From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity.

The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.

Intrinsic neural timescales: temporal integration and segregation.

We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal-transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.

The brain and its time: intrinsic neural timescales are key for input processing.

We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs' stochastics with the ongoing temporal statistics of the brain's neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.

Prestimulus dynamics blend with the stimulus in neural variability quenching.

Neural responses to the same stimulus show significant variability over trials, with this variability typically reduced (quenched) after a stimulus is presented. This trial-to-trial variability (TTV) has been much studied, however how this neural variability quenching is influenced by the ongoing dynamics of the prestimulus period is unknown. Utilizing a human intracranial stereo-electroencephalography (sEEG) data set, we investigate how prestimulus dynamics, as operationalized by standard deviation (SD), shapes poststimulus activity through trial-to-trial variability (TTV). We first observed greater poststimulus variability quenching in those real trials exhibiting high prestimulus variability as observed in all frequency bands. Next, we found that the relative effect of the stimulus was higher in the later (300-600ms) than the earlier (0-300ms) poststimulus period. Lastly, we replicate our findings in a separate EEG dataset and extend them by finding that trials with high prestimulus variability in the theta and alpha bands had faster reaction times. Together, our results demonstrate that stimulus-related activity, including its variability, is a blend of two factors: 1) the effects of the external stimulus itself, and 2) the effects of the ongoing dynamics spilling over from the prestimulus period - the state at stimulus onset - with the second dwarfing the influence of the first.

Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization.

The human cortex exhibits intrinsic neural timescales that shape a temporal hierarchy. Whether this temporal hierarchy follows the spatial hierarchy of its topography, namely the core-periphery organization, remains an open issue. Using magnetoencephalography data, we investigate intrinsic neural timescales during rest and task states; we measure the autocorrelation window in short (ACW-50) and, introducing a novel variant, long (ACW-0) windows. We demonstrate longer ACW-50 and ACW-0 in networks located at the core compared to those at the periphery with rest and task states showing a high ACW correlation. Calculating rest-task differences, i.e., subtracting the shared core-periphery organization, reveals task-specific ACW changes in distinct networks. Finally, employing kernel density estimation, machine learning, and simulation, we demonstrate that ACW-0 exhibits better prediction in classifying a region's time window as core or periphery. Overall, our findings provide fundamental insight into how the human cortex's temporal hierarchy converges with its spatial core-periphery hierarchy.

The self in art therapy - Brain-based assessment of the drawing process.

Art therapy plays important role in classical psychological assessment as it allows expressing the subject's sense of self. However, its effectiveness and validity could be impeded by lack of relationship to the patients' neuronal changes in their brain. The aim of our theoretical-empirical paper is to propose a novel brain-based quantitative objective measurement of the self and how it shapes the drawing process. We discuss recent data that how the autocorrelation window (ACW) is related to the temporal continuity of self in current neuroscience and further develop a method to use ACW to measure the temporal continuity of the drawing process, probing it in two case studies. As expected, the schizophrenic subject shows lower ACW values compared to the healthy subject and reflects the well-known deficit in the temporal continuity of the self in schizophrenia. We concluded that ACW and eventually other measures of the brain's spatiotemporal structure might be able to serve as objective markers of the self in the drawing process. As our approach connects brain, self, and drawing process, it provides the theoretical basis for the future development of a brain-based assessment of the self in the drawing process and art therapy.

Neural Correlates of Craving in Methamphetamine Abuse.

INTRODUCTION: Methamphetamine is a powerful psychostimulant that causes significant neurological impairments with long-lasting effects and has provoked serious international concerns about public health. Denial of drug abuse and drug craving are two important factors that make the diagnosis and treatment extremely challenging. Here, we present a novel and rapid noninvasive method with potential application for differentiation and monitoring methamphetamine abuse. METHODS: Visual stimuli comprised a series of images with neutral and methamphetamine-related content. A total of 10 methamphetamine abusers and 10 age-gender matched controls participated in the experiments. Event-related potentials (ERPs) were recorded and compared using a time window analysis method. The ERPs were divided into 19 time windows of 100 ms with 50 ms overlaps. The area of positive sections below each window was calculated to measure the differences between the two groups. RESULTS: Significant differences between two groups were observed from 250 to 500 ms (P300) in response to methamphetamine-related visual stimuli and 600 to 800 ms in response to neutral stimuli. CONCLUSION: This study presented a novel and noninvasive method based on neural correlates to discriminate healthy individuals from methamphetamine drug abusers. This method can be employed in treatment and monitoring of the methamphetamine abuse.

State dependent effect of transcranial direct current stimulation (tDCS) on methamphetamine craving.

Transcranial direct current stimulation (tDCS) has been shown to modulate subjective craving ratings in drug dependents by modification of cortical excitability in dorsolateral prefrontal cortex (DLPFC). Given the mechanism of craving in methamphetamine (meth) users, we aimed to test whether tDCS of DLPFC could also alter self-reported craving in abstinent meth users while being exposed to meth cues. In this double-blinded, crossover, sham-controlled study, thirty two right-handed abstinent male meth users were recruited. We applied 20 min 'anodal' tDCS (2 mA) or 'sham' tDCS over right DLPFC in a random sequence while subjects performed a computerized cue-induced craving task (CICT) starting after 10 min of stimulation. Immediate craving was assessed before the stimulation, after 10 min of tDCS, and after tDCS termination by visual analog scale (VAS) of 0 to 100. Anodal tDCS of rDLPFC altered craving ratings significantly. We found a significant reduction of craving at rest in real tDCS relative to the sham condition (p = 0.016) after 10 min of stimulation. On the other hand, cue-induced VAS craving was rated significantly higher in the real condition in comparison with sham stimulation (p = 0.012). Our findings showed a state dependent effect of tDCS: while active prefrontal tDCS acutely reduced craving at rest in the abstinent meth users, it increased craving during meth-related cue exposure. These findings reflect the important role of the prefrontal cortex in both cue saliency evaluation and urge to meth consumption.

Methodological dimensions of transcranial brain stimulation with the electrical current in human.

Transcranial current stimulation (TCS) is a neuromodulation method in which the patient is exposed to a mild electric current (direct or alternating) at 1-2 mA, resulting in an increase or a decrease in the brain excitability. This modification in neural activities can be used as a method for functional human brain mapping with causal inferences. This method might also facilitate the treatments of many neuropsychiatric disorders based on its inexpensive, simple, safe, noninvasive, painless, semi-focal excitatory and inhibitory effects. Given this, a comparison amongst different brain stimulation modalities has been made to determine the potential advantages of the TCS method. In addition, considerable methodological details on using TCS in basic and clinical neuroscience studies in human subjects have been introduced. Technical characteristics of TCS devices and their related accessories with regard to safety concerns have also been well articulated. Finally, some TCS application opportunities have been emphasized, including its potential use in the near future.