25 research outputs found
Neural Correlate of Filtering of Irrelevant Information from Visual Working Memory
In a dynamic environment stimulus task relevancy could be altered through time and it is not always possible to dissociate relevant and irrelevant objects from the very first moment they come to our sight. In such conditions, subjects need to retain maximum possible information in their WM until it is clear which items should be eliminated from WM to free attention and memory resources. Here, we examined the neural basis of irrelevant information filtering from WM by recording human ERP during a visual change detection task in which the stimulus irrelevancy was revealed in a later stage of the task forcing the subjects to keep all of the information in WM until test object set was presented. Assessing subjects' behaviour we found that subjects' RT was highly correlated with the number of irrelevant objects and not the relevant one, pointing to the notion that filtering, and not selection, process was used to handle the distracting effect of irrelevant objects. In addition we found that frontal N150 and parietal N200 peak latencies increased systematically as the amount of irrelevancy load increased. Interestingly, the peak latency of parietal N200, and not frontal N150, better correlated with subjects' RT. The difference between frontal N150 and parietal N200 peak latencies varied with the amount of irrelevancy load suggesting that functional connectivity between modules underlying fronto-parietal potentials vary concomitant with the irrelevancy load. These findings suggest the existence of two neural modules, responsible for irrelevant objects elimination, whose activity latency and functional connectivity depend on the number of irrelevant object
Noţiuni de conectivitate şi rezultatele studiilor de conectivitate în epilepsie
Căile din creierul nostru sunt reţele de comunicare și starea lor fi zică infl uenţează efi cienţa comunicaţiei și, respectiv, manifestarea comportamentală. Schimbările din
structura substanţei albe, datorită proceselor de plasticitate și adaptare la factorii extrinseci și intrinseci, pot amplifi ca sau pot diminua efi cienţa comunicării, determinând modificări comportamentale. Descărcările epileptice cu certitudine
provoacă și, de asemenea, determină schimbările secundare din aceste reţele de comunicare, cu reorganizare funcţională și structurală. Studiile recente atestă schimbări ale conectivităţii structurale în regiunile epileptogenice și ariile interconectate. Reţelele talamocorticale ar putea juca un rol important în cadrul acestei interacţiuni. Articolul dat prezintă o revizuire a studiilor recente de conectivitate în epilepsii. Sunt prezentate problemele de conectivitate structurală și funcţională
Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning
BACKGROUND: Neural substrates underlying motor learning have been widely investigated with neuroimaging technologies. Investigations have illustrated the critical regions of motor learning and further revealed parallel alterations of functional activation during imagination and execution after learning. However, little is known about the functional connectivity associated with motor learning, especially motor imagery learning, although benefits from functional connectivity analysis attract more attention to the related explorations. We explored whether motor imagery (MI) and motor execution (ME) shared parallel alterations of functional connectivity after MI learning. METHODOLOGY/PRINCIPAL FINDINGS: Graph theory analysis, which is widely used in functional connectivity exploration, was performed on the functional magnetic resonance imaging (fMRI) data of MI and ME tasks before and after 14 days of consecutive MI learning. The control group had no learning. Two measures, connectivity degree and interregional connectivity, were calculated and further assessed at a statistical level. Two interesting results were obtained: (1) The connectivity degree of the right posterior parietal lobe decreased in both MI and ME tasks after MI learning in the experimental group; (2) The parallel alterations of interregional connectivity related to the right posterior parietal lobe occurred in the supplementary motor area for both tasks. CONCLUSIONS/SIGNIFICANCE: These computational results may provide the following insights: (1) The establishment of motor schema through MI learning may induce the significant decrease of connectivity degree in the posterior parietal lobe; (2) The decreased interregional connectivity between the supplementary motor area and the right posterior parietal lobe in post-test implicates the dissociation between motor learning and task performing. These findings and explanations further revealed the neural substrates underpinning MI learning and supported that the potential value of MI learning in motor function rehabilitation and motor skill learning deserves more attention and further investigation
FMRI Effective Connectivity and TMS Chronometry: Complementary Accounts of Causality in the Visuospatial Judgment Network
