Browsing by Author "Volpe, G."

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Open Access
Aberrant cerebral network topology and mild cognitive impairment in early Parkinson’s disease
(John Wiley & Sons, Inc., 2015-05-06) Pereira, J. B.; Aarsland, D.; Ginestet, C. E.; Lebedev, A. V.; Wahlund, L. O.; Simmons, A.; Volpe, G.; Westman, E.
The aim of this study was to assess whether mild cognitive impairment (MCI) is associatedwith disruption in large-scale structural networks in newly diagnosed, drug-na€ıve patients with Parkin-son’s disease (PD). Graph theoretical analyses were applied to 3T MRI data from 123 PD patients and 56controls from the Parkinson’s progression markers initiative (PPMI). Thirty-three patients were classifiedas having Parkinson’s disease with mild cognitive impairment (PD-MCI) using the Movement DisordersSociety Task Force criteria, while the remaining 90 PD patients were classified as cognitively normal (PD-CN). Global measures (clustering coefficient, characteristic path length, global efficiency, small-world-ness) and regional measures (regional clustering coefficient, regional efficiency, hubs) were assessed inthe structural networks that were constructed based on cortical thickness and subcortical volume data.PD-MCI patients showed a marked reduction in the average correlation strength between cortical andsubcortical regions compared with controls. These patients had a larger characteristic path length andreduced global efficiency in addition to a lower regional efficiency in frontal and parietal regions com-pared with PD-CN patients and controls. A reorganization of the highly connected regions in the networkwas observed in both groups of patients. This study shows that the earliest stages of cognitive decline inPD are associated with a disruption in the large-scale coordination of the brain network and with adecrease of the efficiency of parallel information processing.
Open Access
Active Brownian motion tunable by light
(Institute of Physics Publishing, 2012) Buttinoni, I.; Volpe, G.; Kümmel, F.; Volpe, G.; Bechinger, C.
Active Brownian particles are capable of taking up energy from their environment and converting it into directed motion; examples range from chemotactic cells and bacteria to artificial micro-swimmers. We have recently demonstrated that Janus particles, i.e.gold-capped colloidal spheres, suspended in a critical binary liquid mixture perform active Brownian motion when illuminated by light. In this paper, we investigate in more detail their swimming mechanism, leading to active Brownian motion. We show that the illumination-borne heating induces a local asymmetric demixing of the binary mixture, generating a spatial chemical concentration gradient which is responsible for the particles self-diffusiophoretic motion. We study this effect as a function of the functionalization of the gold cap, the particle size and the illumination intensity: the functionalization determines what component of the binary mixture is preferentially adsorbed at the cap and the swimming direction (towards or away from the cap); the particle size determines the rotational diffusion and, therefore, the random reorientation of the particle; and the intensity tunes the strength of the heating and, therefore, of the motion. Finally, we harness this dependence of the swimming strength on the illumination intensity to investigate the behavior of a micro-swimmer in a spatial light gradient, where its swimming properties are space-dependent. © 2012 IOP Publishing Ltd.
Open Access
Active matter alters the growth dynamics of coffee rings
(OSA, 2018) Callegari, Agnese; Andaç, Tuğba; Weigmann, Pascal; Velu, Sabareesh K. P.; Pinçe, Erçağ; Volpe, G.; Volpe, Giovanni
We show that bacterial mobility starts playing a major role in determining the growth dynamics of the edge of drying droplets, as the droplet evaporation rate slows down.
Open Access
Active matter alters the growth dynamics of coffee rings
(Royal Society of Chemistry, 2019) Andaç, Tuğba; Weigmann, Pascal; Velu, Sabareesh K. P.; Pinçe, Erçağ; Volpe, G.; Volpe, Giovanni; Callegar, Agnese
How particles are deposited at the edge of evaporating droplets, i.e. the coffee ring effect, plays a crucial role in phenomena as diverse as thin-film deposition, self-assembly, and biofilm formation. Recently, microorganisms have been shown to passively exploit and alter these deposition dynamics to increase their survival chances under harshening conditions. Here, we show that, as the droplet evaporation rate slows down, bacterial mobility starts playing a major role in determining the growth dynamics of the edge of drying droplets. Such motility-induced dynamics can influence several biophysical phenomena, from the formation of biofilms to the spreading of pathogens in humid environments and on surfaces subject to periodic drying. Analogous dynamics in other active matter systems can be exploited for technological applications in printing, coating, and self-assembly, where the standard coffee-ring effect is often a nuisance.
