Presented at the Neuroscience Information Framework (NIF) webinar series on 24/04/2012. An overview of the Mental Functioning Ontology aims and objectives.
Representing addiction in Mental Functioning and Disease ontologiesJanna Hastings
Enabling querying and browsing of biomedical and neuroscientific research on addiction using interoperable ontologies and cross-products. Presented at ICBO 2012.
Pucurull, O., Feixas, G., Aguilera, M. C. & Carrera, M. J. (2011). What Changes in the Personal Construct System During Psychotherapy? A Naturalistic Study of Brief Construct Therapy. Presented at the 19th. International Congress on Personal Construct Psychology. Boston, MA.
Representing addiction in Mental Functioning and Disease ontologiesJanna Hastings
Enabling querying and browsing of biomedical and neuroscientific research on addiction using interoperable ontologies and cross-products. Presented at ICBO 2012.
Pucurull, O., Feixas, G., Aguilera, M. C. & Carrera, M. J. (2011). What Changes in the Personal Construct System During Psychotherapy? A Naturalistic Study of Brief Construct Therapy. Presented at the 19th. International Congress on Personal Construct Psychology. Boston, MA.
A sample lesson in Information Literacy and college-level research strategies, designed for a fictional community college. Created and presented to 9443: The Academic Library. Fall 2013.
Medical and pharmaceutical applications of mobile EEG (brain scanning)andfaulkner
Uses of inexpensive, personal, commercially-available, and portable EEG devices for medical research. Testing of new drugs, patient-specific drug selection, monitoring of patient progress, augmentation of treatments (via neurofeedback), prediction of 'attacks' in mental illnesses (e.g. panic disorder), and better diagnoses of neurological disorders.
Biological Approach in explaining Abnormality & Psychological DisordersSandra Arenillo
Following the Biopsychosocial Model of Psychological Disorders. The presentation will discuss the Biological Basis for Abnormality & Psychological Disorders
CHAPTER SIXThe Age of AnxietyThe multiple perspectives we have.docxtiffanyd4
CHAPTER SIX
The Age of Anxiety
The multiple perspectives we have been using in this book are particularly useful in understanding the impact anxiety has on U.S. society. The word “anxiety” comes from a Latin root meaning to “choke or throttle” connoting a troubled state of mind (Tone, 2009). Anxiety disorders are believed to be the most common mental health problem in the United States. Two common measures are lifetime morbid risk (the theoretical risk of getting a disorder at any point in life) and 12-month prevalence (the proportion of the population thought to suffer from the disorder in any 12-month period). Baxter et al. (2013) conducted a meta-analysis of 87 studies from 44 countries between 1980 and 2009. They found that anxiety disorders are common across the globe with an estimated current prevalence of approximately as much as 28% of the global population. The prevalence of anxiety disorders in the United States is estimated for lifetime morbid risk/12-month prevalence as follows: Specific Phobia 18.4%/12.1%, Social Anxiety Disorder 13%/7.4%, Post Traumatic Stress Disorder (PTSD) 10.1%/3.7%, Generalized Anxiety Disorder 9%/2%, Separation Anxiety Disorder 8.7% /1.2%, and Panic Disorder, 6.8%/2.4%, (Kessler, Petukhova, Sampson, Zaslovsky, & Wittchen, 2012). Although anxiety disorders are prominent, it is important to realize that their incidence has remained steady over several decades despite pharmaceutically funded efforts to make the public think there is an epidemic that needs medicated (Baxter et al., 2014).
Although psychotropic medications are available for anxiety disorders, many psychological treatments also have excellent track records. Remember, from an integrative perspective it is not enough to describe anxiety symptoms, posit a biological explanation, then describe how certain drugs act biologically to (at least temporarily) decrease or eliminate these symptoms. With sentient beings, we have to look to the psychological, cultural and social variables that contribute to anxiety.
