11414805
Characterization of Cortical Networks and Corticocortical Functional Connectivity Mediating Arbitrary Visuomotor Mapping
Adaptive behaviors are built on the arbitrary linkage of sensory inputs to actions and goals. Although the sensorimotor and associative frontostriatal circuits are known to mediate arbitrary visuomotor mappings, the underlying corticocortico dynamics remain elusive. Here, we take a novel approach exploiting gamma-band neural activity to study the human cortical networks and corticocortical functional connectivity mediating arbitrary visuomotor mapping. Single-trial gamma-power time courses were estimated for all Brodmann areas by combing magnetoencephalographic and MRI data with spectral analysis and beam-forming techniques. Linear correlation and Granger causality analyses were performed to investigate functional connectivity between cortical regions. The performance of visuomotor associations was characterized by an increase in gamma-power and functional connectivity over the sensorimotor and frontoparietal network, in addition to medial prefrontal areas. The superior parietal area played a driving role in the network, exerting Granger causality on the dorsal premotor area. Premotor areas acted as relay from parietal to medial prefrontal cortices, which played a receiving role in the network. Link community analysis further revealed that visuomotor mappings reflect the coordination of multiple subnetworks with strong overlap over motor and frontoparietal areas. We put forward an associative account of the underlying cognitive processes and corticocortical functional connectivity. Overall, our approach and results provide novel perspectives toward a better understanding of how distributed brain activity coordinates adaptive behaviors. SIGNIFICANCE STATEMENT In everyday life, most of our behaviors are based on the arbitrary linkage of sensory information to actions and goals, such as stopping at a red traffic light. Despite their automaticity, such behaviors rely on the activity of a large brain network and elusive interareal functional connectivity. We take a novel approach exploiting noninvasive recordings of human brain activity to reveal the cortical networks and corticocortical functional connectivity mediating visuomotor mappings. Parietal areas were found to play a driving role in the network, whereas premotor areas acted as relays from parietal to medial prefrontal cortices, which played a receiving role. Overall, our approach and results provide novel perspectives toward a better understanding of how distributed brain activity coordinates adaptive behaviors.
297877
Premotor and parietal cortex: corticocortical connectivity and combinatorial computations.
The dorsal premotor cortex is a functionally distinct cortical field or group of fields in the primate frontal cortex. Anatomical studies have confirmed that most parietal input to the dorsal premotor cortex originates from the superior parietal lobule. However, these projections arise not only from the dorsal aspect of area 5, as has long been known, but also from newly defined areas of posterior parietal cortex, which are directly connected with the extrastriate visual cortex. Thus, the dorsal premotor cortex receives much more direct visual input than previously accepted. It appears that this fronto-parietal network functions as a visuomotor controller-one that makes computations based on proprioceptive, visual, gaze, attentional, and other information to produce an output that reflects the selection, preparation, and execution of movements.
18358254
Differences in Gamma Frequencies across Visual Cortex Restrict Their Possible Use in Computation
Neuronal oscillations in the gamma band (30-80 Hz) have been suggested to play a central role in feature binding or establishing channels for neural communication. For these functions, the gamma rhythm frequency must be consistent across neural assemblies encoding the features of a stimulus. Here we test the dependence of gamma frequency on stimulus contrast in V1 cortex of awake behaving macaques and show that gamma frequency increases monotonically with contrast. Changes in stimulus contrast over time leads to a reliable gamma frequency modulation on a fast timescale. Further, large stimuli whose contrast varies across space generate gamma rhythms at significantly different frequencies in simultaneously recorded neuronal assemblies separated by as little as 400 microm, making the gamma rhythm a poor candidate for binding or communication, at least in V1. Instead, our results suggest that the gamma rhythm arises from local interactions between excitation and inhibition.
9776546
Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention
In crowded visual scenes, attention is needed to select relevant stimuli. To study the underlying mechanisms, we recorded neurons in cortical area V4 while macaque monkeys attended to behaviorally relevant stimuli and ignored distracters. Neurons activated by the attended stimulus showed increased gamma-frequency (35 to 90 hertz) synchronization but reduced low-frequency (<17 hertz) synchronization compared with neurons at nearby V4 sites activated by distracters. Because postsynaptic integration times are short, these localized changes in synchronization may serve to amplify behaviorally relevant signals in the cortex.
