Rats with lesions in either the fornix, the amygdala, or both were compared with control animals on the acquisition of three different concurrent object discrimination tasks. In the first task the animals received one trial per day on each of six pairs of stimulus objects ('spaced' condition). In the second task the animals received four trials per day on each of six stimulus pairs ('standard' condition), and in the last task the animals received 36 trials on each of two stimulus pairs in just a single day ('massed' condition). Animals with fornical lesions were impaired on all three conditions. In contrast, the amygdala lesions only affected the 'massed' condition and then only when the animals had to select the 'non-preferred' stimulus. Although animals with combined amygdala and fornical lesions were impaired on all three conditions there was no evidence that their deficit was greater than that in the animals with lesions restricted to just the fornix. In view of the evidence that concurrent discrimination learning offers an appropriate test for anterograde amnesia these findings are seen as consistent with the notion that the hippocampus, but not the amygdala, is critically involved in the mnemonic processes disrupted by amnesia.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/s0166-4328(05)80146-9 | DOI Listing |
Sci Rep
January 2025
Research Institute for Brain Development and Peak Performance, RUDN University, Moscow, Russia.
Maze tasks, originally developed in animal research, have become a popular method for studying human cognition, particularly with the advent of virtual reality. However, these experiments frequently rely on simplified environments and tasks, which may not accurately reflect the complexity of real-world situations. Our pilot study aims to transfer a multi-alternative maze with a complex task structure, previously demonstrated to be useful in studying animal cognition, to studying human spatial cognition.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Otolaryngology - Head and Neck Surgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, USA.
Loud noise exposure is one of the leading causes of permanent hearing loss. Individuals with noise-induced hearing loss (NIHL) suffer from speech comprehension deficits and experience impairments to cognitive functions such as attention and decision-making. Here, we investigate the specific underlying cognitive processes during auditory perceptual decision-making that are impacted by NIHL.
View Article and Find Full Text PDFBehav Brain Res
January 2025
Department of Psychology, University of Otago, New Zealand. Electronic address:
A majority of people with schizophrenia will experience motor symptoms such as impairments to coordination, balance and motor sequencing. These neurological soft signs are associated with negative social and functional outcomes, and poor disease prognosis. They occur prior to medication exposure, suggesting they are an intrinsic feature of schizophrenia.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3TA, United Kingdom.
Daily life for humans and other animals requires switching between periods of threat- and reward-oriented behavior. We investigated neural activity associated with spontaneous switching, in a naturalistic task, between foraging for rewards and seeking information about potential threats with 7T fMRI in healthy humans. Switching was driven by estimates of likelihood of threat and reward.
View Article and Find Full Text PDFPLoS One
January 2025
Division of Biological Sciences, US Fish and Wildlife Southwest Regional Office, Albuquerque, New Mexico, United States of America.
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers' observations and selecting the mode classification.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!