Nelson Trujillo-Barreto

• PhD
• Reader at Manchester Metropolitan University

Neurofibromatosis type 1 (NF1) is a rare genetic condition characterised by skin pigmentations, bone deformities, and tumours. Its cognitive phenotype shares similarities with autism spectrum disorder and attention deficit/hyperactivity disorder, including impairments in executive function and working memory processing. In this work, we conducted f...

Background Neurofibromatosis Type 1 (NF1) is a rare, a single-gene neurodevelopmental disorder. Atypical brain activation patterns have been linked to working memory difficulties in NF1 patients. The present work investigated if greater inhibitory activity underlies in interactions between neuronal populations in NF1 patients, as estimated with eff...

We propose a new model for the non-stationary brain state allocation problem from EEG data, based on spectral features and their interaction. Spontaneous EEG data are modeled as continuous Gaussian Processes (GPs) emissions governed by discrete states, represented by a hidden semi-Markov model, that switch in time (HsMM-SGP). The GPs are defined by...

Background: Hallucination-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...

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□blind sham□controlled cross□over randomised atDCS trial. Dynamic causal modelling was used to estimate the effective connectivit...

Task-free brain activity exhibits spontaneous fluctuations between functional states, characterized by synchronized activation patterns in distributed resting-state (RS) brain networks. The temporal dynamics of the networks’ electrophysiological signatures reflect individual variations in brain activity and connectivity linked to mental states and...

Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predicti...

We consider the detection and characterization of brain state transitions, based on ongoing electroencephalography (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 the topography, sources, or network levels. These states and their transi...

Multiple sclerosis is a neuroinflammatory and neurodegenerative disease commonly associated with cognitive impairment. Understanding brain mechanisms of cognitive impairment in multiple sclerosis is crucial for early diagnosis and developing effective interventions to improve the quality of life in patients. Recent studies indicate that individuals...

Background There is inter‐individual variability in the influence of different components (e.g. nociception and expectations) on pain perception. Identifying the individual effect of these components could serve for patient stratification, but only if these influences are stable in time. Methods In this study, 30 healthy participants underwent a c...

Introduction Auditory 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 conti...

Functional brain imaging has shown that the awake brain, independent of a task, spontaneously switches between a small set of functional networks. How useful this dynamical view of brain activity is for clinical studies, e.g., as early markers of subsequent structural and/or functional change or for assessing successful training or intervention eff...

Graph theory has been used in cognitive neuroscience to understand how organisational properties of structural and functional brain networks relate to cognitive function. Graph theory may bridge the gap in integration of structural and functional connectivity by introducing common measures of network characteristics. However, the explanatory and pr...

Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if parcellation schemes can systematically impact the predictive model error. In this work, st...

There is ongoing interest in the dynamics of resting state brain networks (RSNs) as potential predictors of cognitive and behavioural states. Multivariate Autoregressors (MAR) are used to model regional brain activity as a linear combination of past activity in other regions. The coefficients of the MAR are taken as estimates of effective brain con...

Advances in functional magnetic resonance spectroscopy (fMRS) have enabled the quantification of activity-dependent changes in neurotransmitter concentrations in vivo. However, the physiological basis of the large changes in GABA and glutamate observed by fMRS (>10%) over short time scales of less than a minute remain unclear as such changes cannot...

Previous research has demonstrated inter-individual variability in the influence of different components such as nociception or expectations on pain perception. Identifying the relative influence of these components could serve as a patient stratification tool. Nevertheless, this would only be of use if the influence of each component is stable in...

Multivariate autoregressive models [MAR] allows estimating effective brain connectivity by considering both power and phase fluctuations of the signals involved. A MAR models brain activity in one region as a linear combination of past activations in all other regions. A Hidden Markov model, HMM, whose states’ emisions are drawn from state-specific...

Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Many studies have combined structural and functional neuroimaging techniques to uncover the complex relationship between them. Here, we report the first systematic review that assesses how information from structural and functiona...

