Biology subjects

Rodriguez-Herreros, B.

Publications and source records attributed to Rodriguez-Herreros, B..

11 recordsLinked to original sources

bioRxiv2026

Heterogeneity of Brain Dynamics in Genetic and Psychiatric Conditions

Whether the heterogeneity of psychiatric conditions converges on shared neurophysiological alterations or translates into distinct signatures remains unclear. We assembled high-density electroencephalogram (hd-EEG) resting-state recordings from 4,812 individuals aged 5 months to 66 years across 11 psychiatric conditions, a broad spectrum of rare genetic variants, and typically developing (TD) individuals. We established normative developmental trajectories of source-space EEG across spectral organization, connectivity, and signal complexity. Psychiatric conditions showed small deviations, revealing a shared transdiagnostic profile. In contrast, single rare variants showed substantially larger, distinct and sometimes mirror-opposite signatures that collapsed toward the psychiatric profile when pooled. Autism Spectrum Disorder showed some of the smallest group-level effects yet the largest individual deviations, indicating substantial but directionally inconsistent alterations. EEG deviations followed a cortical gradient, with larger effects in sensorimotor regions. We demonstrate that sample sizes in the hundreds are required for robust associations with psychiatric diagnoses. This interactive open resource provides normative scores to benchmark future results.

neuroscience↗

bioRxiv2025

Sample size critically shapes the reliability of EEG case-control findings in psychiatry

Electroencephalography (EEG) studies in psychiatry have produced highly inconsistent findings, particularly in case-control designs. Small sample sizes are widely assumed to contribute to this variability, yet their impact on the reliability of EEG group comparisons has not been systematically quantified at scale. Here, we address this key gap using a large multisite resting-state EEG dataset comprising 2,874 participants aged 5-18 years, including individuals with attention-deficit/hyperactivity disorder, autism spectrum disorder, anxiety, learning disorders, and healthy controls. We extracted a comprehensive set of spectral, temporal, and complexity EEG features and performed repeated case-control comparisons across a wide range of sample sizes using extensive random subsampling. Results from small samples were unstable, with inflated and highly variable effect sizes across iterations. By contrast, larger samples produced consistent and reproducible findings, converging on uniformly small but robust effects. Statistical power rose steeply with sample size, whereas false positive rates remained relatively stable. These results demonstrate the central role of sample size in shaping EEG study outcomes and challenge the utility of conventional case-control approaches for biomarker discovery in psychiatry.

neuroscience↗

bioRxiv2025

Transdiagnostic electrophysiological subtypes reveal brain-behavior dimensions in youth psychiatry

Conventional psychiatric diagnoses often fail to reflect the underlying neurobiological and behavioral complexity of mental health conditions. Here, we propose a transdiagnostic, data-driven framework for stratifying youth based on large-scale multisite electroencephalography (EEG) data from 1,707 individuals aged 5-18 years, including healthy controls and individuals diagnosed with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), anxiety disorders (ANX), and learning disabilities (LD), along with their common comorbidities. By applying normative modeling to quantify individual deviations from typical brain functional maturation, and integrating multidimensional EEG features across spectral, temporal, complexity, and dynamical domains via similarity network fusion clustering, we identified three robust neurophysiological biotypes. These biotypes showed distinct electrophysiological and behavioral profiles, and captured meaningful brain-behavior relationships. Our findings suggest that biologically informed subtypes capture meaningful neuropsychiatric heterogeneity in youth, challenging conventional diagnostic boundaries in psychiatric nosology.

neuroscience↗

bioRxiv2025

Satiety does not abolish Pavlovian-to-instrumental transfer but accelerates devaluation in humans

