- Home
- Medical news & Guidelines
- Anesthesiology
- Cardiology and CTVS
- Critical Care
- Dentistry
- Dermatology
- Diabetes and Endocrinology
- ENT
- Gastroenterology
- Medicine
- Nephrology
- Neurology
- Obstretics-Gynaecology
- Oncology
- Ophthalmology
- Orthopaedics
- Pediatrics-Neonatology
- Psychiatry
- Pulmonology
- Radiology
- Surgery
- Urology
- Laboratory Medicine
- Diet
- Nursing
- Paramedical
- Physiotherapy
- Health news
- Fact Check
- Bone Health Fact Check
- Brain Health Fact Check
- Cancer Related Fact Check
- Child Care Fact Check
- Dental and oral health fact check
- Diabetes and metabolic health fact check
- Diet and Nutrition Fact Check
- Eye and ENT Care Fact Check
- Fitness fact check
- Gut health fact check
- Heart health fact check
- Kidney health fact check
- Medical education fact check
- Men's health fact check
- Respiratory fact check
- Skin and hair care fact check
- Vaccine and Immunization fact check
- Women's health fact check
- AYUSH
- State News
- Andaman and Nicobar Islands
- Andhra Pradesh
- Arunachal Pradesh
- Assam
- Bihar
- Chandigarh
- Chattisgarh
- Dadra and Nagar Haveli
- Daman and Diu
- Delhi
- Goa
- Gujarat
- Haryana
- Himachal Pradesh
- Jammu & Kashmir
- Jharkhand
- Karnataka
- Kerala
- Ladakh
- Lakshadweep
- Madhya Pradesh
- Maharashtra
- Manipur
- Meghalaya
- Mizoram
- Nagaland
- Odisha
- Puducherry
- Punjab
- Rajasthan
- Sikkim
- Tamil Nadu
- Telangana
- Tripura
- Uttar Pradesh
- Uttrakhand
- West Bengal
- Medical Education
- Industry
Reinforcement and punishment learning helpful in explaining OCD: Study - Video
|
Overview
Scientists have shown that uneven reinforcement and punishment learning can be used to explain obsessive-compulsive disorder (OCD). They demonstrated that disparities in brain calculations that relate present outcomes to prior actions can result in disordered behavior based on empirical tests of their theoretical model.
Specifically, this can happen when the memory trace signal for past actions decays differently for good and bad outcomes. In this case, "good" means the result was better than expected, and "bad" means that it was worse than expected. This work helps to explain how OCD develops.
Now, a team led by researchers at NAIST has used reinforcement learning theory to model the disordered cycle associated with OCD. Using simulations, NAIST scientists found that agents implicitly learn obsessive-compulsive behavior when the trace decay factor for memory traces of past actions related to negative prediction errors is much smaller than that related to positive prediction errors . To test this prediction the researchers had 45 patients with OC and 168 healthy control subjects play a computer-based game with monetary rewards and penalties. Patients with OCD showed much smaller compared with , as predicted computational characteristics of OCD. In addition, this imbalanced setting of trace decay factors was normalized by serotonin enhancers, which are first-line medications f treatment of OCD.
Ref:
Yuki Sakai*, Yutaka Sakai*, Yoshinari Abe, Jin Narumoto & Saori C. Tanaka,Memory trace imbalance in reinforcement and punishment systems can reinforce implicit choices leading to obsessive-compulsive behavior,Cell Reports,10.1016/j.celrep.2022.111275
Speakers
Isra Zaman
B.Sc Life Sciences, M.Sc Biotechnology, B.Ed
Isra Zaman is a Life Science graduate from Daulat Ram College, Delhi University, and a postgraduate in Biotechnology from Amity University. She has a flair for writing, and her roles at Medicaldialogues include that of a Sr. content writer and a medical correspondent. Her news pieces cover recent discoveries and updates from the health and medicine sector. She can be reached at editorial@medicaldialogues.in.
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751