Pain-related catastrophising is a maladaptive coping strategy known to have a strong influence on clinical pain outcomes and treatment efficacy. Notwithstanding, little is known about its neurophysiological correlates. There is evidence to suggest catastrophising is associated with resting-state EEG frontal alpha asymmetry (FAA) patterns reflective...

The relationship between structural and functional brain networks has been characterised as complex: the two networks mirror each other and show mutual influence but they also diverge in their organisation. This work explored whether a combination of structural and functional connectivity can improve the fit of regression models of cognitive perfor...

In placebo analgesia, the expectation of pain reduction results in actual reduction in pain experience. Yet, there is substantial variability between participants in the magnitude of the placebo response, allowing a data-driven discrimination between placebo “responders” and “non-responders”. The mechanisms driving the difference between these grou...

Pain-related catastrophising is a maladaptive coping strategy known to have a strong influence on clinical pain outcomes and treatment efficacy. Mounting evidence suggests catastrophising is associated with resting-state EEG frontal alpha asymmetry (FAA) patterns reflective of greater relative right frontal activity, thought to underly withdrawal m...

One-third of the population in the UK and worldwide struggle with chronic pain. Entraining brain alpha activity through noninvasive visual stimulation has been shown to reduce experimental pain in healthy volunteers. Neural oscillations entrainment offers a potential noninvasive and nonpharmacological intervention for patients with chronic pain, wh...

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 tim...

One-third of the population in the UK and worldwide struggle with chronic pain. Entraining brain alpha activity through non-invasive visual stimulation has been shown to reduce experimental pain in healthy volunteers. Neural oscillations entrainment offers a potential non-invasive and non-pharmacological intervention for patients with chronic pain,...

Frequency-dependent reorganization of the primary somatosensory cortex, together with perceptual changes, arises following repetitive sensory stimulation. Here, we investigate the role of GABA in this process. We co-stimulated two finger tips and measured GABA and Glx using magnetic resonance (MR) spectroscopy at the beginning and end of the stimul...

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 muscu...

There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature...

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 muscu...

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 thei...

Significance We extend the concept of frequency-dependent plasticity, thus far used to describe synaptic selective adaptation in response to stimulation at different frequencies, to the level of cortical networks. We demonstrate selective changes in perception, functional topography, and connectivity of the primary somatosensory cortex following ta...

Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emer...

Resonance properties and entrainment of a single-unit. A The effect of varying the excitatory and inhibitory time constants (τe and τi) on the spectral output of a single unit responding to a white-noise input is given, as previously shown in [43,44]. Left figure shows the mean peak frequency of a single unit and the power of the mean peak frequenc...

Effect of extrinsic noise and inter-unit connectivity strengths on the model output. A The mean peak frequency and the power of the mean peak frequency of the 30x30 unit network as a function of increasing the standard deviation of the random white noise input (z) was calculated using the bootstrap method previously described with 100 trials. The m...

This article summarizes the theoretical foundations of Bayesian model inference as regards model selection and model averaging. Although not formally treated here, model combination is also motivated as a variant of Bayesian model averaging. The main practical implementations and approximations to model inference are reviewed, and the relationships...

We analyze the functional significance of different event-related potentials (ERPs) as electrophysiological indices of face perception and face recognition, according to cognitive and neurofunctional models of face processing. Initially, the processing of faces seems to be supported by early extrastriate occipital cortices and revealed by modulatio...

There is amassing evidence that risky decision-making in bipolar disorder is related to reward-based differences in frontostriatal regions. However, the roles of early attentional and later cognitive processes remain unclear, limiting theoretical understanding and development of targeted interventions. Twenty euthymic bipolar disorder and 19 matche...

The neural basis of selective attention within hierarchically organized Navon figures has been extensively studied with event related potentials (ERPs), by contrasting responses obtained when attending the global and the local echelons. The findings are inherently ambiguous because both levels are always presented together. Thus, only a mixture of...

Previous studies with compound letters have not been able to dissociate in time the presentation of the global and local levels. Therefore, direct timing of attentional shifts between levels has not been possible, nor has the Hillyard sustained-selective attention paradigm been fully applied. Here we describe work with a new approach, rapid serial...