Open Access
Active particles in complex and crowded environments
(American Physical Society, 2016-11) Bechinger, C.; Di Leonardo, R.; Löwen, H.; Reichhardt, C.; Volpe, G.
Differently from passive Brownian particles, active particles, also known as self-propelled Brownian particles or microswimmers and nanoswimmers, are capable of taking up energy from their environment and converting it into directed motion. Because of this constant flow of energy, their behavior can be explained and understood only within the framework of nonequilibrium physics. In the biological realm, many cells perform directed motion, for example, as a way to browse for nutrients or to avoid toxins. Inspired by these motile microorganisms, researchers have been developing artificial particles that feature similar swimming behaviors based on different mechanisms. These man-made micromachines and nanomachines hold a great potential as autonomous agents for health care, sustainability, and security applications. With a focus on the basic physical features of the interactions of self-propelled Brownian particles with a crowded and complex environment, this comprehensive review will provide a guided tour through its basic principles, the development of artificial self-propelling microparticles and nanoparticles, and their application to the study of nonequilibrium phenomena, as well as the open challenges that the field is currently facing.
Open Access
Anisotropic dynamics of a self-assembled colloidal chain in an active bath
(Royal Society of Chemistry, 2020) Aporvari, Mehdi Shafiei; Utkur, Mustafa; Sarıtaş, Emine Ülkü; Volpe, G.; Stenhammar, J.
Anisotropic macromolecules exposed to non-equilibrium (active) noise are very common in biological systems, and an accurate understanding of their anisotropic dynamics is therefore crucial. Here, we experimentally investigate the dynamics of isolated chains assembled from magnetic microparticles at a liquid–air interface and moving in an active bath consisting of motile E. coli bacteria. We investigate both the internal chain dynamics and the anisotropic center-of-mass dynamics through particle tracking. We find that both the internal and center-of-mass dynamics are greatly enhanced compared to the passive case, i.e., a system without bacteria, and that the center-of-mass diffusion coefficient D features a non-monotonic dependence as a function of the chain length. Furthermore, our results show that the relationship between the components of D parallel and perpendicular with respect to the direction of the applied magnetic field is preserved in the active bath compared to the passive case, with a higher diffusion in the parallel direction, in contrast to previous findings in the literature. We argue that this qualitative difference is due to subtle differences in the experimental geometry and conditions and the relative roles played by long-range hydrodynamic interactions and short-range collisions.
Open Access
Better stability with measurement errors
(Springer New York LLC, 2016-06) Argun, A.; Volpe, G.
Often it is desirable to stabilize a system around an optimal state. This can be effectively accomplished using feedback control, where the system deviation from the desired state is measured in order to determine the magnitude of the restoring force to be applied. Contrary to conventional wisdom, i.e. that a more precise measurement is expected to improve the system stability, here we demonstrate that a certain degree of measurement error can improve the system stability. We exemplify the implications of this finding with numerical examples drawn from various fields, such as the operation of a temperature controller, the confinement of a microscopic particle, the localization of a target by a microswimmer, and the control of a population.
Open Access
BRAPH: A graph theory software for the analysis of brain connectivity
(Public Library of Science, 2017) Mijalkov, M.; Kakaei, E.; Pereira, J. B.; Westman, E.; Volpe, G.
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. © 2017 Mijalkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Circular motion of asymmetric self-propelling partciles
(American Physical Society, 2013-05-09) Kummel, F.; Hagen, B.; Wittkowski, R.; Buttinoni, I.; Eichhorn, R.; Volpe, G.; Lowen, H.; Bechinger, C.
Micron-sized self-propelled (active) particles can be considered as model systems for characterizing more complex biological organisms like swimming bacteria or motile cells. We produce asymmetric microswimmers by soft lithography and study their circular motion on a substrate and near channel boundaries. Our experimental observations are in full agreement with a theory of Brownian dynamics for asymmetric self-propelled particles, which couples their translational and orientational motion.
Open Access
Computational toolbox for optical tweezers in geometrical optics
(Optical Society of America, 2014-03-04) Callegari, A; Mijalkov, M; Gököz, A. B.; Volpe, G.
