Spatiotemporal Coherence Research Articles

In vivo volumetric analysis of retinal vascular hemodynamics in mice with spatio-temporal optical coherence tomography.

Microcirculation and neurovascular coupling are important parameters to study in neurological and neuro-ophthalmic conditions. As the retina shares many similarities with the cerebral cortex and is optically accessible, a special focus is directed to assessing the chorioretinal structure, microvasculature, and hemodynamics of mice, a vital animal model for vision and neuroscience research. We aim to introduce an optical imaging tool enabling in vivo volumetric mouse retinal monitoring of vascular hemodynamics with high temporal resolution. We translated the spatio-temporal optical coherence tomography (STOC-T) technique into the field of small animal imaging by designing a new optical system that could compensate for the mouse eye refractive error. We also developed post-processing algorithms, notably for the assessment of (i) localized hemodynamics from the analysis of pulse wave-induced Doppler artifact modulation and (ii) retinal tissue displacement from phase-sensitive measurements. We acquired high-quality, in vivo volumetric mouse retina images at a rate of 113Hz over a lateral field of view of . We presented high-resolution en face images of the retinal and choroidal structure and microvasculature from various layers, after digital aberration correction. We were able to measure the pulse wave velocity in capillaries of the outer plexiform layer with a mean speed of 0.35mm/s and identified venous and arterial pulsation frequency and phase delay. We quantified the modulation amplitudes of tissue displacement near major vessels (with peaks of 150nm), potentially carrying information about the biomechanical properties of the retinal layers involved. Last, we identified the delays between retinal displacements due to the passing of venous and arterial pulse waves. The developed STOC-T system provides insights into the hemodynamics of the mouse retina and choroid that could be beneficial in the study of neurovascular coupling and vasculature and flow speed anomalies in neurological and neuro-ophthalmic conditions.

Microfluctuations in Capillary Lumens Independent of Pericyte Lining Density in the Anesthetized Mouse Cortex.

This study aimed to examine the spatiotemporal coherence of capillary lumen fluctuations in relation to spatial variations in the pericyte lining in the cortex of anesthetized mice. Two-photon microscopic angiography data (previously published) were reanalyzed, and spatial variations in capillary diameter fluctuations at rest and in capillary lining with vascular mural cells were measured along capillary centerlines. Relatively large diameters of the capillaries (5.5 μm) coincided with a dense pericyte lining, while small capillaries (4.3 μm) had a sparse pericyte lining. Temporal variations had a frequency of about 0.1 Hz with an amplitude of 0.5 μm, which were negatively correlated with pericyte lining density. Spatial frequency analysis further revealed a common pattern of spatial variations in capillary diameter and pericyte lining, but temporal variations differed. The temporal variations in capillary lumens were locally distinct from those in neighboring locations, suggesting intrinsic fluctuations independent of the pericyte lining. Capillary lumens in the brain exhibit slow microfluctuations that are independent of pericyte lining. These microfluctuations could affect the distribution of flowing blood cells and may be important for homogenizing their distribution in capillary networks.

Characterizing the dynamics of multi-scale global high impact weather events

The quantitative characterization and prediction of localized severe weather events that emerge as coherences generated by the highly non-linear interacting multivariate dynamics of global weather systems poses a significant challenge whose solution is increasingly important in the face of climate change where weather extremes are on the rise. As weather measurement systems (multiband satellite, radar, etc) continue to dramatically improve, increasingly complex time-dependent multivariate 3D datasets offer the potential to inform such problems but pose an increasingly daunting computational challenge. Here we describe the application to global weather systems of a novel computational method called the Entropy Field Decomposition (EFD) capable of efficiently characterizing coherent spatiotemporal structures in non-linear multivariate interacting physical systems. Using the EFD derived system configurations, we demonstrate the application of a second novel computational method called Space-Time Information Trajectories (STITs) that reveal how spatiotemporal coherences are dynamically connected. The method is demonstrated on the specific phenomenon known as atmospheric rivers (ARs) which are a prime example of a highly coherent, in both space and time, severe weather phenomenon whose generation and persistence are influenced by weather dynamics on a wide range of spatial and temporal scales. The EFD reveals how the interacting wind vector field and humidity scalar field couple to produce ARs, while the resulting STITS reveal the linkage between ARs and large-scale planetary circulations. The focus on ARs is also motivated by their devastating social and economic effects that have made them the subject of increasing scientific investigation to which the EFD may offer new insights. The application of EFD and STITs to the broader range of severe weather events is discussed.

