance in connectivity as distance did, and long-range connections were the most functionally specific. Third, es-fMRI revealed direct monosynaptic links between established functional regions, including between the fusiform face area (FFA)2 and the temporoparietal junction (TPJ)3 for social cognition. Fourth, resting-state functional connectivity (rsFC) of a stimulation site was only weakly correlated with that sites es-fMRI connectivity. Together, these results provide a first principled link between anatomical connectivity and functional organization in the human cortex, and establish es-fMRI as a scalable approach to building a tracer-grade connectome of the human brain.

neuroscience↗

bioRxiv2025

Independent Basal Ganglia Neural Populations Encode Speech Production and Ambient-Noise Levels

The function of the basal ganglia (BG), a set of nuclei deep in the brain, is still under debate despite their clinical relevance. Lines of evidence from non-human primate and human experiments suggest that one key causal contribution of the adult primate BG is invigoration of movement according to environmental and energetic constraints. Previous studies have come to this conclusion using primarily limb motor control tasks. We hypothesized BG are also important for invigorating the respiratory, vocal, and articulatory motor systems during speech production. To test this, we used a rare clinical opportunity to record local field potentials-broadband gamma activity (LFP-BGA) and single unit (SU) activity from human basal ganglia during deep brain stimulation implant surgeries. Participants repeated sentences aloud in the operating room. We modulated environmental and energetic constraints of speech production by inducing the Lombard Effect, wherein people reliably increase the intensity of their voice in the presence of background noise. Participants increased voice intensity, pitch, vowel space size, and respiratory depth in the presence of ambient noise. [~]40% of LFP and SU sites were modulated by speech production. Comparing globus pallidus (GP) LFP-BGA, herein reported for the first time during speech, to subthalamic nucleus (STN) LFP-BGA revealed GP activated after STN. STN was more coincident with the speech preparatory period and GP more coincident with speech onset, suggesting differential roles in speech production. We found only weak evidence that STN or GP activity encodes the level of produced speech intensity. Instead, we found that LFP-BGA and SU-FR robustly track the ambient background noise levels. Linear decoding from SU-firing rate revealed we could infer the background noise levels with >75% accuracy in any given time point in the trial, including baseline. Importantly, the ambient-noise-modulated sites were an independent population from speech-modulated sites. We conclude that human BG encode the energetic constraints of communication. We theorize that the code is leveraged in downstream BG-cortical loop nodes to invigorate speech oro-motor gestures and co-speech manual limb gestures, both of which respond to ambient noise levels to maintain high-fidelity communication.

neuroscience↗

bioRxiv2025

Wearable Focused Ultrasound Neuromodulation and Electrophysiological Recording Patch for REM Sleep Enhancement

The rise in sleep disease affecting the general population globally in the past decade has been detrimental to individually and socioeconomically. As of now, approaches often are temporary through medication, permanently using invasive implants with surgical complications or neuromodulation therapy. However, non-invasive, state-dependent neuromodulation during sleep is technically challenging, especially with the lack of flexibility, comfortability and robustness for sleep conditions. Here, we introduce a Non-invasive Electrophysiological Recording and Ultrasound Neuromodulation Sleep Patch (NEUSLeeP) in delivering focused ultrasound stimulation to the subthalamic nucleus (STN) overnight with simultaneous stable polysomnography recording. Our sleep patch integrates a custom eight-channel concentric ring transducer array with real-time electroencephalography (EEG), electrooculography (EOG), electromyography (EMG) recording, and individualized line-of-sight targeting to sonicate deep brain areas while preserving mobility. Our platform operated safely and comfortably across the two-nights sleep study. Stimulation of the left STN was delivered every 90 minutes throughout the night and was associated with a 25% increase in REM (Rapid Eye Movement) sleep duration and a 43 minutes reduction in REM sleep latency compared to a sham night in a study of 26 subjects. Blood Oxygen Level Dependent (BOLD) signal attenuation in functional Magnetic Resonance Imaging (fMRI) was localized primarily to a left ipsilateral basal-ganglia-midbrain-temporal circuit, consistent with selective network modulation rather than global arousal changes. Overall, NEUSLeeP demonstrates feasibility by (i) a light weight and wearable ultrasound neuromodulation and sleep recording during natural sleep; (ii) establishing a potential mechanism relating targeted ultrasound stimulation of STN/sleep networks to REM enhancement.

bioengineering↗

bioRxiv2025

Remote sensing of bird communities in the Peruvian Amazon: evaluating Landsat predictors for biodiversity monitoring.

