Temporal Fidelity Research Articles

Highly accelerated non-contrast-enhanced time-resolved 4D MRA using stack-of-stars golden-angle radial acquisition with a self-calibrated low-rank subspace reconstruction.

To develop a highly accelerated non-contrast-enhanced 4D-MRA technique by combining stack-of-stars golden-angle radial acquisition with a modified self-calibrated low-rank subspace reconstruction. A low-rank subspace reconstruction framework was introduced in radial 4D MRA (SUPER 4D MRA) by combining stack-of-stars golden-angle radial acquisition with control-label k-space subtraction-based low-rank subspace modeling. Radial 4D MRA data were acquired and reconstructed using the proposed technique on 12 healthy volunteers and 1 patient with steno-occlusive disease. The performance of SUPER 4D MRA was compared with two temporally constrained reconstruction methods (golden-angle radial sparse parallel [GRASP] and GRASP-Pro) at different acceleration rates in terms of image quality and delineation of blood dynamics. SUPER 4D MRA outperformed the other two reconstruction methods, offering superior image quality with a clear background and detailed delineation of cerebrovascular structures as well as great temporal fidelity in blood flow dynamics. SUPER 4D MRA maintained excellent performance even at higher acceleration rates. SUPER 4D MRA is a promising technique for highly accelerating 4D MRA acquisition without comprising both temporal fidelity and image quality.

Simultaneous recordings from vestibular Type I hair cells and their calyceal afferents in mice.

The vestibular hair cell receptors of anamniotes, designated Type II, are presynaptic to bouton endings of vestibular nerve distal neurites. An additional flask-shaped hair cell receptor, Type I, is present in amniotes, and communicates with a chalice-shaped afferent neuritic ending that surrounds the entire hair cell except its apical neck. Since the full repertoire of afferent fiber dynamics and sensitivities observed throughout the vertebrate phyla can be accomplished through Type II hair cell-bouton synapses, the functional contribution(s) of Type I hair cells and their calyces to vestibular performance remains a topic of great interest. The goal of the present study was to investigate electrical coupling between the Type I hair cell and its enveloping calyx in the mouse semicircular canal crista ampullaris. Since there are no gap junctions between these two cells, evidence for electrical communication would necessarily involve other mechanisms. Simultaneous recordings from the two cells of the synaptic pair were used initially to verify the presence of orthodromic quantal synaptic transmission from the hair cell to the calyx, and then to demonstrate bi-directional communication due to the slow accumulation of potassium ions in the synaptic cleft. As a result of this potassium ion accretion, the equilibrium potentials of hair cell conductances facing the synaptic cleft become depolarized to an extent that is adequate for calcium influx into the hair cell, and the calyx inner face becomes depolarized to a level that is near the threshold for spike initiation. Following this, paired recordings were again employed to characterize fast bi-directional electrical coupling between the two cells. In this form of signaling, cleft-facing conductances in both the hair cell and calyx increase, which strengthens their coupling. Because this mechanism relies on the cleft resistance, we refer to it as resistive coupling. We conclude that the same three forms of hair cell-calyceal transmission previously demonstrated in the turtle are present in the mammalian periphery, providing a biophysical basis for the exceptional temporal fidelity of the vestibular system.

Cross-regional coordination of activity in the human brain during autobiographical self-referential processing

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.

Nongenetic Precise Neuromodulation and Spatiotemporal Neuroprotection for Epilepsy Therapy via Rationally Designed Multifunctional Nanotransducer.

