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| DATE | 2020-03-06 |
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| SUBJECT | Subject: [Hangout - NYLXS] Announcing the inaugural issue of IEEE OJEMB
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Subject: [Hangout - NYLXS] Announcing the inaugural issue of IEEE OJEMB
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IEEE Open Journal of Engineering in Medicine and Biology Inaugural Issue T=
he IEEE OJEMB Inaugural Issue OJEMB Home | Advisory Board | Instruction for=
Authors | Submit an Article To facilitate bringing together researchers wh=
o typically publish their work in Science and Nature and researchers who ty=
pically publish their work in IEEE=E2=80=A6 authors can use the Science Man=
uscript template or the Technology Manuscript template for their submission=
s. Featured Articles Small-World Propensity Reveals the Frequency Specifici=
ty of Resting State Networks Riccardo Iandolo; Marianna Semprini; Stefano B=
uccelli; Federico Barban; Mingqi Zhao; Jessica Samogin; Gaia Bonassi; Laura=
Avanzino; Dante Mantini; Michela Chiappalone Functional connectivity (FC) =
is an important indicator of the brain=E2=80=99s state in different conditi=
ons, such as rest/task or health/pathology. Here we used high-density elect=
roencephalography coupled to source reconstruction to assess frequency-spec=
ific changes of FC during resting state. Specifically, we computed the Smal=
l-World Propensity (SWP) index to characterize network small-world architec=
ture across frequencies. Methods: We collected resting state data from heal=
thy participants and built connectivity matrices maintaining the heterogene=
ity of connection strengths. For a subsample of participants, we also inves=
tigated whether the SWP captured FC changes after the execution of a workin=
g memory (WM) task. Results: We found that SWP demonstrated a selective inc=
rease in the alpha and low beta bands. Moreover, SWP was modulated by a cog=
nitive task and showed increased values in the bands entrained by the WM ta=
sk. Conclusions: SWP is a valid metric to characterize the frequency-specif=
ic behavior of resting state networks. Read more Modulating the Structure o=
f Motor Variability for Skill Learning Through Specific Muscle Synergies in=
Elderlies and Young Adults Vincent C. K. Cheung; Xiao-Chang Zheng; Roy T. =
H. Cheung; Rosa H. M. Chan Motor variability =E2=80=93 performance variatio=
ns across task repetitions =E2=80=93 has been assumed to be undesirable. Bu=
t recent studies argue that variability facilitates early motor learning by=
allowing exploratory search of reward-generating motion, and that variabil=
ity=E2=80=99s structure may be modulated by neural circuits for furthering =
learning. What are the neural sources of learning-relevant motor variabilit=
y and its modulation in humans of different ages? Methods: Elderlies and yo=
ung adults played a 3-session virtual bowling while multi-muscle electromyo=
graphic signals were collected. We quantified trial-to-trial variability of=
muscle synergies =E2=80=93 neuromotor control modules =E2=80=93 and of the=
ir activations. Results: In elderlies, bowling-score gain correlated with c=
hange of activation timing variability of specific synergies, but in young =
adults, with variability changes of synergy-activation magnitude, and of th=
e synergies themselves. Conclusions: Variability modulation of specific mus=
cle synergies and their activations contribute to early motor learning. Eld=
erly and young individuals may rely on different aspects of motor variabili=
ty to drive learning. Read more On Error-Related Potentials During Sensorim=
otor-Based Brain-Computer Interface: Explorations With a Pseudo-Online Brai=
n-Controlled Speller Michele Bevilacqua; Serafeim Perdikis; Jos=C3=A9 del R=
. Mill=C3=A1n Brain-computer interface (BCI) spelling is a promising commun=
ication solution for people in paralysis. Currently, BCIs suffer from imper=
fect decoding accuracy which calls for methods to handle spelling mistakes.=
Detecting error-related potentials (ErrPs) has been early identified as a =
potential remedy. Nevertheless, few works have studied the elicitation of E=
rrPs during engagement with other BCI tasks, especially when BCI feedback i=
s provided continuously. Methods: Here, we test the possibility of correcti=
ng errors during pseudo-online Motor Imagery (MI) BCI spelling through ErrP=
s, and investigate whether BCI feedback hinders their generation. Ten subje=
cts performed a series of MI spelling tasks with and without observing BCI =
feedback. Results: The average pseudo-online ErrP detection accuracy was fo=
und to be significantly above the chance level in both conditions and did n=
ot significantly differ between the two (74% with, and 78% without feedback=
). Conclusions: Our results support the possibility to detect ErrPs during =
MI-BCI spelling and suggest the absence of any BCI feedback-related interfe=
rence. Read more Accelerometry-Based Digital Gait Characteristics for Class=
ification of Parkinson=E2=80=99s Disease: What Counts? Rana Zia Ur Rehman; =
Christopher Buckley; Maria Encarna Mic=C3=B3-Amigo; Cameron Kirk; Michael D=
unne-Willows; Claudia Mazz=C3=A0; Jian Qing Shi; Lisa Alcock; Lynn Rocheste=
r; Silvia Del Din Gait may be a useful biomarker that can be objectively me=
asured with wearable technology to classify Parkinson=E2=80=99s disease (PD=
). This study aims to: (i) comprehensively quantify a battery of commonly u=
tilized gait digital characteristics (spatiotemporal and signal-based), and=
(ii) identify the best discriminative characteristics for the optimal clas=
sification of PD. Methods: Six partial least square discriminant analysis (=
PLS-DA) models were trained on subsets of 210 characteristics measured in 1=
42 subjects (81 people with PD, 61 controls (CL)). Results: Models accuracy=
ranged between 70.42-88.73% (AUC: 78.4-94.5%) with a sensitivity of 72.84-=
90.12% and a specificity of 60.3-86.89%. Signal-based digital gait characte=
ristics independently gave 87.32% accuracy. The most influential characteri=
stics in the classification models were related to root mean square values,=
power spectral density, step velocity and length, gait regularity and age.=
Conclusions: This study highlights the importance of signal-based gait cha=
racteristics in the development of tools to help classify PD in the early s=
tages of the disease. Read more Predicting Lymphoma Development by Exploiti=
ng Genetic Variants and Clinical Findings in a Machine Learning-Based Metho=
dology With Ensemble Classifiers in a Cohort of Sj=C3=B6gren=E2=80=99s Synd=
rome Patients Konstantina D. Kourou; Vasileios C. Pezoulas; Eleni I. Georga=
; Themis Exarchos; Costas Papaloukas; Michalis Voulgarelis; Andreas Goules;=
Andrianos Nezos; Athanasios G. Tzioufas; =CE=97aralampos M. Moutsopoulos; =
Clio Mavragani; Dimitrios I. Fotiadis Lymphoma development constitutes one =
of the most serious clinico-pathological manifestations of patients with Sj=
=C3=B6gren=E2=80=99s Syndrome (SS). Over the last decades the risk for lymp=
homagenesis in SS patients has been studied aiming to identify novel biomar=