1Tropical forests harbour some of the highest biodiversity on Earth but are undergoing rapid loss and degradation. In the Amazon more than one-third of forests have been altered through human activities, with major implications for wildlife communities. While Earth observation satellites effectively monitor forest cover at scale, it remains unclear how well satellite-derived variables capture variation in bird communities. We tested whether Landsat reflectance and vegetation indices can predict bird species occurrence and community composition in the Peruvian Amazon. We analysed 3,129 point counts and mist-net bird surveys conducted over 16 years in the Tambopata Forest, south-eastern Peru. As predictors we compared the effectiveness of remote sensing derived surface reflectance and vegetation indices (e.g. NDVI and tasselled cap), with traditional land-type and forest cover descriptors. Species occurrence probabilities and community composition of 135 frequently recorded bird species were estimated using multi-species occupancy models that account for imperfect detection. Models using Landsat reflectance and vegetation indices outperformed those based on habitat categories in predicting species occupancy (mean AUC = 0.68 vs 0.58). They also achieved high predictive accuracy (AUC > 0.7) for more species (49 compared with 20). However, low detection rates across surveys limited all models ability to accurately estimate full community composition and to detect change over time. Our results demonstrate that satellite-derived variables can improve predictions of bird occurrence compared with habitat categories, but their effectiveness depends strongly on survey design and species detectability. Integrating remote sensing with well-structured field surveys provides a scalable approach to monitoring biodiversity trends in tropical forests.

ecology↗

bioRxiv2025

Flight height patterns of a critically endangered insectivorous bat, impacted by wind turbine collision

BackgroundRenewable energy production is being developed worldwide to reduce reliance on fossil fuels and thereby moderate the rate of anthropogenic climate change. Harnessing wind energy, using wind turbines, is a prominent form of renewable energy production. There are, however, biodiversity impacts, including collisions by birds and bats with rotating blades. High levels of mortalities can cause localised and species-level population declines, which is especially significant for threatened species. The height at which species fly is a key collision risk factor. In this study we investigated the flight height patterns of a critically endangered bat to inform mitigations to reduce impacts. MethodsWe captured and GPS tagged 244 Southern Bent-wing Bats (Miniopterus orianae bassanii) (14 - 19 g) in south-eastern Australia, in spring and late summer/early autumn. We retrieved 93 units, yielding 4,289 bat observations from an 18-21 day period in each season. The vertical measurement error of the GPS units at different heights and sampling intervals was investigated with drone test flights. A Bayesian state-space modelling approach was then developed to estimate flight height distributions while accounting for measurement error. ResultsOur results suggest that the majority of bat activity occurs between ground level and 30 m altitude, at least in early spring and late summer/early autumn. However, the bats were recorded taking short flights above 60 m and at times even flew above 80 m (maximum model estimate was 92.7 m with a maximum 95% CI of 144.1 m) and demonstrated that they are capable of quick and frequent altitudinal changes from ground level to almost 40 m. Flight heights were on average higher when associated with trees in summer. Mean flight heights appear to be higher when associated with treed habitats in summer. ConclusionsThis study shows that the flight height distribution of small bats can be investigated using store-on-board GPS devices and illustrates a statistical approach that incorporates vertical measurement error. It provides the first insights into the flight heights of this small bat species, which can help inform a more complete flight height profile across different seasons and conditions with future improvements in GPS technology. Results suggest that, although the Southern Bent-wing Bat primarily flies at lower heights, it exceeds 30 m altitude at times, increasing the risk of mortalities due to wind turbine collision. Accurately determining the proportion of time that threatened species such as the Southern Bent-wing Bats spend within high-risk flight zones will provide the evidence base for implementing effective mitigation measures to reduce population-level impacts.

ecology↗

bioRxiv2024

Brain-wide mapping of oligodendrocyte organization and oligodendrogenesis across the murine lifespan

