Investigating the neuronal dynamics supporting brain functions and understanding how the alterations in these mechanisms result in pathological conditions represents a fundamental challenge. Preclinical research on model organisms allows for a multiscale and multiparametric analysis in vivo of the neuronal mechanisms and holds the potential for better linking the symptoms of a neurological disorder to the underlying cellular and circuit alterations, eventually leading to the identification of therapeutic/rescue strategies. In recent years, brain research in model organisms has taken advantage, along with other techniques, of the development and continuous refinement of methods that use light and optical approaches to reconstruct the activity of brain circuits at the cellular and system levels, and to probe the impact of the different neuronal components in the observed dynamics. These tools, combining low-invasiveness of optical approaches with the power of genetic engineering, are currently revolutionizing the way, the scale and the perspective of investigating brain diseases. The aim of this review is to describe how brain functions can be investigated with optical approaches currently available and to illustrate how these techniques have been adopted to study pathological alterations of brain physiology. Understanding how the brain encodes even a simple sensory stimulus and generates a functional outcome is a challenging task because of the complexity of the underlying neuronal structure and function. Neuronal networks, along with other non-neural elements, form intricate local and global functional assemblies displaying coordinated and interdependent activity among different brain areas. These neuronal circuits show distinctive wiring diagrams, characteristic electrophysiological features, neurotransmitter specificity and distinct molecular mechanisms. Moreover, the structural and functional interactions supported by these components are tightly linked one to the other, and from this relationship emerge, in normal conditions, the fundamental brain capabilities of communication and information processing. Evidence from clinical and pre-clinical studies indicates that the normal level of coordination in the activity of neurons within the circuit is altered in several neurological and neuropsychiatric disorders, resulting in suboptimal or significantly impaired performances. It is noteworthy that in many cases these alterations can already appear in the prodromal phase of the disease. As a consequence, studying the brain functions, in normal and pathological conditions, requires multiscale approaches, from micrometers to several centimeters and from milliseconds to days. Moreover, it is crucial to consider different natural functional states, such as resting, sleep and sensory stimulation, as well as considering the animal model engaged in active tasks of different kinds. Traditionally, this has been achieved by means of electrophysiological recordings such as electroencephalogram (EEG) and Local Field Potentials (LFP), and/or recording from single or a limited number of cells. These methods are capable of providing a general picture of the ongoing dynamics but lack the possibility to capture extended network dynamics with the desired resolution, and to dissect the contribution of the different neuronal components is only partially possible. To integrate this information, these approaches have been complemented with different paradigms of neuromodulation relying on electrical stimulation or pharmacological treatments, aiming at isolating the role of different neuronal substrates or molecular mechanisms. However, this goal is challenging to achieve as pharmacological approaches can miss the target-specificity required as they typically present a broad spatio-temporal action spectrum, preventing investigation of a specific subpopulation of cells with precise resolution. In addition, they may exhibit undesired side effects, limiting the strength of the conclusions one can draw from such approaches. More recently, taking advantage of light-based activity reporters and actuators, optical methods have extended and refined the range of investigation and the number of units detectable along with their position. In the last 15 years, the amount and specificity of information retrieved from neuronal population recordings has substantially increased, leveraging improved cellular specificity. This result has been obtained with refined genetic strategies which allow targeting genetically-encoded activity reporters based on fluorescent proteins to identified neuronal or cellular populations. Along with the design of increasingly more refined genetically encoded molecular tools, suitable technologies and optical methods have been developed and are continuously optimized to extend the investigation in the depth, including subcortical brain areas, and in the width, encompassing larger neuronal populations over wide regions of the brain. To fully characterize the components of neuronal circuits and their role in network dynamics, genetically encoded activity reporters have been complemented with genetically-encoded modulators of cellular activity. Most of these light-activated molecules have been developed for non-invasively controlling the membrane potential of the target cells and, with this, their firing properties. Optogenetic stimulation relies indeed on the light-dependent gating of specific ion channels that once triggered and override ongoing cellular activity. Once the cells have been conferred with this kind of light-dependent membrane permeability, depending on the molecule (ion channel/pump), on its particular spectral sensitivity and on its intrinsic ion specificity, it is possible to modulate in a bidirectional manner, depolarizing or hyperpolarizing the cell membrane potential. The impact of the optogenetic intervention is sufficient to modulate the firing rate of a number of target cells at once, during repeated cycles of perturbations, or for prolonged time windows, according to the experimental protocol and to the biophysical properties of the selected opsin. In comparison with electrical stimulation, this approach is characterized by a largely improved cellular specificity and by an extremely refined spatial selectivity, as far as proper illumination methods and transgene expression approaches are adopted. A growing number of researchers currently use optical methods to gain insights into the circuit dynamics underlying distinct brain mechanisms and functions, either by recording the ongoing circuit activity in different scenarios and/or by assessing the impact of optogenetic manipulations of specific neuronal populations on circuits activity and, more generally, on brain function. On the other side, considering the study of neurological or genetic brain diseases, these approaches are still in their take-off phase, despite their recognized potential. The aim of this review is then to present the most common optical technologies available for the analysis of neurodegenerative, psychiatric and neurological disease models and to showcase a series of applications in the study of different pathologies. 2+ levels [2+ indicators (GECI) have been designed to optically report the increase in the calcium level associated with the firing activity of neurons . The N-terminus of cpGFP is linked to the M13 fragment of the light chain of myosin kinase, which is a target sequence for Calmodulin (CaM), hence the name calmodulin binding peptide (CBP), whereas the C-terminus of cpGFP is linked to CaM [2+-dependent conformational changes of CaM, also through its interactions with CBP, propagates to the rest of the protein modulating the GFP chromophore environment, resulting in increased fluorescence quantum yield. Through iterative rounds of protein modifications and optimization, several versions of GECI, incorporating different fluorophores [2+ fluctuations in fine neuronal processes, such as dendrites and spines, when the labelling is sparse. In conditions of dense labelling, the neuropil also represents an obstacle to clearly measure Ca2+ activity in individual soma, which are often enwrapped by neuronal processes. In addition, dendritic arborization in superficial brain layers can act as a shield, preventing the monitoring of the Ca2+ dependent fluorescence changes in deeper layers, where cell bodies are located. To overcome this limitation, GECI have been efficiently targeted to the cell body or the nucleus in zebrafish and fly [2+ dynamics with reduced contamination from the neuropil. With this sensor, the fluorescence signal derives mostly from the soma, which is enriched in ribosome with respect to the neuropil [2+ dynamics with reduced background noise due to the reduction of the signal contamination from the neuropil. This results in higher SNR, both in mice and fish, and in the possibility, under favorable circumstances, to track suprathreshold dynamics with single action potential (AP) resolution [The most widely used genetically encoded Cad to CaM . Ca2+-derophores ,7 with irophores ,8,9. Cyt and fly ,11,12. I2+ concentration associated with cell firing [In fact, although calcium imaging proved to be an excellent technique to probe neuronal dynamics from cellular to network level, calcium events in neurons are a good proxy of their spiking activity only in certain working conditions. Indeed, molecular kinetics of GECI are intrinsically too slow to allow for accurate and temporally resolved tracking of network activity down to individual action potentials with single cell resolution over wide fields of view . As a col firing ,9,17. ThGenetically Encoded Voltage Indicators (GEVIs) have the potential to overcome the limitations of GECIs allowing for cellular resolution voltage imaging and recording the dynamics of a small population of neurons in a living organism . The genA change in the membrane potential leads to a conformational re-arrangement of the GEVI structure, resulting in the increase or decrease of the FRET signal . The appFrom the hardware point of view, classical raster scanning imaging systems are sub-optimal for GEVIs mainly as a consequence of slow scanning speed compared to the fast GEVI dynamics which reflect the rapid fluctuations of the membrane potentials. Given the relatively low SNR associated with GEVI imaging, high excitation power is typically required when compared with GECI . PhototoFrom the perspective of network neuroscience, GEVI are interesting and fast developing tools to be applied at different scales: from the cortex-wide meso and macroscopic