Search results for "Brain state"
showing 6 items of 6 documents
The Importance of Cerebellar Connectivity on Simulated Brain Dynamics
2020
The brain shows a complex multiscale organization that prevents a direct understanding of how structure, function and dynamics are correlated. To date, advances in neural modeling offer a unique opportunity for simulating global brain dynamics by embedding empirical data on different scales in a mathematical framework. The Virtual Brain (TVB) is an advanced data-driven model allowing to simulate brain dynamics starting from individual subjects' structural and functional connectivity obtained, for example, from magnetic resonance imaging (MRI). The use of TVB has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting…
Cortical Temperature Change: A Tool for Modulating Brain States?12
2016
Reduction in temperature depolarizes neurons by a partial closure of potassium channels but decreases the vesicle release probability within synapses. Compared with cooling, neuromodulators produce qualitatively similar effects on intrinsic neuronal properties and synapses in the cortex. We used this similarity of neuronal action in ketamine-xylazine-anesthetized mice and non-anesthetized mice to manipulate the thalamocortical activity. We recorded cortical electroencephalogram/local field potential (LFP) activity and intracellular activities from the somatosensory thalamus in control conditions, during cortical cooling and on rewarming. In the deeply anesthetized mice, moderate cortical co…
An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo.
2021
Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal–hippocampal function, but data are dispersed and diverse. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) a…
Estimating brain load from the EEG.
2009
Modern work requires cognitively demanding multitasking and the need for sustained vigilance, which may result in work-related stress and may increase the possibility of human error. Objective methods for estimating cognitive overload and mental fatigue of the brain on-line, during work performance, are needed. We present a two-channel electroencephalography (EEG)–based index, theta Fz/alpha Pz ratio, potentially implementable into a compact wearable device. The index reacts to both acute external and cumulative internal load. The index increased with the number of tasks to be performed concurrently (p= 0.004) and with increased time awake, both after normal sleep (p= 0.002) and sleep restr…
Effects of complex movements on the brain as a result of increased decision-making
2019
Non-linearity is considered to be an essential property of complex systems. The associated high sensitivity of the result on the constraints leads to fundamental problems of a system description based on variables selected in the reductionist tradition. The attempt to compensate the problems by averaging data leads to the neglect of the individual and the moment. However, both is of enormous importance for effective therapy, training, and learning. The theory of differential learning suggests an alternative approach to dealing with these problems. With constantly changing complex whole-body movements, extensive decisions are demanded from the learner, which lead to brain states through an o…
A multi-scale approach for testing and detecting peaks in time series
2020
An approach is presented that combines a statistical test for peak detection with the estimation of peak positions in time series. Motivated by empirical observations in neuronal recordings, we aim at investigating peaks of different heights and widths. We use a moving window approach to compare the differences of estimated slope coefficients of local regression models. We combine multiple windows and use the global maximum of all different processes as a test statistic. After rejection, a multiple filter algorithm combines peak positions estimated from multiple windows. Analysing neuronal activity recorded in anaesthetized mice, the procedure could identify significant differences between …