(Image by A. Argun)Deep Learning for Imaging and Microscopy
Giovanni Volpe Symposium on AI, Neuroscience, and Aging, Stockholm, Sweden, 27 November 2023 Date: 27 November 2023 Time: 15:55
Video microscopy has a long history of providing insights and breakthroughs for a broad range of disciplines, from physics to biology. Image analysis to extract quantitative information from video microscopy data has traditionally relied on algorithmic approaches, which are often difficult to implement, time consuming, and computationally expensive. Recently, alternative data-driven approaches using deep learning have greatly improved quantitative digital microscopy, potentially offering automatized, accurate, and fast image analysis. However, the combination of deep learning and video microscopy remains underutilized primarily due to the steep learning curve involved in developing custom deep-learning solutions. To overcome this issue, we have introduced a software, DeepTrack 2.1, to design, train and validate deep-learning solutions for digital microscopy. We use it to exemplify how deep learning can be employed for a broad range of applications, from particle localization, tracking and characterization to cell counting and classification. Thanks to its user- friendly graphical interface, DeepTrack 2.1 can be easily customized for user-specific applications, and, thanks to its open-source object-oriented programming, it can be easily expanded to add features and functionalities, potentially introducing deep-learning-enhanced video microscopy to a far wider audience.
Complex Dynamics in Active Matter Systems, Frustration Effects, Magnus Forces and Synchronization
Charles Reichhardt
Los Alamos National Laboratory
30 November 2023, 16:30, Nexus
Active matter denotes systems with self-propulsion and arises in biological, soft, robotic, and social settings [1]. Here, we outline some of our group’s recent efforts in active systems, including active matter interacting with ordered and disordered substrates, where various kinds of active clogging and commensuration effects can occur that have connections with frustrated systems and Mott physics. We also discuss chiral active systems with a Magnus force, where we find edge currents similar to those found for topological systems or charged particles in magnetic fields. In the presence of quenched disorder, the chiral active system also shows side jump effects with an active matter Hall angle. Finally, we discuss coupled active matter swarmulators where, in addition to activity, the particles have an internal degree of freedom that can become synchronized or antisynchronized. This system shows a variety of new kinds of motility-induced phase-separated states, including active matter stripes, frustrated states, gels, cluster fluids, and glassy states.
[1] Active Brownian particles in complex and crowded environments, Clemens Bechinger, Roberto Di Leonardo, Hartmut Lowen, Charles Reichhardt Giorgio Volpe, and Giovanni Volpe, Reviews of Modern Physics 88 045006 (2016).
Since their invention by Ashkin et al. in the 1980s, optical tweezers have evolved into an indispensable tool in physics, especially in biophysics, with applications spanning from cell sorting to stretching single DNA strands. By the 2000s, commercial systems became available. Nevertheless, owing to their unique requirements, many labs prefer to construct their own, often drawing inspiration from existing designs.
A prominent optical tweezers design is the “miniTweezers” system, pioneered by Bustamante’s group in the late 1990s. This system has been widely adopted globally for force spectroscopy experiments on single molecules, including DNA, proteins, and RNA.
In this presentation, we unveil an advanced iteration of the miniTweezers. By enhancing its control and acquisition capabilities, we’ve augmented its versatility, enabling new experiment types. A significant breakthrough is the integration of real-time image feedback, which paves the way for automated procedures via deep learning-based image analysis, the first of which we demonstrate in this presentation.
We showcase this system’s capabilities through three distinct experiments:
A pulling experiment on a λ-DNA strand. By tethering DNA between two polystyrene beads – one anchored in a micropipette and the other manipulated by the tweezer – we illustrate near-complete automation, with the system autonomously handling bead trapping, attachment of the DNA and the pulling procedure.
An exploration of Coulomb interactions between charged particles. Here, one particle remains in a micropipette, while the other orbits the stationary bead, providing a 3D map of the interaction.
A non-contact stretching experiment on red blood cells is conducted under low osmotic pressure conditions. Modulating the laser power induces cell elongation along the laser’s propagation direction. By correlating this elongation with the optical force exerted by the lasers, we present a simple and non-invasive method to measure membrane rigidity.
In summary, these advancements mark a significant leap in the capabilities and applications of optical tweezers in biophysics. As we push the boundaries of automation and precision, we envision a future where such instruments can unravel even more intricate molecular interactions and cellular mechanics, setting the stage for groundbreaking discoveries.