Environmental cues that predict palatable food can robustly drive behavior, override satiety signals and promote maladaptive eating habits. However, conventional human paradigms often fail to capture the dynamic interplay between hunger, satiety, and cue-induced behavioral actions. To address this, we built a novel automated dispenser synchronized with task events and integrated into an adapted human Pavlovian-to-instrumental transfer (PIT) paradigm to deliver real, consumable food rewards in real time--allowing participants to eat online and thereby induce satiation or sustain hunger. In one experiment, we manipulated food rewards by varying portion size and consumption timing. Large portions consumed immediately induced rapid satiation, whereas small, trial-by-trial portions kept participants non-satiated; correspondingly, large portions accelerated devaluation of the food reward--evidenced by a pronounced decline in instrumental responding--while small portions sustained cue-driven behavior over time. In a subsequent experiment, small, immediately consumed food rewards (which kept participants non-satiated) were directly compared with real-time monetary rewards. Although both reward types initially invigorated behavior, the motivational impact of monetary rewards declined quicker, suggesting that the absence of physiological feedback renders secondary reinforcers more vulnerable to rapid devaluation. These findings suggest that satiety accelerates, rather than abolishes, the influence of food-associated cues. The distinct temporal dynamics observed for food and monetary outcomes underscore the importance of real-time ingestion in human PIT paradigms, offering new insights into the mechanisms by which physiological states modulate cue-driven devaluation.

neuroscience↗

bioRxiv2025

Satiety Does Not Silence Food Attention: BMI Modulates Attentional Bias Toward High-Calorie Cues

BackgroundAttentional bias (AB) for palatable foods has been linked to overeating, yet data on its modulation with body-mass index (BMI) and hunger/satiety are inconsistent. We tested whether hunger, sensory-specific satiety and BMI interact to shape automatic capture of attention by real high-calorie snack foods. MethodsTwo emotional-attentional-blink (EAB) experiments presented food distractors either 300 msec (lag-3) or 900 msec (lag-9) before a neutral target. Experiment 1 (N = 183; whole BMI range) randomly assigned participants to taste (non-satiated), satiated or non-eating conditions; the snacks eaten (or not eaten) subsequently re-appeared as distractors in the EAB task. Experiment 2 (N = 61; 31 overweight/obese, 30 normal-weight) manipulated hunger/satiety states and snack type (consumed vs. novel) orthogonally, in a double session design. ResultsExperiment 1-- food images presented at lag-3 reduced target detection compared with lag-9 (OR = 0.61, CI 0.50-0.75, p <.01. Higher BMI predicted a larger AB when hungry, but a smaller AB when satiated (OR = 0.65, CI 0.48-0.88, p < 0.01). Experiment 2-- For novel snacks, an interaction revealed that participants with overweight/obesity retained robust AB after satiation, whereas AB declined for participants with normal-weight (OR = 2.45, CI 1.09-5.51, p = 0.03). For snacks just eaten, AB remained significant in both groups (lag-3 vs. lag-9: OR = 0.37, CI 0.25-0.55, p <.001). ConclusionsReal-food cues automatically biased attention regardless of metabolic state, with BMI modulating this effect: even when satiated, individuals with overweight/obesity continue to orient their attention toward both familiar and novel high-calorie foods. These findings suggest that satiety signals alone may be insufficient to curb attentional capture by food in obesity, highlighting the need for interventions that target attentional control and limit food availability.

neuroscience↗

bioRxiv2025

Riding the savory horse: An active mindset and food macronutrient composition influence attentional bias toward food cues

Food cues that appear in the visual field capture our attention easily and can influence eating behavior. The current study investigated the influence of food-related stimuli on visual attention, considering the macronutrient composition of food items. Images representing sweet and savory foods were employed, the latter consisting primarily of high-protein foods. The participants were primed with these images prior to performing the attentional task. We found that both sets of food images elicited an emotional attentional blink (EAB), but a stronger EAB was observed for the high-protein foods, and this observation was further supported by a negative correlation between the attentional bias (ABias) and the proportion of protein consumed by the participants before the experiment, with participants who consumed less protein exhibiting a stronger ABias toward high-protein foods. These findings suggest that an ABias might also arise to facilitate the consumption of high-protein foods when prior consumption of this macronutrient is low.

neuroscience↗

bioRxiv2025

Social, cognitive and sensory dimensions of cortical network overconnectivity in young children with autism spectrum disorder

