Auditory verbal hallucinations: imaging, analysis, and intervention

In this article, we will link neuroimaging, data analysis, and intervention methods in an important psychiatric condition: auditory verbal hallucinations (AVH). The clinical and phenomenological background as well as neurophysiological findings will be covered and discussed with respect to noninvasive brain stimulation. Additionally, methods of noninvasive brain stimulation will be presented as ways to intervene with AVH. Finally, preliminary conclusions and possible future perspectives will be proposed.

Uncrossed cortico-muscular projections in humans are abundant to facial muscles of the upper and lower face, but may differ between sexes

It is a popular concept in clinical neurology that muscles of the lower face receive predominantly crossed cortico-bulbar motor input, whereas muscles of the upper face receive additional ipsilateral, uncrossed input. To test this notion, we used focal transcranial magnetic brain stimulation to quantify crossed and uncrossed cortico-muscular projections to 6 different facial muscles (right and left Mm. frontalis, nasalis, and orbicularis oris) in 36 healthy right-handed volunteers (15 men, 21 women, mean age 25 years). Uncrossed input was present in 78% to 92% of the 6 examined muscles. The mean uncrossed: crossed response amplitude ratios were 0.74/0.65 in right/left frontalis, 0.73/0.59 in nasalis, and 0.54/0.71 in orbicularis oris; ANOVA p>0.05). Judged by the sizes of motor evoked potentials, the cortical representation of the 3 muscles was similar. The amount of uncrossed projections was different between men and women, since men had stronger left-to-left projections and women stronger right-to-right projections. We conclude that the amount of uncrossed pyramidal projections is not different for muscles of the upper from those of the lower face. The clinical observation that frontal muscles are often spared in central facial palsies must, therefore, be explained differently. Moreover, gender specific lateralization phenomena may not only be present for higher level behavioural functions, but may also affect simple systems on a lower level of motor hierarchy.

Effect of discharge desynchronization on the size of motor evoked potentials: an analysis

OBJECTIVE: Motor evoked potentials (MEPs) after transcranial magnetic brain stimulation (TMS) are smaller than CMAPs after peripheral nerve stimulation, because desynchronization of the TMS-induced motor neurone discharges occurs (i.e. MEP desynchronization). This desynchronization effect can be eliminated by use of the triple stimulation technique (TST; Brain 121 (1998) 437). The objective of this paper is to study the effect of discharge desynchronization on MEPs by comparing the size of MEP and TST responses. METHODS: MEP and TST responses were obtained in 10 healthy subjects during isometric contractions of the abductor digiti minimi, during voluntary background contractions between 0% and 20% of maximal force, and using 3 different stimulus intensities. Additional data from other normals and from multiple sclerosis (MS) patients were obtained from previous studies. RESULTS: MEPs were smaller than TST responses in all subjects and under all stimulating conditions, confirming the marked influence of desynchronization on MEPs. There was a linear relation between the amplitudes of MEPs vs. TST responses, independent of the degree of voluntary contraction and stimulus intensity. The slope of the regression equation was 0.66 on average, indicating that desynchronization reduced the MEP amplitude on average by one third, with marked inter-individual variations. A similar average proportion was found in MS patients. CONCLUSIONS: The MEP size reduction induced by desynchronization is not influenced by the intensity of TMS and by the level of facilitatory voluntary background contractions. It is similar in healthy subjects and in MS patients, in whom increased desynchronization of central conduction was previously suggested to occur. Thus, the MEP size reduction observed may not parallel the actual amount of desynchronization.

Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice.

Humans are noted for their capacity to over-ride self-interest in favor of normatively valued goals. We examined the neural circuitry that is causally involved in normative, fairness-related decisions by generating a temporarily diminished capacity for costly normative behavior, a 'deviant' case, through non-invasive brain stimulation (repetitive transcranial magnetic stimulation) and compared normal subjects' functional magnetic resonance imaging signals with those of the deviant subjects. When fairness and economic self-interest were in conflict, normal subjects (who make costly normative decisions at a much higher frequency) displayed significantly higher activity in, and connectivity between, the right dorsolateral prefrontal cortex (DLPFC) and the posterior ventromedial prefrontal cortex (pVMPFC). In contrast, when there was no conflict between fairness and economic self-interest, both types of subjects displayed identical neural patterns and behaved identically. These findings suggest that a parsimonious prefrontal network, the activation of right DLPFC and pVMPFC, and the connectivity between them, facilitates subjects' willingness to incur the cost of normative decisions.

