Numerous studies demonstrated a close relationship between cannabis abuse and schizophrenia with similar impairments in cognitive processing, particularly in P300 generation. Recently, an (AAT)n triplet repeat polymorphism within the cannabinoid receptor gene CNR1 has been found to be associated with both schizophrenia and substance dependence, and to modulate the P300 potential. As previously reported, both acute oral Δ(9)-tetrahydrocannabinol (Δ(9)-THC), the main psychoactive constituent of cannabis, and standardized cannabis extract containing Δ(9)-THC and cannabidiol (CBD) revealed a significant reduction of P300 amplitudes in healthy subjects but did not show any differences among each other. The aim of this study was to investigate whether the (AAT)n polymorphism differentially modulates the effects of Δ(9)-THC and cannabis extract on P300 generation in 20 healthy volunteers during an auditory choice reaction task. For the >10/>10 genotype, there was a significant decrease of P300 amplitude as well as a significant prolongation of P300 latency under pure Δ(9)-THC but not under cannabis extract. Moreover, we found a significant correlation between the number of AAT repeats and P300 variables for the Δ(9)-THC condition. Our data thus indicate that the CNR1 gene seems to be involved in the regulation of the P300 wave as a marker of selective attention and working memory. Moreover, it appears that variations within CNR1 may differentially alter the sensitivity to the acute effects of cannabinoids on P300 generation in healthy subjects.
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http://dx.doi.org/10.1016/j.neulet.2011.04.003 | DOI Listing |
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Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address:
Psychophysiology
January 2025
Department of Psychology, Goethe University Frankfurt, Frankfurt Am Main, Germany.
According to the predictive processing framework, our brain constantly generates predictions based on past experiences and compares these predictions with incoming sensory information. When an event contradicts these predictions, it results in a prediction error (PE), which has been shown to enhance subsequent memory. However, the neural mechanisms underlying the influence of PEs on subsequent memory remain unclear.
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Computer and Information Sciences, University of Strathclyde, Glasgow, UK.
Measuring transient functional connectivity is an important challenge in electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high-temporal resolution is confounded by the inherent noise of the medium and the spurious nature of correlations computed over short temporal windows. We propose a methodology to overcome these problems called filter average short-term (FAST) functional connectivity.
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The Laboratory of Heart Development Research, College of Life Science, Hunan Normal University, Changsha 410081, China.
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