data collection (one and two-photon) in behaving animals, to more local, microcircuit-oriented applications. Furthermore, extending GEVI applications to finer subcellular compartments allow for spine voltage imaging. GEVI-directed expression to cell classes or cortical layers of interest leverages recent intersectional genetic approaches, extends the application of these tools beyond classic electrophysiological methods and opens the field of so-called “all optical electrophysiology” .In conclusion, GEVI are an exceptional tool for network neuroscience, still amenable to large improvements possibly beyond GECI capabilities and thereby allowing, in perspective, more precise dissection of underlying mechanisms such as neurodegenerative diseases, developmental dysfunctions or basic circuit dynamics associated with perception and behavior.Cognitive functions at all levels relies on fine tuning of neurotransmitters and neuromodulators (NT/NM) release, both in time and space ,24. EvenThe general design for NT/NM reporters, similar to the one described for GECI and GEVI, comprises a fluorescent component that can be a single fluorescent protein or a FRET couple a. The flm, iGluh, iGlul [f) and ultrafast  fused to the circularly permutated enhanced green fluorescence protein (cpEGFP), SFGluSnFR, was developed . Varianth, iGlul  and the t (iGluu  have a bt (iGluu ) or red-t (iGluu ). In cont  are GRAB sensors, in which cpEGFP is inserted in the third loop of the adrenergic receptor alfa 2 (α2AR). This family of sensors for NE, indicated as GRABand mice . GRABNEsnephrine .Genetically encoded sensors are also available for opioid, ATP and glycine. The sensor for opioids, called OR sensor , is baseATP1.0. This sensor is characterized by high temporal resolution (subseconds) and high affinity (tens of nanomolar) for ATP. These features make possible to track ATP dynamics at cellular and subcellular level in vitro and in vivo, in different models, i.e., zebrafish and mouse, providing a versatile tool to follow ATP kinetics in basal conditions and in response to stimuli, both in physiological and pathological conditions. A ratiometric biosensor for ATP, named ATeam3.10, is a FRET-based sensor, developed from the bacterial ε subunit of FoF1-ATP synthase flanked by a FRET pair. In order to detect extracellular ATP, the sensor is endowed with an immunoglobulin K leader sequence and a transmembrane anchor domain from the PDGFR, resulting in the decoration of extracellular aspect of the plasma membrane . The senAgrobacterium tumefaciens. Atu2422 binds to glycine, serine and GABA. However, engineering the Atu2422 binding site resulted in a Glycine specific mutant named AYW, which was inserted between EGFP and mVenus FPs [Recently a FRET-based sensor for glycine, named GlySF, was developed using the Atu2442 protein from enus FPs . Unfortu5HT1.0 [The sensor for Serotonin is also a GRAB sensor, where cpGFP is inserted in the third loop of the serotonin receptor, 5HT2C. Mutagenesis and screening of different versions of the 5HT2C-based sensor, in particular of the linker regions and cpGFP, resulted in a sensor named GRAB5HT1.0 , charact5HT1.0 .In order to optically record neuronal activity from specific neuronal populations, it is crucial to select the appropriate strategy for transgene delivery. One such approach involves the microinjection of a plasmid construct, carrying the coding and regulatory sequences for the indicator in the embryo of a recipient model organism . With the in-utero electroporation (IUE) method, the ventricle (s) of mouse embryos is injected with small amounts of solution containing the plasmid, whose migration to the neurogenic epithelium is driven by the application of a carefully designed electric field. This approach allows for the migration and incorporation of the exogenous DNA in neuronal progenitor cells while operating in laparoscopy so that gestation can follow normal progress after the intervention ,60. By sSome rAAV serotypes display marked retrograde/anterograde transport from the injection site, allowing for the labelling of structures afferent/efferent to a selected target region, a useful property in functional connectome studies ,67. Seve−15 s). This process named multi-photon (MPE) or two-photon excitation (2PE) was theoretically predicted by Maria Göppert-Mayer in 1931.Fluorescence microscopy is a powerful and largely used approach in biology to analyze morphological and functional properties of cells in living tissues, as long as a sufficient amount of light can reach the target region within the tissue. Biological samples indeed typically absorb and scatter incident photons in the visible wavelengths. As a result, the thicker the biological sample, the higher the loss of incident light intensity at the focal point, resulting in a progressive degradation of contrast caused by the light scattering itself. In confocal microscopy, in which the incident light is focused to a diffraction-limited spot, and the emitted fluorescence photons are collected through a conjugated pinhole, the contribution of the scattered light coming from planes out of focus is partially rejected. However, this approach is efficient if the sample is not very thick (below 80–100 μm). Increasing the power of the incident light does not help to get a better image deeper in the tissue as this leads to deterioration of the signal retrieved as consequence of the increased background levels. Furthermore, this comes with significant disadvantages due to the photodamage of the fluorophores (photobleaching) and to the tissue caused by the absorption of visible light. One photon excitation (1PE) is therefore sub-optimal for deep tissue imaging, especially in living tissues. These major drawbacks of confocal microscopy have been overcome by multi-photon microscopy (MPM) which allows optical sectioning and improved depth penetration, favoring neuronal recording deep in the whole living brain. MPM is based on the principle that multiple photons of lesser energy can produce the same excitation that is caused by the absorption of a single photon of higher energy, when the multiphoton absorption occurs “at the same time”  away from it along the light propagation direction. This property gives MPE an “intrinsic” optical sectioning; the vast majority of the fluorescence signal comes from a small region , whereas very little absorption of incident photons happens along the light path above and below the focal point . To maxiThe general configuration for optically reconstructing the neuronal activity in vivo is based on a layout for multiphoton microscopy and stems from a pulsed oscillator, ensuring high repetition rate and high energy emission of light pulses b. ConcenOptical recording of neuronal activity can be achieved with different approaches. In the imaging approach based on raster scanning schemes, the excitation beam visits all pixels along the scanning trajectory, agnostic of the position of cells or region of interest. Pixels belonging to cellular structures can be indeed a minority of imaged pixels, the remaining part being represented by background/neuropil structures. As a consequence, a relevant fraction of scanning time is spent acquiring signals of no or little interest, limiting the spatial and temporal resolution achievable. To overcome this limitation, a random-access sampling scheme is commonly adopted, where the excitation beam travels along a predefined trajectory, visiting the cells or the regions of interest and discarding the uninformative parts of the field of view. This scheme can be implemented by properly driving a galvo–galvo scanner but the mechanical inertia of these elements limits the maximal switching rate. For this approach, in fact, a different type of scanner, not based on moving mirrors but relying on acousto-optic deflectors (AODs) to steer the beam at different locations is more commonly used. AODs are crystal elements where the geometric distribution of the refractive index can be controlled with an appropriate sound wave, resulting in the modulation of light propagation properties. In this case, the switching time in the position of the excitation beam, typically in the order of a few us, is only limited by the propagation speed of the sound through the crystal and the size of the active region of the material. An AOD scanner is designed with two orthogonally oriented crystals, each coupled with a mechanical traducer driven by an electrical signal controlling the beam deflection along one axis of the plane. As an alternative to a layout with a single beam sequentially scanning the sample, in order to increase the acquisition bandwidth, parallel solutions based on spatial or temporal beam multiplexing have been developed. These approaches rely on the generation at the sample of a small set of simultaneous foci, each illuminating one specific point of the plane. This is achieved by splitting the original beam, either by a dedicated optical path or by using a structured illumination system to engineer the light distribution at the sample. In this design, the detection of the emitted signal originating at the different foci typically implements a pixelated detector as a camera or source separation algorithms to disentangle the different components ,77. Brain circuits in general do not lay on a single plane but rather span over a certain thickness of the tissue, and this has prompted the development of a series of methods to extending the imaging capability along the third dimension, allowing to sample from a volume rather than a single plane. The easiest implementation uses a mechanical piezoelectric actuator to move the objectives along the light propagation axis and in this way moves the actual depth in the tissue where the excitation beam is focused . Such syPractically, such design includes two AODs driven with two counter-propagating waves to render a symmetric curvature of the light wave front. Other inertia-free approaches are based on active control of the light wave front properties based on the use of Spatial Light Modulators (SLMs) or Deformable Mirrors (DMs) ,88.These devices, conjugated with the back aperture of the objective, are used to impose a Zernike defocus correction pattern, in this way shifting longitudinally the focal position. From the implementation point of view, these solutions require the design of a dedicated optical layout, but do offer more flexibility in the control of the excitation beam as, along with the control of the focal position, one could impose other Zernike patterns to correct for coarse system aberrations. Whereas