We recall a client (Elijah) who lived in what could be described as a “toxic environment.” Elijah's urban residence was the regular scene of violence, and he himself had witnessed two shootings in his 23 years. He was court-ordered to receive treatment for an alcohol-related charge (drunk and disorderly conduct). Even after abstaining from all drugs for 60 days, Elijah was what could only be described as “a nervous wreck.” He showed symptoms of both Panic Disorder and PTSD (the latter related to stimuli associated with the shootings he had witnessed). In consultation with a psychiatrist, who prescribed SSRI medication, Elijah asked why he had his symptoms, and the doctor replied, “Some people have a genetic predisposition to such things.” As Charlie Brown would say, “Good grief!” In this client's case, genetic predisposition not withstanding, there were clearly psychological, cultural, and social contributors to his anxiety. His alcohol use was a .
A sample lesson in Information Literacy and college-level research strategies, designed for a fictional community college. Created and presented to 9443: The Academic Library. Fall 2013.
Medical and pharmaceutical applications of mobile EEG (brain scanning)andfaulkner
Uses of inexpensive, personal, commercially-available, and portable EEG devices for medical research. Testing of new drugs, patient-specific drug selection, monitoring of patient progress, augmentation of treatments (via neurofeedback), prediction of 'attacks' in mental illnesses (e.g. panic disorder), and better diagnoses of neurological disorders.
Biological Approach in explaining Abnormality & Psychological DisordersSandra Arenillo
Following the Biopsychosocial Model of Psychological Disorders. The presentation will discuss the Biological Basis for Abnormality & Psychological Disorders
CHAPTER SIXThe Age of AnxietyThe multiple perspectives we have.docxtiffanyd4
CHAPTER SIX
The Age of Anxiety
The multiple perspectives we have been using in this book are particularly useful in understanding the impact anxiety has on U.S. society. The word “anxiety” comes from a Latin root meaning to “choke or throttle” connoting a troubled state of mind (Tone, 2009). Anxiety disorders are believed to be the most common mental health problem in the United States. Two common measures are lifetime morbid risk (the theoretical risk of getting a disorder at any point in life) and 12-month prevalence (the proportion of the population thought to suffer from the disorder in any 12-month period). Baxter et al. (2013) conducted a meta-analysis of 87 studies from 44 countries between 1980 and 2009. They found that anxiety disorders are common across the globe with an estimated current prevalence of approximately as much as 28% of the global population. The prevalence of anxiety disorders in the United States is estimated for lifetime morbid risk/12-month prevalence as follows: Specific Phobia 18.4%/12.1%, Social Anxiety Disorder 13%/7.4%, Post Traumatic Stress Disorder (PTSD) 10.1%/3.7%, Generalized Anxiety Disorder 9%/2%, Separation Anxiety Disorder 8.7% /1.2%, and Panic Disorder, 6.8%/2.4%, (Kessler, Petukhova, Sampson, Zaslovsky, & Wittchen, 2012). Although anxiety disorders are prominent, it is important to realize that their incidence has remained steady over several decades despite pharmaceutically funded efforts to make the public think there is an epidemic that needs medicated (Baxter et al., 2014).
Although psychotropic medications are available for anxiety disorders, many psychological treatments also have excellent track records. Remember, from an integrative perspective it is not enough to describe anxiety symptoms, posit a biological explanation, then describe how certain drugs act biologically to (at least temporarily) decrease or eliminate these symptoms. With sentient beings, we have to look to the psychological, cultural and social variables that contribute to anxiety.
We recall a client (Elijah) who lived in what could be described as a “toxic environment.” Elijah's urban residence was the regular scene of violence, and he himself had witnessed two shootings in his 23 years. He was court-ordered to receive treatment for an alcohol-related charge (drunk and disorderly conduct). Even after abstaining from all drugs for 60 days, Elijah was what could only be described as “a nervous wreck.” He showed symptoms of both Panic Disorder and PTSD (the latter related to stimuli associated with the shootings he had witnessed). In consultation with a psychiatrist, who prescribed SSRI medication, Elijah asked why he had his symptoms, and the doctor replied, “Some people have a genetic predisposition to such things.” As Charlie Brown would say, “Good grief!” In this client's case, genetic predisposition not withstanding, there were clearly psychological, cultural, and social contributors to his anxiety. His alcohol use was a .
