Working Memory (WM) is a short-term memory for processing and storing information. When investigating WM mechanisms using Electroencephalogram (EEG), its rhythmic synchronization properties inevitably become one of the focal features. To further leverage these features for better improve WM task performance, this paper uses a novel algorithm: Weight K-order propagation number (WKPN) to locate important brain nodes and their coupling characteristic in different frequency bands while subjects are proceeding French word retaining tasks, which is an intriguing but original experiment paradigm. Based on this approach, we investigated the node importance of PLV brain networks under different memory loads and found that the connectivity between frontal and parieto-occipital lobes in theta and beta frequency bands enhanced with increasing memory load. We used the node importance of the brain network as a feature vector of the SVM to classify different memory load states, and the highest classification accuracy of 95% is obtained in the beta band. Compared to the Weight degree centrality (WDC) and Weight Page Rank (WPR) algorithm, the SVM with the node importance of the brain network as the feature vector calculated by the WKPN algorithm has higher classification accuracy and shorter running time. It is concluded that the algorithm can effectively spot active central hubs so that researchers can later put more energy to study these areas where active hubs lie in such as placing Transcranial alternating current stimulation (tACS). Working Memory (WM) is one type of memory that retaining information in a short time, it can somewhat reflect people’ s intelligence capability . Due to Communication between neurons is the basis for cognitive activities ,4, more Since WM is a complex process completed by the collaboration of various brain regions, and inter-connection among the brain regions is identical to a network , the conThere are growing number of researches on WM based on brain networks. Hwang et al.  surveyedTo address these deficiencies above-mentioned in previous research, this article makes the following innovations: Firstly, a new WM experiment paradigm based on the French word memory is proposed, which highlights the process of memorization by constantly memorizing words and is more suitable for the study of words working memory. Then, the Phase Locking Value (PLV) between the electrodes are employed to construct a functional brain network so that the synchronous relationship of brain regions during working memory can be acquired, and based on Surrogate data method proposed by Hurtado et al. , the braThe paper is arranged as follows: In order to elicit word working memory while reducing the impact of the experiment on the subjects’ linguistic base, we selected a language that none of the subjects had any basic background as the memory task. In order to simulate the process of memorizing words, we used the familiar language paired with the French language to facilitate memorization. On this basis, English, the subjects’ second language, was chosen as the pairing language, taking into account that Chinese and French are not cognate languages and that the subjects may have associative memory during the memory process.The experiment paradigm is shown in We invited 20 right-handed students as subjects . All subjects report no brain injury and medical treatment history, no implanted medical device in the body, no neurological disease family history, and pregnancy. The Ethics Committee of the Brain Hospital Affiliated of the Nanjing Medical University approved the experimental protocol [2020-KY052-01]. This protocol complies with the Ethical Principles for Medical Research Involving Human Subjects established by the Declaration of Helsinki. In the two weeks after the experiment, we did not receive any adverse feedback.EEG recording is obtained from the scalp by 64 Agcl electrodes . The algorithm configuration is shown in ® , including two functions with Brainstorm, EEGLab [The signal pre-processing module is implemented using the , EEGLab ,36 Figur, EEGLab , and theTo begin with, all epoch signals are transformed from time domain sequences to the frequency domain spectrum. In addition, the spectrum is split into four bands with respect to international standard: theta (3–7 Hz), alpha (7–13 Hz), beta (13–30 Hz), gamma (30–60 Hz). Considering that the power spectrum in the delta band (1–3 Hz) is not strongly correlated with the cognitive processes of working memory , no furtThe result of the brain topographies in four frequency bands  is shown as j represents the imaginary part, and Phase lock value indicated the synchronization of the two signals is used to construct the complex brain networks. At first, the PLV between electrodes in theta, alpha, and beta bands is calculated. Assuming signals of two electrodes are Then, the binarization of brain network in each band is achieved according to the surrogate data methods. Hurtado et al.  generateThe binarized brain network in three bands are shown as ocessing . In the According to the above result, we could observe that the binarized brain network can clearly demonstrate the difference in connectivity of the brain network between the different memory load states. Next, we will use a new algorithm to further investigate the characteristics of binarized brain networks.K-order Propagation Number proposed by our team as a novel algorithm, and be used to explore the nodes importance of PLV brain networks in this study ,43. The The specific node importance is calculated as follows: According to the previous binarized brain network, the Step 1: Calculating the K -order propagation number. In the brain network, we set the d is the maximum connected path of the network.Step 2: Testing the heterogeneity of the network. To reduce the effect of different propagation time K, the structure entropy Step 3: Calculating the ranking of the node importance in the brain network. The propagation time play an important role in the algorithm. If the importance of a node is measured only by the number of infected individuals in the network at a single propagation time, it may miss information at other propagation times. Therefore, in this paper, all moments of K taken from 0 to d will be examined together. The importance of the nodes is calculated according to the structure entropy The SVM was aim to find a hyperplane that can correctly separate the two types of data points as much as possible . In thisBased on the WKPN algorithm, 1600 epochs from 20 subjects are used to calculate the node importance features of the brain network, which are set as the feature vector of the SVM. The feature vectors of all samples are randomly assigned as training and test samples in the ratio of 3:2 for cross-validation to ensure that the data samples are randomly assigned for cross-validation. We repeat this process several times to ensure that the assignment of samples is random and different each time.p < 0.05). Contrary with the theta band, the location of the important nodes transforms from the frontal midline to the right front-parietal lobe in alpha band, and the difference of node importance between the two states was reveled at the node POZ (p = 0.03 < 0.05). In the beta band, we can observe the significant change (p < 0.05) in the distribution of brain network node importance at the left temporal parietal lobe TP7 and right posterior occipital lobe PO4 in the two states.To explore the changes in the importance of brain network nodes under different memory loads more objectively, we normalized the node importance index, set the same threshold, and the nodes whose importance exceeded the threshold would be marked. By examining the number of marked nodes in different states, we can conclude that the number of important nodes increases with memory load in the theta and beta bands, and thus the synchronization of the brain network increases with the memory task. In contrast, the number of marked nodes in the alpha band decreases. In summary, the results of K-order propagation number can well distinguish the characteristics of brain networks in different memory load states.The classification results of SVM are shown in Meanwhile, in order to save the computing time while ensuring the accuracy, according to the ranking of the node importance, the classification accuracy with the different length of feature vectors in the beta band is calculated. To further verify the classification effectiveness of the algorithm, we used the WDC and WPR algorithms to analyze the node importance of the brain network in the beta band, and the network features of two algorithms were used as input data for the SVM. The number of training times and samples are the same as those of SVM. In this paper, we proposed an original experimental paradigm grounded on word memory to scrutinize the mechanism of the WM from an EEG angle. To begin with, PSD is harnessed to inspect the power attribute of the theta, alpha, beta, and gamma bands through the easy and hard task; here we concentrate on the bands with substantial power differences between the two states. Additionally, the complex brain networks are set up by taking advantage of PLV, which can manifest the properties of rhythm synchronization in the corresponding bands. We eventually operated the K-order propagation number algorithm to compute the node importance of the brain networks.In contrast to the conventional EEG signal characterization analysis approaches, several merits of this work are underlined as follows: (1) A novel experimental paradigm is proposed to provoke WM by remembering French words. The paradigm is planned in the practice of the English and French word pair, hence it reduces the obstruction of the experimental results by the subjects with language bias. Since there are a uncommon studies emphasis on WM of words, our paradigm supplements the researches in this area. (2) Studying WM from the view of brain networks blended with conventional time-frequency domain methods. Seeing that WM is a joint process between several brain regions and based on accessible studies, WM is allied with the rhythm synchronization among diverse brain regions, we can well uncover the features of EEG signals during WM by constructing a PLV based brain network: the rhythm synchronization between the prefrontal and the parietooccipital rises when increasing WM load. (3) We offered a novel algorithm, i.e., the K-order propagation number algorithm. To study the characteristic of brain network, WKPN, Compared with other algorithms, takes into account the function of bridge nodes in the network, which has less computational complexity and superior robustness. The calculated node importance sequences can well bare the characteristics of the brain network under altered memory loads, which we set as feature vector as the input of the SVM, which can achieve about 95% accuracy in the beta band.Nonetheless, limitations exist and our work needs to be improved: (1) The capacity of WM is correlated with the rhythmic synchronization of neuroelectric activity. However, the neuronal rhythm synchronization is influenced by one brain region to another. Consequently, we should construct directed brain networks in future research, which can make the outcomes more valid. (2) The heterogeneity among subjects is omnipresent in the task of classification, which can be associated to our setting of thresholds when normalizing the brain network. As a result, extra fine-tuning of the algorithm is indispensable.In the future, the succeeding issues will be addressed: (1) The directed brain network construction. Regarding the Granger causality between nodes, it is feasible to perceive the movement of information amid different brain regions throughout WM tasks and could better consider the node importance of the brain network. (2) Devise a transcranial stimulation paradigm that can be adaptively regulated based on the node importance analysis of brain networks. Recently, Transcranial Electric Stimulation (tES) method could augment the connectivity between the neurons by applying micro-electrical stimulation at specific brain regions shed lights into neuroregulation and treatment field , in whic


