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Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences.

Fetterhoff D, Kraft RA, Sandler RA, Opris I, Sexton CA, Marmarelis VZ, Hampson RE, Deadwyler SA - Front Syst Neurosci (2015)

Bottom Line: Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses.These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality.Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience Program, Wake Forest School of Medicine Winston-Salem, NC, USA ; Department of Physiology and Pharmacology, Wake Forest School of Medicine Winston-Salem, NC, USA.

ABSTRACT
Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC), a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs), quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states.

No MeSH data available.


Related in: MedlinePlus

Correlations of fractality (Hurst exponent) and multifractality (singularity spectrum width) with spike train variability and frequency spectrum measures. Correlations (Spearman's rho) are plotted with 95% confidence intervals as error bars. (A) The Hurst exponent is negatively correlated with mean ISI and ISI STD during task recordings independent of drug condition—indicating that faster spiking and less variable firing patterns are correlated with greater LRTCs during the task only. (B) The coefficient of variation (CV) was positively correlated with multifractal complexity (width)—indicating “burstiness” correlates with multifractality. Delta power was positively correlated with multifractality (width) during the task phase, regardless of drug condition.
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Figure 9: Correlations of fractality (Hurst exponent) and multifractality (singularity spectrum width) with spike train variability and frequency spectrum measures. Correlations (Spearman's rho) are plotted with 95% confidence intervals as error bars. (A) The Hurst exponent is negatively correlated with mean ISI and ISI STD during task recordings independent of drug condition—indicating that faster spiking and less variable firing patterns are correlated with greater LRTCs during the task only. (B) The coefficient of variation (CV) was positively correlated with multifractal complexity (width)—indicating “burstiness” correlates with multifractality. Delta power was positively correlated with multifractality (width) during the task phase, regardless of drug condition.

Mentions: We tested whether LRTCs were associated with changes in variability or frequency content using correlation. A strong relationship was found between the Hurst exponent and mean ISI during task recordings (Figure 9A), indicating that LRTCs are more prominent with shorter average ISIs (i.e., when neurons fire more frequently). The Hurst exponent was negatively correlated with ISI STD during the task (Figure 9A), indicating that LRTCs and self-similarity occur more frequently when neurons fire with less variable ISIs. Both of these correlations were weaker during the resting phase recordings (pre- and post-task), suggesting a task-specific relationship of fractal vs. firing rate and variability patterns. None of the other three relationships were strong, which indicate that LRTCs and self-similarity quantified by the Hurst exponent are independent from CV, theta and delta power.


Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences.

Fetterhoff D, Kraft RA, Sandler RA, Opris I, Sexton CA, Marmarelis VZ, Hampson RE, Deadwyler SA - Front Syst Neurosci (2015)

Correlations of fractality (Hurst exponent) and multifractality (singularity spectrum width) with spike train variability and frequency spectrum measures. Correlations (Spearman's rho) are plotted with 95% confidence intervals as error bars. (A) The Hurst exponent is negatively correlated with mean ISI and ISI STD during task recordings independent of drug condition—indicating that faster spiking and less variable firing patterns are correlated with greater LRTCs during the task only. (B) The coefficient of variation (CV) was positively correlated with multifractal complexity (width)—indicating “burstiness” correlates with multifractality. Delta power was positively correlated with multifractality (width) during the task phase, regardless of drug condition.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585000&req=5

Figure 9: Correlations of fractality (Hurst exponent) and multifractality (singularity spectrum width) with spike train variability and frequency spectrum measures. Correlations (Spearman's rho) are plotted with 95% confidence intervals as error bars. (A) The Hurst exponent is negatively correlated with mean ISI and ISI STD during task recordings independent of drug condition—indicating that faster spiking and less variable firing patterns are correlated with greater LRTCs during the task only. (B) The coefficient of variation (CV) was positively correlated with multifractal complexity (width)—indicating “burstiness” correlates with multifractality. Delta power was positively correlated with multifractality (width) during the task phase, regardless of drug condition.
Mentions: We tested whether LRTCs were associated with changes in variability or frequency content using correlation. A strong relationship was found between the Hurst exponent and mean ISI during task recordings (Figure 9A), indicating that LRTCs are more prominent with shorter average ISIs (i.e., when neurons fire more frequently). The Hurst exponent was negatively correlated with ISI STD during the task (Figure 9A), indicating that LRTCs and self-similarity occur more frequently when neurons fire with less variable ISIs. Both of these correlations were weaker during the resting phase recordings (pre- and post-task), suggesting a task-specific relationship of fractal vs. firing rate and variability patterns. None of the other three relationships were strong, which indicate that LRTCs and self-similarity quantified by the Hurst exponent are independent from CV, theta and delta power.

Bottom Line: Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses.These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality.Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience Program, Wake Forest School of Medicine Winston-Salem, NC, USA ; Department of Physiology and Pharmacology, Wake Forest School of Medicine Winston-Salem, NC, USA.

ABSTRACT
Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC), a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs), quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states.

No MeSH data available.


Related in: MedlinePlus