kers and risk factors predicting lymphoma development in this patient popul=
ation. Objective: The current study aims to explore whether genetic suscept=
ibility profiles of SS patients along with known clinical, serological and =
histological risk factors enhance the accuracy of predicting lymphoma devel=
opment in this patient population. Methods: The potential predicting role o=
f both genetic variants, clinical and laboratory risk factors were investig=
ated through a Machine Learning-based (ML) framework which encapsulates ens=
emble classifiers. Results : Ensemble methods empower the classification ac=
curacy with approaches which are sensitive to minor perturbations in the tr=
aining phase. The evaluation of the proposed methodology based on a 10-fold=
stratified cross validation procedure yielded considerable results in term=
s of balanced accuracy (GB: 0.7780 =C2=B1 0.1514, RF Gini: 0.7626 =C2=B1 0.=
1787, RF Entropy: 0.7590 =C2=B1 0.1837). Conclusions: The initial clinical,=
serological, histological and genetic findings at an early diagnosis have =
been exploited in an attempt to establish predictive tools in clinical prac=
tice and further enhance our understanding towards lymphoma development in =
SS. Read more Engineered Three-Dimensional Scaffolds Modulating Fate of Bre=
ast Cancer Cells Using Stiffness and Morphology Related Cell Adhesion Samer=
ender N. Hanumantharao; Carolynn A. Que; Brennan J. Vogl; Smitha Rao Artifi=
cially engineering the tumor microenvironment in vitro as a vital tool for =
understanding the mechanism of tumor progression. In this study, we develop=
ed three-dimensional cell scaffold systems with different topographical fea=
tures and mechanical properties but similar surface chemistry. The cell beh=
avior was modulated by the topography and mechanical properties of the scaf=
fold. Methods: Adenocarcinoma (MCF7), triple-negative (MDA-MB-231) and prem=
alignant (MCF10AneoT) breast cancer cells were seeded on the scaffold syste=
ms. The cell viability, cell-cell interaction and cell-matrix interactions =
were analyzed. The preferential growth and alignment of specific population=
of cells were demonstrated. Results: Among the different scaffolds, triple=
-negative breast cancer cells preferred honeycomb scaffolds while adenocarc=
inoma cells favored mesh scaffolds and premalignant cells preferred the ali=
gned scaffolds. Conclusions: The 3D model system developed here can be used=
to support growth of only specific cell populations or for the growth of t=
umors. This model can be used for understanding the topographical and mecha=
nical features affecting tumorigenesis, cancer cell growth and migration be=
havior of malignant and metastatic cancer cells. Read more Ultrasound Based=
Planning and Navigation for Non-Anatomical Liver Resections =E2=80=93 An E=
x-Vivo Study Iwan Paolucci; Raluca-Maria Sandu; Luca Sahli; Gian Andrea Pre=
vost; Federico Storni; Daniel Candinas; Stefan Weber; Anja Lachenmayer Non-=
anatomical resections of liver tumors can be very challenging as the surgeo=
n cannot use anatomical landmarks on the liver surface or in the ultrasound=
image for guidance. This makes it difficult to achieve negative resection =
margins (R0) and still preserve as much healthy liver tissue as possible. E=
ven though image-guided surgery systems have been introduced to overcome th=
is challenge, they are still rarely used due to their inaccuracy, time-effo=
rt and complexity in usage and setup. Methods: We have developed a novel ap=
proach, which allows us to create an intra-operative resection plan using n=
avigated ultrasound. First, the surface is scanned using a navigated ultras=
ound, followed by tumor segmentation on a midsection ultrasound image. Base=
d on this information, the navigation system calculates an optimal resectio=
n strategy and displays it along with the tracked surgical instruments. In =
this study, this approach was evaluated by three experienced hepatobiliary =
surgeons on ex-vivo porcine models. Results: Using this technique, an R0 re=
section could be achieved in 22 out of 23 (95.7% R0 resection rate) cases w=
ith a median resection margin of 5.9 mm (IQR 3.5=E2=80=937.7 mm). The resec=
tion margin between operators 1, 2 and 3 was 7.8 mm, 4.15 mm and 5.1 mm res=
pectively (p =3D 0.054). Conclusions: This approach could represent a usefu=
l tool for intra-operative guidance in non-anatomical resection alongside c=
onventional ultrasound guidance. However, instructions and training are ess=
ential especially if the operator has not used an image-guidance system bef=
ore. Read more Ultrasound Stimulations Induce Prolonged Depolarization and =
Fast Action Potentials in Leech Neurons Francesca Dedola; Francesco Paolo U=
lloa Severino; Nicol=C3=B2 Meneghetti; Th=C3=A9o Lemaire; Andrea Cafarelli;=
Leonardo Ricotti; Arianna Menciassi; Annarita Cutrone; Alberto Mazzoni; Si=
lvestro Micera Ultrasound (US) stimulation carries the promise of a selecti=
ve, reversible, and non-invasive modulation of neural activity without the =
need for genetic manipulation of neural structures. However, the mechanisms=
of US-induced generation of action potentials (APs) are still unclear. Met=
hods: Here we address this issue by analyzing intracellularly recorded resp=
onses of leech nociceptive neurons to controlled delivery of US. Results: U=
S induced a depolarization linearly accumulating in time and outlasting the=
duration of the stimulation. Spiking activity was reliably induced for an =
optimal US intensity range. Moreover, we found that APs induced by US diffe=
r in smaller amplitude and faster repolarization from those induced by elec=
trical stimulation in the same cell but display the same repolarization rat=
e. Conclusions: These results shed light on the mechanism by which spikes a=
re induced by US and pave the way for designing more efficient US stimulati=
on patterns. Read more Temozolomide in Combination With NF-=CE=BAB Inhibito=
r Significantly Disrupts the Glioblastoma Multiforme Spheroid Formation Hui=
Xia; Naze G. Avci; Yasemin Akay; Yoshua Esquenazi; Lisa H. Schmitt; Nitin =
Tandon; Jay-Jiguang Zhu; Metin Akay Glioblastoma multiforme (GBM) is the mo=
st common malignant primary brain tumor, accounting for 50% of all cases. G=
BM patients have a five-year survival rate of merely 5.6% and a median over=
all survival of 14.6 months with the =E2=80=9CStupp=E2=80=9D regimen, 20.9 =
months with tumor treatment fields (TTF, OptuneR) in patients who participa=
ted in clinical trials, and 11 months for all GBM patients prior to TTF use=
. Objective: Our group recently developed a brain cancer chip which generat=
es tumor spheroids, and provides large-scale assessments on the response of=
tumor cells to various concentrations and combinations of drugs. This plat=
form could optimize the use of tumor samples derived from GBM patients to p=
rovide valuable insight on the tumor growth and responses to drug therapies=
. To minimize any sample loss in vitro, we improved our brain cancer chip s=
ystem by adding an additional laminar flow distribution layer, which reduce=
s sample loss during cell seeding and prevents spheroids from escaping from=
the microwells. Methods: In this study, we cultured 3D spheroids from GBM =