Huntington’s disease (HD) is a neurodegenerative disorder caused by the aggregation of the mutant huntingtin (mHTT) protein in nerve cells. mHTT self-aggregates to form soluble oligomers and insoluble fibrils, which interfere in a number of key cellular functions. This leads to cell quiescence and ultimately cell death. There are currently still no treatments available for HD, but approaches targeting the HTT levels offer systematic, mechanism-driven routes towards curing HD and other neurodegenerative diseases. This review summarizes the current state of knowledge of the mRNA targeting approaches such as antisense oligonucleotides and RNAi system; and the novel methods targeting mHTT and aggregates for degradation via the ubiquitin proteasome or the autophagy-lysosomal systems. These methods include the proteolysis-targeting chimera, Trim-Away, autophagosome-tethering compound, autophagy-targeting chimera, lysosome-targeting chimera and approach targeting mHTT for chaperone-mediated autophagy. These molecular strategies provide a knowledge-based approach to target HD and other neurodegenerative diseases at the origin. Huntington’s disease (HD) is a neurodegenerative disease, caused by the aggregation of the huntingtin (HTT) protein in the human brain nerve cells. It is a rare disease with the incidence rate of 5–10 per 100,000 in most of Europe, South and North America, and lower in Asia and Africa . This auHD leads to the loss of nerve cells and brain mass, and the most prominently affected are the neurons of the striatal part of the basal ganglia  Figure . As the HTT gene on chromosome 4, and is 3,142 amino acids long. It is a largely α-helical protein that comprises an N-terminal domain containing an extensive polyglutamine (polyQ) stretch, encoded by a repeat of CAG nucleotides, and multiple 50 amino acid-long HEAT  domains  has an expanded polyQ domain, which is caused by the increase in number of glutamine encoding CAG repeats. The number of repeats in healthy individuals ranges from 6 to 35, and individuals who have more than 39 repeats of CAG are certain to develop HD  Figure . The numWhereas HD is a neurodegenerative disease, with a known monogenic etiology and well identified disease-causing agents, there is still no treatment. The advances in the understanding of the molecular mechanisms of HD allow for new molecular strategies for drug development, by targeting HTT protein aggregation. These strategies mainly focus on lowering the levels of mHTT in the cells .This review describes the current state of knowledge of the molecular strategies that can target protein aggregation in HD. First, it describes the molecular mechanisms of HD and the potential targets for HD treatment, and then summarizes the different molecular strategies researched to target mHTT protein aggregation. These strategies work by either targeting the mHTT mRNA or protein for degradation.The polyQ extensions in mHTT is inherited in an autosomal dominant manner and leads to a gain-of-function, whereby the mutant induces a toxic effect regardless of the presence of the normal HTT. The number of repeats inherited leads to somatic instability of the region, which causes the expansion of the polyQ repeat domain over time, which in turn aggravates the severity of the mutation . AdditioEven though HTT is expressed ubiquitously in the body, mHTT has the biggest cytotoxic effect in nerve cells, predominantly in the striatum. This could be due to the differential transcription of HTT mRNA in cells of neuronal and non-neuronal origin, where nerve cells have more HTT mRNA present in the cell nucleus, suggesting higher protein levels favouring aggregation . SecondlThe development of HD is driven by the expansion of the polyQ region of HTT. However it is not the whole protein that is the involved in the pathophysiology, but only the N-terminal fragments, predominantly the ones encoded by exon 1, are identified as the cytotoxic variants . The toxThe N-terminal fragment can be generated through aberrant splicing of mRNA or through protease-mediated cleavage of the protein, and both mechanisms are affected by the pathogenic expansion of the polyQ region. The expanded polyQ domain leads to the incomplete pre-mRNA splicing of exon 1 to exon 2 . The resThe pathogenic exon 1 of the mHTT protein consists of three domains, including the polyQ sequence flanked by N- and C-terminal domains . The polNT) is a 17 amino acid long sequence and predominantly takes on the form of a compact α-helical coil structure . It remains to be seen how closely artificial HTT structures resemble fibrils in vivo.Notably, these structural data are derived from artificial systems. In other neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease the shape of fibrils obtained from primary material differ in structure from fibrils produced The process of HTT aggregation has an initial a lag phase, followed by an exponential growth phase and then plateau. The aggregation of mHTT is initiated by primary nucleation where a spontaneous aggregation nucleus induces the conformation change of other proteins promoting their addition to the aggregate, through templated aggregation . The sizAggregates expand through the interactions between the polyQ repeat regions, which adopt a β-sheet conformations . These aHTT oligomers and IBs greatly impact cell function by attracting and sequestering a number of proteins involved in processes of energy production, protein trafficking, RNA post-translational modifications and cell death . This alIn cell culture models, mammalian soluble mHTT oligomers can interact with up to 800 different proteins . The proIn addition to the intracellular effect of mHTT in cells that express it, mHTT is able to spread its aggregating potential to neighbouring cells. The mHTT monomers and aggregates can spread through the late endosomal/lysosomal secretory pathway and via cell-cell contacts through tunnelling nanotubes , and areA factor that enhances the cytotoxicity of mHTT is the reduced functionality of the protein quality control and turnover machinery in case of HD. The half life time of wtHTT in Q19 cells is 57 h, while that of mHTT in Q68 cells is reduced to 28 h . In healThe current understanding of the molecular basis of HD, allows for the identification of the toxic agent, mHTT, and the different forms of aggregation that it adopts. The awareness of how the different structures induce cell damage leading to cell death provides a promising platform to propose mechanism that could be used to treat the development of HD.In vivo studies indicate that abolishing mHTT expression slows down aggregation formation, thus limiting HD progression and can even reverse the HD associated progressive motor decline  and RNA interference (RNAi) mechanisms.ASOs are short, synthetic, single-stranded oligonucleotide analogues. They are 16–22 nucleotides long and bind predominantly to pre-mRNA through Watson-Crick binding . DependiThe design of ASOs can target a number of different sequences that are specific to the mHTT pre-mRNA, allowing for the selective targeting of mHTT production. ASOs can be designed to selectively target the expanded polyQ repeat region of the mHTT mRNA, without affecting the wtHTT mRNA levels . Anotherin vitro and in vivo in mice and non-human primate models suggest that ASOs are able to reduce mHTT in a dose-dependent manner, both in the nucleus and the cytoplasm  . Once inRNAi based technologies can be used as therapeutic approaches to reduce mHTT levels, as they use the endogenous RNAi mechanism that mediates post-transcriptional gene silencing. RNAi is facilitated by a small interfering RNA (siRNA), generated by endoribonuclease processing of a double stranded RNA (dsRNA). The dsRNA is processed to generate the siRNA guide strand, and releases the complementary passenger strand, which is discarded. The siRNA then combines with the RNA-induced silencing complex (RISC), associate with the target mRNA, and induces its degradation . This enIntroduction of an artificially generated siRNA into the cell is an approach to target mHTT mRNA . The siRIn vivo studies in animal models, show that siRNA silences mHTT expression, leading to reduced sizes of IB, prolonged longevity of striatal nerve cells, and reduced HD associated motor function disturbances . These two molecules illustrate an unprecedented potential of mRNA targeting approaches to fight HD, even though there is still a long way to being accepted as therapeutics.A wealth of data indicates the potential of targeting the mHTT mRNA for preventing mHTT protein aggregation and subsequent development of HD. In fact, two molecules targeting mHTT mRNA are in phase I/IIa of clinical trials. First one is ASO IONIS-HTTearly HD . Second,Despite promising results in animal experiments, RNA-based therapeutics for HD did not yet hit the clinics. Lack of experience with RNA-based drugs in the human brain means that tolerability and efficiency of a drug can vary between patients and the potential effects on the cellular machinery are not yet fully understood. The most significant limitation is, however, that RNA drugs do not pass the blood-brain barrier. Therapies can circumvent this mainly by two strategies, direct injection into the brain or CSF, or application by adenoviruses. Injections into the brain require a complex neurosurgical procedure. After application, it needs to be ensured that the RNA drug is spread through the tissue. While this is effective in animal models with ranging brain sizes, from mice, rats, minipigs to sheep , a succeThe protein-based approaches to targeting protein aggregation in HD act through inducing the degradation of the whole mHTT protein, instead of inhibiting its function or physically preventing its aggregation. This approach removes the mutant protein in its different aggregate forms from the cell and inhibits any potentially detrimental effects of a gain-of-function variant. It relates to the disturbance of degradation pathways restoring either UPS or autophagy for aggregation-prone HTT variants. Protein degradation also overcomes potential cellular drug resistance that can be acquired by inhibiting protein function. The removal of proteins is also a fast and reversible method of knocking down of proteins, which allows better temporal control of protein concentration in the cell . FurtherThe protein degradation platforms described in this review utilize the endogenous cellular protein degradation mechanisms, namely the UPS or the autophagy-lysosomal pathways. The research targeting protein degradation is in its infancy; nevertheless, it explores promising approaches that could develop into powerful therapeutics.UPS is one of the principal post-translational modification pathways, responsible for, amongst many, protein quality control, and maintenance of protein homeostasis. One of its main functions is targeting of misfolded proteins to proteasomal degradation. The UPS system relies on the post-translational conjugation of a small regulatory protein, ubiquitin, to the target protein. The ubiquitin tag can be a monomer or a polyubiquitin chain, consecutively attached to the lysine (K) residues of the previous