Quantification and automatized adaptive detection of in vivo and in vitro neuronal bursts based on signal complexity.

2015

In this paper, we propose employing entropy values to quantify action potential bursts in electrophysiological measurements from the brain and neuronal cultures. Conventionally in the electrophysiological signal analysis, bursts are quantified by means of conventional measures such as their durations, and number of spikes in bursts. Here our main aim is to device metrics for burst quantification to provide for enhanced burst characterization. Entropy is a widely employed measure to quantify regularity/complexity of time series. Specifically, we investigate the applicability and differences of spectral entropy and sample entropy in the quantification of bursts in in vivo rat hippocampal meas…

Disrupting neural activity related to awake-state sharp wave-ripple complexes prevents hippocampal learning

2012

Oscillations in hippocampal local-field potentials (LFPs) reflect the crucial involvement of the hippocampus in memory trace formation: theta (4–8 Hz) oscillations and ripples (~200 Hz) occurring during sharp waves are thought to mediate encoding and consolidation, respectively. During sharp wave-ripple complexes (SPW-Rs), hippocampal cell firing closely follows the pattern that took place during the initial experience, most likely reflecting replay of that event. Disrupting hippocampal ripples using electrical stimulation either during training in awake animals or during sleep after training retards spatial learning. Here, adult rabbits were trained in trace eyeblink conditioning, a hippoc…

Human Pluripotent Stem Cell-Derived Neuronal Networks:Their Electrical Functionality and Usability for Modelling and Toxicology

2011

Micro electrode array (MEA)-based platforms have been used to study neuronal networks for decades. The used cells have, for the most part, been rodent primary neurons. The gained knowledge has indeed increased the understanding of neuronal network development and maturation both in vitro and in vivo. If aiming to understand the development of human brain, however, the used cell type should preferably be of human origin due to difficult interpolation from the rodent cell data. In addition, the development of functional human neuronal networks would open up a new era for, e.g., toxicology testing, drug screening and disease modelling. The use of MEA with bioelectrically active cells was first…

Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

2017

Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…

The role of adolescents' temperament in their positive and negative emotions as well as in psychophysiological reactions during achievement situations

2019

Abstract This study examined the role of adolescents' (n = 190) temperament in their emotional reactions in achievement situations. Adolescents rated their temperament (i.e., surgency/extraversion, negative affectivity, effortful control) and completed achievement tasks in Grade 6. They also reported their emotions before and during challenging and non-challenging tasks. In addition, adolescents' autonomic nervous system reactions (i.e., skin conductance levels) were recorded. The results showed that high effortful control was related to higher levels of positive emotions independent of the degree of task difficulty. Low negative affectivity and high effortful control were related to lower …

Corrigendum: Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements

2020

Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony

2016

In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relati…

Erratum to ‘‘Attenuated carbohydrate and gill Na+, K+-ATPase stress responses in whitefish caged near bleached kraft mill discharges’’[Ecotoxicol. En…

2003

Phase matters: responding to and learning about peripheral stimuli depends on hippocampal θ phase at stimulus onset.

2015

Hippocampal θ (3–12 Hz) oscillations are implicated in learning and memory, but their functional role remains unclear. We studied the effect of the phase of local θ oscillation on hippocampal responses to a neutral conditioned stimulus (CS) and subsequent learning of classical trace eyeblink conditioning in adult rabbits. High-amplitude, regular hippocampal θ-band responses (that predict good learning) were elicited by the CS when it was timed to commence at the fissure θ trough (Trough group). Regardless, learning in this group was not enhanced compared with a yoked control group, possibly due to a ceiling effect. However, when the CS was consistently presented to the peak of θ (Peak group…