A complex brain network, centered on the hippocampus, supports episodic memories throughout their lifetimes. Classically, upon memory encoding during active behavior, hippocampal activity is dominated by theta oscillations (6-10Hz). During inactivity, hippocampal neurons burst synchronously, constituting sharp waves, which can propagate to other structures, theoretically supporting memory consolidation. This 'two-stage' model has been updated by new data from high-density electrophysiological recordings in animals that shed light on how information is encoded and exchanged between hippocampus, neocortex and subcortical (...) structures such as the striatum. Cell assemblies (tightly related groups of cells) discharge together and synchronize across brain structures orchestrated by theta, sharp waves and slow oscillations, to encode information. This evolving dynamical schema is key to extending our understanding of memory processes. (shrink)

Neurofeedback is a complex learning scenario, as the task consists of trying out mental strategies while processing a feedback signal that signifies activation in the brain area to be self-regulated and acts as a potential reward signal. In an attempt to dissect these subcomponents, we obtained whole-brain networks associated with efficient self-regulation in two paradigms: parallel, where the task was performed concurrently, combining feedback with strategy execution; and serial, where the task was performed consecutively, separating feedback processing from (...) strategy execution. Twenty participants attempted to control their anterior midcingulate cortex using functional magnetic resonance imaging NF in 18 sessions over 2 weeks, using cognitive and emotional mental strategies. We analyzed whole-brain fMRI activations in the NF training runs with the largest aMCC activation for the serial and parallel paradigms. The equal length of the strategy execution and the feedback processing periods in the serial paradigm allows a description of the two task subcomponents with equal power. The resulting activation maps were spatially correlated with functionally annotated intrinsic connectivity brain maps. Brain activation in the parallel condition correlates with the basal ganglia network, the cingulo-opercular network, and the frontoparietal control network ; brain activation in the serial strategy execution condition with the default mode network, the FPCN, and the visual processing network; while brain activation in the serial feedback processing condition predominantly with the CON, the DMN, and the FPCN. Additional comparisons indicate that BG activation is characteristic to the parallel paradigm, while supramarginal gyrus and superior temporal gyrus activations are characteristic to the serial paradigm. The multifaceted view of the subcomponents allows describing the cognitive processes associated with strategy execution and feedback processing independently in the serial feedback task and as combined processes in the multitasking scenario of the conventional parallel feedback task. (shrink)

Lucid dreaming refers to a dream state characterized by the dreamers awareness of being in a dream and being able to volitionally control its content. The aim of this study was to find neurophysiological evidence for the 7 criteria of lucid dreaming proposed by Paul Tholey. Each of the criteria was analyzed separately with regard to its underlying neurocircuits. We hypothesized that not one, but many regions are involved in the state of lucid dreaming. Our results have shown a satisfactory (...) overlap of the theoretical components and the brain regions activated during a lucid dream. During lucid dreaming, a brain network seems to emerge, that is more than the sum of its parts. Further research is needed to understand the psychoneurological underpinnings of lucid dreams. (shrink)

Traditional rehabilitation strategies become difficult in the chronic phase stage of stroke prognosis. Brain–computer interface combined with external devices may improve motor function in chronic stroke patients, but it lacks comprehensive assessments of neurological changes regarding functional rehabilitation. This study aimed to comprehensively and quantitatively investigate the changes in brain activity induced by BCI–FES training in patients with chronic stroke. We analyzed the EEG of two groups of patients with chronic stroke, one group received functional electrical stimulation (...) rehabilitation training and the other group received BCI combined with FES training. We constructed functional networks in both groups of patients based on direct directed transfer function and assessed the changes in brain activity using graph theory analysis. The results of this study can be summarized as follows: after rehabilitation training, the Fugl–Meyer assessment scale score was significantly improved in the BCI–FES group, and there was no significant difference in the FES group. Both the global and local graph theory measures of the brain network of patients with chronic stroke in the BCI–FES group were improved after rehabilitation training. The node strength in the contralesional hemisphere and central region of patients in the BCI–FES group was significantly higher than that in the FES group after the intervention, and a significant increase in the node strength of C4 in the contralesional sensorimotor cortex region could be observed in the BCI–FES group. These results suggest that BCI–FES rehabilitation training can induce clinically significant improvements in motor function of patients with chronic stroke. It can improve the functional integration and functional separation of brain networks and boost compensatory activity in the contralesional hemisphere to a certain extent. The findings of our study may provide new insights into understanding the plastic changes of brain activity in patients with chronic stroke induced by BCI–FES rehabilitation training. (shrink)

