A5078365445- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Visual perception and processing mechanisms
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
- Motor Control and Adaptation
- Face Recognition and Perception
- Visual Attention and Saliency Detection
- Neural Networks and Applications
- Cell Image Analysis Techniques
- Neural and Behavioral Psychology Studies
- Retinal Development and Disorders
- ECG Monitoring and Analysis
- Explainable Artificial Intelligence (XAI)
- Heart Rate Variability and Autonomic Control
- Adipose Tissue and Metabolism
- Cancer Genomics and Diagnostics
- Machine Learning and Data Classification
- Viral Infections and Outbreaks Research
- Analog and Mixed-Signal Circuit Design
- Renal and related cancers
- Single-cell and spatial transcriptomics
- Extracellular vesicles in disease
- Anomaly Detection Techniques and Applications
- COVID-19 epidemiological studies
System Biosciences (United States)
2019-2020
Northwestern University
2013-2019
Shirley Ryan AbilityLab
2013-2019
University of Pennsylvania
2017
Aalto University
2011-2016
Brain (Germany)
2010
University of Helsinki
2009
In the absence of external stimuli, human hemodynamic brain activity displays slow intrinsic variations. To find out whether such fluctuations would be altered by persistent pain, we asked 10 patients with unrelenting chronic pain different etiologies and sex- age-matched control subjects to rest eyes open during 3-T functional MRI. Independent component analysis was used identify functionally coupled networks. Time courses an independent comprising insular cortices both hemispheres showed...
How to move efficiently is an optimal control problem, whose computational complexity grows exponentially with the horizon of planned trajectory. Breaking a compound movement into series chunks, each over shorter can thus reduce overall and associated costs while limiting achievable efficiency. This trade-off suggests cost-effective learning strategy: learn new movements we should start many short chunks (to limit cost computation). As practice reduces impediments more complex computation,...
Rewards associated with actions are critical for motivation and learning about the consequences of one's on world. The motor cortices involved in planning executing movements, but it is unclear whether they encode reward over above limb kinematics dynamics. Here, we report a categorical signal dorsal premotor (PMd) primary (M1) neurons that corresponds to an increase firing rates when trial was not rewarded regardless or expected. We show this unrelated error magnitude, prediction error,...
Current knowledge about the precise timing of visual input to cortex relies largely on spike timings in monkeys and evoked-response latencies humans. However, quantifying activation onset does not unambiguously describe stimulus-feature-specific information processing. Here, we investigated content early human cortical activity by decoding low-level features from single-trial magnetoencephalographic (MEG) responses. MEG was measured nine healthy subjects as they viewed annular sinusoidal...
Neuroscience has long focused on finding encoding models that effectively ask "what predicts neural spiking?" and generalized linear (GLMs) are a typical approach. It is often unknown how much of explainable activity captured, or missed, when fitting model. Here we compared the predictive performance simple to three leading machine learning methods: feedforward networks, gradient boosted trees (using XGBoost), stacked ensembles combine predictions several methods. We predicted spike counts...
Our bodies and the environment constrain our movements. For example, when arm is fully outstretched, we cannot extend it further. More generally, distribution of possible movements conditioned on state in environment, which constantly changing. However, little known about how brain represents such distributions, uses them movement planning. Here, record from dorsal premotor cortex (PMd) primary motor (M1) while monkeys reach to randomly placed targets. The hand's position within workspace...
When a saccade is expected to result in reward, both neural activity oculomotor areas and the itself (e.g., its vigor latency) are altered (compared with when no reward expected). As such, it unclear whether correlations of indicate representation beyond movement representation; modulated may simply represent differences motor output due reward. Here, distinguish between these possibilities, we trained monkeys perform natural scene search task while recorded from frontal eye field (FEF)....
Every movement we make represents one of many possible actions. In reaching tasks with multiple targets, dorsal premotor cortex (PMd) appears to represent all actions simultaneously. However, in situations are not presented explicit choices. Instead, must estimate the best action based on noisy information and execute it while still uncertain our choice. Here asked how both primary motor (M1) PMd represented reach direction during a task which monkey made reaches noisy, target information....
