Biology subjects

Marbach, F.

Publications and source records attributed to Marbach, F..

3 recordsLinked to original sources

bioRxiv2023

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animals performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouses choice could be reliably decoded from the recorded neural activity. Our findings suggest that in spite of modulation of auditory cortical activity by task priors, auditory cortex does not represent sufficient information about these priors to exploit them optimally and that decisions in this task require that rapidly changing sensory information be combined with more slowly varying task information extracted and represented in brain regions other than auditory cortex.

neuroscience↗

bioRxiv2023

LZTR1 polymerization provokes cardiac pathology in recessive Noonan syndrome

Noonan syndrome patients harboring causative variants in LZTR1 are particularly at risk to develop severe and early-onset hypertrophic cardiomyopathy. However, the underling disease mechanisms of LZTR1 missense variants driving the cardiac pathology are poorly understood. Hence, therapeutic options for Noonan syndrome patients are limited. In this study, we investigated the mechanistic consequences of a novel homozygous causative variant LZTR1L580Pby using patient-specific and CRISPR/Cas9-corrected iPSC-cardiomyocytes. Molecular, cellular, and functional phenotyping in combination with in silico prediction of protein complexes uncovered a unique LZTR1L580P-specific disease mechanism provoking the cardiac hypertrophy. The homozygous variant was predicted to alter the binding affinity of the dimerization domains facilitating the formation of linear LZTR1 polymer chains. The altered polymerization resulted in dysfunction of the LZTR1-cullin 3 ubiquitin ligase complexes and subsequently, in accumulation of RAS GTPases, thereby provoking global pathological changes of the proteomic landscape ultimately leading to cellular hypertrophy. Furthermore, our data showed that cardiomyocyte-specific MRAS degradation is mediated by LZTR1 via the autophagosome, whereas RIT1 degradation is mediated by both LZTR1-dependent and LZTR1-independent proteasomal pathways. Importantly, uni-or biallelic genetic correction of the LZTR1L580P missense variant rescued the molecular and cellular disease-associated phenotype, providing proof-of-concept for CRISPR-based gene therapies.

cell biology↗

bioRxiv2022

Action prediction error: a value-free dopaminergic teaching signal that drives stable learning

Animals choice behavior is characterized by two main tendencies: taking actions that led to rewards and repeating past actions. Theory suggests these strategies may be reinforced by different types of dopaminergic teaching signals: reward prediction error (RPE) to reinforce value-based associations and movement-based action prediction errors to reinforce value-free repetitive associations. Here we use an auditory-discrimination task in mice to show that movement-related dopamine activity in the tail of the striatum encodes the hypothesized action prediction error signal. Causal manipulations reveal that this prediction error serves as a value-free teaching signal that supports learning by reinforcing repeated associations. Computational modeling and experiments demonstrate that action prediction errors alone cannot support reward-guided learning but when paired with the RPE circuitry they serve to consolidate stable sound-action associations in a value-free manner. Together we show that there are two types of dopaminergic prediction errors that work in tandem to support learning.

neuroscience↗