Optical tweezers have found widespread application in many fields, from physics to biology. Here, we explain in detail how optical forces and torques can be described within the geometrical optics approximation, and we show that this approximation provides reliable results in agreement with experiments for particles whose characteristic dimensions are larger than the wavelength of the trapping light. Furthermore, we provide an object-oriented software package implemented in MATLAB for the calculation of optical forces and torques in the geometrical optics regime: Optical Tweezers in Geometrical Optics (OTGO). We provide all source codes for OTGO as well as documentation and code examples—e.g., standard optical tweezers, optical tweezers with elongated particles, the windmill effect, and Kramers transitions between two optical traps—necessary to enable users to effectively employ it in their research.
Open Access
Controlling active brownian particles in complex settings
(OSA, 2017) Velu, Sabareesh K. P.; Pinçe, Erçağ; Callegari, Agnese; Elahi, Parviz; Gigan, S.; Volpe, Giovanni; Volpe, G.
We show active Brownian particles (passive Brownian particles in a bacterial bath) switches between two long-term behaviors, i.e. gathering and dispersal of individuals, in response to the statistical properties of the underlying optical potential.
Open Access
A critical microscopic engine in an optical tweezers
(OSA, 2018) Schmidt, F.; Magazzù, Agnese; Callegari, A.; Biancofiore, Luca; Cichos, F.; Volpe, G.
An optically trapped absorbing microsphere in a sub-critical mixture rotates around the optical trap thanks to diffusiophoretic propulsion, which can be controlled by adjusting the optical power, the temperature, and the criticality of the mixture.
Open Access
Disorder-mediated crowd control in an active matter system
(Nature Publishing Group, 2016) Pinçe, E.; Velu, S. K. P.; Callegari, A.; Elahi, P.; Gigan, S.; Volpe, G.; Volpe, G.
Living active matter systems such as bacterial colonies, schools of fish and human crowds, display a wealth of emerging collective and dynamic behaviours as a result of far-from-equilibrium interactions. The dynamics of these systems are better understood and controlled considering their interaction with the environment, which for realistic systems is often highly heterogeneous and disordered. Here, we demonstrate that the presence of spatial disorder can alter the long-term dynamics in a colloidal active matter system, making it switch between gathering and dispersal of individuals. At equilibrium, colloidal particles always gather at the bottom of any attractive potential; however, under non-equilibrium driving forces in a bacterial bath, the colloids disperse if disorder is added to the potential. The depth of the local roughness in the environment regulates the transition between gathering and dispersal of individuals in the active matter system, thus inspiring novel routes for controlling emerging behaviours far from equilibrium.
Open Access
Disrupted network topology in patients with stable and progressive mild cognitive impairment and alzheimer's disease
(Oxford University Press, 2016) Pereira, J. B.; Mijalkov, M.; Kakaei, E.; Mecocci, P.; Vellas, B.; Tsolaki, M.; Kłoszewska, I.; Soininen, H.; Spenger, C.; Lovestone, S.; Simmons, A.; Wahlund, L.-O.; Volpe, G.; Westman, E.
Recent findings suggest that Alzheimer's disease (AD) is a disconnection syndrome characterized by abnormalities in large-scale networks. However, the alterations that occur in network topology during the prodromal stages of AD, particularly in patients with stable mild cognitive impairment (MCI) and those that show a slow or faster progression to dementia, are still poorly understood. In this study, we used graph theory to assess the organization of structural MRI networks in stable MCI (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients from 2 large multicenter cohorts: ADNI and AddNeuroMed. Our findings showed an abnormal global network organization in all patient groups, as reflected by an increased path length, reduced transitivity, and increased modularity compared with controls. In addition, lMCIc, eMCIc, and AD patients showed a decreased path length and mean clustering compared with the sMCI group. At the local level, there were nodal clustering decreases mostly in AD patients, while the nodal closeness centrality detected abnormalities across all patient groups, showing overlapping changes in the hippocampi and amygdala and nonoverlapping changes in parietal, entorhinal, and orbitofrontal regions. These findings suggest that the prodromal and clinical stages of AD are associated with an abnormal network topology.
Open Access
Effective drifts in dynamical systems with multiplicative noise: a review of recent progress
(Institute of Physics Publishing, 2016) Volpe, G.; Wehr, J.
