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Articles 1 - 6 of 6
Full-Text Articles in Psychology
Assessing The Impact Of Lipopolysaccharide On Learning And Memory In Rats, Anahat Luthra
Assessing The Impact Of Lipopolysaccharide On Learning And Memory In Rats, Anahat Luthra
Undergraduate Student Research Internships Conference
The immune system and the central nervous system (CNS) have a bi-direction relationship, modulating one another.4 Proinflammatory cytokines released from CNS immune cells have an impact on cognitive processes such as learning and memory.1 Liposaccharide (LPS), a cell wall component of Gram-negative bacteria, which is used to activate proinflammatory cytokine release has been found to impact learning and memory processes, such as in the anticipatory nausea paradigm (ANP).2 Anticipatory nausea and vomiting is that which may occur before a chemotherapy treatment session begins in a patient who has had chemotherapy before. It is caused by triggers like …
Using A Musical Beat To Influence Linguistic Statistical Learning, Aspen Leung
Using A Musical Beat To Influence Linguistic Statistical Learning, Aspen Leung
Undergraduate Student Research Internships Conference
The similarities between music and language continue to provide research questions in the area of psychology. Despite the large amount of research on this area of knowledge, there are still many existing questions in regards to the processing of musical and linguistic stimuli. Statistical learning involves the ability to extract statistical regularities from a stimulus and continues to be studied in both domains due to the similar hierarchical structure of music and language. Recently, neural entrainment (the synchronization of neural oscillations with the rhythm of an external stimulus) has been studied as a mechanism of statistical learning. Music has been …
The Ommaba Project, Katsiaryna Buchko
The Ommaba Project, Katsiaryna Buchko
Undergraduate Student Research Internships Conference
The Open Multimodal Music and Auditory Brain Archive (OMMABA) is the first multimodal (behavioural, EEG, and neuroimaging) database characterizing normal human auditory processing. My project aims to shed light on the importance of this collaborative project that is transforming the field of auditory cognitive neuroscience.
Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat
Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat
MODVIS Workshop
No abstract provided.
Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni
Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni
MODVIS Workshop
We report on preliminary results of an anatomically-inspired deep learning model of the visual system and its role in explaining the face inversion effect. Contrary to the generally accepted wisdom, our hypothesis is that the face inversion effect can be accounted for by the representation in V1 combined with the reliance on the configuration of features due to face expertise. We take two features of the primate visual system into account: 1) The foveated retina; and 2) The log-polar mapping from retina to V1. We simulate acquisition of faces, etc., by gradually increasing the number of identities the network learns. …
Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno
Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno
MODVIS Workshop
We concluded in our previous study that model cortical visual pathways actively retained information differently according to the different goals of the training tasks. One limitation of our study was that there was only one object in each input image whereas in reality there may be multiple objects in a scene. In our current study, we try to find a brain-like algorithm that can recognize and localize multiple objects.