Pipeline for automated structure-based classification in the ChEBI ontologyJanna Hastings
Presented at the ACS in Dallas: ChEBI is a database and ontology of chemical entities of biological interest, organised into a structure-based and role-based classification hierarchy. Each entry is extensively annotated with a name, definition and synonyms, other metadata such as cross-references, and chemical structure information where appropriate. In addition to the
classification hierarchy, the ontology also contains diverse chemical and ontological relationships. While ChEBI is primarily manually maintained, recent developments have focused on improvements in curation through partial automation of common tasks. We will describe a pipeline we have developed for structure-based classification of chemicals into the ChEBI structural classification. The pipeline connects class-level structural knowledge encoded in Web Ontology Language (OWL) axioms as an extension to the ontology, and structural information specified in standard MOLfiles. We make use of the Chemistry Development Kit, the OWL API and the OWLTools library. Harnessing the pipeline, we are able to suggest the best structural classes for the classification of novel structures within the ChEBI ontology.
Data integration is a perennial challenge facing large-scale data scientists. Bio-ontologies are useful in this endeavour as sources of synonyms and also for rules-based fuzzy integration pipelines.
Using ChEBI to explore the underlying biology in metabolomics studiesJanna Hastings
ChEBI is a chemical database and ontology that is widely used to annotate biological data. Here, we show a tool that is currently in development that allows exploration of the biological annotations for metabolites that are found to be enriched in metabolomics investigations. This tool will be made available online soon.
Chemical classification for the Semantic WebJanna Hastings
Classification conveys the type for data that is published in the Semantic Web. Classification using OWL ontoloiges dramatically enhances the potential of the chemical Semantic Web. ChEBI provides a classification that can be used across multiple data resources.
Bio-ontologies in bioinformatics: Growing up challengesJanna Hastings
Bio-ontologies are growing up, and their use is becoming widespread in many areas of computational science. The new maturity is bringing new challenges, however, in particular visualization of complex ontologies; moving from OBO to OWL; using multiple ontologies in conjunction; training appropriate for biologists and community building.
From chemicals to minds: Integrated ontologies in the search for scientific u...Janna Hastings
Presented at the 2012 Interdisciplinary Ontology (InterOntology) Conference in Tokyo, February 24th 2012. This presentation gives a whirlwind tour of some "reports from the front lines" of practical bio-ontology development in ChEBI and in the Mental Functioning and Emotion Ontology projects.
Modularity requirements in bio-ontologies: a case study of ChEBIJanna Hastings
A wish list for tools for modularity support in bio-ontology engineering based on the ChEBI ontology requirements. Presented at the workshop on modular ontologies, WoMO, 2011, in Ljubljana.
The SHAPES workshop, and Holes in living beings Janna Hastings
The SHAPES workshop brought together interdisciplinary shape researchers. Our paper presents some challenges in applying shapes -- and holes -- in living beings.
Presented at the AI center of the Stanford Research Institute: chemical ontologies provide a chemical view into biological systems. Various challenges with modelling "active properties" (roles, functions, dispositions) are discussed.
Presented at the ICBO 2011 conference in Buffalo, we tackle the controversial 'is about' relationship in the information artifact ontology (IAO) in the context of chemical diagrams.
The emotion ontology: enabling interdisciplinary research in the affective sc...Janna Hastings
Presented at the 2011 ICBO, we motivate and introduce the Emotion Ontology currently under development in the Swiss Centre for Affective Sciences in collaboration with the University at Buffalo.
Hyperontology for the biomedical ontologistJanna Hastings
Presented at the 2011 ICBO Workshop on working with multiple biomedical ontologies. We present a framework for designing and interrelating ontology modules which are indvidually represented in different underlying logical formalisms.
Using multiple ontologies to characterise the bioactivity of small moleculesJanna Hastings
Presented at the 2011 ICBO workshop on working with multiple biomedical ontologies. We describe work on text mining for relationship extraction between chemical and biological entities via a language model for bioactivity.
Presented at the 2011 ISMB Bio-ontologies SIG. A detour into the difficulties of representing the properties of processes in ontologies, and some steps towar
Ontological dependence, dispositions and institutional reality in chemistryJanna Hastings
Presented at the 2010 Formal Ontology in Information Systems conference (FOIS 2010). Discusses different classifications of the activity of chemical entities (in the context of the ChEBI ontology).
