Biology subjects

Miletic, S.

Publications and source records attributed to Miletic, S..

12 recordsLinked to original sources

bioRxiv2024

Joint models reveal human subcortical underpinnings of choice and learning behaviour

Decision making and learning processes together enable adaptive goal-oriented behaviour. Animal studies demonstrated the importance of subcortical regions in these cognitive processes, but the human subcortical contributions remain poorly characterised. Here, we study choice and learning processes in the human subcor-tex, using a tailored ultra-high field 7 T fMRI imaging protocol combined with joint models. Joint models provide unbiased estimates of brain-behaviour rela-tions by simultaneously including behavioural and neural data at the participant and group level. Results demonstrate relations between subcortical regions and the adjustment of decision urgency. Value-related BOLD differences were found with opposite BOLD polarity in different parts of the striatum. Multiple sub-cortical regions showed BOLD signatures of reward prediction error processing, but contrary to expectations, these did not include the dopaminergic midbrain. Combined, this study characterises the human subcortical contributions to choice and learning, and demonstrates the feasibility and value of joint modelling in facilitating our understanding of brain-behaviour relationships.

neuroscience↗

bioRxiv2024

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory

Subcortical nuclei of the ascending arousal system play an important role in regulating brain and cognition. However, functional MRI of these nuclei in humans involves unique challenges due to their size and location deep within the brain. Here, we used ultra-high-field MRI and other methodological advances to investigate the activity of six subcortical nuclei during reward anticipation and memory encoding: the locus coeruleus, basal forebrain, median and dorsal raphe nuclei, substantia nigra and ventral tegmental area. Participants performed a monetary incentive delay task, which successfully induced a state of reward anticipation, and a 24-hour delayed surprise memory test. Region-of-interest analyses revealed that activity in all subcortical nuclei increased in anticipation of potential rewards as opposed to neutral outcomes. In contrast, activity in none of the nuclei predicted memory performance 24 hours later. These findings provide new insights into the cognitive functions that are supported by the human ascending arousal system.

neuroscience↗

bioRxiv2024

De novo design of potent inhibitors of Clostridioides difficile toxin B

Clostridioides difficile is a major cause of secondary disease in hospitals. During infection, C. difficile toxin B drives disease pathology. Here we use deep learning and Rosetta-based approaches to de novo design small proteins that block the entry of TcdB into cells. These molecules have binding affinities and neutralization IC50s in the pM range and are compelling candidates for further clinical development. By directly targeting the toxin rather than the pathogen, these molecules have the advantage of immediate cessation of disease and lower selective pressure for escape compared to conventional antibiotics. As C. difficile infects the colon, the protease and pH resistance of the designed proteins opens the door to oral delivery of engineered biologics. Significance statementC. difficile infection (CDI) is a major public health concern with over half a million cases in the United States annually resulting in 30,000 deaths. Current therapies are inadequate and frequently result in cycles of recurrent infection (rCDI). Progress has been made in the development of anti-toxin mAb therapies that can reduce the rate of rCDI, but these remain unaffordable and out of reach for many patients. Using de novo protein design, we developed small protein inhibitors targeting two independent receptor binding sites on the toxin that drives pathology during CDI. These molecules are high affinity, potently neutralizing and stable in simulated intestinal fluid, making them strong candidates for the clinical development of new CDI therapies.

microbiology↗

bioRxiv2024

The ageing stopping network: Regional and network changes in the IFG, preSMA, and STN across the adult lifespan

Response inhibition, the cancellation of planned movement, is essential for everyday motor control. Extensive fMRI and brain stimulation research provides evidence for the crucial role of a number of cortical and subcortical regions in response inhibition, including the subthalamic nucleus (STN), pre-supplementary motor area (preSMA), and the inferior frontal gyrus (IFG). Current models assume that these regions operate as a network, with action cancellation originating in the cortical areas and then executed rapidly via the subcortex. Response inhibition slows in older age, a change that has been attributed to deterioration or changes in the connectivity and integrity of this network. However, previous research has mainly used whole-brain approaches when investigating changes in structural connectivity across the lifespan, or have used simpler measures to investigate structural ageing. Here, we used high-resolution quantitative and diffusion MRI to extensively examine the anatomical changes that occur in this network across the lifespan. We found substantial changes in iron concentration in these tracts, increases in the apparent diffusion coefficient, and some evidence for demyelination. Conversely, we found very little evidence for age-related anatomical changes in the regions themselves. We propose that some of the functional changes observed in these regions in older adult populations (e.g., increased BOLD recruitment) are a reflection of alterations to the connectivity between the regions, rather than localised regional change.