6663131
Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4
To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene. To find a target object in a crowded scene, a face in a crowd for example, the visual system might turn the neural representation of each object on and off in a serial fashion, testing each representation against a template of the target item. Alternatively, it might allow the processing of all objects in parallel but bias activity in favor of those neurons that represent critical features of the target, until the target emerges from the background. To test these possibilities, we recorded neurons in area V4 of monkeys freely scanning a complex array to find a target defined by color, shape, or both. Throughout the period of searching, neurons gave enhanced responses and synchronized their activity in the gamma range whenever a preferred stimulus in their receptive field matched a feature of the target, as predicted by parallel models. Neurons also gave enhanced responses to candidate targets that were selected for saccades, or foveation, reflecting a serial component of visual search. Thus, serial and parallel mechanisms of response enhancement and neural synchrony work together to identify objects in a scene.
1896991
Temporal structure in neuronal activity during working memory in macaque parietal cortex
Many cortical structures have elevated firing rates during working memory, but it is not known how the activity is maintained. To investigate whether reverberating activity is important, we studied the temporal structure of local field potential (LFP) activity and spiking from area LIP in two awake macaques during a memory-saccade task. Using spectral analysis, we found spatially tuned elevated power in the gamma band (25–90 Hz) in LFP and spiking activity during the memory period. Spiking and LFP activity were also coherent in the gamma band but not at lower frequencies. Finally, we decoded LFP activity on a single-trial basis and found that LFP activity in parietal cortex discriminated between preferred and anti-preferred direction with approximately the same accuracy as the spike rate and predicted the time of a planned movement with better accuracy than the spike rate. This finding could accelerate the development of a cortical neural prosthesis.
13100525
Simultaneous MEG and intracranial EEG recordings during attentive reading
The relationship between neural oscillations recorded at various spatial scales remains poorly understood partly due to an overall dearth of studies utilizing simultaneous measurements. In an effort to study quantitative markers of attention during reading, we performed simultaneous magnetoencephalography (MEG) and intracranial electroencephalography (iEEG) recordings in four epileptic patients. Patients were asked to attend to a specific color when presented with an intermixed series of red words and green words, with words of a given color forming a cohesive story. We analyzed alpha, beta, and gamma band oscillatory responses to the word presentation and compared the strength and spatial organization of those responses in both electrophysiological recordings. Time-frequency analysis of iEEG revealed a network of clear attention-modulated high gamma band (50-150 Hz) power increases and alpha/beta (9-25 Hz) suppressions in response to the words. In addition to analyses at the sensor level, MEG time-frequency analysis was performed at the source level using a sliding window beamformer technique. Strong alpha/beta suppressions were observed in MEG reconstructions, in tandem with iEEG effects. While the MEG counterpart of high gamma band enhancement was difficult to interpret at the sensor level in two patients, MEG time-frequency source reconstruction revealed additional activation patterns in accordance with iEEG results. Importantly, iEEG allowed us to confirm that several sources of gamma band modulation observed with MEG were indeed of cortical origin rather than EMG muscular or ocular artifact.
14322909
Human and Rodent Homologies in Action Control: Corticostriatal Determinants of Goal-Directed and Habitual Action
Recent behavioral studies in both humans and rodents have found evidence that performance in decision-making tasks depends on two different learning processes; one encoding the relationship between actions and their consequences and a second involving the formation of stimulus–response associations. These learning processes are thought to govern goal-directed and habitual actions, respectively, and have been found to depend on homologous corticostriatal networks in these species. Thus, recent research using comparable behavioral tasks in both humans and rats has implicated homologous regions of cortex (medial prefrontal cortex/medial orbital cortex in humans and prelimbic cortex in rats) and of dorsal striatum (anterior caudate in humans and dorsomedial striatum in rats) in goal-directed action and in the control of habitual actions (posterior lateral putamen in humans and dorsolateral striatum in rats). These learning processes have been argued to be antagonistic or competing because their control over performance appears to be all or none. Nevertheless, evidence has started to accumulate suggesting that they may at times compete and at others cooperate in the selection and subsequent evaluation of actions necessary for normal choice performance. It appears likely that cooperation or competition between these sources of action control depends not only on local interactions in dorsal striatum but also on the cortico-basal ganglia network within which the striatum is embedded and that mediates the integration of learning with basic motivational and emotional processes. The neural basis of the integration of learning and motivation in choice and decision-making is still controversial and we review some recent hypotheses relating to this issue.