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Mental functioning ontology for interdisciplinary research into mental disease, emotions and drugs
1. NIF Webinar, 24 April 2012
Mental Functioning Ontology
for interdisciplinary research
into mental disease, emotions and drugs
Janna Hastings1,2
(ChEBI, MF and the Emotion Ontology)
1 Cheminformatics and Metabolism, European Bioinformatics Institute, UK
2 Swiss Center for Affective Sciences, University of Geneva, Switzerland
2. Why mental
functioning? I want…
Oxytocin is believed to play a role in various behaviors,
including orgasm, social recognition, pair bonding, anxiety …
it is sometimes referred to as the "love hormone".
The inability to secrete oxytocin and feel empathy is I think…
linked to sociopathy, psychopathy, narcissism and
general manipulativeness.
Tuesday, April 24, 2012 2
3. Many chemicals
can affect mental functioning
The Chemical
Ontology
Tuesday, April 24, 2012 3
4. How does mental functioning
actually work?
EEG
Biology Mouse
Psychology
Human Cognitive Science
fMRI
Genetic PET
profiling Gene
Neuroscience expression
analysis Psychiatry
Metabolic Chemistry Self-reports
analysis Questionnaires
5. Theories of mental functioning have
Abducted!
testable implications for research Replaced!
into mental disease
Capgras delusion:
a disorder in which a person
holds a delusion that a friend,
spouse, parent, or other close
family member has been replaced
by an identical-looking impostor.
Faulty perception?
Normal perception, faulty reasoning?
Faulty emotional reaction to perception?
Overactive imagination?
TESTABLE IMPLICATIONS
10. Bio-ontologies facilitate
interdisciplinary scientific research
1. Standardised vocabulary with definitions and
synonyms for unified database annotations
2. Hierarchical organisation for aggregation and multi-
level comparison of results
3. Community adoption for comparison of results to
other project results worldwide
4. Explicit relationships and underlying logic for
automated reasoning to related entities
5. Explicit bridging relationships between different
ontologies for exploring underlying mechanisms
Tuesday, April 24, 2012 10
11. Modern scientific research relies on
computational support
Patient histories,
EHR
Synthesis
Caregiver, Data
pscyhiatric reports
Analysis
Genomic and Data
metabolomic
profiles Reporting
Questionnaires Data Publication
and self-reports
Brain scans
Tuesday, April 24, 2012 11
12. Ontology for standardisation
Semantics-free unique identifiers that are
stable and maintained
MD:0000901
CODE (MD) indicates WHICH ONTOLOGY
substance abuse
A numeric identifier is unique per term
is a
Unambiguous preferred label together
MD:0000902
with a textual definition guide the annotation
marijuana abuse
of this ontology term to associated data
is abuse of substance
S:09090909 Synonyms and other metadata are collected
marijuana to facilitate searching, disambiguation and
--------------------------- text processing
Synonym: cannabis
Synonym: THC Synonyms may be in several languages
Synonym: dronabinol or reflect differing naming practices in different
disciplines
Tuesday, April 24, 2012 12
13. Ontology annotations are generic
across multiple databases
ID Patient Finding type Detail
1111 Smith, John MF:0000902 Occasional
(marijuana abuse)
1111 Smith, John MF:0000903 Occasional
(alcohol abuse)
1111 Smith, John MF:0000904 Frequent
(nicotine abuse)
Same IDs
Sample ID Sample type Conditions Genotype
1111 Illumina Golden Gate MF:0000903; MF:0000902 …
Tuesday, April 24, 2012 13
14. Population-wide science depends on
aggregation of data
Are there genes significantly enriched in all people
who suffer from some addiction?
Are there differences between those people who
suffer from substance addiction compared to those
who suffer from process addictions?
Are there differences between those people who
suffer from opiate substance addictions and those
who suffer from addictions to benzodiazepines?
Tuesday, April 24, 2012 14
15. Ontology for hierarchical organisation
MD:0000046
addiction
MD:0000053 MD:0000053
process addiction substance addiction
MD:0000054 MD:0000066 MD:0000065
gambling addiction benzodiazepine addiction opiate addiction
MD:0000055 MD:0000067 MD:0000059
sex addiction diazepam addiction heroin addiction
MD:0000064 MD:0000068
internet addiction morphine addiction
Every ‘sex addiction’ is a ‘process addiction’, every ‘process addiction’ is an ‘addiction’
Every ‘heroin addiction’ is an ‘opiate addiction’, every ‘opiate addiction’ is a ‘substance
addiction’, every ‘substance addiction’ is an ‘addiction’. And so on.