neuroscience↗

bioRxiv2024

Exploring working memory updating processes of the human subcortex using 7T MRI

A growing body of research suggests that dopamine is involved in working memory updating and that the striatum takes up a critical role in the subprocess of working memory gating (Braver & Cohen, 2000; Cools & DEsposito, 2011; DArdenne et al., 2012; Jongkees, 2020). In this study, we investigated subcortical-in particular, possible dopaminergic-involvement in working memory updating subprocesses using the reference-back task and ultra-high field 7 Tesla fMRI. Using a scanning protocol optimized for BOLD-sensitivity in the subcortex, we found no evidence of subcortical activation during working memory gate opening, predominantly activations in frontoparietal network regions, which challenges the idea of a striatal gating mechanism. However, during gate closing, subcortical activation was observed. Furthermore, a ready-to-update mode demonstrated large-spread subcortical activation, including basal ganglia nuclei, suggesting that the basal ganglia are engaged in general updating processes rather than specifically controlling the working memory gate. Moreover, substituting new information into working memory elicited activation in dopamine-producing midbrain regions along with the striatum, thalamus, and prefrontal cortex, indicating engagement of the basal ganglia-thalamo-cortical loop possibly driven by (potential) dopaminergic activity. These findings expand our understanding of subcortical regions involved in working memory updating, shifting the focus from gate opening to substitution as a midbrain-driven updating process.

neuroscience↗

bioRxiv2023

The canonical stopping network: Revisiting the role of the subcortex in response inhibition

This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task (SST) to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites. This meta-analysis, along with other recent aggregatory fMRI studies, does not find evidence for the innervation of the hyperdirect or indirect cortico-basal-ganglia pathways in successful response inhibition. What we do find, is large subcortical activity profiles for failed stop trials. We discuss possible explanations for the mismatch of findings between the fMRI results presented here and results from other research modalities that have implicated nodes of the basal ganglia in successful inhibition. We also highlight the substantial effect smoothing can have on the conclusions drawn from task-specific GLMs. First and foremost, this study presents a proof of concept for meta-analytical methods that enable the merging of extensive, unprocessed or unreduced datasets. It demonstrates the significant potential that open-access data sharing can offer to the research community. With an increasing number of datasets being shared publicly, researchers will have the ability to conduct meta-analyses on more than just summary data.

neuroscience↗

bioRxiv2021

No evidence for three functionally specialized subregions in the subthalamic nucleus: A model-based 7 T fMRI study

The subthalamic nucleus (STN) is a small, subcortical brain structure. It is a target for deep brain stimulation, an invasive treatment that reduces motor symptoms of Parkinsons disease. Side effects of DBS are commonly explained using the tripartite model of STN organization, which proposes three functionally distinct subregions in the STN specialized in cognitive, limbic, and motor processing. However, evidence for the tripartite model exclusively comes from anatomical studies and functional studies using clinical patients. Here, we provide the first experimental tests of the tripartite model in healthy volunteers using ultra-high field 7 Tesla (T) functional magnetic resonance imaging (fMRI). 34 participants performed a random-dot motion decision-making task with a difficulty manipulation and a choice payoff manipulation aimed to differentially affect cognitive and limbic networks. Moreover, participants responded with their left and right index finger, differentially affecting motor networks. We analysed BOLD signal in three subregions of equal volume of the STN along the dorsolateral-ventromedial axis, identified using manually delineated high resolution anatomical images. Our results indicate that all segments responded equally to the experimental manipulations, and did not support the tripartite model.

neuroscience↗

bioRxiv2021

Charting human subcortical maturation with in vivo 7 T MRI

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

neuroscience↗

bioRxiv2020

Substrate-engaged type III secretion system structures reveal gating mechanism for unfolded protein translocation

Many bacterial pathogens strictly rely on the activity of type III secretion systems (T3SSs) to secrete and translocate effector proteins in order to establish infection. The central component of T3SSs is the needle complex, a supramolecular machine which assembles a continuous conduit crossing the bacterial envelope and the host cell membrane to allow bacterial effectors to gain entry into the host cell cytoplasm to modulate signal transduction processes. Disruption of this process impairs pathogenicity, providing an avenue for antimicrobial design. However, the molecular principles underlying T3 secretion remain elusive. Here, we report the first structure of an active Salmonella enterica sv. Typhimurium needle complex engaged with the late effector protein SptP in two functional states, revealing the complete 800[A]-long secretion conduit and unravelling the critical role of the export apparatus (EA) subcomplex in T3 secretion. Unfolded substrates enter the EA through a hydrophilic constriction formed by SpaQ proteins, which enables side chain-independent transport, explaining heterogeneity and structural disorder of signal sequences in T3SS effector proteins. Above, a methionine gasket formed by SpaP proteins functions as a gate that dilates to accommodate substrates but prevents leaky pore formation to maintain the physical boundaries of compartments separated by a biological membrane. Following gate penetration, a moveable SpaR loop first folds up to then act akin to a linear ratchet to steer substrates through the needle complex. Together, these findings establish the molecular basis for substrate translocation through T3SSs, improving our understanding of bacterial pathogenicity and motility of flagellated bacteria, and paves the way for the development of novel concepts combating bacterial infections.

