Biology subjects

Sviatko, K.

Publications and source records attributed to Sviatko, K..

6 recordsLinked to original sources

bioRxiv2023

Altered reactivity to threatening stimuli in Drosophila models of Parkinson's disease, revealed by a trial-based assay

The fruit fly Drosophila melanogaster emerges as an affordable, genetically tractable model of behavior and brain diseases. However, despite the surprising level of evolutionary conservation from flies to humans, significant genetic, circuit-level and behavioral differences hinder the interpretability of fruit fly models for human disease. Therefore, to allow a more direct fly-versus-human comparison, we surveyed the rarely exploited, rich behavioral repertoire of fruit flies with genetic alterations relevant to Parkinsons disease (PD), including overexpression of human mutant Parkin or -synuclein proteins and mutations in dopamine receptors. Flies with different genetic backgrounds displayed variable behaviors, including freezing, slowing and running, in response to predator-mimicking passing shadows used as threatening stimuli in a single-animal trial-based assay. We found that the expression of human mutant Parkin in flies resulted in reduced walking speed and decreased reactivity to passing shadows. Flies with dopamine receptor mutations showed similar alterations, consistent with the motor and cognitive deficits typical in humans with PD. We also found age-dependent trends in behavioral choice during the fly lifespan, while dopamine receptor mutant flies maintained their decreased general reactivity throughout all age groups. Our data demonstrate that single-trial behavioral analysis can reveal subtle behavioral changes in mutant flies that can be used to further our understanding of disease pathomechanisms and help gauge the validity of genetic Drosophila models of neurodegeneration, taking us one step closer to bridging the gap in fly-to-human translation.

neuroscience↗

bioRxiv2022

Cholinergic neuronal responses to probabilistic outcome-predicting stimuli follow a weighed, unsigned prediction error model and anticipate behavioral responses

Basal forebrain cholinergic neurons (BFCNs) play an important role in associative learning, suggesting that BFCNs may participate in processing sensory stimuli that predict future outcomes. However, little is known about how BFCNs respond to outcome-predictive sensory cues and the impact of outcome probabilities on BFCN responses has not been explored. Therefore, we performed bulk calcium imaging and recorded spiking output of identified cholinergic neurons from the basal forebrain of mice performing a probabilistic Pavlovian cued outcome task that allowed us to control the predictive strength of cue stimuli. BFCNs responded strongly to sensory cues predicting likely reward, while little response was observed for cues that were rarely paired with reward. Reward delivery led to the activation of BFCNs, with less expected rewards eliciting a stronger response, while air puff punishments also evoked positive-going responses from BFCNs. We propose that BFCNs differentially weigh predictions of positive and negative reinforcement, reflecting divergent relative salience of forecasting appetitive and aversive outcomes, in accordance with a simple reinforcement learning model of a weighed, unsigned prediction error. Finally, the extent of cholinergic activation after cue stimuli predicted subsequent decision speed, suggesting that the expectation-gated cholinergic firing is instructive to reward-seeking behaviors.

neuroscience↗

bioRxiv2021

Microglia control cerebral blood flow and neurovascular coupling via P2Y12R-mediated actions

Microglia, the main immunocompetent cells of the brain regulate neuronal function in health and disease, but their contribution to cerebral blood flow (CBF) remained elusive. Here we identify microglia as important modulators of CBF both under physiological conditions and during hypoperfusion. We show that microglia establish direct purinergic contacts with cells in the neurovascular unit that shape cerebral perfusion in both mice and humans. Surprisingly, the absence of microglia or blockade of microglial P2Y12 receptor (P2Y12R) substantially impairs neurovascular coupling in the barrel cortex after whisker stimulation. We also reveal that hypercapnia, which is associated with acidification, induces microglial adenosine production, while depletion of microglia reduces brain pH and impairs hypercapnia-induced vasodilation. Furthermore, the absence or dysfunction of microglia markedly impairs adaptation to hypoperfusion via P2Y12R after transient unilateral common carotid artery occlusion, which is also influenced by CX3CR1-mediated actions. Thus, our data reveal a previously unrecognized role for microglia in CBF regulation with broad implications for common neurological diseases.

