Michael D. Nunez

Michael D. Nunez
University of Amsterdam | UVA · Department of Psychological Methods

PhD Psychology, MS Cognitive Neuroscience, MS Statistics

About

33
Publications
37,771
Reads
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367
Citations
Citations since 2016
32 Research Items
362 Citations
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Introduction
In general my research focus is on model-based Cognitive Neuroscience. That is, I develop mathematical theories and find parameter estimates of neurocognitive models that explain and predict both human behavior and observed human neural data. I am currently working on decision making and epilepsy projects using scalp and intracranial EEG respectively. More information including open-access papers and presentations at www.michaeldnunez.com
Additional affiliations
September 2017 - March 2018
University of California, Irvine
Position
  • Researcher
June 2012 - June 2017
University of California, Irvine
Position
  • PhD Student
Description
  • http://hnl.ss.uci.edu/ http://www.cidlab.com/
September 2011 - May 2012
Tulane University
Position
  • Research Assistant

Publications

Publications (33)
Article
Full-text available
Perceptual decision making can be accounted for by drift-diffusion models, a class of decision-making models that assume a stochastic accumulation of evidence on each trial. Fitting response time and accuracy to a drift-diffusion model produces evidence accumulation rate and non-decision time parameter estimates that reflect cognitive processes. Ou...
Preprint
Full-text available
Decision-making in two-alternative forced choice tasks has several underlying components including stimulus encoding, perceptual categorization, response selection, and response execution. Sequential sampling models of decision-making are based on an evidence accumulation process to a decision boundary. Animal and human studies have focused on perc...
Article
Full-text available
Encoding of a sensory stimulus is believed to be the first step in perceptual decision making. Previous research has shown that electrical signals recorded from the human brain track evidence accumulation during perceptual decision making (Gold and Shadlen, 2007; O’Connell et al., 2012; Philiastides et al., 2014). In this study we directly tested t...
Preprint
Full-text available
A popular model of decision-making suggests that in primates, including humans, decisions evolve within forebrain structures responsible for preparing voluntary actions; a concert referred to as embodied cognition. Embodied cognition posits that in decision tasks, neuronal activity generally associated with preparing an action, actually reflects th...
Article
Visual perceptual decision-making involves multiple components including visual encoding, attention, accumulation of evidence, and motor execution. Recent research suggests that EEG signals can identify the time of encoding and the onset of evidence accumulation during perceptual decision-making. Although scientists show that spatial attention impr...
Preprint
Despite advances in techniques for exploring reciprocity in brain-behavior relations, few studies focus on building neurocognitive models that describe both human EEG and behavioral modalities at the single-trial level. Here, we introduce a new integrative joint modeling framework for the simultaneous description of single-trial EEG measures and co...
Preprint
Full-text available
Human decision making behavior is observed with choice-response time data during psychological experiments. Drift-diffusion models of this data consist of a Wiener first-passage time (WFPT) distribution and are described by cognitive parameters: drift rate, boundary separation, and starting point. These estimated parameters are of interest to neuro...
Preprint
Full-text available
Visual perceptual decision-making involves multiple components including visual encoding, attention, accumulation of evidence, and motor execution. Recent research suggests that EEG oscillations can identify the time of encoding and the onset of evidence accumulation during perceptual decision-making. Although scientists show that spatial attention...
Preprint
Full-text available
We present motivation and practical steps necessary to find parameter estimates of joint models of behavior and neural electrophysiological data. This tutorial is written for researchers wishing to build joint models of human behavior and scalp and intracranial electroencephalographic (EEG) or magnetoencephalographic (MEG) data, and more specifical...
Article
Full-text available
Objective: High frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection. However, the number of HFOs per minute (i.e. the HFO "rate") is not stable over the duration of intracranial recordings; for example, the rate of HFOs increases du...
Article
Full-text available
Trained monkeys performed a two-choice perceptual decision-making task in which they reported the perceived orientation of a dynamic Glass pattern, before and after unilateral, reversible, inactivation of a brainstem area—the superior colliculus (SC)—involved in preparing eye movements. We found that unilateral SC inactivation produced significant...
Poster
Full-text available
Joint computational modeling of human EEG and behavior reveal cognition during decision making
Article
Decision-making in two-alternative forced choice tasks has several underlying components including stimulus encoding, perceptual categorization, response selection, and response execution. Sequential sampling models of decision-making are based on an evidence accumulation process to a decision boundary. Animal and human studies have focused on perc...
Article
Full-text available
Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address...
Preprint
Full-text available
Objective High frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection. However, the number of HFOs per minute (i.e. the HFO “rate”) is not stable over the duration of intracranial recordings; for example, the rate of HFOs increases duri...
Article
Full-text available
A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuin...
Preprint
Previous research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used...
Article
Previous research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used...
Poster
Full-text available
High rates of HFOs may be used to localize epileptic tissue for surgical resection. However previous research has shown that the rates of HFOs are not stable over the duration of intracranial recordings. The rate of HFOs increases during periods of slow-wave sleep, and the rate may trend up or down within each sleep stage (von Ellenrieder et al., 2...
Poster
Full-text available
A theory of decision making predicts distinct time periods that contribute to a response time (RT): visual encoding time (VET; figure-ground segregation), visual evidence accumulation (VEA), motor evidence accumulation (MEA), and motor execution time (MET). It is our goal to accurately measure these time periods within participants using EEG and hu...
Preprint
Full-text available
Objectives: Provide a biophysical framework to interpret of electrophysiological data recorded from multiple spatial scales of brain tissue. Methods: Apply the physics of conductive media to brain tissue. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography. Sources may be categ...
Preprint
Full-text available
Encoding of a sensory stimulus is believed to be the first step in perceptual decision making. Previous research has shown that electrical signals recorded from the human brain track evidence accumulation during perceptual decision making (Gold and Shadlen, 2007; O’Connell et al., 2012; Philiastides et al., 2014). In this study we directly tested t...
Preprint
Full-text available
Previous research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information-processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used...
Conference Paper
High frequency oscillations (HFOs) > 80 Hz are a promising biomarker of epileptic tissue. Recent evidence has shown that spontaneous HFOs can be recorded from the scalp, but detection of these electrographic events remains a challenge. Here, we modified a simple automatic detector, used originally for intracranial EEG (iEEG) recordings, to detect r...
Article
Full-text available
Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address...
Poster
Full-text available
Exploring methods to verify human cognitive processing times with EEG, human behavior and hierarchical Bayesian methods
Thesis
Full-text available
The cognitive process and time course of quick human decision making was evaluated using reaction time, choice distributions, and human electrophysiology as recorded by EEG. These data were used to evaluate drift-diffusion models, a class of decision-making models that assume a stochastic accumulation of evidence on each trial, within hierarchical...
Article
Full-text available
Sequential sampling decision-making models have been successful in accounting for reaction time (RT) and accuracy data in two-alternative forced choice tasks. These models have been used to describe the behavior of populations of participants, and explanatory structures have been proposed to account for between individual variability in model param...

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