A global dataset of the fraction of absorbed photosynthetically active radiation for 1982–2022

The fraction of absorbed photosynthetically active radiation (FPAR) is an essential biophysical parameter that characterizes the structure and function of terrestrial ecosystems. Despite the extensive utilization of several satellite-derived FPAR products, notable temporal inconsistencies within each product have been underscored. Here, the new generation of the GIMMS FPAR product, GIMMS FPAR4g, was developed using a combination of a machine learning algorithm and a pixel-wise multi-sensor records integration approach. PKU GIMMS NDVI, which eliminates the orbital drift and sensor degradation issues, was used as the data source. Comparisons with ground-based measurements indicate root mean square errors ranging from 0.10 to 0.14 with R-squared ranging from 0.73 to 0.87. More importantly, our product demonstrates remarkable spatiotemporal coherence and continuity, revealing a persistent terrestrial darkening over the past four decades (0.0004 yr−1, p < 0.001). The GIMMS FPAR4g, available for half-month intervals at a spatial resolution of 1/12° from 1982 to 2022, promises to be a valuable asset for in-depth analyses of vegetation structures and functions spanning the last 40 years.

Burst-Enhanced Super-Resolution Network (BESR).

Multi-frame super-resolution (MFSR) leverages complementary information between image sequences of the same scene to increase the resolution of the reconstructed image. As a branch of MFSR, burst super-resolution aims to restore image details by leveraging the complementary information between noisy sequences. In this paper, we propose an efficient burst-enhanced super-resolution network (BESR). Specifically, we introduce Geformer, a gate-enhanced transformer, and construct an enhanced CNN-Transformer block (ECTB) by combining convolutions to enhance local perception. ECTB efficiently aggregates intra-frame context and inter-frame correlation information, yielding an enhanced feature representation. Additionally, we leverage reference features to facilitate inter-frame communication, enhancing spatiotemporal coherence among multiple frames. To address the critical processes of inter-frame alignment and feature fusion, we propose optimized pyramid alignment (OPA) and hybrid feature fusion (HFF) modules to capture and utilize complementary information between multiple frames to recover more high-frequency details. Extensive experiments demonstrate that, compared to state-of-the-art methods, BESR achieves higher efficiency and competitively superior reconstruction results. On the synthetic dataset and real-world dataset of BurstSR, our BESR achieves PSNR values of 42.79 dB and 48.86 dB, respectively, outperforming other MFSR models significantly.

Functional analysis of variance (ANOVA) for carbon flux estimates from remote sensing data

Abstract. The constellation of Earth-observing satellites has now produced atmospheric greenhouse gas concentration estimates covering a period of several years. Their global coverage is providing additional information on the global carbon cycle. These products can be combined with complex inversion systems to infer the magnitude of carbon sources and sinks around the globe. Multiple factors, including the atmospheric transport model and satellite product aggregation method, can impact such flux estimates. Analysis of variance (ANOVA) is a well-established statistical framework for estimating common signals while partitioning variability across factors in the analysis of experiments. Functional ANOVA extends this approach with a statistical model that incorporates spatiotemporal correlation for each ANOVA component. The approach is illustrated on inversion experiments with different satellite retrieval aggregation methods and identifies consistent significant patterns in flux increments that span large spatial scales. Functional ANOVA identifies these patterns while accounting for the uncertainty at small spatial scales that is attributed to differences in the aggregation method. Functional ANOVA is also applied to a recent flux model intercomparison project (MIP), and the relative magnitudes of inversion system effects and data source (satellite versus in situ) are similar but exhibit slightly different importance for fluxes over different continents. In all examples, the unexplained residual variability is locally sizable in magnitude but with limited spatial and temporal correlation. These common behaviors across flux inversion experiments demonstrate the diagnostic capability for functional ANOVA to simultaneously distinguish the spatiotemporal coherence of carbon cycle processes and algorithmic factors.

