RESUMO

Characterization of brain states is essential for understanding its functioning in the absence of external stimuli. Brain states differ on their balance between excitation and inhibition, and on the diversity of their activity patterns. These can be respectively indexed by 1/f slope and Lempel-Ziv complexity (LZc). However, whether and how these two brain state properties relate remain elusive. Here we analyzed the relation between 1/f slope and LZc with two in-silico approaches and in both rat EEG and monkey ECoG data. We contrasted resting state with propofol anesthesia, which directly modulates the excitation-inhibition balance. We found convergent results among simulated and empirical data, showing a strong, inverse and non trivial monotonic relation between 1/f slope and complexity, consistent at both ECoG and EEG scales. We hypothesize that differentially entropic regimes could underlie the link between the excitation-inhibition balance and the vastness of the repertoire of brain systems.

Assuntos

RESUMO

La planificación es definida como la habilidad de desarrollar un plan secuenciado de pasos conductuales para alcanzar una meta y forma parte de un conjunto de funciones cognitivas de alto orden denominadas funciones ejecutivas. Esta función se ve afectada en diversas situaciones de la vida cotidiana y en una variedad de trastornos neuropsiquiátricos (por ej., depresión, ansiedad, déficit atencional, esquizofrenia, etc.). Tanto el diseño de pruebas cognitivas para evaluar planificación en el contexto clínico, como también el diseño de paradigmas experimentales de evaluación de la planificación en el contexto de investigación, continúa siendo un desafío para la neuropsicología clínica y para las neurociencias. En este artículo de revisión sistemática que sigue las direcciones PRISMA, revisamos la teoría e investigación en relación con la evaluación clínica y la investigación de las bases neurobiológicas de la planificación y los aportes a la comprensión de los mecanismos de su implementación. Se reportan medidas metodológicas comunes y se resumen las aproximaciones teóricas que contribuyen en su comprensión. Nuestros hallazgos muestran la implicancia de la corteza prefrontal en el rendimiento en planificación, en particular el área dorsolateral, corteza cingulada anterior y frontopolar. Mayores estudios clínicos, instrumentales y experimentales son necesarios para comprender mejor la planificación en el contexto de una teoría integrativa de las funciones ejecutivas y del rol de la corteza prefrontal.

Planning is defined as the ability to develop a sequenced plan of behavioral steps to achieve a goal and is part of a set of high-order cognitive functions called executive functions. This function is affected in various daily life situations and in a variety of neuropsychiatric disorders (e.g., depression, anxiety, attention deficit disorder, schizophrenia, etc.). Both the design of cognitive tests to assess planning in the clinical context, as well as the design of experimental paradigms for evaluating planning in research context, continues to be a challenge for clinical neuropsychology and neurosciences. In this PRISMA systematic review article, we review theory and research regarding clinical assessment and research into the neurobiological bases of planning and contributions to understanding the mechanisms of its implementation. Common methodological measures are reported and the theoretical approaches that contribute to their understanding are summarized. Our findings show the involvement of the prefrontal cortex in planning performance, particularly the dorsolateral area, the anterior cingulate cortex, and the frontopolar cortex. Further clinical, instrumental, and experimental studies are needed to better understand planning in the context of an integrative theory of executive functions and the role of the prefrontal cortex.

Assuntos

RESUMO

Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the "happiness emotional brain state" of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4-1 Median = 6.563%; Range = 4.10-27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1-15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.

RESUMO

Detection of novel stimuli that violate statistical regularities in the sensory scene is of paramount importance for the survival of biological organisms. Event-related potentials, phasic increases in pupil size, and evoked changes in oscillatory power have been proposed as markers of sensory novelty detection. However, how conscious access to novelty modulates these different brain responses is not well understood. Here, we studied the neural responses to sensory novelty in the auditory modality with and without conscious access. We identified individual thresholds for conscious auditory discrimination and presented to our participants sequences of tones, where the last stimulus could be another standard, a subthreshold target or a suprathreshold target. Participants were instructed to report whether the last tone of each sequence was the same or different from those preceding it. Results indicate that attentional orientation to behaviorally relevant stimuli and overt decision-making mechanisms, indexed by the P3 event-related response and reaction times, best predict whether a novel stimulus will be consciously accessed. Theta power and pupil size do not predict conscious access to novelty, but instead reflect information maintenance and unexpected sensory uncertainty. These results highlight the interplay between bottom-up and top-down mechanisms and how the brain weights neural responses to novelty and uncertainty during perception and goal-directed behavior.

Assuntos

RESUMO

Hippocampal-dependent memories emerge late during postnatal development, aligning with hippocampal maturation. During sleep, the two-stage memory formation model states that through hippocampal-neocortical interactions, cortical slow-oscillations (SO), thalamocortical Spindles, and hippocampal sharp-wave ripples (SWR) are synchronized, allowing for the consolidation of hippocampal-dependent memories. However, evidence supporting this hypothesis during development is still lacking. Therefore, we performed successive object-in-place tests during a window of memory emergence and recorded in vivo the occurrence of SO, Spindles, and SWR during sleep, immediately after the memory encoding stage of the task. We found that hippocampal-dependent memory emerges at the end of the 4th postnatal week independently of task overtraining. Furthermore, we observed that those animals with better performance in the memory task had increased Spindle density and duration and lower density of SWR. Moreover, we observed changes in the SO-Spindle and Spindle-SWR temporal-coupling during this developmental period. Our results provide new evidence for the onset of hippocampal-dependent memory and its relationship to the oscillatory phenomenon occurring during sleep that helps us understand how memory consolidation models fit into the early stages of postnatal development.