Tuesday, April 24, 2012 15
16. Research involves comparison of results
to existing data arising from other
projects, stored in public databases
A researcher obtains brain scans for several addicted patients. In order
to determine how they compare to existing scans of other addicted
patients and to non-addicted patients, (s)he looks in public databases.
Relating to addiction, manual examination of the BrainMap database
searchcriteria suggests two patient diagnosis categories that may
be relevant: alcoholism and pathological
gambling
… as well as many unstructured keywords
Tuesday, April 24, 2012 16
19. To amass the correct search criteria to find the data for
each comparison requires careful manual examination
… and that’s only one database out of hundreds
Tuesday, April 24, 2012 19
20. A shared community ontology for
annotation allows unified searching
across databases (e.g. GOA)
RIKEN
BrainMap
Neuroimaging
Platform
Brede Nifti
fMRI Data
OpenfMRI NeuroSynth
Center
Tuesday, April 24, 2012 20
21. Computers can’t “see” implicit
relationships between entities
Substance addiction is characterised by symptoms such as
preoccupation with substance and repeated failed attempts
to control the use of the substance. These are non-
canonical thinking and planning activities.
But, there is no easy way to automatically compare with
data from other conditions that have similar symptoms.
Patient data – Patient data –
Patient data – impaired rational preoccupation or
addicted patients control of actions other compulsive
or planning thinking
Tuesday, April 24, 2012 21
22. Ontologies capture explicit computable
relationships between entities
MD:0001002 MD:0001001
non-canonical (impaired) non-canonical (impaired)
thinking process planning process
MD:0001012 MD:0001011 Relationships
preoccupation with failed attempts to are named
substance use stop substance use
and have
definitions
has part
MD:0001053 They are used
MD:0000053 realized in
substance addiction
substance addiction for automated
disease course reasoning and
question
Tuesday, April 24, 2012 answering22
23. Related entities are themselves used
in annotations
MD:0001002
non-canonical (impaired)
thinking process Patient data on
Patient data on
symptom symptom
assessment assessment
MD:0001001 (Dysexecutive
(Addiction)
non-canonical (impaired) syndrome)
planning process
… which allows patient data
from disparate diseases (and research into
normal functioning) to be compared
Tuesday, April 24, 2012 23
24. Different domains operate at different
levels of granularity and focus
METABOLIC
DATA (e.g. NMR)
GENE
EXPRESSION
PATHWAYS, biological DATA
Tuesday, April 24, 2012 24
processes
25. Urine samples of addicted patients reveal metabolites
NMR data for
metabolites
of cocaine
is found in
metabolomics
databases -- indexed
by small molecules
Tuesday, April 24, 2012 25
26. Ontology relationships can explicitly
bridge across different ontologies at
different levels
MD:0000071
realized in MD:0010071
cocaine addiction
cocaine addiction
disease course
has part
S:00100100 has input MD:0020071
portion of cocaine use of cocaine
has granular part
CHEBI:27958
Chemical and
cocaine
metabolic data
Tuesday, April 24, 2012 26
27. Current status and ongoing work
in the Emotion Ontology
Tuesday, April 24, 2012 27
28. The Emotion Ontology (MFO-EM)
BFO:Entity BFO
MFO
BFO:Continuant BFO:Occurrent MFO-EM
BFO:Independent BFO:Dependent
Continuant Continuant BFO:Process
Organism BFO:Disposition Bodily Process
Physiological
Response to
Emotion Process
Mental Process
Cognitive
inheres_in
Representation
Appraisal
Process
Emotional Action
Tendencies Affective is_output_of
Representation Appraisal
Emotional
Behavioural Process
Subjective
Emotional Feeling
has_part
agent_of
Emotion Occurrent
30. To define the characteristics of different
emotions start with canonical emotions
Emotion types (such as fear) show enormous variance across instances
Just as do anatomical types, e.g. human bodies
Ontology expresses what is always true… But also aims to say
something useful for representation of domain knowledge.