neuroscience↗

bioRxiv2021

Huygens synchronization of medial septal pacemaker neurons generates hippocampal theta oscillation

Episodic learning and memory retrieval are critically dependent on a hippocampal 4-12 Hz oscillatory clock signal, the theta oscillation. This clock is largely externally paced, by a network of GABAergic neurons in the medial septum (MS). Theoretical studies suggested a range of hypotheses how this network may achieve theta synchrony; however, experimental evidence is still lacking. By recording multiple single MS neurons and hippocampal local field potential oscillations simultaneously, with both acute and chronically implanted silicon probes, we show that MS pacemaker units oscillate at individual frequencies within the theta range in rodents. Synchronization of MS neuron frequencies, accompanied by an elevation of firing rates, was found to parallel hippocampal theta formation in multiple rodent model systems. This suggests a general mechanism for theta synchronization, akin to the synchronization of weakly coupled pendulum clocks observed by Huygens in the 17th century. We optogenetically identified the MS pacemaker units as parvalbumin-expressing GABAergic neurons, while the previously enigmatic MS glutamatergic neurons were mostly theta-activated non-rhythmic cells. Our data were consistent with a network model of partially connected single-compartment inhibitory pacemaker neurons, in which synchronization and de-synchronization in the frequency domain upon waxing and waning tonic excitatory drive was sufficient to toggle MS network output between theta and non-theta states. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for the countless examples of synchronization processes in the central nervous system from Nematoda to Anthropoda to Chordate and Vertebrate phyla.

neuroscience↗

bioRxiv2020

In Vivo Localization of Deep Brain Implants in Mice

Electrophysiology provides a direct readout of neuronal activity at a temporal precision only limited by the sampling rate. However, interrogating deep brain structures, implanting multiple targets or aiming at unusual angles still poses significant challenges even for expert operators, and errors are only discovered by post-hoc histological reconstruction. Here, we propose a method combining the high-resolution information about bone landmarks provided by micro-CT scanning with the soft tissue contrast of the MRI, which allowed us to precisely localize electrodes and optic fibers in mice in vivo. This enables arbitrating the success of implantation directly after surgery with a precision comparable to the gold standard histological reconstruction. Adjustment of the recording depth with electrode microdrives or early termination of unsuccessful experiments saves many working hours, while fast 3-dimensional feedback helps surgeons to avoid systematic errors. Increased aiming precision will allow more precise targeting of small or deep brain nuclei and multiple targeting of specific cortical layers.

neuroscience↗

bioRxiv2018

Open source toolkit for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations

Understanding how the brain controls behavior requires observing and manipulating neural activity in awake behaving animals. Neuronal firing is timed at millisecond precision. Therefore, to decipher temporal coding, it is necessary to monitor and control animal behavior at the same level of temporal accuracy. However, it is technically challenging to deliver sensory stimuli and reinforcers as well as to read the behavioral responses they elicit with millisecond precision. Presently available commercial systems often excel in specific aspects of behavior control, but they do not provide a customizable environment allowing flexible experimental design while maintaining high standards for temporal control necessary for interpreting neuronal activity. Moreover, delay measurements of stimulus and reinforcement delivery are largely unavailable. We combined microcontroller-based behavior control with a sound delivery system for playing complex acoustic stimuli, fast solenoid valves for precisely timed reinforcement delivery and a custom-built sound attenuated chamber using high-end industrial insulation materials. Together this setup provides a physical environment to train head-fixed animals, enables calibrated sound stimuli and precisely timed fluid and air puff presentation as reinforcers. We provide latency measurements for stimulus and reinforcement delivery and an algorithm to perform such measurements on other behavior control systems. Combined with electrophysiology and optogenetic manipulations, the millisecond timing accuracy will help interpret temporally precise neural signals and behavioral changes. Additionally, since software and hardware provided here can be readily customized to achieve a large variety of paradigms, these solutions enable an unusually flexible design of rodent behavioral experiments.

neuroscience↗