Intracavity optical tweezers are a valuable tool for capturing microparticles in water by exploiting the nonlinear feedback effect induced by particle motion when confined in a laser cavity. This feedback effect arises as a consequence of the particle confinement inside a laser cavity, leading to fluctuations in the optical losses of the cavity due to Brownian motion. Our study extends intracavity optical trapping to both single-beam and counter-propagating dual-beam configurations, allowing us to investigate what happens when the two beams are slightly misaligned.
We used a 1030-nm Yb-doped ring fiber laser (pumped at 976 nm) with a hybrid optical path that allows light propagation in both fiber and air. To switch between single-beam and dual-beam configurations, a free-space removable isolator is incorporated, resulting in a single-beam configuration when the isolator is installed and a dual-beam configuration when the isolator is removed. We tracked particle positions in 3D using digital holographic microscopy and simultaneously measured the powers of the two counter-propagating beams, providing insight into the feedback effect. A crucial aspect of our experiment is the ability to introduce a transverse offset between the two optical beams in the two-beam configuration, resulting in periodic particle motion.
Our study has revealed a periodic orbital rotation of the particle that is closely related to the behavior of the two laser beam powers. We investigated the effect of beam separation and laser pump power on this phenomenon.
This phenomenon results from the interplay of gradient force, scattering force, and nonlinear feedback. The trapped particle undergoes periodic transitions between the two traps, causing a periodic variation in the laser power of the two beams. As a result, the particle acts as a micro-isolator, attenuating the beam in which it is trapped and amplifying the other beam. It was also observed that the duration of the transition increases as the pump power decreases and the distance between the two traps increases.
Future research will focus on refining the trapping configurations to exploit their potential for precise particle manipulation in the field of nanothermodynamics.
Logo of the Gun and Bertil Stohne’s Foundation. (Image from the Foundation’s website.)
Yu-Wei Chang received one of the Gun and Bertil Stohnes Foundation Prizes for PhD students, with his recent research focusing on deep learning analysis of longitudinal tau pathology. The price consists in 100000 SEK given to one – or shared between two – student(s) at a Swedish university.
The Gun and Bertil Stohnes Foundation awards this prize to research projects in geriatrics that the Board deems of exceptional interest and value.
Anna Canal Garcia, from Karolinska Institutet and supervised by Prof. Joana B. Pereira, is the other recipient of this award. Anna’s research focuses on the intricate multilayer network analysis of brain neuroimaging data.
Non-monotonic size dependence of group formation on environmental crowding. (Excerpt from Fig. 2 of the manuscript.)Environmental Memory Boosts Group Formation of Clueless Individuals
Cristóvão S. Dias, Manish Trivedi, Giovanni Volpe, Nuno A. M. Araújo, Giorgio Volpe
Nature Communications, 14, 7324 (2023)
doi: 10.1038/s41467-023-43099-0
arXiv: 2306.00516
The formation of groups of interacting individuals improves performance and fitness in many decentralised systems, from micro-organisms to social insects, from robotic swarms to artificial intelligence algorithms. Often, group formation and high-level coordination in these systems emerge from individuals with limited information-processing capabilities implementing low-level rules of communication to signal to each other. Here, we show that, even in a community of clueless individuals incapable of processing information and communicating, a dynamic environment can coordinate group formation by transiently storing memory of the earlier passage of individuals. Our results identify a new mechanism of indirect coordination via shared memory that is primarily promoted and reinforced by dynamic environmental factors, thus overshadowing the need for any form of explicit signalling between individuals. We expect this pathway to group formation to be relevant for understanding and controlling self-organisation and collective decision making in both living and artificial active matter in real-life environments.
Opponent Saikat Chatterjee (on Zoom), Yu-Wei Chang (left), and PhD co-supervisor Joana B. Pereira (right). (Photo by P.-J. Chien.)Yu-Wei Chang completed the first half of his doctoral studies and he defended his half-time on the 3rd of November 2023.
The presentation was conducted in a hybrid format, with part of the audience present in the Nexus room and the remainder connected through Zoom. The seminar comprised a presentation covering both his completed and planned projects, followed by a discussion and questions posed by his opponent, Prof. Saikat Chatterjee.
The presentation commenced with an overview of his concluded projects. The first project involves handling incomplete medical datasets using neural networks and is published in ‘Machine Learning: Science and Technology.‘ It then transitioned to his second project, focusing on the development of software for brain connectivity analysis using multilayer graphs and deep learning. The corresponding repository is accessible on GitHub. In the final segment, he outlined the proposed continuation of his PhD, discussing an ongoing project centered around the deep learning analysis of longitudinal brain neural imaging data.
