A method for the estimation of functional brain connectivity from time-series data

A central issue in cognitive neuroscience is which cortical areas are involved in managing information processing in a cognitive task and to understand their temporal interactions. Since the transfer of information in the form of electrical activity from one cortical region will in turn evoke electrical activity in other regions, the analysis of temporal synchronization provides a tool to understand neuronal information processing between cortical regions. We adopt a method for revealing time-dependent functional connectivity. We apply statistical analyses of phases to recover the information flow and the functional connectivity between cortical regions for high temporal resolution data. We further develop an evaluation method for these techniques based on two kinds of model networks. These networks consist of coupled Rössler attractors or of coupled stochastic Ornstein–Uhlenbeck systems. The implemented time-dependent coupling includes uni- and bi-directional connectivities as well as time delayed feedback. The synchronization dynamics of these networks are analyzed using the mean phase coherence, based on averaging over phase-differences, and the general synchronization index. The latter is based on the Shannon entropy. The combination of these with a parametric time delay forms the basis of a connectivity pattern, which includes the temporal and time lagged dynamics of the synchronization between two sources. We model and discuss potential artifacts. We find that the general phase measures are remarkably stable. They produce highly comparable results for stochastic and periodic systems. Moreover, the methods proves useful for identifying brief periods of phase coupling and delays. Therefore, we propose that the method is useful as a basis for generating potential functional connective models.     

Resolving the dynamics of EEG generators by multichannel recordings

The voltage recorded over the cortex (ECoG) or over the scalp (EEG) is generated by currents derived from many sources called “generators”. Different patterns and amplitudes are observed in aroused, sleepy, epileptic or other brain states. Differences in amplitude are generally attributed to differences in synchrony among generators. The degree of EEG synchrony is measured by the correlation between electrodes placed over different cortical regions. We present a new way to quantitatively assess the degree of synchronization of these generators via multichannel recordings. We illustrate how situations where there are several groups of generators with different inter-group and intra-group synchronies can be analyzed. Finally, we present a way to identify the organization of groups exhibiting topographic organization. Although the model presented here is highly simplified, several methods are based on averaging activity over increasingly larger areas. These types of measurements may be applied as well to EEG and ECoG recordings.     

Inter-Network Interactions: Impact of Connections between Oscillatory Neuronal Networks on Oscillation Frequency and Pattern

Oscillations in electrical activity are a characteristic feature of many brain networks and display a wide variety of temporal patterns. A network may express a single oscillation frequency, alternate between two or more distinct frequencies, or continually express multiple frequencies. In addition, oscillation amplitude may fluctuate over time. The origin of this complex repertoire of activity remains unclear. Different cortical layers often produce distinct oscillation frequencies. To investigate whether interactions between different networks could contribute to the variety of oscillation patterns, we created two model networks, one generating on its own a relatively slow frequency (20 Hz; slow network) and one generating a fast frequency (32 Hz; fast network). Taking either the slow or the fast network as source network projecting connections to the other, or target, network, we systematically investigated how type and strength of inter-network connections affected target network activity. For high inter-network connection strengths, we found that the slow network was more effective at completely imposing its rhythm on the fast network than the other way around. The strongest entrainment occurred when excitatory cells of the slow network projected to excitatory or inhibitory cells of the fast network. The fast network most strongly imposed its rhythm on the slow network when its excitatory cells projected to excitatory cells of the slow network. Interestingly, for lower inter-network connection strengths, multiple frequencies coexisted in the target network. Just as observed in rat prefrontal cortex, the target network could express multiple frequencies at the same time, alternate between two distinct oscillation frequencies, or express a single frequency with alternating episodes of high and low amplitude. Together, our results suggest that input from other oscillating networks may markedly alter a network''s frequency spectrum and may partly be responsible for the rich repertoire of temporal oscillation patterns observed in the brain.     

Molecular alignment of proteins in bicellar solutions: quantitative evaluation of effects induced in 2D COSY spectra

Partial molecular alignment leads to an incomplete averaging of anisotropic magnetic interactions such as magnetic dipole interaction or chemical shift anisotropy. In the present contribution we quantitatively describe and evaluate the effects induced by the addition of magnetically oriented lipid bicelles in homonuclear two-dimensional (2D) NMR correlation (COSY) spectra of proteins. It is shown that 2D COSY experiments allow the measurement of H(N)-H(alpha) residual dipole couplings of positive sign which can be used for structure refinement. In contrast to the double- and triple-resonance experiments previously proposed, these measurements can be carried out even on nonisotope-enriched samples.     

