Cuentos interactivos para el desarrollo de las habilidades comunicativas del idioma quechua en niños de cinco años de Comas, 2021

La presente investigación fue titulada Cuentos interactivos para el desarrollo de las habilidades comunicativas del idioma Quechua en niños de cinco años de Comas, 2021 tuvo como objetivo general determinar la influencia de los cuentos interactivos para el desarrollo de las habilidades comunicativas del idioma Quechua en niños de cinco años de la institución educativa “Señor de los Milagros” del distrito de Comas, 2021 para su realización se empleó un enfoque cuantitativo de tipo aplicada con un diseño cuasi experimental con una población de 19 niños de cinco años. Para llevar a cabo la recolección de datos se usó la técnica de la encuesta aplicándose como instrumentos al pre test y post test los cuales contaron con 20 ítems, asimismo, para realizar una mejor evaluación se hizo uso de una lista de cotejo la cual fue aplicada luego de ejecutarse el programa experimental (post test) obteniéndose como resultado que el 94.7% de los infantes llegó al nivel “logrado” demostrando dominio en la expresión y comprensión oral, concluyendo que la mayoría de los infantes alcanzaron el nivel logrado en el desarrollo de habilidades comunicativas de la expresión y comprensión oral del idioma quechua luego de haber participado del programa Yachaqay Quechua

Application of Transcranial Direct Current Stimulation in Psychiatry

Transcranial direct current stimulation (tDCS) is a neuromodulation technique, which noninvasively alters cortical excitability via weak polarizing currents between two electrodes placed on the scalp. Since it is comparably easy to handle, cheap to use and relatively well tolerated, tDCS has gained increasing interest in recent years. Based on well-known behavioral effects, a number of clinical studies have been performed in populations including patients with major depressive disorder followed by schizophrenia and substance use disorders, in sum with heterogeneous results with respect to efficacy. Nevertheless, the potential of tDCS must not be underestimated since it could be further improved by systematically investigating the various stimulation parameters to eventually increase clinical efficacy. The present article briefly explains the underlying physiology of tDCS, summarizes typical stimulation protocols and then reviews clinical efficacy for various psychiatric disorders as well as prevalent adverse effects. Future developments include combined and more complex interactions of tDCS with pharmacological or psychotherapeutic interventions. In particular, using computational models to individualize stimulation protocols, considering state dependency and applying closed-loop technologies will pave the way for tDCS-based personalized interventions as well as the development of home treatment settings promoting the role of tDCS as an effective treatment option for patients with mental health problems

Echoes of Affective Stimulation in Brain connectivity Networks

Affective experience has effects on subjective feelings, physiological indices, entails immediate activity changes in the brain, and even influences brain networks in a protracted manner. However, it is still unclear, how the functional connectivity (FC) interplay between major intrinsic connectivity networks upon affective stimulation depends on affective valence, and whether this is specific for affective experience, i.e., can be distinguished from cognitive task execution. Our study included fMRI scans during and after affective stimulation with sad and neutral movies and a working memory task complemented with measures of cardiovascular activity and mood. Via parcellation of the brain into default mode network (DMN), central executive network (CEN), and dorsal attention network, and application of network-based statistics, we identified subnetworks associated with changing psychological contexts. Specific effects for affective stimulation with negative valence were both reduced heart rate variability and mood, and upregulated FC of inter-CEN-DMN connections while intra-DMN connections were downregulated. Furthermore, results demonstrated a valence-specific dynamic carry-over effect in nodes of the CEN, which temporarily increased their FC strength after affective stimulation with negative valence and exhibited distinct temporal profiles. The reported effects were clearly distinguishable from those of a cognitive task and further elucidate the trajectory of affective experience

Echoes of Affective Stimulation in Brain connectivity Networks

Affective experience has effects on subjective feelings, physiological indices, entails immediate activity changes in the brain, and even influences brain networks in a protracted manner. However, it is still unclear, how the functional connectivity (FC) interplay between major intrinsic connectivity networks upon affective stimulation depends on affective valence, and whether this is specific for affective experience, i.e., can be distinguished from cognitive task execution. Our study included fMRI scans during and after affective stimulation with sad and neutral movies and a working memory task complemented with measures of cardiovascular activity and mood. Via parcellation of the brain into default mode network (DMN), central executive network (CEN), and dorsal attention network, and application of network-based statistics, we identified subnetworks associated with changing psychological contexts. Specific effects for affective stimulation with negative valence were both reduced heart rate variability and mood, and upregulated FC of inter-CEN-DMN connections while intra-DMN connections were downregulated. Furthermore, results demonstrated a valence-specific dynamic carry-over effect in nodes of the CEN, which temporarily increased their FC strength after affective stimulation with negative valence and exhibited distinct temporal profiles. The reported effects were clearly distinguishable from those of a cognitive task and further elucidate the trajectory of affective experience

