Consciousness and cerebral baseline activity fluctuations

Brain microstate spatio-temporal dynamics as a candidate endotype of consciousness

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC.

Putative cause of seizure-induced cognitive alterations: The oscillatory reconfiguration of seizure network

Introduction

The dynamic reconfiguration of network oscillations is connected with cognitive processes. Changes in how neural networks and signaling pathways work are crucial to how epilepsy and related conditions develop. Specifically, there is evidence that prolonged or recurrent seizures may induce or exacerbate cognitive impairment. However, it still needs to be determined how the seizure brain configures its functional structure to shape the battle of strong local oscillations vs. slow global oscillations in the network to impair cognitive function.

Methods

In this paper, we aim to deduce the network mechanisms underlying seizure-induced cognitive impairment by comparing the evolution of strong local oscillations with slow global oscillations and their link to the resting state of healthy controls. Here, we construct a dynamically efficient network of pathological seizures by calculating the synchrony and directionality of information flow between nine patients' SEEG signals. Then, using a pattern-based method, we found hierarchical modules in the brain's functional network and measured the functional balance between the network's local strong and slow global oscillations.

Results and discussion

According to the findings, a tremendous rise in strong local oscillations during seizures and an increase in slow global oscillations after seizures corresponded to the initiation and recovery of cognitive impairment. Specifically, during the interictal period, local strong and slow global oscillations are in metastable balance, which is the same as a normal cognitive process and can be switched easily. During the pre-ictal period, the two show a bimodal pattern of separate peaks that cannot be easily switched, and some flexibility is lost. During the seizure period, a single-peak pattern with negative peaks is showcased, and the network eventually transitions to a very intense strong local oscillation state. These results shed light on the mechanism behind network oscillations in epilepsy-induced cognitive impairment. On the other hand, the differential (similarity) of oscillatory reorganization between the local (non) epileptogenic network and the global network may be an emergency protective mechanism of the brain, preventing the spread of pathological information flow to more healthy brain regions.

Triple network activation causes tinnitus in patients with sudden sensorineural hearing loss: A model-based volume-entropy analysis

Tinnitus can be defined as the conscious perception of phantom sounds in the absence of corresponding external auditory signals. Tinnitus can develop in the setting of sudden sensorineural hearing loss (SSNHL), but the underlying mechanism is largely unknown. Using electroencephalography, we investigated differences in afferent node capacity between 15 SSNHL patients without tinnitus (NT) and 30 SSNHL patients with tinnitus (T). Where the T group showed increased afferent node capacity in regions constituting a "triple brain network" [default mode network (DMN), central executive network (CEN), and salience network (SN)], the NT group showed increased information flow in regions implicated in temporal auditory processing and noise-canceling pathways. Our results demonstrate that when all components of the triple network are activated due to sudden-onset auditory deprivation, tinnitus ensues. By contrast, auditory processing-associated and tinnitus-suppressing networks are highly activated in the NT group, to overcome the activation of the triple network and effectively suppress the generation of tinnitus.

Neural correlates of consciousness and related disorders: From phenotypic descriptors of behavioral and relative consciousness to cortico-subcortical circuitry

We report a review of medical aspects of the consciousness. The behavioral dimension, phenotypic descriptors, relative consciousness and neural correlates of consciousness and related disorders were addressed successively in a holistic and chronological approach. Consciousness is relative, specific to each individual across time and space. Historically defined as the perception of the self and the environment, it cannot be separated from behaviors, entailing an idea of conscious behavior with metapractic and metagnostic aspects. Observation of spontaneous and evoked overt behavior distinguishes three main types of disorder of consciousness (DoC): coma, vegetative state or unresponsive wakefulness, and minimally conscious or relationally impoverished state. Modern functional exploration techniques, such as imaging, increase the understanding of DoCs and consciousness. Whether consciousness is a superior function and/or an instrumental function is discussed. Neural correlates can be subdivided into two wakefulness pathways (superior thalamic cholinergic and inferior extra-thalamic), and cortico-subcortical circuitry. The deep brain structures are those described in the well-known sensorimotor, associative and limbic loops, as illustrated in the mesolimbic model of DoC. The cortices can be segregated into several overlapping networks: (1) a global workspace including thalamo-cortical loops; (2) the default mode network (DMN) and related intrinsic connectivity networks (i.e., central executive, medial DMN and salience networks); (3) a 3-fold network comprising the fronto-parietal control system and its dorsal and ventral attentional sub-networks, the fronto-parietal executive control network, and the cingulo-opercular salience network; (4) the internal and external cortices, respectively medial, turned toward the self, and lateral, turned toward the environment. The network dynamics is the reflection of consciousness, notably anticorrelations such as the decrease in activity of the posterior cingulate-precuneus regions during attentional tasks. Thanks to recent advances in DoC pathophysiology, further significative therapeutic progress is expected, taking into account the societal context. This depends notably on the dissemination of medical knowledge and its transfer to a wider public.

Foundations of Human Consciousness: Imaging the Twilight Zone

What happens in the brain when conscious awareness of the surrounding world fades? We manipulated consciousness in two experiments in a group of healthy males and measured brain activity with positron emission tomography. Measurements were made during wakefulness, escalating and constant levels of two anesthetic agents (experiment 1, n = 39), and during sleep-deprived wakefulness and non-rapid eye movement sleep (experiment 2, n = 37). In experiment 1, the subjects were randomized to receive either propofol or dexmedetomidine until unresponsiveness. In both experiments, forced awakenings were applied to achieve rapid recovery from an unresponsive to a responsive state, followed by immediate and detailed interviews of subjective experiences during the preceding unresponsive condition. Unresponsiveness rarely denoted unconsciousness, as the majority of the subjects had internally generated experiences. Unresponsive anesthetic states and verified sleep stages, where a subsequent report of mental content included no signs of awareness of the surrounding world, indicated a disconnected state. Functional brain imaging comparing responsive and connected versus unresponsive and disconnected states of consciousness during constant anesthetic exposure revealed that activity of the thalamus, cingulate cortices, and angular gyri are fundamental for human consciousness. These brain structures were affected independent from the pharmacologic agent, drug concentration, and direction of change in the state of consciousness. Analogous findings were obtained when consciousness was regulated by physiological sleep. State-specific findings were distinct and separable from the overall effects of the interventions, which included widespread depression of brain activity across cortical areas. These findings identify a central core brain network critical for human consciousness.