ubiquitin. Depending on the lysine residue attachment, the ubiquitinated protein is destined for different degradation fates—K48 for UPS and K63 for autophagosome. The enzymatic cascade that leads to the covalent binding of ubiquitin molecules to the target protein involves the E1, E2, and E3 ligases which are responsible for activating, conjugating and ligating ubiquitin to the target protein, respectively  Figure .The UPS system has potential to efficiently reduce mHTT aggregation and development of HD, by the means of mHTT degradation. Even though the UPS system is not efficient in endogenously degrading mHTT oligomers and larger aggregates, artificial tagging of mHTT monomers could reduce the mHTT pool and thus slow down aggregation. This approach is employed by two molecular strategies, the proteolysis-targeting chimera (PROTAC) and Trim-Away.The proteolysis-targeting chimera (PROTAC) is a small molecule that artificially targets a protein of interest (POI) to the UPS based proteolysis pathway  Figure . PROTACsPROTAC mediates the interaction between POI and E3 ligase enzyme, leading to the K48 polyubiquitination of POI, targeting it for proteasomal degradation. During this process, PROTAC is not degraded and therefore one molecule can catalyse the ubiquitination of multiple POIs. The PROTAC approach is dependent on UPS; hence, it can only target soluble proteins with cytosolic domains. In the context of mHTT, this approach can target the soluble monomers and oligomers of mHTT. Specifically targeting oligomeric aggregation precursors would allow specific removal of the course of the toxic aggregation without interfering with the biological function of the monomer.PROTAC molecules efficiently cross the cell membrane and experimental data suggests they can be administered orally or by intraperitoneal injection . HoweverThe E3 ligase ligand recruits the E3 ligase to the PROTAC bound POI. Initially, these were peptide based short motifs that endogenously recruit the E3 ligase . HoweverWarhead and E3 recruitment unit are connected by a linker. This linker moiety is critical for stability and functionality of the PROTAC. It is often based on alkyl, poly (ethylene glycol) (PEG) or extended glycol chains. These materials are synthetically available, have known flexibilities and their structure can be easily be fine-tuned by robust chemical methods . The fleUp to date, over 40 protein targets are successfully degraded using PROTACs . Most ofin vitro cell culture system  and autophagy-targeting chimera (AUTAC). The method based on the endo-lysosomal degradation pathway is a lysosome-targeting chimera (LYTAC) and another method is using the CMA pathway; in both cases proteins are degraded by targeting them straight to the lysosome.Drosophila and mouse models with human mHTT, revealed that the molecules can specifically target the mHTT to the autophagosome, leading to mHTT degradation and its reduced levels. The identified molecules do not show any major adverse effect on the cellular function, and interestingly, do not affect the global autophagy function. Additionally, some of the identified molecules can pass through the blood-brain barrier, and can function at low concentrations. Even though the tests so far are based on in vitro cell culture models and in vivo tests, the preliminary results showing successful and specific mHTT degradation indicate a promising therapeutic potential of ATTEC for HD and other proteopathy diseases (The autophagosome-tethering compound (ATTEC) is a direct strategy to target POI for degradation via the autophagosome. ATTEC mediates the tethering of POI to LC3, one of the main autophagy proteins found in the phagophore and later autophagosome  Figure . Once sediseases .S-guanylation. The tag is recognized by the ubiquitination system and leads to the K63 polyubiquitination of the POI. The selective autophagy pathway, via the p62 reporter of autophagy, in turn recognizes this modification and sequesters POI in the autophagosome and destines it for degradation.A recent approach that targets proteins for degradation via autophagosomes, is the autophagy-targeting chimera (AUTAC) based system  Figure . The priin vitro proof-of-concept studies show that this technique can successfully degrade cytosolic proteins as well as larger structures, such as mitochondria. The ability to degrade structures of different sizes makes AUTAC an interesting approach for degrading larger mHTT aggregates. Further in vitro and in vivo studies, together with the knowledge gained from PROTAC design, can make the AUTAC molecule a very promising HD therapeutic method.The AUTAC approach has not yet been tested on HTT; however, A different cellular pathway, based on lysosomal degradation, considered for targeted protein degradation is CMA . CMA tarIn vitro studies show that RHQ is able to distinguish between the polyQ size difference between mHTT and wtHTT, and selectively induce mHTT monomer degradation. The in vivo experiments indicate the efficiency of RHQ in degrading mHTT in.A proof-of-concept study has demonstrated feasibility of the CMA based approach of targeted mHTT degradation . The molin vivo via the rAAV approach. Nevertheless, the CMA based approach presents yet another potential therapeutic solution for targeting protein aggregation in HD, by targeting mHTT to the lysosome.The mice striatum and reversing the HD symptoms, by improving metabolic and neurobehavioral outcomes. A shortcoming of this approach is the peptide structure of the molecule, which reduces the efficiency of passing through the plasma membrane, and requires its delivery The previously presented methods focus on the degradation of cytoplasmic mHTT monomers and aggregates. However, mHTT is also found in the extracellular space, where it induces the spread of mHTT aggregation in the brain tissue. This form of cytotoxic mHTT can potentially be targeted using the lysosome-targeting chimera (LYTAC) technology, which exploits the endosomal/lysosomal pathway and triggers the degradation of extracellular and membrane bound proteins  Figure . The appin vitro and in vivo (There are no studies of applying this method to degrade mHTT, but two proof-of-concept studies show that this method successfully degrades both, membrane bound and extracellular proteins, both  in vivo . Additio in vivo . TogetheIn vitro and in vivo studies show that this chaperone machine can supress amyloid fibril formation, reduce aggregation and also lead to disaggregation of already formed amyloid fibrils (An important factor in preventing HTT aggregation is the cellular protein quality control machinery, and it is an intriguing thought to exploit this system to complement other therapeutic approaches. Chaperones interact with HTT, specifically the Hsp70 machinery consisting of HSC70, the nucleotide exchange factor HSP110 and the J-domain protein DNAJB1 . Loss of fibrils . Interes fibrils . This me fibrils . Another fibrils . The draThere is a wealth of research on the potential molecular methods to target protein aggregation in HD. HD is caused by a trinucleotide expansion mutation in the HTT protein, which generates a mutant protein prone to aggregation. The formation of different mHTT aggregate structures induces a highly cytotoxic effect, leading to nerve cell death, brain atrophy and neurodegeneration. Accumulating experimental evidence demonstrates that lowering mHTT levels ameliorates HD symptoms and disease development. The proof-of-concept and preclinical studies show the possibility or potential of molecular methods to target mHTT and reduce its levels in the cell. The different mRNA and protein targeting techniques present a promising avenue for finding a treatment for HD by removing mHTT oligomers.Development of drugs targeting HD could profit from progress on targeting protein aggregation in other neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. Successful development of an effective treatment of mHTT aggregation could then be expanded to develop treatment for other protein aggregation diseases caused by polyQ expansion  or by otSeveral challenges also emerge with the fact that the targeting of mHTT protein production and aggregation is done in the nerve cells. Firstly, it remains to be elucidated whether the soluble aggregates or the fibrils are the HD causative agents, making the targeting of the toxic molecule more complicated. Secondly, the nerve cells targeted for treatment do not undergo further mitosis, meaning any manipulation leading to cell death leads to permanent cell loss. Thirdly, the interference in protein production and aggregation needs to be selective and to precisely target degradation of the cytotoxic agent, not to disturb other endogenous pathways, cause adverse side effects and lead to fatal loss of neurons.The well-understood molecular basis of HD is a good base for the development and preliminary design of possible treatments. However, several knowledge gaps remain and progress in addressing them would facilitate finding effective therapeutic methods for treating HD. One them is identification of the exact molecular agent that is toxic and causes most of the damage in the nerve cell. Both, the soluble aggregates and insoluble fibrils interact with a wide range of proteins, but it is still debatable which one is more toxic. Some studies suggest that the soluble aggregates are more dangerous for the cell and the fibrils are a safety mechanism to sequester the aggregates , whereasin vitro studies allowed a better understanding of the fibril structure and shapes (in vivo structures of the oligomers, soluble aggregates, and fibrils, are not well understood. The identification of aggregate specific structures and targetable protein domains, for example the N- and C-terminal domains, would allow for more precise targeting of the toxic mHTT, while protecting the wtHTT.Additionally, a more in-depth understanding of the structure of different mHTT aggregate forms could advance identification of sites that can be used for targeting the protein and aggregates for degradation. For now, the HTT monomer structure has been resolved by Cryo-EM , and in d shapes . HoweverBetter insight into the function of wtHTT in the organism would allow for improved assessment of the potential effect of its removal. The targeted reduction of mHTT leads to an overall reduced HTT levels in the cell; therefore, it would be important to understand potential effects of lowering of HTT on the cell. Some studies indicate it to have little effect on the cells or organisms studied , whereasThe presented molecular strategies to target mHTT aggregation in HD are promising and the experimental research shows their potential, by inducing the degradation of mHTT at the pre- and post-translational level. However, a number of crucial concerns remain before these molecular strategies are translated to human clinical trials.One such concern is that most molecular strategies, as their efficiencies are based on proof-of-concept trials in cell culture or model organisms with much smaller brains than human, such as mice. Despite similarities at cellular level, the orders of magnitude larger size of the human brain limits comparability for transport processes through the brain. This is an issue for both mRNA targeting methods and protein-based approaches. Even though the methods were tested for a wide range of animals, including mice, rats, minipigs, and sheep and rhesus macaques, the dimensions of the human brain are much more extensive than that of animals. Size and structure of brains of different organisms can affect the molecule’s pharmacokinetics and pharmacodynamics, affecting the way it carries out its function. Thus, a compound working