Quantitative Biology
@BioPapers
Followers
2K
Following
0
Media
0
Statuses
22K
New Quantitative Biology submissions to https://t.co/tH1RfLBayL (not affiliated with https://t.co/tH1RfLBayL)
Worldwide
Joined April 2010
Bitbox: Behavioral Imaging Toolbox for Computational Analysis of Behavior from Videos.
arxiv.org
Computational measurement of human behavior from video has recently become feasible due to major advances in AI. These advances now enable granular and precise quantification of facial expression,...
0
0
4
How Light Shapes Memory: Beta Synchrony in the Temporal-Parietal Cortex Predicts Cognitive Ergonomics for BCI Applications.
arxiv.org
Working memory is a promising paradigm for assessing cognitive ergonomics of brain states in brain-computer interfaces(BCIs). This study decodes these states with a focus on environmental...
0
0
3
Gravity Prior and Temporal Horizon Shape Interceptive Behavior under Active Inference.
arxiv.org
Accurate interception of moving objects, such as catching a ball, requires the nervous system to overcome sensory delays, noise, and environmental dynamics. One key challenge is predicting future...
0
1
6
From Priors to Predictions: Explaining and Visualizing Human Reasoning in a Graph Neural Network Framework.
arxiv.org
Humans excel at solving novel reasoning problems from minimal exposure, guided by inductive biases, assumptions about which entities and relationships matter. Yet the computational form of these...
0
0
3
Spatial Spiking Neural Networks Enable Efficient and Robust Temporal Computation.
arxiv.org
The efficiency of modern machine intelligence depends on high accuracy with minimal computational cost. In spiking neural networks (SNNs), synaptic delays are crucial for encoding temporal...
0
2
19
Scientific Machine Learning of Chaotic Systems Discovers Governing Equations for Neural Populations.
arxiv.org
Discovering governing equations that describe complex chaotic systems remains a fundamental challenge in physics and neuroscience. Here, we introduce the PEM-UDE method, which combines the...
0
0
2
Unsupervised discovery of the shared and private geometry in multi-view data.
arxiv.org
Studying complex real-world phenomena often involves data from multiple views (e.g. sensor modalities or brain regions), each capturing different aspects of the underlying system. Within...
0
0
1
From Minutes to Days: Scaling Intracranial Speech Decoding with Supervised Pretraining.
arxiv.org
Decoding speech from brain activity has typically relied on limited neural recordings collected during short and highly controlled experiments. Here, we introduce a framework to leverage week-long...
0
0
0
The hands of time: Moving my body to keep time order in the brain.
arxiv.org
The brain is very often viewed as a network of cells, mostly neurons. Here we introduce a conjecture, in the spirit of a philosophical though experiment, which proposes that the present cannot be...
0
2
21
Dynamical Mechanisms for Coordinating Long-term Working Memory Based on the Precision of Spike-timing in Cortical Neurons.
arxiv.org
In the last century, most sensorimotor studies of cortical neurons relied on average firing rates. Rate coding is efficient for fast sensorimotor processing that occurs within a few seconds. Much...
0
2
2
Human-computer interactions predict mental health.
arxiv.org
Scalable assessments of mental illness, the leading driver of disability worldwide, remain a critical roadblock toward accessible and equitable care. Here, we show that human-computer interactions...
0
0
1
A tutorial on electrogastrography using low-cost hardware and open-source software.
arxiv.org
Electrogastrography is the recording of changes in electric potential caused by the stomach's pacemaker region, typically through several cutaneous sensors placed on the abdomen. It is a...
0
0
0
When sufficiency is insufficient: the functional information bottleneck for identifying probabilistic neural representations.
arxiv.org
The neural basis of probabilistic computations remains elusive, even amidst growing evidence that humans and other animals track their uncertainty. Recent work has proposed that probabilistic...
0
0
1
The Role of Affect and Priors in the Generation of Hallucinations in Early Psychosis.
arxiv.org
Background: Stress and negative affect play significant roles in developing psychosis. Bayesian analyses applied to the conditioned hallucinations (CH) task suggest that hallucinations arise when...
0
0
13
Forecasting Excessive Anesthesia Depth Using EEG {\alpha}-Spindle Dynamics and Machine Learning.
arxiv.org
Objectives. Accurately predicting transitions to anesthetic drugs overdosage is a critical challenge in general anesthesia as it requires the identification of EEG indicators relevant for...
0
0
0
Developmental Symmetry-Loss: A Free-Energy Perspective on Brain-Inspired Invariance Learning.
arxiv.org
We propose Symmetry-Loss, a brain-inspired algorithmic principle that enforces invariance and equivariance through a differentiable constraint derived from environmental symmetries. The framework...
0
0
6
Arbor-TVB: A Novel Multi-Scale Co-Simulation Framework with a Case Study on Neural-Level Seizure Generation and Whole-Brain Propagation.
arxiv.org
Computational neuroscience has traditionally focused on isolated scales, limiting understanding of brain function across multiple levels. While microscopic models capture biophysical details of...
0
0
1
Temporal interference stimulation for deep brain neuromodulation in humans.
arxiv.org
For decades, focal non-invasive neuromodulation of deep brain regions has not been possible because of the steep depth-focality trade-off of conventional non-invasive brain stimulation (NIBS)...
0
0
1
Forecasting Excessive Anesthesia Depth Using EEG {\alpha}-Spindle Dynamics and Machine Learning.
arxiv.org
Objectives. Accurately predicting transitions to anesthetic drugs overdosage is a critical challenge in general anesthesia as it requires the identification of EEG indicators relevant for...
0
0
0