The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Ali Yousefi - One of the best experts on this subject based on the ideXlab platform.
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Compass an open source general purpose software toolkit for computational psychiatry
Frontiers in Neuroscience, 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and few of toolboxes and analytical platforms are capable of processing these categories of signals. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package, to be easy to use and capable of integrating signals with a variety of distributions. Compass has tools to process signals with continuous-valued and binary measurements or signals with incomplete - missing or censored - measurements, which makes it well suited for processing signals captured during psychophysical tasks After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. We also demonstrate Compass application in a censored-data problem and compare its performance result with naive estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry
Frontiers Media S.A., 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience
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Data_Sheet_2_Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry.docx
2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass an open source general purpose software toolkit for computational psychiatry
bioRxiv, 2018Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced programming skills. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit of a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data, and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
Alik S Widge - One of the best experts on this subject based on the ideXlab platform.
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Compass an open source general purpose software toolkit for computational psychiatry
Frontiers in Neuroscience, 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and few of toolboxes and analytical platforms are capable of processing these categories of signals. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package, to be easy to use and capable of integrating signals with a variety of distributions. Compass has tools to process signals with continuous-valued and binary measurements or signals with incomplete - missing or censored - measurements, which makes it well suited for processing signals captured during psychophysical tasks After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. We also demonstrate Compass application in a censored-data problem and compare its performance result with naive estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry
Frontiers Media S.A., 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience
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Data_Sheet_2_Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry.docx
2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass an open source general purpose software toolkit for computational psychiatry
bioRxiv, 2018Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced programming skills. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit of a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data, and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
Anne Louise Oaklander - One of the best experts on this subject based on the ideXlab platform.
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validation of the composite autonomic symptom scale 31 Compass 31 in patients with and without small fiber polyneuropathy
European Journal of Neurology, 2015Co-Authors: Roi Treister, Kate Oneil, Heather M Downs, Anne Louise OaklanderAbstract:Background and purpose The recently developed composite autonomic symptom score 31 (Compass-31) is a questionnaire that assess symptoms of dysautonomia. It was distilled from the well-established Autonomic Symptom Profile questionnaire. Compass-31 has not yet been externally validated. To do so, its psychometric properties and convergent validity in patients with and without objective diagnosis of small fiber polyneuropathy (SFPN) were assessed. Methods Internal validity and reliability of Compass-31 were assessed in participants with or without SFPN spanning the full range of severity of autonomic symptoms. Convergent validity was assessed by comparing results of the Compass-31 with the “gold standard” autonomic function testing that measures cardiovagal, adrenergic and sudomotor functions. Additionally, relationships between Compass-31 and the Short Form McGill Pain Questionnaire, Short Form Health Survey and 0–10 numeric pain scale were measured. Compass-31 and all other questionnaire results were compared between patients with or without evidence of SFPN, objectively confirmed by distal-leg PGP9.5-immunolabeled skin biopsy. Results Amongst 66 participants (28 SFPN+, 38 SFPN−), Compass-31 total scores had excellent internal validity (Cronbach's α = 0.919), test–retest reliability (rs = 0.886; P < 0.001) and good convergent validity (rs = 0.474; P < 0.001). Compass-31 scores differed between subjects with or without SFPN (Z = −3.296, P < 0.001) and demonstrated fair diagnostic accuracy. Area under the Receiver Operating Characteristic curve was 0.749 (P = 0.01, 95% confidence interval 0.627–0.871). Conclusions Compass-31 has good psychometric properties in the population of patients being evaluated for SFPN and thus it might be useful as an initial screening tool for the more expensive SFPN objective tests.
John B. Phillips - One of the best experts on this subject based on the ideXlab platform.
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Use of a light-dependent magnetic Compass for y-axis orientation in European common frog (Rana temporaria) tadpoles
Journal of Comparative Physiology A, 2013Co-Authors: Francisco Javier Diego-rasilla, Rosa M Luengo, John B. PhillipsAbstract:We provide evidence for the use of a magnetic Compass for y -axis orientation (i.e., orientation along the shore-deep water axis) by tadpoles of the European common frog ( Rana temporaria ). Furthermore, our study provides evidence for a wavelength-dependent effect of light on magnetic Compass orientation in amphibians. Tadpoles trained and then tested under full-spectrum light displayed magnetic Compass orientation that coincided with the trained shore-deep water axes of their training tanks. Conversely, tadpoles trained under long-wavelength (≥500 nm) light and tested under full-spectrum light, and tadpoles trained under full-spectrum light and tested under long-wavelength (≥500 nm) light, exhibited a 90° shift in magnetic Compass orientation relative to the trained y -axis direction. Our results are consistent with earlier studies showing that the observed 90° shift in the direction of magnetic Compass orientation under long-wavelength (≥500 nm) light is due to a direct effect of light on the underlying magnetoreception mechanism. These findings also show that wavelength-dependent effects of light do not compromise the function of the magnetic Compass under a wide range of natural lighting conditions, presumably due to a large asymmetry in the relatively sensitivity of antagonistic short- and long-wavelength inputs to the light-dependent magnetic Compass.