The heterogeneity in both the neurobiological mechanisms and the phenotypic presentation of autism spectrum disorder (ASD) poses a major challenge to clinical and translational research. Early inefficiencies in functional connectivity (FC) have been associated with ASD, yet it remains unclear whether and how abnormal brain network properties may account for individual differences across ASD-related symptomatology and behaviors. We applied source-level reconstruction to resting-state high-definition EEG data in a cohort of 113 young children (40 with ASD) to identify early global and local alterations of cortical network connectivity. We subsequently used regularized canonical correlation analysis (rCCA) to characterize specific FC patterns linked to variation in cognitive, social and sensory dimensions within the autism spectrum. We found increased low-frequency FC in frontotemporal cross-hemispheric networks and lateral-occipital regions of young ASD children. RCCA revealed three distinct FC patterns in recurrent ASD-related networks, each contributing to predict individual differences in cognitive, social and sensory features. These linked FC-behavior dimensions may shed light on atypical brain network topology conferring risk for specific phenotypic manifestations of ASD, which may implicate unique underlying neurobiological mechanisms.

neuroscience↗

bioRxiv2024

Beyond homogeneity: Charting the landscape of heterogeneity in psychiatric electroencephalography

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patients heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity-across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.

neuroscience↗

bioRxiv2022

Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily examined single CNV loci in small clinical cohorts. It remains unknown how distinct CNVs escalate the risk for the same developmental and psychiatric disorders. Here, we quantitatively dissect the impact on brain organization and behavioral differentiation across eight key CNVs. In 534 clinical CNV carriers from multiple sites, we explored CNV-specific brain morphology patterns. We extensively annotated these CNV-associated patterns with deep phenotyping assays through the UK Biobank resource. Although the eight CNVs cause disparate brain changes, they are tied to similar phenotypic profiles across [~]1000 lifestyle indicators. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

genetics↗

bioRxiv2021

Fasting reduces inhibitory and attentional control of food-related cues

The metabolic and cognitive systems interact to create the motivational drive that occasionally leads to disrupted consummatory eating behaviors. In this study, we investigated whether stimulus-specific alterations of the inhibitory function are present following a period of food deprivation. Twenty-six participants with normal weight performed the Stop Signal Task (SST) and the Go/No-go (GNG) task to measure response inhibition to food images containing high or low caloric content after following -or not- a 12-hour fasting period. Response inhibition performance in the SST did not exhibit significant differences when considering neither fasting, stimulus type nor food caloric content. We instead found a higher percentage of commission errors in the No-go trials of the GNG task in the fasting session, and specially with high-caloric food items. In contrast, the accuracy in the Go trials was similar between conditions. A mixed logistic regression model confirmed the remarkable impact of fasting on the performance of response inhibition. Overall, our findings support an interpretation of the motivational drive to eat strongly associated with aspects of the inhibitory function underlying high attentional control, rather than to a proper response inhibition per se.

neuroscience↗

bioRxiv2020

Effects-sizes of deletions and duplications on autism risk across the genome

ObjectiveDeleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, only 13 genomic loci have been formally associated with autism because the majority of CNVs are too rare to perform individual association studies. To investigate the implication of undocumented CNVs in neurodevelopmental disorders, we recently developed a new framework to estimate their effect-size on intelligence quotient (IQ) and sought to extend this approach to autism susceptibility and multiple cognitive domains. MethodsWe identified CNVs in two autism samples (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models integrating scores of genes encompassed in CNVs were used to explain their effect on autism susceptibility and multiple cognitive domains. ResultsAmong 9 scores of genes, the "probability-of-being loss-of-function intolerant" (pLI) best explains the effect of CNVs on IQ and autism risk. Deletions decrease IQ by a mean of 2.6 points per point of pLI. The effect of duplications on IQ is three-fold smaller. The odd ratios for autism increases when deleting or duplicating any point of pLI. This increased autism risk is similar in subgroups of individuals below or above median IQ. Once CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behaviour, and phonological memory, whereas both equally affect motor skills. ConclusionsAutism risk conferred by duplications is less influenced by IQ compared to deletions. CNVs increase autism risk similarly in individuals with high and low IQ. Our model, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk. These models will help interpreting CNVs identified in the clinic.

genetics↗