The precise modulation of electrical activity in specific neuronal populations is paramount for rectifying abnormal neurological functions and is a critical element in the therapeutic arsenal for neurological disorders. However, achieving a balance between minimal invasiveness and robust neuroprotection poses a considerable challenge. Herein, we present a nanoneuromodulation strategy integrating neuroprotective features to effectively address epilepsy with minimal invasiveness and enable wireless functionality. Strategically engineered nanotransducer, adorned with platinum (Pt) decoration with titanium disulfide (TiS2) (TiS2/Pt), enables precise modulation of neuronal electrical activity in vitro and in vivo, ensuring exceptional temporal fidelity under millisecond-precision near-infrared (NIR) light pulses irradiation. Concurrently, TiS2/Pt showcase a pronounced enhancement in enzyme-mimicking activity, offering a robust defense against oxidative neurological injury in vitro. Nanotransducer-enabled wireless neuromodulation with biocatalytic neuroprotective capacity is highly effective in alleviating epileptic high-frequency neural activity and diminishing oxidative stress levels, thereby restoring redox equilibrium. This integrated therapeutic approach reduces the severity of epilepsy, demonstrating minimal invasiveness and obviating the requirements for genetic manipulation and optical fiber implantation, while providing an alternative avenue for neurological disorder treatment.

Assessment of temporal changes in glomerular filtration rate following clamp ischemia in male and female rats using transcutaneous FITC-sinistrin clearance

Warm arterial clamping with reperfusion in rats is a commonly utilized model of ischemic kidney injury (IRI). Traditionally, changes in plasma creatinine or creatinine clearance have been utilized to assess kidney function in this model. A limitation of these approaches, however, is that changes in plasma creatinine are relatively slow to occur, resulting in low temporal fidelity. This limits our ability to relate changes in kidney function to histo-pathological changes observed during reperfusion of the kidneys. Transcutaneous assessment of FITC-sinistrin clearance enables accurate, repeated measurement of glomerular filtration rate in conscious animals over short segments of time (hours) without drawing blood. The goal of the current study was to characterize temporal changes in renal function in male and female rats after reperfusion from bi-lateral warm arterial clamp ischemia using transcutaneous FITC-sinistrin clearance. Our study was performed in age matched male (n=8) and female (n=5) Sprague Dawley rats (12-20wks of age). FITC sinistrin clearance was measured by affxing a miniaturized transcutaneous measurement device between the shoulder blades (MediBeacon) of rats. 50mg/kg of FITC-sinistrin was then injected i.v via the tail vein and the device allowed to record for ~3 hours. Measurements were taken either at pre-surgery (baseline), 1-3 hours, 24 hours or 7 days following reperfusion of the kidneys from warm bilateral arterial clamp ischemia. For the ischemic surgery, animals were anesthetized with isoflurane (2-5%, 95% O2) and the right and left kidneys were accessed by flank incisions. After being exposed, the renal arteries were separated from the renal veins via dissection. Both renal arteries were then clamped with microserrefines for 45 minutes. After the ischemic period, the clamps were removed, allowing blood flow to be restored to the kidneys. Body temperature was measured via a rectal probe and maintained at 37°C throughout the procedure by a servo-controlled heating table and UV heating lamp. The wounds were then closed, and the animals allowed to recover. Buprenorphine was administered as an analgesic. For each measurement, the ½ life of FITC sinistrin was determined using a 1-compartment model (MB Lab software) and glomerular filtration rate (GFR) per 100g of body weight rate calculated. Baseline GFR was 0.94±0.03ml/min/100g in males and 1.09±0.02/min/100g in females (PTTEST=0.04). Following 45 minutes of warm bilateral arterial ischemia and reperfusion, GFR fell to 0.24±0.08ml/min/100g in male and 0.36±0.15ml/min/100g in females within 1-3 hours of reperfusion. At 24 hours of reperfusion, GFR averaged 0.06±0.03ml/min/100g in males and 0.28±0.16ml/min/100g in females. GFR recovered in males and females by 7 days of reperfusion averaging 0.86±0.10ml/min/100g in males and 0.83±0.00ml/min/100g in females. There was no significant difference between FITC-sinistrin clearance between males and females at any time point after IRI. Our data indicate that most of the reduction in GFR is present immediately after releasing the clamp. This is consistent with continued vascular disturbances mediating the initial decline in glomerular filtration rate in this model (i.e. vasospasm). The absence of sex differences in GFR decline using this method suggests that sex-differences detected using plasma creatinine may be, at least in part, secondary to the more rapid production of creatinine in males than in females or greater baseline filtration/body weight ratio in females compared to males rather than differences in renal function decline to ischemia. American Heart Association Transformational Project Award 970585 to Paul O'Connor. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Synaptic alterations associated with disrupted sensory encoding in a mouse model of tauopathy.

