This research paper presents SIMPL (Scalable Iterative Maximization of Population-coded Latents), a novel, computationally efficient algorithm designed to refine the estimation of latent variables and tuning curves from neural population activity. Latent variables in neural data represent essential low-dimensional quantities encoding behavioral or cognitive states, which neuroscientists seek to identify to understand brain computations better. Background and Motivation Traditional approaches commonly assume the observed behavioral variable as the latent neural code. However, this assumption can lead to inaccuracies because neural activity sometimes encodes internal cognitive states differing subtly from observable behavior (e.g., anticipation, mental simulation). Existing latent variable models face challenges such as high computational cost, poor scalability to large datasets, limited expressiveness of tuning models, or difficulties interpreting complex neural network-based functio...
Benign
Epileptiform Transients of Sleep (BETS) are transient EEG patterns that
commonly occur during light sleep, particularly in stages 1 and 2 of non-rapid
eye movement (NREM) sleep.
Characteristics:
o BETS are sharply
contoured, temporal region transients that are more apparent during the slow
activity of sleep compared to wakefulness.
o These transients
typically have a monophasic or diphasic waveform with an abrupt rise and
steeper fall, with the principal phase being electronegative on the scalp.
o While most BETS
have a sharp contour, some may also exhibit an after-going slow wave, although
less commonly.
2. Occurrence:
o BETS are most
commonly observed during stages 1 and 2 of NREM sleep, indicating a
relationship between these EEG patterns and specific sleep stages.
o The occurrence of
BETS during sleep suggests a physiological rather than pathological origin, as
they are considered benign and not indicative of epilepsy.
3. Localization:
o Studies using
low-resolution electromagnetic tomography (LORETA) have identified consistent
localization patterns for BETS across different patients.
o The localization
of BETS includes two components separated by a short interval, with one
component in the ipsilateral posterior insular region and the other in the
ipsilateral mesial temporal-occipital region.
4. Differentiation
from Epileptiform Activity:
o Depth electrode
recordings of BETS have demonstrated differences from interictal epileptiform
discharges (IEDs) occurring within the same recording, supporting the benign
nature of BETS.
o The consistent
localization of BETS and their distinct characteristics help differentiate them
from epileptiform activity, emphasizing their benign nature.
Overall, BETS are
transient EEG patterns that occur during sleep, particularly in NREM stages,
and exhibit specific waveform characteristics and consistent localization
patterns. Understanding the features of BETS is essential for accurate EEG
interpretation and differentiation from epileptiform activity.
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