Abstract Independent component analysis (ICA) of electroencephalographic (EEG) and magnetoencephalographic (MEG) data is usually performed over the temporal dimension: each channel one row matrix, a linear transformation maximizing independence time courses sought. In functional magnetic resonance imaging (fMRI), by contrast, most studies use spatial ICA: point constitutes patterns maximized. Here, we show utility ICA in characterizing oscillatory neuromagnetic signals. We project sensor...
When we search for visual objects, the features of those objects bias our attention across landscape (feature-based attention). The brain uses these top-down cues to select eye movement targets (spatial selection). frontal field (FEF) is a prefrontal region implicated in selecting movements and thought reflect feature-based spatial selection. Here, study how FEF facilitates selection complex natural scenes. We ask whether neurons facilitate by representing search-relevant or they are...
In this paper, we explore visually evoked potentials (VEPs) as a potential tool for biometric identification. Using clinical stimulation paradigm, single channel pattern onset VEPs are recorded from raw EEG 10 healthy male subjects aged between 20 and 24. Following this, two feature extraction techniques employed to characterize the signals. Specifically, novel, physiologically relevant peak matching algorithm is proposed its performance compared features obtained multi-resolution wavelet...
Independent component analysis (ICA) is increasingly used to analyze patterns of spontanous activity in brain imaging. However, there are hardly any methods for answering the fundamental question: Are obtained components statistically significant? Most considering significance either consider group-differences or use arbitrary thresholds with weak statistical justification. In previous work, we proposed a principled method testing if coefficients mixing matrix similar different subjects...
Abstract Neuroscience has long focused on finding encoding models that effectively ask “what predicts neural spiking?” and generalized linear (GLMs) are a typical approach. It is often unknown how much of explainable activity captured, or missed, when fitting GLM. Here we compared the predictive performance GLMs to three leading machine learning methods: feedforward networks, gradient boosted trees (using XGBoost), stacked ensembles combine predictions several methods. We predicted spike...
Generalized linear models (GLMs) are well-established tools for regression and classification widely applied across the sciences, economics, business, finance.Owing to their convex loss, they easy efficient fit.Moreover, relatively interpret because of well-defined noise distributions point-wise nonlinearities.
Abstract Our bodies and the environment constrain our movements. For example, when arm is fully outstretched, we cannot extend it further. More generally, distribution of possible movements conditioned on state in environment, which constantly changing. However, little known about how brain represents such distributions, uses them movement planning. Here, recorded from dorsal premotor cortex (PMd) primary motor (M1) while monkeys reached to randomly placed targets. The hand’s position within...
Abstract Cerebral organoids provide unparalleled access to human brain development in vitro. However, variability induced by current culture methodologies precludes using as robust disease models. To address this, we developed an automated Organoid Culture and Assay (ORCA) system support longitudinal unbiased phenotyping of at scale across multiple patient lines. We then characterized organoid novel machine learning methods found that the contribution donor, clone, batch is significant...
Abstract Neurons are often probed by presenting a set of stimuli that vary along one dimension (e.g. color) and quantifying how this stimulus property affect neural activity. An open question, in particular where higher-level areas involved, is much tuning measured with reveals about to new set. Here we ask question estimating hue macaque V4 from natural scenes simple color stimuli. We found was strong each dataset but not correlated across the datasets, finding expected if neurons have...
ABSTRACT Demultiplexing methods have facilitated the widespread use of single-cell RNA sequencing (scRNAseq) experiments by lowering costs and reducing technical variations. Here, we present demuxalot : a method for probabilistic genotype inference from aligned reads, with no assumptions about allele ratios efficient incorporation prior information historical in multi-batch setting. Our efficiently incorporates additional across reads originating same transcript, enabling up to 3x more calls...
Like humans, monkeys make saccades nearly three times a second. To understand the factors guiding this frequent decision, computational models of vision attempt to predict fixation locations using bottom-up visual features and top-down goals. How do relative influences these evolve over multiple time scales? Here we analyzed at fixations retinal transform that provides realistic acuity by suitably degrading information in periphery. In task which searched for Gabor target natural scenes,...