The resting frontal alpha asymmetry across the menstrual cycle: a magnetoencephalographic study

Gonadotropic hormones play an important role in the regulation of emotion. Previous studies have demonstrated that estrogen can modulate appetitive (approach/positive) and aversive (avoidance/negative) affective behaviors during the menstrual cycle. Frontal alpha asymmetry (a measure of relative difference of the alpha power between the two anterior hemispheres) has been associated with the trait and state reactivity of different affective styles. We studied the pattern change of frontal alpha asymmetry across the menstrual cycle. 16 healthy women participated in this resting magneto-encephalographic (MEG) study during the peri-ovulatory (OV) and menstrual (MC) phases. Our results showed significant interaction of resting MEG alpha activity between hemispheric side and menstrual phases. Difference in spontaneous frontal alpha asymmetry pattern across the menstrual cycle was also noted. Relatively higher right frontal activity was found during the OV phase; relatively higher left frontal activity was noted during the MC phase. The alteration of frontal alpha asymmetry might serve a sub-clinical correlate for hormonal modulation effect on dynamic brain organization for the predisposition and conceptualization of different affective styles across the menstrual cycle.     

Fluctuations in Neuronal Synchronization in Brain Activity Correlate with the Subjective Experience of Visual Recognition

The scientific study of subjective experience is a current major research area in the neurosciences. Coordination patterns of brain activity are being studied to address the question of how brain function relates to behaviour, and particularly methods to estimate neuronal synchronization can unravel the spatio-temporal dynamics of the transient formation of neuronal assemblies. We report here a biophysical correlate of subjective experience. Subjects visualised figures with different levels of noise, while their brain activity was recorded using magnetoencephalography (MEG), and reported the moment in time (corresponding to a noise level) of figure recognition, which varied between individuals, as well as the moment when they saw the figure more clearly, which was mostly common among the participants (thus less subjective). This latter moment is considered to represent psychophysical stochastic resonance (PSR). Fluctuations in neuronal synchronization, quantified using a diffusion coefficient, were lower in occipital cortex when subjects recognised the figure, for a certain noise level, but did not correlate with the moment of PSR. A different pattern was observed in frontal cortex, where lower values of the diffusion coefficient in neuronal synchronization was maintained from the moment of recognition to the moment of PSR. No specific pattern was found analysing signals from temporal or parietal cortical areas. These observations provide support for distinct synchronization patterns in different cortical areas, and represent another demonstration that the subjective, first-person perspective is accessible to scientific methods.      

基于粒子群优化算法的脑磁图源定位

脑磁图作为一种新型的脑探测技术,具有较高定位精度和毫秒级时间分辨率的特点。快速准确地利用脑磁图技术对三维空间中的脑神经活动源进行定位,对于脑功能研究和医学临床应用都具有重要的应用价值。可是,目前的脑磁图源定位广泛采用了多信号分类方法,它要求对三维大脑空间进行全局扫描,需要大量的计算,存在速度慢的缺点。针对这一问题,提出了一种基于粒子群优化算法的脑磁图源定位方法。先利用粒子群优化算法全局搜索能力强的特点寻找出目标函数的全局最优值,进行初步的脑磁图源定位;然后,再在小范围内进行小网格的搜索,进一步实现精确的定位。实验结果表明,基于粒子群优化算法的脑磁图源定位能够很好地解决上述问题,具有计算速度快、定位精度高的特点。     

基于混沌优化算法的MUSIC脑磁图源定位方法

如何利用实验测得的脑磁图数据准确定位脑磁图源的真实活动位置是脑功能研究和临床应用中的一个关键问题.在脑磁活动源定位问题中,多信号分类算法是被广泛研究和采用的一类方法.为了克服多信号分类算法及其改进算法--递归多信号分类算法全局扫描时速度太慢的缺点,提出了一种基于混沌优化算法的脑磁图源定位新方法.该方法利用混沌运动遍历性的特点估计目标函数的全局最大值,进行初步的脑磁图源定位;然后,在小范围内结合网格的方法,进一步进行精确的定位.实验结果表明,此方法可实现多个脑磁图源的定位,并且定位速度大大加快,同时又能达到所要求的定位精度.     

Distinct dynamical patterns that distinguish willed and forced actions

The neural pathways for generating willed actions have been increasingly investigated since the famous pioneering work by Benjamin Libet on the nature of free will. To better understand what differentiates the brain states underlying willed and forced behaviours, we performed a study of chosen and forced actions over a binary choice scenario. Magnetoencephalography recordings were obtained from six subjects during a simple task in which the subject presses a button with the left or right finger in response to a cue that either (1) specifies the finger with which the button should be pressed or (2) instructs the subject to press a button with a finger of their own choosing. Three independent analyses were performed to investigate the dynamical patterns of neural activity supporting willed and forced behaviours during the preparatory period preceding a button press. Each analysis offered similar findings in the temporal and spatial domains and in particular, a high accuracy in the classification of single trials was obtained around 200 ms after cue presentation with an overall average of 82%. During this period, the majority of the discriminatory power comes from differential neural processes observed bilaterally in the parietal lobes, as well as some differences in occipital and temporal lobes, suggesting a contribution of these regions to willed and forced behaviours.     

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e., perform group-level analysis) based on a common cortical coordinate space.     

Frequency and periodicity are represented in orthogonal maps in the human auditory cortex: evidence from magnetoencephalography

Timbre and pitch are two independent perceptual qualities of sounds closely related to the spectral envelope and to the fundamental frequency of periodic temporal envelope fluctuations, respectively. To a first approximation, the spectral and temporal tuning properties of neurons in the auditory midbrain of various animals are independent, with layouts of these tuning properties in approximately orthogonal tonotopic and periodotopic maps. For the first time we demonstrate by means of magnetoencephalography a periodotopic organization of the human auditory cortex and analyse its spatial relationship to the tonotopic organization by using a range of stimuli with different temporal envelope fluctuations and spectra and a magnetometer providing high spatial resolution. We demonstrate an orthogonal arrangement of tonotopic and periodotopic gradients. Our results are in line with the organization of such maps in animals and closely match the perceptual orthogonality of timbre and pitch in humans. Accepted: 25 July 1997     

Do cortical maps depend on the timing of sensory input? Experimental evidence and computational model

Fast adaptations in the functional organization of primary sensory cortex are generally assumed to result from changes of network connectivity. However, the effects of intrinsic neuronal excitability alterations due to the activation of neighboring cortical representational zones, which might as well account for the changes of cortical representative maps, have been paid little attention to. In a recent experiment (Braun et al. 2000b) we showed by neuromagnetic source imaging that random or fixed sequence stimulation of three digits of both hands led to stimulation-timing-induced changes in primary somatosensory (SI) cortical maps. The distance between the cortical representation of thumb and middle finger became significantly shorter during the fixed sequence stimulation. The analysis on the time course of the cortical map changes revealed that these reorganizations occurred within minutes and were fully reversible. The previously reported results were interpreted as the involvement of a superordinate center responsible for detecting and activating the appropriate maps. Here we present an alternative parsimonious explanation that is supported by a computational model. Based on the experimental evidence, we developed a simple model that took intrinsic neuronal excitability together with subthreshold activation into account and assumed partial cortical overlap of the representational zones of neighboring digits. Furthermore, in the model the neuronal excitability decayed slowly with respect to the stimulation frequency. The observed cortical map changes in the experiment could be reproduced by the two-layer feed-forward computational network. Our model thus suggests that the dynamic shifts of cortical maps can be explained by the state and time course of intrinsic neuronal excitability and subthreshold activation, without involving changes in network connectivity.