Self-control in social decision making: A neurobiological perspective

Self-control is defined as the process in which thoughts, emotions, or prepotent responses are inhibited to efficiently enact a more focal goal. Self-control not only allows for more adaptive individual decision making but also promotes adaptive social decision making. In this chapter, we examine a burgeoning area of interdisciplinary research: the neuroscience of self-control in social decision making. We examine research on self-control in complex social contexts examined from a social neuroscience perspective. We review correlational evidence from neuroimaging studies and causal evidence from neuromodulation studies (i.e., brain stimulation). We specifically highlight research that shows that self-control involves the lateral prefrontal cortex (PFC) across a number of social domains and behaviors. Research has also begun to directly integrate nonsocial with social forms of self-control, showing that the basic neurobiological processes involved in stopping a motor response appear to be involved in social contexts that require self-control. Further, neural traits, such as baseline activation in the lateral PFC, can explain sources of individual differences in self-control capacity. We explore whether techniques that change brain functioning could target neural mechanisms related to self-control capacity to potentially enhance self-control in social behavior. Finally, we discuss several research questions ripe for examination. We broadly suggest that future research can now turn to exploring how neural traits and situational affordances interact to impact self-control in social decision making in order to continue to elucidate the processes that allow people to maintain and realize stable goals in a dynamic and often uncertain social environment.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Cathodal HD-tDCS on the right V5 improves motion perception in humans

Brain lesions in the visual associative cortex are known to impair visual perception, i.e., the capacity to correctly perceive different aspects of the visual world, such as motion, color, or shapes. Visual perception can be influenced by non-invasive brain stimulation such as transcranial direct current stimulation (tDCS). In a recently developed technique called high definition (HD) tDCS, small HD-electrodes are used instead of the sponge electrodes in the conventional approach. This is believed to achieve high focality and precision over the target area. In this paper we tested the effects of cathodal and anodal HD-tDCS over the right V5 on motion and shape perception in a single blind, within-subject, sham controlled, cross-over trial. The purpose of the study was to prove the high focality of the stimulation only over the target area. Twenty one healthy volunteers received 20 min of 2 mA cathodal, anodal and sham stimulation over the right V5 and their performance on a visual test was recorded. The results showed significant improvement in motion perception in the left hemifield after cathodal HD-tDCS, but not in shape perception. Sham and anodal HD-tDCS did not affect performance. The specific effect of influencing performance of visual tasks by modulating the excitability of the neurons in the visual cortex might be explained by the complexity of perceptual information needed for the tasks. This provokes a "noisy" activation state of the encoding neuronal patterns. We speculate that in this case cathodal HD-tDCS may focus the correct perception by decreasing global excitation and thus diminishing the "noise" below threshold.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

A new mechanism of sound generation in songbirds

Our current understanding of the sound-generating mechanism in the songbird vocal organ, the syrinx, is based on indirect evidence and theoretical treatments. The classical avian model of sound production postulates that the medial tympaniform membranes (MTM) are the principal sound generators. We tested the role of the MTM in sound generation and studied the songbird syrinx more directly by filming it endoscopically. After we surgically incapacitated the MTM as a vibratory source, zebra finches and cardinals were not only able to vocalize, but sang nearly normal song. This result shows clearly that the MTM are not the principal sound source. The endoscopic images of the intact songbird syrinx during spontaneous and brain stimulation-induced vocalizations illustrate the dynamics of syringeal reconfiguration before phonation and suggest a different model for sound production. Phonation is initiated by rostrad movement and stretching of the syrinx. At the same time, the syrinx is closed through movement of two soft tissue masses, the medial and lateral labia, into the bronchial lumen. Sound production always is accompanied by vibratory motions of both labia, indicating that these vibrations may be the sound source. However, because of the low temporal resolution of the imaging system, the frequency and phase of labial vibrations could not be assessed in relation to that of the generated sound. Nevertheless, in contrast to the previous model, these observations show that both labia contribute to aperture control and strongly suggest that they play an important role as principal sound generators.