The human central auditory system can automatically extract abstract regularities from a variant auditory input. To this end, temporarily separated events need to be related. This study tested whether the timing between events, falling either within or outside the temporal window of integration (~350 ms), impacts the extraction of abstract feature...

Introduction: We propose that active Bayesian inference—a general framework for decision-making—can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant...

The N400 component is commonly associated with the detection of linguistic incongruity. A few studies have shown that the N400 can also be elicited by non-linguistic stimuli. Different spatiotemporal patterns were observed between the typical Linguistic N400 and the Non-linguistic N400, suggesting distinct brain generators. The aim of this study wa...

Does temporal regularity facilitate prediction in audition? To test this, we recorded human event-related potentials to frequent standard tones and infrequent pitch deviant tones, pre-attentively delivered within isochronous and anisochronous (20% onset jitter) rapid sequences. Deviant tones were repeated, either with high or low probability. Stand...

The lack of clear understanding of the pathophysiology of chronic pain could explain why we currently have only a few effective treatments. Understanding how pain relief is realised during placebo analgesia could help develop improved treatments for chronic pain. Here, we tested whether experimental placebo analgesia was associated with altered res...

The auditory processing of self-generated sounds is characterized by an attenuated vertex N1-component of the event-related potential (ERP) compared to the responses elicited by externally generated sounds. Typically, a motor condition where sounds are actively produced by button presses is compared with a passive listening condition. While this ef...

The role of induced gamma-band responses (iGBRs) in the human electroencephalogram (EEG) is a controversial topic. On the one hand, iGBRs have been associated with neuronal activity reflecting the (re-)activation of cortical object representations. On the other hand, it was shown that miniature saccades (MSs) lead to high-frequency artifacts in the...

The remarkable capabilities displayed by humans in making sense of an overwhelming amount of sensory information cannot be explained easily if perception is viewed as a passive process. Current theoretical and computational models assume that to achieve meaningful and coherent perception, the human brain must anticipate upcoming stimulation. But ho...

Brain Electric/Magnetic Tomography (BET /BMT) consists of a 3D-image reconstruction of the Primary Current Density inside the brain from the signals measured outside the head, which can be considered as a functional neuroimaging modality. Mathematically, this is known as the EEG/MEG inverse problem (IP), which is ill posed (non-unique solution). To...

The automatic processing of deviances from the temporal context of the visual environment has become an important topic in visual cognitive sciences, which is often investigated using the visual mismatch negativity (vMMN). This event-related potential (ERP) component is elicited by an irregular stimulus (e.g., a red disc) presented in a series of s...

The precise neural mechanisms underlying speech sound representations are still a matter of debate. Proponents of 'sparse representations' assume that on the level of speech sounds, only contrastive or otherwise not predictable information is stored in long-term memory. Here, in a passive oddball paradigm, we challenge the neural foundations of suc...

Conventional neuroscientific methods are inadequate for separating the brain responses related to the simultaneous processing of different parts of a natural scene. In the present human electroencephalogram (EEG) study, we overcame this limitation by tagging concurrently presented backgrounds and objects with different presentation frequencies. As...

Induced gamma band responses (iGBRs) in the human electroencephalogram (EEG) have been ascribed to the activation of cortical object representations. Recently, this claim was challenged and it was stated that iGBRs occurring in the time window between 200 and 350 ms after stimulus onset are, to a great extent, generated by an electromyogenic artifa...

In present high density electroencephalogram (EEG) study, we examined steady-state visual evoked potential (SSVEP) correlates of object recognition. In SSVEP tasks a visual stimulus is presented repetitively at a specific flickering rate and typically elicits a continuous oscillatory brain response. This response is characterized by the same fundam...

Electrophysiological (EEG/MEG) imaging challenges statistics by providing two views of the same underlying spatio-temporal brain activity: a topographic view (EEG/MEG) and tomographic view (EEG/MEG source reconstructions). It is a common practice that statistical parametric mapping (SPM) for these two situations is developed separately. In particul...