Synapse loss is currently the best biological correlate of cognitive decline in Alzheimer's disease and other tauopathies. Synapses seem to be highly vulnerable to tau-mediated disruption in neurodegenerative tauopathies. However, it is unclear how and when this leads to alterations in function related to the progression of tauopathy and neurodegeneration. We used the well-characterized rTg4510 mouse model of tauopathy at 5-6 months and 7-8 months of age, respectively, to study the functional impact of cortical synapse loss. The earlier age was used as a model of prodromal tauopathy, with the later age corresponding to more advanced tau pathology and presumed progression of neurodegeneration. Analysis of synaptic protein expression in the somatosensory cortex showed significant reductions in synaptic proteins and NMDA and AMPA receptor subunit expression in rTg4510 mice. Surprisingly, in vitro whole-cell patch clamp electrophysiology from putative pyramidal neurons in layer 2/3 of the somatosensory cortex suggested no functional alterations in layer 4 to layer 2/3 synaptic transmission at 5-6 months. From these same neurons, however, there were alterations in dendritic structure, with increased branching proximal to the soma in rTg4510 neurons. Therefore, in vivo whole-cell patch clamp recordings were utilized to investigate synaptic function and integration in putative pyramidal neurons in layer 2/3 of the somatosensory cortex. These recordings revealed a significant increase in the peak response to synaptically driven sensory stimulation-evoked activity and a loss of temporal fidelity of the evoked signal to the input stimulus in rTg4510 neurons. Together, these data suggest that loss of synapses, changes in receptor expression and dendritic restructuring may lead to alterations in synaptic integration at a network level. Understanding these compensatory processes could identify targets to help delay symptomatic onset of dementia.

Video stabilization based on low‐rank constraint and trajectory optimization

AbstractVideo stabilization plays a pivotal role in enhancing video quality by eliminating unwanted jitter in shaky videos. This paper introduces a novel video stabilization algorithm that leverages low‐rank constraint and trajectory optimization to effectively eliminate undesirable motion and generate stabilized videos. In the proposed algorithm, a low‐rank constraint regularization term is incorporated to enhance the smoothness of motion trajectories. Additionally, a predictive path smoothness term is integrated to ensure the consistency of motion across neighbouring frames. To address the problem of excessive cropping resulting from aggressive smoothing, a flexible local window strategy that emphasizes local motion relationships within the trajectories is introduced. The experimental results show that, compared to other excellent video stabilization algorithms, the proposed algorithm improves the stability metric by approximately 2.3%. Furthermore, in the stabilized videos generated by the algorithm, an approximate improvement of 2.18 dB in average image temporal fidelity and a 5.7% increase in average structural similarity between adjacent frames are achieved. The code that implements the proposed method is publicly accessible at https://github.com/CZS0319/VS_Low‐Rank_Constraint_Trajectory_Optimization.

Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism

Accurate prediction of spatial–temporal extreme wind gust is vital for the wind farm dynamic regulation, the floating wind turbine deployment and its early warning. Deep-learning approaches have been applied for wind prediction to alleviate the computational challenges of traditional numerical models. Yet, most previous studies emphasized the prediction accuracy only employing location-specific dataset, such methodologies are site-specific and ignore the importance of spatial–temporal fidelity. Furthermore, the Recurrent Neural Networks (RNN)-based approach previous employed exhibit low efficiency in terms of model convergence and on the aspect of practical engineering purposes. This study firstly proposed the wind gust prediction net (WGPNet), using residual learning with attention modulations to predict the instantaneous spatial–temporal wind gust in the West Pacific region with great potential wind-energy. And a public reanalysis dataset with very high resolution (0.25° x 0.25°) was employed to verify the proposed method under different criteria. The overall RMSE of predicted gust fields obtained by the proposed method dropped to 0.18 m/s. Comprehensive discussions with both temporal and spatial perspective, revealing that the proposed model can offer an accurate 2D wind gust prediction along timeline (the PCC equals to 0.98).

Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction.

Simultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image reconstruction but result in high noise level. Alternatively, iterative reconstruction techniques based on temporal regularization (ITER) improve image quality but are associated with reduced temporal signal fidelity and long computation time limiting their online use. The aim is to develop an image reconstruction technique for SMS-bSSFP myocardial perfusion imaging combining parallel imaging and image-based denoising using a novel noise map estimation network (NoiseMapNet), which preserves both sharpness and temporal signal profiles and that has low computational cost. The proposed reconstruction of SMS images consists of a standard temporal parallel imaging reconstruction (TGRAPPA) with motion correction (MOCO) followed by image denoising using NoiseMapNet. NoiseMapNet is a deep learning network based on a 2D Unet architecture and aims to predict a noise map from an input noisy image, which is then subtracted from the noisy image to generate the denoised image. This approach was evaluated in 17 patients who underwent stress perfusion imaging using a SMS-bSSFP sequence. Images were reconstructed with (a) TGRAPPA with MOCO (thereafter referred to as TGRAPPA), (b) iterative reconstruction with integrated motion compensation (ITER), and (c) proposed NoiseMapNet-based reconstruction. Normalized mean squared error (NMSE) with respect to TGRAPPA, myocardial sharpness, image quality, perceived SNR (pSNR), and number of diagnostic segments were evaluated. NMSE of NoiseMapNet was lower than using ITER for both myocardium (0.045 ± 0.021 vs. 0.172 ± 0.041, p < 0.001) and left ventricular blood pool (0.025 ± 0.014 vs. 0.069 ± 0.020, p < 0.001). There were no significant differences between all methods for myocardial sharpness (p = 0.77) and number of diagnostic segments (p = 0.36). ITER led to higher image quality than NoiseMapNet/TGRAPPA (2.7 ± 0.4 vs. 1.8 ± 0.4/1.3 ± 0.6, p < 0.001) and higher pSNR than NoiseMapNet/TGRAPPA (3.0 ± 0.0 vs. 2.0 ± 0.0/1.3 ± 0.6, p < 0.001). Importantly, NoiseMapNet yielded higher pSNR (p < 0.001) and image quality (p < 0.008) than TGRAPPA. Computation time of NoiseMapNet was only 20s for one entire dataset. NoiseMapNet-based reconstruction enables fast SMS image reconstruction for stress myocardial perfusion imaging while preserving sharpness and temporal signal profiles.

Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance.

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient in conveying the overall scene context, it may be insufficient to control precisely. In this paper, we explore customized video generation by utilizing text as context description and motion structure (e.g. frame- wise depth) as concrete guidance. Our method, dubbed Make-Your-Video, involves joint-conditional video generation using a Latent Diffusion Model that is pre-trained for still image synthesis and then promoted for video generation with the introduction of temporal modules. This two-stage learning scheme not only reduces the computing resources required, but also improves the performance by transferring the rich concepts available in image datasets solely into video generation. Moreover, we use a simple yet effective causal attention mask strategy to enable longer video synthesis, which mitigates the potential quality degradation effectively. Experimental results show the superiority of our method over existing baselines, particularly in terms of temporal coherence and fidelity to users' guidance. In addition, our model enables several intriguing applications that demonstrate potential for practical usage. The code, model weights, and videos are publicly available at our project page: https://doubiiu.github.io/projects/Make-Your-Video/.