in one organism may not have sufficient activity in another, and this is a key challenge for drug delivery.Another challenge is the importance to exclude side effects. Neurons do not undergo further mitosis. As these cells do not regenerate, possible side effects could lead to irreversible damage. Some of the mRNA and protein targeting approaches show the inability to selectively target the mHTT molecule from the HTT protein pool, and also reduce wtHTT levels. Selectivity is critical to reduce any potential negative effects that reducing wtHTT availability might have on the cell. Additionally, off-target effects may influence other functions of the cell, for instance by overwhelming the endogenous systems leading to the loss of their efficacy. Overexpression of shRNA targeting the mHTT mRNA can interfere with endogenous RNAi processing . AddressConsidering advantages and disadvantages of different molecular strategies against mHTT aggregation, a picture emerges which traits an ideal therapeutic against HD may have. These traits include high selectivity of the drug, which would target specifically the mutant protein, in either monomeric or oligomeric form, to prevent any further aggregation and fibril formation at the earliest stage. The therapeutic would also be able to pass through the blood-brain barrier allowing for an easier and less invasive form of administration of the drug to the patient. Ideally, the drug would be able to diffuse easily through the whole brain tissue preventing the spread of the disease to other brain parts. Finally, the molecular strategy should not interfere with any other cellular mechanisms, to ensure no side effects and potential damage to the cell.This review is presenting the wealth of research conducted, with the aim of finding treatment for a protein aggregation based disease, HD. The examined approaches are in different stages of preclinical and proof-of-concept experiments. In-depth understanding of the molecular process of mHTT aggregation, the targeting chemistry and bioavailability of the drug are needed to boost translation from preclinical studies to treatments in humans. The new strategies presented here are promising for targeting a protein such as HTT with no known inhibition sites. Progress made in different experiments on treating polyQ and aggregating protein diseases, such as HD, can be also beneficial for developing treatments for other aggregate diseases, such as Alzheimer’s, spinocerebellar ataxia types and Parkinson’s disease, which are detrimental for affected individuals and have a huge societal impact. Compared to these diseases, development of a treatment strategy for HD has a much clearer focus: It is known that the aggregation process of Htt is causing the disease, and any drug must enter the nerve cells. This is a tremendous challenge for developing biologics towards clinical application. This challenge is also a chance—we know who the villain is and where to send the police to round them up.


In our daily lives, we use eye movements to actively sample visual information from our environment (“active vision”). However, little is known about how the underlying mechanisms are affected by goal-directed behavior. In a study of 31 participants, magnetoencephalography was combined with eye-tracking technology to investigate how interregional interactions in the brain change when engaged in two distinct forms of active vision: freely viewing natural images or performing a guided visual search. Regions of interest with significant fixation-related evoked activity (FRA) were identified with spatiotemporal cluster permutation testing. Using generalized partial directed coherence, we show that, in response to fixation onset, a bilateral cluster consisting of four regions  formed a highly connected network during free viewing. A comparable network also emerged in the right hemisphere during the search task, with the right supramarginal gyrus acting as a central node for information exchange. The results suggest that all four regions are vital to visual processing and guiding attention. Furthermore, the right supramarginal gyrus was the only region where activity during fixations on the search target was significantly negatively correlated with search response times. Based on our findings, we hypothesize that, following a fixation, the right supramarginal gyrus supplies the right supplementary eye field (SEF) with new information to update the priority map guiding the eye movements during the search task. In neurocognitive experiments, researchers generally perform multiple repetitions of the same experimental condition in a tightly controlled environment with the goal of isolating specific aspects of the cognitive process in question. An experimental setting involving simple but easily controlled sensory stimuli increases the likelihood of deducting useful knowledge from its outcome. When studying visual processing in the human brain, the high complexity of naturalistic stimuli has typically been avoided in favor of artificial and simple stimuli, such as bars, gratings, letters, or simplified scenarios like controlled saccade tasks , readingHowever, while artificial stimuli make it easier to reduce the complexity of studies, there is no guarantee that responses to artificially simplified stimuli used in laboratories reflect neural responses to natural scenes . Indeed,Compared to common experimental paradigms where participants either have to fixate on a specific point continuously or where eye movements are elicited by the appearance of a stimulus, the exploration of natural still images is driven by self-paced gaze shifts over a longer period of time (“active vision”) . This usHowever, the self-paced nature of the eye movements makes comparisons across participants and/or trials difficult. A possible solution to this is to combine eye-tracking with high temporal resolution neuroimaging to obtain a comprehensive record of the visual system . In thisThe fixation-related evoked potential (FRP), i.e., the electrophysical response following a fixation, has recently been identified as a neural marker of natural visual processing . Thus, uTo effectively interact with the environment, it is important for the brain to process information selectively in line with contextual priorities. Previous studies have reported evidence for such task-dependent selective information processing. For example, modulations of large-scale brain networks during the processing of complex visual information were highly predictive of the task   and goalIn the present study, the same experimental paradigm as employed by We hypothesize that, during a guided visual search, top-down processes occurring as a result of the specification of a search target would affect the topography of whole-brain connectivity networks. In particular, the main difference between searching and freely viewing naturalistic images would be that the visual input has to be compared to a mental representation of the search target to determine whether the input matches the target . FurtherOur analysis identified two clusters of ROIs per hemisphere: one cluster in the dorsal cortex and the other in the temporoparietal cortex. These clusters exhibited significant activity during both free viewing and guided visual searching. The temporoparietal cluster consisted of parts of the posterior insula, the transverse temporal gyri, the superior temporal cortex and the supramarginal gyrus. Based on the findings from the Granger causality analysis, these four regions were highly inter-connected. In particular, one part of the temporoparietal junction, the right supramarginal gyrus, was especially well-connected during visual searching. Moreover, the correlation analysis showed that higher activity in the right supramarginal gyrus is associated with shorter response times during visual searching. Taken together, our results suggest that the right supramarginal gyrus acts as a hub for information exchange during a guided visual search.Thirty-eight healthy participants between the ages of 18 and 40 took part in the study, out of which 16 were female. Seven participants were discarded due to excessive movements during the measurement, i.e., the deviation in head position at the beginning and at the end of a measurement run was greater than 2 cm. In total, 31 participants remained for analysis, out of which 14 were female.All participants were right-handed, as assessed with a German version of the handedness questionnaire . Twenty-None of the participants reported a history of neurological or psychiatric diseases, as assessed by the German version of Beck’s Depression Inventory . After hParticipants performed voluntary visual exploration of still images depicting scenes of everyday life under three different task conditions: visual search (VS), memorizing (ME), and free viewing (FV) . Five obFor VS trials, following the presentation of the task indicator, a target object was displayed for 3 s, followed by a 2 s presentation of the fixation cross. A scene image was then presented for 6 s. During this time, the participants had to search the image for the previously presented target object. The participants were asked to press a button to indicate that they had found the target.In FV trials, the task indicator was immediately followed by a 2 s display of the fixation cross. The scene image was then presented for 6 s. The participants viewed the image freely without any additional cognitive tasks.Since the same stimuli were used as in the studies of Stimulus presentation was performed using the Python package PsychoPy 2.0 . A BarcoBrain activity was recorded with 248 magnetometers in blocks of 30 trials at a sampling rate of 1017.25 Hz using the Magnes 3600 WH MEG system from 4D-Neuroimaging . This resulted in a total of three ∼13-min MEG recording runs per participant. At the beginning and at the end of each recording run, the participant’s head position was determined. Cardiac and ocular activity were recorded at a sampling rate of 5,000 Hz using electrocardiography (ECG) and electrooculography (EOG) with the BrainAmp ExG MR system from Brain Products . Eye movements were recorded at a sampling rate of 1,000 Hz using the EyeLink 1000 Long Range eye tracker from SR Research .At the beginning of each recording run and after every six trials, the eye tracker was calibrated using EyeLink’s 13-point calibration method . If the A structural MR scan was performed with a MAGNETOM Trio 3T MRI scanner from Siemens  using MPRAGE . The MR Data analysis was performed using Python 3.6, with MNE python v0.19 being the main package for the MEG data analysis .After each recording session and for each of the three recording runs, the four data sets  were time-aligned and combined into single MNE python raw objects with sampling frequencies of 1017.25 Hz following resampling of the ECG, EOG, and the eye-tracking data. It is important to note that, due to potentially different head positions between recordings of the same participant, the three recording runs had to be processed separately until after the transformation to the source space for the extraction of ROI time courses (cf. section “Extraction of Regions of Interest Time Courses”).MEG channels with strong artifacts were identified in the time and frequency domain using an in-house machine learning algorithm based on density-based spatial clustering of applications with noise (DBSCAN), as implemented in scikit-learn . These cEnvironmental noise was removed from the MEG signals by subtracting the reference signals that were recorded in parallel with the MEG signals . Power lAs it has been reported that filtering has a negative effect on Granger causality , the