molecular biology↗

bioRxiv2020

A new model of decision processing in instrumental learning tasks

Learning and decision making are interactive processes, yet cognitive modelling of error-driven learning and decision making have largely evolved separately. Recently, evidence accumulation models (EAMs) of decision making and reinforcement learning (RL) models of error-driven learning have been combined into joint RL-EAMs that can in principle address these interactions. However, we show that the most commonly used combination, based on the diffusion decision model (DDM) for binary choice, consistently fails to capture crucial aspects of response times observed during reinforcement learning. We propose a new RL-EAM based on an advantage racing diffusion (ARD) framework for choices among two or more options that not only addresses this problem but captures stimulus difficulty, speed-accuracy trade-off, and stimulus-response-mapping reversal effects. The RL-ARD avoids fundamental limitations imposed by the DDM on addressing effects of absolute values of choices, as well as extensions beyond binary choice, and provides a computationally tractable basis for wider applications.

neuroscience↗

bioRxiv2019

Structural control for the coordinated assembly into functional pathogenic type-3 secretion systems

Functional injectisomes of the type-3 secretion system assemble into highly defined and stoichiometric bacterial molecular machines essential for infecting human and other eukaryotic cells. However, the mechanism that governs the regulated step-wise assembly process from the nucleation-phase, to ring-assembly, and the filamentous phase into a membrane embedded needle complex is unclear. We here report that the formation of a megadalton-sized needle complexes from Salmonella enterica serovar Typhimurium (SPI-1, Salmonella pathogenicity island-1) with proper stoichiometries is highly structurally controlled competing against the self-assembly propensity of injectisome components, leading to a highly unusual structurally-pleiotropic phenotype. The structure of the entire needle complex from pathogenic injectisomes was solved by cryo electron microscopy, focused refinements (2.5-4 [A]) and co-variation analysis revealing an overall asymmetric arrangement containing cyclic, helical, and asymmetric sub-structures. The centrally located export apparatus assembles into a conical, pseudo-helical structure and provides a structural template that guides the formation of a 24-mer cyclic, surrounding ring, which then serves as a docking interface comprising three different conformations for sixteen N-terminal InvG subunits of the outer secretin ring. Unexpectedly, the secretin ring excludes the 16th protein chain at the C-terminal outer ring, resulting in a pleiotropic 16/15-mer ring and consequently to an overall 24:16/15 basal body structure. Finally, we report how the transition from the pseudo-helical export apparatus into the helical filament is structurally resolved to generate the protein secretion channel, which provides the structural basis to restrict access of unfolded effector substrates. These results highlight the diverse molecular signatures required for a highly coordinated assembly process and provide the molecular basis for understanding triggering and transport of unfolded proteins through injectisomes.

molecular biology↗

bioRxiv2018

How to control for confounds in decoding analyses of neuroimaging data

Over the past decade, multivariate pattern analyses and especially decoding analyses have become a popular alternative to traditional mass-univariate analyses in neuroimaging research. However, a fundamental limitation of decoding analyses is that the source of information driving the decoder is ambiguous, which becomes problematic when the to-be-decoded variable is confounded by variables that are not of primary interest. In this study, we use a comprehensive set of simulations and analyses of empirical data to evaluate two techniques that were previously proposed and used to control for confounding variables in decoding analyses: counterbalancing and confound regression. For our empirical analyses, we attempt to decode gender from structural MRI data when controlling for the confound brain size. We show that both methods introduce strong biases in decoding performance: counterbalancing leads to better performance than expected (i.e., positive bias), which we show in our simulations is due to the subsampling process that tends to remove samples that are hard to classify; confound regression, on the other hand, leads to worse performance than expected (i.e., negative bias), even resulting in significant below-chance performance in some scenarios. In our simulations, we show that below-chance accuracy can be predicted by the variance of the distribution of correlations between the features and the target. Importantly, we show that this negative bias disappears in both the empirical analyses and simulations when the confound regression procedure performed in every fold of the cross-validation routine, yielding plausible model performance. From these results, we conclude that foldwise confound regression is the only method that appropriately controls for confounds, which thus can be used to gain more insight into the exact source(s) of information driving ones decoding analysis.\n\nHIGHLIGHTSO_LIThe interpretation of decoding models is ambiguous when dealing with confounds;\nC_LIO_LIWe evaluate two methods, counterbalancing and confound regression, in their ability to control for confounds;\nC_LIO_LIWe find that counterbalancing leads to positive bias because it removes hard-to-classify samples;\nC_LIO_LIWe find that confound regression leads to negative bias, because it yields data with less signal than expected by chance;\nC_LIO_LIOur simulations demonstrate a tight relationship between model performance in decoding analyses and the sample distribution of the correlation coefficient;\nC_LIO_LIWe show that the negative bias observed in confound regression can be remedied by cross-validating the confound regression procedure;\nC_LI

neuroscience↗