We investigate the long-term evolution of degree-degree correlations (assortativity) in functional brain networks from epilepsy patients. Functional networks are derived from continuous multi-day, multi-channel electroencephalographic data, which capture a wide range of physiological and pathophysiological activities. In contrast to previous studies which all reported functional brain networks to be assortative on average, even in case of various neurological and neurodegenerative disorders, we observe large fluctuations in time-resolved degree-degree correlations ranging from assortative to dissortative mixing. Moreover, in some patients (...) these fluctuations exhibit some periodic temporal structure which can be attributed, to a large extent, to daily rhythms. Relevant aspects of the epileptic process, particularly possible pre-seizure alterations, contribute marginally to the observed long-term fluctuations. Nevertheless, our findings suggest that physiological and pathophysiological activity may modify functional brain networks in a different and process-specific way. We evaluate factors that possibly influence the long-term evolution of degree-degree correlations. (shrink)

Several research groups have identified a network of regions of the adult cortex that are activated during social perception and cognition tasks. In this paper we focus on the development of components of this social brain network during early childhood and test aspects of a particular viewpoint on human functional brain development: “interactive specialization.” Specifically, we apply new data analysis techniques to a previously published data set of event-related potential ~ERP! studies involving 3-, 4-, and 12-month-old (...) infants viewing faces of different orientation and direction of eye gaze. Using source separation and localization methods, several likely generators of scalp recorded ERP are identified, and we describe how they are modulated by stimulus characteristics. We then review the results of a series of experiments concerned with perceiving and acting on eye gaze, before reporting on a new experiment involving young children with autism. Finally, we discuss predictions based on the atypical emergence of the social brain network. (shrink)

Autism spectrum disorder is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model analysis for resting-state functional MRI from a large multicenter dataset of 507 male subjects. Specifically, the (...) 507 subjects included 209 subjects with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange. Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls. Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network, sensory processing networks [including visual network, auditory network, and sensory and motor network ]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD. (shrink)

We investigated if emotion regulation can be improved through self-regulation training on non-emotional brain regions, as well as how to change the brain networks implicated in this process. During the training period, the participants were instructed to up-regulate their right dorsolateral prefrontal cortex activity according to real-time functional near-infrared spectroscopy neurofeedback signals, and there was no emotional element. The results showed that the training significantly increased emotion regulation, resting-state functional connectivity within the emotion regulation network and (...) frontoparietal network, and rsFC between the ERN and amygdala; however, training did not influence the rsFC between the FPN and the amygdala. However, self-regulation training on rDLPFC significantly improved emotion regulation and generally increased the rsFCs within the networks; the rsFC between the ERN and amygdala was also selectively increased. The present study also described a safe approach that may improve emotion regulation through self-regulation training on non-emotional brain regions. (shrink)

Spontaneous brain activity has received increasing attention as demonstrated by the exponential rise in the number of published papers on this topic over the last thirty years. Such “intrinsic” brain activity, generated in the absence of an explicit task, is frequently associated with resting-state or default-mode networks. The focus on characterizing spontaneous brain activity promises to shed new light on questions concerning the structural and functional architecture of the brain and how they are (...) related to “mind”. However, many critical questions have yet to be addressed. In this review, we focus on a scarcely explored area, specifically the energetic requirements and constraints of spontaneous activity, taking into account both thermodynamical and informational perspectives. We argue that the “classical” definitions of spontaneous activity do not take into account an important feature, that is, the critical thermodynamic energetic differences between spontaneous and evoked brain activity. Spontaneous brain activity is associated with slower oscillations compared with evoked, task-related activity, hence it exhibits lower levels of enthalpy and “free-energy” (i.e. the energy that can be converted to do work), thus supporting noteworthy thermodynamic energetic differences between spontaneous and evoked brain activity. Increased spike frequency during evoked activity has a significant metabolic cost, consequently, brain functions traditionally associated with spontaneous activity, such as mind wandering, require less energy that other nervous activities. We also review recent empirical observations in neuroscience, in order to capture how spontaneous brain dynamics and mental function can be embedded in a non-linear dynamical framework, which considers nervous activity in terms of phase spaces, particle trajectories, random walks, attractors and/or paths at the edge of the chaos. This takes us from the thermodynamic free-energy, to the realm of “variational free-energy”, a theoretical construct pertaining to probability and information theory which allows explanation of unexplored features of spontaneous brain activity. (shrink)

The complex activity of the human brain makes it difficult to get a big picture of how the brain works and functions as the mind. We examine pertinent studies, as well as evolutionary and embryologic evidence to support our theoretical model consisting of separate but interactive layers of human neural activity. The most basic layer involves default mode network (DMN)activity and cardiorespiratory oscillations. We propose that these oscillations support other neural activity and cognitive (...) processes. The second layer involves limbic system activity accompanied by corresponding changes in cardiorespiratory oscillations. The third layer consists of corticothalamic processing and involves higher cortical functions including awareness, cognition,and consciousness. These layers interact to form the complex neural activity of the human brain. Examining the origins and relationships of various neural and physiologic oscillations may provide better understanding of human neurophysiology and consciousness. (shrink)