anaIndependent component analysis (ICA) was used to remove components containing significant contributions of ocular or cardiac activity . For thiThe EyeLink 1000 system detects saccades and fixations automatically in the recorded eye-tracking data. These fixation timings were used to create FRF epochs for FV and VS, with time 0 corresponding to fixation onset. For VS, fixation events after task completion, i.e., after the response was given, were ignored. The time interval of −0.2 s (for the bandpass-filtered data) or −0.4 s (for the unfiltered data) to 0 s from fixation onset was used as a baseline, i.e., the mean of the sensor time courses was calculated for that interval and subtracted from the entire epoch on a per sensor basis. The standard deviation across all channels was then computed for the baseline interval, and the sensor time courses from the entire epoch were divided by this standard deviation. Epochs for fixations during the presentation of the fixation cross were extracted in a similar fashion.Based on the filtered FRF data averaged across the epochs, ROIs were identified using SCPT. The averaged FRF data from each recording run was projected from the sensor space onto the source space using dynamic statistical parametric mapping (dSPM) . The resSource space construction was performed using FreeSurfer . For groTo account for possible brain activity evoked by physical eye movements but not related to processing visual information during active vision, FRA during the presentation of the fixation cross was subtracted from the FRA during FV or VS. These contrasts were then used as the input for SCPT.Two separate sets of ROIs were constructed using SCPT, one for fixation onset during FV and one for fixation onset during VS. The cluster tests were performed with 30,000 permutations based on the first 200 ms after fixation onset of the respective FRA time courses. With 31 participants and three runs, this resulted in input arrays of shape: .p < 0.05) with a minimum size of five vertices (about 1.95 cm2) and a temporal extent of greater than 20 ms were accepted for further analysis. Since the resulting clusters were generally large and covered several anatomical areas, all remaining vertices that were part of at least one significant cluster were grouped together and then partitioned into ROIs based on the anatomical labels as defined by the Desikan-Killiany atlas  was determined for each ROI. Subsequently, the representative single-epoch time courses for a given ROI were computed by averaging the time courses of all vertices of that ROI within a radius of 12.4 mm from the vertex with maximum activity, where 12.4 mm corresponded to twice the average vertex-to-vertex distance (see section “Identification of Regions of Interest”).However, it is important to note that, since the source activity was projected onto the vector normal to the cortical surface, the time courses of vertices at opposing sides of a sulcus are likely to have opposite signs if the direction of the underlying current is the same in both vertices. As a result, activity in these vertices would be canceled out when using a simple average. To avoid this issue, the sign of some vertices were adjusted prior to averaging. These vertices were determined using the Pearson correlation coefficient. First, the vertex time courses were averaged across epochs, and then the correlation coefficient was computed between the average time course of the vertex with maximum activity and the average time courses of the other surrounding vertices. If the correlation coefficient was negative for a given vertex, the sign of the respective single-epoch time courses was flipped.r) was calculated between the bandpass filtered (1–45 Hz) single-trial FRA time series during the first fixation on the search target and the respective single-trial response times. Multiple comparisons were accounted for by controlling the false discovery rate (FDR)  .For each ROI, the full width at half maximum (FWHM) time interval was determined based on the grand average of the single-epoch FRA time courses across participants and trials, and the FRA amplitude of a given ROI was then computed as the average, absolute activity during the respective FWHM time interval. The FRA amplitudes obtained across trials were correlated with the respective response times, which were defined as the latencies from the onset of the first fixation on the search target to the participant’s response via button press.Only trials with correct responses were included in the analysis. A response was defined as correct if, within ±500 ms of giving the response, the participant fixated within 1.7° of visual angle from the center of the target object. Furthermore, trials with response times longer than 1 s were discarded from the analysis.N simultaneously observed time seriesAutoregressive models provide the mathematical framework for the calculation of Granger causality. A set of p MVAR(p):can be represented by a multivariate autoregressive model of order kth time lag is given by A(k), and E(t) is a vector containing white noise error terms  . The whiGPDC, as implemented in SCoT, was used for the Granger causality analysis. The goal of GPDC is to identify directed interactions between pairs of time series after removing the influence of other simultaneously observed time series .nth to the mth signal can be calculated as:To compute GPDC, the MVAR model first has to be written in the frequency representation where the coefficient matrix is given by k)e-2ifk . Then, Gm is the variance of the white noise error process Em(t) for the mth signal and mth row and the nth column representing the strength of causal interaction from the nth to the mth signal.where σFor each participant, GPDC was computed on the unfiltered (except for the notch filter) ROI FRA time courses in the interval of 0–300 ms from fixation onset. Only fixations that occurred prior to the participant’s response were included in the analysis of the search task. Therefore, the number of events during VS is lower than the number of events during FV. To ensure comparable SNRs for both FV and VS, the maximum number of epochs to be used for a participant was set to the minimum number of epochs across participants and conditions plus 10%. For example, if the number of epochs for one participant exceeded the threshold by 50%, every third epoch was excluded from the analysis.To identify significant causal interactions between ROIs, surrogate data were computed for each participant. This was achieved by shuffling the data along the time axis to destroy the phase information of the ROI time courses. For each surrogate, the maximum GPDC value was identified for each frequency bin. This procedure was repeated 1,000 times per participant. The significance threshold for causal interactions in a specific frequency band was determined by averaging the 99.99th percentile of the corresponding frequency bins. Connections with a strength below the threshold were set to zero.p < 0.001) at the group level, it was assumed that number of participants for which a connection appeared with significant strength was distributed according to a binomial distribution with the number of independent trials N = 31 and probability p = 0.5. For each connection, the p-value was determined based on the number of participants featuring the connection.To determine which causal interactions were significant  was used per participant in the GPDC analysis for both tasks. The average fixation durations during FV and VS were 229.49 ± 116.64 and 201.14 ± 101.09 ms, respectively, while the saccade durations were 38.50 ± 26.52 and 41.20 ± 22.66 ms.In VS, 75.91 ± 9.03% of search targets were identified correctly, i.e., a response was given within ± 500 ms of fixating within a 1.7° visual angle from the center of the target object. The lowest rate of successful trials was 56.67%, while the highest rate of success was 93.33%.SCPT was performed on FRA time course contrasts (image presentation vs. fixation cross presentation) to identify ROIs with significant activity related to visual processing during FV and VS (see section “Identification of Regions of Interest” for details). The ROIs formed the basis for the subsequent correlation and Granger causality analyses.The spatiotemporal clusters were generally very similar across cognitive tasks, and the activity was strongly symmetric across hemispheres. For FV, two clusters were found in each hemisphere and were noted to be at similar locations when compared across hemispheres. The first cluster was located in the posterior part of the brain, covering the occipital lobe, parts of the parietal lobe, the temporal lobe, and large parts of the cingulate cortex . In the Six clusters were found for VS and were at roughly the same locations as compared to the clusters found during FV. However, while the dorsal cluster covered one contiguous area in the left hemisphere during FV, the cluster was split into three separate clusters during VS, one large and two considerably smaller ones. One of the smaller clusters covered parts of the entorhinal cortex (#12) and the parahippocampal cortex (#13) in the left hemisphere .In order to identify the ROIs involved in processing visual information related to the search target, the relationship between the activity recorded during the first fixation in a trial on the search target and the associated response in that trial was analyzed. For this, the Pearson correlation was calculated between the single-trial FRA amplitudes and the single-trial response times  was found between the response time and the FRA amplitude in the right SMG .p < 0.05). Using the HQIC, the optimal MVAR model order was estimated to be 42. Furthermore, using SCoT, it was confirmed that the resulting MVAR models represented stable  processes and that the residuals could be considered white according to the LMLP test  and the ParaCeL in the frontal lobe. Out of the four ROIs in the temporoparietal cluster, the right SMG particularly stood out as having the highest number of connections with other areas and was connected with all of the regions mentioned above, in addition to the other temporoparietal cluster regions. The high local degree of connectedness of the temporoparietal cluster was absent in the left hemisphere. The only inter-hemispheric causal interactions were from the right C to the left C and vice versa, the right EC to the left PHG, the left ICC to the right ICC and vice versa, from the left ICC to the right LG, from the left LG to the right PreC, and from the right LG to the left PeriCC.For both tasks, the majority of the intra-sectional connections and even many of the inter-sectional connections were short-range connections, i.e., the majority of interactions took place between neighboring ROIs during both tasks. Few regions featured directed interactions across hemispheres.For a direct comparison of GPDC results for FV and VS, the causality matrix for VS was subtracted from the causality matrix for FV cf. . From thFor each task, random permutation analysis revealed several ROIs with a high node degree in at least one of the frequency bands . Twelve The high local degree of connectedness observed between temporoparietal cluster regions during FV was absent in the left hemisphere during VS. At the same time, the right SMG had a higher node degree during VS as compared to FV across the majority of frequency bands , Search.For FV, the highest total number of connections was eight, which was found in the gamma band in the SMG in both hemispheres and in the left PreC  were identified for FV and 36 (16 in the left and 20 in the right hemisphere) for VS . The ROIThe temporoparietal junction is