all the methods described above take advantage of the small size of the excitation spot to acquire the image from a densely labelled preparation, under certain circumstances, when the labelling is sparser or the detail size can be relaxed, it is possible to maximize the sampling capabilities in terms of speed by shaping laterally or axially and elongating the excitation spot. While two-photon microscopy is a powerful tool for high resolution explorations of the neuronal circuits in limited regions of the dorsal structures of the brain, the extension of the investigation in a deeper or larger fashion faces a series of limitations. First, at increasing depths within the tissue, the light scattering tends to reduce the amount of collected photons to keep consistent the ballistic photon density of the excitation and the signal level, which necessarily requires increasing the laser intensity. Above a certain threshold increasing the light dose could more critically affect the preservation of the original properties of the sample ,90,91. MIn line with this design, Gradient-Index (GRIN) optical components were successfully applied as relay elements for deep brain imaging in several flavors. GRIN optics can be customized in terms of diameter and length in order to limit the footprint and invasiveness when implanted in the animal model while preserving excellent optical properties. Typically, a GRIN rod is mechanically fixed to the skull of the animal and descends toward the target region without the need for a large tissue removal. The optical path of the acquisition and excitation system is then aligned to the GRIN lens, granting a good coupling between the microscope’s imaging plane and the distal part of the GRIN rod where a new imaging plane is formed. Contrary to fiber photometry, in which only a coarse measure of bulk fluorescence collected from the fiber tip is possible, using GRIN lenses makes it possible to reconstruct an actual image of the structures in the focal plane and, depending on the excitation/acquisition set-up, makes it possible to record functional signals with subcellular and millisecond precision. In a paper from Tang et al. , single-Reconstructing the activity from wide brain circuits frequently requires not only mapping neuronal responses at different depths within the tissue but also covering relatively large areas. Regarding this last aspect, a typical two-photon microscope can capture a field of view that is rather limited with respect to the mouse brain size (0.8–1 mm vs. 12–14 mm). To overcome this limitation, a few groups have developed different methods to extend the accessible field of view to larger size, typically 2–4 mm in diameter, and engineering dedicated optical paths in combination with novel or adapted objectives ,105,106.In parallel, one could consider fluorescence laminar optical tomography (FLOT) . In thisAxial resolution of around 200 μm can be achieved for several millimeters. Interestingly, this technique can be used to perform time-resolved imaging, for example, in the perfused rat heart loaded with voltage sensitive dyes and to reconstruct the 3D shape and dynamics of its electrical activity . With apMeasuring the neuronal activity, either from a specific region or across the whole brain, represents an invaluable tool to pinpoint extended or localized alterations of the circuit mechanisms associated with a pathological condition. Such identification of the altered dynamics is fundamental to eventually bring the investigators closer to the determination of the causes and of the origins of the identified abnormalities. However, this approach is not capable, per se, of revealing to what extent certain neuronal components are required to support processing or to clearly dissect the origin of the abnormal activity recorded. This is because reconstructing the activity of a neuronal circuit provides mostly a correlative type of information, i.e., one event occurs concurrently with another, not offering the possibility to unravel causality relationships between the ongoing dynamics. Furthermore, even if the origin of the abnormalities could be identified, exploiting that information in the translational perspective would easily require a method to intervene on the system with a spatial-, temporal- and cell-specific manner according to the information available. With respect to activity recording approaches, neuromodulation methods could allow for precisely evaluating the impact of a specific population on the circuit dynamics on one side and, on the other side, for re-tuning the circuits closer to the physiological functionality, at least at the level of a proof-of-principle on a model organism of the disease.Traditionally, the modulation of circuit activity has been performed with electrophysiological and chemical approaches. These methods, independent of the level of invasiveness, typically miss the required specificity and flexibility to bring their effects to the identified neuronal populations or cellular compartments, and come with a number of side-effects, sometimes masking or altering the observable outcomes. In recent decades, on one hand, the techniques of molecular biology have offered unprecedented capabilities for the engineering of molecules and their targeting to specific cellular populations or compartments. On the other hand, new optical technologies have enabled researchers to work with model organisms with minimal invasiveness more frequently each day in conscious and freely behaving conditions. This has led in the last 10 years to the refinement of genetically encoded light-activated molecules capable of interacting with the targeted cellular signaling in general and to bi-directionally modulate the membrane potential in specific neuronal sub-populations. These tools bring together the advantages of the spatio-temporal precise light delivery in the living tissue with the genetic specificity allowed by the techniques of molecular engineering, prompting the emergence of a completely new field called optogenetics. From the original idea of using light to actively operate on the system, the concept has been extended to also cover light-based approaches relying on genetically encoded molecules to record neuronal activity. In order to get the most out of these tools, many labs have contributed to the development of optical technologies capable of supporting the researchers in the investigation of the neuronal circuits. Following the first approaches, where the activity of populations of neurons was modulated by using an optic fiber to shine the light over a targeted region, more sophisticated methods have been refined to increase the spatial precision of photostimulation. These latter methods, relying on the illumination of the sample with an arbitrary three-dimensional distribution of light, allow for high spatial and temporal precision in the modulation of arbitrary groups of neurons with cellular resolution across different compartments of a neuronal circuit. Since 2014, this high-resolution light-based modulation has been integrated with optical recordings of the neuronal activity, resulting in the creation of “all-optical” protocols, allowing for probing of neuronal circuits at cellular resolution ,115,116.In the following paragraphs, we will first describe the currently available toolbox of light-based modulators of neuronal activity, focusing on those genetically encoded and their basic working mechanisms. Then, we will report on the optical techniques currently available to use these tools in the investigation of neuronal mechanisms in physiological and pathological conditions. The large family of light-based modulators of neuronal activity is generally divided into two main branches, the class of synthetic compounds and the class of genetically encoded molecules. Synthetic optogenetics traditionally represents the first approach using light to control cellular processes and is currently an umbrella term covering a variety of tools and techniques, such as chemical-optogenetics, photo-pharmacology or optogenetic pharmacology. Their general design envisages conferring light-sensitivity to a protein or a molecule. In contrast to the second class of genetically encoded optogenetic tools that incorporate naturally occurring chromophores, this strategy employs synthetic, light-sensitive photoswitches that undergo chemical reactions following the absorption of specific wavelengths. One of the most common mechanisms relies on the trans-to-cis isomerization of azobenzene, resulting in a large geometrical change and significant reduction in the length of the molecule. Azobenzenes are mostly in –trans configuration in the dark or following green-light illumination, but isomerize to the –cis form upon UV light absorption. Therefore, isomerization can be utilized to alter/modulate a protein’s and molecule’s functionality. Different strategies of conjugation of these moieties with intrinsic molecules and proteins, or exogenous molecules, have produced a large library of photo-uncaged compounds such as allosteric modulators of receptors ,119,120 Nowadays, modulation of neurons and their activity mostly takes advantage of a large toolbox of genetically encoded light-sensitive channels and pumps. These membrane proteins (termed opsins) are typically derived from structures found in animal mechanisms of light conversion and they all rely on a natural chromophore in the form of retinal bound to a portion of these molecules. When retinal absorbs a photon, an isomerization process is activated, resulting in a series of conformational changes favoring, with characteristic temporal dynamics, the diffusion or the transportation of ions across the membrane a. This t2 [2 [Depolarizing opsins drive inward currents by allowing the movement of cations and protons inside the cells. Channelrhodopsin-2 (ChR2) has been the first-used optogenetic tool; it is a blue light-activated cation channel derived from a green alga . Since i2 . Chronos2 [2 . From Ch2 [2 ; the two2 [2 .