SIGNIFICANCE STATEMENT Trying to understand the biological basis of human consciousness is currently one of the greatest challenges of neuroscience. While the loss and return of consciousness regulated by anesthetic drugs and physiological sleep are used as model systems in experimental studies on consciousness, previous research results have been confounded by drug effects, by confusing behavioral “unresponsiveness” and internally generated consciousness, and by comparing brain activity levels across states that differ in several other respects than only consciousness. Here, we present carefully designed studies that overcome many previous confounders and for the first time reveal the neural mechanisms underlying human consciousness and its disconnection from behavioral responsiveness, both during anesthesia and during normal sleep, and in the same study subjects.

Reorganization of rich-clubs in functional brain networks during propofol-induced unconsciousness and natural sleep

BACKGROUND

General anesthesia (GA) provides an invaluable experimental tool to understand the essential neural mechanisms underlying consciousness. Previous neuroimaging studies have shown the functional integration and segregation of brain functional networks during anesthetic-induced alteration of consciousness. However, the organization pattern of hubs in functional brain networks remains unclear. Moreover, comparisons with the well-characterized physiological unconsciousness can help us understand the neural mechanisms of anesthetic-induced unconsciousness.

METHODS

Resting-state functional magnetic resonance imaging was performed during wakefulness, mild propofol-induced sedation (m-PIS), and deep PIS (d-PIS) with clinical unconsciousness on 8 healthy volunteers and wakefulness and natural sleep on 9 age- and sex-matched healthy volunteers. Large-scale functional brain networks of each volunteer were constructed based on 160 regions of interest. Then, rich-club organizations in brain functional networks and nodal properties (nodal strength and efficiency) were assessed and analyzed among the different states and groups.

RESULTS

Rich-clubs in the functional brain networks were reorganized during alteration of consciousness induced by propofol. Firstly, rich-club nodes were switched from the posterior cingulate cortex (PCC), angular gyrus, and anterior and middle insula to the inferior parietal lobule (IPL), inferior parietal sulcus (IPS), and cerebellum. When sedation was deepened to unconsciousness, the rich-club nodes were switched to the occipital and angular gyrus. These results suggest that the rich-club nodes were switched among the high-order cognitive function networks (default mode network [DMN] and fronto-parietal network [FPN]), sensory networks (occipital network [ON]), and cerebellum network (CN) from consciousness (wakefulness) to propofol-induced unconsciousness. At the same time, compared with wakefulness, local connections were switched to rich-club connections during propofol-induced unconsciousness, suggesting a strengthening of the overall information commutation of networks. Nodal efficiency of the anterior and middle insula and ventral frontal cortex was significantly decreased. Additionally, from wakefulness to natural sleep, a similar pattern of rich-club reorganization with propofol-induced unconsciousness was observed: rich-club nodes were switched from the DMN (including precuneus and PCC) to the sensorimotor network (SMN, including part of the frontal and temporal gyrus). Compared with natural sleep, nodal efficiency of the insula, frontal gyrus, PCC, and cerebellum significantly decreased during propofol-induced unconsciousness.

CONCLUSIONS

Our study demonstrated that the rich-club reorganization in functional brain networks is characterized by switching of rich-club nodes between the high-order cognitive and sensory and motor networks during propofol-induced alteration of consciousness and natural sleep. These findings will help understand the common neurological mechanism of pharmacological and physiological unconsciousness.

Network Analysis in Disorders of Consciousness: Four Problems and One Proposed Solution (Exponential Random Graph Models)

In recent years, the study of the neural basis of consciousness, particularly in the context of patients recovering from severe brain injury, has greatly benefited from the application of sophisticated network analysis techniques to functional brain data. Yet, current graph theoretic approaches, as employed in the neuroimaging literature, suffer from four important shortcomings. First, they require arbitrary fixing of the number of connections (i.e., density) across networks which are likely to have different "natural" (i.e., stable) density (e.g., patients vs. controls, vegetative state vs. minimally conscious state patients). Second, when describing networks, they do not control for the fact that many characteristics are interrelated, particularly some of the most popular metrics employed (e.g., nodal degree, clustering coefficient)-which can lead to spurious results. Third, in the clinical domain of disorders of consciousness, there currently are no methods for incorporating structural connectivity in the characterization of functional networks which clouds the interpretation of functional differences across groups with different underlying pathology as well as in longitudinal approaches where structural reorganization processes might be operating. Finally, current methods do not allow assessing the dynamics of network change over time. We present a different framework for network analysis, based on Exponential Random Graph Models, which overcomes the above limitations and is thus particularly well suited for clinical populations with disorders of consciousness. We demonstrate this approach in the context of the longitudinal study of recovery from coma. First, our data show that throughout recovery from coma, brain graphs vary in their natural level of connectivity (from 10.4 to 14.5%), which conflicts with the standard approach of imposing arbitrary and equal density thresholds across networks (e.g., time-points, subjects, groups). Second, we show that failure to consider the interrelation between network measures does lead to spurious characterization of both inter- and intra-regional brain connectivity. Finally, we show that Separable Temporal ERGM can be employed to describe network dynamics over time revealing the specific pattern of formation and dissolution of connectivity that accompany recovery from coma.

Test-retest reliability of prefrontal transcranial Direct Current Stimulation (tDCS) effects on functional MRI connectivity in healthy subjects

Transcranial Direct Current Stimulation (tDCS) of the prefrontal cortex (PFC) can be used for probing functional brain connectivity and meets general interest as novel therapeutic intervention in psychiatric and neurological disorders. Along with a more extensive use, it is important to understand the interplay between neural systems and stimulation protocols requiring basic methodological work. Here, we examined the test-retest (TRT) characteristics of tDCS-induced modulations in resting-state functional-connectivity MRI (RS fcMRI). Twenty healthy subjects received 20minutes of either active or sham tDCS of the dorsolateral PFC (2mA, anode over F3 and cathode over F4, international 10-20 system), preceded and ensued by a RS fcMRI (10minutes each). All subject underwent three tDCS sessions with one-week intervals in between. Effects of tDCS on RS fcMRI were determined at an individual as well as at a group level using both ROI-based and independent-component analyses (ICA). To evaluate the TRT reliability of individual active-tDCS and sham effects on RS fcMRI, voxel-wise intra-class correlation coefficients (ICC) of post-tDCS maps between testing sessions were calculated. For both approaches, results revealed low reliability of RS fcMRI after active tDCS (ICC_(2,1) = -0.09 - 0.16). Reliability of RS fcMRI (baselines only) was low to moderate for ROI-derived (ICC_(2,1) = 0.13 - 0.50) and low for ICA-derived connectivity (ICC_(2,1) = 0.19 - 0.34). Thus, for ROI-based analyses, the distribution of voxel-wise ICC was shifted to lower TRT reliability after active, but not after sham tDCS, for which the distribution was similar to baseline. The intra-individual variation observed here resembles variability of tDCS effects in motor regions and may be one reason why in this study robust tDCS effects at a group level were missing. The data can be used for appropriately designing large scale studies investigating methodological issues such as sources of variability and localisation of tDCS effects.