Noisy dynamical models are employed to describe a wide range of phenomena. Since exact modeling of these phenomena requires access to their microscopic dynamics, whose time scales are typically much shorter than the observable time scales, there is often need to resort to effective mathematical models such as stochastic differential equations (SDEs). In particular, here we consider effective SDEs describing the behavior of systems in the limits when natural time scales become very small. In the presence of multiplicative noise (i.e. noise whose intensity depends upon the system's state), an additional drift term, called noise-induced drift or effective drift, appears. The nature of this noise-induced drift has been recently the subject of a growing number of theoretical and experimental studies. Here, we provide an extensive review of the state of the art in this field. After an introduction, we discuss a minimal model of how multiplicative noise affects the evolution of a system. Next, we consider several case studies with a focus on recent experiments: the Brownian motion of a microscopic particle in thermal equilibrium with a heat bath in the presence of a diffusion gradient; the limiting behavior of a system driven by a colored noise modulated by a multiplicative feedback; and the behavior of an autonomous agent subject to sensorial delay in a noisy environment. This allows us to present the experimental results, as well as mathematical methods and numerical techniques, that can be employed to study a wide range of systems. At the end we give an application-oriented overview of future projects involving noise-induced drifts, including both theory and experiment.
Open Access
Engineering particle trajectories in microfluidic flows using speckle light fields
(SPIE, 2014) Volpe, G.; Volpe, Giovanni; Gigan, S.
Optical tweezers have been widely used in physics, chemistry and biology to manipulate and trap microscopic and nanoscopic objects. Current optical trapping techniques rely on carefully engineered setups to manipulate nanoscopic and microscopic objects at the focus of a laser beam. Since the quality of the trapping is strongly dependent on the focus quality, these systems have to be very carefully aligned and optimized, thus limiting their practical applicability in complex environments. One major challenge for current optical manipulation techniques is the light scattering occurring in optically complex media, such as biological tissues, turbid liquids and rough surfaces, which give rise to apparently random light fields known as speckles. Here, we discuss an experimental implementation to perform optical manipulation based on speckles. In particular, we show how to take advantage of the statistical properties of speckle patterns in order to realize a setup based on a multimode optical fiber to perform basic optical manipulation tasks such as trapping, guiding and sorting. We anticipate that the simplicity of these "speckle optical tweezers" will greatly broaden the perspectives of optical manipulation for real-life applications. © 2014 SPIE.
Open Access
Engineering sensorial delay to control phototaxis and emergent collective behaviors
(American Physical Society, 2016-01) Mijalkov, M.; McDaniel, A.; Wehr, J.; Volpe, G.
Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors fromsimple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.
Open Access
Formation, compression and surface melting of colloidal clusters by active particles
(Royal Society of Chemistry, 2015) Kümmel, F.; Shabestari, P.; Lozano, C.; Volpe, G.; Bechinger, C.
We demonstrate with experiments and numerical simulations that the structure and dynamics of a suspension of passive particles is strongly altered by adding a very small (<1%) number of active particles. With increasing passive particle density, we observe first the formation of dynamic clusters comprised of passive particles being surrounded by active particles, then the merging and compression of these clusters, and eventually the local melting of crystalline regions by enclosed active particles.
Open Access
Kümmel et al. Reply
(American Physical Society, 2014-05-19) Kümmel, F.; Hagen, B. T.; Wittkowski, R.; Takagi, D.; Takagi, I.; Eichhorn, R.; Volpe, G.; Löwen, H.; Bechinger, C.
Open Access
Long-term influence of fluid inertia on the diffusion of a Brownian particle
(American Physical Society, 2014) Pesce, G.; Volpe, G.; Volpe, G.; Sasso, A.
We experimentally measure the effects of fluid inertia on the diffusion of a Brownian particle at very long time scales. In previous experiments, the use of standard optical tweezers introduced a cutoff in the free diffusion of the particle, which limited the measurement of these effects to times comparable with the relaxation time of the fluid inertia, i.e., a few milliseconds. Here, by using blinking optical tweezers, we detect these inertial effects on time scales several orders longer up to a few seconds. The measured mean square displacement of a freely diffusing Brownian particle in a liquid shows a deviation from the Einstein-Smoluchowsky theory that diverges with time. These results are consistent with a generalized theory that takes into account not only the particle inertia but also the inertia of the surrounding fluid. © 2014 American Physical Society.