Biology subjects

Raz, G.

Publications and source records attributed to Raz, G..

7 recordsLinked to original sources

bioRxiv2024

A stimulus-computable rational model of habituation in infants and adults

How do we decide what to look at and when to stop looking? Even very young infants engage in active visual selection, looking less and less as stimuli are repeated (habituation) and regaining interest when novel stimuli are subsequently introduced (dishabituation). The mechanisms underlying these looking time changes remain uncertain, however, due to limits on both the scope of existing formal models and the empirical precision of measurements of infant behavior. To address this, we developed the Rational Action, Noisy Choice for Habituation (RANCH) model, which operates over raw images and makes quantitative predictions of participants looking behaviors in a classic visual habituation paradigm. In a series of pre-registered experiments, we exposed infants and adults to stimuli for varying durations and measured looking time to familiar and novel stimuli. We found that these data were well captured by RANCH. Using RANCHs stimulus-computability, we also tested its out-of-sample predictions about the magnitude of dishabituation in a new experiment in which we manipulated the similarity between the familiar and novel stimulus. By framing looking behaviors as rational decision-making, this work identified how the dynamics of learning and exploration guide our visual attention from infancy through adulthood.

animal behavior and cognition↗

bioRxiv2024

Generalizable Neural Models of Emotional Engagement and Disengagement

Emotional experiences are never static but continuously evolve in response to internal and external contexts. Little is known about how neural patterns change as a function of these experiences, particularly in response to complex, real-world stimuli. This study aimed to identify generalizable neural patterns as individuals collectively engage and disengage from emotions dynamically. To do so, we analyzed functional magnetic resonance imaging (fMRI) along with subjective emotional annotations from two independent studies as individuals watched negative and neutral movie clips. We used predictive modeling to test if a model trained to predict a group emotional signature response in one study generalizes to the other study and vice versa. Disengagement patterns generalized specifically across intense clips. They were supported by connections within and between the sensorimotor and salience networks, maybe reflecting the processing of feeling states as individuals regulate their emotions. Prediction success for the engagement signature was mixed, but primarily linked to connections within the visual and between the visual and dorsal attention networks, maybe supporting visual attention orienting as emotions intensify. This work offers potential pathways for identifying generalizable neural patterns contributing to future affective research and clinical applications aiming to better understand dynamic emotional responses to naturalistic stimuli.

neuroscience↗

bioRxiv2020

A Non-stop identity complex (NIC) supervises enterocyte identity and protects from pre-mature aging

A hallmark of aging is the inability of differentiated cells to maintain their identity. In the aged Drosophila midgut differentiated enterocytes (ECs) lose their identity, and the integrity of the midgut tissue and its homeostasis are impaired. To discover regulators of EC identity relevant to aging we performed an RNAi screen targeting 453 ubiquitin-related genes in fully differentiated ECs. Seventeen genes were identified, including the de-ubiquitinase Non-stop (Not/dUSP22; CG4166). Acute loss of Non-stop in young ECs phenotypically resembled aged ECs. Lineage tracing experiments established that Non-stop-deficient young ECs as well as wild-type aged ECs are no longer differentiated. Aging or acute loss of Non-stop also resulted in progenitor cell hyperproliferation and mis-differentiation, loss of gut integrity, and reduced organismal survival. Proteomic analysis unveiled that Non-stop maintains identity as part of a Non-stop identity complex (NIC) that contains E(y)2, Sgf11, Cp190, (Mod) mdg4, and Nup98. Transcriptionally, Non-stop ensured chromatin accessibility at EC genes, maintained an EC-specific gene expression signature, and silenced non-EC-relevant transcriptional programs. Within the NIC, Non-stop was required for stabilizing of NIC subunits. Upon aging, the levels of Non-stop and NIC subunits declined, and the large-scale organization of the nucleus was distorted. Maintaining youthful levels of Non-stop in wildtype aged ECs safeguarded the protein level of NIC subunits, restored the large-scale organization of the differentiated nucleus, and suppressed aging phenotypes and tissue integrity. Thus, the isopeptidase Non-stop, and NIC, supervise EC identity and protects from premature aging.

cell biology↗

bioRxiv2020

How can noise alter neurophysiology in order to improve human behaviour? A combined transcranial random noise stimulation and electroencephalography study

