Intracortical recordings and fMRI: an attempt to study operational modules and networks simultaneously

Functional MRI in Radiology—A Personal Review

We, here, provide a personal review article on the development of a functional MRI in the radiology departments of two German university medicine units. Although the international community for human brain mapping has met since 1995, the researchers fascinated by human brain function are still young and innovative. However, the impact of functional magnetic resonance imaging (fMRI) on prognosis and treatment decisions is restricted, even though standardized methods have been developed. The tradeoff between the groundbreaking studies on brain function and the attempt to provide reliable biomarkers for clinical decisions is large. By describing some historical developments in the field of fMRI, from a personal view, the rise of this method in clinical neuroscience during the last 25 years might be understandable. We aim to provide some background for (a) the historical developments of fMRI, (b) the establishment of two research units for fMRI in the departments of radiology in Germany, and (c) a description of some contributions within the selected fields of systems neuroscience, clinical neurology, and behavioral psychology.

A human prefrontal-subthalamic circuit for cognitive control

The subthalamic nucleus is a key site controlling motor function in humans. Deep brain stimulation of the subthalamic nucleus can improve movements in patients with Parkinson's disease; however, for unclear reasons, it can also have cognitive effects. Here, we show that the human subthalamic nucleus is monosynaptically connected with cognitive brain areas such as the prefrontal cortex. Single neurons and field potentials in the subthalamic nucleus are modulated during cognitive processing and are coherent with 4-Hz oscillations in medial prefrontal cortex. These data predict that low-frequency deep brain stimulation may alleviate cognitive deficits in Parkinson's disease patients. In line with this idea, we found that novel 4-Hz deep brain stimulation of the subthalamic nucleus improved cognitive performance. These data support a role for the human hyperdirect pathway in cognitive control, which could have relevance for brain-stimulation therapies aimed at cognitive symptoms of human brain disease.awx300media15660002226001.

Metastable States of Multiscale Brain Networks Are Keys to Crack the Timing Problem

The dynamics of the environment where we live in and the interaction with it, predicting events, provided strong evolutionary pressures for the brain functioning to process temporal information and generate timed responses. As a result, the human brain is able to process temporal information and generate temporal patterns. Despite the clear importance of temporal processing to cognition, learning, communication and sensory, motor and emotional processing, the basal mechanisms of how animals differentiate simple intervals or provide timed responses are still under debate. The lesson we learned from the last decade of research in neuroscience is that functional and structural brain connectivity matter. Specifically, it has been accepted that the organization of the brain in interacting segregated networks enables its function. In this paper we delineate the route to a promising approach for investigating timing mechanisms. We illustrate how novel insight into timing mechanisms can come by investigating brain functioning as a multi-layer dynamical network whose clustered dynamics is bound to report the presence of metastable states. We anticipate that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic functioning associated to time perception. This new point of view will help further clarifying mechanisms of neuropsychiatric disorders.

High frequency neurons determine effective connectivity in neuronal networks

The emergence of flexible information channels in brain networks is a fundamental question in neuroscience. Understanding the mechanisms of dynamic routing of information would have far-reaching implications in a number of disciplines ranging from biology and medicine to information technologies and engineering. In this work, we show that the presence of a node firing at a higher frequency in a network with local connections, leads to reliable transmission of signals and establishes a preferential direction of information flow. Thus, by raising the firing rate a low degree node can behave as a functional hub, spreading its activity patterns polysynaptically in the network. Therefore, in an otherwise homogeneous and undirected network, firing rate is a tunable parameter that introduces directionality and enhances the reliability of signal transmission. The intrinsic firing rate across neuronal populations may thus determine preferred routes for signal transmission that can be easily controlled by changing the firing rate in specific nodes. We show that the results are generic and the same mechanism works in the networks with more complex topology.

Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations

Chronic pain is the greatest source of disability globally and claims related to chronic pain feature in many insurance and medico-legal cases. Brain imaging (for example, functional MRI, PET, EEG and magnetoencephalography) is widely considered to have potential for diagnosis, prognostication, and prediction of treatment outcome in patients with chronic pain. In this Consensus Statement, a presidential task force of the International Association for the Study of Pain examines the capabilities of brain imaging in the diagnosis of chronic pain, and the ethical and legal implications of its use in this way. The task force emphasizes that the use of brain imaging in this context is in a discovery phase, but has the potential to increase our understanding of the neural underpinnings of chronic pain, inform the development of therapeutic agents, and predict treatment outcomes for use in personalized pain management. The task force proposes standards of evidence that must be satisfied before any brain imaging measure can be considered suitable for clinical or legal purposes. The admissibility of such evidence in legal cases also strongly depends on laws that vary between jurisdictions. For these reasons, the task force concludes that the use of brain imaging findings to support or dispute a claim of chronic pain - effectively as a pain lie detector - is not warranted, but that imaging should be used to further our understanding of the mechanisms underlying pain.