A dielectric particle under the influence of the gradient and scattering force. (Image by L. Pérez García.)Laura Pérez García defended her PhD thesis on the 12th of October at 13:15. Congrats!
The defense took place in Faraday, Institutionen för fysik, Origovägen 6b, Göteborg.
Title: Advanced methods for the calibration of optical tweezers
Abstract: Optical tweezers have enabled the manipulation of micron-sized particles with great accuracy since their invention by Arthur Ashkin and colleagues in the 1980s. This technique has had an impact in multiple areas, including biology, physics, nanotechnology, spectroscopy, soft matter and nanothermodynamics. To perform experiments requiring quantitative transduction of forces with optical tweezers, the optical tweezers need to be calibrated; that is their stiffness needs to be determined. In this thesis, I present the results that I have obtained for the calibration of optical tweezers using probabilistic approaches. The goal of these approaches is to use the available data most efficiently and even be able to have an estimation of the error associated with the calibration. This is of the utmost importance when one has limited data, as is often the case with systems out of equilibrium, low signal-to-noise ratios, and systems in which the conditions change with time quite fast. This thesis is divided into two problems. The first problem I had was the unavailability of a comprehensive method to measure force fields in extended, non-conservative, and unstable equilibrium points. For this problem I used Bayesian inference in the form of a maximum likelihood estimator, which allowed me to characterize the force field even in conditions previously not possible to tackle. This parameter-free method called FORMA proved to be more precise, accurate, faster, and less data-intensive than the previous conventional method, i.e. equipartition, MSD, ACF, and PSF. Not only that, but it allowed me to characterize the force field generated by Laguerre-Gaussian beams with different orbital/spin angular momentum, a double-well potential, and a speckle pattern. The second problem I tackled was the error in the estimators due to limited bandwidth and finite integration time. For this, we developed the joint probability density function of observing the particle at a given set of positions and times. We derived generalized formulas for the calibration methods; these new formulas successfully correct for the overestimation of the stiffness and the underestimation of the diffusion coefficient caused by a finite integration time; it also accounts for the limited sampling frequency and the trajectory length. In general, this thesis shows the potential of having a probabilistic and inference approach to the problem of deducing the set of parameters that characterize the Langevin equation of motion of a particle from a time series of its position. The solution to this problem has applications not only to the calibration of optical tweezers but also to microrheology, the behavior of single molecules inside a cell, and animal migration.
Schematic of a red blood cell in a focused optical beam. (Image by E. Erdem.)Optical trapping of red blood cells and different geometrical shapes
Emir Erdem
Red Blood Cells (RBC), also known as erythrocyts, are essential cells that are present in the blood of every vertebrate. Because of their hemoglobin protein content, they carry oxygen to the cells and perform a vital function. Due to their complex shapes, behavior of cells like RBCs under optical forces are not fully been discovered. In this study, the behavior of RBCs as well as other shapes under optical trap are simulated using OTGO which is a numeric toolbox utilizing geometrical optics approximation for optical calculations. As a result of the simulations, it is observed that the RBC aligns itself in a vertical configuration, parallel to the incident beam propagating towards the cell from below. Conducted static analysis showed that it is possible to stably trap a RBC in all three dimensions. The center of the trap is near the edge of the cell, where the thickness is larger. After the analysis on RBC, how well different geometrical shapes can optically be trapped are investigated by integrating different shapes modeled by spherical harmonics to OTGO. A similar static analysis is conducted on a dumbbell shape and its trapping effectiveness is compared with an ellipsoid. A dumbbell shape can effectively be trapped in the horizontal plane similar to an ellipsoid, but in the light propagation direction, it is more challenging to trap the shape and it requires modifications on optical properties of the setup. The aim of this study after this point is to optimize the optical force calculations by training a neural network model and to apply flow conditions to cells.
(Image adapted from here.)Giovanni Volpe received the Faculty of Science’s 2023 Research Award for using methods from physics to look into complex and biological systems.
The Research Award of the Faculty of Science of the University of Gothenburg recognizes development of a research specialization that significantly contributes to novelty in the faculty’s research. The award recipient receives a diploma and a research grant of SEK 250,000. This year, the award ceremony will be held on 19 October.
