Complex networks in brain electrical activity

We analyze the complex networks associated with brain electrical activity. Multichannel EEG measurements are first processed to obtain 3D voxel activations using the tomographic algorithm LORETA. Then, the correlation of the current intensity activation between voxel pairs is computed to produce a voxel cross-correlation coefficient matrix. Using several correlation thresholds, the cross-correlation matrix is then transformed into a network connectivity matrix and analyzed. To study a specific example, we selected data from an earlier experiment focusing on the MMN brain wave. The resulting analysis highlights significant differences between the spatial activations associated with Standard and Deviant tones, with interesting physiological implications. When compared to random data networks, physiological networks are more connected, with longer links and shorter path lengths. Furthermore, as compared to the Deviant case, Standard data networks are more connected, with longer links and shorter path lengths--i.e., with a stronger ``small worlds'' character. The comparison between both networks shows that areas known to be activated in the MMN wave are connected. In particular, the analysis supports the idea that supra-temporal and inferior frontal data work together in the processing of the differences between sounds by highlighting an increased connectivity in the response to a novel sound.Comment: 22 pages, 5 figures. Starlab preprint. This version is an attempt to include better figures (no content change

Accessing forgotten memory traces from long-term memory via visual movements

Because memory retrieval often requires overt responses, it is difficult to determine to what extend forgetting occurs as a problem in explicit accessing of long-term memory traces. In this study, we used eye-tracking measures in combination with a behavioural task that favoured high forgetting rates to investigate the existence of memory traces from long-term memory in spite of failure in accessing them consciously. In 2 experiments, participants were encouraged to encode a large set of sound-picture56 location associations. In a later test, sounds were presented and participants were instructed to visually scan, before a verbal memory report, for the correct location of the associated pictures in an empty screen. We found the reactivation of associated memories by sound cues at test biased oculomotor behaviour towards locations congruent with memory representations, even when participants failed to consciously provide a memory report of it. These findings reveal the emergence of a memory-guided behaviour that can be used to map internal representations of forgotten memories from long-term memory

Amygdala Lesions Reduce Anxiety-like Behavior in a Human Benzodiazepine-Sensitive Approach-Avoidance Conflict Test

BACKGROUND: Rodent approach-avoidance conflict tests are common preclinical models of human anxiety disorder. Their translational validity mainly rests on the observation that anxiolytic drugs reduce rodent anxiety-like behavior. Here, we capitalized on a recently developed approach-avoidance conflict computer game to investigate the impact of benzodiazepines and of amygdala lesions on putative human anxiety-like behavior. In successive epochs of this game, participants collect monetary tokens on a spatial grid while under threat of virtual predation. METHODS: In a preregistered, randomized, double-blind, placebo-controlled trial, we tested the effect of a single dose (1 mg) of lorazepam (n = 59). We then compared 2 patients with bilateral amygdala lesions due to Urbach-Wiethe syndrome with age- and gender-matched control participants (n = 17). Based on a previous report, the primary outcome measure was the effect of intra-epoch time (i.e., an adaptation to increasing potential loss) on presence in the safe quadrant of the spatial grid. We hypothesized reduced loss adaptation in this measure under lorazepam and in patients with amygdala lesions. RESULTS: Lorazepam and amygdala lesions reduced loss adaptation in the primary outcome measure. We found similar results in several secondary outcome measures. The relative reduction of anxiety-like behavior in patients with amygdala lesions was qualitatively and quantitatively indistinguishable from an impact of anterior hippocampus lesions found in a previous report. CONCLUSIONS: Our results establish the translational validity of human approach-avoidance conflict tests in terms of anxiolytic drug action. We identified the amygdala, in addition to the hippocampus, as a critical structure in human anxiety-like behavior

ENOBIO - First tests of a dry electrophysiology electrode using carbon nanotubes

We describe the development and first tests of Enobio, a dry electrode sensor concept for biopotential applications. In the proposed electrodes, the tip of the electrode is covered with a forest of multi-walled CNTs that can be coated with Ag/AgCl to provide ionic-electronic transduction. The CNT brush-like structure is to penetrate the outer layers of the skin improving electrical contact as well as increae the contact surface area. In this paper, we report the results of the first tests of this concept -- immersion on saline solution and pig skin signal detection. These indicate performance on a par with state of the art research-oriented wet electrodes.Comment: Submitted and accepted at the 28th IEEE EMBS International Conference, New York City, August 31st-September 3rd, 2006. Figures updated with proper filtering and averagin