Modulating signalling lifetime to optimise a prototypical animal opsin for optogenetic applications

Animal opsins are light activated G-protein-coupled receptors, capable of optogenetic control of G-protein signalling for research or therapeutic applications. Animal opsins offer excellent photosensitivity, but their temporal resolution can be limited by long photoresponse duration when expressed outside their native cellular environment. Here, we explore methods for addressing this limitation for a prototypical animal opsin (human rod opsin) in HEK293T cells. We find that the application of the canonical rhodopsin kinase (GRK1)/visual arrestin signal termination mechanism to this problem is complicated by a generalised suppressive effect of GRK1 expression. This attenuation can be overcome using phosphorylation-independent mutants of arrestin, especially when these are tethered to the opsin protein. We further show that point mutations targeting the Schiff base stability of the opsin can also reduce signalling lifetime. Finally, we apply one such mutation (E122Q) to improve the temporal fidelity of restored visual responses following ectopic opsin expression in the inner retina of a mouse model of retinal degeneration (rd1). Our results reveal that these two strategies (targeting either arrestin binding or Schiff-base hydrolysis) can produce more time-delimited opsin signalling under heterologous expression and establish the potential of this approach to improve optogenetic performance.

Spatial-temporal offshore wind speed characteristics prediction based on an improved purely 2D CNN approach in a large-scale perspective using reanalysis dataset

Accurate prediction of spatial–temporal wind speed with a large-scale perspective is vital for the wind farm dynamic regulation, the floating wind turbine deployment and its early warning. Machine-learning approaches have been applied for wind prediction to alleviate the computational challenges of traditional numerical models. Yet, most previous studies emphasized the forecasting accuracy employing location-specific dataset, such methodologies are site-specific and ignore the importance of spatial–temporal fidelity required by the 2D regional wind farm blueprint. Furtherly, the Recurrent Neural Networks based approach they employed exhibit low efficiency in terms of model convergence on the aspect of practical engineering purposes. This study firstly proposed an improved Unet-based machine learning method using residual learning to predict the spatial–temporal wind field in the North Atlantic Ocean with great potential wind-energy in a large spatial-scale perspective. Several state-of-the-art machine learning methods were established for a better performance comparison. A public reanalysis dataset with very high resolution (0.25° x 0.25°) was employed to verify the proposed method with multi-steps ahead predictions, the model performance was furtherly compared with the rest approaches under different criteria, consisting of Pearson correlation coefficient (PCC), Mean absolutely error (MAE), Root mean square error (RMSE) and symmetric mean absolute percentage error (SMAPE), all exhibiting considerable improvements. The overall forecasting RMSE for the proposed method dropped to 0.088 m/s and 0.087 m/s for wind component U and V correspondingly. Furtherly, comprehensive discussions were provided with both temporal and spatial perspective, revealing that the proposed model can offer an accurate 2D wind speed prediction along timeline (the PCC equals to 0.99). The proposed data-driven method presents promising potential to accurately preserve the spatial-resolved patterns which are variant in both spatial and temporal dimensions, and show superiority in terms of computational efficiency in terms of achieving large-scale wind pattern predictions.

Understanding the heterogeneous immune repertoire of brain metastases for designing next‐gen therapeutics

AbstractApproximately 20% of cancer patients experience brain metastases in the advanced stages as circulating tumor cells migrate to and colonize the brain microvasculature. Due to the challenges associated with biopsies, our understanding of the tumor microenvironment and heterogeneity in brain metastases remains limited, hindering the development of systemic approaches for detection and treatment. Emerging evidence suggests that specific brain metastases induce a substantial level of immune activation and infiltration, which provides an opportunity to design specific immunotherapies targeting brain metastases. This perspective aims to summarize recent advancements in molecular profiling of the immune repertoires of brain metastases using biopsy‐based approaches, with an emphasis on tumor‐reactive T cells. Additionally, we discuss the potential of alternative tissues and technologies that offer improved temporal resolution, throughput, and fidelity for tracking tumor dynamics.

A critical evaluation of protein kinase regulation by activation loop autophosphorylation.