Restoring function after neuromuscular trauma: novel paradigms for enhancing volitional control of neural activity in untethered environments and vHAB, a gamified therapy platform

Thesis (Ph.D.)--University of Washington, 2016-08

Neurophysiologie du langage : apports de la neuro-imagerie et état des connaissances

International audience

Limits to tDCS effects in language:failures to modulate word production in healthy participants with frontal or temporal tDCS

Transcranial direct current stimulation (tDCS) is a method of non-invasive brain stimulation widely used to modulate cognitive functions. Recent studies, however, suggests that effects are unreliable, small and often non-significant at least when stimulation is applied in a single session to healthy individuals. We examined the effects of frontal and temporal lobe anodal tDCS on naming and reading tasks and considered possible interactions with linguistic activation and selection mechanisms as well possible interactions with item difficulty and participant individual variability. Across four separate experiments (N, Exp 1A = 18; 1B = 20; 1C = 18; 2 = 17), we failed to find any difference between real and sham stimulation. Moreover, we found no evidence of significant effects limited to particular conditions (i.e., those requiring suppression of semantic interference), to a subset of participants or to longer RTs. Our findings sound a cautionary note on using tDCS as a means to modulate cognitive performance. Consistent effects of tDCS may be difficult to demonstrate in healthy participants in reading and naming tasks, and be limited to cases of pathological neurophysiology and/or to the use of learning paradigms.

Differential expression of Egr-1-like DNA-binding activities in the naive rat brain and after excitatory stimulation

Egr-1 and related proteins are inducible transcription factors within the brain recognizing the same consensus DNA sequence. Three Egr DNA-binding activities were observed in regions of the naive rat brain. Egr-1 was present in all brain regions examined. Bands composed, at least in part, of Egr-2 and Egr-3 were present in different relative amounts in the cerebral cortex, striatum, hippocampus, thalamus, and midbrain. All had similar affinity and specificity for the Egr consensus DNA recognition sequence. Administration of the convulsants NMDA, kainate, and pentylenetetrazole differentially induced Egr-1 and Egr-2/3 DNA-binding activities in the cerebral cortex, hippocampus, and cerebellum. All convulsants induced Egr-1 and Egr-2 immunoreactivity in the cerebral cortex and hippocampus. These data indicate that the members of the Egr family are regulated at different levels and may interact at promoters containing the Egr consensus sequence to fine tune a program of gene expression resulting from excitatory stimuli.

Epidermal growth factor (EGF) stimulation of cultured brain cells. I. Enhancement of the developmental increase in glial enzymatic activity.

Serum-free aggregating cell cultures of fetal rat telencephalon grown in the presence of 3 ng/ml (5 X 10(-10) M) epidermal growth factor (EGF) until day 12 showed 2- to 3-fold increased activities in the two glial enzymes, glutamine synthetase (GLU-S) and 2',3'-cyclic nucleotide 3'-phosphohydrolase (CNPase). This effect was concentration-dependent, with maximal stimulation in cultures treated daily with 3 ng/ml EGF. Addition of EGF during the first 10 culture days was sufficient to produce a maximal stimulation of both GLU-S and CNPase on day 19, whereas treatments starting on day 12 were ineffective. The stimulation of GLU-S preceded that of CNPase. The EGF-induced increase in GLU-S activity was not directly dependent on the presence of insulin, triiodothyronine, or hydrocortisone in the medium, whereas insulin was required for the stimulation of CNPase. A single dose of 5 ng/ml EGF on day 2 caused a slight but significant decrease in DNA synthesis after day 6. The present results indicate that in serum-free aggregating cell cultures of fetal rat telencephalon EGF partially inhibits DNA synthesis, and stimulates an early step in glial differentiation.