Insulating sheaths of myelin accelerate neuronal signaling in complex networks of the mammalian brain. In the CNS, myelin sheaths are exclusively produced by oligodendrocytes, which continue to be generated throughout life to change patterns of myelination. However, a brain-wide analysis of oligodendrocyte dynamics across the lifespan has not been performed. We developed a rapid, robust cellular mapping pipeline involving tissue clearing, lightsheet microscopy, atlas alignment, and automated segmentation to define the location of all oligodendrocytes in the mouse brain. This analysis demonstrated the remarkable consistency of oligodendrocyte patterns between hemispheres, individuals, and sexes, and established that oligodendrocyte maps estimate myelin coverage. We trained a vision transformer to identify newly generated oligodendrocytes from millions of mature cells, highlighting age- and region-specific differences in oligodendrogenesis, and revealing areas of enhanced oligodendrocyte resilience and regenerative capacity following demyelination, demonstrating the utility of this pipeline for uncovering brain-wide oligodendrocyte dynamics in health and disease.

neuroscience↗

bioRxiv2023

The effects of cell-cell orientation in modeling the hallmarks of lung cancer in vitro

To better understand and develop treatments for lung cancer, it is important to have reliable and physiologically relevant culture models. Traditional methods of growing lung cancer cells in two- dimensional (2D) monolayers have limitations in mimicking the complex architecture and microenvironment of lung tumors in vivo, limiting their value as reliably informative disease models. In this study, we introduce a new cell culture platform called "tumoroids," which involves growing HCC827 lung cancer cells in three-dimensional (3D) configurations. By comparing transcriptional profiles of HCC827 cells grown as tumoroids versus the same cells grown in 2D monolayers, we investigate how cell-cell orientation and signaling impact the cancer-driving properties of lung cancer. We examine key features associated with cancer progression, such as epithelial mesenchymal transition, replicative ability, and induction of angiogenesis. Additionally, we assess the functional characteristics of the 3D tumoroid culture system by subjecting the cells to irradiation. Through comparing the gene expression profiles of the 3D tumoroid and 2D cultures with those of primary human lung adenocarcinoma, we find that the 3D tumoroid cultures more closely resemble the characteristics of primary human lung cancer. This suggests that the 3D tumoroid culture platform can serve as a valuable in vitro model for studying lung cancer, offering greater clinical relevance compared to traditional 2D cultures. Overall, this study highlights the importance of using advanced culture models like 3D tumoroids to improve our understanding of lung cancer and facilitate the development of effective treatments.

cancer biology↗

bioRxiv2023

Subthalamic nucleus neurons encode syllable sequence and phonetic characteristics during speech

Speech is a complex behavior that can be used to study unique contributions of the basal ganglia to motor control in the human brain. Computational models suggest that the basal ganglia encodes either the phonetic content or the sequence of speech elements. To explore this question, we investigated the relationship between phoneme and sequence features of a spoken syllable triplet and the firing rate of subthalamic nucleus (STN) neurons recorded during the implantation of deep brain stimulation (DBS) electrodes in individuals with Parkinsons disease. Patients repeated aloud a random sequence of three consonant-vowel (CV) syllables in response to audio cues. Single-unit extracellular potentials were sampled from the sensorimotor STN; a total of 227 unit recordings were obtained from the left STN of 25 subjects (4 female). Of these, 113 (50%) units showed significant task-related increased firing and 53 (23%) showed decreased firing (t-test relative to inter-trial period baseline, p<0.05). Linear regression analysis revealed that both populations of STN neurons encode phoneme and sequence features of produced speech. Maximal phoneme encoding occurred at the time of phoneme production, suggesting efference copyor sensory-related processing, rather than speech motor planning (-50ms and +175ms relative to CV transition for consonant and vowel encoding, respectively). These findings demonstrate that involvement of the basal ganglia in speaking includes separate single unit representations of speech sequencing and phoneme selection in the STN.