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Light-dependent magnetic Compass in Iberian green frog tadpoles
Naturwissenschaften, 2010Co-Authors: Francisco Javier Diego-rasilla, Rosa Milagros Luengo, John B. PhillipsAbstract:Here, we provide evidence for a wavelength-dependent effect of light on magnetic Compass orientation in Pelophylax perezi (order Anura), similar to that observed in Rana catesbeiana (order Anura) and Notophthalmus viridescens (order Urodela), and confirm for the first time in an anuran amphibian that a 90° shift in the direction of magnetic Compass orientation under long-wavelength light (≥500 nm) is due to a direct effect of light on the underlying magnetoreception mechanism. Although magnetic Compass orientation in other animals (e.g., birds and some insects) has been shown to be influenced by the wavelength and/or intensity of light, these two amphibian orders are the only taxa for which there is direct evidence that the magnetic Compass is light-dependent. The remarkable similarities in the light-dependent magnetic Compasses of anurans and urodeles, which have evolved as separate clades for at least 250 million years, suggest that the light-dependent magnetoreception mechanism is likely to have evolved in the common ancestor of the Lissamphibia (Early Permian, ~294 million years) and, possibly, much earlier. Also, we discuss a number of similarities between the functional properties of the light-dependent magnetic Compass in amphibians and blue light-dependent responses to magnetic stimuli in Drosophila melanogaster , which suggest that the wavelength-dependent 90° shift in amphibians may be due to light activation of different redox forms of a cryptochrome photopigment. Finally, we relate these findings to earlier studies showing that the pineal organ of newts is the site of the light-dependent magnetic Compass and recent neurophysiological evidence showing magnetic field sensitivity in the frog frontal organ (an outgrowth of the pineal).
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calibration of magnetic and celestial Compass cues in migratory birds a review of cue conflict experiments
The Journal of Experimental Biology, 2006Co-Authors: Rachel Muheim, Frank R Moore, John B. PhillipsAbstract:Migratory birds use multiple sources of Compass information for orientation, including the geomagnetic field, the sun, skylight polarization patterns and star patterns. In this paper we review the results of cue-conflict experiments designed to determine the relative importance of the different Compass mechanisms, and how directional information from these Compass mechanisms is integrated. We focus on cue-conflict experiments in which the magnetic field was shifted in alignment relative to natural celestial cues. Consistent with the conclusions of earlier authors, our analyses suggest that during the premigratory season, celestial information is given the greatest salience and used to recalibrate the magnetic Compass by both juvenile and adult birds. Sunset polarized light patterns from the region of the sky near the horizon appear to provide the calibration reference for the magnetic Compass. In contrast, during migration, a majority of experiments suggest that birds rely on the magnetic field as the primary source of Compass information and use it to calibrate celestial Compass cues, i.e. the relative saliency of magnetic and celestial cues is reversed. An alternative possibility, however, is suggested by several experiments in which birds exposed to a cue conflict during migration appear to have recalibrated the magnetic Compass, i.e. their response is similar to that of birds exposed to cue conflicts during the premigratory season. The general pattern to emerge from these analyses is that birds exposed to the cue conflict with a view of the entire sunset sky tended to recalibrate the magnetic Compass, regardless of whether the cue conflict occurred during the premigratory or migratory period. In contrast, birds exposed to the cue conflict in orientation funnels and registration cages that restricted their view of the region of sky near the horizon (as was generally the case in experiments carried out during the migratory season) did not recalibrate the magnetic Compass but, instead, used the magnetic Compass to calibrate the other celestial Compass systems. If access to critical celestial cues, rather than the timing of exposure to the cue conflict (i.e. premigratory vs migratory), determines whether recalibration of the magnetic Compass occurs, this suggests that under natural conditions there may be a single calibration reference for all of the Compass systems of migratory birds that is derived from sunset (and possibly also sunrise) polarized light cues from the region of sky near the horizon. In cue-conflict experiments carried out during the migratory season, there was also an interesting asymmetry in the birds' response to magnetic fields shifted clockwise and counterclockwise relative to celestial cues. We discuss two possible explanations for these differences: (1) lateral asymmetry in the role of the right and left eye in mediating light-dependent magnetic Compass orientation and (2) interference from the spectral and intensity distribution of skylight at sunset with the response of the light-dependent magnetic Compass.
