Biology subjects

Kofler, M.

Publications and source records attributed to Kofler, M..

4 recordsLinked to original sources

bioRxiv2025

Converting Spectral Evoked-to-Background Ratio intoTime-Domain Signal-to-Noise Ratio - Validation for HighFrequency Oscillations

N -Interval Fourier Transform Analysis (N -FTA) allows for spectral separation of an evoked target signal from uncorrelated background activity. It computes the frequency-dependent evoked-to-background ratio (EBR). The developed method allows for conversion of the spectral EBR into expected values for improvement of signal-to-noise ratio with progressing sweep count. Our study presents the mathematical basis for this conversion along with a validation for simulated and recorded data. The major findings are: O_LIThree factors enter the calculus of the expected SNR: the ratio of durations of the single sweep cycle and the evoked response window, the mean EBR in the spectral target band, and the sweep count. By conversion of all factors to dB, the expected SNR is defined by their sum. C_LIO_LIThe two fundamental theories governing the improvement of SNR with increasing sweep count, the law of large numbers and the uncertainty principle of signal processing, deliver identical results. C_LIO_LIConversion of EBR to expected SNR was successfully validated by simulated and recorded data and can be applied to all types of evoked data. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/662283v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@6f34d6org.highwire.dtl.DTLVardef@f5d607org.highwire.dtl.DTLVardef@1b6a18eorg.highwire.dtl.DTLVardef@1288e35_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

Spectral Separation of Evoked and Background Cortical Activity - Application to Short Latency Median Nerve Evoked Potentials

BackgroundSpectral analysis of repeatedly evoked potentials (EPs) is challenging since recordings contain a superposition of evoked signals and background activity. We developed a novel approach, N-interval Fourier Transform Analysis (N-FTA), which allows for reliable separation and accurate assessment of evoked and background spectral components. We applied this approach to spectral analysis of median nerve short latency EPs for identifying spectral bands of clinical relevance. MethodsWe performed right median nerve stimulation in two volunteers at 2.46 Hz and 3.95 Hz stimulation rate (600 and 1000 repetitions respectively). We applied N-FTA for splitting the periodically repeated evoked components from irregular background activity and investigated spectral components in the low, medium and high frequency (LF-, MF-, HF-) bands. We present a signal processing approach, which allows for accurately extracting diagnostically relevant features (signal morphology, latency and amplitude) using an 18 Hz to 240 Hz bandwidth. ResultsIn the LF-band < 10 Hz, evoked-to-background ratio (EBR) was below -15 dB due to the high level near DC background activity (1/f-activity, eye blinks,{theta} -band). Highest EBR was near -5 dB and obtained at a few tens of Hz. Relatively broad continuous segments of evoked activity were detected in the MF band. These frequencies of a few hundred Hz were linked to the signal segment between the N20 and P25 peaks in the time domain. High frequency oscillations (HFOs) near 600 Hz were approximately -25 dB below the background level and near the limit of the sensitivity of N-FTA. By subtracting stimulation artifacts and applying zero-phase filters it was possible to extract diagnostically relevant short latency EP features (signal morphology, latency and amplitude) only from the MF-band with a similar accuracy as a routinely used broad-band setting. HFOs displayed amplitudes of a few tenths of {micro}V. SummaryN-FTA allows for accurate, simultaneous spectral analysis of evoked and background activity in individual trials. The approach allowed for identifying target frequency bands of high evoked activity and for tailoring signal processing such, that morphology and latency can be obtained at a significantly reduced bandwidth. This should allow for development of more robust and faster recording techniques in the near future.

neuroscience↗

bioRxiv2020

Cumulative distribution functions: An alternative approach to examine the triggering of prepared motor actions in the StartReact effect

There has been much debate concerning whether startling sensory stimuli can activate a fast-neural pathway for movement triggering (StartReact) which is different from that of voluntary movements. Activity in sternocleidomastoid (SCM) electromyogram is suggested to indicate activation of this pathway. We evaluated whether SCM activity can accurately identify trials which may differ in their neurophysiological triggering and assessed the use of cumulative distribution functions (CDFs) of reaction time (RT) data to identify trials with the shortest RTs for analysis. Using recent datasets from the StartReact literature, we examined the relationship between RT and SCM activity. We categorised data into short/longer RT bins using CDFs and used linear mixed effects models to compare potential conclusions that can be drawn when categorising data on the basis of RT versus on the basis of SCM activity. The capacity of SCM to predict RT is task-specific, making it an unreliable indicator of distinct neurophysiological mechanisms. Classification of trials using CDFs is capable of capturing potential task- or muscle-related differences in triggering whilst avoiding the pitfalls of the traditional SCM activity based classification method. We conclude that SCM activity is not always evident on trials that show the early triggering of movements seen in the StartReact phenomenon. We further propose that a more comprehensive analysis of data may be achieved through the inclusion of CDF analyses. These findings have implications for future research investigating movement triggering as well as for potential therapeutic applications of StartReact.

neuroscience↗

bioRxiv2017

The Fes tyrosine kinase guides CD19 receptor fate in B-cells by shaping regulatory Src phosphorylation networks

The c-Fes protein tyrosine kinase is a proto-oncogene that can also act as a tumor suppressor. We implemented an unbiased phosphoproteomics-based analysis that establishes cognate kinase-substrate associations, and revealed that c-Fes directly phosphorylates Dok1, Ptpn18 and Sts1, facilitating recruitment of the Src inhibitory kinase Csk to these substrates. These interactions resulted in modulation of Src signaling following B-cell receptor (BCR) stimulation and subsequent alteration of the protein levels of CD19, a membrane-localized BCR co-receptor and emerging key protein affecting the development of B- and plasma cell-lymphoma. Strikingly, manipulating c-Fes expression levels drove opposing biological outcomes. Low-level exogenous c-Fes expression led to a strong increase in CD19 protein levels while high c-Fes expression abolished CD19 protein levels. Thus, we propose that a balance of c-Fes and Src signaling can regulate receptor maintenance, which may influence cellular outcome such as tumorigenesis or tumor suppression.

systems biology↗