Internal motional averaging and three-dimensional structure determination by nuclear magnetic resonance.

Dynamic averaging effects from internal motions on interproton distances estimated from nuclear Overhauser effects (NOE) are determined by using a molecular dynamics simulation of lysozyme. Generalized order parameters measuring angular averaging and radial averaging parameters are calculated. The product of these two parameters describes the full averaging effects on cross-relaxation. Analysis of 2778 non-methyl NOE interactions from the protein interior and surface indicates that distances estimated by assuming a rigid molecule have less than 10% error for 89% of the NOE interactions. However, analysis of 1854 methyl interactions found that only 68% of the distances estimated from cross-relaxation rates would have less than 10% error. Qualitative evaluation of distances according to strong, medium and weak NOE intensities, when used to define only the upper bound for interproton separation, would misassign less than 1% of the distance constraints because of motional averaging. Internal motions do not obscure the identification of secondary structure, although some instances of significant averaging effects were found for interactions in alpha-helical regions. Interresidue NOEs for amino acids more than three residues apart in the primary sequence are more extensively averaged than intraresidue or short-range interresidue NOEs. Intraresidue interactions exhibit a greater degree of angular averaging than those involving interresidue proton pairs. An internal motion does not equally affect all NOE interactions for a particular proton. Thus, incorporation of averaging parameters in nuclear magnetic resonance structure determination procedures must be made on a proton-pair-wise basis. On the basis of the motional averaging results, particular fixed-distance proton pairs in proteins are suggested for use as distance references. A small percentage of NOE pairs localized to three regions of the protein exhibit extreme averaging effects from internal motions. The regions and types of motions involved are described.     

Complex, multifocal, individual-specific attention-related cortical functional circuits

Recent studies focusing on the analysis of individual patterns of non-sensory-motor CNS activity may significantly alter our view of CNS functional mapping. We have recently provided evidence for highly variable attention-related Slow Potential (SP) generating cortical areas across individuals (Basile et al., 2003, 2006). In this work, we present new evidence, searching for other physiological indexes of attention by a new use of a well established method, for individual-specific sets of cortical areas active during expecting attention. We applied latency corrected peak averaging to oscillatory bursts, from 124-channel EEG recordings, and modeled their generators by current density reconstruction. We first computed event-related total power, and averaging was based on individual patterns of narrow task-induced band-power. This method is sensitive to activity out of synchrony with stimuli, and may detect task-related changes missed by regular Event-Related Potential (ERP) averaging. We additionally analyzed overall inter-electrode phase-coherence. The main results were (1) the detection of two bands of attention-induced beta range oscillations (around 25 and 21 Hz), whose scalp topography and current density cortical distribution were complex multi-focal, and highly variable across subjects, including prefrontal and posterior cortical areas. Most important, however, was the observation that (2) the generators of task-induced oscillations are largely the same individual-specific sets of cortical areas active during the resting, baseline state. We concluded that attention-related electrical cortical activity is highly individual-specific (significantly different from sensory-related visual evoked potentials or delta and theta induced band-power), and to a great extent already established during mere wakefulness. We discuss the critical implications of those results, in combination with other studies presenting individual data, to functional mapping: the need to abandon group averaging of task-related cortical activity and to revise studies on group averaged data, since the assumption of universal function to each cortical area appears deeply challenged. Clinical implications regard the interpretation of focal lesion consequences, functional reorganization, and neurosurgical planning.     

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

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

Outline of a theory for the ontogenesis of iso-orientation domains in visual cortex