Dreaming under anesthesia: is it a real possiblity? Investigation of the effect of preoperative imagination on the quality of postoperative dream recalls

Background

Images evoked immediately before the induction of anesthesia by means of suggestions may influence dreaming during anesthesia. This study is a retrospective re-evaluation of the original prospective randomized trial.

Methods

Dream reports were studied in two groups. In group 1. dreams of patients who received suggestions, and in group 2, those of the control group of patients who did not. The incidence of dream reports and the characteristics and the theme of the reported dreams were compared among the groups.

Results

In general, the control and the psychological intervention groups were different in terms of dreaming frequency, and non-recall dreaming. The incidence of dream reports was significantly higher in the suggestion group (82/190 at 10 min and 71/190 at 60 min respectively) than in the control group (16/80 at 10 min and 13/80 at 60 min, respectively; p₁₀ = 0.001 and p₆₀ = 0.002). There were no differences in the nature (thought- like or cinematic), quality (color or B&W) and the mood (positive vs. negative) of the recalled dreams. In general, the contents of the imaginary favorite place and the reported dream were identical in 73.2 %. Among the topics most successfully applied in the operating theater were loved ones (83.8 %), holiday (77.8 %) and sport (63.6 %).

Conclusion

The results of the present study suggest that dreams during anesthesia are influenced by suggestions administered immediately preceding anesthesia.

Trial registration

The study was registered in ClinicalTrials.gov. Identifier: Q1 NCT01839201, Date: 12 Apr. 2013.

Coherence in resting-state EEG as a predictor for the recovery from unresponsive wakefulness syndrome

We investigated differences of EEG coherence within (short-range), and between (long-range) specified brain areas as diagnostic markers for different states in disorders of consciousness (DOC), and their predictive value for recovery from unresponsive wakefulness syndrome (UWS). EEGs of 73 patients and 24 controls were recorded and coma recovery scale- revised (CRS-R) scores were assessed. CRS-R of UWS patients was collected after 12 months and divided into two groups (improved/unimproved). Frontal, parietal, fronto-parietal, fronto-temporal, and fronto-occipital coherence was computed, as well as EEG power over frontal, parietal, occipital, and temporal areas. Minimally conscious patients (MCS) and UWS patients could not be differentiated based on their coherence patterns or on EEG power. Fronto-parietal and parietal coherence could positively predict improvement of UWS patients, i.e. recovery from UWS to MCS. Parietal coherence was significantly higher in delta and theta frequencies in the improved group, as well as the coherence between frontal and parietal regions in delta, theta, alpha, and beta frequencies. High parietal delta and theta, and high fronto-parietal theta and alpha coherence appear to provide strong early evidence for recovery from UWS with high predictive sensitivity and specificity. Short and long-range coherence can have a diagnostic value in the prognosis of recovery from UWS.

Repetitive transcranial magnetic stimulation induced slow wave activity modification: A possible role in disorder of consciousness differential diagnosis?

Slow wave activity (SWA) generation depends on cortico-thalamo-cortical loops that are disrupted in patients with chronic Disorders of Consciousness (DOC), including the Unresponsive Wakefulness Syndrome (UWS) and the Minimally Conscious State (MCS). We hypothesized that the modulation of SWA by means of a repetitive transcranial magnetic stimulation (rTMS) could reveal residual patterns of connectivity, thus supporting the DOC clinical differential diagnosis. We enrolled 10 DOC individuals who underwent a 24hh polysomnography followed by a real or sham 5Hz-rTMS over left primary motor area, and a second polysomnographic recording. A preserved sleep-wake cycle, a standard temporal progression of sleep stages, and a SWA perturbation were found in all of the MCS patients and in none of the UWS individuals, only following the real-rTMS. In conclusion, our combined approach may improve the differential diagnosis between MCS patients, who show a partial preservation of cortical plasticity, and UWS individuals, who lack such properties.

Resting-state networks in healthy adult subjects: a comparison between a 32-element and an 8-element phased array head coil at 3.0 Tesla

BACKGROUND

Little research exists on the influence of a magnetic resonance imaging (MRI) head coil's channel count on measured resting-state functional connectivity.

PURPOSE

To compare a 32-element (32ch) and an 8-element (8ch) phased array head coil with respect to their potential to detect functional connectivity within resting-state networks.

MATERIAL AND METHODS

Twenty-six healthy adults (mean age, 21.7 years; SD, 2.1 years) underwent resting-state functional MRI at 3.0 Tesla with both coils using equal standard imaging parameters and a counterbalanced design. Independent component analysis (ICA) at different model orders and a dual regression approach were performed. Voxel-wise non-parametric statistical between-group contrasts were determined using permutation-based non-parametric inference.

RESULTS

Phantom measurements demonstrated a generally higher image signal-to-noise ratio using the 32ch head coil. However, the results showed no significant differences between corresponding resting-state networks derived from both coils (p < 0.05, FWE-corrected).

CONCLUSION

Using the identical standard acquisition parameters, the 32ch head coil does not offer any significant advantages in detecting ICA-based functional connectivity within RSNs.

Disruption of thalamic functional connectivity is a neural correlate of dexmedetomidine-induced unconsciousness

Understanding the neural basis of consciousness is fundamental to neuroscience research. Disruptions in cortico-cortical connectivity have been suggested as a primary mechanism of unconsciousness. By using a novel combination of positron emission tomography and functional magnetic resonance imaging, we studied anesthesia-induced unconsciousness and recovery using the α₂-agonist dexmedetomidine. During unconsciousness, cerebral metabolic rate of glucose and cerebral blood flow were preferentially decreased in the thalamus, the Default Mode Network (DMN), and the bilateral Frontoparietal Networks (FPNs). Cortico-cortical functional connectivity within the DMN and FPNs was preserved. However, DMN thalamo-cortical functional connectivity was disrupted. Recovery from this state was associated with sustained reduction in cerebral blood flow and restored DMN thalamo-cortical functional connectivity. We report that loss of thalamo-cortical functional connectivity is sufficient to produce unconsciousness.

DOI:http://dx.doi.org/10.7554/eLife.04499.001

Although we are all familiar with the experience of being conscious, explaining precisely what consciousness is and how it arises from activity in the brain remains extremely challenging. Indeed, explaining consciousness is so challenging that it is sometimes referred to as ‘the hard question’ of neuroscience.