Multiwavelength laser doppler holography (MLDH) in spatiotemporal optical coherence tomography (STOC-T)

Spatiotemporal optical coherence tomography (STOC-T) is the novel modality for high-speed, crosstalk- and aberration-free volumetric imaging of biological tissue in vivo. STOC-T extends the Fourier-Domain holographic Optical Coherence Tomography by the spatial phase modulation that enables the reduction of spatial coherence of the tunable laser. By reducing the spatial coherence of the laser, we suppress coherent noise, and, consequently, improve the imaging depth. Furthermore, we remove geometrical aberrations computationally in postprocessing. We recently demonstrated high-speed, high-resolution STOC-T of human retinal imaging in vivo. Here, we show that the dataset produced by STOC-T can be processed differently to reveal blood flow in the human retina in vivo. To render the blood flow, we first pre-process STOC-T holographic data to access the approximated information about the Doppler-shifted optical field backscattered from the sample. Then, we analyze it using methods from the laser Doppler flowmetry, namely, by analyzing the Doppler broadening caused by moving light scatterers (red blood cells). However, contrary to conventional approaches, we use multiple illumination wavelengths. This enables us to render the structural volumetric and blood flow images from the same dataset concurrently. Our method, denoted as multiwavelength laser Doppler holography (MLDH), links laser Doppler flowmetry with multiwavelength holographic detection to enable noninvasive visualization and possible blood flow quantification at different human retina layers at high speeds and high transverse resolution in vivo.

Imaging the retinal and choroidal vasculature using Spatio-Temporal Optical Coherence Tomography (STOC-T)

Spatio-Temporal Optical Coherence Tomography (STOC-T) is a novel imaging technique using light with controlled spatial and temporal coherence. Retinal images obtained using the STOC-T system maintain high resolution in all three dimensions, on a sample of about 700 μm, without the need for mechanical scanning. In the present work, we use known data processing algorithms for optical coherence tomography angiography (OCTA) and modify them to improve the rendering of the vasculature in the human retina at different depths by introducing the angio STOC-T method. The algorithms are primarily sensitive to the strong signal phase variance corresponding to the appearance of a wide Doppler band in STOC-T signals obtained for millisecond exposure times. After using STOC-T angiography, we can render high contrast images of the choroid.

Method for generating spatiotemporal coherency vortices and spatiotemporal dislocation curves.

A simple method for designing spatiotemporal coherency vortices (STCVs) and spatiotemporal dislocation curves (STDCs) is introduced by means of coherent-mode representation and Fourier transforms. A partially coherent pulsed beam is represented by an incoherent superposition of a Gaussian and a Hermite-Gaussian pulsed beam with different waist positions. It well demonstrates that there exist STCVs and STDCs in the space-time plane. The detailed numerical calculations are performed to address the dependence of waist distance of two modes, reference position, beam order, distribution of original spectrum, topological charge and mode weights ratio on the STCVs and STDCs. The physical interpretation behind numerical results is shown. A possible scheme for experimental synthesis of the STCVs is proposed. The obtained results may have potential applications in the fields of light-matter interaction, spatiotemporal spin-orbit angular momentum coupling and STCV-based optical trapping and optical manipulation.

Spatio-temporal coherence of circadian clocks and temporal control of differentiation in Anabaena filaments.