cell lines and patient-derived GBM cells in vitro, and investigated the eff=
ect of the combination of Temozolomide and nuclear factor-=CE=BAB inhibitor=
on tumor growth. Results: Our study revealed that these drugs have synergi=
stic effects in inhibiting spheroid formation when used in combination. Con=
clusions: These results suggest that the brain cancer chip enables large-sc=
ale, inexpensive and sample-effective drug screening to 3D cancer tumors in=
vitro, and could be applied to related tissue engineering drug screening s=
tudies. Read more About OJEMB IEEE Engineering in Medicine and Biology Soci=
ety | 445 Hoes Lane, Piscataway, NJ 08854 Unsubscribe ruben-at-mrbrklyn.com Up=
date Profile | About Constant Contact Sent by noreply-at-embs.org in collabora=
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51, 136); font-weight: bold;">OJEMB Home1, 136);"> >| /r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNO=
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8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4=
iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34,=
51, 136); font-weight: bold;">Advisory Board34, 51, 136); font-size: 14px;"> | jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA=
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qG452ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34, 51, 136); font-=
weight: bold;">Instruction for Authors 136); font-size: 14px;"> | =3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAcq1MM=
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Kdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452=
ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34, 51, 136); font-weigh=
t: bold;">Submit an Article
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ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
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ding=3D"0" cellspacing=3D"0" border=3D"0" style=3D"border-collapse: collaps=
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10px;">
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=3D"center" valign=3D"top" style=3D"background-color: #A898C0;" bgcolor=3D"=
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e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
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le=3D"font-size: 28px;">Featured Articles
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mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
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Helvetica,sans-serif; font-size: 14px; word-wrap: break-word; text-align: l=
eft; color: #36495F; padding: 10px 20px;" align=3D"left">
e: 24px; color: rgb(34, 51, 136); font-weight: bold;">Small-World Propensit=
y Reveals the Frequency Specificity of Resting State Networks
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAhwM0nCQNEgUmbML-RDv2zfU02_R1OEcZ2vmWwff4Oq=
c2ML0Lwf32ReNb-RCCUy-VlfiC-Lhs-KlKz-eHSepSkP9ckXu5uk0hJG98D6HsbSGW74z685Gl8=
Q=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Riccardo Iandolo=
: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; = Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmANN1gIze343ngAcGZK_zlzpv1QOjW1yoy4ciZsbiRfc=
-Ydo4aoum55Nm5so0i8GY0ZQD7JIpnw1ao_7riiEzAQYFqRuCz4WChw5BT4h5w3k3R_AsBbEWT0=
w=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Marianna Semprin=
in: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; >oUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA_6QoVOyG9L3DFYxgKnJeXMjpFFCZtD0GZGozDPx7L=
_fNGIEIm0Saf4Sgmux5Cairwpm-0veS4hd4Wwlt9ZwxNm42kZddcDTXqOzUbubNiFpVZZWuXtGc=
pw=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&c=
h=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D=
"_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration:=
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Stefano Buccell=
in: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; >oUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAslH_W-55e0H8Orh7SgOqJmSRUmuzGoHy8hshIk8Yp=
mcJAyVHdw9N2ze8H1rSkx3MN1pHUH5PeZGP7oQfl_CxKzT1yxJ9-ju67RSgal1fPuX4hBs1z5B4=
Eg=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&c=
h=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D=
"_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration:=
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Federico Barban=
: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; =
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAvC_Y5lO_XYPg8PSVLX4jz-z-7tcBeyDyed0Wuzi4IN=
jTE4GowDMpfc-JMnlu1p4RfAgVwBocNE8kK5DKTBs0hIu_F7bygJQZ8Y_lW-c-FSCQuAfVOPFbF=
A=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Mingqi Zhhref=3D"http://r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0=
R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAvC_Y5lO_XYPg8PSVLX4jz-z-7tcBeyDyed0Wuzi4INjTE=
4GowDMpfc-JMnlu1p4RfAgVwBocNE8kK5DKTBs0hIu_F7bygJQZ8Y_lW-c-FSCQuAfVOPFbFA=
=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">ao=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: none;">; =
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAJRWtbGkZfEO2OONyWRrwlgZ1lNMHM8J6Ci0PkoK_X1=
HE0hFfptLYgBKNbTqUFYkO58TqbK5JSFtgR4a7Ji25XB6jsuA7L0hoOi6c29YbTPJ8W2zNAZRbj=
w=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">Jessica Samogin=
">; qNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmABa-K0zqf_NfaUUSz2vIeiPPgmxMH7Jv=
SdbGSo3d14bD2ljHrzV3OsI7OFBxTPyqyc83B3FNm1mTiDB1_x5GzMSi8bh968maMYGhpwSwstW=
QavvguwZfppw=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQr=
Lg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D"=
target=3D"_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-deco=
ration: none; font-family: Arial, Verdana, Helvetica, sans-serif;">Gaia Bon=
assin: none;">; QupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAPSz79j4z705lpp73Ww2UaqO=
fcHDW6DC6-yLQTmxpMTV_R8KUe66snkxQ3qDWffHziXzSiubCgmvRxYGQkiEGNttnCVBo_7h_uE=
qFP1AsrYgyA45X4vAUOQ=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-=
zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9o=
A=3D=3D" target=3D"_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); t=
ext-decoration: none; font-family: Arial, Verdana, Helvetica, sans-serif;">=
Laura Avanzino-decoration: none;">; 2Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAOL2oGz2r4tzgK=
RipqEGMb6qKDOTnFwZ5tPmUqNif0vVUHZVGVyTzMbpjC0Jq4913FHBOfbQCSY7Kx2jSYccZD_cY=
9G30Fg5wuTW0mSfM8OVwteJpOPOYqg=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015=
eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNb=
NqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-size: 12px; color: rgb(0=
, 0, 0); text-decoration: none; font-family: Arial, Verdana, Helvetica, san=
s-serif;">Dante Mantini 0); text-decoration: none;">; f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAiwrF=
0dOT4sJ8gzgObXa0bAtNkVaNgvX_2iL5K4qCL0lRLu-Pru8c7dL-_WyIRKPJcTJ8XKzim5q8O7Y=
68BE6cUObI9eHYJR406LXk2eENcEyDFGxNsh0JQ=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0=
I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPP=
B-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-size: 12px; col=
or: rgb(0, 0, 0); text-decoration: none; font-family: Arial, Verdana, Helve=
tica, sans-serif;">Michela Chiappalone
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s=3D"galileo-ap-layout-editor" style=3D"border-collapse: collapse; mso-tabl=