One way to obtain insights into the neural basis of consciousness is to compare patterns of activity in the brains of conscious subjects with patterns of brain activity in the same subjects under anesthesia. The results of some experiments of this kind suggest that loss of consciousness occurs when the communication between specific regions within the outer layer of the brain, the cortex, is disrupted. However, other studies seem to contradict these findings by showing that this communication can sometimes remain intact in unconscious subjects.

Akeju, Loggia et al. have now resolved this issue by using brain imaging to examine the changes that occur as healthy volunteers enter and emerge from a light form of anesthesia roughly equivalent to non-REM sleep. An imaging technique called PET revealed that the loss of consciousness in the subjects was accompanied by reduced activity in a structure deep within the brain called the thalamus. Reduced activity was also seen in areas of cortex at the front and back of the brain.

A technique called fMRI showed in turn that communication between the cortex and the thalamus was disrupted as subjects drifted into unconsciousness, whereas communication between cortical regions was spared. As subjects awakened from the anesthesia, communication between the thalamus and the cortex was restored.

These results suggest that changes within distinct brain regions give rise to different depths of unconsciousness. Loss of communication between the thalamus and the cortex generates the unconsciousness of sleep or light anesthesia, while the additional loss of communication between cortical regions generates the unconsciousness of general anesthesia or coma. In addition to explaining the mixed results seen in previous experiments, this distinction could lead to advances in the diagnosis of patients with disorders of consciousness, and even to the development of therapies that target the thalamus and its connections with cortex.

DOI:http://dx.doi.org/10.7554/eLife.04499.002

Structure-Function Relationships behind the Phenomenon of Cognitive Resilience in Neurology: Insights for Neuroscience and Medicine

The phenomenon of cognitive resilience, that is, the dynamical preservation of normal functions despite neurological disorders, demonstrates that cognition can be highly robust to devastating brain injury. Here, cognitive resilience is considered across a range of neurological conditions. Simple computational models of structure-function relationships are used to discuss hypotheses about the neural mechanisms of resilience. Resilience expresses functional redundancies in brain networks and suggests a process of dynamic rerouting of brain signals. This process is underlined by a global renormalization of effective connectivity, capable of restoring information transfer between spared brain structures via alternate pathways. Local mechanisms of synaptic plasticity mediate the renormalization at the lowest level of implementation, but it is also driven by top-down cognition, with a key role of self-awareness in fostering resilience. The presence of abstraction layers in brain computation and networking is hypothesized to account for the renormalization process. Future research directions and challenges are discussed regarding the understanding and control of resilience based on multimodal neuroimaging and computational neuroscience. The study of resilience will illuminate ways by which the brain can overcome adversity and help inform prevention and treatment strategies. It is relevant to combating the negative neuropsychological impact of aging and fostering cognitive enhancement.

Anesthetic effects of propofol in the healthy human brain: functional imaging evidence

Functional imaging methods, including positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), have become important tools for studying how anesthetic drugs act in the human brain to induce the state of general anesthesia. Recent imaging studies using fMRI and PET techniques have demonstrated the regional effects of propofol on the brain. However, the pharmacological mechanism of the action of propofol in the intact human central nervous system is unclear. To explore the possible action targets of propofol in the human brain, a systematic review of the literature was performed. The literature search was performed with limiting factors of "propofol," "functional imaging," "positron emission tomography", and "functional magnetic resonance imaging" from 1966 to July 2013 (using Medline, EMBASE, CINAHL and hand searches of references). Studies meeting the inclusion criteria were reviewed and critiqued for the purpose of this literature research. Eighteen researches meeting the inclusion criteria were reviewed in terms of the appropriateness of valuation technique. In the unconscious state, propofol sharply reduces the regional glucose metabolism rate (rGMR) and regional cerebral blood flow (rCBF) in all brain regions, particularly in the thalamus. However, GMR, such as in the occipital, temporal, and frontal lobes, was obviously decreased at a sedative dosage of propofol, whereas, changes in the thalamus were not obvious. Using fMRI, several studies observed a decrease of connectivity of the thalamus versus an increase of connectivity within the pons of the brainstem during propofol-induced mild sedation. During deep sedation, propofol preserves cortical sensory reactivity, the specific thalamocortical network is moderately affected, whereas the nonspecific thalamocortical network is severely suppressed. In contrast, several recent fMRI studies are consistent on the systemic decreased effects of propofol in the frontoparietal network. Accumulating evidence suggest that propofol-induced unconsciousness is associated with a global metabolic and vascular depression in the human brain and especially with a significant reduction in the thalamocortical network and the frontoparietal network.

Disorders of consciousness after acquired brain injury: the state of the science

The concept of consciousness continues to defy definition and elude the grasp of philosophical and scientific efforts to formulate a testable construct that maps to human experience. Severe acquired brain injury results in the dissolution of consciousness, providing a natural model from which key insights about consciousness may be drawn. In the clinical setting, neurologists and neurorehabilitation specialists are called on to discern the level of consciousness in patients who are unable to communicate through word or gesture, and to project outcomes and recommend approaches to treatment. Standards of care are not available to guide clinical decision-making for this population, often leading to inconsistent, inaccurate and inappropriate care. In this Review, we describe the state of the science with regard to clinical management of patients with prolonged disorders of consciousness. We review consciousness-altering pathophysiological mechanisms, specific clinical syndromes, and novel diagnostic and prognostic applications of advanced neuroimaging and electrophysiological procedures. We conclude with a provocative discussion of bioethical and medicolegal issues that are unique to this population and have a profound impact on care, as well as raising questions of broad societal interest.

Cerebral mechanisms of general anesthesia

How does general anesthesia (GA) work? Anesthetics are pharmacological agents that target specific central nervous system receptors. Once they bind to their brain receptors, anesthetics modulate remote brain areas and end up interfering with global neuronal networks, leading to a controlled and reversible loss of consciousness. This remarkable manipulation of consciousness allows millions of people every year to undergo surgery safely most of the time. However, despite all the progress that has been made, we still lack a clear and comprehensive insight into the specific neurophysiological mechanisms of GA, from the molecular level to the global brain propagation. During the last decade, the exponential progress in neuroscience and neuro-imaging led to a significant step in the understanding of the neural correlates of consciousness, with direct consequences for clinical anesthesia. Far from shutting down all brain activity, anesthetics lead to a shift in the brain state to a distinct, highly specific and complex state, which is being increasingly characterized by modern neuro-imaging techniques. There are several clinical consequences and challenges that are arising from the current efforts to dissect GA mechanisms: the improvement of anesthetic depth monitoring, the characterization and avoidance of intra-operative awareness and post-anesthesia cognitive disorders, and the development of future generations of anesthetics.

