Duyan, Yalcın Akın

Profile URL
https://hdl.handle.net/20.500.11779/2779
Name Variants
Duyan, Yalçin A.
Job Title
Email Address
duyany@mef.edu.tr
Main Affiliation
04.02. Department of Psychology
Status
Current Staff
Website
ORCID ID
0000-0002-4527-0165
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Files
1728235818-academic-1900004133.avif (14.45 KB)

Research Topics

Domains
Life SciencesPhysical Sciences
Fields
NeuroscienceMathematics
Subfields
Cognitive NeuroscienceStatistics and Probability
Specific Research Areas
Neuroscience and Music Perception
Cognitive and developmental aspects of mathematical skills
Visual perception and processing mechanisms
Memory and Neural Mechanisms
Neural dynamics and brain function

Sustainable Development Goals

SDG data is not available
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.

Publication Collaboration

Affiliation Name Count
Koç University 13
MEF University 4
University of Manitoba 3
University of Colorado Boulder 2
University of Oxford 2
1 / 22
Data obtained from OpenAlex
Scholarly Output

3

Articles

3

Views / Downloads

192/56

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

28

Scopus Citation Count

28

Patents

0

Projects

0

WoS Citations per Publication

9.33

Scopus Citations per Publication

9.33

Open Access Source

1

Supervised Theses

0

JournalCount
Animal Cognition2
Behavior Research Methods1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

2020 - 20233

Settings

Author of Publication: search.filters.isAuthorOfPublication.e710df36-7a41-408f-a41d-2c5d98163b28

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Article
    Citation - WoS: 16
    Citation - Scopus: 16
    The Timing Database: an Open-Access, Live Repository for Interval Timing Studies
    (Springer, 2023-01-03) Brochard, Renaud; Karşılar, Hakan; Akdoğan, Başak; De Corte, Benjamin; Aydoğan, Turaç; Baccarani, Alessia; Duyan, Yalçın Akın; Balci, Fuat
    Interval timing refers to the ability to perceive and remember intervals in the seconds to minutes range. Our contemporary understanding of interval timing is derived from relatively small-scale, isolated studies that investigate a limited range of intervals with a small sample size, usually based on a single task. Consequently, the conclusions drawn from individual studies are not readily generalizable to other tasks, conditions, and task parameters. The current paper presents a live database that presents raw data from interval timing studies (currently composed of 68 datasets from eight different tasks incorporating various interval and temporal order judgments) with an online graphical user interface to easily select, compile, and download the data organized in a standard format. The Timing Database aims to promote and cultivate key and novel analyses of our timing ability by making published and future datasets accessible as open-source resources for the entire research community. In the current paper, we showcase the use of the database by testing various core ideas based on data compiled across studies (i.e., temporal accuracy, scalar property, location of the point of subjective equality, malleability of timing precision). The Timing Database will serve as the repository for interval timing studies through the submission of new datasets.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Mice Make Temporal Inferences About Novel Locations Based on Previously Learned Spatiotemporal Contingencies
    (Springer, 2022-11-17) Balci, Fuat; Gür, Ezgi; Duyan, Yalçin A.
    Animals learn multiple spatiotemporal contingencies and organize their anticipatory responses accordingly. The representational/computational capacity that underlies such spatiotemporally guided behaviors is not fully understood. To this end, we investigated whether mice make temporal inferences of novel locations based on previously learned spatiotemporal contingencies. We trained 18 C57BL/6J mice to anticipate reward after three different intervals at three different locations and tested their temporal expectations of a reward at five locations simultaneously, including two locations that were not previously associated with reward delivery but adjacent to the previously trained locations. If mice made spatiotemporal inferences, they were expected to interpolate between duration pairs associated with previously reinforced hoppers surrounding the novel hopper. We found that the maximal response rate at the novel locations indeed fell between the two intervals reinforced at the surrounding hoppers. We argue that this pattern of responding might be underlain by spatially constrained Bayesian computations.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 9
    Numerical Averaging in Mice
    (Springer, 2020-11-04) Balcı, Fuat; Duyan, Yalcın Akın; Gür, Ezgi
    Rodents can be trained to associate different durations with different stimuli (e.g., light/sound). When the associated stimuli are presented together, maximal responding is observed around the average of individual durations (akin to averaging). The current study investigated whether mice can also average independently trained numerosities. Mice were initially trained to make 10 or 20 lever presses on a single (run) lever to obtain a reward and each fixed-ratio schedule was signaled either with an auditory or visual stimulus. Then, mice were trained to press another lever to obtain the reward after they responded on the run lever for the minimum number of presses [Fixed Consecutive Number (FCN)-10 or -20 trials] signaled by the corresponding discriminative stimulus. Following this training, FCN trials with the compound stimulus were introduced to test the counting behavior of mice when they encountered conflicting information regarding the number of responses required to obtain the reward. Our results showed that the numbers of responses on these compound test trials were around the average of the number of responses in FCN-10 and FCN-20 trials particularly when the auditory stimulus was associated with a fewer number of required responses. The counting strategy explained the behavior of the majority of the mice in the FCN-Compound test trials (as opposed to the timing strategy). The number of responses in FCN-Compound trials was accounted for equally well by the arithmetic, geometric, and Bayesian averages of the number of responses observed in FCN-10 and FCN-20 trials.