e-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
th=3D"100%" style=3D"padding: 0px;">parent; width: 100%; cursor: default; border-collapse: collapse; mso-table-=
lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;" class=3D"galileo-=
ap-content-editor" bgcolor=3D"transparent">base divider-solid" style=3D"height: 1px; line-height: 1px; padding: 8px 0p=
x;" align=3D"center" valign=3D"top" width=3D"100%">
ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
background-color: #36495F;" border=3D"0" cellpadding=3D"0" cellspacing=3D"=
0" align=3D"center" bgcolor=3D"#36495F">
g-bottom: 0px; border-bottom-style: none;" align=3D"center" height=3D"1">
/1101116784221/S.gif" style=3D"display: block; height: 1px; width: 5px;" bo= rder=3D"0" height=3D"1" hspace=3D"0" vspace=3D"0" width=3D"5">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
p">
ding=3D"0" cellspacing=3D"0" border=3D"0" style=3D"border-collapse: collaps=
e; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
10px;">
![3D""]() y: block; height: auto !important; max-width: 100% !important;" width=3D"37= 6" border=3D"0" hspace=3D"0" vspace=3D"0" src=3D"https://files.constantcont= act.com/60f676b8001/2dbd1a7b-53de-41a8-b86c-a29690d149af.jpg">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
p">
e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
ly: Arial,Verdana,Helvetica,sans-serif; font-size: 14px; word-wrap: break-w=
ord; text-align: left; color: #36495F; padding: 10px 20px;" align=3D"left">
ize: 14px; color: rgb(0, 0, 0);">Functional connectivity (FC) is an importa=
nt indicator of the brain’s state in different conditions, such as r=
est/task or health/pathology. Here we used high-density electroencephalogra=
phy coupled to source reconstruction to assess frequency-specific changes o=
f FC during resting state. Specifically, we computed the Small-World Propen=
sity (SWP) index to characterize network small-world architecture across fr=
equencies. Methods: We collected resting state data from healthy participan=
ts and built connectivity matrices maintaining the heterogeneity of connect=
ion strengths. For a subsample of participants, we also investigated whethe=
r the SWP captured FC changes after the execution of a working memory (WM) =
task. Results: We found that SWP demonstrated a selective increase in the a=
lpha and low beta bands. Moreover, SWP was modulated by a cognitive task an=
d showed increased values in the bands entrained by the WM task. Conclusion=
s: SWP is a valid metric to characterize the frequency-specific behavior of=
resting state networks.
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e-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
th=3D"100%" style=3D"padding: 0px;">parent; width: 100%; cursor: default; border-collapse: collapse; mso-table-=
lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;" class=3D"galileo-=
ap-content-editor" bgcolor=3D"transparent">base divider-solid" style=3D"height: 1px; line-height: 1px; padding: 8px 0p=
x;" align=3D"center" valign=3D"top" width=3D"100%">
ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
background-color: #36495F;" border=3D"0" cellpadding=3D"0" cellspacing=3D"=
0" align=3D"center" bgcolor=3D"#36495F">
g-bottom: 0px; border-bottom-style: none;" align=3D"center" height=3D"1">
/1101116784221/S.gif" style=3D"display: block; height: 1px; width: 5px;" bo= rder=3D"0" height=3D"1" hspace=3D"0" vspace=3D"0" width=3D"5">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
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e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
Helvetica,sans-serif; font-size: 14px; word-wrap: break-word; text-align: l=
eft; color: #36495F; padding: 10px 20px;" align=3D"left">
e: 24px; color: rgb(34, 51, 136); font-weight: bold;">Modulating the Struct=
ure of Motor Variability for Skill Learning Through Specific Muscle Synergi=
es in Elderlies and Young Adults
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA0R3SHKoxWb_oMeu2taL6be-ateefRHg2SmmGjXLIg9=
Qly6pnXAapDRiXqSZpo_7x2i5Sk3wTALVkXPuBdVrwoUtR_V7K_2dgl3wKOjohFmELfMx3MipWJ=
g=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">Vincent C. K. Cheun=
gl, Verdana, Helvetica, sans-serif;">; .net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKg=
fCv_QOmAXCMlfiYzYQ_6ea7ZO2U4bFsYe2KaWhcvIlYIS0kniBwunpzD2k6yRDldy8WmDX3sRzV=
o5y4GgaTngFdbSCd7YhqwJBEXO-Or4Y3n0jf-3WlgCy5DxiXEBg=3D=3D&c=3Dubm1sNxhg3e7y=
1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNi=
BT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-siz=
e: 12px; color: rgb(0, 0, 0); font-family: Arial, Verdana, Helvetica, sans-=
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font-family: Arial, Verdana, Helvetica, sans-serif; text-decoration: none;=
">Roy T. H. Cheungfont-family: Arial, Verdana, Helvetica, sans-serif;">; =3D"http://r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KF=
HyPCWUOxNOfgIZAqKgfCv_QOmA5wOq8VSF3Pt5LIfusgS_7qpJYHC5Vi7kC9yiAXpNNKly3cS_X=
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&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ=
2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank"=
style=3D"font-size: 12px; color: rgb(0, 0, 0); font-family: Arial, Verdana=
, Helvetica, sans-serif; text-decoration: none;">Rosa H. M. Chan
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ly: Arial,Verdana,Helvetica,sans-serif; font-size: 14px; word-wrap: break-w=
ord; text-align: left; color: #36495F; padding: 10px 20px;" align=3D"left">
ize: 14px; color: rgb(0, 0, 0);">Motor variability – performance var=
iations across task repetitions – has been assumed to be undesirable=
. But recent studies argue that variability facilitates early motor learnin=
g by allowing exploratory search of reward-generating motion, and that vari=
ability’s structure may be modulated by neural circuits for furtheri=
ng learning. What are the neural sources of learning-relevant motor variabi=
lity and its modulation in humans of different ages? Methods: Elderlies and=
young adults played a 3-session virtual bowling while multi-muscle electro=
myographic signals were collected. We quantified trial-to-trial variability=
of muscle synergies – neuromotor control modules – and of th=
eir activations. Results: In elderlies, bowling-score gain correlated with =
change of activation timing variability of specific synergies, but in young=
adults, with variability changes of synergy-activation magnitude, and of t=
he synergies themselves. Conclusions: Variability modulation of specific mu=
scle synergies and their activations contribute to early motor learning. El=
derly and young individuals may rely on different aspects of motor variabil=
ity to drive learn--===============0642427246==
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IEEE Open Journal of Engineering in Medicine and Biology Inaugural Issue T=
he IEEE OJEMB Inaugural Issue OJEMB Home | Advisory Board | Instruction for=
Authors | Submit an Article To facilitate bringing together researchers wh=
o typically publish their work in Science and Nature and researchers who ty=
pically publish their work in IEEE=E2=80=A6 authors can use the Science Man=
uscript template or the Technology Manuscript template for their submission=