− that combines larger photocurrents driven by low light power (3.5 mW/mm2) with fast kinetics in the millisecond range [2+ influx at the presynaptic level and then to spontaneous vesicular release [2. The kinetics, as well as the spectra sensitivity, are different between the two proteins with GtACR2 being faster (0.04 s) and more green-shifted. The identification of these new anion channels, together with the production of engineered opsins [Hyperpolarizing opsins drive outward currents, mediating either the influx of anions via light-gated channels and pumps or the efflux of protons. Silencing of the neurons during an experiment can either require opsins with fast kinetics that allow precise temporal control, such as during behavioral experiments, or opsins with slow kinetics that suppress the action potential initiation for the entire duration of the experiment. A widely used hyperpolarizing opsin is Halorodopsin (eNpHR3.0), a yellow light-driven ion pump selective for Clnd range ,141. eArnd range . However release . In 2015 release . They bod opsins ,143, hasd opsins ,146,147.d opsins ; in thisd opsins . Using light sensitive tools to control the membrane potential or more, in general, the cell signalling assumes that optical methods are in place to deliver light into the sample according to an appropriate spatio-temporal pattern derived from experimental questions. The major constrains for this task come from the absorption of the light into the tissue, limiting the depth within the tissue where light can be delivered, and the size and position of the population one would like to target with the modulation. Within these tenets, current technologies allow for a range of modulation scenarios, from the activation of large areas of the brain at once to the cell resolution control of the activity in hundreds of identified cells in three dimensions. There is no optical approach that can currently cover both these scenarios, so the subsequent paragraphs will focus on summarizing the options available for the different conditions.Even though there is no clear definition for low-resolution neuromodulation strategies and the boundaries of these approaches can vary from case to case, this concept includes all the techniques allowing for addressing light in the visible range of the spectrum and, consequently, the modulation, in a defined region of the brain. The size of the region targeted can be as small as a patch of 50 μm in diameter or as big as a brain cortical area or more. In this case, the goal is typically to recruit a subpopulation of neurons that are prominent in one region. This approach is also known as “widefield” stimulation, to highlight the fact that all the opsin expressing cells belonging to the illuminated region are recruited at the same time. The techniques adopted for this scheme in general can be very different. A common microscope objective can be used to deliver into the sample the visible excitation light generated by a fluorescent lamp or a light-emitting diode, and by reducing the size of the microscope field aperture, the effective stimulated region is limited. Selection of the region of stimulation requires, in this case, moving either the objective or the sample in proximity to the other, while the temporal protocol can be easily supported by an electronically actuated shutter under the control of a digital signal. Even if this is a very effective method perfectly working in combination with electrophysiological recording in dissociated cultures or ex-vivo slices, traditionally, most of the neurostimulation studies have used a light delivery approach based on optic fibers b. Light 2curve, where r is the longitudinal distance from the focus, in the case of non-linear two-photon excitation, absorption probability away from the focus decays more rapidly, with a 1/r4 relation. Second, a further improvement of the longitudinal confinement of the excitation spots can be achieved considering the fact that multiphoton excitation uses laser sources emitting short pulses of light, usually in the order of hundreds of femtoseconds. In this case, a technique of controlled temporal dispersion of the light pulses called “temporal focusing” can be implemented, so that the absorption probability, depending linearly on the inverse of the duration of light pulse, is enhanced in the focal plane and reduced in the region out of focus. This combination allows for confining the opsin excitation at the plane corresponding to the focal position and preserves the spatial resolution in three dimensions. Independent of the particular scheme and hardware configuration, it is important to keep in mind two important facts: that the single channel conductance of these opsins is generally extremely small, well below the values corresponding to many common voltage-gated ion channels involved in the generation of action potentials; and that the opsin density on the membrane surface might vary from cell to cell and from an experimental condition to the other. It follows then that for an effective modulation, one has to maximize the ion transport across the membrane. This is typically achieved, leveraging a mechanism of spatio-temporal integration of the photocurrent, either by quickly scanning the beam along a spiral trajectory across the somatic membrane (“scanning approach”) or, alternatively, illuminating the cell body with a 2D light patch of the corresponding size (“scanless approach”). Whereas the first approach is rather straight-forward, as it requires the programming of the microscope XY scanner to follow a defined trajectory, the scanless method envisages the use of additional optical elements to correct the beam propagation properties upstream of the objective to extend the lateral width of the excitation spot. In this case, one can opt either for a static optical element, such as a beam expander, to limit the beam diameter and obtain an extension of the focal spot, or a dynamic component capable of quickly and easily re-configuring the light wavefront entering the objective in a way to change the size of the illuminated spot at the sample according to the requirements. Dynamic control of the light wavefront is typically obtained with devices called Spatial Light Modulators (SLMs), which are large matrixes of liquid crystals where the refractive index of each pixel can be individually controlled with an electric signal, with the result of delaying the light wavefront in that position of an amount proportional to the amplitude of the control signal. According to optics law, there is a mathematical relationship linking the light intensity distribution at the sample to the geometrical features of the wavefront; therefore, it is possible to engineer the shape and size of the illuminated areas by properly configuring the map of delays on the SLMs  is complex disorder which originates from a combination of genetic, epigenetic and environmental factors. In the past several decades, the understanding of the mechanism underlying psychiatric disorders has progressed significantly. In humans, alterations in excitatory/inhibitory balance, neurodevelopmental processes and neuromodulation have been identified at cellular, molecular and synaptic level . At the  stimuli ,158, in  stimuli . Similareletions . Again, eletions . More reeletions . On a sieletions . Calciumeletions . Modulateletions . Furthereletions . Similareletions .Altogether, these findings shift the focus of the research at the neuronal circuits level, considered to be the critical architecture for processing neuronal information, and whose disruption may lead to psychiatric disorders. These results also indicated that therapeutic approaches for SCZ, as well as other psychiatric disorders, must aim at restoring neuronal activity at the systems level, to reintegrate the selective cooperation of distinct groups of neurons which represent the functional unit of information processing in the brain.As mentioned above, aberrant oscillations are a signature not only of neuropsychiatric but also of neurodegenerative disorders . In AlzhParkinson’s disease (PD), the second most common progressive neurodegenerative disorder, is characterized by distinct motor impairments due to the accumulation in the basal ganglia of misfolded, phosphorylated proteins, mostly composed of alfa synuclein . Prior to motor impairments, PD patients exhibit several non-motor symptoms which appear during a long prodromal phase. Among these, olfactory deficits, present in more than 90% of PD patients, are among the earliest ones and can precede the onset of motor impairments by years. The progression of the clinical symptoms reflects changes in the pathology in the central nervous system (CNS). Imaging and neuropathological evidence along with clinical and epidemiological data indicate that the olfactory bulb, the first brain area where olfactory information is elaborated, is one of the first regions of the CNS where aggregates of pathogenic proteins accumulate ,172. FroDeep Brain Stimulation (DBS) is a therapeutic intervention applied to intractable neurological and psychiatric disorders. In PD, high frequency stimulation (HFS) of the subthalamic nucleus (STN) has provided an effective intervention for medically non-responsive PD ,180. AltThe focus of the research on stroke, i.e., an acute ischemic event in the central nervous system, is to limit the damage caused by the ischemia and favor the recovery of the neurological functions. To accomplish these goals, the research has to: 1. follow the progression of the possible alterations of neuronal network dynamics around and far from the ischemic area and 2. design appropriate neuromodulation interventions to rescue neuronal activity and functions. Mesoscopic imaging has been the gold standard to monitor blood flow and neuronal circuits dynamics in large brain areas after a stroke in several mouse models. Balbi et al.  establisOptogenetic stimulation has been largely used in mouse models of stroke to re-establish the excitatory–inhibitory balance in neuronal networks. In a mouse model of stroke upon middle cerebral artery occlusion (MCAO), stimulation of striatal GABAergic interneurons expressing ChR2 (excitatory effects) and Arch (inhibitory effects) revealed that the inhibition of GABAergic striatal interneurons favors functional recovery. Namely, GABAergic interneurons inhibition reduces the volume of the atrophic brain area by increasing micro-vessel density and limiting cell death. On the contrary, stimulation of GABAergic striatal interneurons promoted detrimental effects that worsen the pathological situation . FurtherTo restore neurological function, the spared neuronal circuits have to reorganize and reactivate. This reorganization involves not only the area interested by the stroke, but also the connected areas. In particular, ischemic events in the somatosensory cortex were shown, by functional imaging, to reduce neuronal excitability not just in the ischemic cortex but also in the thalamo-cortical projections. It is noteworthy that optical stimulation of the surviving thalamo-cortical axons favors new and stable connections. Furthermore, chronic optical stimulation was found to restore somatosensory circuit function, sensory motor integration and behavioral outcome. These data demonstrated that optical stimulation of thalamic circuits favor rewiring and functional recovery . In mostAbnormal neuronal dynamics are the pathological signature of epilepsy, a neurological disorder characterized by spontaneous and recurrent seizures that are generated by abnormal neuronal activity and hyper-synchrony in various brain areas. Seizures, according to the areas involved, cause cognitive, sensory and emotional alterations and frank deficits . CurrentThe hyperexcitability which characterizes epileptic networks is known to also be related to the diminished, if not absent, inhibitory GABAergic drive. Electrophysiological recordings from hippocampal and cortical tissue excised from epileptic patients to optimize their treatment revealed that GABA antagonists reduce the frequency of the epileptic seizures, indicating that GABA is excitatory in these chronically epileptic tissues ,204,205.