The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge.

Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.

Cortical mapping of callosal connections in healthy young adults.

The corpus callosum (CC) is the principal white matter bundle supporting communication between the two brain hemispheres. Despite its importance, a comprehensive mapping of callosal connections is still lacking. Here, we constructed the first bidirectional population-based callosal connectional atlas between the midsagittal section of the CC and the cerebral cortex of the human brain by means of diffusion-weighted imaging tractography. The estimated connectional topographic maps within this atlas have the most fine-grained spatial resolution, demonstrate histological validity, and were reproducible in two independent samples. This new resource, a complete and comprehensive atlas, will facilitate the investigation of interhemispheric communication and come with a user-friendly companion online tool (CCmapping) for easy access and visualization of the atlas.

Three-dimensional neuronavigation in SEEG-guided epilepsy surgery.

OBJECTIVES: Epilepsy surgery is mainly cortical surgery and the precise definition of the epileptogenic zone on the complex cortical surface is of paramount importance. Stereoelectroencephalography (SEEG) may delineate the epileptogenic zone even in cases of non-lesional epilepsy. The aim of our study was to present a technique of 3D neuronavigation based on the brain surface and SEEG electrodes reconstructions using FSL and 3DSlicer software. PATIENTS AND METHODS: Our study included 26 consecutive patients operated on for drug-resistant epilepsy after SEEG exploration between January 2015 and December 2017. All patients underwent 1.5 T pre-SEEG MRI, post-SEEG CT, DICOM data post-processing using FSL and 3DSlicer, preoperative planning on 3DSlicer, and intraoperative 3D neuronavigation. Accuracy and precision of 3D SEEG reconstruction and 3D neuronavigation was assessed. RESULTS: We identified 125 entry points of SEEG electrodes during 26 operations. The accuracy of 3D reconstruction was 0.8 mm (range, 0-2 mm) with a precision of 1.5 mm. The accuracy of 3D SEEG neuronavigation was 2.68 mm (range, 0-6 mm). The precision of 3D neuronavigation was 1.48 mm. CONCLUSION: 3D neuronavigation for SEEG-guided epilepsy surgery using free software for post-processing of common MRI sequences is possible and a reliable method even with navigation systems without a brain extraction tool.

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence.

BACKGROUND: During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described. METHODS: The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults. RESULTS: Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults. CONCLUSION: Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Effects of combined anodal transcranial direct current stimulation and motor control exercise on cortical topography and muscle activation in individuals with chronic low back pain: A randomized controlled study.

BACKGROUND: Aberrant movement in chronic low back pain (CLBP) is associated with a deficit in the lumbar multifidus (LM) and changes in cortical topography. Anodal transcranial direct current stimulation (a-tDCS) can be used to enhance cortical excitability by priming the neuromuscular system for motor control exercise (MCE), thereby enhancing LM activation and movement control. This study aimed to determine the effects of a 6-week MCE program combined with a-tDCS on cortical topography, LM activation, movement patterns, and clinical outcomes in individuals with CLBP. METHODS: Twenty-two individuals with CLBP were randomly allocated to the a-tDCS group (a-tDCS; n = 12) or sham-tDCS group (s-tDCS; n = 10). Both groups received 20 min of tDCS followed by 30 min of MCE. The LM and erector spinae (ES) cortical topography, LM activation, movement control battery tests, and clinical outcomes (disability and quality of life) were measured pre- and post-intervention. RESULTS: Significant interaction (group × time; p < 0.01) was found in the distance between LM and ES cortical locations. The a-tDCS group demonstrated significantly fewer discrete peaks (p < 0.05) in both ES and LM and significant improvements (p < 0.05) in clinical outcomes post-intervention. The s-tDCS group demonstrated a significant increase (p < 0.05) in the number of discrete peaks in the LM cortical topography. No significant changes (p > 0.05) in LM activation were observed in either group; however, both groups demonstrated improved movement patterns. DISCUSSION: Our findings suggest that combined a-tDCS with MCE can separate LM and ES locations over time while s-tDCS (MCE alone) reduces the distance. Our study did not find superior benefits of adding a-tDCS before MCE for LM activation, movement patterns, or clinical outcomes.

Semantic cognition versus numerical cognition: a topographical perspective.

Semantic cognition and numerical cognition are dissociable faculties with separable neural mechanisms. However, recent advances in the cortical topography of the temporal and parietal lobes have revealed a common organisational principle for the neural representations of semantics and numbers. We discuss their convergence and divergence through the prism of topography.

The neural basis of intelligence in fine-grained cortical topographies.

