ArticleJournal of neuroscience methods2015
Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ⁹-tetrahydrocannabinol administration.
Article in Journal of neuroscience methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- The absence of Neuroligin-1 shapes wake/sleep architecture, rhythmic and arrhythmic activities of the electrocorticogram in female mice.Molecular brain · 2025Article
- Morphology and Fractal-Based Classifications of Neurons and Microglia in Two and Three Dimensions.Advances in neurobiology · 2024Review
- Altered Brain Criticality in Schizophrenia: New Insights From Magnetoencephalography.Frontiers in neural circuits · 2022Article
- Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Adolescent ΔFrontiers in psychiatry · 2020Article
- The informational entropy endowed in cortical oscillations.Cognitive neurodynamics · 2018Article
- Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3.PLoS computational biology · 2017Article
- The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus.Journal of computational neuroscience · 2017Article
- Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences.Frontiers in systems neuroscience · 2015Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMultifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. NEW
methodWavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain-computer interfaces and nonlinear neuronal models.
resultsNeurons involved in memory processing ("Functional Cell Types" or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid type-1 receptor (CB1R) partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. COMPARISON WITH EXISTING
methodsWLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events.
conclusionz-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain-computer interfaces.
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