−/− to dissect the mechanism underlying sensory alterations in ASD. Shank3B−/− mice exhibit hyper sensitivity to weak stimulation of the vibrissae. When performing calcium imaging with cellular resolution in the somatosensory cortex, Chen et al. found increased spontaneous and sensory-evoked activity in the pyramidal neurons in the somatosensory cortex (SS1), and reduced activity in the GABAergic neurons of the same brain area. Selective deletion of Shank 3B in GABAergic interneurons resulted in hyperexcitability of SS1 pyramidal neurons and hyper sensitivity to vibrissae motion. These data unraveled that GABAergic interneurons altered functionality is responsible for hyperactivity of excitatory neurons and altered sensory perception. These data corroborate a long-standing hypothesis which posits that alterations in development and/or function of inhibitory interneurons are thought to play a critical role and likely represent a common mechanistic link in the heterogenous scenario of ASD [Autism spectrum disorders (ASD) are complex neurodevelopmental disorders characterized by a wide range of social and cognitive deficits. In addition, hyper-reactivity to sensory stimuli, a common and debilitating symptom, is thought to contribute, if not being causative, to impaired social interactions and cognitive functions ,211. Theo of ASD ,214,215.−/− larvae. In mutants, auditory-evoked responses were more plentiful and/or stronger in distinct auditory brain areas. In addition, functional connectivity was higher in mutants with respect to the control larvae, whereas the decoding capacity of the distinct component of the ascending auditory pathway was altered.One of the major limitations in understanding the neuronal basis of hypersensitivity and other core features of ASD is the challenge to investigate the neuronal information processing across the different brain areas involved and dissecting the dynamics of distributed neuronal circuits. A suitable model organism to overcome this limitation is offered by the larvae of zebrafish. The transparency and small size of this organism enable whole-brain functional imaging at cellular resolution, making it possible to investigate the entire pipeline along which neuronal information is elaborated. Combining whole-brain functional imaging along with anatomical location of distinct active neurons  identifiMigraine is a common and debilitating neurological disorder, characterized by a strong head ache preceded by an aura, which most commonly is a sensory hallucination, such as flushing visual percepts, numbness and tingling ,218. TheAnimal models mimicking depression-like phenotypes most frequently involves challenging mice with stressors in chronic or acute paradigms, relying on the well-established relationship between stress and depression in humans ,222. SocNon-human primates (NHPs) are in many respects more similar to human beings than other animal models, including behavioral, social and cognitive aspects related to so- called higher cognitive functions. Exploring disease mechanisms impacting on such “human-like” phenotypes, such as neuropsychiatric disorders or neurodevelopmental and cognitive dysfunctions using these animal models is extremely valuable ,244,245.The recent and constant innovations in the field of imaging cellular activity in vivo and in the use of light to control cellular dynamics provide powerful and unparallel tools to collect functional data from large populations of neurons and unravel the contribution of the different components of the brain circuits in the functionality or dysfunctionality of a brain mechanism. Along with being a valuable resource in basic research investigation, the developed approaches hold an enormous potential for a more detailed characterization of the alterations associated with neurodegenerative, neurological and psychiatric disorders essential to design-effective treatments.


The recent elevation of cases infected from novel COVID-19 has placed the human life in trepidation mode, especially for those suffering from comorbidities. Most of the studies in the last few months have undeniably raised concerns for hypertensive patients that face greater risk of fatality from COVID-19. Furthermore, one of the recent WHO reports has estimated a total of 1.13 billion people are at a risk of hypertension of which two-thirds live in low and middle income countries. The gradual escalation of the hypertension problem andthe sudden rise of COVID-19 cases have placed an increasingly higher number of human lives at risk in low and middle income countries. To lower the risk of hypertension, most physicians recommend drugs that have angiotensin-converting enzyme (ACE) inhibitors. However, prolonged use of such drugs is not recommended due to metabolic risks and the increase in the expression of ACE-II which could facilitate COVID-19 infection. In contrast, the intake of optimal macronutrients is one of the possible alternatives to naturally control hypertension. In the present study, a nontrivial feature selection and machine learning algorithm is adopted to intelligently predict the food-derived antihypertensive peptide. The proposed idea of the paper lies in reducing the computational power while retaining the performance of the support vector machine (SVM) by estimating the dominant pattern in the features space through feature filtering. The proposed feature filtering algorithm has reported a trade-off performance by reducing the chances of Type I error, which is desirable when recommending a dietary food to patients suffering from hypertension. The maximum achievable accuracy of the best performing SVM models through feature selection are 86.17% and 85.61%, respectively. The novel pandemic coronavirus disease 2019 (COVID-19 or SARS-CoV-2) has undoubtedly created global anxiety, especially for people suffering from severe chronic diseases. Most of the recent studies concomitant to COVID-19 from China have suggested the fatalistic role of the novel virus for patients with comorbidities such as cerebrovascular diseases, diabetes, hypertension and others. One of the studies conducted on 191 confirmed cases in China asserted that, the most frequent comorbidities that were found in the nonsurviving patients were hypertension (48%), diabetes 31%) and coronary heart disease (24%) [1% and coHypertension is the physical exertion of the blood on the walls of the blood vessels, and is currently one of the major concern which is aggravating the risk of fatality through COVID-19 by approximately 250% . Other tTo counter the problem of high blood pressure in patients, most physicians recommend the use of drugs having ACE inhibitors that have a tendency to relax blood vessels and eventually reduce blood pressure. However, prolonged use of such drugs can have severe adverse side effects such as hyperkalemia, dry cough etc. ,11,12. FOne of the alternatives to prevent the side effects of the drugs is to focus on the intake of optimal macronutrients ,15. ClinOver the past few years, depending on the type of dataset, the machine learning methods are acting as vital tool for identifying various diseases such as diabetes, cancer, hypertension and many more ,25,26,27Siqueira et al.  have claThe investigations have revealed that inclusion of the trivial features while training the models not only increases the computational complexity of the algorithm but also adversely impacts the prediction accuracy of the model ,29,30. IHowever, the high dimensional biological systems are prone to noise or disturbances that may lead to erroneous data points ,32. HencIt is worth noting that most of the machine learning algorithms that can identify the food-derived antihypertensive peptides are diverse in nature and are solely established through objective-based studies. The methods reported in the literature that predict antihypertensive peptides have a major limitation point out that: (a) no clear factor has been defined to differentiate and label the positive and negative classes of antihypertensive peptides, and (b) they use a trivial feature for training the computational model.The aforementioned limitations may result in performance deterioration of computational algorithms by prioritising statistical Type I error. Moreover, while supervising a machine learning model, it is desirable to use an integrated method to predict bioactive peptides from food protein sequences which hold vital information of biological sequences in the form of physical features of the peptides.Thus, the aim of the present study is to develop a machine-learning-based computational model that can predict the antihypertensive food peptides with better accuracy. The proposed idea is helpful in abating the frequency of drug intake and elevating the habit of a balanced diet constituting equal amount of optimal macronutrients which can control hypertension. Note that such transformation is highly desirable to constrain the upregulation of ACE-II which plays a leading role in facilitating COVID-19 infection.This paper is organized as follows. A brief overview of materials and methods is described in http://hazralab.iitr.ac.in/ahdb/index.php (accessed on 29 April 2021) [The training and testing datasets were prepared from food-derived antihypertensive peptides which are available on the weblink Note that the hypertensive sub-dataset is comprised of 136 peptides while the anti-hypertensive sub-dataset is comprised of 579 peptides of which approximately 10% of the data values from each sub-dataset  were randomly picked and reserved for testing the accuracy of the