Consciousness in humans and non-human animals: recent advances and future directions

This joint article reflects the authors' personal views regarding noteworthy advances in the neuroscience of consciousness in the last 10 years, and suggests what we feel may be promising future directions. It is based on a small conference at the Samoset Resort in Rockport, Maine, USA, in July of 2012, organized by the Mind Science Foundation of San Antonio, Texas. Here, we summarize recent advances in our understanding of subjectivity in humans and other animals, including empirical, applied, technical, and conceptual insights. These include the evidence for the importance of fronto-parietal connectivity and of “top-down” processes, both of which enable information to travel across distant cortical areas effectively, as well as numerous dissociations between consciousness and cognitive functions, such as attention, in humans. In addition, we describe the development of mental imagery paradigms, which made it possible to identify covert awareness in non-responsive subjects. Non-human animal consciousness research has also witnessed substantial advances on the specific role of cortical areas and higher order thalamus for consciousness, thanks to important technological enhancements. In addition, much progress has been made in the understanding of non-vertebrate cognition relevant to possible conscious states. Finally, major advances have been made in theories of consciousness, and also in their comparison with the available evidence. Along with reviewing these findings, each author suggests future avenues for research in their field of investigation.

Sleep and the functional connectome

Sleep and the functional connectome are research areas with considerable overlap. Neuroimaging studies of sleep based on EEG-PET and EEG-fMRI are revealing the brain networks that support sleep, as well as networks that may support the roles and processes attributed to sleep. For example, phenomena such as arousal and consciousness are substantially modulated during sleep, and one would expect this modulation to be reflected in altered network activity. In addition, recent work suggests that sleep also has a number of adaptive functions that support waking activity. Thus the study of sleep may elucidate the circuits and processes that support waking function and complement information obtained from fMRI during waking conditions. In this review, we will discuss examples of this for memory, arousal, and consciousness after providing a brief background on sleep and on studying it with fMRI.

Towards an integrative theory of consciousness: part 1 (neurobiological and cognitive models)

The study of consciousness is poised today at interesting crossroads. There has been a surge of research into various neurobiological underpinnings of consciousness in the past decade. The present article looks at the theories regarding this complex phenomenon, especially the ones that neurobiology, cognitive neuroscience and cognitive psychology have to offer. We will first discuss the origin and etymology of word consciousness and its usage. Neurobiological correlates of consciousness are discussed with structures like the ascending reticular activating system, the amygdala, the cerebellum, the thalamus, the frontoparietal circuits, the prefrontal cortex and the precuneus. The cellular and microlevel theories of consciousness and cerebral activity at the neuronal level contributing to consciousness are highlighted, along with the various theories posited in this area. The role of neuronal assemblies and circuits along with firing patterns and their ramifications for the understanding of consciousness are discussed. A section on the role of anaesthesia and its links to consciousness is presented, along with details of split-brain studies in consciousness and altered states of awareness, including the vegetative states. The article finally discusses the progress cognitive psychology has made in identifying and theorising various perspectives of consciousness, perceptual awareness and conscious processing. Both recent and past researches are highlighted. The importance and salient features of each theory are discussed along with the pitfalls, if present. A need for integration of various theories to understand consciousness from a holistic perspective is stressed, to enable one to reach a theory that explains the ultimate neurobiology of consciousness.

Graph theoretical analysis of sedation's effect on whole brain functional system in school-aged children

The neurophysiological mechanism underlying sedation, especially in school-aged children, remains largely unknown. The recently emerged resting-state functional magnetic resonance imaging (rsfMRI) technique, capable of delineating brain's functional interaction pattern among distributed brain areas, proves to be a unique and powerful tool to study sedation-induced brain reorganization. Based on a relatively large school-aged children population (n=28, 10.3±2.6 years, range 7-15 years) and leveraging rsfMRI and graph theoretical analysis, this study aims to delineate sedation-induced changes in brain's information transferring property from a whole brain system perspective. Our results show a global deterioration in brain's efficiency properties (p=0.0085 and 0.0018, for global and local efficiency, respectively) with a locally graded distribution featuring significant disruptions of key consciousness-related regions. Moreover, our results also indicate a redistribution of brain's information-processing hubs characterized by a right and posterior shift as consistent with the reduced level of consciousness during sedation. Overall, our findings inform a sedation-induced functional reorganization pattern in school-aged children that greatly improve our understanding of sedation's effect in children and may potentially serve as reference for future sedation-related experimental studies and clinical applications.

Roles of default-mode network and supplementary motor area in human vigilance performance: evidence from real-time fMRI

We used real-time functional magnetic resonance imaging (fMRI) to determine which regions of the human brain have a role in vigilance as measured by reaction time (RT) to variably timed stimuli. We first identified brain regions where activation before stimulus presentation predicted RT. Slower RT was preceded by greater activation in the default-mode network, including lateral parietal, precuneus, and medial prefrontal cortices; faster RT was preceded by greater activation in the supplementary motor area (SMA). We examined the roles of these brain regions in vigilance by triggering trials based on brain states defined by blood oxygenation level-dependent activation measured using real-time fMRI. When activation of relevant neural systems indicated either a good brain state (increased activation of SMA) or a bad brain state (increased activation of lateral parietal cortex and precuneus) for performance, a target was presented and RT was measured. RTs on trials triggered by a good brain state were significantly faster than RTs on trials triggered by a bad brain state. Thus human performance was controlled by monitoring brain states that indicated high or low vigilance. These findings identify neural systems that have a role in vigilance and provide direct evidence that the default-mode network has a role in human performance. The ability to control and enhance human behavior based on brain state may have broad implications.

Classifying fMRI-derived resting-state connectivity patterns according to their daily rhythmicity

The vast majority of biological functions express rhythmic fluctuations across the 24-hour day. We investigated the degree of daily modulation across fMRI (functional Magnetic Resonance Imaging) derived resting-state data in 15 subjects by evaluating the time courses of 20 connectivity patterns over 8h (4 sessions). For each subject, we determined the chronotype, which describes the relationship between the individual circadian rhythm and the local time. We could therefore analyze the daily time course of the connectivity patterns controlling for internal time. Furthermore, as the participants' scan times were staggered as a function of their chronotype, we prevented sleep deprivation and kept time awake constant across subjects. Individual functional connectivity within each connectivity pattern was defined at each session as connectivity strength measured by a mean z-value and, in addition, as the spatial extent expressed by the number of activated voxels. Highly rhythmic connectivity patterns included two sub-systems of the Default-Mode Network (DMN) and a network extending over sensori-motor regions. The network characterized as the most stable across the day is mainly associated with processing of executive control. We conclude that the degree of daily modulation largely varies across fMRI derived resting-state connectivity patterns, ranging from highly rhythmic to stable. This finding should be considered when interpreting results from fMRI studies.