neuroscience↗

bioRxiv2023

Environmental DNA captures the internal structure of a pond metacommunity

Technological progress is enabling ecologists to create repeated, large-scale, structured, and standardised community surveys. However, it is unclear how best to extract information from these novel community data. We metabarcoded 48 vertebrate species from their eDNA in 320 ponds in England and applied the internal-structure approach, which uses joint species distribution models to explain community compositions as the outcome of four metacommunity assembly processes: environmental filtering, dispersal, species interactions, and stochasticity. We find that the environment plays an important role in community assembly and that the inferred environmental preferences of species are consistent with their ecologies. We also infer negative biotic covariances between fish and amphibians, which is consistent with predator-prey interactions, and high spatial autocorrelation for the palmate newt, which is consistent with its hypothesised relictual distribution. Comparing sites in the metacommunity, environmentally and spatially distinctive sites are better explained by their environmental covariates and geographic locations, respectively, revealing sites where environmental filtering and dispersal limitation act more strongly. Furthermore, species belonging to different trait groups differ in how well environmental covariates, biotic covariances, and geographical locations explain their distributions. Overall, our results highlight the value of a modern interpretation of metacommunity ecology that embraces the fact that assembly processes differ between individual species and sites. We discuss how novel community data make feasible several study-design improvements that will strengthen the inference of metacommunity assembly processes from observational data.

ecology↗

bioRxiv2023

Speech induces spatiotemporal and frequency specific subthalamic-cortical spike-phase coupling events

Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct intracranial recordings across cortical-basal ganglia networks are rare. We recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where subjects spoke syllable repetitions. We discovered that individual STN neurons have transient (200ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons was coordinated with the phase of theta-alpha oscillations in the posterior supramarginal and superior temporal gyrus during speech planning and production. Speech sound errors occurred when this STN-cortical interaction was delayed. Our results suggest that the STN supports mechanisms of speech planning and auditory-sensorimotor integration during speech production that are required to achieve high fidelity of the phonological and articulatory representation of the target phoneme. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.

neuroscience↗

bioRxiv2023

Decoding auditory working memory content from intracranial high frequency activity in humans

Working memory (WM), the human brains system for maintaining and manipulating information over short timescales, is critical for goal-directed behavior. Classic neurophysiological models, which emphasize persistent delay activity, are being challenged by an idea that WM is maintained through dynamic and activity-silent mechanisms, where the memory trace is preserved by transient changes in the connections between neurons. To date, human evidence for this alternative model has been limited to non-invasive studies. Here, leveraging high-resolution intracranial stereo-EEG with advanced machine learning decoding techniques, we investigate neuronal mechanisms of human auditory WM. Neuronal activity is quantified as broadband high frequency activity (70-190 Hz), a correlate of neuronal firing activity. Our multivariate pattern analyses, validated via robust non-parametric permutation testing, show that WM content is represented in multiple brain regions, exhibiting dynamic rather than persistent delay activity. Crucially, by using task-irrelevant sounds to probe latent mnemonic states, we provide the first human intracranial evidence of activity silent WM maintenance in a local sensory network.

neuroscience↗

bioRxiv2023

A supervised data-driven spatial filter denoising method for acoustic-induced artifacts in intracranial electrophysiological recordings

Neurosurgical procedures that enable direct brain recordings in awake patients offer unique opportunities to explore the neurophysiology of human speech. The scarcity of these opportunities and the altruism of participating patients compel us to apply the highest rigor to signal analysis. Intracranial electroencephalography (iEEG) signals recorded during overt speech can contain a speech artifact that tracks the fundamental frequency (F0) of the participants voice, involving the same high-gamma frequencies that are modulated during speech production and perception. To address this artifact, we developed a spatial-filtering approach to identify and remove acoustic-induced contaminations of the recorded signal. We found that traditional reference schemes jeopardized signal quality, whereas our data-driven method denoised the recordings while preserving underlying neural activity.

neuroscience↗

bioRxiv2023

Systematic Nature Positive Markets

Despite decades of global commitments, and increasingly urgent warning of environmental instability, the demand for land to support economic production is still increasing. Isolated and disorganized actions will not be enough to avert ecosystem failures. As many developers are already required to compensate for their ecological impacts through restoration, many see markets trading biodiversity credits as a financial mechanism to counteract degradation and drive investment in conservation. The challenge stems from a desire to recognize the multidimensional nature of biodiversity that contributes to ecosystem integrity without making suitable offsets intractable to supply. Instead, most regulators have opted to streamline ecological assessment, and undermine ecological rigour, in favour of promoting offset supply and economic efficiency. As a result, all evidence suggests offset trading programs have so far failed to mitigate losses, let alone support "nature positive" outcomes. To overcome this disconnect, and support more effective and equitable biodiversity markets, we propose credits be defined by the irreplaceability of a site, a metric long-established in the domain of systematic conservation planning. Irreplaceability avoids the limitations of like-for-like trading, reduces costs of offsetting to developers and society, ensures farmers willing to sell are fairly rewarded for loss of earnings, and that sites critical to achieving conservation goals are safeguarded. We developed an ecological-economic model of a biodiversity offset market to demonstrate irreplaceability guarantees no net loss of biodiversity and is the most efficient metric for guiding investment toward the recovery of Nature.