Phosphorylation of proteins is a ubiquitous mechanism of regulating their function, localization, or activity. Protein kinases, enzymes that use ATP to phosphorylate protein substrates are, therefore, powerful signal transducers in eukaryotic cells. The mechanism of phosphoryl-transfer is universally conserved among protein kinases, which necessitates the tight regulation of kinase activity for the orchestration of cellular processes with high spatial and temporal fidelity. In response to a stimulus, many kinases enhance their own activity by autophosphorylating a conserved amino acid in their activation loop, but precisely how this reaction is performed is controversial. Classically, kinases that autophosphorylate their activation loop are thought to perform the reaction in trans, mediated by transient dimerization of their kinase domains. However, motivated by the recently discovered regulation mechanism of activation loop cis-autophosphorylation by a kinase that is autoinhibited in trans, we here review the various mechanisms of autoregulation that have been proposed. We provide a framework for critically evaluating biochemical, kinetic, and structural evidence for protein kinase dimerization and autophosphorylation, and share some thoughts on the implications of these mechanisms within physiological signaling networks.

Protecting the fidelity of a pulsed-driven harmonic oscillator

The temporal fidelity of a non-dissipative quantised harmonic oscillator (QHO) driven by two types of pulsed laser; namely, rectangular and train of n-chirped Gaussian pulses is investigated. The computational results are presented for two initial states of the HO, namely, the superposition of coherent states (Schrödinger cat states type) and squeezed coherent state. Quantum interference between the two component states |α〉 and |−α〉 of the initial cat state in the non-resonance case induces oscillatory behaviour in the fidelity. The case of initial squeezed coherent state shows profound maximum bounds of the fidelity or lesser maximum peaks, depending on the pulse shape and other system parameters (squeezing, chirp and pulse number parameters).

Light at the end of the tunnel of Corti

Light at the end of the tunnel of Corti

High-fidelity encoding of mechanostimuli by tactile food-sensing neurons requires an ensemble of ion channels

The nematode C.elegans uses mechanosensitive neurons to detect bacteria, which are food for worms. These neurons release dopamine to suppress foraging and promote dwelling. Through a screen of genes highly expressed in dopaminergic food-sensing neurons, we identify a K2P-family potassium channel-TWK-2-that damps their activity. Strikingly, loss of TWK-2 restores mechanosensation to neurons lacking the NOMPC-like channel transient receptor potential 4 (TRP-4), which was thought to be the primary mechanoreceptor for tactile food sensing. The alternate mechanoreceptor mechanism uncovered by TWK-2 mutation requires three Deg/ENaC channel subunits: ASIC-1, DEL-3, and UNC-8. Analysis of cell-physiological responses to mechanostimuli indicates that TRP and Deg/ENaC channels work together to set the range of analog encoding of stimulus intensity and to improve signal-to-noise characteristics and temporal fidelity of food-sensing neurons. We conclude that a specialized mechanosensory modality-tactile food sensing-emerges from coordination of distinct force-sensing mechanisms housed in one type of sensory neuron.

Use of high-speed angiography HSA-derived boundary conditions and Physics Informed Neural Networks (PINNs) for comprehensive estimation of neurovascular hemodynamics.

Physics-informed neural networks (PINNs) and computational fluid dynamics (CFD) have both demonstrated an ability to derive accurate hemodynamics if boundary conditions (BCs) are known. Unfortunately, patient-specific BCs are often unknown, and assumptions based upon previous investigations are used instead. High speed angiography (HSA) may allow extraction of these BCs due to the high temporal fidelity of the modality. We propose to investigate whether PINNs using convection and Navier-Stokes equations with BCs derived from HSA data may allow for extraction of accurate hemodynamics in the vasculature. Imaging data generated from in vitro 1000 fps HSA, as well as simulated 1000 fps angiograms generated using CFD were utilized for this study. Calculations were performed on a 3D lattice comprised of 2D projections temporally stacked over the angiographic sequence. A PINN based on an objective function comprised of the Navier-Stokes equation, the convection equation, and angiography-based BCs was used for estimation of velocity, pressure and contrast flow at every point in the lattice. Imaging-based PINNs show an ability to capture such hemodynamic phenomena as vortices in aneurysms and regions of rapid transience, such as outlet vessel blood flow within a carotid artery bifurcation phantom. These networks work best with small solution spaces and high temporal resolution of the input angiographic data, meaning HSA image sequences represent an ideal medium for such solution spaces. The study shows the feasibility of obtaining patient-specific velocity and pressure fields using an assumption-free data driven approach based purely on governing physical equations and imaging data.