Intelligent thought is the product of efficient neural information processing, which is embedded in fine-grained, topographically organized population responses and supported by fine-grained patterns of connectivity among cortical fields. Previous work on the neural basis of intelligence, however, has focused on coarse-grained features of brain anatomy and function because cortical topographies are highly idiosyncratic at a finer scale, obscuring individual differences in fine-grained connectivity patterns. We used a computational algorithm, hyperalignment, to resolve these topographic idiosyncrasies and found that predictions of general intelligence based on fine-grained (vertex-by-vertex) connectivity patterns were markedly stronger than predictions based on coarse-grained (region-by-region) patterns. Intelligence was best predicted by fine-grained connectivity in the default and frontoparietal cortical systems, both of which are associated with self-generated thought. Previous work overlooked fine-grained architecture because existing methods could not resolve idiosyncratic topographies, preventing investigation where the keys to the neural basis of intelligence are more likely to be found.

Percolation theory for the recognition of patterns in topographic images of the cortical activity.

Electroencephalogram (EEG) is one of the mechanisms used to collect complex data. Its use includes evaluating neurological disorders, investigating brain function and correlations between EEG signals and real or imagined movements. The Topographic Image of Cortical Activity (TICA) records obtained by the EEG make it possible to observe, through color discrimination, the cortical areas that represent greater or lesser activity. Percolation Theory (PT) reveals properties on the aspects of fluid spreading from a central point, these properties being related to the aspects of the medium, topological characteristics and ease of penetration of a fluid in materials. The hypothesis presented so far considers that synaptic activities originate in points and spread from them, causing different areas of the brain to interact in a diffusive associative behavior, generating electric and magnetic fields by the currents that spread through the brain tissue and have an effect on the scalp sensors. Brain areas spatially separated create large-scale dynamic networks that are described by functional and effective connectivity. The proposition is that this phenomenon behaves like a fluidic spreading, so we can use the PT, through the topological analysis we detect specific signatures related to neural phenomena that manifest changes in the behavior of synaptic diffusion. This signature must be characterized by the Fractal Dimension (FD) values of the scattering clusters, these values will be used as properties in the k-Nearest Neighbors (kNN) method, an TICA will be categorized according to the degree of similarity to the preexisting patterns. In this context, our hypothesis will consolidate as a more computational resource in the service of medicine and another way that opens with the possibility of analysis and detailed inferences of the brain through TICA that go beyond a simply visual observation, as it happens in the present day.

Gradients of connectivity distance in the cerebral cortex of the macaque monkey.

Cortical connectivity conforms to a series of organizing principles that are common across species. Spatial proximity, similar cortical type, and similar connectional profile all constitute factors for determining the connectivity between cortical regions. We previously demonstrated another principle of connectivity that is closely related to the spatial layout of the cerebral cortex. Using functional connectivity from resting-state fMRI in the human cortex, we found that the further a region is located from primary cortex, the more distant are its functional connections with the other areas of the cortex. However, it remains unknown whether this relationship between cortical layout and connectivity extends to other primate species. Here, we investigated this relationship using both resting-state functional connectivity as well as gold-standard tract-tracing connectivity in the macaque monkey cortex. For both measures of connectivity, we found a gradient of connectivity distance extending between primary and frontoparietal regions. In the human cortex, the further a region is located from primary areas, the stronger its connections to distant portions of the cortex, with connectivity distance highest in frontal and parietal regions. The similarity between the human and macaque findings provides evidence for a phylogenetically conserved relationship between the spatial layout of cortical areas and connectivity.

EEG topography during sleep inertia upon awakening after a period of increased homeostatic sleep pressure.

OBJECTIVE: Behavioral and physiological indexes of high sleep inertia (SI) characterize the awakening from recovery (REC) sleep after prolonged wakefulness, but the associated electroencephalogram (EEG) topography has never been investigated. Here, we compare the EEG topography following the awakening from baseline (BSL) and REC sleep. METHODS: We have recorded the EEG waking activity of 26 healthy subjects immediately after the awakening from BSL sleep and from REC sleep following 40 h of prolonged wakefulness. In both BSL and REC conditions, 12 subjects were awakened from stage 2 sleep, and 14 subjects from rapid eye movement (REM) sleep. The full-scalp waking EEG (eyes closed) was recorded after all awakenings. RESULTS: Subjects awakened from REC sleep showed a reduction of fronto-central alpha and beta-1 activities, while no significant effects of the sleep stage of awakening have been observed. Positive correlations between pre- and post-awakening EEG modifications following REC sleep have been found in the posterior and lateral cortices in the frequency ranges from theta to beta-2 and (only for REM awakenings) extending to the fronto-central regions in the beta-1 band, and in the midline central and parietal derivations for the alpha and delta bands, respectively. CONCLUSIONS: These findings suggest that the higher SI after REC sleep may be due to the fronto-central decrease of alpha and beta-1 activity and to the persistence of the sleep EEG features after awakening in the posterior, lateral, and fronto-central cortices, without influences of the sleep stage of awakening.