15077032
Larger interregional synchrony is associated with greater behavioral success in a complex sensory integration task in humans.
Successful behavior depends on effective communication between distant brain regions. Moreover, disturbance of effective communication can cause neurological symptoms like apraxia, dyslexia or object agnosia. Interregional communication can be assessed by coherence analysis of synchronized neuronal oscillations, and has been referred to as synchrony or "binding". The concept of synchrony as a means of information coding is attractive, but its functional relevance has been challenged. We hypothesized that if synchrony is functionally relevant in humans, then more synchrony should determine better behavioral performance. Here, we show in a visuotactile integration task that the amount of low-frequency (7-13Hz), long-range electroencephalographic coherence between visual and sensorimotor cortex is significantly correlated with the level of performance. Trials with highest coherences were the most successful ones and vice versa in the absence of differences in regional activation measured as task-related spectral power. In summary, quantitatively linking the amount of long-range synchrony with the degree of behavioral success in humans, the present data suggest that the ability to generate topographically specific synchrony of high amplitude is functionally relevant for behavioral success. They also raise the possibility that the magnitude of regional activation is less representative of the efficacy of brain functioning than interregional synchrony.
13772082
Coupling between Neuronal Firing Rate, Gamma LFP, and BOLD fMRI Is Related to Interneuronal Correlations
BACKGROUND
To what extent is activity of individual neurons coupled to the local field potential (LFP) and to blood-oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI)? This issue is of high significance for understanding brain function and for relating animal studies to fMRI, yet it is still under debate.


RESULTS
Here we report data from simultaneous recordings of isolated unit activity and LFP by using multiple electrodes in the human auditory cortex. We found a wide range of coupling levels between the activity of individual neurons and gamma LFP. However, this large variability could be predominantly explained (r = 0.66) by the degree of firing-rate correlations between neighboring neurons. Importantly, this phenomenon occurred during both sensory stimulation and spontaneous activity. Concerning the coupling of neuronal activity to BOLD fMRI, we found that gamma LFP was well coupled to BOLD measured across different individuals (r = 0.62). By contrast, the coupling of single units to BOLD was highly variable and, again, tightly related to interneuronal-firing-rate correlations (r = 0.70).


CONCLUSIONS
Our results offer a resolution to a central controversy regarding the coupling between neurons, LFP, and BOLD signals by demonstrating, for the first time, that the coupling of single units to the other measures is variable yet it is tightly related to the degree of interneuronal correlations in the human auditory cortex.
15595531
Causality detection based on information-theoretic approaches in time series analysis
Synchronization, a basic nonlinear phenomenon, is widely observed in diverse complex systems studied in physical, biological and other natural sciences, as well as in social sciences, economy and finance. While studying such complex systems, it is important not only to detect synchronized states, but also to identify causal relationships (i.e. who drives whom) between concerned (sub) systems. The knowledge of information-theoretic measures (i.e. mutual information, conditional entropy) is essential for the analysis of information flow between two systems or between constituent subsystems of a complex system. However, the estimation of these measures from a set of finite samples is not trivial. The current extensive literatures on entropy and mutual information estimation provides a wide variety of approaches, from approximation-statistical, studying rate of convergence or consistency of an estimator for a general distribution, over learning algorithms operating on partitioned data space to heuristical approaches. The aim of this paper is to provide a detailed overview of information theoretic approaches for measuring causal influence in multivariate time series and to focus on diverse approaches to the entropy and mutual information estimation.
61235136
Spectral Analysis for Physical Applications
Note: Includes bibliographical references and indexes Reference Record created on 2004-09-07, modified on 2016-08-08
7516286
Relation between functional magnetic resonance imaging (fMRI) and single neuron, local field potential (LFP) and electrocorticography (ECoG) activity in human cortex
The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on the published literature including findings from the authors' laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the “default” network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships. Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR) and NIH grant NS065186 (JO)
15082296
Localization of brain electrical activity via linearly constrained minimum variance spatial filtering
A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach.