s. Featured Articles Small-World Propensity Reveals the Frequency Specifici=
ty of Resting State Networks Riccardo Iandolo; Marianna Semprini; Stefano B=
uccelli; Federico Barban; Mingqi Zhao; Jessica Samogin; Gaia Bonassi; Laura=
Avanzino; Dante Mantini; Michela Chiappalone Functional connectivity (FC) =
is an important indicator of the brain=E2=80=99s state in different conditi=
ons, such as rest/task or health/pathology. Here we used high-density elect=
roencephalography coupled to source reconstruction to assess frequency-spec=
ific changes of FC during resting state. Specifically, we computed the Smal=
l-World Propensity (SWP) index to characterize network small-world architec=
ture across frequencies. Methods: We collected resting state data from heal=
thy participants and built connectivity matrices maintaining the heterogene=
ity of connection strengths. For a subsample of participants, we also inves=
tigated whether the SWP captured FC changes after the execution of a workin=
g memory (WM) task. Results: We found that SWP demonstrated a selective inc=
rease in the alpha and low beta bands. Moreover, SWP was modulated by a cog=
nitive task and showed increased values in the bands entrained by the WM ta=
sk. Conclusions: SWP is a valid metric to characterize the frequency-specif=
ic behavior of resting state networks. Read more Modulating the Structure o=
f Motor Variability for Skill Learning Through Specific Muscle Synergies in=
Elderlies and Young Adults Vincent C. K. Cheung; Xiao-Chang Zheng; Roy T. =
H. Cheung; Rosa H. M. Chan Motor variability =E2=80=93 performance variatio=
ns across task repetitions =E2=80=93 has been assumed to be undesirable. Bu=
t recent studies argue that variability facilitates early motor learning by=
allowing exploratory search of reward-generating motion, and that variabil=
ity=E2=80=99s structure may be modulated by neural circuits for furthering =
learning. What are the neural sources of learning-relevant motor variabilit=
y and its modulation in humans of different ages? Methods: Elderlies and yo=
ung adults played a 3-session virtual bowling while multi-muscle electromyo=
graphic signals were collected. We quantified trial-to-trial variability of=
muscle synergies =E2=80=93 neuromotor control modules =E2=80=93 and of the=
ir activations. Results: In elderlies, bowling-score gain correlated with c=
hange of activation timing variability of specific synergies, but in young =
adults, with variability changes of synergy-activation magnitude, and of th=
e synergies themselves. Conclusions: Variability modulation of specific mus=
cle synergies and their activations contribute to early motor learning. Eld=
erly and young individuals may rely on different aspects of motor variabili=
ty to drive learning. Read more On Error-Related Potentials During Sensorim=
otor-Based Brain-Computer Interface: Explorations With a Pseudo-Online Brai=
n-Controlled Speller Michele Bevilacqua; Serafeim Perdikis; Jos=C3=A9 del R=
. Mill=C3=A1n Brain-computer interface (BCI) spelling is a promising commun=
ication solution for people in paralysis. Currently, BCIs suffer from imper=
fect decoding accuracy which calls for methods to handle spelling mistakes.=
Detecting error-related potentials (ErrPs) has been early identified as a =
potential remedy. Nevertheless, few works have studied the elicitation of E=
rrPs during engagement with other BCI tasks, especially when BCI feedback i=
s provided continuously. Methods: Here, we test the possibility of correcti=
ng errors during pseudo-online Motor Imagery (MI) BCI spelling through ErrP=
s, and investigate whether BCI feedback hinders their generation. Ten subje=
cts performed a series of MI spelling tasks with and without observing BCI =
feedback. Results: The average pseudo-online ErrP detection accuracy was fo=
und to be significantly above the chance level in both conditions and did n=
ot significantly differ between the two (74% with, and 78% without feedback=
). Conclusions: Our results support the possibility to detect ErrPs during =
MI-BCI spelling and suggest the absence of any BCI feedback-related interfe=
rence. Read more Accelerometry-Based Digital Gait Characteristics for Class=
ification of Parkinson=E2=80=99s Disease: What Counts? Rana Zia Ur Rehman; =
Christopher Buckley; Maria Encarna Mic=C3=B3-Amigo; Cameron Kirk; Michael D=
unne-Willows; Claudia Mazz=C3=A0; Jian Qing Shi; Lisa Alcock; Lynn Rocheste=
r; Silvia Del Din Gait may be a useful biomarker that can be objectively me=
asured with wearable technology to classify Parkinson=E2=80=99s disease (PD=
). This study aims to: (i) comprehensively quantify a battery of commonly u=
tilized gait digital characteristics (spatiotemporal and signal-based), and=
(ii) identify the best discriminative characteristics for the optimal clas=
sification of PD. Methods: Six partial least square discriminant analysis (=
PLS-DA) models were trained on subsets of 210 characteristics measured in 1=
42 subjects (81 people with PD, 61 controls (CL)). Results: Models accuracy=
ranged between 70.42-88.73% (AUC: 78.4-94.5%) with a sensitivity of 72.84-=
90.12% and a specificity of 60.3-86.89%. Signal-based digital gait characte=
ristics independently gave 87.32% accuracy. The most influential characteri=
stics in the classification models were related to root mean square values,=
power spectral density, step velocity and length, gait regularity and age.=
Conclusions: This study highlights the importance of signal-based gait cha=
racteristics in the development of tools to help classify PD in the early s=
tages of the disease. Read more Predicting Lymphoma Development by Exploiti=
ng Genetic Variants and Clinical Findings in a Machine Learning-Based Metho=
dology With Ensemble Classifiers in a Cohort of Sj=C3=B6gren=E2=80=99s Synd=
rome Patients Konstantina D. Kourou; Vasileios C. Pezoulas; Eleni I. Georga=
; Themis Exarchos; Costas Papaloukas; Michalis Voulgarelis; Andreas Goules;=
Andrianos Nezos; Athanasios G. Tzioufas; =CE=97aralampos M. Moutsopoulos; =
Clio Mavragani; Dimitrios I. Fotiadis Lymphoma development constitutes one =
of the most serious clinico-pathological manifestations of patients with Sj=
=C3=B6gren=E2=80=99s Syndrome (SS). Over the last decades the risk for lymp=
homagenesis in SS patients has been studied aiming to identify novel biomar=
kers and risk factors predicting lymphoma development in this patient popul=
ation. Objective: The current study aims to explore whether genetic suscept=
ibility profiles of SS patients along with known clinical, serological and =
histological risk factors enhance the accuracy of predicting lymphoma devel=
opment in this patient population. Methods: The potential predicting role o=
f both genetic variants, clinical and laboratory risk factors were investig=
ated through a Machine Learning-based (ML) framework which encapsulates ens=
emble classifiers. Results : Ensemble methods empower the classification ac=
curacy with approaches which are sensitive to minor perturbations in the tr=
aining phase. The evaluation of the proposed methodology based on a 10-fold=
stratified cross validation procedure yielded considerable results in term=