machine learning model, while the remaining 643 peptides were used to train the machine learning model. The objective behind reserving 72 peptides from the training dataset is to create a small veiled set of data points which can later be used to analyse the accuracy of the machine learning models.50 value. The ACE-I inhibitory activity assays have been used to obtain the experimental IC50 concentration of a peptide [The quantification of inhibition is determined by the concentration of peptide at which it inhibits 50% of the target, which is expressed as IC peptide ,34. At lA knowledge-based heuristic approach has been used to select features for the purpose of machine learning. These features are divided into two categories, namely structural features and pseudoamino acid composition (PseACC) features. The peptide sequence descriptors include amino acid composition as well as Chou’s pseudoamino acid composition for incorporation of the sequence order information . With suhe ACE-I . It has he ACE-I .k-nearest neighbour [k-nearest neighbour algorithm is divided into two variants depending on the number of neighbours and distance metric. The two variants of k-nearest neighbour are fine (having 5 neighbours and Euclidean as distance metric) and cosine (set to 5 neighbours and cosine as distance metric). Out of all the aforementioned machine learning algorithms, the SVM model with radial basis kernel function has outperformed in terms of accuracy . It has been found that, out of all, the RBF kernel gives the best performance with comparatively the highest prediction accuracy. Hence, in this work, the RBF kernel fined as:K of rank r into three unitary matrices U,  and VT, which satisfies the following expression: XUVT is a diagonal matrix which contains nonzero eigenvalues of the feature space, i.e., = diagVT is comprised of eigenvectors whose strength of contribution in the feature space has been quantified by respective eigenvalues in matrix . Due to the direct relation of eigenvalue matrix  with feature space matrix X, equating the lowest values of  to zero will result into low dimensional approximate feature space. In other words, to estimate the dominant feature(s), it is desirable to find We investigate the percentage of variability explained by each feature in the feature space that has been analysed with the help of singular value decomposition (SVD) . The SVDTo estimate the nontrivial feature space subset within the complete dataset, two methods, namely MRMR ,46 and SIn this section, the role of feature selection in estimating the relevant feature space is investigated, which helps in enhancing the accuracy of the SVM model by eliminating trivial features from the training dataset. Prior to adopting any feature selection approach, it is necessary to predict the importance or dominance of specific feature(s) in the entire feature space with the help of SVD analysis. Observing R, On the other hand, et refer b that hop-value of all the features is coming out to be <0.05, resembling rejection of the null hypothesis; hence it concludes that the data is not following a normal distribution. The null hypothesis of this test is based on the assumption that the samples are drawn from same population or both samples have equal median values [In contrast, the SIDR algorithm utilises a nonparametric Kruskal–Wallis one-way ANOVA test, which has been applied on the feature space that is in the ordinal measurement scale such as the subset of positive and negative hypertensive peptides. Note that the normality of the features has been analysed using the D’Agostino–Pearson test of normality by setting a critical chi-squared value to 0.05 . The p-vn values . As per In the previous section, the statistical analysis indicated the role of some vital amino acids and structural features in significantly differentiating the properties of the peptides. These features potentially assist in identifying the proteins from which antihypertensive peptides can be extracted. Food-derived peptides satisfying the characteristics of the predicted features of the peptides are immensely functional. The possible biological significance of some of the nontrivial amino acids and structural characteristics that are significantly contributing to the MRMR and SIDR algorithms in predicting the antihypertensive activities of the peptides is discussed in To analyse the impact of dominant patterns on the estimation of antihypertensive peptides, five performance evaluation metrics have been included, namely, accuracy, area under curve (AUC), sensitivity, specificity and Matthew’s correlation coefficient (MCC). Out of all the five performance metrics, the accuracy of the SVM has been considered as the highest priority metric to estimate the best performing combination of variables Hence, instead of using an optimisation function, a systematic combination search algorithm has been performed to find the best performing combinations of The filtering of trivial features using algorithms such asMRMR and SIDR  is much lower than Type II error  , which mThe maximum attainable accuracy of the proposed SVM model in predicting the antihypertensive peptide is 86.17%, which is better than the previously existing models demonstrated in the artificial intelligence empowered web servers such as AHTpin and PAAP giving average accuracy of 78.58% and 84.73%, respectively ,52. NoteIt is worth noting that when considering a trade-off between Type I and Type II errors, it is desirable to adopt an SIDR , which mimics the human gastrointestinal tract digestion.During the digestion process, the egg white protein breaks into 339 peptides, out of which 37 antihypertensive peptides have been found to be directly matching with the experimentally validated training dataset; while the remaining peptides have been seeded into pre-trained SVM models for predicting the antihypertensive activity refer to . From threfer to . The afoThe impact of COVID-19 has been largely observed in the patients suffering from hypertension. The frequent use of drugs that have an ACE inhibitory property can result into upregulation of ACE-II, which contributes to facilitating COVID-19 infection. In this paper, we have proposed to abate the frequency of drug intake and adopt a diet constituting optimal macronutrients. To estimate the food-derived antihypertensive peptide, a nontrivial feature selection and machine learning approach have been suggested which can predict natural hypertension controllers and minimise the intake of ACE inhibitory drugs. The ACE inhibitory peptide database containing 715 peptides is used in this study which have been experimentally validated through in vivo and in vitro models. The maximum attainable accuracy and specificity of the SIDR (


Picea abies) beams reinforced with carbon-fibre fabric. In the experimental program, each beam is tested for bending with and without CFRP reinforcement in order to determine specimen-specific stiffness increase on an individual basis. The reinforcement yielded an increase of The strengthening of timber beams with carbon-fibre-reinforced polymers (CFRP) has been widely used in the last decades to enhance the behaviour of historical or new timber structures, usually for bending. While considerable improvement in capacity and ductility is typically achieved, the increase in stiffness was, in many cases, well short of analytical expectations, which tend to overestimate stiffness. This study addresses the problem by investigating the underlying mechanical behaviour using experimental, analytical, and numerical tools on a sample of Norway spruce ( Wood is a popular building material for a wide range of lightweight structures. Further to its good mechanical properties and simplicity of manufacturing, its aesthetic appearance also makes it a favourable construction material.The increase of loads or material deterioration in timber structures may sometimes be responsible for the destruction of existing buildings. However, it is often less costly and more time-effective to reinforce damaged wood pieces or structural members rather than replace them entirely. Carbon-fibre-reinforced polymers (CFRP) are currently strongly suggested for structural retrofitting. They have many benefits, including high elastic modulus, strength, corrosion resistance, durability, adequate bonding to wood, and low density. Compared with other types of fibres—e.g., glass or basalt—carbon fibre is more expensive to produce and tends to show brittle failure, though these drawbacks are well counterweighed by numerous advantages. It possesses high stiffness and strength, making it an appropriate alternative to steel in structural reinforcement or completely replacing it, e.g., high-strength steel bridge cables . Its gooFibre-reinforced polymers are formed by embedding high-strength fibres  in a matrix  and can take a range of shapes and sizes , as well as can be prepared on-site or prefabricated. Attachment to wood can usually be externally bonded, near-surface mounted, glued-in, etc. Due to its high modulus and strength, increases in stiffness, capacity, and ductility of reinforced timber structural elements is expected.The prediction of mechanical behaviour is heavily affected by the uncertainty and variability of material properties of both timber and reinforcement. On the one hand, in the case of CFRP, the manufacturer specifies the properties of fibres. While factory-made composites are available with expected quality and specifications, in situ preparation of the reinforcement always involves uncertainty to a degree. On the other hand, timber quality widely varies due to its natural origin, which is further increased by factors such as moisture content, age, density, species, etc. Measured mechanical properties may show significant differences between samples even from the same species and are frequently only informative ,5.The adhesive’s performance directly influences the bond strength and effectiveness of the composite. It is crucial for achieving a robust CFRP-to-wood bond interface that can successfully transmit shear and normal stresses from the timber to the composite material . The bonSeveral experimental studies were carried out to evaluate the effect of CFRP on the flexural behaviour of wood structural components focusing on stiffness, capacity, and ductility. With a good interface between the wood and the CFRP, a significant improvement (maximum of a 60% increase in capacity and a 30% increase in stiffness) was achieved . Two difIt was also shown that, in most cases, strengthening timber elements with CFRP had only a minor