known to comprise parts of the SMG and STG, and several authors have reported that damage in the right temporoparietal junction causes visual processing defects, such as left spatial neglect or hemiextinction . ShulmanHowever, significant activity was also seen in the left temporoparietal junction during FV while being absent during VS. A potential reason for this difference would be the differential response of the left and right temporoparietal junction to target and non-target (distractor) stimuli. It has been reported that the left temporoparietal junction responds only to distractor stimuli in the right hemifield, while the right temporoparietal junction responds to distractors in both hemifields . At the The ParaCeL, which was also absent for VS in the left hemisphere, was shown to encompass the supplementary eye field (SEF), which is, along with the frontal eye field and the parietal eye field, one of the three main areas in primates dedicated to the execution of eye movements . ElectriThe ROIs were found to form two major clusters in each hemisphere: the temporoparietal cluster and the dorsal cluster. The fact that the PI and the TTG formed the temporoparietal cluster together with the SMG and the STG indicates existing functional relationships between these areas. Activations in the insula have been observed in a multitude of tasks , althougIn addition to the temporoparietal cluster, SCPT also revealed significant activity in the dorsal regions of the brain during both FV and VS, forming the dorsal cluster. According to the probabilistic maps of visual areas created by Despite clear differences in the processing requirements for FV and VS, the areas covered by the clusters were mostly identical in both tasks. Furthermore, if the ROI identification is performed using the contrast of the average FRAs between FV and VS, no significant clusters were found (results not shown). Consequently, potential differences in the averaged time courses between the two tasks were small, possibly indicating that important differences on a single-epoch level were lost in the averaging process. Indeed, the single-epoch Granger causality analysis revealed differences in the causality networks between the two tasks . This suggests that, although mostly the same ROIs are being engaged, the way in which these ROIs interact with one another is crucial for understanding the difference between free viewing and guided visual searching.In summary, literature evidence indicates that all four areas of the temporoparietal cluster are involved in visual processing and/or attention shifting and not just the temporoparietal junction (SMG and STG). It has been observed that damage to these areas or inactivation, e.g., through TMS, can result in defects in visual processing. Since significant FRA was seen during both FV and VS, it is likely that the temporoparietal cluster plays an important role in visual search and visual exploration. Finally, when comparing the two tasks, the overall differences between the areas with significant FRA were small, suggesting that the same areas are required for performing search tasks and when freely viewing images. We therefore hypothesize that the important distinctions only lie in how these areas interact with one another during each task.To relate the neuronal activity to behavioral performance during VS, we examined the correlation between the FRA amplitudes for the first fixation on the target object and the subjects’ response times on single trials. A significant, albeit rather weak, negative correlation was found between the FRA amplitude in the right SMG and the response time, indicating that stronger activity in the right SMG is associated with shorter response times. No significant correlation was found for any other ROIs.The FRA in the right SMG exhibited the largest amplitude in the time interval between 113 and 181 ms from fixation onset, and the activity in this time period was significantly correlated with the response time. Previous studies have indicated that representations of complex visual objects would already have been established in the visual system before this time interval. For example, in an experiment on macaque monkeys performing a rapid face categorization task, discrimination between different stimuli is possible after, on average, 108 ms from stimulus onset based on single-unit activity in the anterior superior temporal sulcus . Since hFirst, according to the feature integration theory proposed by Of the three possible interpretations for the observed negative correlation between the FRA in the right SMG following the first fixation on the search target and the response time , both binding and trans-saccadic integration are processes modulated by attention. Since the SMG has previously been associated with attention-related processes, we believe these two processes offer a more likely explanation than template matching. The results support previous findings that the right SMG participates in target detection.We hypothesized that the processes required for a guided visual search would affect the topography of the whole-brain causal interaction network. To test this hypothesis, causal interactions between ROIs in the time interval between 0 and 300 ms from fixation onset were computed for FV and VS using GPDC. Based on random permutations, ROIs with significant node degrees were identified. The obtained causal interaction networks and node degrees indeed exhibited distinct properties depending on the task, as discussed in detail below.For FV, ROIs in the temporoparietal cluster  exhibited a large number of local causal interactions. The node degrees of all these ROIs, with the exception of the left PI, were significantly high in both hemispheres. This is consistent with previous findings from For VS, the highest total node degree was always found in the right SMG throughout the frequency bands , and manAccording to our hypothesis, two possible mechanisms could explain the increased connectivity in the right SMG. First, if one compares the process of searching an image to that of freely viewing an image, an obvious difference is that searching requires a comparison of the visual information sampled at a fixation point with the mental image of the search target in order to recognize the search target. This is a cognitive process sometimes referred to as target template matching . Second,In relation to the process of attention shifting, there was one intriguing causal interaction that was only present during VS, i.e., the connection from the right SMG to the right ParaCeL, the location of the SEF (section “Regions of Interests”). This connection was found in the delta, theta, and alpha bands. The SEF has been reported to play a critical role in controlling the saccade direction in the face of several competing options . It has Most of the observations discussed above do not show clear differences between the examined frequency bands. Hence, it is difficult to make statements regarding which functions are particularly associated with which frequencies. Moreover, several of the discussed connections are present in all frequency bands. This might mean that the communication involving the ROIs in the temporoparietal cluster is overall enhanced during VS, without specific enhancement of a particular function.In summary, our results uphold the hypothesis that the temporoparietal junction, i.e., the SMG and STG, participate in recognizing the target and guiding eye movements during visual search. A novel observation in the present study is that the PI and the TTG are also potentially relevant for these processes. Based on the strong connections within the right temporoparietal cluster during VS, we further hypothesize that the ROIs in this cluster form a functional unit for these processes, with the SMG being a central node. We highlight the connection from the right SMG to the right ParaCeL to be of particular importance for guiding eye movements according to a search priority map.To the best of our knowledge, this study is the first to analyze the directed interactions of MEG signals in the context of natural vision by combing SCPT with Granger-based GPDC. We found a temporoparietal cluster with significant fixation-related evoked activity consisting of the PI, TTG, STG, and SMG, as well as a dorsal cluster composed of the occipital area  and areas associated with the ventral and dorsal visual streams . GPDC analysis revealed these areas in the temporoparietal cluster to be tightly connected with each other as well as with areas outside the cluster during both the FV and the VS task. Our results point toward these regions being involved in guiding eye movements during active vision. In particular, the right SMG exhibited the highest degree of causal interactions during the search task, indicating its central role in guided visual searching. We specifically note that the interaction from the right SMG to the right SEF would suggest that the former provides the latter with the information necessary to update a priority map for saccade guidance. This view was further supported by the finding that higher activity in the right SMG during fixations on the search target was correlated with shorter response times, indicating the right SMG’s involvement in the integration of visual input for object recognition. Taken as a whole, these findings support the hypothesis that the temporoparietal junction (SMG and STG) is a central part in the connectivity networks during guided visual searching and that it is involved in object recognition and the guidance of eye movements.The ROI time courses supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of RWTH Aachen University Hospital (EK 225/17). The participants provided their written informed consent to participate in this study.CK developed and designed the methodology, performed the formal analysis, and wrote the original draft of the manuscript. CK and FB set up the experiment and wrote the software for conducting the experiment. JI was involved in the formal analysis, reviewed, and edited the manuscript. RW reviewed and edited the manuscript. NS provided resources for conducting the experiment and reviewed and edited the manuscript. SG and JD conceptualized the experiment, devised the methodology, acquired funding, edited, and reviewed the manuscript. JD was responsible for the project administration and supervision. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Objectives: Grip force during hand tool operation is the primary contributor to tendon strain and related wrist injuries, whereas push force is a contributor to shoulder injuries. However, both cannot be directly measured using a single measurement instrument. The objective of this research was to develop and test an algorithm to isolate the grip and push force distributions from in-situ hand-handle pressure measurements and to quantify their distributions among industrial workers using an electric nutrunner. Methods: Experienced automobile assembly line workers used an industrial nutrunner to tighten fasteners at various locations and postures. The pressure applied by the hand on the tool handle was measured dynamically using pressure sensors mounted on the handle. An algorithm was developed to compute the push force applied to the handle of an electric pistol-grip nutrunner based on recorded pressure measurements. An optimization problem was solved to find the contribution of each measured pressure to the actual pushing force of the tool. Finally, the grip force was determined from the difference between the measured pressure and the calculated pushing pressure. Results: The grip force and push force were successfully isolated and there was no correlation between the two forces. The computed grip force increased from low to high fastener locations, whereas the push force significantly increased during overhead fastening. A significant difference across the participants’ computed grip forces was observed. The grip force distribution showed that its contribution to total hand force was larger than other definitions in the literature. Conclusions: The developed algorithm can aid in better understanding the risk of injury associated with different tasks through the notion of grip and push force distribution. This was shown to be important as even workers with considerable power tool experience applied significantly more grip and push force than other participants, all of whom successfully completed each task. Moreover, the fact that both forces were uncorrelated shows the need for extracting them independently. Upper extremity cumulative trauma disorders (UECTD) are a major contributor to lost work hours in manufacturing environments, often resulting from forceful and repetitive tasks . Many inRisk factors for UECTDs are split into two categories: non-occupational and occupational. Non-occupational factors include age and obesity, while occupational factors include repetitiveness and forcefulness. It is well known that a higher incidence of CTS is associated with forceful exertions of the hand , but alsh-axis of the biodynamic hand coordinate system defined in ISO 8727 [h-axis [Task repetition, such as the number of bolts fastened, is easy to quantify and ergonomists continually strive to minimize it. Quantifying the force, specifically the grip force, is far more challenging. Grip force is usually measured on a single axis using a dynamometer. This approach has been widely used to monitor and control the grip force during glove tests, biodynamic response measurements, and many other experiments involving hand-grip simulations ,9,10. AcISO 8727 . This is [h-axis .The grip force is an important contributor to the overall hand force, but the quantification of grip force during industrial tool operation is challenging. The grip force must be separated from other forces applied to the hand tool, such as push and pull forces, which, by themselves, increase the risk of shoulder injuries . UniaxiaThere is no clear consensus on which measurements are required to quantify the stress imposed on the anatomical hand-arm system by different hand tools. An attractive alternative to directly measuring the grip and push forces is the measurement of the force distribution on the handle , which iThe goal of this paper is to demonstrate the feasibility of separating the grip and push force distributions from the measured hand-handle force distribution. For this purpose, an algorithm is proposed to decouple the measured force distribution on a handle into distinct grip and push force distributions, in contrast to single force vectors. The algorithm first solves static equilibrium equations to find the resulting push force from pressure map data. Then, a minimization algorithm is used to find the contribution of each force measurement to the push force, thereby extracting the push force distribution. This is then subtracted from the pressure map data to find the grip force distribution on the handle.The second objective of this study is to demonstrate the usefulness of such force isolation by collecting data on low, high, and overhead fastening tasks with a pistol-grip electric nutrunner, which simulates the range of fastening locations that is typically found in an automobile assembly line.An in situ-study was designed to measure the force distribution applied to a pistol-grip hand tool during a common bolt fastening task at an automobile manufacturing facility. The subject group consisted of five male and four female participants with power tool experience ranging from 6 months to 25 years, all of whom were employed by the same automobile manufacturer. One male and one female participant were left hand dominant; however, both preferred to operate power tools with their right hand. Participant information is summarized in An electric, handheld, pistol-grip nutrunner manufactured by Atlas Copco (Model ETP ST32-10-10) was used for this study. This is a common direct-current (DC) hand tool that is typically used to tighten fasteners in a manufacturing assembly line. The handle had an ellipsoidal cross-section with minor and major axis lengths of 20 mm and 30 mm, respectively. The tool handle was instrumented with a trimmable Tekscan 9830 pressure mapping sensor  Tekscana. The diThe pressure map was carefully cut in order to adapt to the shape of the tool handle without damaging the electronic circuitry. Each sensor measured a raw output value between 0 and 255 units based on the locally applied pressure. The pressure map was connected to a computer via proprietary hardware and the data were collected using Tekscan’s I-Scan 5.90 software. The pressure map was calibrated using deadweights of known mass before and after the study in order to convert the raw output of the sensor into force in Newtons, since Tekscan does not provide the one-off calibration curve for each sensor.Each participant used the hand tool to fasten three bolts at three different locations and postures on a custom frame see —low  was used to process the data. First, the bias from each sensor was subtracted in order to remove the residual pressure measurement that resulted from contouring the pressure map around the tool handle. Second, the calibration factor was applied to convert the raw pressure values to Newtons. Finally, the measurements from sensors in the same column  were sumThe pressure on each sensor is uniformly distributed.Friction forces on the handle are negligible.All forces acting perpendicular to the handle surface are measured.The goal of the optimization algorithm is to find the proportion The first step of the algorithm is to solve the equation for the static equilibrium condition represented in With the reaction force Subject to:The minimization algorithm maximizes the spread of the force (minimizing the variance) contributing to the pushing of the tool ) was then recomputed to maximize the variance (instead of minimizing it) in order to observe the effect of the cost function on the grip force distribution. The gripping contact force, defined as the sum of the norm of the grip force distribution at the hand-handle interface, was then computed to observe any difference across the participants as follows:The mean force data while the trigger was engaged were analyzed in this paper. The means of six trials for every task for each participant were computed to visualize the effect of the task on the grip and push forces. A subject-specific Pearson correlation coefficient was computed between the contact grip force and the contact push force in order to understand the coupling between the two forces. The contribution of the grip force to the total force (oupling) ,24, wherp = 0.05) with Bonferroni corrections to identify any statistical differences between the tasks/participants. Those statistical tests are non-parametric, and there was no underlying assumption regarding the distributions of the tested samples.Friedman tests (α = 0.05) were used to identify any statistical difference at the group level (comparing more than two distributions). If a difference was observed at the group level, the Friedman test was followed by Wilcoxon signed rank tests  are shown in 2 of 0.95 illustrates strong estimation capabilities.The estimated contact forces from the extracted Each participant mean force p < 0.05) showing a significant difference in both gripping contact forces and pushing contact forces between participants.The gripping contact forces, The subject-specific Pearson correlation coefficient between the The participants’ mean contact gripping and pushing forces for each task are shown in The comparison of the grip force contribution to the total hand force when using the coupling force definition  to the accomplishment of a given task, which was underestimated by previous methods. This can, in turn, be used by ergonomists to better design workstations in assembly lines but could also be used to identify workers who are at a higher risk of injury.The algorithm was able to reconstruct the push force distribution with low error  ranged between 6.1° and 34.2° about the Y-axis   when refISO 8727 . The zh-e Y-axis . Therefoh-axis).It was shown that the proposed linear relationship between grip force, push force, and the contact force is still applicable with an ellipsoidal cross-section handle  see Fig. The linnd b, in  were 3.4Other than assuming all of the forces applied by the user on the pistol-grip tool are measured, the main hypothesis behind the algorithm is the cost function used. We hypothesized that when a user pushed on the tool handle, the distribution of the pressure on their hand is maximized due to the compliance of the hand. It has to be emphasized that minimizing the variance of the pushing force components, subject to the constraints herein, could only spread the force on half of the handle since half of it was constrained to be 0 N. In the case of seven discrete circumferential measurements, it was shown that the cost function has little impact on the final grip force distribution . Other tOne of the main benefits of using the algorithm presented here is to be able to extract the amount of contact grip and push forces between tasks solely from the pressure measurements, as shown in Extracting contact grip and push forces is also helpful when comparing individuals’ performance. As observed in It was shown that for the fastening tasks tested herein, the grip force had a larger contribution to the overall hand force than the pushing action . This waThe main limitation of this study is the lack of validation of the computed push and grip forces using an instrumented handle and/or a force plate. However, based on ,21, a smIt is well known that forceful exertion is directly related to UECTD; therefore, it is important to reduce the unnecessary gripping force that is applied during the hand tool operation by monitoring hand-handle contact forces. New assembly line workers can experience high levels of muscle fatigue by applying grip force far beyond what is required for the task, while experienced workers can be set in their way of over-gripping, further increasing their risk of injury as they age. This is especially relevant when considering non-occupational UECTD risk factors given North America’s aging and overweight workforce. Werner et al. found that automotive and industrial workers over 40 years old have a 76% increased risk of upper extremity tendonitis, while those classified as obese (BMI > 30) are 93% more likely to be diagnosed with CTS . With anIn this paper, an algorithm is proposed to isolate the measured force distribution on a handle into distinct grip and push force distributions, in contrast to other available methods, which decouples grip and push into single force vectors. The contributions of this paper are two-fold. First, we demonstrated the feasibility of separating the grip and push force distributions from the measured hand-handle force distribution, which can provide salient information on the task being performed. Second, the collected data on low, high, and overhead fastening tasks with a pistol-grip electric nutrunner showed a large variability in grip and push forces across tasks, as well as a large variability between individuals. Moreover, the uncorrelated nature of the grip and push forces illustrated the need to decouple the force measurements in order to accordingly minimize the risk of injuries.