Circadian clock arrays in multicellular filaments of the heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 display remarkable spatio-temporal coherence under nitrogen-replete conditions. To shed light on the interplay between circadian clocks and the formation of developmental patterns, we followed the expression of a clock-controlled gene under nitrogen deprivation, at the level of individual cells. Our experiments showed that differentiation into heterocysts took place preferentially within a limited interval of the circadian clock cycle, that gene expression in different vegetative intervals along a developed filament was discoordinated, and that the circadian clock was active in individual heterocysts. Furthermore, Anabaena mutants lacking the kaiABC genes encoding the circadian clock core components produced heterocysts but failed in diazotrophy. Therefore, genes related to some aspect of nitrogen fixation, rather than early or mid-heterocyst differentiation genes, are likely affected by the absence of the clock. A bioinformatics analysis supports the notion that RpaA may play a role as master regulator of clock outputs in Anabaena, the temporal control of differentiation by the circadian clock and the involvement of the clock in proper diazotrophic growth. Together, these results suggest that under nitrogen-deficient conditions, the clock coherent unit in Anabaena is reduced from a full filament under nitrogen-rich conditions to the vegetative cell interval between heterocysts.IMPORTANCECircadian clocks, from unicellular organisms to animals, temporally align biological processes to day and night cycles. We study the dynamics of a circadian clock-controlled gene at the individual cell level in the multicellular filamentous cyanobacterium Anabaena, under nitrogen-stress conditions. Under these conditions, some cells along filaments differentiate to carry out atmospheric nitrogen fixation and lose their capability for oxygenic photosynthesis. We found that clock synchronization is limited to organismic units of contiguous photosynthetic cells, contrary to nitrogen-replete conditions in which clocks are synchronized over a whole filament. We provided evidence that the circadian clock regulates the process of differentiation, allowing it to occur preferentially within a limited time window during the circadian clock period. Lastly, we present evidence that the signal from the core clock to clock-regulated genes is conveyed in Anabaena as in unicellular cyanobacteria.

Anomalous Relativistic Emission from Self-Modulated Plasma Mirrors.

The interaction of intense laser pulses with plasma mirrors has demonstrated the ability to generate high-order harmonics, producing a bright source of extreme ultraviolet (XUV) radiation and attosecond pulses. Here, we report an unexpected transition in this process. We show that the loss of spatiotemporal coherence in the reflected high harmonics can lead to a new regime of highly efficient coherent XUV generation, with an extraordinary property where the radiation is directionally anomalous, propagating parallel to the mirror surface. With analytical calculations and numerical particle-in-cell simulations, we discover that the radiation emission is due to laser-driven oscillations of relativistic electron nanobunches that originate from a plasma surface instability.

Alpha-frequency feedback to early visual cortex orchestrates coherent naturalistic vision.

During naturalistic vision, the brain generates coherent percepts by integrating sensory inputs scattered across the visual field. Here, we asked whether this integration process is mediated by rhythmic cortical feedback. In electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) experiments, we experimentally manipulated integrative processing by changing the spatiotemporal coherence of naturalistic videos presented across visual hemifields. Our EEG data revealed that information about incoherent videos is coded in feedforward-related gamma activity while information about coherent videos is coded in feedback-related alpha activity, indicating that integration is indeed mediated by rhythmic activity. Our fMRI data identified scene-selective cortex and human middle temporal complex (hMT) as likely sources of this feedback. Analytically combining our EEG and fMRI data further revealed that feedback-related representations in the alpha band shape the earliest stages of visual processing in cortex. Together, our findings indicate that the construction of coherent visual experiences relies on cortical feedback rhythms that fully traverse the visual hierarchy.

