Biology subjects

Trujillo-Barreto, N. J.

Publications and source records attributed to Trujillo-Barreto, N. J..

8 recordsLinked to original sources

bioRxiv2026

Thalamic Nuclei Functional Controllability Accounts for Cognitive Impairment in Multiple Sclerosis Over and Above Structural Damage

BackgroundThe thalamus has emerged as a key region involved in cognitive dysfunction in multiple sclerosis (MS). While previous studies have identified associations between thalamic structural damage, altered functional connectivity, and cognitive performance, the specific contributions of individual thalamic nuclei and the added value of integrating structural and functional metrics remain poorly understood. MethodsT1-weighted MRI, diffusion MRI, resting-state fMRI, and neuropsychological data were collected from 102 individuals with MS and 27 healthy controls. Thalamic grey matter volume, white matter microstructural integrity, and functional controllability were calculated for each nucleus and compared between individuals with MS and healthy controls, as well as between MS cognitive subgroups. Partial Spearman correlations were used to examine the relationship between imaging metrics across the three modalities, and also between imaging metrics and cognitive performance in MS. Sparse canonical correlation analysis models were used to examine the covariance between thalamic imaging metrics and cognitive performance in MS. ResultsWidespread atrophy and microstructural damage were observed across all thalamic nuclei in individuals with MS, regardless of cognitive status. In contrast, alterations in functional controllability were more spatially specific, primarily affecting the medial dorsal anterior nuclei, and were most pronounced in cognitively impaired individuals. These functional controllability metrics were independent of grey matter volume, white matter integrity, and lesion load. Combining thalamic functional controllability with structural metrics yielded a stronger association with cognitive performance in MS than either modality alone. ConclusionThis study provides novel evidence that functional controllability in the thalamus, particularly within the medial dorsal anterior nuclei, plays a critical role in cognitive impairment in MS. By applying a network control framework, our findings offer a dynamic systems perspective that extends beyond traditional connectivity analyses, capturing the thalamuss role in supporting flexible cognitive transitions. The integration of structural and functional controllability metrics enhances the ability to characterise individual differences in cognitive performance and may inform future efforts to identify biomarkers of cognitive dysfunction in MS.

neuroscience↗

bioRxiv2026

Thalamic Nuclei Functional Controllability Explains Cognition Over and Above Grey and White Matter Structure

IntroductionThe thalamic nuclei play a crucial role in regulating information flow to the cortex and supports diverse cognitive functions. Although previous studies have linked thalamic structural and functional characteristics to cognition, these measures do not fully capture the thalamuss role in dynamic control, which is essential for complex cognitive processes. Moreover, it remains unclear how these different metrics relate to each other in the way they account for cognition. MethodsT1-weighted MRI, diffusion MRI, resting-state fMRI, and neuropsychological data were obtained from 419 unrelated participants in the Human Connectome Project. We measured grey matter volume, white matter integrity, and functional controllability of each thalamic nucleus to examine their associations with cognitive performance across domains identified through clustering analysis of the neuropsychological data. We also assessed the relationships among these structural and functional metrics and evaluated their individual and combined contributions in capturing covariance with performance in various cognitive domains. ResultsSignificant correlations were observed between thalamic grey matter volume and white matter integrity; however, thalamic functional controllability showed no significant association with either structural metric. White matter integrity demonstrated the strongest association with sequence working memory and language processing. In contrast, thalamic controllability metrics accounted more for performance in executive function, reasoning and encoding, visuospatial processing, and impulse control, outperforming the combination of grey and white matter structural metrics. ConclusionThis study highlights the critical role of the thalamus from a dynamic control perspective, demonstrating that thalamic structural and functional metrics provide complementary rather than redundant information related to cognitive performance. These findings underscore a promising new direction for understanding the complex and dynamic contributions of the thalamus to human cognition.

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bioRxiv2024

Differentiating hallucination proneness dimensions through resting state alpha dynamics

BackgroundHallucination-like experiences (HLEs) are untriggered sensory perceptions linked to externalizing bias - the misattribution of self-generated sensory experiences to an external source. The vulnerability to HLEs, i.e., hallucination proneness (HP), is typically assessed by the Launay-Slade Hallucination Scale (LSHS). A recent LSHS factor analysis revealed four distinct HP dimensions: Multisensory HLEs, Auditory daydreaming, Vivid thoughts and inner speech, and Personified HLEs. The current study assesses whether these HP dimensions map onto distinct patterns of resting state brain dynamics in the alpha frequency band due to its modulatory role in attention and perception. MethodsWe used a Hidden semi-Markov Model to segment continuous RS alpha activity into nine recurrent brain states and extracted the total number of transitions (TT) and the number of visits per state (SV). We assessed how the HP dimensions relate to these metrics, calculated across the entire 3-minute recording and within shorter sliding windows to capture finer temporal changes. ResultsAll HP dimensions and increased RS time correlated with increased TT. Increased Personified HLEs scores linked to different time-dependent changes of SV in two states (SV to state 5 decreased over time, while visits to state 9 increased), highlighting distinct alpha dynamics in high- and low-hallucination prone individuals. ConclusionsIncreased TT could indicate frequent attentional switches between internal and external states. Different SV patterns related to higher Personified HLEs scores suggest unstable source monitoring, potentially inducing an externalizing bias. These findings provide novel predictors of HP dimensions, revealing distinct neural profiles associated with different vulnerability profiles.