ecology↗

bioRxiv2023

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/f{chi} broadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinsons disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent ({chi}STN=1.3{+/-}0.2, {chi}VIM=1.4{+/-}0.1, {chi}GPi=1.4{+/-}0.1) that differed markedly from cortical values ({chi}Cortex=3.2{+/-}0.4, fkCortex=17{+/-}5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex. Significance StatementThe broadband aperiodic component of local field potentials is a useful and reproducible index of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters, with which we fit cortical, basal ganglia and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinsons disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the broadband aperiodic components of basal ganglia and thalamic signals compared to those from neocortex, suggesting that the aperiodic neural timescale of subcortical LFPs is slower than that in cortex.

neuroscience↗

bioRxiv2021

A spatio-spectral approach for movement decoding from cortical and subcortical recordings in patients with Parkinson's disease

The application of machine learning to intracranial signal analysis has the potential to revolutionize deep brain stimulation (DBS) by personalizing therapy to dynamic brain states, specific to symptoms and behaviors. Most decoding pipelines for movement decoding in the context of adaptive DBS are based on single channel frequency domain features, neglecting spatial information available in multichannel recordings. Such features are extracted either from DBS lead recordings in the subcortical target and/or from electrocorticography (ECoG). To optimize the simultaneous use of both types of signals, we developed a supervised online-compatible movement decoding pipeline based on multichannel and multiple site recordings. We found that adding spatial information to the model has the potential to improve decoding. In addition, we demonstrate movement decoding from spatio-spectral features derived from cortical and subcortical oscillations. We demonstrate between-patients variability of the spatial neural maps and its relationship to feature decoding performance. This application of spatial filters to decode movement from combined cortical and subcortical recordings is an important step in developing machine learning approaches for intelligent DBS systems.

neuroscience↗

bioRxiv2021

Differentiation of speech-induced artifacts from physiological high gamma activity in intracranial recordings

There is great interest in identifying the neurophysiological underpinnings of speech production. Deep brain stimulation (DBS) surgery is unique in that it allows intracranial recordings from both cortical and subcortical regions in patients who are awake and speaking. The quality of these recordings, however, may be affected to various degrees by mechanical forces resulting from speech itself. Here we describe the presence of speech-induced artifacts in local-field potential (LFP) recordings obtained from mapping electrodes, DBS leads, and cortical electrodes. In addition to expected physiological increases in high gamma (60-200 Hz) activity during speech production, time-frequency analysis in many channels revealed a narrowband gamma component that exhibited a pattern similar to that observed in the speech audio spectrogram. This component was present to different degrees in multiple types of neural recordings. We show that this component tracks the fundamental frequency of the participants voice, correlates with the power spectrum of speech and has coherence with the produced speech audio. A vibration sensor attached to the stereotactic frame recorded speech-induced vibrations with the same pattern observed in the LFPs. No corresponding component was identified in any neural channel during the listening epoch of a syllable repetition task. These observations demonstrate how speech-induced vibrations can create artifacts in the primary frequency band of interest. Identifying and accounting for these artifacts is crucial for establishing the validity and reproducibility of speech-related data obtained from intracranial recordings during DBS surgery.

neuroscience↗

bioRxiv2020

Thalamic encoding of lexical status is lateralized during reading aloud

To explore whether the thalamus participates in lexical status encoding, local field potentials were recorded in patients undergoing deep brain stimulation lead implantation while they read aloud single-syllable words and nonwords. Bilateral decreases in thalamic beta (12-30Hz) activity were preferentially locked to stimulus presentation, and these decreases were greater when nonwords were read. Increased broadband gamma (70-150Hz) activity also was locked preferentially to speech onset bilaterally, but greater nonword-related increases in this activity were observed only on the left, demonstrating lateralization of thalamic gamma selectivity for lexical status. In addition, this lexical status effect was strongest in more anterior thalamic locations, regions which are more likely to receive pallidal than cerebellar afferents. These results provide evidence from intracranial thalamic recordings for the lateralization and topography of subcortical lexical status processing.

neuroscience↗