The following statements are assumed as experimental facts: The majority of cells in visual cortex is selectively sensitive to stimuli in the form of lines or edges of a certain orientation. Optimal orientation varies smoothly from cell to cell over the cortical surface. This structure is present, in immature form, at the time of eye opening. The problem is to find a plausible mechanism for the ontogenesis of this structure. Published theories are reviewed and found to be insufficient in one or more respects. A new theory is proposed. It distinguishes two processes: A) In the previsual period, intracortical connections re-organize themselves such that they restrict activity to an appropriate family of patterns (e.g. stripes of different phases). B) Later, a one-to-one mapping is developed that couples each stimulus orientation to one of the cortical patterns. The coupling may take place in two stages: a) Still before eye opening, two sets of afferent pilot fibres serve to fix the mapping in two points. (The pilot fibres can be assigned to these two sets on the basis of correlated or anticorrelated spike activity. They have genetically programmed orientation preferences which fall into two groups. A fibre sorting mechanism analogous to the one producing ocularity domains concentrates the sets of fibres into complementary activity patterns.) b) After eye opening, a more precise mapping of orientations to cortical patterns develops with the help of visual stimulation and synaptic plasticity according to a well-known mechanism. Experimental evidence for the theory is discussed. The theory can be evaluated in terms of general principles of brain organization.Supported in part by NATO grant No. 1791     

The impact of brain imaging technology on our understanding of motor function and dysfunction

Brain imaging techniques have demonstrated functional specialisation of multiple areas within the motor system. They have also defined the patterns of interactions between these regions during normal motor function and in motor disorders. Functional imaging makes visible the changes in cortical activity that take place over time during motor functions, from the activations a fraction of a second before voluntary action to cortical neuronal plasticity several weeks after injury. Recently, the functional abnormalities underlying various acquired and developmental motor disorders have been described, as well as the effects of therapeutic intervention.     

Real-Time Localization of Moving Dipole Sources for Tracking Multiple Free-Swimming Weakly Electric Fish

In order to survive, animals must quickly and accurately locate prey, predators, and conspecifics using the signals they generate. The signal source location can be estimated using multiple detectors and the inverse relationship between the received signal intensity (RSI) and the distance, but difficulty of the source localization increases if there is an additional dependence on the orientation of a signal source. In such cases, the signal source could be approximated as an ideal dipole for simplification. Based on a theoretical model, the RSI can be directly predicted from a known dipole location; but estimating a dipole location from RSIs has no direct analytical solution. Here, we propose an efficient solution to the dipole localization problem by using a lookup table (LUT) to store RSIs predicted by our theoretically derived dipole model at many possible dipole positions and orientations. For a given set of RSIs measured at multiple detectors, our algorithm found a dipole location having the closest matching normalized RSIs from the LUT, and further refined the location at higher resolution. Studying the natural behavior of weakly electric fish (WEF) requires efficiently computing their location and the temporal pattern of their electric signals over extended periods. Our dipole localization method was successfully applied to track single or multiple freely swimming WEF in shallow water in real-time, as each fish could be closely approximated by an ideal current dipole in two dimensions. Our optimized search algorithm found the animal’s positions, orientations, and tail-bending angles quickly and accurately under various conditions, without the need for calibrating individual-specific parameters. Our dipole localization method is directly applicable to studying the role of active sensing during spatial navigation, or social interactions between multiple WEF. Furthermore, our method could be extended to other application areas involving dipole source localization.     

Bayesian model averaging for evaluation of candidate gene effects

Statistical assessment of candidate gene effects can be viewed as a problem of variable selection and model comparison. Given a certain number of genes to be considered, many possible models may fit to the data well, each including a specific set of gene effects and possibly their interactions. The question arises as to which of these models is most plausible. Inference about candidate gene effects based on a specific model ignores uncertainty about model choice. Here, a Bayesian model averaging approach is proposed for evaluation of candidate gene effects. The method is implemented through simultaneous sampling of multiple models. By averaging over a set of competing models, the Bayesian model averaging approach incorporates model uncertainty into inferences about candidate gene effects. Features of the method are demonstrated using a simulated data set with ten candidate genes under consideration.     