Auditory nerve responses to combined optogenetic and electrical stimulation in chronically deaf mice

Objective. Optogenetic stimulation of the auditory nerve offers the ability to overcome the limitations of cochlear implants through spatially precise stimulation, but cannot achieve the temporal precision nor temporal fidelity required for good hearing outcomes. Auditory midbrain recordings have indicated a combined (hybrid) stimulation approach may permit improvements in the temporal precision without sacrificing spatial precision by facilitating electrical activation thresholds. However, previous research has been conducted in undeafened or acutely deafened animal models, and the impact of chronic deafness remains unclear. Our study aims to compare the temporal precision of auditory nerve responses to optogenetic, electrical, and combined stimulation in acutely and chronically deafened animals. Methods. We directly compare the temporal fidelity (measured as percentage of elicited responses) and precision (i.e. stability of response size and timing) of electrical, optogenetic, and hybrid stimulation (varying sub-threshold or supra-threshold optogenetic power levels combined with electrical stimuli) through compound action potential and single-unit recordings of the auditory nerve in transgenic mice expressing the opsin ChR2-H134R in auditory neurons. Recordings were conducted immediately or 2–3 weeks following aminoglycoside deafening when there was evidence of auditory nerve degeneration. Main results. Results showed that responses to electrical stimulation had significantly greater temporal precision than optogenetic stimulation (p < 0.001 for measures of response size and timing). This temporal precision could be maintained with hybrid stimulation, but only when the optogenetic stimulation power used was below or near activation threshold and worsened with increasing optical power. Chronically deafened mice showed poorer facilitation of electrical activation thresholds with concurrent optogenetic stimulation than acutely deafened mice. Additionally, responses in chronically deafened mice showed poorer temporal fidelity, but improved temporal precision to optogenetic and hybrid stimulation compared to acutely deafened mice. Significance. These findings show that the improvement to temporal fidelity and temporal precision provided by a hybrid stimulation paradigm can also be achieved in chronically deafened animals, albeit at higher levels of concurrent optogenetic stimulation levels.

Modulation of potassium conductances optimizes fidelity of auditory information.

Potassium channels in auditory neurons are rapidly modified by changes in the auditory environment. In response to elevated auditory stimulation, short-term mechanisms such as protein phosphorylation and longer-term mechanisms such as accelerated channel synthesis increase the amplitude of currents that promote high-frequency firing. It has been suggested that this allows neurons to fire at high rates in response to high sound levels. We have carried out simple simulations of the response to postsynaptic neurons to patterns of neurotransmitter release triggered by auditory stimuli. These demonstrate that the amplitudes of potassium currents required for optimal encoding of a low-amplitude auditory signal differ from those for louder sounds. Specifically, the cross-correlation of the output of a neuron with an auditory stimulus is improved by increasing potassium currents as sound amplitude increases. Temporal fidelity for low-frequency stimuli is improved by increasing potassium currents that activate at negative potentials, while that for high-frequency stimuli requires increases in currents that activate at positive membrane potentials. These effects are independent of the firing rate. Moreover, levels of potassium currents that maximize the fidelity of the output of an ensemble of neurons differ from those that maximize fidelity for a single neuron. This suggests that the modulatory mechanisms must coordinate channel activity in groups of neurons or an entire nucleus. The simulations provide an explanation for the modulation of the intrinsic excitability of auditory brainstem neurons by changes in environmental sound levels, and the results may extend to information processing in other neural systems.