Random noise has been shown to improve the detection of suboptimal signals in humans and machines. Based on that, transcranial random noise stimulation (tRNS) has aimed to improve human behaviour by targeting neuronal activity. To uncover the poorly understood mechanistic underpinnings of tRNS, we recorded electroencephalography data during arithmetic training while delivering active or sham tRNS above the dorsolateral prefrontal cortex (dlPFC). By successfully removing the tRNS artefact in the time and frequency domains, we examined the mechanisms that underlie its behavioural improvement. We found that active tRNS improved arithmetic performance and impacts specific ERPs components that are associated with attentional mechanisms. Furthermore, the tRNS effect was maximal in individuals with suboptimal arithmetic ability and neurophysiological measures of top-down control and excitation/inhibition ratio. These results providing a novel mechanistic explanation for the effect of tRNS on human behaviour and highlight how suboptimal task-specific behaviour and neurophysiology predicts its effect.

neuroscience↗

bioRxiv2019

Electroencephalographic evidence for the involvement of mirror neuron and error monitoring related processes in virtual body ownership

The illusion that an artificial or virtual object becomes part of ones body has been demonstrated and productively investigated in the past two decades. Empirical and theoretical accounts of this phenomenon suggest that the body ownership illusion relies not on a single process, but rather on the alignment of the biological and the alternative bodies across multiple aspects. However, the portrayal of these aspects and the demarcation of their neurophysiological correlates has yet to be established.\n\nOur study examines electroencephalographic (EEG) markers of two extensively studied systems in the context of virtual body ownership illusion: the mirror neuron system (MNS) and the error monitoring system (EMS). We designed an experimental manipulation of brief involuntary virtual hand bounces, which triggers both systems, and examined how the response of EEG markers of these systems to this manipulation is modulated by three aspects of body ownership: agency, visuotactile synchronicity, and semantic congruence between the participants hands and its virtual representation.\n\nWe found evidence for enhanced MNS-related suppression of power at the Mu band in the synchronous and semantic congruence conditions. On the other hand, the EMS-related Pe/P300 wave was reduced by semantic congruence. This Pe/P300 effect was stronger among participants who exhibited higher acceptance of the spatial illusion and increased tendency for affective empathy. Mu power and Pe/P300 were not correlated, suggesting a dissociation between the distinct aspects of body ownership they probe. The findings suggest that synchronicity and semantic congruence induce sensorimotor sensitivity to the alternative body, whereas the latter parameter also buffers minor erroneous virtual motions. These neurophysiological markers may be added to the arsenal of body ownership probes, and integrated in VR rehabilitation protocols.

neuroscience↗

bioRxiv2019

Transfer learning of deep neural network representations for fMRI decoding

BackgroundDeep neural networks have revolutionised machine learning, with unparalleled performance in object classification. However, in brain imaging (e.g. fMRI), the direct application of Convolutional Neural Networks (CNN) to decoding subject states or perception from imaging data seems impractical given the scarcity of available data. New methodIn this work we propose a robust method to transfer information from deep learning (DL) features to brain fMRI data with the goal of decoding. By adopting Reduced Rank Regression with Ridge Regularisation we establish a multivariate link between imaging data and the fully connected layer (fc7) of a CNN. We exploit the reconstructed fc7 features by performing an object image classification task on two datasets: one of the largest fMRI databases, taken from different scanners from more than two hundred subjects watching different movie clips, and another with fMRI data taken while watching static images, ResultsThe fc7 features could be significantly reconstructed from the imaging data, and led to significant decoding performance. Comparison with existing methodsThe decoding based on reconstructed fc7 outperformed the decoding based on imaging data alone. ConclusionIn this work we show how to improve fMRI-based decoding benefiting from the mapping between functional data and CNN features. The potential advantage of the proposed method is twofold: the extraction of stimuli representations by means of an automatic procedure (unsupervised) and the embedding of high-dimensional neuroimaging data onto a space designed for visual object discrimination, leading to a more manageable space from dimensionality point of view.

neuroscience↗

bioRxiv2017

Context of psychotropic drug delivery modulates its neurobehavioral effects: the case of methylphenidate

Pharmacotherapy is substantially hindered by poor drug targeting, resulting in low specificity and efficacy. Here, we tested a novel, non-invasive targeting approach (termed functional-pharmacology), which couples drug administration with a task that activates the drugs sites-of-action in the brain, thus possibly improving absorption and efficacy. Methylphenidate (MPH) or Placebo were administered to healthy subjects, which then performed a cognitive induction or a control task. N-Back fMRI before and after drug-task coupling measured therapeutic effects. Only following MPH, subjects that performed better in the cognitive induction task showed greater improvements in N-back performance. Moreover, only under MPH-Cognitive induction condition, there existed a significant correlation between improved recruitment of N-Back rDLPFC activation, and a concurrent improvement in task performance. Importantly, mediation analysis suggested a causal role of rDLPFC activation in these coupling effects. Our results support the functional-pharmacology concept feasibility and efficacy, hence opening a new horizon for patient-tailored, context-driven drug therapy.

neuroscience↗