Population level inference for multivariate MEG analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions

Hippocampal Theta-Phase Modulation of Replay Correlates with Configural-Relational Short-Term Memory Performance

Thereis now growing evidencethatthe hippocampus generatestheta rhythmsthat can phase biasfast neural oscillationsinthe neocortex, allowing coordination of widespread fast oscillatory populations outside limbic areas. A recent magnetoencephalographic study showed that maintenance of configural-relational scene information in a delayed match-to-sample (DMS) task was associated with replay of that information during the delay period. The periodicity of the replay was coordinated by the phase of the ongoing theta rhythm, and the degree of theta coordination during the delay period was positively correlated with DMS performance. Here, we reanalyzed these data to investigate which brain regions were involved in generating the theta oscillations that coordinated the periodic replay of configural- relational information. We used a beamformer algorithm to produce estimates of regional theta rhythms and constructed volumetric images of the phase-locking between the local theta cycle and the instances of replay (in the 13- 80 Hz band). We found that individual differences in DMS performancefor configural-relational associations were relatedtothe degree of phase coupling of instances of cortical reactivations to theta oscillations generated in the right posterior hippocampus and the right inferior frontal gyrus. This demonstrates that the timing of memory reactivations in humans is biased toward hippocampal theta phas

A simultaneous modulation of reactive and proactive inhibition processes by anodal tDCS on the right inferior frontal cortex

Proactive and reactive inhibitory processes are a fundamental part of executive functions, allowing a person to stop inappropriate responses when necessary and to adjust performance in in a long term in accordance to the goals of a task. In the current study, we manipulate, in a single task, both reactive and proactive inhibition mechanisms, and we investigate the within-subjects effect of increasing, by means of anodal transcranial direct current stimulation (tDCS), the involvement of the right inferior frontal cortex (rIFC). Our results show a simultaneous enhancement of these two cognitive mechanisms when modulating the neural activity of rIFC. Thus, the application of anodal tDCS increased reaction times on Go trials, indicating a possible increase in proactive inhibition. Concurrently, the stop-signal reaction time, as a covert index of the inhibitory process, was reduced, demonstrating an improvement in reactive inhibition. In summary, the current pattern of results validates the engagement of the rIFC in these two forms of inhibitory processes, proactive and reactive inhibition and it provides evidence that both processes can operate concurrently in the brain

Theta-alpha oscillations bind the hippocampus, prefrontal cortex, and striatum during recollection: Evidence from simultaneous EEG-fMRI

Recollection of contextual information represents the core of human recognition memory. It has been associated with theta (4-8 Hz) power in electrophysiological recordings and, independently, with BOLD effects in a network including the hippocampus and frontal cortex. Although the notion of the hippocampus coordinating neocortical activity by synchronization in the theta range is common among theoretical models of recollection, direct evidence supporting this hypothesis is scarce. To address this apparent gap in our understanding of memory processes, we combined EEG and fMRI during a remember/know recognition task. We can show that recollection-specific theta-alpha (4-13Hz) effects are correlated with increases in hippocampal connectivity with the prefrontal cortex and, importantly, the striatum, areas that have repeatedly been linked to retrieval success. Taken together, our results provide compelling evidence that low frequency oscillations in the theta and alpha range provide a mechanism to functionally bind the hippocampus, prefrontal cortex and striatum during successful recollection

Individual differences in true and false memory retrieval are related to white matter brain microstructure

We sometimes vividly remember things that did not happen, a phenomenon with general relevance not only in the court-room. It is unclear, to what extent individual differences in false memories are driven by anatomical differences in memory relevant brain regions. Here we show in humans that microstructural properties of different white matter tracts as quantified using Diffusion Tensor Imaging (DTI) are strongly correlated with true and false memory recollection. To investigate these hypotheses we tested a large group of participants in a version of the Deese-Roediger-McDermott (DRM) paradigm (recall and recognition) and subsequently obtained DTI images. A voxel-based whole-brain level linear regression analysis was performed to relate fractional anisotropy to indices of true and false memory recall and recognition. True memory was correlated to diffusion anisotropy in the inferior longitudinal fascicle, the major connective pathway of the medial temporal lobe, whereas a greater proneness to retrieve false items was related to the superior longitudinal fascicle connecting fronto-parietal structures. Our results show that individual differences in white-matter micro-structure underlie true and false memory performance