Rationale: Addiction is characterized by maladaptive decision-making, in which individuals seem unable to use adverse outcomes to modify their behavior. Adverse outcomes are often infrequent, delayed, and even rare events, especially when compared to the reliable rewarding drug-associated outcomes. As a result, recognizing and using information about their occurrence put a premium on the operation of so-called model-based systems of behavioral control, which allow one to mentally simulate outcomes of different courses of action based on knowledge of the underlying associative structure of the environment. This suggests that addiction may reflect, in part, drug-induced dysfunction in these systems. Here, we tested this hypothesis.
Objectives: This study aimed to test whether cocaine causes deficits in model-based behavior and learning independent of requirements for response inhibition or perception of costs or punishment.
Methods: We trained rats to self-administer sucrose or cocaine for 2 weeks. Four weeks later, the rats began training on a sensory preconditioning and inferred value blocking task. Like devaluation, normal performance on this task requires representations of the underlying task structure; however, unlike devaluation, it does not require either response inhibition or adapting behavior to reflect aversive outcomes.
Results: Rats trained to self-administer cocaine failed to show conditioned responding or blocking to the preconditioned cue. These deficits were not observed in sucrose-trained rats nor did they reflect any changes in responding to cues paired directly with reward.
Conclusions: These results imply that cocaine disrupts the operation of neural circuits that mediate model-based behavioral control.
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http://dx.doi.org/10.1007/s00213-013-3222-6 | DOI Listing |
Int J Mol Sci
January 2025
School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun 130117, China.
The aging process will lead to a gradual functional decline in the human body, and even accelerate a significantly increased risk of degenerative diseases. DNA methylation patterns change markedly with one's age, serving as a biomarker of biological age and closely linked to the occurrence and progression of age-related diseases. Currently, diagnostic methods for individual degenerative diseases are relatively mature.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Optoelectronics, Military University of Technology, Gen. S. Kaliskiego 2, Warsaw, 00-908, Poland.
Brain tumors present a significant global health challenge, and their early detection and accurate classification are crucial for effective treatment strategies. This study presents a novel approach combining a lightweight parallel depthwise separable convolutional neural network (PDSCNN) and a hybrid ridge regression extreme learning machine (RRELM) for accurately classifying four types of brain tumors (glioma, meningioma, no tumor, and pituitary) based on MRI images. The proposed approach enhances the visibility and clarity of tumor features in MRI images by employing contrast-limited adaptive histogram equalization (CLAHE).
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The partitioner learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification.
View Article and Find Full Text PDFBrain Inj
January 2025
Centers for Disease Control and Prevention (CDC), National Center for Injury Prevention and Control (NCIPC), Division of Injury Prevention, Atlanta, Georgia, USA.
Objectives: This manuscript describes traumatic brain injury (TBI)-related mortality in the United States during 2021, by geography, sociodemographic characteristics, mechanism of injury, and injury intent.
Method: Multivariable modeling of TBI mortality was performed to assess the simultaneous effect of multiple factors (geographic region, sex, race and ethnicity, and age) included in the model. Authors analyzed multiple-cause-of-death data from the National Vital Statistics System and included records when an International Classification of Diseases, Tenth Revision (ICD-10) underlying cause of death injury code, and a TBI-related ICD-10 diagnosis code were both listed.
J Trauma Acute Care Surg
December 2024
From the Department of Surgery, University of Cincinnati, Cincinnati, Ohio.
Background: Red blood cell (RBC) aggregation can be initiated by calcium and tissue factor, which may independently contribute to microvascular and macrovascular thrombosis after injury and transfusion. Previous studies have demonstrated that increased blood storage duration may contribute to thrombotic events. The aims of this study were to first determine the effect of blood product components, age, and hematocrit (HCT) on the aggregability of RBCs, followed by measurement of RBC aggregability in two specific injury models including traumatic brain injury (TBI) and hemorrhagic shock.
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