Solution: encode such knowledge in ‘canonical’ types
canonical Has part appraisal Has output Appraisal of
fear process dangerousness
Canonical fear results from an appraisal of dangerousness
Tuesday, April 24, 2012 30
31. Canonical fear
fear
subtype
canonical
fear
EMOTION COMPONENT CHARACTERISTIC FOR FEAR
Action tendency Fight-or-flight
Subjective emotional feeling Negative, tense, powerless
Behavioural response Characteristic fearful facial
expression
Characteristic appraisal Something is dangerous to me
Tuesday, April 24, 2012 31
32. Canonical and non-canonical fear
Canonical fear gives rise to action tendencies
that are conformant to the perceived danger
Phobia =
disposition giving rise to non-canonical fear
laridaphobia : intense fear of seagulls
Tuesday, April 24, 2012 32
37. Annotation of data from Cognitive
Neuroscience of Emotion
Study Task Annotation class in MFO/MFOEM
Recognition of gender in emotional facial Visual perception of emotional facial
expressions expressions (subClassOf perception)
Recall of personal emotional memories Memory of emotional episodes
with instructions to try re-create feeling (subClassOf memory)
Listening to emotional sounds (e.g. grunts Auditory perception of emotional stimuli
of disgust) (subClassOf perception)
Viewing emotional film extracts Visual and auditory perception of
emotional stimuli (subClassOf perception)
The link from perception of emotional fear in facial
expressions to canonical fear is subject to empirical research
Tuesday, April 24, 2012 37
38. (Part of) the biochemical basis of
emotion is in ChEBI
Emotions are effected in part by
neurotransmitters such as dopamine, tryptophan
molecular entity biological role Molecular function emotion
(CHEBI:25375) (CHEBI:24432) (GO:0003674) (MFOEM:1)
subtype
neurotransmitter
happiness
dopamine neurotransmitter receptor activity
(MFOEM:42)
(CHEBI:25375) (CHEBI:25512) (GO:0030594)
has role realized in part of
Tuesday, April 24, 2012 38
39. Biological processes in affective
disorders
Some mental diseases involve altered emotional
functioning. (E.g. depression, bipolar disorder)
Disposition Process
mental
emotion biological process
disease Mechanism of
action:
complex
down-regulation disturbances in
non-canonical of dopaminergic
depression underlying
sadness system systems
(GO:0032227)
realized in has part
Tuesday, April 24, 2012 39
40. Availability, Contacts
Mental Functioning Ontology available at:
http://mental-functioning-
ontology.googlecode.com/svn/trunk/ontology/MF.owl
Emotion Ontology available at:
http://emotion-
ontology.googlecode.com/svn/trunk/ontology/MFOEM.owl
Discussion mailing lists:
mfo-discuss@googlegroups.com
emotion-ontology@googlegroups.com
Tuesday, April 24, 2012 40
41. Acknowledgements
Thanks!
Buffalo Ontologists
Barry Smith, Werner Ceusters, Mark Jensen
Emotion Researchers in Geneva
Kevin Mulligan, David Sander, Julien Deonna
Chemistry, Biology, Neuroscience
Christoph Steinbeck, Nicolas le Novère, Colin Batchelor,
David Osumi-Sutherland, Jane Lomax,
Jessica Turner, Angela Laird
Tuesday, April 24, 2012 41
Editor's Notes
There are 134 hits for ‘has role’ some psychotropic in ChEBI in February 2012. This screenshot (inter alia) shows Lithium (a mood stabilizer); chlorpromazine (an antipsychotic); valproate (antimanic); 5-methoxy-N,N-dimethyltryptamine (hallucinogen);
(Not the million dollar question, but the many billion dollars question!)We’re drowning in data and starving for knowledge! Not only different domains BUT different methods and different subjects (model organisms etc)Huge piles of different sorts of information coming out of different research areas. DIFFERENT PERSPECTIVES: if you try to get people to agree on names, they just don’t. But give them semantics-free identifiers and their own preferred (scoped) synonyms and you can get agreement on the definitions. Nobody is an expert in everything, most scientists are stuck in their narrow area of focus and expertise (which is a good thing for progress because you HAVE to become that specialised)
Different interpretations for the same results can ensue; based on the underlying theory of mental functioning. Linking the theory directly to the paradigm (tests) and the research results allows more straightforward generation of testable hypothesis for evaluating different theories… getting away from conceptual arguments, or at least helping to resolve them(Explicit logical formulation)
SNOMED, MeSH, ICD, ICF, Cognitive Atlas, Cognitive Paradigm Ontology, We will build on these vocabulary resources as sources, but maintain links so that we don’t lose mappings which have already been annotated to these sources.Most of these sources maintain controlled vocabularies but not real ontologies. There is a shortage of explicit relationships and formal (computable) definitions, so you can’t make computational inferences.
