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...
The distinguished features of cardiac artifacts in EEG recordings include characteristics specific to different types of cardiac artifacts, such as ECG artifacts, pacemaker artifacts, and pulse artifacts.
1. ECG Artifacts:
o Waveform: ECG artifacts
typically appear as poorly formed QRS complexes, with the P wave and T wave
usually not evident. The QRS complex may be diphasic or monophasic.
o Location: ECG artifacts
are often better formed and larger on the left side when using bipolar
montages, with clearer QRS waveforms over the temporal regions.
o Regular Intervals: ECG artifacts
may exhibit periodic occurrences with intervals that are multiples of a similar
time interval, aiding in their identification.
o Conservation of
Waveform: ECG
artifacts show conservation of waveform and temporal association with the QRS
complex in an ECG channel, helping differentiate them from other patterns.
2. Pacemaker
Artifacts:
o Waveform: Pacemaker artifacts
exhibit high-frequency polyphasic potentials with a shorter duration compared
to ECG artifacts.
o Distribution: These artifacts
may have a broader field of distribution across the head compared to other
types of cardiac artifacts.
o Synchronization: Simultaneous
occurrences of pacemaker artifacts with similarly appearing discharges in the
ECG channel can indicate a permanent pacemaker source.
3. Pulse Artifacts:
o Source: Pulse artifacts
result from the mechanical effects of the circulatory pulse on EEG electrodes,
leading to waveform distortions in the recorded signals.
o Appearance: Pulse artifacts
manifest as slow waves following the ECG peak, often exhibiting periodicity and
a regular interval related to the cardiac cycle.
o Location: Pulse artifacts
commonly occur over frontal and temporal regions but can be present anywhere on
the scalp.
o Alteration: Applying
pressure to the electrode producing the artifact can alter its appearance on
the EEG recording, aiding in identification.
Understanding
these distinguished features of cardiac artifacts is crucial for accurate
interpretation and differentiation of artifacts from genuine brain activity in
EEG recordings. Researchers and clinicians can use these features to identify
and mitigate the impact of cardiac artifacts on EEG data analysis and
interpretation.
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