s of balanced accuracy (GB: 0.7780 =C2=B1 0.1514, RF Gini: 0.7626 =C2=B1 0.=
1787, RF Entropy: 0.7590 =C2=B1 0.1837). Conclusions: The initial clinical,=
serological, histological and genetic findings at an early diagnosis have =
been exploited in an attempt to establish predictive tools in clinical prac=
tice and further enhance our understanding towards lymphoma development in =
SS. Read more Engineered Three-Dimensional Scaffolds Modulating Fate of Bre=
ast Cancer Cells Using Stiffness and Morphology Related Cell Adhesion Samer=
ender N. Hanumantharao; Carolynn A. Que; Brennan J. Vogl; Smitha Rao Artifi=
cially engineering the tumor microenvironment in vitro as a vital tool for =
understanding the mechanism of tumor progression. In this study, we develop=
ed three-dimensional cell scaffold systems with different topographical fea=
tures and mechanical properties but similar surface chemistry. The cell beh=
avior was modulated by the topography and mechanical properties of the scaf=
fold. Methods: Adenocarcinoma (MCF7), triple-negative (MDA-MB-231) and prem=
alignant (MCF10AneoT) breast cancer cells were seeded on the scaffold syste=
ms. The cell viability, cell-cell interaction and cell-matrix interactions =
were analyzed. The preferential growth and alignment of specific population=
of cells were demonstrated. Results: Among the different scaffolds, triple=
-negative breast cancer cells preferred honeycomb scaffolds while adenocarc=
inoma cells favored mesh scaffolds and premalignant cells preferred the ali=
gned scaffolds. Conclusions: The 3D model system developed here can be used=
to support growth of only specific cell populations or for the growth of t=
umors. This model can be used for understanding the topographical and mecha=
nical features affecting tumorigenesis, cancer cell growth and migration be=
havior of malignant and metastatic cancer cells. Read more Ultrasound Based=
Planning and Navigation for Non-Anatomical Liver Resections =E2=80=93 An E=
x-Vivo Study Iwan Paolucci; Raluca-Maria Sandu; Luca Sahli; Gian Andrea Pre=
vost; Federico Storni; Daniel Candinas; Stefan Weber; Anja Lachenmayer Non-=
anatomical resections of liver tumors can be very challenging as the surgeo=
n cannot use anatomical landmarks on the liver surface or in the ultrasound=
image for guidance. This makes it difficult to achieve negative resection =
margins (R0) and still preserve as much healthy liver tissue as possible. E=
ven though image-guided surgery systems have been introduced to overcome th=
is challenge, they are still rarely used due to their inaccuracy, time-effo=
rt and complexity in usage and setup. Methods: We have developed a novel ap=
proach, which allows us to create an intra-operative resection plan using n=
avigated ultrasound. First, the surface is scanned using a navigated ultras=
ound, followed by tumor segmentation on a midsection ultrasound image. Base=
d on this information, the navigation system calculates an optimal resectio=
n strategy and displays it along with the tracked surgical instruments. In =
this study, this approach was evaluated by three experienced hepatobiliary =
surgeons on ex-vivo porcine models. Results: Using this technique, an R0 re=
section could be achieved in 22 out of 23 (95.7% R0 resection rate) cases w=
ith a median resection margin of 5.9 mm (IQR 3.5=E2=80=937.7 mm). The resec=
tion margin between operators 1, 2 and 3 was 7.8 mm, 4.15 mm and 5.1 mm res=
pectively (p =3D 0.054). Conclusions: This approach could represent a usefu=
l tool for intra-operative guidance in non-anatomical resection alongside c=
onventional ultrasound guidance. However, instructions and training are ess=
ential especially if the operator has not used an image-guidance system bef=
ore. Read more Ultrasound Stimulations Induce Prolonged Depolarization and =
Fast Action Potentials in Leech Neurons Francesca Dedola; Francesco Paolo U=
lloa Severino; Nicol=C3=B2 Meneghetti; Th=C3=A9o Lemaire; Andrea Cafarelli;=
Leonardo Ricotti; Arianna Menciassi; Annarita Cutrone; Alberto Mazzoni; Si=
lvestro Micera Ultrasound (US) stimulation carries the promise of a selecti=
ve, reversible, and non-invasive modulation of neural activity without the =
need for genetic manipulation of neural structures. However, the mechanisms=
of US-induced generation of action potentials (APs) are still unclear. Met=
hods: Here we address this issue by analyzing intracellularly recorded resp=
onses of leech nociceptive neurons to controlled delivery of US. Results: U=
S induced a depolarization linearly accumulating in time and outlasting the=
duration of the stimulation. Spiking activity was reliably induced for an =
optimal US intensity range. Moreover, we found that APs induced by US diffe=
r in smaller amplitude and faster repolarization from those induced by elec=
trical stimulation in the same cell but display the same repolarization rat=
e. Conclusions: These results shed light on the mechanism by which spikes a=
re induced by US and pave the way for designing more efficient US stimulati=
on patterns. Read more Temozolomide in Combination With NF-=CE=BAB Inhibito=
r Significantly Disrupts the Glioblastoma Multiforme Spheroid Formation Hui=
Xia; Naze G. Avci; Yasemin Akay; Yoshua Esquenazi; Lisa H. Schmitt; Nitin =
Tandon; Jay-Jiguang Zhu; Metin Akay Glioblastoma multiforme (GBM) is the mo=
st common malignant primary brain tumor, accounting for 50% of all cases. G=
BM patients have a five-year survival rate of merely 5.6% and a median over=
all survival of 14.6 months with the =E2=80=9CStupp=E2=80=9D regimen, 20.9 =
months with tumor treatment fields (TTF, OptuneR) in patients who participa=
ted in clinical trials, and 11 months for all GBM patients prior to TTF use=
. Objective: Our group recently developed a brain cancer chip which generat=
es tumor spheroids, and provides large-scale assessments on the response of=
tumor cells to various concentrations and combinations of drugs. This plat=
form could optimize the use of tumor samples derived from GBM patients to p=
rovide valuable insight on the tumor growth and responses to drug therapies=
. To minimize any sample loss in vitro, we improved our brain cancer chip s=
ystem by adding an additional laminar flow distribution layer, which reduce=
s sample loss during cell seeding and prevents spheroids from escaping from=
the microwells. Methods: In this study, we cultured 3D spheroids from GBM =
cell lines and patient-derived GBM cells in vitro, and investigated the eff=
ect of the combination of Temozolomide and nuclear factor-=CE=BAB inhibitor=
on tumor growth. Results: Our study revealed that these drugs have synergi=
stic effects in inhibiting spheroid formation when used in combination. Con=
clusions: These results suggest that the brain cancer chip enables large-sc=
ale, inexpensive and sample-effective drug screening to 3D cancer tumors in=
vitro, and could be applied to related tissue engineering drug screening s=
tudies. Read more About OJEMB IEEE Engineering in Medicine and Biology Soci=
ety | 445 Hoes Lane, Piscataway, NJ 08854 Unsubscribe ruben-at-mrbrklyn.com Up=
date Profile | About Constant Contact Sent by noreply-at-embs.org in collabora=
tion with Try email marketing for free today!
