Joaquín Rapela, Dmitrii
Torodov (accepted). Hidden Markov models applied to LFPs from layer two and
three of human
cortex reveal highly stereotypical discrete states in epileptic seizures
separated by more than an hour. 2019 41st Annual International Conference of
the IEEE Engineering in Medicine and Biology
Society (EMBC), Berlin.Main article and supplementary information.
We characterized microelectrode arrray recordings from cortical layers two and
three of a person with epilepsy using a hidden Markov model with an
autoregressive observation model. In agreement with previous studies, we found
that seizure activity is highly stereotypical across different seizures
separated by more than one hour from each other, and showed that seizures
evolve as sequences of long-duration discrete states. Beyond previous
studies, we showed that this stereotypicality and discreteness is evident
outside seizures, in pre- and post-ictal periods.
Joaquín Rapela, Timothee
Proix, Dmitrii Torodov, Wilson Truccolo (accepted for oral presentation).
structure in high-dimensional representations of
long-term recordings in people with epilepsy.
Proceeding of the 2019
41st Annual International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBC), Berlin.
free reprint ,
We investigated low-dimensional structure of high-dimensional representations
of micro-electrode array recordings from a person with epilepsy. We found that
t-distributed stochastic neighbor embedding (t-SNE) finds two-dimensional
descriptors of very high-dimensonal representation of epileptic recordings,
which separates well inter-ictal, pre-ictal, ictal and post-ictal periods. We
used XGBoost to build a parametric version of t-SNE, allowing to find
low-dimensional descriptors in very long-duration recordings, typical of
epilepsy. We used a novel clustering algorithm (Rodriguez and Laio 2014) to
automatically discover structure in t-SNE low-dimensional descriptors and
introduced a procedure to find this structure in very long-duration recordings.
Joaquín Rapela, Marissa Westerfield, Jeanne Townsend
(2018a). A new foreperiod effect on single-trial phase coherence. Part I:
existence and relevance. Neural Computation 30(9): 2348-83. Main article, and supplementary information.
This article contains scientific and methodological innovations.
Scientifically, we discovered a new effect of the elapsed time between the
presentation of a warning signal and the presentation of subsequent standard
stimuli (stimuli to which subjects did not respond) on the coherence of the
phase evoked by these standards. Methodolgically, we were able to detect this
effect thanks to a single-trial analysis of the electroencephalogram using
variational Bayes linear regression.
Timothée Proix, Dmitrii Todorov, Wilson Truccolo (2018b).
Uncovering the low-dimensional structure of high-dimensional
electrophysiological recordings in epilepsy.
SfN abstract SfN poster.
We are studying the hypothesis that epileptic activity (as recorded by
high-density multi-electrode arrays in humans) can be efficiently represented
in a low-dimensional space. We are using different low-dimensional
representation methods (e.g., t-distributed stochastic neighbor embedding,
hidden markov models, principal component analysis). To quantify the quality of
these low-dimensional representations, we are comparing how well we
can predict the occurence of seizures based on them.
Joaquín Rapela (2018).
Traveling waves appear and disappear in unison with produced speech
Here we show that the traveling waves reported in Rapela 2016, 2017 do not
occur continuously, but tend to appear before the initiation of a
consonant-vowel syllable, tend to disappear before their termination, and
during moments of silence, between productions of CVSs, TWs tend to reverse
Joaquín Rapela (2017).
Rhythmic production of consonant-vowel syllables synchronizes traveling waves in speech-processing brain regions
Nature is abundant in oscillatory activity, with oscillators that have the
remarkable ability of synchronizing to external events. Using
electrocorticographic (ECoG) recordings from a subject rhythmically producing
consonant-vowel syllables (CVSs) we show that traveling waves over speech
processing brain regions become precisely synchronized (in dynamical systems
terms) to initiations of the production of CVSs. We use synchronization
patterns to identify an extended traveling waves in voltages (filtered around
the median frequency of speech production) moving from primary auditory to
primary motor cortex, and a traveling waves in coupled high-gamma power moving
along the same trajectory but in opposite direction.
Joaquín Rapela (2016).
Entrainment of traveling waves to rhythmic motor acts.
Here I characterize high-density ECoG recordings from a patient producing
consonant-vowel syllables (recordings from Bouchard et al., 2013).
I show strong effects of the production of consonant-vowel syllables on the
phase of low-frequency neural oscillation (phase alignment,
phase-amplitude-coupling and traveling waves). To my knowledge, this is the
first report of motor actions organizing (a) the phase coherence of
low-frequency brain oscillations, (b) the coupling between the phase of these
oscillations and the amplitude of high-frequency oscillations, and (c)
traveling waves. It is also the first demonstration that traveling waves induce
an organization of phase-amplitude coupling so that spiking across different
spatial locations is synchronized to behaviorally relevant times.
Joaquín Rapela, Peter F. Rowat, Tim Mullen, Edward F.