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bioRxiv2024

Effects of non-invasive brain stimulation on effective connectivity during working memory task in Neurofibromatosis Type 1 patients

This study examined the effects of anodal transcranial direct current stimulation (atDCS) on effective connectivity during a working memory task. Eighteen adolescents with Neurofibromatosis Type 1 (NF1) completed a single{square}blind sham{square}controlled cross{square}over randomised atDCS trial. Dynamic causal modelling was used to estimate the effective connectivity between regions that showed working memory effects from the fMRI. Group-level inferences for between sessions (pre- and post-stimulation) and stimulation type (atDCS and sham) effects were carried out using the parametric empirical Bayes approach. A correlation analysis was performed to relate the estimated effective connectivity parameters of left dlPFC pre-atDCS and post-atDCS to the concentration of gamma-aminobutyric acid (GABA) measured via magnetic resonance spectroscopy (MRS-GABA). Next, correlation analysis was repeated using all working memory performance and all pre-atDCS and post-atDCS connectivity parameters. It was found that atDCS decreased average excitatory connectivity from left dorsolateral prefrontal cortex (dlPFC) to left superior frontal gyrus and increased average excitatory connectivity to left globus pallidus. Further, reduced average intrinsic (inhibitory) connectivity of left dlPFC was associated with lower MRS-GABA. However, none of the connectivity parameters of dlPFC showed any association with performance on a working memory task. These findings suggest that atDCS reorganised connectivity from frontal to fronto-striatal connectivity. As atDCS-related changes were not specific to the effect of working memory, they may have impacted general cognitive control processes. In addition, by reducing MRS-GABA, atDCS might make dlPFC more sensitive and responsive to external stimulation, such as performance of cognitive tasks. Highlights- atDCS was applied to left dlPFC in NF1 patients during working memory - After atDCS, no effect on modulatory connectivity - Evidence for increased N-back average connectivity from dlPFC to globus pallidus - Less dlPFC MRS-GABA was associated with less dlPFC inhibition

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bioRxiv2023

EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

IntroductionAuditory verbal hallucinations (AVH) are a transdiagnostic phenomenon but also occur in the general population. The disposition to experience AVH is considered a continuous expression from non-clinical to clinical hallucination proneness (HP). Currently, little is known about the neurophysiology of the non-clinical HP part of the continuum. AVH might result from a heightened sensitivity to sensory inputs and a decreased ability to differentiate between externally and internally generated input. Resting state (RS) alpha band activity is associated with perceptual sensitivity, attentional shifts, and cognitive control. Accordingly, spontaneous alpha fluctuations might present as a HP correlate. To investigate the time-varying dynamics of alpha band activity, we deployed a novel method for brain state allocation. MethodsWe recorded RS electroencephalography (EEG) data from 33 individuals with varying levels of HP but without clinically relevant hallucinations and used a Hidden Semi-Markov Model (HsMM) to identify five recurrent alpha states with unique temporal dynamics and topographies. The states mean duration and occupancy were analyzed as a function of HP. The sources of each state were reconstructed to identify the most active brain areas and their correspondence with known resting state networks. ResultsOccupancy and mean duration of a state corresponding to sensorimotor, auditory, and default-mode network (DMN) areas significantly predicted auditory and auditory-verbal HP, but not general HP. The temporal dynamics of all other states did not relate to HP. ConclusionAlpha brain state sources align with prior results on the role of the alpha in the DMN. The temporal dynamics of alpha might reflect individual differences for attentional biases to internally generated sensory events and altered auditory perceptual sensitivity. Thus, changes in the temporal brain state dynamics of RS alpha oscillations could present as a neural marker of increased vulnerability to auditory hallucinatory experiences.