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magnetic Compass mediates nocturnal homing by the alpine newt triturus alpestris
Behavioral Ecology and Sociobiology, 2005Co-Authors: Francisco Javier Diegorasilla, Rosa M Luengo, John B. PhillipsAbstract:Experiments were carried out to investigate the use of magnetic Compass cues in the nocturnal homing ori- entation of the alpine newt Triturus alpestris. Tests were carried out at a site 9 km to the east-northeast of the breed- ing pond. Newts were tested at night in an outdoor circular arena that provided an unimpeded view of celestial cues, in one of four symmetrical alignments of an earth-strength magnetic field. In tests carried out under partly cloudy skies newts exhibited homeward magnetic Compass orientation. Because the moon was visible in some trials, but obscured by clouds in others, we investigated whether the presence of the moon contributed to the scatter in the distribution of magnetic bearings. When the moon was visible, the distri- bution of magnetic bearings was more scattered than when the moon was obscured by clouds, although in neither case was the distribution significant due, in part, to the small sample sizes. Moreover, when the moon was visible, newts oriented along a bimodal axis perpendicular to the moon azimuth, suggesting that the presence of the moon may have affected the newts behavior. To provide a more rigorous test of the role of magnetic Compass cues when celestial cues were unavailable, nocturnal tests were carried out during the following migratory season under total overcast. In the absence of celestial Compass cues, the distribution of mag- netic bearings exhibited highly significant orientation in the homeward direction. These findings indicate that newts are able to orient in the homeward direction at night using the magnetic Compass as the sole source of directional infor- mation. Moon light altered the newts' behavior. However, this apparently resulted from the asymmetrical distribution of moon light in the testing arena, rather than the use of an alternative Compass.
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use of a specialized magnetoreception system for homing by the eastern red spotted newt notophthalmus viridescens
The Journal of Experimental Biology, 1994Co-Authors: John B. Phillips, S C BorlandAbstract:Laboratory experiments were carried out to investigate the effects of varying the wavelength of light on the use of an earth-strength magnetic field for shoreward orientation and for the Compass component of homing. In the earlier shoreward orientation experiments, newts tested under full-spectrum and short-wavelength (i.e. 400 and 450 nm) light exhibited shoreward magnetic Compass orientation. Under long-wavelength (i.e. 550 and 600 nm) light, newts exhibited magnetic Compass orientation that was rotated 90 d counterclockwise to the shoreward direction. This wavelength-dependent shift in magnetic Compass orientation was shown to be due to a direct effect of light on the underlying magnetoreception mechanism. In homing experiments, newts tested under full-spectrum and short-wavelength light exhibited homeward magnetic Compass orientation. Under long-wavelength light, newts were randomly distributed with respect to the magnetic field. The different effects of long-wavelength light on shoreward orientation and homing confirmed earlier evidence that different magnetoreception systems mediate these two forms of orientation behaviour. The properties of the newt9s homing response are consistent with the use of a hybrid magnetoreception system receiving inputs from the light-dependent magnetic Compass and from a non-light-dependent intensity (or inclination) detector which, unlike the Compass, is sensitive to the polarity of the magnetic field.
Darin D Dougherty - One of the best experts on this subject based on the ideXlab platform.
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Compass an open source general purpose software toolkit for computational psychiatry
Frontiers in Neuroscience, 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and few of toolboxes and analytical platforms are capable of processing these categories of signals. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package, to be easy to use and capable of integrating signals with a variety of distributions. Compass has tools to process signals with continuous-valued and binary measurements or signals with incomplete - missing or censored - measurements, which makes it well suited for processing signals captured during psychophysical tasks After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. We also demonstrate Compass application in a censored-data problem and compare its performance result with naive estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry
Frontiers Media S.A., 2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience
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Data_Sheet_2_Compass: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry.docx
2019Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Jonathan L Mirsky, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. Compass has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, Compass allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that Compass can replicate two computational behavioral analyses from different groups. Compass replicates and can slightly improve on the original modeling results. We also demonstrate the use of Compass application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
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Compass an open source general purpose software toolkit for computational psychiatry
bioRxiv, 2018Co-Authors: Ali Yousefi, Angelique C Paulk, Ishita Basu, Darin D Dougherty, Emad N Eskandar, Uri T Eden, Alik S WidgeAbstract:Mathematical modeling of behavior during psychophysical tasks, referred to as "computational psychiatry", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced programming skills. We developed the Computational Psychiatry Adaptive State-Space (Compass) toolbox, an open-source MATLAB-based software package. After specifying a few parameters in a small set of user-friendly functions, Compass allows the user to efficiently fit of a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data, and can be tested using goodness-of-fit methods. Here, we demonstrate that Compass can replicate two computational behavior analyses from different groups. Compass replicates and, in one case, slightly improves on the original modeling results. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.