Spontaneous Neural Dynamics and Multi-scale Network Organization

Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire.

Functional magnetic resonance imaging networks induced by intracranial stimulation may help defining the epileptogenic zone

Patients with medically intractable epilepsy often undergo invasive evaluation and surgery, with a 50% success rate. The low success rate is likely due to poor identification of the epileptogenic zone (EZ), the brain area causing seizures. This work introduces a new method using functional magnetic resonance imaging (fMRI) with simultaneous direct electrical stimulation of the brain that could help localize the EZ, performed in five patients with medically intractable epilepsy undergoing invasive evaluation with intracranial depth electrodes. Stimulation occurred in a location near the hypothesized EZ and a location away. Electrical recordings in response to stimulation were recorded and compared to fMRI. Multiple stimulation parameters were varied, like current and frequency. The brain areas showing fMRI response were compared with the areas resected and the success of surgery. Robust fMRI maps of activation networks were easily produced, which also showed a significant but weak positive correlation between quantitative measures of blood-oxygen-level-dependent (BOLD) activity and measures of electrical activity in response to direct electrical stimulation (mean correlation coefficient of 0.38 for all acquisitions that produced a strong BOLD response). For four patients with outcome data at 6 months, successful surgical outcome is consistent with the resection of brain areas containing high local fMRI activity. In conclusion, this method demonstrates the feasibility of simultaneous direct electrical stimulation and fMRI in humans, which allows the study of brain connectivity with high resolution and full spatial coverage. This innovative technique could be used to better define the localization and extension of the EZ in intractable epilepsies, as well as for other functional neurosurgical procedures.

Large-scale topology and the default mode network in the mouse connectome

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)--a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans.

Effective connectivity maps in the swine somatosensory cortex estimated from electrocorticography and validated with intracortical local field potential measurements

Macroscopic techniques are increasingly being used to estimate functional connectivity in the brain, which provides valuable information about brain networks. In any such endeavors it is important to understand capabilities and limitations of each technique through direct validation, which is often lacking. This study evaluated a multiple dipole source analysis technique based on electrocorticography (ECOG) data in estimating effective connectivity maps and validated the technique with intracortical local field potential (LFP) recordings. The study was carried out in an animal model (swine) with a large brain to avoid complications caused by spreading of the volume current. The evaluation was carried out for the cortical projections from the trigeminal nerve and corticocortical connectivity from the first rostrum area (R1) in the primary somatosensory cortex. Stimulation of the snout and layer IV of the R1 did not activate all projection areas in each animal, although whenever an area was activated in a given animal, its location was consistent with the intracortical LFP. The two types of connectivity maps based on ECOG analysis were consistent with each other and also with those estimated from the intracortical LFP, although there were small discrepancies. The discrepancies in mean latency based on ECOG and LFP were all very small and nonsignificant: snout stimulation, -1.1-2.0 msec (contralateral hemisphere) and 3.9-8.5 msec (ipsilateral hemisphere); R1 stimulation, -1.4-2.2 msec for the ipsilateral and 0.6-1.4 msec for the contralateral hemisphere. Dipole source analysis based on ECOG appears to be quite useful for estimating effective connectivity maps in the brain.

Psychiatric disorders: diagnosis to therapy

Recent findings in a range of scientific disciplines are challenging the conventional wisdom regarding the etiology, classification, and treatment of psychiatric disorders. This Review focuses on the current state of the psychiatric diagnostic nosology and recent progress in three areas: genomics, neuroimaging, and therapeutics development. The accelerating pace of novel and unexpected findings is transforming the understanding of mental illness and represents a hopeful sign that the approaches and models that have sustained the field for the past 40 years are yielding to a flood of new data and presaging the emergence of a new and more powerful scientific paradigm.

Interpreting the effects of altered brain anatomical connectivity on fMRI functional connectivity: a role for computational neural modeling

Recently, there have been a large number of studies using resting state fMRI to characterize abnormal brain connectivity in patients with a variety of neurological, psychiatric, and developmental disorders. However, interpreting what the differences in resting state fMRI functional connectivity (rsfMRI-FC) actually reflect in terms of the underlying neural pathology has proved to be elusive because of the complexity of brain anatomical connectivity. The same is the case for task-based fMRI studies. In the last few years, several groups have used large-scale neural modeling to help provide some insight into the relationship between brain anatomical connectivity and the corresponding patterns of fMRI-FC. In this paper we review several efforts at using large-scale neural modeling to investigate the relationship between structural connectivity and functional/effective connectivity to determine how alterations in structural connectivity are manifested in altered patterns of functional/effective connectivity. Because the alterations made in the anatomical connectivity between specific brain regions in the model are known in detail, one can use the results of these simulations to determine the corresponding alterations in rsfMRI-FC. Many of these simulation studies found that structural connectivity changes do not necessarily result in matching changes in functional/effective connectivity in the areas of structural modification. Often, it was observed that increases in functional/effective connectivity in the altered brain did not necessarily correspond to increases in the strength of the anatomical connection weights. Note that increases in rsfMRI-FC in patients have been interpreted in some cases as resulting from neural plasticity. These results suggest that this interpretation can be mistaken. The relevance of these simulation findings to the use of functional/effective fMRI connectivity as biomarkers for brain disorders is also discussed.