Although subtle anatomical anomalies long precede the onset of clinical symptoms in Alzheimer's disease, their impact on the reorganization of brain networks underlying cognitive functions has not been fully explored. A unique window into this reorganization is provided by presymptomatic cases of familial Alzheimer's disease (FAD). Here we studied...

The goal of this paper is to assess the P-value of local maxima of time-varying cross-correlation random fields. The motivation for this comes from an electroencephalography (EEG) experiment, where one seeks connectivity between all pairs of voxels inside the brain at each time point of the recording window. In this way, we extend the results of [C...

One of the most interesting problems studied in Random Field Theory (RFT) is to approximate the distribution of the maximum of a random field. This problem usually appears in a general hypothesis testing framework, where the statistics of interest are the maximum of a random field of a known distribution. In this paper, we use the RFT approach to c...

In this work, we attempt to extend to the schizophrenia's research the evidence that different frequency bands may emerge from different sources during early-stage visual processing, in a mental state-specific manner, while subjects are passively viewing a visual stimulus. We applied standard pattern reversal stimulation (checker-board), a task wit...

This paper extends a previously formulated deterministic metabolic/hemodynamic model for the generation of blood oxygenated level dependent (BOLD) responses to include both physiological and observation stochastic components (sMHM). This adds a degree of flexibility when fitting the model to actual data by accounting for un-modelled activity. We th...

Binocular rivalry occurs when dissimilar images are presented to corresponding retinal regions of the two eyes: visibility alternates irregularly between the two images, interspersed by brief transitions when parts of both may be visible. We measured event-related potentials (ERPs) following binocular rivalry by changing the stimulus viewed by one...

This article proposes a Bayesian spatio-temporal model for source reconstruction of M/EEG data. The usual two-level probabilistic model implicit in most distributed source solutions is extended by adding a third level which describes the temporal evolution of neuronal current sources using time-domain General Linear Models (GLMs). These comprise a...

This paper presents a variational treatment of dynamic models that furnishes time-dependent conditional densities on the path or trajectory of a system's states and the time-independent densities of its parameters. These are obtained by maximising a variational action with respect to conditional densities, under a fixed-form assumption about their...

Contingent relations between sensory events render the environment predictable and thus facilitate adaptive behavior. The human capacity to detect such relations has been comprehensively demonstrated in paradigms in which contingency rules were task-relevant or in which they applied to motor behavior. The extent to which contingencies can also be e...

Natural stimuli are compiled of numerous features, which are cortically represented in dispersed structures. Synchronized oscillations in the Gamma-Band (>30 Hz; induced Gamma-Band Responses, iGBRs), are regarded as a plausible mechanism to re-integrate these regions into a meaningful cortical object representation. Using electroencephalography (EE...

This paper describes an application of hierarchical or empirical Bayes to the distributed source reconstruction problem in electro- and magnetoencephalography (EEG and MEG). The key contribution is the automatic selection of multiple cortical sources with compact spatial support that are specified in terms of empirical priors. This obviates the nee...

When something appears, how soon is the first neural correlate of awareness of it, and where is that activity in the brain? To answer these questions, we measured the electroencephalogram under conditions in which visual stimuli changed identically but in which awareness differed. We manipulated awareness by using binocular rivalry between orthogon...

Our goal is to model the coupling between neuronal activity, cerebral metabolic rates of glucose and oxygen consumption, cerebral blood flow (CBF), electroencephalography (EEG) and blood oxygenation level-dependent (BOLD) responses. In order to accomplish this, two previous models are coupled: a metabolic/hemodynamic model (MHM) for a voxel, linkin...

This article proposes a Bayesian spatio-temporal model for source reconstruction of M/EEG data. The usual two-level probabilistic model implicit in most distributed source solutions is extended by adding a third level which describes the temporal evolution of neuronal current sources using time-domain General Linear Models (GLMs). These comprise a...

We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimized. The application we have in mind is a spatiotemporal model for imaging data. We illustrate the method on a ra...