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text-align: center;" align=3D"center"> Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA4-t9R4_BgUWvYk6n_MN_kiGKL2CgMje-04hRsp8W2I=
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KYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34, =
51, 136); font-weight: bold;">OJEMB Home1, 136);"> >| /r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNO=
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iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34,=
51, 136); font-weight: bold;">Advisory Board34, 51, 136); font-size: 14px;"> | jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA=
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qG452ih9oA=3D=3D" target=3D"_blank" style=3D"color: rgb(34, 51, 136); font-=
weight: bold;">Instruction for Authors 136); font-size: 14px;"> | =3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAcq1MM=
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t: bold;">Submit an Article
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ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
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ding=3D"0" cellspacing=3D"0" border=3D"0" style=3D"border-collapse: collaps=
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10px;">
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=3D"center" valign=3D"top" style=3D"background-color: #A898C0;" bgcolor=3D"=
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e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
,Verdana,Helvetica,sans-serif; font-size: 24px; word-wrap: break-word; text=
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le=3D"font-size: 28px;">Featured Articles
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mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
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Helvetica,sans-serif; font-size: 14px; word-wrap: break-word; text-align: l=
eft; color: #36495F; padding: 10px 20px;" align=3D"left">
e: 24px; color: rgb(34, 51, 136); font-weight: bold;">Small-World Propensit=
y Reveals the Frequency Specificity of Resting State Networks
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAhwM0nCQNEgUmbML-RDv2zfU02_R1OEcZ2vmWwff4Oq=
c2ML0Lwf32ReNb-RCCUy-VlfiC-Lhs-KlKz-eHSepSkP9ckXu5uk0hJG98D6HsbSGW74z685Gl8=
Q=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Riccardo Iandolo=
: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; = Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmANN1gIze343ngAcGZK_zlzpv1QOjW1yoy4ciZsbiRfc=
-Ydo4aoum55Nm5so0i8GY0ZQD7JIpnw1ao_7riiEzAQYFqRuCz4WChw5BT4h5w3k3R_AsBbEWT0=
w=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Marianna Semprin=
in: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; >oUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA_6QoVOyG9L3DFYxgKnJeXMjpFFCZtD0GZGozDPx7L=
_fNGIEIm0Saf4Sgmux5Cairwpm-0veS4hd4Wwlt9ZwxNm42kZddcDTXqOzUbubNiFpVZZWuXtGc=
pw=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&c=
h=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D=
"_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration:=
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Stefano Buccell=
in: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; >oUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAslH_W-55e0H8Orh7SgOqJmSRUmuzGoHy8hshIk8Yp=
mcJAyVHdw9N2ze8H1rSkx3MN1pHUH5PeZGP7oQfl_CxKzT1yxJ9-ju67RSgal1fPuX4hBs1z5B4=
Eg=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&c=
h=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D=
"_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration:=
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Federico Barban=
: none; font-family: Arial, Verdana, Helvetica, sans-serif;">; =
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAvC_Y5lO_XYPg8PSVLX4jz-z-7tcBeyDyed0Wuzi4IN=
jTE4GowDMpfc-JMnlu1p4RfAgVwBocNE8kK5DKTBs0hIu_F7bygJQZ8Y_lW-c-FSCQuAfVOPFbF=
A=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(51, 51, 51); text-decoration: =
none; font-family: Arial, Verdana, Helvetica, sans-serif;">Mingqi Zhhref=3D"http://r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0=
R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAvC_Y5lO_XYPg8PSVLX4jz-z-7tcBeyDyed0Wuzi4INjTE=
4GowDMpfc-JMnlu1p4RfAgVwBocNE8kK5DKTBs0hIu_F7bygJQZ8Y_lW-c-FSCQuAfVOPFbFA=
=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">ao=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: none;">; =
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAJRWtbGkZfEO2OONyWRrwlgZ1lNMHM8J6Ci0PkoK_X1=
HE0hFfptLYgBKNbTqUFYkO58TqbK5JSFtgR4a7Ji25XB6jsuA7L0hoOi6c29YbTPJ8W2zNAZRbj=
w=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">Jessica Samogin=
">; qNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmABa-K0zqf_NfaUUSz2vIeiPPgmxMH7Jv=
SdbGSo3d14bD2ljHrzV3OsI7OFBxTPyqyc83B3FNm1mTiDB1_x5GzMSi8bh968maMYGhpwSwstW=
QavvguwZfppw=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQr=
Lg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D"=
target=3D"_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-deco=
ration: none; font-family: Arial, Verdana, Helvetica, sans-serif;">Gaia Bon=
assin: none;">; QupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAPSz79j4z705lpp73Ww2UaqO=
fcHDW6DC6-yLQTmxpMTV_R8KUe66snkxQ3qDWffHziXzSiubCgmvRxYGQkiEGNttnCVBo_7h_uE=
qFP1AsrYgyA45X4vAUOQ=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-=
zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9o=
A=3D=3D" target=3D"_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); t=
ext-decoration: none; font-family: Arial, Verdana, Helvetica, sans-serif;">=
Laura Avanzino-decoration: none;">; 2Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAOL2oGz2r4tzgK=
RipqEGMb6qKDOTnFwZ5tPmUqNif0vVUHZVGVyTzMbpjC0Jq4913FHBOfbQCSY7Kx2jSYccZD_cY=
9G30Fg5wuTW0mSfM8OVwteJpOPOYqg=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015=
eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNb=
NqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-size: 12px; color: rgb(0=
, 0, 0); text-decoration: none; font-family: Arial, Verdana, Helvetica, san=
s-serif;">Dante Mantini 0); text-decoration: none;">; f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAiwrF=
0dOT4sJ8gzgObXa0bAtNkVaNgvX_2iL5K4qCL0lRLu-Pru8c7dL-_WyIRKPJcTJ8XKzim5q8O7Y=
68BE6cUObI9eHYJR406LXk2eENcEyDFGxNsh0JQ=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0=
I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPP=
B-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-size: 12px; col=
or: rgb(0, 0, 0); text-decoration: none; font-family: Arial, Verdana, Helve=
tica, sans-serif;">Michela Chiappalone
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s=3D"galileo-ap-layout-editor" style=3D"border-collapse: collapse; mso-tabl=
e-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
th=3D"100%" style=3D"padding: 0px;">parent; width: 100%; cursor: default; border-collapse: collapse; mso-table-=
lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;" class=3D"galileo-=
ap-content-editor" bgcolor=3D"transparent">base divider-solid" style=3D"height: 1px; line-height: 1px; padding: 8px 0p=
x;" align=3D"center" valign=3D"top" width=3D"100%">
ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
background-color: #36495F;" border=3D"0" cellpadding=3D"0" cellspacing=3D"=
0" align=3D"center" bgcolor=3D"#36495F">
g-bottom: 0px; border-bottom-style: none;" align=3D"center" height=3D"1">
/1101116784221/S.gif" style=3D"display: block; height: 1px; width: 5px;" bo= rder=3D"0" height=3D"1" hspace=3D"0" vspace=3D"0" width=3D"5">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
p">
ding=3D"0" cellspacing=3D"0" border=3D"0" style=3D"border-collapse: collaps=
e; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
10px;">
![3D""]() y: block; height: auto !important; max-width: 100% !important;" width=3D"37= 6" border=3D"0" hspace=3D"0" vspace=3D"0" src=3D"https://files.constantcont= act.com/60f676b8001/2dbd1a7b-53de-41a8-b86c-a29690d149af.jpg">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
mso-table-rspace: 0pt;" class=3D"galileo-ap-layout-editor">
p">
e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
ly: Arial,Verdana,Helvetica,sans-serif; font-size: 14px; word-wrap: break-w=
ord; text-align: left; color: #36495F; padding: 10px 20px;" align=3D"left">
ize: 14px; color: rgb(0, 0, 0);">Functional connectivity (FC) is an importa=
nt indicator of the brain’s state in different conditions, such as r=
est/task or health/pathology. Here we used high-density electroencephalogra=
phy coupled to source reconstruction to assess frequency-specific changes o=
f FC during resting state. Specifically, we computed the Small-World Propen=
sity (SWP) index to characterize network small-world architecture across fr=
equencies. Methods: We collected resting state data from healthy participan=
ts and built connectivity matrices maintaining the heterogeneity of connect=
ion strengths. For a subsample of participants, we also investigated whethe=
r the SWP captured FC changes after the execution of a working memory (WM) =
task. Results: We found that SWP demonstrated a selective increase in the a=
lpha and low beta bands. Moreover, SWP was modulated by a cognitive task an=
d showed increased values in the bands entrained by the WM task. Conclusion=
s: SWP is a valid metric to characterize the frequency-specific behavior of=
resting state networks.
