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<span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt;">Dear all,</span><br>
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<span style="margin:0px; font-family:Calibri,Helvetica,sans-serif; font-size:12pt">Hope everyone is having a good week!</span></div>
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<span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif">Today at 2 pm, we have our last S3RI seminar before the Easter break! </span><span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif">Dr Marina Knight (University of York)
will speak to us on</span><br>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; color: black;">"</span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; color: black;"><span style="box-sizing:border-box; font-family:Calibri,Helvetica,sans-serif; font-size:12pt">Multiscale
spectral modelling for nonstationary time series within a multiple-trial experiment.</span></span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; color: black;">"</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; color: black;"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;">Please see below for the details of the talk and how to
join the seminar online. This talk will not be recorded.</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;">Hope to see you at the talk later today!</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;">Kind regards,</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 11.5pt; color: rgb(32, 31, 30); background-color: white;"><br>
</span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: black;">Jessie</span></p>
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<span style="margin: 0px; font-size: 15px; font-family: Calibri, Arial, Helvetica, sans-serif; background-color: white; color: black;"><span style="margin:0px; font-size:12pt; font-family:Calibri,Helvetica,sans-serif"><b><em><strong><span style="color: rgb(0, 0, 0); font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; background-color: rgb(255, 255, 255); display: inline !important;">Multiscale
spectral modelling for nonstationary time series within a multiple-trial experiment</span></strong></em></b></span></span></span></p>
<div style="margin: 0px; background-color: white; color: black;"><span style="margin:0px; font-size:12pt; font-family:Calibri,Helvetica,sans-serif"><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; display: inline !important;">Marina
Knight (</span><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); display: inline !important;"><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; display: inline !important;">University
of York)</span><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); display: inline !important;"><span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif"> </span></span></span></span><i><span style="margin: 0px; font-size: 12pt; background-color: white;"></span></i></div>
<div style="margin: 0px; background-color: white; color: black;"><span style="margin:0px; font-size:12pt; font-family:Calibri,Helvetica,sans-serif"><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); display: inline !important;"><span style="color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); display: inline !important;"><span><br>
</span></span></span></span></div>
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<span style="box-sizing:border-box; font-family:"Segoe UI",system-ui,"Apple Color Emoji","Segoe UI Emoji",sans-serif; font-size:12pt"></span><span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif">Within the neurosciences, it is natural to observe
variability across time in the dynamics of an underlying brain process. Wavelets are essential in analyzing brain signals because, even within a single trial, brain signals exhibit nonstationary behaviour. However, neurological signals generated within an
experiment may also potentially exhibit evolution across trials (replicates) even for identical stimuli. As neurologists consider localized spectra of brain signals to be most informative, here we propose the MULtiple-Trials Locally Stationary Wavelet (MULT-LSW)
process that directly gives a stochastic wavelet representation of the time series itself and captures the potential nonstationary behaviour both within and across trials, while accounting for between-trial correlation. Modelling within this new framework
allows us to define and rigourously develop the associated wavelet spectral estimation framework and establish its asymptotic properties, yielding a natural desired time and trial-localisation of the process dynamics. By means of thorough simulation studies,
we demonstrate the theoretical estimator properties hold in practice. A real data investigation into the evolutionary dynamics of the hippocampus and nucleus accumbens during an associative learning experiment, demonstrate the applicability of our proposed
methodology, as well as the new insights it provides.</span>
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<span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif">This is joint work with Jonathan Embleton (York) and Hernando Ombao (KAUST).</span>
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