Negative BOLD response to interictal epileptic discharges in focal epilepsy

In EEG-fMRI studies, BOLD responses related to interictal epileptic discharges (IEDs) are most often the expected positive response (activation) but sometimes a surprising negative response (deactivation). The significance of deactivation in the region of IED generation is uncertain. The aim of this study was to determine if BOLD deactivation was caused by specific IED characteristics. Among focal epilepsy patients who underwent 3T EEG-fMRI from 2006 to 2011, those with negative BOLD having a maximum t-value in the IED generating region were selected. As controls, subjects with maximum activation in the IED generating region were selected. We established the relationship between the type of response (activation/deactivation) and (1) presence of slow wave in the IEDs, (2) lobe of epileptic focus, (3) occurrence as isolated events or bursts, (4) spatial extent of the EEG discharge. Fifteen patients with deactivation and 15 with activation were included. The IEDs were accompanied by a slow wave in 87 % of patients whose primary BOLD was a deactivation and only in 33 % of patients with activation. In the deactivation group, the epileptic focus was more frequently in the posterior quadrant and involved larger cortical areas, whereas in the activation group it was more frequently temporal. IEDs were more frequently of long duration in the deactivation group. The main factor responsible for focal deactivations is the presence of a slow wave, which is the likely electrographic correlate of prolonged inhibition. This adds a link to the relationship between electrophysiological and BOLD activities.

Recording visual evoked potentials and auditory evoked P300 at 9.4T static magnetic field

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has shown a number of advantages that make this multimodal technique superior to fMRI alone. The feasibility of recording EEG at ultra-high static magnetic field up to 9.4T was recently demonstrated and promises to be implemented soon in fMRI studies at ultra high magnetic fields. Recording visual evoked potentials are expected to be amongst the most simple for simultaneous EEG/fMRI at ultra-high magnetic field due to the easy assessment of the visual cortex. Auditory evoked P300 measurements are of interest since it is believed that they represent the earliest stage of cognitive processing. In this study, we investigate the feasibility of recording visual evoked potentials and auditory evoked P300 in a 9.4T static magnetic field. For this purpose, EEG data were recorded from 26 healthy volunteers inside a 9.4T MR scanner using a 32-channel MR compatible EEG system. Visual stimulation and auditory oddball paradigm were presented in order to elicit evoked related potentials (ERP). Recordings made outside the scanner were performed using the same stimuli and EEG system for comparison purposes. We were able to retrieve visual P100 and auditory P300 evoked potentials at 9.4T static magnetic field after correction of the ballistocardiogram artefact using independent component analysis. The latencies of the ERPs recorded at 9.4T were not different from those recorded at 0T. The amplitudes of ERPs were higher at 9.4T when compared to recordings at 0T. Nevertheless, it seems that the increased amplitudes of the ERPs are due to the effect of the ultra-high field on the EEG recording system rather than alteration in the intrinsic processes that generate the electrophysiological responses.

EEG acquisition in ultra-high static magnetic fields up to 9.4 T

The simultaneous acquisition of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data has gained momentum in recent years due to the synergistic effects of the two modalities with regard to temporal and spatial resolution. Currently, only EEG-data recorded in fields of up to 7 T have been reported. We investigated the feasibility of recording EEG inside a 9.4 T static magnetic field, specifically to determine whether meaningful EEG information could be recovered from the data after removal of the cardiac-related artefact. EEG-data were recorded reliably and reproducibly at 9.4 T and the cardiac-related artefact increased in amplitude with increasing B0, as expected. Furthermore, we were able to correct for the cardiac-related artefact and identify auditory event related responses at 9.4 T in 75% of subjects using independent component analysis (ICA). Also by means of ICA we detected event related spectral perturbations (ERSP) in subjects at 9.4 T in response to opening/closing the eyes comparable with the response at 0 T. Overall our results suggest that it is possible to record meaningful EEG data at ultra-high magnetic fields. The simultaneous EEG-fMRI approach at ultra-high-fields opens up the horizon for investigating brain dynamics at a superb spatial resolution and a temporal resolution in the millisecond domain.