influence on stiffness ,15,16, aIt is apparent that results are scattered in a wide range and sometimes contradict expectations. A review comparison between the measured stiffness increase and the theoretical values obtained from calculations using classical beam theory was shown in  based onSeveral numerical and analytical investigations addressed the question. They attributed the differences to an individual factor such as the boundary conditions, the adhesive stiffness, the FRP-to-wood ratio, or the wood material characteristics to resolve the disparities from a technical perspective. For instance, ref.  observedAll the methods mentioned above are strategies to resolve the problem from a technical point of view without explaining the cause of the problem, whereas this work investigates the underlying mechanical behaviour of the materials of CFRP-reinforced timber beams and gives an explanation as to the observed differences between measurements and analysis. For this purpose, a number of sawn Norway spruce beams were tested. Opposed to conventional testing programs, in this work, the bending stiffness properties and enhancement were not obtained as statistics on samples but each specimen was measured with and without unidirectional carbon-fibre fabric reinforcement attached to the tension side in order to obtain a series of specimen-specific data on mechanical properties. Analysis by both classical beam theory and three-dimensional finite element modelling was performed, also capable of predicting the non-linear behaviour by appropriate settings of material parameters. Recommendations concluded by this study on timber modelling enable more adequate assessment of reinforced timber beams in terms of stiffness, preventing possible overestimation of actual stiffness and failing to comply with design objectives.The outline of the paper is as follows. A series of experiments were carried out for the determination of elastic stiffness of the timber beams with and without reinforcement in order to provide data for the subsequent analysis.Picea abies). The test beams had a length of approx. 1000 mm (to ensure a clear span of 900 mm) and rectangular cross-sections of approx. 45 mmThe timber material used is sawn wood of Norway spruce  at full width in the clear span leaving space for supports .A series of four-point bending tests were carried out involving several groups of specimens using a standard MTS testing device with a capacity of 600 kN. The testing arrangement had a clear span of 900 mm, and the force exerted by a single actuator was transmitted onto the specimens at two points at exact thirds of the span via a loading bridge. Small hardwood (beech) blocks were placed at points of application of forces to avoid undesired stress concentration and excessive transverse strains in the softwood specimens. The schematic drawing and a photograph of the test arrangement are shown in The beams were tested under displacement-controlled loading producing load–deflection data. The loading rate was set to 7 mm/min. The series contained 19 specimens, including 6 without reinforcement (group 0) and 13 reinforced with CFRP fabric (group F), see Before measurements, the physical dimensions and weights of the specimens were measured and documented. The density was computed. . The procedure was displacement-controlled in order to capture the entire curves.Data obtained from the experiments form the basis of analytical and numerical investigations. The overall purpose is to evaluate the effect of the CFRP on the bending stiffness of timber beams to make an adequate assessment of the material properties and to provide an accurate prediction for the stiffness increase using analytical and numerical approaches. The individual steps are as follows.Stiffness of all tested beams are determined by linear curve fitting to the linear sections of the load–deflection diagrams.Considering the classical Euler beam model, equilibrium equations of a homogeneous cross-section (for a non-reinforced beam) and of an inhomogeneous (composite) cross-section (reinforced beam) are formulated in terms of geometric data and the modulus of elasticity for timber and fibre reinforcement. In each measurement pair (same timber beam with and without reinforcement), modulus for timber can be computed from the stiffness of the non-reinforced one, and then the modulus for reinforcement from the other once the modulus for timber is known.As in several cases, the obtained modulus for reinforcement is beyond any acceptable tolerance for the factory data provided by the manufacturer, an improved model involving different moduli for tension and compression is introduced, and the equations are reformulated. With the assumption of the factory data for reinforcement, the timber moduli are computed from the equations.In order to cross-check the validity of computations based on the Euler beam, a three-dimensional finite element model was constructed involving a fully orthotropic material model and non-linear analysis. The two models are compared for each beam.The methods are detailed in the following.S of the line fitted with linear regression relates the increment of applied force F and of displacement e of the actuator as All load–deflection curves recorded in the bending tests can be evaluated to obtain bending stiffness characterising linearly elastic behaviour. In the case of loading in the linearly elastic range, the entire curves are used for linear fitting, whereas in the case of total loading (until failure) only the section between E is the modulus of elasticity (customarily denoted by the acronym MOE), I is the moment of inertia related to the axis of bending, and L is the span. This allows the computation of the modulus of elasticity from the measurements. It is important to note that the modulus of elasticity is unquestionably the most determining of the material properties of timber beams in terms of displacements. The properties of natural materials vary in a large range, even within the same species. This implies that the calculation of the actual values of MOE for non-reinforced timber beams enables a more accurate evaluation of the same beams with reinforcement than the adoption of statistical averages from literature data or other samples.Considering the classical Euler beam model, some straightforward analytical derivation yields the stiffness of a homogeneous beam under the given test arrangement as N, M, and z is the vertical coordinate of points of the domain in a suitable coordinate system. Strains Values of modulus of elasticity determined for specimens in group F in the non-reinforced stage are incorporated in the subsequent analysis of reinforcements. The increase in the bending stiffness of reinforced beams is attributed to the contribution of CFRP to the composite structure. Stresses in the inhomogeneous cross-section ought to satisfy conditionsThe analytically predicted behaviour may differ from the observations, which is readily reflected in possible discrepancies between calculated and nominal moduli of the CFRP. Differences may be attributable to the effectiveness of the preparation of in situ reinforcement with accidental damages or imperfections introduced during the procedure or inaccurate assessment of timber material properties.Several authors reported a low or moderate increase in stiffness resulting from FRP reinforcement. In a number of cases, the measured and predicted values significantly differ, as shown in a review article . Therefoe.g., by ,36, for e.g., by .)t and c refer to tension and compression in timber, respectively, and E is the modulus of elasticity of an equivalent homogeneous cross-section. Tension and compression domains and strains are to be expressed parametrically with the position of the neutral axis. The solution of the equation system yields the formulaBy tension and compression zones distinguished in terms of material properties, the resulting inhomogeneous cross-section should satisfy conditionsStress resultants in the cross-section are to be modified to account for the different moduli such that in Equations (1a) and (1b), the wood domain is divided into tension and compression zones:Assuming the modulus of the reinforcement to be nominal, the solution of the equation system , a, a4a), aMechanical behaviour beyond the linear range is dependent on the non-linearity of timber in compression. Considering the commonly used constitutive model consisting of linear elasticity and perfect plasticity a, the stthe beam b. The stthe beam c, which the beam d based oFinite element simulations were carried out to verify the analytical derivations based on the one-dimensional beam model. The three-dimensional FE models for both test groups (0 and F) were created in the general purpose software ANSYS . The finite element mesh of a reinforced beam is shown in In structural modelling, wood is considered a linearly elastic orthotropic material at low-stress levels. While it is typically assumed that elasticity is preserved until brittle failure in tension, some kind of non-linear behaviour is adopted beyond elastic limit stress or yield stress in compression. This can be perfect plasticity, multilinearity, higher-order stress–strain relationships, etc.In this study, elastic behaviour is characterised by the general form of Hooke’s law with nine orthotropic constants in the material stiffness matrix. Moduli parallel to grain were taken from the computation of this work, while the rest of the constants were adopted from literature ,5,38,39.Non-linearity was effectuated by the generalised anisotropic Hill potential model incorporated in ANSYS, which allows the definition of distinct yield strengths in tension and compression and different behaviour in the principal material directions. An anisotropic work-hardening rule and an associated flow rule are included in the model. The material behaviour is characterised by the stress–strain curves in the three orthogonal and shear directions. For each direction, a bilinear response is considered. Plasticity is represented by zero tangent modulus at the compression yield stress and the absence of plasticity in tension by sufficiently large values for yield stress. The elastic moduli of the material are the same for compression and tension. In order to implement different values, the timber domain was divided into a tension part and a compression part such that the appropriate modulus is defined in each.f and m refer to fibre and matrix, respectively. The shear modulus The composite reinforcement is a mixture of epoxy matrix and fibres forming a