Functional Heterogeneity within the Default Network during Semantic Processing and Speech Production

This fMRI study investigated the functional heterogeneity of the core nodes of the default mode network (DMN) during language processing. The core nodes of the DMN were defined as task-induced deactivations over multiple tasks in 94 healthy subjects. We used a factorial design that manipulated different tasks (semantic matching or speech production) and stimuli (familiar words and objects or unfamiliar stimuli), alternating with periods of fixation/rest. Our findings revealed several consistent effects in the DMN, namely less deactivations in the left inferior parietal lobule during semantic than perceptual matching in parallel with greater deactivations during semantic matching in anterior subdivisions of the posterior cingulate cortex (PCC) and the ventromedial prefrontal cortex (MPFC). This suggests that, when the brain is engaged in effortful semantic tasks, a part of the DMN in the left angular gyrus was less deactivated as five other nodes of the DMN were more deactivated. These five DMN areas, where deactivation was greater for semantic than perceptual matching, were further differentiated because deactivation was greater in (i) posterior ventral MPFC for speech production relative to semantic matching, (ii) posterior precuneus and PCC for perceptual processing relative to speech production, and (iii) right inferior parietal cortex for pictures of objects relative to written words during both naming and semantic decisions. Our results thus highlight that task difficulty alone cannot fully explain the functional variability in task-induced deactivations. Together these results emphasize that core nodes within the DMN are functionally heterogeneous and differentially sensitive to the type of language processing.

Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually

A better understanding of how behavioral performance emerges from interacting brain systems may come from analysis of functional networks using functional magnetic resonance imaging. Recent studies comparing such networks with human behavior have begun to identify these relationships, but few have used a time scale small enough to relate their findings to variation within a single individual's behavior. In the present experiment we examined the relationship between a psychomotor vigilance task and the interacting default mode and task positive networks. Two time-localized comparative metrics were calculated: difference between the two networks' signals at various time points around each instance of the stimulus (peristimulus times) and correlation within a 12.3-s window centered at each peristimulus time. Correlation between networks was also calculated within entire resting-state functional imaging runs from the same individuals. These metrics were compared with response speed on both an intraindividual and an interindividual basis. In most cases, a greater difference or more anticorrelation between networks was significantly related to faster performance. While interindividual analysis showed this result generally, using intraindividual analysis it was isolated to peristimulus times 4 to 8 s before the detected target. Within that peristimulus time span, the effect was stronger for individuals who tended to have faster response times. These results suggest that the relationship between functional networks and behavior can be better understood by using shorter time windows and also by considering both intraindividual and interindividual variability.

Reduction in inter-hemispheric connectivity in disorders of consciousness

Clinical diagnosis of disorders of consciousness (DOC) caused by brain injury poses great challenges since patients are often behaviorally unresponsive. A promising new approach towards objective DOC diagnosis may be offered by the analysis of ultra-slow (<0.1 Hz) spontaneous brain activity fluctuations measured with functional magnetic resonance imaging (fMRI) during the resting-state. Previous work has shown reduced functional connectivity within the “default network”, a subset of regions known to be deactivated during engaging tasks, which correlated with the degree of consciousness impairment. However, it remains unclear whether the breakdown of connectivity is restricted to the “default network”, and to what degree changes in functional connectivity can be observed at the single subject level. Here, we analyzed resting-state inter-hemispheric connectivity in three homotopic regions of interest, which could reliably be identified based on distinct anatomical landmarks, and were part of the “Extrinsic” (externally oriented, task positive) network (pre- and postcentral gyrus, and intraparietal sulcus). Resting-state fMRI data were acquired for a group of 11 healthy subjects and 8 DOC patients. At the group level, our results indicate decreased inter-hemispheric functional connectivity in subjects with impaired awareness as compared to subjects with intact awareness. Individual connectivity scores significantly correlated with the degree of consciousness. Furthermore, a single-case statistic indicated a significant deviation from the healthy sample in 5/8 patients. Importantly, of the three patients whose connectivity indices were comparable to the healthy sample, one was diagnosed as locked-in. Taken together, our results further highlight the clinical potential of resting-state connectivity analysis and might guide the way towards a connectivity measure complementing existing DOC diagnosis.

Brain connectivity in disorders of consciousness

The last 10 years witnessed a considerable increase in our knowledge of brain function in survivors to severe brain injuries with disorders of consciousness (DOC). At the same time, a growing interest developed for the use of functional neuroimaging as a new diagnostic tool in these patients. In this context, particular attention has been devoted to connectivity studies-as these, more than measures of brain metabolism, may be more appropriate to capture the dynamics of large populations of neurons. Here, we will review the pros and cons of various connectivity methods as potential diagnostic tools in brain-damaged patients with DOC. We will also discuss the relevance of the study of the level versus the contents of consciousness in this context.

Prefrontal transcranial direct current stimulation changes connectivity of resting-state networks during fMRI

Transcranial direct current stimulation (tDCS) has been proposed for experimental and therapeutic modulation of regional brain function. Specifically, anodal tDCS of the dorsolateral prefrontal cortex (DLPFC) together with cathodal tDCS of the supraorbital region have been associated with improvement of cognition and mood, and have been suggested for the treatment of several neurological and psychiatric disorders. Although modeled mathematically, the distribution, direction, and extent of tDCS-mediated effects on brain physiology are not well understood. The current study investigates whether tDCS of the human prefrontal cortex modulates resting-state network (RSN) connectivity measured by functional magnetic resonance imaging (fMRI). Thirteen healthy subjects underwent real and sham tDCS in random order on separate days. tDCS was applied for 20 min at 2 mA with the anode positioned over the left DLPFC and the cathode over the right supraorbital region. Patterns of resting-state brain connectivity were assessed before and after tDCS with 3 T fMRI, and changes were analyzed for relevant networks related to the stimulation-electrode localizations. At baseline, four RSNs were detected, corresponding to the default mode network (DMN), the left and right frontal-parietal networks (FPNs) and the self-referential network. After real tDCS and compared with sham tDCS, significant changes of regional brain connectivity were found for the DMN and the FPNs both close to the primary stimulation site and in connected brain regions. These findings show that prefrontal tDCS modulates resting-state functional connectivity in distinct functional networks of the human brain.