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e-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;">
th=3D"100%" style=3D"padding: 0px;">parent; width: 100%; cursor: default; border-collapse: collapse; mso-table-=
lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;" class=3D"galileo-=
ap-content-editor" bgcolor=3D"transparent">base divider-solid" style=3D"height: 1px; line-height: 1px; padding: 8px 0p=
x;" align=3D"center" valign=3D"top" width=3D"100%">
ollapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; table-layout: fixed;=
background-color: #36495F;" border=3D"0" cellpadding=3D"0" cellspacing=3D"=
0" align=3D"center" bgcolor=3D"#36495F">
g-bottom: 0px; border-bottom-style: none;" align=3D"center" height=3D"1">
/1101116784221/S.gif" style=3D"display: block; height: 1px; width: 5px;" bo= rder=3D"0" height=3D"1" hspace=3D"0" vspace=3D"0" width=3D"5">
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e=3D"table-layout: fixed; border-collapse: collapse; mso-table-lspace: 0pt;=
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e=3D"border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0p=
t; table-layout: fixed;">
Helvetica,sans-serif; font-size: 14px; word-wrap: break-word; text-align: l=
eft; color: #36495F; padding: 10px 20px;" align=3D"left">
e: 24px; color: rgb(34, 51, 136); font-weight: bold;">Modulating the Struct=
ure of Motor Variability for Skill Learning Through Specific Muscle Synergi=
es in Elderlies and Young Adults
Uy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmA0R3SHKoxWb_oMeu2taL6be-ateefRHg2SmmGjXLIg9=
Qly6pnXAapDRiXqSZpo_7x2i5Sk3wTALVkXPuBdVrwoUtR_V7K_2dgl3wKOjohFmELfMx3MipWJ=
g=3D=3D&c=3Dubm1sNxhg3e7y1f_koo8bfAf0I7U8W0015eVexiLKdc-zxFpwpQrLg=3D=3D&ch=
=3D9qXQ2eESZBomupswiPfgNiBT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"=
_blank" style=3D"font-size: 12px; color: rgb(0, 0, 0); text-decoration: non=
e; font-family: Arial, Verdana, Helvetica, sans-serif;">Vincent C. K. Cheun=
gl, Verdana, Helvetica, sans-serif;">; .net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKg=
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BT42c4iKYLPPB-6-IFzNbNqG452ih9oA=3D=3D" target=3D"_blank" style=3D"font-siz=
e: 12px; color: rgb(0, 0, 0); font-family: Arial, Verdana, Helvetica, sans-=
serif; text-decoration: none;">Xiao-Chang Zheng: 12px; color: rgb(0, 0, 0); font-family: Arial, Verdana, Helvetica, sans-s=
erif;">; DBQupDGByNqNktZ0_m4koUy0R_KFHyPCWUOxNOfgIZAqKgfCv_QOmAubCc_MGmJvir7OEps7wvd=
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font-family: Arial, Verdana, Helvetica, sans-serif; text-decoration: none;=
">Roy T. H. Cheungfont-family: Arial, Verdana, Helvetica, sans-serif;">; =3D"http://r20.rs6.net/tn.jsp?f=3D001v12Gxz68o4DBQupDGByNqNktZ0_m4koUy0R_KF=
HyPCWUOxNOfgIZAqKgfCv_QOmA5wOq8VSF3Pt5LIfusgS_7qpJYHC5Vi7kC9yiAXpNNKly3cS_X=
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style=3D"font-size: 12px; color: rgb(0, 0, 0); font-family: Arial, Verdana=
, Helvetica, sans-serif; text-decoration: none;">Rosa H. M. Chan
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10px;">
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t; table-layout: fixed;">
ly: Arial,Verdana,Helvetica,sans-serif; font-size: 14px; word-wrap: break-w=
ord; text-align: left; color: #36495F; padding: 10px 20px;" align=3D"left">
ize: 14px; color: rgb(0, 0, 0);">Motor variability – performance var=
iations across task repetitions – has been assumed to be undesirable=
. But recent studies argue that variability facilitates early motor learnin=
g by allowing exploratory search of reward-generating motion, and that vari=
ability’s structure may be modulated by neural circuits for furtheri=
ng learning. What are the neural sources of learning-relevant motor variabi=
lity and its modulation in humans of different ages? Methods: Elderlies and=
young adults played a 3-session virtual bowling while multi-muscle electro=
myographic signals were collected. We quantified trial-to-trial variability=
of muscle synergies – neuromotor control modules – and of th=
eir activations. Results: In elderlies, bowling-score gain correlated with =
change of activation timing variability of specific synergies, but in young=
adults, with variability changes of synergy-activation magnitude, and of t=
he synergies themselves. Conclusions: Variability modulation of specific mu=
scle synergies and their activations contribute to early motor learning. El=
derly and young individuals may rely on different aspects of motor variabil=
ity to drive learn |
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