BACKGROUND: While traditionally quite distinct, functional neuroimaging (e.g. functional magnetic resonance imaging: fMRI) and functional interference techniques (e.g. transcranial magnetic stimulation: TMS) increasingly address similar questions of functional brain organization, including connectivity, interactions, and causality in the brain. Time-resolved TMS over multiple brain network nodes can elucidate the relative timings of functional relevance for behavior ("TMS chronometry"), while fMRI functional or effective connectivity (fMRI EC) can map task-specific interactions between brain regions based on the interrelation of measured signals. The current study empirically assessed the relation between these different methods. METHODOLOGY/PRINCIPAL FINDINGS: One group of 15 participants took part in two experiments: one fMRI EC study, and one TMS chronometry study, both of which used an established cognitive paradigm involving one visuospatial judgment task and one color judgment control task. Granger causality mapping (GCM), a data-driven variant of fMRI EC analysis, revealed a frontal-to-parietal flow of information, from inferior/middle frontal gyrus (MFG) to posterior parietal cortex (PPC). FMRI EC-guided Neuronavigated TMS had behavioral effects when applied to both PPC and to MFG, but the temporal pattern of these effects was similar for both stimulation sites. At first glance, this would seem in contradiction to the fMRI EC results. However, we discuss how TMS chronometry and fMRI EC are conceptually different and show how they can be complementary and mutually constraining, rather than contradictory, on the basis of our data. CONCLUSIONS/SIGNIFICANCE: The findings that fMRI EC could successfully localize functionally relevant TMS target regions on the single subject level, and conversely, that TMS confirmed an fMRI EC identified functional network to be behaviorally relevant, have important methodological and theoretical implications. Our results, in combination with data from earlier studies by our group (Sack et al., 2007, Cerebral Cortex), lead to informed speculations on complex brain mechanisms, and TMS disruption thereof, underlying visuospatial judgment. This first in-depth empirical and conceptual comparison of fMRI EC and TMS chronometry thereby shows the complementary insights offered by the two methods
Computational Inference of Neural Information Flow Networks
Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks
Contribution of Exploratory Methods to the Investigation of Extended Large-Scale Brain Networks in Functional MRI: Methodologies, Results, and Challenges
A large-scale brain network can be defined as a set of segregated and integrated
regions, that is, distant regions that share strong anatomical connections
and functional interactions. Data-driven investigation of such networks has
recently received a great deal of attention in blood-oxygen-level-dependent
(BOLD) functional magnetic resonance imaging (fMRI). We here review the
rationale for such an investigation, the methods used, the results obtained,
and also discuss some issues that have to be faced for an efficient exploration
Autism: a world changing too fast for a mis-wired brain ?
International audienceDisorders in verbal and emotional communication and imitation, social reciprocity and higher order cognition observed in individuals with autism spectrum disorders (ASD) are presented here as phenotypic expressions of temporo-spatial processing disorders (TSPDs). TSPDs include various degrees of disability in (i) processing multi-sensory dynamic stimuli online, (ii) associating them into meaningful and coherent patterns and (iii) producing real-time sensory-motor adjustments and motor outputs. In line with this theory, we found that slowing down the speed opf facial and vocal events enhanced imitative, verbal and cognitive abilities in some ASD children, particularly those with low functioning autism. We then argue that TSPDs may result from Multi-system Brain Disconnectivity-Dissynchrony (MBD), defined as an increase or decrease in functional connectivity and neuronal synchronization within/between multiple neurofunctional territories and pathways. Recent functional magnetic resonance imaging (fMRI) and electrophysiological studies supporting MBD are outlined. Finally, we review the suspected underlying neurobiological mechanisms of MBD as evidenced in neuroimaging, genetic, environmental and epigenetic studies. Overall, our TSPD/MBD approach to ASD may open new promising avenues for a better understanding of neuro-physio-psychopathology of ASD and clinical rehabilitation of people affected by these syndromes
Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System
A new method is presented for extraction of population firing-rate models for
both thalamocortical and intracortical signal transfer based on stimulus-evoked
data from simultaneous thalamic single-electrode and cortical recordings using
linear (laminar) multielectrodes in the rat barrel system. Time-dependent
population firing rates for granular (layer 4), supragranular (layer 2/3), and
infragranular (layer 5) populations in a barrel column and the thalamic
population in the homologous barreloid are extracted from the high-frequency
portion (multi-unit activity; MUA) of the recorded extracellular signals. These
extracted firing rates are in turn used to identify population firing-rate
models formulated as integral equations with exponentially decaying coupling
kernels, allowing for straightforward transformation to the more common
firing-rate formulation in terms of differential equations. Optimal model
structures and model parameters are identified by minimizing the deviation
between model firing rates and the experimentally extracted population firing
rates. For the thalamocortical transfer, the experimental data favor a model
with fast feedforward excitation from thalamus to the layer-4 laminar population
combined with a slower inhibitory process due to feedforward and/or recurrent
connections and mixed linear-parabolic activation functions. The extracted
firing rates of the various cortical laminar populations are found to exhibit
strong temporal correlations for the present experimental paradigm, and simple
feedforward population firing-rate models combined with linear or mixed
linear-parabolic activation function are found to provide excellent fits to the
data. The identified thalamocortical and intracortical network models are thus
found to be qualitatively very different. While the thalamocortical circuit is
optimally stimulated by rapid changes in the thalamic firing rate, the
intracortical circuits are low-pass and respond most strongly to slowly varying
inputs from the cortical layer-4 population