Measuring the fading consciousness in the human brain

PURPOSE OF REVIEW

Recent neuroimaging studies have provided novel insights on residual brain function in patients with disorders of consciousness, but also raised a number of ethical issues concerning the clinical management of these patients.

RECENT FINDINGS

Clinical studies have rated the Coma Recovery Scale as the most appropriate scale to accurately differentiate patients in a vegetative state from patients in a minimally conscious state. At the population level, a number of neuroimaging studies have provided evidence for more preserved brain activity patterns and cerebral tissue integrity in minimally conscious as compared to vegetative-state patients. However, the use of neuroimaging techniques to diagnose consciousness at the single-patient level remains challenging. In particular, it has been shown that whereas command-following functional MRI paradigms may sometimes detect residual awareness in patients that are behaviorally unresponsive, they can also produce negative results in patients that are communicative at the bedside.

SUMMARY

There is an urgent need of validation of functional MRI active paradigms on larger patient populations before they can be used in clinical routine. Further research on neural correlates of consciousness should hopefully allow using passive paradigms to assess the patients' conscious state without requiring their active collaboration.

Thalamic resting-state functional networks: disruption in patients with mild traumatic brain injury

PURPOSE

To explore the neural correlates of the thalamus by using resting-state functional magnetic resonance (MR) imaging and to investigate whether thalamic resting-state networks (RSNs) are disrupted in patients with mild traumatic brain injury (MTBI).

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board, and written informed consent was obtained from 24 patients with MTBI and 17 healthy control subjects. The patients had varying degrees of symptoms, with a mean disease duration of 22 days. The resting-state functional MR imaging data were analyzed by using a standard seed-based whole-brain correlation method to characterize thalamic RSNs. Student t tests were used to perform comparisons. The association between thalamic RSNs and performance on neuropsychologic and neurobehavioral measures was also investigated in patients with MTBI by using Spearman rank correlation.

RESULTS

A normal pattern of thalamic RSNs was demonstrated in healthy subjects. This pattern was characterized as representing relatively symmetric and restrictive functional thalamocortical connectivity, suggesting an inhibitory property of the thalamic neurons during the resting state. This pattern was disrupted, with significantly increased thalamic RSNs (P ≤ .005) and decreased symmetry (P = .03) in patients with MTBI compared with healthy control subjects. Increased functional thalamocortical redistributive connectivity was correlated with diminished neurocognitive functions and clinical symptoms in patients with MTBI.

CONCLUSION

These findings of abnormal thalamic RSNs lend further support to the presumed subtle thalamic injury in patients with MTBI. Resting-state functional MR imaging can be used as an additional imaging modality for detection of thalamocortical connectivity abnormalities and for better understanding of the complex persistent postconcussive syndrome.

Identifying the default-mode component in spatial IC analyses of patients with disorders of consciousness

OBJECTIVES

Recent fMRI studies have shown that it is possible to reliably identify the default-mode network (DMN) in the absence of any task, by resting-state connectivity analyses in healthy volunteers. We here aimed to identify the DMN in the challenging patient population of disorders of consciousness encountered following coma.

EXPERIMENTAL DESIGN

A spatial independent component analysis-based methodology permitted DMN assessment, decomposing connectivity in all its different sources either neuronal or artifactual. Three different selection criteria were introduced assessing anticorrelation-corrected connectivity with or without an automatic masking procedure and calculating connectivity scores encompassing both spatial and temporal properties. These three methods were validated on 10 healthy controls and applied to an independent group of 8 healthy controls and 11 severely brain-damaged patients [locked-in syndrome (n = 2), minimally conscious (n = 1), and vegetative state (n = 8)].

PRINCIPAL OBSERVATIONS

All vegetative patients showed fewer connections in the default-mode areas, when compared with controls, contrary to locked-in patients who showed near-normal connectivity. In the minimally conscious-state patient, only the two selection criteria considering both spatial and temporal properties were able to identify an intact right lateralized BOLD connectivity pattern, and metabolic PET data suggested its neuronal origin.

CONCLUSIONS

When assessing resting-state connectivity in patients with disorders of consciousness, it is important to use a methodology excluding non-neuronal contributions caused by head motion, respiration, and heart rate artifacts encountered in all studied patients.

Brain connectivity in pathological and pharmacological coma

Recent studies in patients with disorders of consciousness (DOC) tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low-level cortical activation in response to external stimulation in patients in a "vegetative state" or unresponsive wakefulness syndrome. While activation of these "primary" sensory cortices does not necessarily reflect conscious awareness, activation in higher-order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread frontoparietal "global neuronal workspace" in DOC patients including the midline default mode network ("intrinsic" system) and the lateral frontoparietal cortices or "extrinsic system." Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma, and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory, or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between "intrinsic" and "extrinsic" brain networks.

Computing moment-to-moment BOLD activation for real-time neurofeedback

Estimating moment-to-moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment-to-moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment-to-moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI time series, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method.

The relation of ongoing brain activity, evoked neural responses, and cognition

Ongoing brain activity has been observed since the earliest neurophysiological recordings and is found over a wide range of temporal and spatial scales. It is characterized by remarkably large spontaneous modulations. Here, we review evidence for the functional role of these ongoing activity fluctuations and argue that they constitute an essential property of the neural architecture underlying cognition. The role of spontaneous activity fluctuations is probably best understood when considering both their spatiotemporal structure and their functional impact on cognition. We first briefly argue against a "segregationist" view on ongoing activity, both in time and space, which would selectively associate certain frequency bands or levels of spatial organization with specific functional roles. Instead, we emphasize the functional importance of the full range, from differentiation to integration, of intrinsic activity within a hierarchical spatiotemporal structure. We then highlight the flexibility and context-sensitivity of intrinsic functional connectivity that suggest its involvement in functionally relevant information processing. This role in information processing is pursued by reviewing how ongoing brain activity interacts with afferent and efferent information exchange of the brain with its environment. We focus on the relationship between the variability of ongoing and evoked brain activity, and review recent reports that tie ongoing brain activity fluctuations to variability in human perception and behavior. Finally, these observations are discussed within the framework of the free-energy principle which - applied to human brain function - provides a theoretical account for a non-random, coordinated interaction of ongoing and evoked activity in perception and behavior.

On consciousness, resting state fMRI, and neurodynamics

BACKGROUND

During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively.

RESULTS

The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics - in particular the Wilson-Cowan model and stochastic resonance.