Early and Phasic Cortical Metabolic Changes in Vestibular Neuritis Onset

Functional brain activation studies described the presence of separate cortical areas responsible for central processing of peripheral vestibular information and reported their activation and interactions with other sensory modalities and the changes of this network associated to strategic peripheral or central vestibular lesions. It is already known that cortical changes induced by acute unilateral vestibular failure (UVF) are various and undergo variations over time, revealing different cortical involved areas at the onset and recovery from symptoms. The present study aimed at reporting the earliest change in cortical metabolic activity during a paradigmatic form of UVF such as vestibular neuritis (VN), that is, a purely peripheral lesion of the vestibular system, that offers the opportunity to study the cortical response to altered vestibular processing. This research reports [¹⁸F]fluorodeoxyglucose positron emission tomography brain scan data concerning the early cortical metabolic activity associated to symptoms onset in a group of eight patients suffering from VN. VN patients’ cortical metabolic activity during the first two days from symptoms onset was compared to that recorded one month later and to a control healthy group. Beside the known cortical response in the sensorimotor network associated to vestibular deafferentation, we show for the first time the involvement of Entorhinal (BAs 28, 34) and Temporal (BA 38) cortices in early phases of symptomatology onset. We interpret these findings as the cortical counterparts of the attempt to reorient oneself in space counteracting the vertigo symptom (Bas 28, 34) and of the emotional response to the new pathologic condition (BA 38) respectively. These interpretations were further supported by changes in patients’ subjective ratings in balance, anxiety, and depersonalization/derealization scores when tested at illness onset and one month later. The present findings contribute in expanding knowledge about early, fast-changing, and complex cortical responses to pathological vestibular unbalanced processing.     

Four concurrent feedforward and feedback networks with different roles in the visual cortical hierarchy

Visual stimuli evoke fast-evolving activity patterns that are distributed across multiple cortical areas. These areas are hierarchically structured, as indicated by their anatomical projections, but how large-scale feedforward and feedback streams are functionally organized in this system remains an important missing clue to understanding cortical processing. By analyzing visual evoked responses in laminar recordings from 6 cortical areas in awake mice, we uncovered a dominant feedforward network with scale-free interactions in the time domain. In addition, we established the simultaneous presence of a gamma band feedforward and 2 low frequency feedback networks, each with a distinct laminar functional connectivity profile, frequency spectrum, temporal dynamics, and functional hierarchy. We could identify distinct roles for each of these 4 processing streams, by leveraging stimulus contrast effects, analyzing receptive field (RF) convergency along functional interactions, and determining relationships to spiking activity. Our results support a dynamic dual counterstream view of hierarchical processing and provide new insight into how separate functional streams can simultaneously and dynamically support visual processes.

Visual stimuli evoke fast-evolving activity patterns that are distributed across multiple cortical areas, but how large-scale feedforward and feedback streams are functionally organized in this system remains unclear. Visual evoked responses in laminar recordings from six cortical areas in awake mice reveal how layers and rhythms dynamically orchestrate functional streams in vision.     

Modelling corticothalamic feedback and the gating of the thalamus by the cerebral cortex

Morphological studies have shown that excitatory synapses from the cortex constitute the major source of synapses in the thalamus. However, the effect of these corticothalamic synapses on the function of the thalamus is not well understood because thalamic neurones have complex intrinsic firing properties and interact through multiple types of synaptic receptors. Here we investigate these complex interactions using computational models. We show first, using models of reconstructed thalamic relay neurones, that the effect of corticothalamic synapses on relay cells can be similar to that of afferent synapses, in amplitude, kinetics and timing, although these synapses are located in different regions of the dendrites. This suggests that cortical EPSPs may complement (or predict) the afferent information. Second, using models of reconstructed thalamic reticular neurones, we show that high densities of the low-threshold Ca2+ current in dendrites can give these cells an exquisite sensitivity to cortical EPSPs, but only if their dendrites are hyperpolarized. This property has consequences at the level of thalamic circuits, where corticothalamic EPSPs evoke bursts in reticular neurones and recruit relay cells predominantly through feedforward inhibition. On the other hand, with depolarized dendrites, thalamic reticular neurones do not generate bursts and the cortical influence on relay cells is mostly excitatory. Models therefore suggest that the cortical influence can either promote or antagonize the relay of information, depending on the state of the dendrites of reticular neurones. The control of these dendrites may therefore be a determinant of attentional mechanisms. We also review the effect of corticothalamic feedback at the network level, and show how the cortical control over the thalamus is essential in co-ordinating widespread, coherent oscillations. We suggest mechanisms by which different modes of corticothalamic interaction would allow oscillations of very different spatiotemporal coherence to coexist in the thalamocortical system.     

Multiple frequency steady-state evoked magnetic field mapping of digit representation in primary somatosensory cortex

Magnetic source imaging of multiple frequency steady-state somatosensory evoked responses was examined using a 151-channel magnetoencephalography (MEG) system and a dual-channel electrical stimulator. Somatotopy of digit representation was studied in healthy subjects and effects of injury-related cortical plasticity in patients with unilateral transections of the median or the ulnar nerve. Dipole source locations exhibited somatotopic order with overlap between neighboring digits. In two of three nerve injury patients evidence for cortical reorganization was found. The location of sources related to digits neighboring deafferented digits was changed and their dipole moments were enlarged by comparsion with the sources related to contralateral homologue control digits. As a basis for magnetic source imaging, the recording of multiple frequency somatosensory steady-state evoked responses may be a viable and time saving alternative to the recording of transient evoked responses.     