transversely isotropic material. Epoxy is a linearly elastic isotropic material with modulus Poisson’s ratio x-direction), and 12 and 6 elements in the other two directions . By constraining the displacements of respective nodes, conditions of the test arrangement were realised (simple supports at the bottom face and two lines of loads at the top).Three-dimensional solid elements (SOLID45) were employed to represent the wood material. The eight-node element has three translational degrees of freedom per node and is compatible with the defined Hill anisotropic model. A fine mesh was achieved by dividing the beam into 200 elements longitudinally  were used to represent the unidirectional CFRP composites and epoxy. This element can be used to create multilayered thick shells or solids, and the anisotropic material characteristics are included in the element input data. The element needs to be associated with predefined shell sections for both the FRP and the epoxy with their specifications . The CFRP is relatively thin; so, the mesh had to be generated carefully to comply with rules on aspect ratios and to avoid improperly shaped elements for adequate accuracy. The longitudinal lines within the volume representing the CFRP were divided into certain sub-lines. The vertical ones along the CFRP thickness were divided into two sub-lines and the mesh was later defined accordingly.No constraint equations were defined to link the wood and CFRP components since both solid elements had the same degrees of freedom. Interface components and slide behaviour were not considered as an adequate bond between the wood and the CFRP was assumed.Load–displacement curves of all tests are displayed in t-tests showing that the samples can be regarded as coming from the same distribution at significance level Specimen data of all test groups are summarised in uted see  with twoee e.g., , particuSpecimens in group F were tested until failure after the reinforcement was applied, and the linear section of the load–deflection curves was used as input for curve fitting. The obtained slopes (SR) are shown in In group F (fabric reinforcement), it was found that three specimens produced exceptionally low increases (only up to 7%), which was contradictory to prior expectations. Inspection revealed that one of these specimens suffered a failure in the bond between the timber and fabric, as apparent from the slip of the reinforcement at one end of the beam both in the longitudinal and transverse directions leading to insufficient exertion of the capacities of the reinforcement, see The rest of the specimens did not exhibit any unexpected behaviour producing stiffness increments in the range of approx. 13% to 30%. The bending stiffness quations  and (1b)Assuming nominal reinforcement behaviour and different wood moduli in the tension and compression, the solution of the equation system , a, a4a), at-test showed that the samples possess equal means at significance level The calculated compression moduli are compared with the results of compression tests presented in Load–deflection curves shown in Contrary to the analysis of stiffness, load-bearing capacity and ultimate deflection cannot be determined for both non-reinforced and reinforced configurations of a beam (because of its obvious destructive nature); instead, two different samples (0 and F) are compared statistically. Mean values and standard deviations in both groups and increase by reinforcement with respect to the non-reinforced group are given in All specimens in the non-reinforced group failed in tension with the splitting of fibres parallel to the grain. The tension zone was free from knots to avoid the loss of capacity they may potentially cause.  The failure originated in weak points in the tension zone, and the fracture of the fibres is usually followed by horizontal cracks propagating towards the ends parallel to the grain. Most specimens exhibited insignificant ductility, suggesting that the tensile failure took place before the plastic capacity of wood in compression could be utilised. In the case of one specimen, the ductility was not negligible; this specimen had the highest load-bearing capacity and potentially the highest tensile strength, allowing for some plasticity in the compression zone to develop.With a few exceptions, the reinforced specimens had significantly larger ultimate displacement and ductility than the reference group. This supports the purpose of reinforcement to attract tensile stresses in order to facilitate the exploitation of both the tension and compression capacities of timber. Most of the specimens underwent moderate deformation in compression before sudden tension failure. One specimen behaved differently as it contained a knot. Even though it was located in the compression zone of the timber, the disturbed fibre paradigm with intense fibre curvature reached into the tension zone. It caused stress concentration that initiated the failure in the tension zone, though the effect of its contribution cannot be assessed. A few failure cases are illustrated in In an experimental study involving similar reinforcement of the same wood species , it was Compliance, the energy absorption measure of the specimens, can also be computed to quantify the load–deflection behaviour. It is numerically evaluated as the area covered under the curve in the diagram. The increase in mean compliance in the reinforced group F compared with the non-reinforced reference group 0 was Analysis of the entire load–deflection behaviour, including the non-linear part, was carried out using both the one-dimensional beam model and the three-dimensional finite element simulation. The former incorporates non-linearity with respect to material plasticity through the moment–curvature relationship, while the latter implements a complete non-linear analysis in all aspects . The longitudinal normal stresses are dominant in the orthotropic stress fields. For each specimen, moduli obtained for tension and compression were applied. The difference between the simulated and measured load–deflection curves can be quantified by the sum of least squares, and the plastic yield stress in the simulations was set to result in the minimum error, which could be easily achieved with the required precision after a few trials. One particular specimen (F-6) is shown for illustration in Both simulated curves fit to the measurements very closely, with the result of the finite-element analysis being slightly softer as it is less rigid than the classical beam model. The mean difference in stiffness (slope of the linear part of the curves) between the finite element results and the measurements is For comparison, beam model calculations with a single wood modulus It is clear that the mean values are in good correspondence, which indicates that the inversely calculated values are adequately verified by measurements.The match between the simulated and the measured load–deflection curves can also be given by other quantities. The relative difference between the ultimate loads at the ultimate displacement had a mean value of only Note that even though the measured and simulated load–deflection curves are in good correspondence, the differences may further be reduced by applying more sophisticated non-linear models , though it requires more material parameters to achieve.The adequate in situ reinforcement of non-defected timber beams produced an increase in stiffness in the range t-test showing statistical match at Computations assuming different tension and compression moduli for timber showed in most cases that measured stiffness increase could be achieved using the nominal factory value for reinforcement modulus. Both the beam model and the finite element simulations using three-dimensional models showed good correspondence with the measured data with appropriately set compression yield stresses, indicating that the applied models are adequate for the description of the non-linear behaviour as well. The finite element simulations of the load–deflection curves resulted in an average error of Statistical comparison of stiffness values in the reinforced group with the non-reinforced reference group showed that they come from the same sample. The average increases of The results lead to the conclusion that the differences observed between experiments and analytical considerations regarding the bending stiffness of reinforced timber beams are likely to be attributed to the use of a single modulus in timber for tension and compression, and the distinction enables adequate modelling complying with experiments.Over the last few decades, several studies reported on the mechanical enhancement of timber by applying fibre-reinforced polymers. The increase in stiffness observed in experiments covered a wide range with a minimum near zero and often clearly contradicted expectations by analytical models. This work presented an experimental, analytical, and numerical study on timber beams reinforced with CFRP to provide better modelling for the explanation of the discrepancies. The experiments featured measurements of stiffness of beams under bending, with and without CFRP reinforcement of each producing specimen-specific data, which enabled the direct analysis of stiffness increase on an individual basis. The role of fibre-reinforced fabric in the analysis is significant because the composite structure enables the distinction between tension and compression moduli as opposed to a pure timber structure in which the moduli cannot be uniquely determined. The main findings of the work are summarised as follows:Differences between simulated and experimentally obtained stiffness increase are in most cases in favour of the calculations, which would therefore overestimate the stiffness of the reinforced beams in a design process. This, in turn, would lead to non-compliance with the objectives on structural deflections at the expense of safety. Its effect is likely to rise if larger amounts of reinforcement (in volume ratio) are applied. Inclusion of this distinction into modelling could more efficiently describe the mechanical behaviour of timber with or without reinforcement, and enable designers to apply the right amount of reinforcement for their task.The research can be continued with experimental investigation of beams with different dimensions and amount of reinforcement; however, attention needs to be paid to eliminate all factors that could invalidate calculations, e.g., imperfections of in situ reinforcement, insufficient bond contact if factory-product lamellae are used, defects of timber, etc.