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Dive into the research topics where Donald J. Kalar is active.

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Featured researches published by Donald J. Kalar.


Frontiers in Neuroinformatics | 2011

The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience

Russell A. Poldrack; Aniket Kittur; Donald J. Kalar; Eric N. Miller; Christian Seppa; Yolanda Gil; D. Stott Parker; Fred W. Sabb; Robert M. Bilder

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what “mental processes” exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.


Cognitive Neuropsychiatry | 2009

Cognitive ontologies for neuropsychiatric phenomics research

Robert M. Bilder; Fred W. Sabb; D. Stott Parker; Donald J. Kalar; Wesley W. Chu; Jared Fox; Nelson B. Freimer; Russell A. Poldrack

Now that genome-wide association studies (GWAS) are dominating the landscape of genetic research on neuropsychiatric syndromes, investigators are being faced with complexity on an unprecedented scale. It is now clear that phenomics, the systematic study of phenotypes on a genome-wide scale, comprises a rate-limiting step on the road to genomic discovery. To gain traction on the myriad paths leading from genomic variation to syndromal manifestations, informatics strategies must be deployed to navigate increasingly broad domains of knowledge and help researchers find the most important signals. The success of the Gene Ontology project suggests the potential benefits of developing schemata to represent higher levels of phenotypic expression. Challenges in cognitive ontology development include the lack of formal definitions of key concepts and relations among entities, the inconsistent use of terminology across investigators and time, and the fact that relations among cognitive concepts are not likely to be well represented by simple hierarchical “tree” structures. Because cognitive concept labels are labile, there is a need to represent empirical findings at the cognitive test indicator level. This level of description has greater consistency, and benefits from operational definitions of its concepts and relations to quantitative data. Considering cognitive test indicators as the foundation of cognitive ontologies carries several implications, including the likely utility of cognitive task taxonomies. The concept of cognitive “test speciation” is introduced to mark the evolution of paradigms sufficiently unique that their results cannot be “mated” productively with others in meta-analysis. Several projects have been initiated to develop cognitive ontologies at the Consortium for Neuropsychiatric Phenomics (www.phenomics.ucla.edu), in the hope that these ultimately will enable more effective collaboration, and facilitate connections of information about cognitive phenotypes to other levels of biological knowledge. Several free web applications are available already to support examination and visualisation of cognitive concepts in the literature (PubGraph, PubAtlas, PubBrain) and to aid collaborative development of cognitive ontologies (Phenowiki and the Cognitive Atlas). It is hoped that these tools will help formalise inference about cognitive concepts in behavioural and neuroimaging studies, and facilitate discovery of the genetic bases of both healthy cognition and cognitive disorders.


PLOS Computational Biology | 2012

Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping

Russell A. Poldrack; Jeanette A. Mumford; Tom Schonberg; Donald J. Kalar; Bishal Barman; Tal Yarkoni

Neuroimaging research has largely focused on the identification of associations between brain activation and specific mental functions. Here we show that data mining techniques applied to a large database of neuroimaging results can be used to identify the conceptual structure of mental functions and their mapping to brain systems. This analysis confirms many current ideas regarding the neural organization of cognition, but also provides some new insights into the roles of particular brain systems in mental function. We further show that the same methods can be used to identify the relations between mental disorders. Finally, we show that these two approaches can be combined to empirically identify novel relations between mental disorders and mental functions via their common involvement of particular brain networks. This approach has the potential to discover novel endophenotypes for neuropsychiatric disorders and to better characterize the structure of these disorders and the relations between them.


Journal of Vision | 2017

Identification of fixations in noisy eye movement data via recursive subdivision

Jeffrey B. Mulligan; Donald J. Kalar

The Problem The noise level in a modern video-based eye-tracker is usually larger than the size of the smallest saccades. Thus, it can be challenging to discriminate small eye movements from system noise. Various methods have been proposed, but most require hand-tuning of parameters to achieve good performance. We would like a method that automatically adapts to the statistics of the input signal.


Avant: Journal of the Philosophical-Interdisciplinary Vanguard | 2016

Atlas poznawczy: W stronę fundamentów wiedzy w neurokognitywistyce

Russell A. Poldrack; Aniket Kittur; Donald J. Kalar; Eric N. Miller; Christian Seppa; Yolanda Gil; Stott Parker; Fred W. Sabb; Robert M. Bilder

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what “mental processes” exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.


Topics in Cognitive Science | 2010

Towards an Ontology of Cognitive Control

Agatha Lenartowicz; Donald J. Kalar; Eliza Congdon; Russell A. Poldrack


Vision Research | 2010

A unified model of illusory and occluded contour interpolation

Donald J. Kalar; Patrick Garrigan; Thomas D. Wickens; James D. Hilger; Philip J. Kellman


national conference on artificial intelligence | 2004

A solution to the binding problem for compositional connectionism

John E. Hummel; Keith J. Holyoak; Collin Green; Leonidas A.A. Doumas; Derek Devnich; Aniket Kittur; Donald J. Kalar


national conference on artificial intelligence | 2004

Compositional Connectionism in Cognitive Science: Papers from the AAAI Fall Symposium

John E. Hummel; Keith J. Holyoak; Collin Green; Leonidas A. A. Doumas; Derek Devnich; Aniket Kittur; Donald J. Kalar


Archive | 2009

The Neuropsychology of Mental Illness: Cognitive phenomics

Robert M. Bilder; Russell A. Poldrack; D. Stott Parker; Steven P. Reise; J. David Jentsch; Tyrone D. Cannon; Edythe D. London; Fred W. Sabb; Lara Foland-Ross; Angela Rizk-Jackson; Donald J. Kalar; Nik Brown; Audrey Carstensen; Nelson B. Freimer

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Aniket Kittur

Carnegie Mellon University

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Collin Green

University of California

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Eric N. Miller

University of California

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