Intertrial Variability in the Premotor Cortex Accounts for Individual Differences in Peripersonal Space

We live in a dynamic environment, constantly confronted with approaching objects that we may either avoid or be forced to address. A multisensory and sensorimotor interface, the peripersonal space (PPS), mediates every physical interaction between our body and the environment. Behavioral investigations show high variability in the extension of PPS across individuals, but there is a lack of evidence on the neural underpinnings of these large individual differences. Here, we used approaching auditory stimuli and fMRI to capture the individual boundary of PPS and examine its neural underpinnings. Precisely, we tested the hypothesis that intertrial variability (ITV) in brain regions coding PPS predicts individual differences of its boundary at the behavioral level. Selectively in the premotor cortex, we found that ITV, rather than trial-averaged amplitude, of BOLD responses to far rather than near dynamic stimuli predicts the individual extension of PPS. Our results provide the first empirical support for the relevance of ITV of brain responses for individual differences in human behavior

Large-scale brain networks account for sustained and transient activity during target detection.

Target detection paradigms have been widely applied in the study of human cognitive functions, particularly those associated with arousal, attention, stimulus processing and memory. In EEG recordings, the detection of task-relevant stimuli elicits the P300 component, a transient response with latency around 300 ms. The P300 response has been shown to be affected by the amount of mental effort and learning, as well as habituation. Furthermore, trial-by-trial variability of the P300 component has been associated with inter-stimulus interval, target-to-target interval or target probability; however, understanding the mechanisms underlying this variability is still an open question. In order to investigate whether it could be related to the distinct cortical networks in which coherent intrinsic activity is organized, and to understand the contribution of those networks to target detection processes, we carried out a simultaneous EEG-fMRI study, collecting data from 13 healthy subjects during a visual oddball task. We identified five large-scale networks, that largely overlap with the dorsal attention, the ventral attention, the core, the visual and the sensory-motor networks. Since the P300 component has been consistently associated with target detection, we concentrated on the first two brain networks, the time-course of which showed a modulation with the P300 response as detected in simultaneous EEG recordings. A trial-by-trial EEG-fMRI correlation approach revealed that they are involved in target detection with different functional roles: the ventral attention network, dedicated to revealing salient stimuli, was transiently activated by the occurrence of targets; the dorsal attention network, usually engaged during voluntary orienting, reflected sustained activity, possibly related to search for targets

Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis.

The simultaneous recording of EEG and fMRI is a promising method for combining the electrophysiological and hemodynamic information on cerebral dynamics. However, EEG recordings performed in the MRI scanner are contaminated by imaging, ballistocardiographic (BCG) and ocular artifacts. A number of processing techniques for the cancellation of fMRI environment disturbances exist: the most popular is averaged artifact subtraction (AAS), which performs well for the imaging artifact, but has some limitations in removing the BCG artifact, due to the variability in cardiac wave duration and shape; furthermore, no processing method to attenuate ocular artifact is currently used in EEG/fMRI, and contaminated epochs are simply rejected before signal analysis. In this work, we present a comprehensive method based on independent component analysis (ICA) for simultaneously removing BCG and ocular artifacts from the EEG recordings, as well as residual MRI contamination left by AAS. The ICA method has been tested on event-related potentials (ERPs) obtained from a visual oddball paradigm: it is very effective in attenuating artifacts in order to reconstruct clear brain signals from EEG acquired in the MRI scanner. It performs significantly better than the AAS method in removing the BCG artifact. Furthermore, since ocular artifacts can be completely suppressed, a larger number of trials is available for analysis. A comparison of ERPs inside the magnetic environment with those obtained out of the MRI scanner confirms that no systematic bias in the ERP waveform is produced by the ICA method

Common and unique neuro-functional basis of induction, visualization, and spatial relationships as cognitive components of fluid intelligence.

Neuroimaging research of fluid intelligence (Gf) has mainly focused on the neural basis of abilities explaining performance on cognitive tasks. However, the neuro-functional basis of clearly defined theoretical cognitive components underlying Gf remains unclear. Induction, visualization, and spatial relationships have the highest relevance for Gf (Carroll, 1993). Here we report a functional magnetic resonance imaging (fMRI) study exploring the neural correlates of these abilities characterized by their unidimensionality and matched for task-difficulty, as evidenced by a psychometric calibration study. Twenty-two healthy young adult females, recruited from a large sample of 300 participants, with either below- or above-average Gf abilities underwent fMRI scanning during Gf task performance. The results reveal that these tasks activate a shared frontoparietal network. Specific activations were also observed, in particular for induction and visualization. The key findings suggest that Gf comprises distinguishable cognitive abilities, but the Gf construct is associated with a common network

Long-range functional interactions of anterior insula and medial frontal cortex are differently modulated by visuospatial and inductive reasoning tasks.

The brain is organized into functionally specific networks as characterized by intrinsic functional relationships within discrete sets of brain regions. However, it is poorly understood whether such functional networks are dynamically organized according to specific task-states. The anterior insular cortex (aIC)-dorsal anterior cingulate cortex (dACC)/medial frontal cortex (mFC) network has been proposed to play a central role in human cognitive abilities. The present functional magnetic resonance imaging (fMRI) study aimed at testing whether functional interactions of the aIC-dACC/mFC network in terms of temporally correlated patterns of neural activity across brain regions are dynamically modulated by transitory, ongoing task demands. For this purpose, functional interactions of the aIC-dACC/mFC network are compared during two distinguishable fluid reasoning tasks, Visualization and Induction. The results show an increased functional coupling of bilateral aIC with visual cortices in the occipital lobe during the Visualization task, whereas coupling of mFC with right anterior frontal cortex was enhanced during the Induction task. These task-specific modulations of functional interactions likely reflect ability related neural processing. Furthermore, functional connectivity strength between right aIC and right dACC/mFC reliably predicts general task performance. The findings suggest that the analysis of long-range functional interactions may provide complementary information about brain-behavior relationships. On the basis of our results, it is proposed that the aIC-dACC/mFC network contributes to the integration of task-common and task-specific information based on its within-network as well as its between-network dynamic functional interactions

Common and unique neuro-functional basis of induction, visualization, and spatial relationships as cognitive components of fluid intelligence.

Neuroimaging research of fluid intelligence (Gf) has mainly focused on the neural basis of abilities explaining performance on cognitive tasks. However, the neuro-functional basis of clearly defined theoretical cognitive components underlying Gf remains unclear. Induction, visualization, and spatial relationships have the highest relevance for Gf (Carroll, 1993). Here we report a functional magnetic resonance imaging (fMRI) study exploring the neural correlates of these abilities characterized by their unidimensionality and matched for task-difficulty, as evidenced by a psychometric calibration study. Twenty-two healthy young adult females, recruited from a large sample of 300 participants, with either below- or above-average Gf abilities underwent fMRI scanning during Gf task performance. The results reveal that these tasks activate a shared frontoparietal network. Specific activations were also observed, in particular for induction and visualization. The key findings suggest that Gf comprises distinguishable cognitive abilities, but the Gf construct is associated with a common network

Interspecies activity correlations reveal functional correspondences between monkey and human brain areas

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. For cases in which functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assessed similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by temporal correlation. Using natural vision data, we revealed regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models.status: publishe