CONCLUSIONS

Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research.

Neuroimaging after coma

Following coma, some patients will recover wakefulness without signs of consciousness (only showing reflex movements, i.e., the vegetative state) or may show non-reflex movements but remain without functional communication (i.e., the minimally conscious state). Currently, there remains a high rate of misdiagnosis of the vegetative state (Schnakers et. al. BMC Neurol, 9:35, 8) and the clinical and electrophysiological markers of outcome from the vegetative and minimally conscious states remain unsatisfactory. This should incite clinicians to use multimodal assessment to detect objective signs of consciousness and validate para-clinical prognostic markers in these challenging patients. This review will focus on advanced magnetic resonance imaging (MRI) techniques such as magnetic resonance spectroscopy, diffusion tensor imaging, and functional MRI (fMRI studies in both "activation" and "resting state" conditions) that were recently introduced in the assessment of patients with chronic disorders of consciousness.

Correlated low-frequency BOLD fluctuations in the resting human brain are modulated by recent experience in category-preferential visual regions

The resting brain is associated with significant intrinsic activity fluctuations, such as the correlated low-frequency (LF) blood oxygen level-dependent (BOLD) fluctuations measured by functional magnetic resonance imaging. Despite a recent expansion of studies investigating resting-state LF-BOLD correlations, their nature and function are poorly understood. A major constraint on LF-BOLD correlations appears to be stable properties of anatomic connectivity. There is also evidence that coupling can be modulated by recent or ongoing task performance, suggesting that certain components of correlated dynamics are malleable on short timescales. Here, we compared activity during extended periods of rest following performance of 2 distinct cognitive tasks using different categories of visual stimuli-faces and complex scenes. Prolonged exposure to these distinct categories of visual information caused frontal networks to couple differentially with posterior category-preferential visual regions during subsequent periods of rest. In addition, we report preliminary evidence suggesting that conditions exist in which the degree of modulation of LF-BOLD correlations predicts subsequent memory. The finding that resting-state LF-BOLD correlations are modulated by recent experience in functionally specific brain regions engaged during prior task performance clarifies their role as a dynamic phenomenon which may be involved in mnemonic processes.

Learning sculpts the spontaneous activity of the resting human brain

The brain is not a passive sensory-motor analyzer driven by environmental stimuli, but actively maintains ongoing representations that may be involved in the coding of expected sensory stimuli, prospective motor responses, and prior experience. Spontaneous cortical activity has been proposed to play an important part in maintaining these ongoing, internal representations, although its functional role is not well understood. One spontaneous signal being intensely investigated in the human brain is the interregional temporal correlation of the blood-oxygen level-dependent (BOLD) signal recorded at rest by functional MRI (functional connectivity-by-MRI, fcMRI, or BOLD connectivity). This signal is intrinsic and coherent within a number of distributed networks whose topography closely resembles that of functional networks recruited during tasks. While it is apparent that fcMRI networks reflect anatomical connectivity, it is less clear whether they have any dynamic functional importance. Here, we demonstrate that visual perceptual learning, an example of adult neural plasticity, modifies the resting covariance structure of spontaneous activity between networks engaged by the task. Specifically, after intense training on a shape-identification task constrained to one visual quadrant, resting BOLD functional connectivity and directed mutual interaction between trained visual cortex and frontal-parietal areas involved in the control of spatial attention were significantly modified. Critically, these changes correlated with the degree of perceptual learning. We conclude that functional connectivity serves a dynamic role in brain function, supporting the consolidation of previous experience.

Background and evoked activity and their interaction in the human brain

Most functional neuroimaging studies have investigated brain activity evoked by certain types of stimulation or tasks. In recent years, resting brain activity and its influence on evoked activity has become accessible for investigation. However, despite numerous studies on background and evoked activities, either observed with vascular (functional magnetic resonance imaging, positron emission tomography, optical) or electrophysiological (electroencephalography, magnetoencephalography) or a combination of both methods, so far, there is no generally accepted view concerning both the precise meaning of background activity and its relationship to evoked activity. In this article, we give an overview of the current knowledge on this issue and we review recent studies examining the influence of ongoing activity on behavioral responses and the relationship between ongoing and evoked activity.

What's new in neuroimaging methods?

The rapid advancement of neuroimaging methodology and its growing availability has transformed neuroscience research. The answers to many questions that we ask about how the brain is organized depend on the quality of data that we are able to obtain about the locations, dynamics, fluctuations, magnitudes, and types of brain activity and structural changes. In this review an attempt is made to take a snapshot of the cutting edge of a small component of the very rapidly evolving field of neuroimaging. For each area covered, a brief context is provided along with a summary of a few of the current developments and issues. Then, several outstanding papers, published in the past year or so, are described, providing an example of the directions in which each area is progressing. The areas covered include functional magnetic resonance imaging (fMRI), voxel-based morphometry (VBM), diffusion tensor imaging (DTI), electroencephalography (EEG), magnetoencephalography (MEG), optical imaging, and positron emission tomography (PET). More detail is included on fMRI; its subsections include fMRI interpretation, new fMRI contrasts, MRI technology, MRI paradigms and processing, and endogenous oscillations in fMRI.

Ongoing activity fluctuations in hMT+ bias the perception of coherent visual motion

We have recently shown that intrinsic fluctuations of ongoing activity during baseline have an impact on perceptual decisions reported for an ambiguous visual stimulus (Hesselmann et al., 2008). To test whether this result generalizes from the visual object domain to other perceptual and neural systems, the current study investigated the effect of ongoing signal fluctuations in motion-sensitive brain regions on the perception of coherent visual motion. We determined motion coherence thresholds individually for each subject using a dynamic random dot display. During functional magnetic resonance imaging (fMRI), brief events of subliminal, supraliminal, and periliminal coherent motion were presented with long and variable interstimulus intervals between them. On each trial, subjects reported whether they had perceived "coherent" or "random" motion, and fMRI signal time courses were analyzed separately as a function of stimulus and percept type. In the right motion-sensitive occipito-temporal cortex (hMT+), coherent percepts of periliminal stimuli yielded a larger stimulus-evoked response than random percepts. Prestimulus baseline activity in this region was also significantly higher in these coherent trials than in random trials. As in our previous study, however, the relation between ongoing and evoked activity was not additive but interacted with perceptual outcome. Our data thus suggest that endogenous fluctuations in baseline activity have a generic effect on subsequent perceptual decisions. Although mainstream analytical techniques used in functional neuroimaging do not capture this nonadditive effect of baseline on evoked response, it is in accord with postulates from theoretical frameworks as, for instance, predictive coding.