Multiple cortical areas of the human brain motor system interact coherently in the low frequency range (< 0.1 Hz), even in the absence of explicit tasks. Following stroke, cortical interactions are functionally disturbed. How these interactions are affected and how the functional organization is regained from rehabilitative treatments as people begin to recover motor behaviors has not been systematically studied. We recorded the intrinsic functional magnetic resonance imaging (fMRI) signals from 30 participants: 17 young healthy controls and 13 aged (...) stroke survivors. Stroke participants underwent mental practice (MP) or both mental practice and physical therapy (MP + PT) within 14-51 days following stroke. We investigated the network activity of five core areas in the motor-execution network, consisting of the left primary motor area (LM1), the right primary motor area (RM1), the left pre-motor cortex (LPMC), the right pre-motor cortex (RPMC) and the supplementary motor area (SMA). We discovered that (i) the network activity dominated in the frequency range 0.06 Hz – 0.08 Hz for all the regions, and for both able-bodied and stroke participants (ii) the causal information flow between the regions: LM1 and SMA, RPMC and SMA, RPMC and LM1, SMA and RM1, SMA and LPMC, was reduced significantly for stroke survivors (iii) the flow did not increase significantly after MP alone and (iv) the flow among the regions during MP+PT increased significantly. We also found that sensation and motor scores were significantly higher and correlated with directed functional connectivity measures when the stroke-survivors underwent MP+PT but not MP alone. The findings provide evidence that a combination of mental practice and physical therapy can be an effective means of treatment for stroke survivors to recover or regain the strength of motor behaviors, and that the spectra of causal information flow can be used as a reliable biomarker for evaluating rehabilitation in stroke survivors. (shrink)

The main purpose of this article is to identify the inner human activity Peirce calls musement with the mental processes that arise through the workings of the brain’s default mode network. This network is a specific, recently anatomically defined brain system, which is most active when individuals are not focused on the external environment. In doing so, musement, which was defined by Peirce over a hundred years ago, will finally be situated within what today we (...) understand as its neurobiological origin. (shrink)

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Method: Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. (...) They then had to respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials two seconds prior to the stimulus being presented were identified. Results: Pre-stimulus activity levels were higher in the right temporoparietal junction (RTPJ), the right temporal pole (RTP), and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Conclusion: Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. (shrink)

This book tackles the question of why the brain is so difficult to fully understand. In neuroscience, data are acquired and analyzed with astonishing techniques and accumulate rapidly. Nevertheless, try to explain how a person can think or why there is such a condition as schizophrenia, and it appears that we really know little. To approach these difficulties, the authors first present a number of case studies in which the operation of a neural circuit is worked out in some (...) detail and, at the same time, the functional significance of the operation is also understood. These examples are complicated in their biologic specifics but are conceptually straightforward. The examples are hoped to provoke an appreciation for what neuroscience can accomplish. The authors then develop some thoughts on how these issues can be addressed----instead of considering cognition in general, taking instead a subset of cognition that does lend itself to formal description. (shrink)

BackgroundFreezing of gait is a disabling burden for Parkinson’s disease patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear.MethodsTwelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic (...) medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off, conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes.ResultsClinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta, alpha, and high-beta band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas.ConclusionsSTN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD. (shrink)

We are frequently exposed to hand written digits 0-9 in today’s modern life. Success in decoding-classification of hand written digits helps us understand the corresponding brain mechanisms and processes and assists seriously in designing more efficient brain-computer interfaces. However, all digits belong to the same semantic category and similarity in appearance of hand written digits makes this decoding-classification a challenging problem. In present study, for the first time, augmented naïve Bayes classifier is used for classification of fMRI (functional (...) Magnetic Resonance imaging) measurements to decode the hand written digits which took advantage of brain connectivity information in decoding-classification. fMRI was recorded from three healthy participants, with an age range of 25-30. Results in different brain lobes (frontal, occipital, parietal and temporal) show that utilizing connectivity information significantly improves decoding-classification and capability of different brain lobes in decoding-classification of hand written digits were compared to each other. In addition, in each lobe the most contributing areas and brain connectivities were determined and connectivities with short distances between their endpoints were recognized to be more efficient. Moreover, data driven method was applied to investigate the similarity of brain areas in responding to stimuli and this revealed both similarly active areas and active mechanisms during this experiment. Interesting finding was that during the experiment of watching hand written digits, there were some active networks (visual, working memory, motor and language processing), but the most relevant one to the task was language processing network according to the voxel selection. (shrink)