Chang, Kristofer Bouchard (2015). Modeling neural
activity at the ensemble level. arXiv:1505.00041 [q-bio.NC]
Here we demonstrate that the activity of neural ensembles can be quantitatively
modeled using an ensemble dynamical model of the probability density function
that a neuron in the ensemble will fire at a given time (Omurtag
et al., 2000).
For populations of Integrate and Fire neurons, we validate that the probability
density function resulting from the integration of the previous model precisely
agrees with large-scale simulation of interacting single neurons. The previous
ensemble dynamical models is a high-dimensional system of nonlinear
differential equations. To facilitate the estimation of its parameters from
neural recordings we implemented a dimensionality reduction method (Knight,
We developed a maximum-likelihood method to infer the value of model parameters
from data. Finally, we showed that the ensemble dynamical model and the method
to estimate its parameters accurately approximate the high-gamma power evoked
by pure tones in the auditory cortex of rodents.
Joaquín Rapela, Klaus
Gramann, Marissa Westerfield, Jeanne Townsend, and Scott Makeig (2012a). Brain
oscillations in Switching vs. Focusing audio-visual attention. Proceedings of
the 34th Annual International Conference of the IEEE EMBS, San Diego,
reprint, IEEE version
We performed audio-visual attention-shift EEG experiments, where subjects
had to quickly and repeatedly switch their attention between the visual and
the auditory modalities (SWITCH blocks), or steadily fix their attention on
a single modality (FOCUS blocks). Using a novel experimental design we
studied oscillatory attention-related activity generated by
attention-shifting cues, by stimuli following these cues, and interactions
between them. We observed that the amount of oscillatory attention-related
activity generated by the first visual stimuli after a cue was larger in
SWITCH that in FOCUS blocks, and that the enhanced activity in SWITCH
blocks decayed progressively for stimuli following the first one. The
results from this study suggest that cross-modal switches of attention may
generate a transient attentional arousal in all the modalities involved in
multimodal attention experiments.
Joaquín Rapela, Tsong-Yan Lin, Marissa Westerfield,
Tzyy-Ping Jung, and Jeanne Townsend (2012b). Assisting autistic children with wireless
EOG technology. Proceedings of the 34th Annual International Conference
of the IEEE EMBS, San Diego, California. free copy, IEEE version
We proposed a novel intervention to train the speed and accuracy of
attention orienting and eye movements in Autism Spectrum Disorder
(ASD). Training eye movements and attention could not only affect
those important functions directly, but could also result in broader
improvement of social communication skills. To this end we described a
system that would allow ASD children to improve their fixation skills while
playing a computer game controlled by an eye tracker. Because this intervention
will probably be time consuming, this system should be designed to be used at
homes. To make this possible, we proposed an implementation based on
wireless and dry electrooculography (EOG) technology. If successful, this
system would develop an approach to therapy that would improve clinical
and behavioral function in children and adults with ASD. As our initial
steps in this direction, we described the design of a computer game to be
used in this system, and the predictions of gaze position from EOG data
recorded while a subject played this game.
Joaquín Rapela, Gidon Felsen, Jon Touryan, Jerry M. Mendel, and Norberto M. Grzywacz (2010).
ePPR: a very general linear-nonlinear model for the spatio-temporal characterization of visual cells from natural images. Network: Computation in Neural Systems. 21(1-2): 35-90
We developed the extended Projection Pursuit Regression (ePPR) algorithm that,
by using an efficient projection pursuit estimation algorithm, allows to
estimate a very general linearn-nonlinear model of visual cells using
arbitrary, including natural, stimuli. We showed that ePPR compares favorably
to spike-triggered and information-theoretic techniques.
Joaquín Rapela, Jerry M. Mendel, and Norberto M. Grzywacz (2006). Estimating nonlinear receptive fields from natural images. Journal of Vision 6(4): 441-474.
We introduced the Volterra Relevant Space Technique to estimate spatial
Volterra models of visual cells from their responses to natural stimuli.
David W. Shattuck, Joaquín Rapela, Evren Asma, Arion X.
Chatzioannou, Jinyi Qi, and Richard M. Leahy (2002). Internet2-based 3D PET image reconstruction using
a PC cluster. Physics in Medicine and Biology 47: 2785-2795.
We built a system for 3D PET image reconstructions using a statistically
optimal maximum a posteriori (MAP) reconstruction algorithm. To speed up the
reconstruction process we implemented a pararellized version of the
reconstruction algorithm, and run the reconstructions on a cluster of personal
computers. To allow scanning facilities remotely access our reconstruction
system, we developed a Java interace to the cluster that only requires a
standard Web browser to run 3D PET image reconstructions.
Joaquín Rapela (2001). Automatically combining ranking heuristics for
HTML documents. Proceedings of the third international workshop on Web
information and data management. ACM Press, NY, USA: 61-67.
I constructed a technique that learned from a training collection of HTML
documents the optimal way to combine several HTML ranking heuristics into a
single similarity measure for HTML documents.