This note derives the variational free energy under the Laplace approximation, with a focus on accounting for additional model complexity induced by increasing the number of model parameters. This is relevant when using the free energy as an approximation to the log-evidence in Bayesian model averaging and selection. By setting restricted maximum l...

Ignore condition for concrete rules. a) Grand-average ERPs elicited by standards (black) and deviants (gray), and deviant minus standard difference wave (red). b) Topographic distributions of the MMN and P3a components (scalp current density, SCD). Electrode positions with SCD values significantly deviating from zero are indicated in the p-value ma...

Distraction condition for concrete rules. a) Grand-average ERPs elicited by standards (black) and deviants (gray), and deviant minus standard difference wave (red). b) Topographic distributions of the MMN and P3a components (scalp current density, SCD). Electrode positions with SCD values significantly deviating from zero are indicated in the p-val...

Detection condition for concrete rules. a) Grand-average ERPs elicited by standards (black) and deviants (gray), and deviant minus standard difference wave (red) for detected deviants. ERPs for undetected deviants are not shown because they occurred too rarely (98% correctly indicated deviants). b) Topographic distributions of the MMN and P3a compo...

Detection patterns. In the abstract detection condition, a higher proportion of deviant tone pairs was registered when the second tone in the pair was long (left panel), and when the absolute frequency difference to the preceding tone pair was large as determined by a median split per subject (right panel). Significance of the differences in detect...

The increase of induced gamma-band responses (iGBRs; oscillations >30 Hz) elicited by familiar (meaningful) objects is well established in electroencephalogram (EEG) research. This frequency-specific change at distinct locations is thought to indicate the dynamic formation of local neuronal assemblies during the activation of cortical object repres...

A biophysical model of the coupling between neuronal activity and the BOLD signal that allows for explicitly evaluating the role of both excitatory and inhibitory activity is formulated in this paper. The model is based on several physiological assumptions. Firstly, in addition to glycolysis, the "glycogen shunt" is assumed for excitatory synapses...

Focusing attention to a specific body location has been shown to improve processing of events presented at this body location. One important debate concerns the stage in the somatosensory pathway at which the neural response is modulated when one attends to a tactile stimulus. Previous studies focused on components of the somatosensory evoked poten...

In previous work (Penny et al., [2005]: Neuroimage 24:350-362) we have developed a spatially regularised General Linear Model for the analysis of functional magnetic resonance imaging data that allows for the characterisation of regionally specific effects using Posterior Probability Maps (PPMs). In this paper we show how it also provides an approx...

The ability to encode rules and to detect rule-violating events outside the focus of attention is vital for adaptive behavior. Our brain recordings reveal that violations of abstract auditory rules are processed even when the sounds are unattended. When subjects performed a task related to the sounds but not to the rule, rule violations impaired ta...

We study the generation of EEG rhythms by means of realistically coupled neural mass models. Previous neural mass models were used to model cortical voxels and the thalamus. Interactions between voxels of the same and other cortical areas and with the thalamus were taken into account. Voxels within the same cortical area were coupled (short-range c...

This note derives the variational free energy under the Laplace approximation, with a focus on accounting for additional model complexity induced by increasing the number of model parameters. This is relevant when using the free energy as an approximation to the log-evidence in Bayesian model averaging and selection. By setting restricted maximum l...

The formation of cortical object representations requires the activation of cell assemblies, correlated by induced oscillatory bursts of activity > 20 Hz (induced gamma band responses; iGBRs). One marker of the functional dynamics within such cell assemblies is the suppression of iGBRs elicited by repeated stimuli. This effect is commonly interpret...

In order to keep track of potentially relevant information in the acoustic environment, the human brain processes sounds to a high extent even when they are not attended: it extracts basic features, encodes regularities, and detects deviances. Here, we deliver evidence that the initial 300 ms of a sound contribute more to this preattentive processi...

The formation of cortical object representations requires the activation of cell assemblies, correlated by induced oscillatory bursts above 20 Hz (gamma band), which are characterized by trial-by-trial latency fluctuations around a mean of approximately 300 ms after stimulus onset. The present electroencephalogram (EEG) study was intended to uncove...