ObjectiveThe effects and possible mechanisms of cerebellar high-frequency repetitive transcranial magnetic stimulation on swallowing-related neural networks were studied using resting-state functional magnetic resonance imaging.MethodA total of 23 healthy volunteers were recruited, and 19 healthy volunteers were finally included for the statistical analysis. Before stimulation, the cerebellar hemisphere dominant for swallowing was determined by the single-pulse TMS. The cerebellar representation of the suprahyoid muscles of this hemisphere was selected as the target for stimulation with 10 Hz rTMS, 100% resting motor threshold, (...) and 250 pulses, with every 1 s of stimulation followed by an interval of 9 s. The motor evoked potential amplitude of the suprahyoid muscles in the bilateral cerebral cortex was measured before and after stimulation to evaluate the cortical excitability. Forty-eight hours after elution, rTMS was reapplied on the dominant cerebellar representation of the suprahyoid muscles with the same stimulation parameters. Rs-fMRI was performed before and after stimulation to observe the changes in amplitude of low-frequency fluctuation and regional homology at 0.01–0.08 Hz, 0.01–0.027 Hz, and 0.027–0.073 Hz.ResultsAfter cerebellar high-frequency rTMS, MEP recorded from swallowing-related bilateral cerebral cortex was increased. The results of rs-fMRI showed that at 0.01–0.08 Hz, ALFF was increased at the pons, right cerebellum, and medulla and decreased at the left temporal lobe, and ReHo was decreased at the left insular lobe, right temporal lobe, and corpus callosum. At 0.01–0.027 Hz, ALFF was decreased at the left temporal lobe, and ReHo was decreased at the right temporal lobe, left putamen, and left supplementary motor area.ConclusionRepetitive transcranial magnetic stimulation of the swallowing cortex in the dominant cerebellar hemisphere increased the bilateral cerebral swallowing cortex excitability and enhanced pontine, bulbar, and cerebellar spontaneous neural activity, suggesting that unilateral high-frequency stimulation of the cerebellum can excite both brainstem and cortical swallowing centers. These findings all provide favorable support for the application of cerebellar rTMS in the clinical practice. (shrink)

A ubiquitous feature of active sleep in mammals and birds is its relative abundance in early development. In rat pups across the first two postnatal weeks, active sleep promotes the expression of synchronized oscillatory activity within and between cortical and subcortical sensorimotor structures. Sensory feedback from self-generated myoclonic twitches – which are produced exclusively during active sleep – also triggers neural oscillations in those structures. We have proposed that one of the functions of active sleep in early infancy is (...) to provide a context for synchronizing developing structures. Specifically, neural oscillations contribute to a variety of neurodevelopmental processes, including synapse formation, neuronal differentiation and migration, apoptosis, and the refinement of topographic maps. In addition, synchronized oscillations promote functional connectivity between distant brain areas. Consequently, any condition or manipulation that restricts active sleep can, in turn, deprive the infant animal of substantial sensory experience, resulting in atypical developmental trajectories. The synchronization of rhythmic neural activity across brain structures provides evidence of communication. In developing sensorimotor networks, such oscillations are triggered most clearly and prominently during REM sleep. We propose that REM sleep provides a context for the emergence and expression of functional connectivity in the developing sensorimotor system. (shrink)

ObjectiveStatic regional homogeneity based on the resting-state functional magnetic resonance imaging has been used to study intrinsic brain activity in Alzheimer’s disease. However, few studies have examined dynamic ReHo in AD. In this study, we used rs-fMRI and dReHo to investigate the alterations in dynamic IBA in patients with AD to uncover dynamic imaging markers of AD.MethodIn total, 111 patients with AD, 29 patients with mild cognitive impairment, and 73 healthy controls were recruited for this study ultimately. After (...) the rs-fMRI scan, we calculated the dReHo values using the sliding window method. ANOVA and post hoc two-sample t-tests were used to detect the differences among the three groups. We used the mini-mental state examination and Montreal Cognitive Assessment to evaluate the cognitive function of the subjects. The associations between the MMSE score, MoCA score, and dReHo were assessed by the Pearson correlation analysis.ResultsSignificant dReHo variability in the right middle frontal gyrus and right posterior cingulate gyrus was detected in the three groups through ANOVA. In post hoc analysis, the AD group exhibited significantly greater dReHo variability in the right MFG than the MCI group. Compared with the HC group, the AD group exhibited significantly increased dReHo variability in the right PCG. Furthermore, dReHo variability in the right PCG was significantly negatively correlated with the MMSE and MoCA scores of patients with AD.ConclusionDisrupted dynamic IBA in the DMN might be an important characteristic of AD and could be a potential biomarker for the diagnosis or prognosis of AD. (shrink)

Recently, a three-dimensional construct model for complex experiential Selfhood has been proposed (Fingelkurts et al., 2016b,c). According to this model, three specific subnets (or modules) of the brain self-referential network (SRN) are responsible for the manifestation of three aspects/features of the subjective sense of Selfhood. Follow up multiple studies established a tight relation between alterations in the functional integrity of the triad of SRN modules and related to them three aspects/features of the sense of self; however, the causality (...) of this relation is yet to be shown. In this article we approached the question of causality by exploring functional integrity within the three SRN modules that are thought to underlie the three phenomenal components of Selfhood while these components were manipulated mentally by experienced meditators in a controlled and independent manner. Participants were requested, in a block-randomised manner, to mentally induce states representing either increased (up-regulation) or decreased (down-regulation) sense of (a) witnessing agency (“Self”), or (b) body representational-emotional agency (“Me”), or (c) reflective/narrative agency (“I”), while their brain activity was recorded by an electroencephalogram (EEG). This EEG-data was complemented by first-person phenomenological reports and standardised questionnaires which focused on subjective contents of three aspects of Selfhood. The results of the study strengthen the case for a direct causative relationship between three phenomenological aspects of Selfhood and related to them three modules of the brain SRN. Furthermore, the putative integrative model of the dynamic interrelations among three modules of the SRN has been proposed. (shrink)

Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses) associative delayed-match-to-sample (WM) task using event-related fMRI and a subsequent associative recognition LTM (...) task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the “retrieval success network” (anterior and posterior midline brain structures). The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of the respective memory system. (shrink)

There is some complementarity of models for the origin of the electroencephalogram (EEG) and neural network models for information storage in brainlike systems. From the EEG models of Freeman, of Nunez, and of the authors' group we argue that the wavelike processes revealed in the EEG exhibit linear and near-equilibrium dynamics at macroscopic scale, despite extremely nonlinear – probably chaotic – dynamics at microscopic scale. Simulations of cortical neuronal interactions at global and microscopic scales are then presented. The simulations (...) depend on anatomical and physiological estimates of synaptic densities, coupling symmetries, synaptic gain, dendritic time constants, and axonal delays. It is shown that the frequency content, wave velocities, frequency/wavenumber spectra and response to cortical activation of the electrocorticogram (ECoG) can be reproduced by a “lumped” simulation treating small cortical areas as single-function units. The corresponding cellular neural network simulation has properties that include those of attractor neural networks proposed by Amit and by Parisi. Within the simulations at both scales, sharp transitions occur between low and high cell firing rates. These transitions may form a basis for neural interactions across scale. To maintain overall cortical dynamics in the normal low firing-rate range, interactions between the cortex and the subcortical systems are required to prevent runaway global excitation. Thus, the interaction of cortex and subcortex via corticostriatal and related pathways may partly regulate global dynamics by a principle analogous to adiabatic control of artificial neural networks. (shrink)

Based on the theoretical analysis of self-consciousness concepts, we hypothesized that the spatio-temporal pattern of functional connectivity within the default-mode network (DMN) should persist unchanged across a variety of different cognitive tasks or acts, thus being task-unrelated. This supposition is in contrast with current understanding that DMN activated when the subjects are resting and deactivated during any attention-demanding cognitive tasks. To test our proposal, we used, in retrospect, the results from our two early studies ([Fingelkurts, 1998] and [Fingelkurts et (...) al., 2003]). In both studies for the majority of experimental trails we indeed found a constellation of operationally synchronized cortical areas (indexed as DMN) that was persistent across all studied experimental conditions in all subjects. Furthermore, we found three major elements comprising this DMN: two symmetrical occipito-parieto-temporal and one frontal spatio-temporal patterns. This new data directly supports the notion that DMN has a specific functional connotation – it provides neurophysiologic basis for self-processing operations, namely first-person perspective taking and an experience of agency. (shrink)

How does segregation along ethnic boundaries emerge in social networks? Human evolution resulted in highly social beings, capable of prosociality, mindreading, and self-control, which are important aspects of the “social brain.” Our neurophysiologically “wired” social cognition implies different cognitive goal frames. In line with recent developments in behavioral theory, the present study defines network ties as episodes of social exchange. This dynamic definition can account for shifts in goal frames during an exchange episode: whereas deliberate choice and hedonic (...) or gain goals drive the initiation of a tie, given the opportunity structure, the normative goal frame activates a strong dynamic effect of reciprocity, which limits actors’ choice set and appears as “self-organization” at the network level. Longitudinal analyses of 18 birthday party networks comprising 501 students support the definition of network ties as exchange episodes, as well as the relevance of humans’ inherent tendency to reciprocate. However, reciprocation is much stronger in dyads of the same ethnicity than in dyads of different ethnicities. Network segregation along ethnic boundaries results from deliberate decisions during the initiation of an episode, but also from different commitments to reciprocity during the ongoing exchange process, depending on intra or interethnic dyadic constellations. (shrink)

Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism (...) in computability theory), (ii) a technique that inspired the notion of logic design (a fundamental part of modern computer design), (iii) the first use of computation to address the mind–body problem, and (iv) the first modern computational theory of mind and brain. (shrink)

Revenge is common in our daily lives, and people feel good when engaging in revenge behavior. However, revenge behavior is a complex process and remains somewhat of a puzzle of human behavior. Neuroimaging studies have revealed that revenge behaviors are associated with activation of a neural network containing the anterior cingulate cortex, ventral striatum, inferior frontal gyrus, and dorsolateral prefrontal cortex. Recent brain stimulation research using transcranial direct current stimulation and transcranial magnetic stimulation has shown a causal relationship (...) between brain regions and revenge behaviors, but the findings have been mixed. In the present study, we aimed to study whether stimulation in the DLPFC can change participants’ revenge behavior in conditions where participants’ wealth was taken away in different ways. We adapted the moonlighting game and designed a new paradigm. Our study revealed that revenge behavior increased following activation in the right DLPFC, suggesting that the right DLPFC plays an important role in overriding self-interest and retaliation. In addition, our results revealed that the right DLPFC is crucial in revenge behavior related to the motivation of invasion. (shrink)

Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this target article, we present a meta-analytic summary of the neuroimaging literature on human emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete (...) emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain–emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: A set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories. (shrink)

It has been argued that complex subjective sense of self is linked to the brain default-mode network (DMN). Recent discovery of heterogeneity between distinct subnets (or operational modules - OMs) of the DMN leads to a reconceptualization of its role for the experiential sense of self. Considering the recent proposition that the frontal DMN OM is responsible for the first-person perspective and the sense of agency, while the posterior DMN OMs are linked to the continuity of ‘I’ experience (...) (including autobiographical memories) through embodiment and localization within bodily space, we have tested in this study the hypothesis that heterogeneity in the operational synchrony strength within the frontal DMN OM among patients who are in a vegetative state (VS) could inform about a stable self-consciousness recovery later in the course of disease (up to six years post-injury). Using EEG operational synchrony analysis we have demonstrated that among the three OMs of the DMN only the frontal OM showed important heterogeneity in VS patients as a function of later stable clinical outcome. We also found that the frontal DMN OM was characterized by the process of active uncoupling (stronger in persistent VS) of operations performed by the involved neuronal assemblies. (shrink)

Self-injurious behavior is associated with diverse psychiatric conditions. Sometimes, SIB is the most dominant symptom, severely restricting the psychosocial functioning and quality of life of the patients and inhibiting appropriate patient care. In severe cases, it can lead to permanent physical injuries or even death. Primary therapy consists of medical treatment and if implementable, behavioral therapy. For patients with severe SIB refractory to conventional therapy, neuromodulation can be considered as a last recourse. In scientific literature, several successful lesioning and deep (...) brain stimulation targets have been described that can indicate a common underlying neuronal pathway. The objectives of this study were to evaluate the short- and long-term clinical outcome of patients with severe, therapy refractory SIB who underwent DBS with diverse underlying psychiatric disorders and to correlate these outcomes with the activated connectivity networks. We retrospectively analyzed 10 patients with SIB who underwent DBS surgery with diverse psychiatric conditions including autism spectrum disorder, organic personality disorder after hypoxic or traumatic brain injury or Tourette syndrome. DBS targets were chosen according to the underlying disorder, patients were either stimulated in the nucleus accumbens, amygdala, posterior hypothalamus, medial thalamus or ventrolateral thalamus. Clinical outcome was measured 6 months after surgery and at long-term follow-up after 10 or more years using the Early Rehabilitation Barthel index and time of restraint. Connectivity patterns were analyzed using normative connectome. Based on previous literature the orbitofrontal cortex, superior frontal gyrus, the anterior cingulate cortex, the amygdala and the hippocampus were chosen as regions of interest. This analysis showed a significant improvement in the functionality of the patients with DBS in the short- and long-term follow-up. Good clinical outcome correlated with higher connectivity to the amygdala and hippocampus. These findings may suggest a common pathway, which can be relevant when planning a surgical procedure in patients with SIB. (shrink)

AimPatients with high myopia reportedly exhibit changes in functional brain activity, but the mechanism underlying such changes is unclear. This study was conducted to observe differences in dynamic spontaneous brain activity between patients with HM and healthy controls via dynamic regional homogeneity analysis.MethodsResting-state functional magnetic resonance imaging scans were performed on 82 patients with HM and 59 HCs who were closely matched for age, sex, and weight. The dReHo approach was used to assess local dynamic (...) class='Hi'>activity in the human brain. The association between mean dReHo signal values and clinical symptoms in distinct brain areas in patients with HM was determined via correlation analysis.ResultsIn the left fusiform gyrus, right inferior temporal gyrus, right Rolandic operculum, right postcentral gyrus, and right precentral gyrus, dReHo values were significantly greater in patients with HM than in HCs.ConclusionPatients with HM have distinct functional changes in various brain regions that mainly include the L-FG, R-ITG, R-ROL, R-PoCG, and R-PreCG. These findings constitute important evidence for the roles of brain networks in the pathophysiological mechanisms of HM and may aid in the diagnosis of HM. (shrink)

