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Estimados MIembros CMM-DIM, <br>
<br>
Se les invita a la conferencia <span style="font-family:
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class=""><span class="">EEG, este viernes 14 abril, a las 12pm.<br>
<br>
</span></span>
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font-size: 16px; outline: currentcolor none medium;" class=""><b>Title:</b></div>
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font-family: "Helvetica Neue", Helvetica, Arial,
sans-serif; font-size: 16px; outline: none;" class="">Recovering
Arrhythmic EEG Transients from Their Stochastic Interference</div>
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font-family: "Helvetica Neue", Helvetica, Arial,
sans-serif; font-size: 16px; outline: none;" class=""><b>Conferencista:</b>
Juan Carlos Letelier, Facultad de Ciencias, Universidad de
Chile</div>
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sans-serif; font-size: 16px; outline: none;" class=""> </div>
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sans-serif; font-size: 16px; outline: none;" class=""><b>Date
& Time:</b> Friday, April 14, 12pm</div>
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sans-serif; font-size: 16px; outline: none;" class=""><b>Venue:</b>
Room B06, Beauchef 851, Escuela de Ingeniería, Universidad de
Chile</div>
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modality, zoom link: </div>
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font-family: "Helvetica Neue", Helvetica, Arial,
sans-serif; font-size: 16px; outline: none;" class=""><a
rel="nofollow noopener noreferrer"
href="https://uchile.zoom.us/j/98591910073?pwd=Qk1MQnVDU2RtRjhQcmhXT3o2NXIxZz09"
target="_blank" style="color: rgb(25, 106, 212); outline:
none;" class="moz-txt-link-freetext">https://uchile.zoom.us/j/98591910073?pwd=Qk1MQnVDU2RtRjhQcmhXT3o2NXIxZz09</a></div>
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<div dir="ltr" style="outline: none;" class="">Organized by
the Millennium Institute of Intelligent Healthcare (iHealth)</div>
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font-size: 16px; outline: currentcolor none medium;" class=""><b>Abstract</b></div>
<div style="font-style: normal; font-variant-caps: normal;
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font-family: "Helvetica Neue", Helvetica, Arial,
sans-serif; font-size: 16px; outline: none;" class="">Traditionally,
the neuronal dynamics underlying electroencephalograms (EEG)
have been understood as arising from rhythmic oscillators with
varying degrees of synchronization. This dominant metaphor
employs frequency domain EEG analysis to identify the most
prominent populations of neuronal current sources in terms of
their frequency and spectral power. However, emerging
perspectives on EEG highlight its arrhythmic nature, which is
primarily inferred from broadband EEG properties like the
ubiquitous 1/f spectrum. In the present study, we use an
arrhythmic superposition of pulses as a metaphor to explain
the origin of EEG. This conceptualization has a fundamental
problem because the interference produced by the
superpositions of pulses generates colored Gaussian noise,
masking the temporal profile of the generating pulse. We
solved this problem by developing a mathematical method
involving the derivative of the autocovariance function to
recover excellent approximations of the underlying pulses,
significantly extending the analysis of this type of
stochastic processes. When the method is applied to
spontaneous mouse EEG sampled at 5 kHz during the sleep-wake
cycle, specific patterns --- called PSI-patterns ---
characterizing NREM sleep, REM sleep, and wakefulness are
revealed. Psi-patterns can be understood theoretically as
power density in the time domain and correspond to
combinations of generating pulses at different time scales.
Remarkably, we report the first EEG wakefulness-specific
feature, which corresponds to an ultra-fast (1 ms) transient
component of the observed patterns. By shifting the paradigm
of EEG genesis from oscillators to random pulse generators,
our theoretical framework pushes the boundaries of traditional
Fourier-based EEG analysis, paving the way for new insights
into the arrhythmic components of neural dynamics.<br>
<br>
Esperando contar con su participación, les saluda, <br>
<br>
Ma. Inés Rivera <br>
<br>
<br>
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