Analysis and application of spatio-temporal correlation characteristics of measured ocean ambient noise

Gain in sonar signal processing is closely linked to the spatio-temporal coherence characteristics of the ocean ambient noise field. The gain relies on the spatio-temporal coherence coefficient of the signal and noise, with the aim of maximizing the former and minimizing the latter. Currently, there has been ample research on the spatial characteristics of the noise field, while studies on the temporal coherence characteristics of single-point noise fields are limited. In this paper, a temporal and spatial coherence model of wind-induced noise is established based on the normal mode theory, and the impact of bandwidth and spectral structure on the time coherence coefficient of wind-induced noise is analyzed.To measure the environmental noise in 103 m of shallow water in the South China Sea, a 64-element vertical array was utilized. The results demonstrate that the measured vertical spatial correlation coefficient aligns closely with the theoretical findings when wind-induced noise is predominant. The measured temporal correlation coefficient of narrowband noise exhibits a cosine function with gradual attenuation of the envelope, and the correlation radius remains independent of frequency. As the bandwidth increases, the measured broadband noise temporal correlation radius gradually decreases. Wind speed has minimal influence on the temporal and spatial correlation coefficients of wind-induced noise. In the presence of interferences such as ships and pulses, the measured temporal and spatial correlation coefficients of wind-induced noise exhibit larger values in certain intervals.Lastly, leveraging the characteristic that the temporal coherence radius of noise is significantly smaller than that of the line spectrum signal, a single-hydrophone cross-spectrum method is proposed to process the line spectrum signal. This approach effectively enhances the signal-to-noise ratio of the line spectrum.

A Hanbury Brown and Twiss renascence: measurement of photon correlations yields spatio-temporal coherence

Investigations of photon correlations similar to the Hanbury Brown and Twiss experiment are since the advent of quantum optics in the center of both fundamental and application-oriented research. We derive a factorial moment-generating function of the probability distribution of electromagnetic radiation emitted by a source and absorbed by a photodetector from which we calculate an analytical expression for the second-order correlation coefficient g^{(2)} which reflects spatial coherence properties of the emitted light. The measurement of g^{(2)} thus allows to retrieve the spatial coherence parameter of the light source in terms of the combination of source area, source-detector distance, wavelength and detector area. The validity of the concept is proven by investigating g^{(2)} of true thermal light from a Xenon arc lamp and from the sun for various detector areas, in excellent agreement with the theory. Finally, we suggest a novel scheme for determining light source diameters by exploiting the spatially dependent statistics and confirm its validity by exemplary calculations. These results based on radiation thermodynamics and photon statistics give fresh insight into quantum optical properties of classical light sources, photon correlations and photodetection with promising applications perspectives, more than 68 years after the original Hanbury Brown and Twiss experiment.

Platform motion estimation in multiple-input multiple-output synthetic aperture sonar with coupled variational autoencoders

Synthetic aperture sonar (SAS) utilizes the motion of the platform carrying the sonar system to synthesize an aperture that is much longer than thephysical antenna by coherently combining data from several pings. Coherent processing in SAS requires platform motion estimation and compensation with sub-wavelength accuracy for high-resolution imaging. Micronavigation, i.e., through-the-sensor platform motion estimation from spatio-temporal coherence measurements of diffuse backscatter on overlapping recordings between successive pings, is essential when positioning information from navigational instruments is absent or inadequately accurate. Representation learning with a variational autoencoder (VAE) offers an unsupervised data-driven micronavigation solution. In this study, we introduce a hierarchical variational model implemented with coupled VAEs to relate the common latent features between datasets of coherence measurements in broadband multiple-input multiple-output SAS systems. We show that self-supervising the training process of independently parameterized but coupled VAEs improves significantly the accuracy of the micronavigation estimates.

Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring

Cyanobacteria harmful algal blooms (cyanoHABs) present a critical public health challenge for aquatic resource and public health managers. Satellite remote sensing is well-positioned to aid in the identification and mapping of cyanoHABs and their dynamics, giving freshwater resource managers a tool for both rapid and long-term protection of public health. Monitoring cyanoHABs in lakes and reservoirs with remote sensing requires robust processing techniques for generating accurate and consistent products across local and global scales at high revisit rates. We leveraged the high spatial and temporal resolution chlorophyll-a (Chla) and phycocyanin (PC) maps from two multispectral satellite sensors, the Sentinel-2 (S2) MultiSpectral Instrument (MSI) and the Sentinel-3 (S3) Ocean Land Colour Instrument (OLCI) respectively, to study bloom dynamics in Utah Lake, United States, for 2018. We used established Mixture Density Networks (MDNs) to map Chla from MSI and train new MDNs for PC retrieval from OLCI, using the same architecture and training dataset previously proven for PC retrieval from hyperspectral imagery. Our assessment suggests lower median uncertainties and biases (i.e., 42% and -4%, respectively) than that of existing top-performing PC algorithms. Additionally, we compared bloom trends in MDN-based PC and Chla products to those from a satellite-derived cyanobacteria cell density estimator, the cyanobacteria index (CI-cyano), to evaluate their utility in the context of public health risk management. Our comprehensive analyses indicate increased spatiotemporal coherence of bloom magnitude, frequency, occurrence, and extent of MDN-based maps compared to CI-cyano and potential for use in cyanoHAB monitoring for public health and aquatic resource managers.

Poster Session: Optoretinography-based frequency characterization of the retinal response to a chirped flickering light.

In this contribution, we present experimental results of in vivo characterization of the photoreceptor's response to a chirped flickering white light stimulating the retina. We acquire the ORG signal with Spatio-Temporal Optical Coherence Tomography (STOC-T) setup, which combines both temporal and coherence gating to overcome limitations present in Full Field Fourier Domain Optical Coherence Tomography. From the acquired volumes, we extract the changes in optical path length (OPL) between the inner and outer photoreceptor junction (ISOS) and the cone outer segment tips (COST). We perform the measurements for frequencies ranging from 5 Hz to 50 Hz. The chirped flickering facilitates significantly shorter data acquisition time. We present results of in vivo measurement from three volunteers. Our results show that we can measure OPL changes between ISOS and COST occurring in response to a chirped flickering stimulation in a reproducible manner and resolve the amplitude of the response in the function of flicker frequency.

Inertial effects in sedimenting suspensions of solid spheres in a liquid

Particle-resolved Direct Numerical Simulations have been performed on the gravitational settling of mono-disperse solid spheres in a viscous fluid and triply periodic domain. In a comprehensive study, the bulk solid volume concentration was varied from ϕ=0.5 to 30%. To study the effect of inertia, three different Galileo numbers were considered in the inertial regime, Ga=144, 178 and 210, for which a single settling sphere exhibits distinctly different wake and path characteristics. The particle/fluid mass density ratio was fixed at 1.5. We find that for ϕ=2−30% the suspension microstructure and dynamics depend predominantly on the bulk concentration. In qualitative agreement with previous studies in literature, three different sedimentation regimes can be distinguished: (1) the dilute concentration regime for ϕ≲2% with preferential settling of particles in vertical trains, (2) the moderate concentration regime for 2%≲ϕ≲10% with preferential settling of particles in horizontal pairs with an interparticle distance of ∼ 1.5 particle diameters, and (3) the dense concentration regime for ϕ≳10% with a nearly random (“hard-sphere”) distribution of the particles in space. The clustering of particles is dictated by, respectively, trapping of particles in the wake of other particles, a drafting–kissing–tumbling (DKT) instability by which two vertically aligned particles quickly reorient themselves into a horizontally aligned particle pair, and short-range multiparticle interactions through viscous lubrication and to a lesser extent collisions between particles. In all cases, hindered settling at a reduced speed is observed as compared to a single settling sphere. The well-known Richardson–Zaki relation for the mean sedimentation velocity appears valid only for the dense concentration regime. We provide ample evidence that in the dense regime the characteristic velocity and time scales of particle motion are proportional to gDp and Dp/g, respectively, with g the gravitational acceleration and Dp the particle diameter. We also observe an ω−3 scaling of the particle velocity spectra for ωDp/g≳0.4 and we propose a model to explain this scaling behavior, based on the inertial response of the particles to small-scale flow perturbations. Kinematic waves, i.e., vertically propagating plane waves in the local concentration field, are observed in all cases, though unrelated particle motions are responsible for significant loss of the spatio-temporal coherence of the waves. The wave speed was determined from repeated space–time autocorrelations of the local concentration field and appears in reasonable agreement with Kynch sedimentation theory using the Richardson–Zaki relation. The passage of kinematic waves causes perturbations in the particle velocity at a frequency that matches well with peak frequencies in the particle velocity spectra for concentrations up to ϕ≈10%. The time-lagged cross-correlation of the vertical and horizontal particle velocity suggests that kinematic waves may trigger DKT instabilities, while conversely DKT instabilities may be responsible for the onset of kinematic waves. Finally, we suggest that obstruction and perturbation of the particle wake by neighboring particles could offer an explanation for the small influence of the Galileo number on the suspension behavior for ϕ=2−30%.