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bioRxiv2021

From synaptic activity to human in vivo quantification of neurotransmitter dynamics: a neural modelling approach

Understanding the role of neurotransmitters glutamate and GABA during normal and abnormal brain function and under external stimulation in humans are critical neuroscientific and clinical goals. The recent development of functional 1H-Magnetic resonance spectroscopy (fMRS) has allowed us to study neuro-transmitter activity in vivo for the first time. However, the physiological basis of the observed fMRS signal remains unclear. It has been proposed that fMRS detects shifts in metabolite concentrations as they move from presynaptic vesicles, where they are largely invisible, to extracellular and cytosolic pools, where they are visible. Here we bridge the gap between neural dynamics and fMRS by developing a mean-field model to link the neurotransmitter dynamics at the microscopic-level to the macroscopic-level imaging measurements. GABA and glutamate are described as cycling between three metabolic pools: in the vesicles; active in the cleft; or undergoing recycling in the astrocytic or neuronal cytosol. We interrogate the model by applying a current to manipulate the mean membrane potential and firing rate of the neural populations. We find that by disregarding the contribution from the vesicular pool, our model predicts activity-dependent changes in the MRS signal, which are consistent with reported empirical findings. Further, we show that current magnitude and direction has a selective effect on the GABA/glutamate-MRS signal: inhibitory stimulation leads to reduction of both metabolites, whereas excitatory stimulation leads to increased glutamate and decreased GABA. In doing so, we link neural dynamics and fMRS and provide a mechanistic account for the activity-dependent change in the observed MRS signal. Key Points SummaryO_LIThe recent development of functional 1H-Magnetic resonance spectroscopy (fMRS) has allowed us to study neurotransmitter activity in vivo for the first time in humans. However, the physiological basis of the observed fMRS signal is unclear. C_LIO_LIIt has been proposed that fMRS detects shifts in metabolite concentrations as they move from presynaptic vesicles, where they are largely invisible to MRS, to extracellular and cytosolic pools, where they are visible to MRS. C_LIO_LIWe test this hypothesis using a mean field model which links the neural dynamics of neurotransmitters at the microscopic-level to the macroscopic-level imaging measurements obtained in experimental studies. C_LIO_LIBy disregarding activity in the vesicular pool, our model can generate activity-dependent changes in the MRS signal in response to stimulation which are consistent with experimental findings in the literature. C_LIO_LIWe provide a mechanistic account for the activity-dependent change in observed neurotransmitter concentrations using MRS. C_LI

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bioRxiv2020

Entraining alpha activity using visual stimulation in patients with chronic musculoskeletal pain. A feasibility study.

Entraining alpha activity with rhythmic visual, auditory, and electrical stimulation can reduce experimentally induced pain. However, evidence for alpha entrainment and pain reduction in patients with chronic pain is limited. This feasibility study investigated whether visual alpha stimulation can increase alpha power in patients with chronic musculoskeletal pain and secondarily, if chronic pain was reduced following stimulation. In a within-subject design, 22 patients underwent 4-minute periods of stimulation at 10 Hz (alpha), 7 Hz (high-theta, control), and 1 Hz (control) in a pseudo-randomized order. Patients underwent stimulation both sitting and standing and verbally rated their pain before and after each stimulation block on a 0-10 numerical rating scale. Global alpha power was significantly higher during 10 Hz compared to 1 Hz stimulation when patients were standing (t = -6.08, p <.001). On a more regional level, a significant increase of alpha power was found in the right-middle and left-posterior region when patients were sitting. With respect to our secondary aim, no significant reduction of pain intensity and unpleasantness was found. However, only the alpha stimulation resulted in a minimal clinically important difference in at least 50% of participants for pain intensity (50%) and unpleasantness ratings (65%) in the sitting condition. This study provides initial evidence for the potential of visual stimulation as a means to enhance alpha activity in patients with chronic musculoskeletal pain. The brief period of stimulation was insufficient to reduce chronic pain. This study is the first to provide evidence that a brief period of visual stimulation at alpha frequency can significantly increase alpha power in patients with chronic musculoskeletal pain. Further study is warranted to investigate optimal dose and individual stimulation parameters to achieve pain relief in these patients.

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bioRxiv2019

The discrete logic of the Brain - Explicit modelling of Brain State durations in EEG and MEG

We consider the detection and characterisation of brain state transitions, based on ongoing Magneto and Electroencephalography (M/EEG). Here a brain state represents a specific brain dynamical regime or mode of operation, which produces a characteristic quasi-stable pattern of activity at topography, sources or network levels. These states and their transitions over time can reflect fundamental computational properties of the brain, shaping human behaviour and brain function. The Hidden Markov Model (HMM) has emerged as a useful model-based approach for uncovering the hidden dynamics of brain state transitions based on observed data. However, the Geometric distribution of state duration (dwell time) implicit in HMM places highest probability on very short durations, which makes it inappropriate for the accurate modelling of brain states in M/EEG. We propose using Hidden Semi Markov Models (HSMM), a generalisation of HMM that models the brain state duration distribution explicitly. We present a Bayesian formulation of HSMM and use the Variational Bayes framework to efficiently estimate the HSMM parameters, the number of brain states and select among alternative brain state duration distributions. We assess HSMM performance against HMM on simulated data and demonstrate that the accurate modelling of state duration is paramount for accurately and robustly modelling non-Markovian EEG brain state features. Finally, we used actual resting-state EEG data to demonstrate the approach in practice and conclude that it provides a flexible parameterised framework that permits closer interrogation of possible generative mechanisms.

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