Mental functioning related anatomical structure: an anatomical structure in which there inheres the disposition to be the agent of a mental processBehaviour inducing state: a bodily quality inhering in a mental functioning related anatomical structure which leads to behaviour of some sortAffective representation: a cognitive representation sustained by an organism about its own emotionsCognitive representation: a representation which specifically depends on an anatomical structure in the cognitive system of an organismMental process: a bodily process which brings into being, sustains or modifies a cognitive representation or a behaviour inducing state
Arrows show ‘imports’ relationships between ontologies
Software engineering for integrative question-answering is made much easier by this approach, as the IDs are well-behaved strings – uniform length, numeric identifiers for quick lookup / indexing and so on.
Obviously, these questions leave aside the complexities of co-occurrences, but for the higher-level questions that would present no problem as long as aggregation occurred with the count of instances not the count of types. For the comparative questions at the lower level, you would want to exclude co-occurrences from the analysis if you were looking for genes that comparatively differed between the different classes.
BrainMap is a database of curated fMRI coordinates from published studies -- BrainMap.org.
These screenshots illustrate the search interface application for BrainMap
Examples of keywords which may be relevant – there are many others – e.g. heroin, opiate, … other sorts of drugs. No hierarchical relationships are expressed between these keywords, so a search would have to be assembled by adding them one by one – no automatic aggregation option is available.
Each database has different organisation and search criteria – here it is patient diagnosis and keywords, or at least those were the only two fields that I could find were relevant.
This desideratum may sound like wishful thinking but in fact it is ALREADY IN PLACE for the Gene Ontology and most biological databases. Databases listed here are a small selection of those that include fMRI coordinate data. For a discussion of the various brain imaging methods and results in studies of addiction, see: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851068/ ‘Imaging the addicted human brain’
It would be useful, therefore, to compare data for addicted patients with data for patients with other preoccupations or failed goal-directed behaviours. But no computational methods facilitate this type of cross-searching at present. Again, it comes down to human effort to find or create the right sort of data. Targeted studies can be designed that do this on a one-by-one basis: see, for example, http://jnnp.bmj.com/content/68/6/731.full – which compares data on dysexecutive syndrome with patients who have alcoholism. Good study design is always a good idea, but the availability of published data on various conditions would allow re-use of that data in other contexts, if the links from symptoms to disorders were made more explicit.
Psychological standard test for ‘dysexective syndrome’ => failure of normal executive functions such as planning, organising, initiating … => http://www.dwp.gov.uk/docs/no2-sum-03-test-review-2.pdfFootnote: data should be compared only if it makes sense to do so! That’s the reason for explicitly characterising and classifying symptoms
Pathway illustration sourced from KEGG: http://www.kegg.jp/kegg-bin/highlight_pathway?scale=1.0&map=map05030&keyword=addictionNMR spectrum illustration (of a derivative of cocaine) comes from http://www.justice.gov/dea/programs/forensicsci/microgram/journal_v4_num14/pg5.html
This data on metabolites of cocaine was sourced from the Human Metabolome Database (HMDB): http://www.hmdb.ca/metabolites/HMDB06348
Canonical fear also involves an action tendency to fight-or-flight, a bad (powerless, negative, anxious) feeling, a behavioural response to the emotion that includes a characteristic fearful facial expression
Cognitive neuroscience uses research “paradigms” – experimental designs intended to allow comparison of brain activation between different conditions. The subtraction of the brain activation for the control condition from the brain activation for the test condition then gives the “net” activation, which is what is reported on in the literature, subject to statistical analysis.
This is, of course, just one tiny part of the story. The overall story would have to be built up out of many, many cross-ontology links.
Depression and bipolar disorder are paradigm affective disorders.