Symmetry-reduced low-dimensional representation of large-scale dynamics in the asymptotic suction boundary layer

An important feature of turbulent boundary layers are persistent large-scale coherent structures in the flow. Here, we use Dynamic Mode Decomposition (DMD), a data-driven technique designed to detect spatio-temporal coherence, to construct optimal low-dimensional representations of such large-scale dynamics in the asymptotic suction boundary layer (ASBL). In the ASBL, fluid is removed by suction through the bottom wall, resulting in a constant boundary layer thickness in streamwise direction. That is, the streamwise advection of coherent structures by the mean flow ceases to be of dynamical importance and can be interpreted as a continuous shift symmetry in streamwise direction. However, this results in technical difficulties, as DMD is known to perform poorly in presence of continuous symmetries. We address this issue using symmetry-reduced DMD (Marensi et al., 2023), and find the large-scale dynamics of the ASBL to be low-dimensional indeed and potentially self-sustained, featuring ejection and sweeping events at large scale. Interactions with near-wall structures are captured when including only a few more modes.

Traveling waves induced by gamma entrainment can explain its therapeutic effects for Alzheimer’s disease

AbstractBackgroundNon‐invasive 40Hz sensory‐induced brain entrainment has shown promising results in Alzheimer’s disease (AD) therapy (Chan et al., medRxiv, 2021; Chan et al., Alzheimer’s &amp; Dementia, 2021). We previously reported on the network‐level mechanisms underlying the spatial and temporal coherence of the induced brain rhythms during gamma entrainment in dementia patients (Lahijanian et al., bioRxiv, 2021). Here, we posit that the induced gamma oscillations propagate as traveling waves circling each hemisphere of the cortex, and that the induction of such waves can explain the spatiotemporal coherence between the frontal and parietal/occipital regions reported to be involved in cognitive processes.MethodEEG data were recorded from two healthy young adults during multi‐trial visual entrainment sessions with 22Hz flickering light. Due to the harmonic property of the brain’s entrained response (Jones et al., Journal of Alzheimer’s Disease, 2019), gamma entrainment was achieved at 44Hz. Separately, EEG data were recorded from 11 dementia patients in multi‐trial auditory entrainment sessions with 40Hz chirp input. The phase of the spatiotemporal pattern at the target gamma frequency was calculated across the entire scalp as an indicator of traveling waves.ResultShortly after the stimulation onset in the young healthy adults, a circling traveling wave is observed in each hemisphere (Fig. 1). The onset and the homogeneity of the induced wave pattern is modulated by the power of the 44Hz entrained oscillations (Fig. 2). The dementia patients can be divided into two groups of entrained and non‐entrained according to the induced gamma power (see Lahijanian et al., bioRxiv, 2021), and the travelling wave effect can be occasionally observed during the stimulation in the entrained group and not in the non‐entrained group.ConclusionCortical traveling waves modulate the brain dynamics and play a critical role in functions ranging from sensory processing to memory consolidation (Muller et al., Nature Reviews Neuroscience, 2018). Gamma entrainment induces traveling waves that connect the occipital/parietal regions of the cortex to the frontal region through the temporal region. The traveling wave promotes spatiotemporal coherence across the brain and hence can serve as a network‐level mechanism for explaining the therapeutic effects of gamma entrainment.