Biology subjects

Prada, J.

Publications and source records attributed to Prada, J..

4 recordsLinked to original sources

bioRxiv2022

Modelling non-local neural information processing in the brain

The representation of the surrounding world emerges through integration of sensory information and actions. We present a novel neural model which implements non-local, parallel information processing on a neocolumnar architecture with lateral interconnections. Information is integrated into a holographic wave interference pattern. We compare the simulated in silico pattern with observed in vivo invasive and non-invasive electrophysiological data in human and non-human primates. Our model replicates the modulation of neural high-frequency activity during visual perception showing that phase-locked low and high-frequency oscillations self-organize efficiently and carry high information content. The simulation further models how criticality (high content) of information processing emerges given a sufficiently high number of correlated neurons. Non-local information processing, forming one holographic wave pattern, suggests a platform for emergence of conscious perception. One sentence summarySimulated non-local information processing on a neocolumnar architecture models well multiple electrophysiological observations of brain activity, including high-frequency activity during visual perception in primates.

neuroscience↗

bioRxiv2021

How biological cells including platelets and megakaryocytes decide complex problems fast but risky

Short AbstractMathematical decision processes are accurate but sometimes take very long time or simply do not happen. Decisions in biology happen fast and driven by evolution, optimizing survival chances. This results in stochastic decisions with on average good adaptation to the environment but an inherent risk of individual errors e.g. developing cancer during cell regeneration. We calculate and show in platelets and megakaryocytes how cellular decision processes increases risk for errors and inflammation. Short cut solutions adapted from nature improve computer strategies for protein folding and network decision processes. Complex problems are not always solved in foreseeable time, instead the fast solutions in biology speed up errors everywhere including biochemical aging of blood vessels, misfolded proteins, mis-programmed cells, cancer and heart failure. One sentence abstractWe investigate in biological networks how complex decision problems are mastered not by an accurate but unforeseeable long mathematical search but rather pragmatic and fast, with an inherent risk of error, a basis for inflammation and cancer.

bioinformatics↗

bioRxiv2020

Transmission and control strategies for porcine reproductive and respiratory syndrome virus

Many aspects of the porcine reproductive and respiratory syndrome virus (PRRSV) between-farm transmission dynamics have been investigated, but uncertainty remains about the significance of farm type and different transmission routes on PRRSV spread. We developed a stochastic epidemiological model calibrated on weekly PRRSV outbreaks accounting for the population dynamics in different pig production phases, breeding herds, gilt development units, nurseries, and finisher farms, of three hog producer companies. Our model accounted for indirect contacts by the close distance between farms (local transmission), between-farm animal movements (pig flow), and reinfection of sow farms (re-break). The fitted model was used to examine the effectiveness of vaccination strategies and complementary interventions such as enhanced PRRSV detection and vaccination delays and forecast the spatial distribution of PRRSV outbreak. The results of our analysis indicated that for sow farms, 59% of the simulated infections were related to local transmission (e.g. airborne, feed deliveries, shared equipment) whereas 36% and 5% were related to animal movements and re-break, respectively. For nursery farms, 80% of infections were related to animal movements and 20% to local transmission; while at finisher farms it was split between local transmission and animal movements. Assuming that the current vaccines are 1% effective in mitigating between-farm PRRSV transmission, weaned pigs vaccination would reduce the incidence of PRRSV outbreaks by 2%, indeed under any scenario vaccination alone was insufficient for completely controlling PRRSV spread. Our results also showed that intensifying PRRSV detection and/or vaccination pigs at placement increased the effectiveness of all simulated vaccination strategies. Our model reproduced the incidence and PRRSV spatial distribution; therefore, this model could also be used to map current and future farms at-risk. Finally, this model could be a useful tool for veterinarians, allowing them to identify the effect of transmission routes and different vaccination interventions to control PRRSV spread.

ecology↗

bioRxiv2019

Quantifying and modelling non-local information processing of associative brain regions

Short abstractBrain world representation emerges not by philosophy but from integrating simple followed by more complex actions (due to drives, instincts) with sensory feedback and inputs such as rewards. Our simulation provides this world representation holistically by identical information encoded as holographic wave patterns for all associative cortex regions. Observed circular activation in cell culture experiments provides building blocks from which such an integrative circuit can evolve just by excitation and inhibition transfer to neighbouring neurons. Large-scale grid-computing of the simulation brought no new emergent phenomena but rather linear gains and losses regarding performance. The circuit integrates perceptions and actions. The resulting simulation compares well with data from electrophysiology, visual perception tasks, and oscillations in cortical areas. Non-local, wave-like information processing in the cortex agrees well with EEG observations such as cortical alpha, beta, and gamma oscillations. Non-local information processing has powerful emergent properties, including key features of conscious information processing.

neuroscience↗