A preliminary design of customized antibiotic-loaded poly-methyl-methacrylate (ALPMMA) spacer characterized by an appropriate footprint according to the specific patient’s anatomy and a reliable mechanical response to severe functional loads  is reported. The targeted virtual prototyping process takes origin from a novel patented 3D geometrical conceptualization characterized by added customization features and it is validated by a preliminary FEM-based analysis. Mechanical and thermomechanical properties of the antibiotic-doped orthopedic PMMA cement, which will be used for the future prototype manufacturing, were measured experimentally by testing samples taken during a real day-running orthopedic surgery and manufactured according to the surgeon protocol. FEM analysis results indicate that small area is subjected to intensive stresses, validating the proposed geometry from the mechanical point of view, under the two loading scenarios, moreover the value of safety margins results positive, and this is representative of the lower stress magnitude compared to the critical material limits. The experimental data confirm that the presence of antibiotic will last during the surgeon period moreover, the temperature dependent modulus of the bone cement is slightly affected by the body range temperature whereas it will drastically drop for higher temperature out the range of interest. A complete customization, according to a patient anatomy, and the corresponding real prototype spacer will be manufactured by 3D printing techniques, and it will be validated by destructive testing during the second stage of this activity before commercialization. Joint replacement (JR) is a life-improving procedure affecting millions of people worldwide each year. Successful JR significantly affects the patients’ personal autonomy and quality of life. Although JR is already a frequently performed procedure, the incidence rate of prosthesis implantation is expected to continue to rise ,2,3,4,5.Antibiotic-loaded PMMA (ALPMMA) spacers aims to preserve anatomical structures, and joint mobility and to allow infection cure by releasing antibiotics locally. Moreover, ALPMMA spacer favor the re-implantation of the definitive prosthesis during the second stage of PJI treatment ,24,25,26Conventionally, ALPMMA spacers are available only in three or four standard sizes, with the impossibility to guarantee the perfect matching of ALPMMA spacers with residual bone (no further bone loss) and gap filling. For these reasons, to obtain a well clinical and functional results, the surgical procedure necessitates an increased time than joint prosthesis implantation. The surgical time is correlated to patient’s blood loss  and incrNo studies have been conducted to introduce design guidelines of ALPMMA spacers as a tool to combine the geometric characteristics of the spacers with its mechanical and functional properties. The present paper aims to evaluate the effect of possible customization on the mechanical performance in operating and simulated worst loading conditions. The expected result is a customized ALPMMA spacer that shows not only an appropriate footprint, as a function of patient’s anatomical behavior but also an adequate response to mechanical stresses. The paper is organized as follows: the proposed ALPMMA geometric 3D model is presented describing the customization feature of the model, which is later used for the FEM numerical simulations. The spacer material is characterized to acquire the necessary information regarding the mechanical properties according to medical standard and procedure, ultimately conclusions are drawn to pave the way for future optimization studies toward the complete customization according to the patients.Standard ALPMMA spacers are often used during staged revision arthroplasty due to bio-film-related infection in cases of extensive or asymmetrical bone loss since standard spacers may not preserve alignment, stability, and anatomical matching, thus causing failure of the procedure. In the following, a not exhaustive list of drawbacks associated with the common used ALPMMA spacers are reported, such as: (I) both femoral-tibial and femoral-patellar instability; (II) the possibility of developing important contractures in flexion; (III) frailty and subsequent breaking of the implant, especially with high doses of antibiotic; (IV) the difficulty of managing malalignments on the three planes of space  and bone defects whether segmental or cavitary . The aforementioned weaknesses may be overcome through the designing of a patient-tailored ALPMMA spacer with specific features to mitigate the above mentioned drawbacks . The objTo evaluate the cause-and-effect link between the geometric characteristics of the ALPMMA spacer along with the surgery and mechanical failures, a multivariable oriented design was set and implemented. The result is an ALPMMA spacer configuration with different degrees of freedom in terms of geometrical parameters to act with to manage efficiently according to the actual patient the alignment, the stability and the anatomical matching see .Femoral condyles were shaped on both sides to effectively reduce pressure on the soft tissue and on anterior patellar. Moreover, to improve sliding and thus reducing the risk of adverse reactions, such as dislocation and ringing after surgery, it is possible to customize the shape of the anterior condyle , the amplitude of the two femoral internal condyles  and also the amplitude of cutting segments  along with corresponding angles . Finally, an augmented ALPMMA femoral spacer is expected to correct severe bone defects reducing after implantation pain and time of recovery. In From The proposed 3D model provides a multitude of degrees of freedom also for the tibial component. In fact, as shown in In order to correctly and accurately predict the mechanical behavior of the proposed geometry, experimental tests are mandatory to retrieve the material properties of the bone cement. The material considered for the prototype of the proposed spacer is a polymethylmethacrylate system loaded with 20% by weight of zirconium dioxide, kindly provided by Zimmer-Biomet Ltd.  . The antIndeed, literature data on the mechanics of bone cements could not be directly compared, due to the induced variability associated with the preparation, the storage of sample and also testing conditions. Hence, in this work, compressive and flexural strengths have been measured experimentally following the recommendation of the ASTM standards, respectively, F451, D5023, and E831 and laboratory protocol for thermos-gravimetrical measurements, respectively. These tests were carried out to evaluate, respectively: the compressive modulus, the temperature dependency of the flexural modulus, the mass loss and the coefficient of thermal expansion. More in details, the compression modulus has been measured according to the indication of ASTM F451 on cylindrical shaped specimens; the effect of the temperature on flexural modulus was determined by Dynamic Mechanical Analysis according to the ASTM D5023, under three point bending configuration under force ramp mode. by using a 1 Hz frequency value and an elastic displacement of 40 μm with a temperature rate of 1 °C/min. In addition, a thermogravimetric analysis (TGA) was carried out, to verify the mass loss as a function of time, at constant temperature , which can be related to the antibiotic released in the human body when the spacer is in position and during the normal service period. Finally, a characterization test was carried out to evaluate the thermal expansion co-efficient of the material in three different temperature ranges.The compressive tests have been carried out according to the standard ASTM F451 on cylinder shaped specimens with nominal dimension of 12 mm high and 6 mm in diameter see . For staThe compression stress vs. strain curves are shown in The three-point bending tests have been performed according to the ASTM D5023 see . This teIn this work, a DMA Q800 by TA INSTR set with a cooling unit was employed to perform the experiments. According to the test, a rectangular cross-section bar is placed on the DMA supports and loaded to achieve a constant elastic displacement  at 1 Hz frequency and 1 °C/min heating ramp. The considered span-to-thickness ratio induces a minimization of the shear forces during the flexural deformation and thus the final modulus can be assumed as the tensile modulus with a very good approximation.Results indicate a sharp variation of the material stiffness sooner above 40 °C with a wide glass transition range up to 90 °C, above this temperature the sample completely deforms reporting a negligible stiffness un the considered displacement. The curve for one of the tested samples is shown in Within the range 34 °C to 41 °C, the bone cement reports an expected linear dependency with the temperature, but this effect is assumed negligible within the range of medical and diagnosis interest .Bone cement weight loss as a function of time, at a constant temperature  was followed by gravimetrical analysis. The test was performed on few milligrams of antibiotic bone cement taken from different location of the casted sample and heated at 1 °C/min under air for 200 min, corresponding to a time period equivalent to a surgery time frame see .The weight variation is very negligible, less than 3%, validating the assumption that during the progression of the surgery the diffusion depletion of the mixed antibiotic content is unexpected, and the material will be triggering the drug release by such factors as pH blood and body location humidity. The initial drop of the curve is reasonably related to the surface absorption of antibiotic al-most immediately lost by the sample.The analysis of the thermomechanical behavior of the cement spacer was performed considering different temperature range , respectThe TMA results highlight theta the coefficient of thermal expansion is within a narrow range of variation between the room condition and the higher body range as also confirmed by the test per-formed within the extended temperature range and the coefficient value reach an averaged value of 118.9 °mm/°C.In the framework of optimized and customizable design, the use of 3D printing process ,30 is maTwo test cases have been considered: level walking (Test Case 1) and 45° bent knee (Test Case 2). The boundary conditions used to simulate the level walking and the 45° bent knee test cases are shown in Moreover, a 2000 N load, equivalent to the load acting on the knee by a 70 kg walking man (multi-plied by a factor of about 300%)  and orieThen, static non-linear analyses have been carried out on each Test Case, to determine the stress distribution on the component when subjected to the service loading conditions.crit. Values of the safety margins lower than 0 indicates that the stress of the structure locally exceeds the critical value of the stress, while positive safety margins are representative of values of the stress lower than the critical one. Higher values of the safety margins indicate higher differences between local and critical stresses. In particular, the safety margin is computed as [In puted as :(1)SafetAccording to In this work, the customization of the spacer has been assessed, based on the mechanical performance in operating and simulated worst loading conditions. The mechanical characteristics of the materials of the prototype have been derived by means of experimental test procedures, using the ASTM standards F451, D5023, and E831. Additionally, thermo-gravimetrical analyses have been carried out to evaluate the weight variation during the progression of the surgery.The analyses have demonstrated that the weight loss is very negligible (<3%) for the considered conditions; moreover, the mechanical performances of the spacer have been investigated by means of finite element approaches in two referred loading modes. The numerical analyses suggested that the spacer is highly over-dimensioned. Actually, suitable configurations, capable of sustaining safely the service operative conditions, can be obtained by reducing, in the most critical regions, the thickness up to an order of magnitude. Indeed, future development could be focused on the size and shape optimization of the spacer, to reduce its total mass especially in the least stressed regions.