59748028
MEG. An introduction to methods
Magnetoencephalography (MEG) is an exciting brain imaging technology that allows real-time tracking of neural activity, making it an invaluable tool for advancing our understanding of brain function. In this comprehensive introduction to MEG, Peter Hansen, Morten Kringelbach, and Riitta Salmelin have brought together the leading researchers to provide the basic tools for planning and executing MEG experiments, as well as analyzing and interpreting the resulting data. Chapters on the basics describe the fundamentals of MEG and its instrumentation, and provide guidelines for designing experiments and performing successful measurements. Chapters on data analysis present it in detail, from general concepts and assumptions to analysis of evoked responses and oscillatory background activity. Chapters on solutions propose potential solutions to the inverse problem using techniques such as minimum norm estimates, spatial filters and beamformers. Chapters on combinations elucidate how MEG can be used to complement other neuroimaging techniques. Chapters on applications provide practical examples of how to use MEG to study sensory processing and cognitive tasks, and how MEG can be used in a clinical setting. These chapters form a complete basic reference source for those interested in exploring or already using MEG that will hopefully inspire them to try to develop new, exciting approaches to designing and analyzing their own studies. This book will be a valuable resource for researchers from diverse fields, including neuroimaging, cognitive neuroscience, medical imaging, computer modelling, as well as for clinical practitioners.
151585
Neuronal Dynamics Underlying High- and Low-Frequency EEG Oscillations Contribute Independently to the Human BOLD Signal
Work on animals indicates that BOLD is preferentially sensitive to local field potentials, and that it correlates most strongly with gamma band neuronal synchronization. Here we investigate how the BOLD signal in humans performing a cognitive task is related to neuronal synchronization across different frequency bands. We simultaneously recorded EEG and BOLD while subjects engaged in a visual attention task known to induce sustained changes in neuronal synchronization across a wide range of frequencies. Trial-by-trial BOLD fluctuations correlated positively with trial-by-trial fluctuations in high-EEG gamma power (60-80 Hz) and negatively with alpha and beta power. Gamma power on the one hand, and alpha and beta power on the other hand, independently contributed to explaining BOLD variance. These results indicate that the BOLD-gamma coupling observed in animals can be extrapolated to humans performing a task and that neuronal dynamics underlying high- and low-frequency synchronization contribute independently to the BOLD signal.
5252772
Visual Grouping and the Focusing of Attention Induce Gamma-band Oscillations at Different Frequencies in Human Magnetoencephalogram Signals
Neural oscillatory synchrony could implement grouping processes, act as an attentional filter, or foster the storage of information in short-term memory. Do these findings indicate that oscillatory synchrony is an unspecific epiphenomenon occurring in any demanding task, or that oscillatory synchrony is a fundamental mechanism involved whenever neural cooperation is requested? If the latter hypothesis is true, then oscillatory synchrony should be specific, with distinct visual processes eliciting different types of oscillations. We recorded magnetoencephalogram (MEG) signals while manipulating the grouping properties of a visual display on the one hand, and the focusing of attention to memorize part of this display on the other hand. Grouping-related gamma oscillations were present in all conditions but modulated by the grouping properties of the stimulus (one or two groups) in the high gamma-band (70120 Hz) at central occipital locations. Attention-related gamma oscillations appeared as an additional component whenever attentional focusing was requested in the low gamma-band (4466 Hz) at parietal locations. Our results thus reveal the existence of a functional specialization in the gamma range, with grouping-related oscillations showing up at higher frequencies than attention-related oscillations. The pattern of oscillatory synchrony is thus specific of the visual process it is associated with. Our results further suggest that both grouping processes and focused attention rely on a common implementation process, namely, gamma-band oscillatory synchrony, a finding that could account for the fact that coherent percepts are more likely to catch attention than incoherent ones.
2924246
Attentional Stimulus Selection through Selective Synchronization between Monkey Visual Areas
A central motif in neuronal networks is convergence, linking several input neurons to one target neuron. In visual cortex, convergence renders target neurons responsive to complex stimuli. Yet, convergence typically sends multiple stimuli to a target, and the behaviorally relevant stimulus must be selected. We used two stimuli, activating separate electrocorticographic V1 sites, and both activating an electrocorticographic V4 site equally strongly. When one of those stimuli activated one V1 site, it gamma synchronized (60-80 Hz) to V4. When the two stimuli activated two V1 sites, primarily the relevant one gamma synchronized to V4. Frequency bands of gamma activities showed substantial overlap containing the band of interareal coherence. The relevant V1 site had its gamma peak frequency 2-3 Hz higher than the irrelevant V1 site and 4-6 Hz higher than V4. Gamma-mediated interareal influences were predominantly directed from V1 to V4. We propose that selective synchronization renders relevant input effective, thereby modulating effective connectivity.