A child’s death is a profound loss for mothers and affects hundreds of thousands of women. Mothers report inconsolable and progressive grief that is distinct from depression and impacts daily emotions and functions. The brain mechanisms responsible for this relatively common and profound mental health problem are unclear, hampering its clinical recognition and care. In an initial exploration of this condition, we used resting state functional MRI (fMRI) scans to examine functional connectivity in key circuits, and task-based fMRI to (...) examine brain network activity in grieving mothers in response to pictures of their deceased child and as well as recognizable deceased celebrities and unfamiliar individuals. We compared nine mothers who had lost an adult child and aged-matched control mothers with a living child of a similar age. Additionally, we collected diffusion imaging scans to probe structural connectivity and complemented the imaging studies with neuropsychological assessments. Increased functional activation in Ventral Attention/Salience Networks accompanied by a reduced activation in the medial prefrontal cortex in response to the deceased child’s picture robustly distinguished the grieving mothers from controls. Heightened resting-state functional connectivity between the paraventricular thalamic nucleus (PVT) and the amygdala distinguished the grieving mothers from the controls and correlated with subjective grief severity. Structurally, maternal grief and its severity were associated with alterations in corticolimbic white matter tracts. Finally, grieving mothers performed worse than controls on neuropsychological tests of learning, memory, and executive function, linked with grief severity. Reduced activation in cortical regions inhibiting emotions and changes in the PVT circuitry—a region involved in long-term emotional memories and decision making under conflict—distinguish grieving mothers from controls. Notably, the magnitude of neurobiological changes correlates with the subjective severity of grief. Together, these new discoveries delineate a prevalent and under-recognized mental health syndrome and chart a path for its appreciation and care. (shrink)

The complexity of the human brain creates a spectrum of sophisticated behavioral repertoires, such as language, tool use, self-awareness, symbolic thought, cultural learning, and consciousness. Understanding how the human brain achieves that has been a longstanding challenge for neuroscientists and may bring insights into the evolution of human cognition and disease states. Human pluripotent stem cells could differentiate into specialized cell types and tissues in vitro. From this pluripotent state, it is possible to generate models of the human (...) brain, such as brain organoids. The recent observation that brain organoids can spontaneously develop complex neural network activity in a dish can help one understand how neural network oscillations evolve and vary between normal and disease states. Moreover, this finding can be leveraged to other applications outside medicine, including engineering and artificial intelligence. However, as the brain model technology becomes more complex, it raises a series of ethical and moral dilemmas. This article discusses the status of this technology, some of its current limitations, and a vision of the future. (shrink)

Some dichotomies related to modeling electrocortical activities are analyzed. Attractor neural networks versus biologically motivated models, near-equilibrium versus nonequilibrium processes, linear and nonlinear dynamics, stochastic and chaotic patterns, local and global scale simulation of cortical activities are discussed.

Self-compassion is a mechanism of symptom improvement in post-traumatic stress disorder, however, the underlying neurobiological processes are not well understood. High levels of self-compassion are associated with reduced activation of the threat response system. Physiological threat responses to trauma reminders and increased arousal are key symptoms which are maintained by negative appraisals of the self and self-blame. Moreover, PTSD has been consistently associated with functional changes implicated in the brain’s saliency and the default mode networks. In this paper, we (...) explore how trauma exposed individuals respond to a validated self-compassion exercise. We distinguish three groups using the PTSD checklist; those with full PTSD, those without PTSD, and those with subsyndromal PTSD. Subsyndromal PTSD is a clinically relevant subgroup in which individuals meet the criteria for reexperiencing along with one of either avoidance or hyperarousal. We use electroencephalography alpha-asymmetry and EEG microstate analysis to characterize brain activity time series during the self-compassion exercise in the three groups. We contextualize our results with concurrently recorded autonomic measures of physiological arousal, parasympathetic activation and self-reported changes in state mood and self-perception. We find that in all three groups directing self-compassion toward oneself activates the negative self and elicits a threat response during the SC exercise and that individuals with subsyndromal PTSD who have high levels of hyperarousal have the highest threat response. We find impaired activation of the EEG microstate associated with the saliency, attention and self-referential processing brain networks, distinguishes the three PTSD groups. Our findings provide evidence for potential neural biomarkers for quantitatively differentiating PTSD subgroups. (shrink)

Recent evidence points to widespread underconnectivity in autistic brains owing to deviant white matter, the fibers that make long connections between areas of the cortex. Subjects with autism show measurably fewer long-range connections between the parietal and prefrontal cortices. These findings may help shed light on the current debate in the consciousness literature about whether conscious states require both prefrontal and parietal/temporal components. If it can be shown that people with autism have conscious states despite such underconnectivity, this would constitute (...) an argument for the claim that conscious states can exist in posterior cortex without associated prefrontal activity. This in turn lends support to a class of theories according to which microconsciousness is possible—consciousness in small areas of cortex without active connections to the prefrontal cortex, as opposed to the higher-order thought (HOT) theory of consciousness, according to which conscious states can only occur when posterior cortical areas (in the parietal or temporal lobes) have active connections to the prefrontal cortex. In this chapter, after listing several candidate examples of consciousness without accompanying prefrontal connections, I will argue that autism provides yet another such example. I will also examine a recent version of the higher-order theory that acknowledges these cases of consciousness without prefrontal activity and, instead depicts consciousness as requiring higher-order thoughts located in posterior cortex. In the final section, I will examine the consequences of these views for our understanding of the metaphysical nature of consciousness itself—the classic mind-body problem. (shrink)

Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, (...) computation, short history, and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain. (shrink)

Deep brain stimulation (DBS) to different sites allows interfering with dysfunctional network function implicated in major depression. Because a prominent clinical feature of depression is anhedonia--the inability to experience pleasure from previously pleasurable activities--and because there is clear evidence of dysfunctions of the reward system in depression, DBS to the nucleus accumbens might offer a new possibility to target depressive symptomatology in otherwise treatment-resistant depression. Three patients suffering from extremely resistant forms of depression, who did not respond to (...) pharmacotherapy, psychotherapy, and electroconvulsive therapy, were implanted with bilateral DBS electrodes in the nucleus accumbens. Stimulation parameters were modified in a double-blind manner, and clinical ratings were assessed at each modification. Additionally, brain metabolism was assessed 1 week before and 1 week after stimulation onset. Clinical ratings improved in all three patients when the stimulator was on, and worsened in all three patients when the stimulator was turned off. Effects were observable immediately, and no side effects occurred in any of the patients. Using FDG-PET, significant changes in brain metabolism as a function of the stimulation in fronto-striatal networks were observed. No unwanted effects of DBS other than those directly related to the surgical procedure (eg pain at sites of implantation) were observed. Dysfunctions of the reward system--in which the nucleus accumbens is a key structure--are implicated in the neurobiology of major depression and might be responsible for impaired reward processing, as evidenced by the symptom of anhedonia. These preliminary findings suggest that DBS to the nucleus accumbens might be a hypothesis-guided approach for refractory major depression. (shrink)

The regional brain networks and the underlying neurophysiological mechanisms subserving the cognition of visual narrative in humans have largely been studied with non-invasive brain recording. In this study, we specifically investigated how regional and cross-regional cortical activities support visual narrative interpretation using intracranial stereotactic electroencephalograms recordings from thirteen human subjects (6 females, and 7 males). Widely distributed recording sites across the brain were sampled while subjects were explicitly instructed to observe images from fables presented in “sequential” order, (...) and a set of images drawn from multiple fables presented in “scrambled” order. Broadband activity mainly within the frontal and temporal lobes were found to encode if a presented image is part of a visual narrative (sequential) or random image set (scrambled). Moreover, the temporal lobe exhibits strong activation in response to visual narratives while the frontal lobe is more engaged when contextually novel stimuli are presented. We also investigated the dynamics of interregional interactions between visual narratives and contextually novel series of images. Interestingly, the interregional connectivity is also altered between sequential and scrambled sequences. Together, these results suggest that both changes in regional neuronal activity and cross-regional interactions subserve visual narrative and contextual novelty processing. (shrink)

Various methods have been employed to investigate different aspects of the brain activity modulation related to the performance of a cycling task. In our study we examined how functional connectivity and brain network efficiency varied during an endurance cycling task. To this purpose, we reconstructed EEG signals at source level: we computed current densities in 28 anatomical regions of interest (ROIs) through the eLORETA algorithm, then we calculated the Lagged Coherence of the 28 current density signals (...) to define the adjacency matrix. To quantify changes of functional network efficiency during an exhaustive cycling task, we computed three graph theoretical indices: local efficiency (LE), global efficiency (GE) and Density (D) in two different frequency bands, Alpha and Beta bands, that indicate alertness processes and motor binding/fatigue respectively. This analysis was conducted for six different task intervals: pre-cycling, initial, intermediate and final stages of cycling, active recovery and passive recovery. Fourteen participants performed an incremental cycling task with simultaneous EEG recording and RPE monitoring to detect participants’ exhaustion. LE remained constant during the endurance cycling task in both bands. Therefore, we speculate that fatigue processes did not affect segregated neural processing. We observed an increase of GE in the Alpha band only during cycling, that could be due to greater alertness processes and preparedness to stimuli during exercise. Conversely, although D did not change significantly over time in the Alpha band, its general reduction in the Beta bands during cycling could be interpreted within the framework of the neural efficiency hypothesis, which posits a reduced neural activity for expert/automated performances. We argue that the use of graph theoretical indices represents a clear methodological advancement in studying endurance performance. (shrink)

Answers to the title's question have been influenced by a history in which an early science of consciousness was rejected by behaviourists on the argument that this entails commitment to ontological dualism and "free will" in the sense of indeterminism. This is, however, a confusion of theoretical assertions with metaphysical assertions. Nevertheless, a legacy within computational and information-processing views of mind rejects or de-emphasises a role for consciousness. This paper sketches a mentalistic metatheory in which conscious states are the sole (...) carriers of symbolic representations, and thus have a central role in the explanation of mental activity and action-while specifying determinism and materialism as useful working assumptions. A mentalistic theory of causal learning, experimentally examined with phenomenal reports, is followed by examination of these questions: Are there common roles for phenomenal reports and brain imaging? Is there defensible evidence for unconscious brain states carrying symbolic representations? Are there interesting dissociations within consciousness? (shrink)