Multiple frequency steady-state evoked magnetic field mapping of digit representation in primary somatosensory cortex

Magnetic source imaging of multiple frequency steady-state somatosensory evoked responses was examined using a 151-channel magnetoencephalography (MEG) system and a dual-channel electrical stimulator. Somatotopy of digit representation was studied in healthy subjects and effects of injury-related cortical plasticity in patients with unilateral transections of the median or the ulnar nerve. Dipole source locations exhibited somatotopic order with overlap between neighboring digits. In two of three nerve injury patients evidence for cortical reorganization was found. The location of sources related to digits neighboring deafferented digits was changed and their dipole moments were enlarged by comparsion with the sources related to contralateral homologue control digits. As a basis for magnetic source imaging, the recording of multiple frequency somatosensory steady-state evoked responses may be a viable and time saving alternative to the recording of transient evoked responses.     

Ethanol''s Effects on Cortical Adenylate Cyclase Activity

The effects of ethanol on beta-adrenergic receptor-coupled adenylate cyclase (AC) of mouse cerebral cortex were examined. The addition of ethanol (20-500 mM) to incubation mixtures containing cortical membranes demonstrated that ethanol could increase AC activity and potentiate the stimulatory effects of guanylyl-imidodiphosphate [Gpp(NH)p] on AC activity. Ethanol increased the rate of activation of AC by guanine nucleotides and concomitantly decreased the EC50 for magnesium required to achieve maximal stimulation of cortical AC. The EC50 values for Gpp(NH)p and isoproterenol stimulation of AC activity were also altered by ethanol. Ethanol was capable of stimulating AC extracted by use of digitonin. The AC activity in the digitonin extract was no longer sensitive to the addition of Gpp(NH)p or NaF, but was still stimulated by ethanol. We propose multiple sites of action for ethanol in stimulating cortical AC activity. These sites include actions at the beta-adrenergic receptor, at the G/F coupling proteins, and at the catalytic unit of cortical AC. Comparison of ethanol's actions on cortical beta receptor coupled AC activity with prior reported actions of ethanol on striatal dopamine (DA)-sensitive AC indicated differential sensitivities of these two AC systems to ethanol. These differences may be determined by specific coupling characteristics of the striatal and cortical AC systems or by differences in the plasma membranes in which striatal and cortical AC systems are located.     

Measuring Granger Causality between cortical regions from voxelwise fMRI BOLD signals with LASSO

Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis.     

Predisposition for and Prevention of Subjective Tinnitus Development

Dysfunction of the inner ear as caused by presbyacusis, injuries or noise traumata may result in subjective tinnitus, but not everyone suffering from one of these diseases develops a tinnitus percept and vice versa. The reasons for these individual differences are still unclear and may explain why different treatments of the disease are beneficial for some patients but not for others. Here we for the first time compare behavioral and neurophysiological data from hearing impaired Mongolian gerbils with (T) and without (NT) a tinnitus percept that may elucidate why some specimen do develop subjective tinnitus after noise trauma while others do not. Although noise trauma induced a similar permanent hearing loss in all animals, tinnitus did develop only in about three quarters of these animals. NT animals showed higher overall cortical and auditory brainstem activity before noise trauma compared to T animals; that is, animals with low overall neuronal activity in the auditory system seem to be prone to develop tinnitus after noise trauma. Furthermore, T animals showed increased activity of cortical neurons representing the tinnitus frequencies after acoustic trauma, whereas NT animals exhibited an activity decrease at moderate sound intensities by that time. Spontaneous activity was generally increased in T but decreased in NT animals. Plastic changes of tonotopic organization were transient, only seen in T animals and vanished by the time the tinnitus percept became chronic. We propose a model for tinnitus prevention that points to a global inhibitory mechanism in auditory cortex that may prevent tinnitus genesis in animals with high overall activity in the auditory system, whereas this mechanism seems not potent enough for tinnitus prevention in animals with low overall activity.