Using routine MRI data of depressed patients to predict individual responses to electroconvulsive therapy

Electroconvulsive therapy (ECT) is one of the most effective treatments in cases of severe and treatment resistant major depression. 60–80% of patients respond to ECT, but the procedure is demanding and robust prediction of ECT responses would be of great clinical value. Predictions based on neuroimaging data have recently come into focus, but still face methodological and practical limitations that are hampering the translation into clinical practice. In this retrospective study, we investigated the feasibility of ECT response prediction using structural magnetic resonance imaging (sMRI) data that was collected during ECT routine examinations. We applied machine learning techniques to predict individual treatment outcomes in a cohort of N = 71 ECT patients, N = 39 of which responded to the treatment. SMRI-based classification of ECT responders and non-responders reached an accuracy of 69% (sensitivity: 67%; specificity: 72%). Classification on additionally investigated clinical variables had no predictive power. Since dichotomisation of patients into ECT responders and non-responders is debatable due to many patients only showing a partial response, we additionally performed a post-hoc regression-based prediction analysis on continuous symptom improvements. This analysis yielded a significant relationship between true and predicted treatment outcomes and might be a promising alternative to dichotomization of patients. Based on our results, we argue that the prediction of individual ECT responses based on routine sMRI holds promise to overcome important limitations that are currently hampering the translation of such treatment biomarkers into everyday clinical practice. Finally, we discuss how the results of such predictive data analysis could best support the clinician's decision on whether a patient should be treated with ECT.ISSN:0014-4886ISSN:1090-243

Cortical Amyloid Burden Relates to Basal Forebrain Volume in Subjective Cognitive Decline.

BACKGROUND Atrophy of cholinergic basal forebrain (BF) nuclei is a frequent finding in magnetic resonance imaging (MRI) volumetry studies that examined patients with prodromal or clinical Alzheimer's disease (AD), but less clear for individuals in earlier stages of the clinical AD continuum. OBJECTIVE To examine BF volume reductions in subjective cognitive decline (SCD) participants with AD pathologic changes. METHODS The present study compared MRI-based BF volume measurements in age- and sex-matched samples of N = 24 amyloid-positive and N = 24 amyloid-negative SCD individuals, based on binary visual ratings of Florbetaben positron emission tomography (PET) measurements. Additionally, we assessed associations of BF volume with cortical amyloid burden, based on semiquantitative Centiloid (CL) analyses. RESULTS Group differences approached significance for BF total volume (p = 0.061) and the Ch4 subregion (p = 0.059) only, showing the expected relative volume reductions for the amyloid-positive subgroup. There were also significant inverse correlations between BF volumes and CL values, which again were most robust for BF total volume and the Ch4 subregion. CONCLUSIONS The results are consistent with the hypothesis that amyloid-positive SCD individuals, which are considered to represent a transitional stage on the clinical AD continuum, already show incipient alterations of BF integrity. The negative association with a continuous measure of cortical amyloid burden also suggests that this may reflect an incremental process. Yet, further research is needed to evaluate whether BF changes already emerge at "grey zone" levels of amyloid accumulation, before amyloidosis is reliably detected by PET visual readings

Aberrant working memory processing in major depression: evidence from multivoxel pattern classification

Major depressive disorder (MDD) is often accompanied by severe impairments in working memory (WM). Neuroimaging studies investigating the mechanisms underlying these impairments have produced conflicting results. It remains unclear whether MDD patients show hyper- or hypoactivity in WM-related brain regions and how potential aberrations in WM processing may contribute to the characteristic dysregulation of cognition–emotion interactions implicated in the maintenance of the disorder. In order to shed light on these questions and to overcome limitations of previous studies, we applied a multivoxel pattern classification approach to investigate brain activity in large samples of MDD patients (N = 57) and matched healthy controls (N = 61) during a WM task that incorporated positive, negative, and neutral stimuli. Results showed that patients can be distinguished from healthy controls with good classification accuracy based on functional activation patterns. ROI analyses based on the classification weight maps showed that during WM, patients had higher activity in the left DLPFC and the dorsal ACC. Furthermore, regions of the default-mode network (DMN) were less deactivated in patients. As no performance differences were observed, we conclude that patients required more effort, indexed by more activity in WM-related regions, to successfully perform the task. This increased effort might be related to difficulties in suppressing task-irrelevant information reflected by reduced deactivation of regions within the DMN. Effects were most pronounced for negative and neutral stimuli, thus pointing toward important implications of aberrations in WM processes in cognition–emotion interactions in MDD