Anosognosia for hemiplegia as a tripartite disconnection syndrome

© 2019 Pacella et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.The syndrome of Anosognosia for Hemiplegia (AHP) can provide unique insights into the neurocognitive processes of motor awareness. Yet, prior studies have only explored predominately discreet lesions. Using advanced structural neuroimaging methods in 174 patients with a right-hemisphere stroke, we were able to identify three neural systems that contribute to AHP, when disconnected or directly damaged: the (i) premotor loop (ii) limbic system, and (iii) ventral attentional network. Our results suggest that human motor awareness is contingent on the joint contribution of these three systems.Peer reviewedFinal Published versio

The subcortical and neurochemical organization of the Ventral and Dorsal Attention Networks

Attention is a core cognitive function that filters and selects behaviourally relevant information in the environment. The cortical mapping of attentional systems identified two segregated networks that mediate stimulus-driven and goal-driven processes, the Ventral and the Dorsal Attention Networks (VAN, DAN). Deep brain electrophysiological recordings, behavioral data from phylogenetic distant species, and observations from human brain pathologies challenge purely corticocentric models. Here, we used advanced methods of functional alignment applied to resting-state functional connectivity analyses to map the subcortical architecture of the Ventral and Dorsal Attention Networks. Our investigations revealed the involvement of the pulvinar, the superior colliculi, the head of caudate nuclei, and a cluster of brainstem nuclei relevant to both networks. These nuclei are densely connected structural network hubs, as revealed by diffusion-weighted imaging tractography. Their projections establish interrelations with the acetylcholine nicotinic receptor as well as dopamine and serotonin transporters, as demonstrated in a spatial correlation analysis with a normative atlas of neurotransmitter systems. This convergence of functional, structural, and neurochemical evidence provides a comprehensive framework to understand the neural basis of attention across different species and brain diseases

Post-stroke deficit prediction from lesion and indirect structural and functional disconnection

Behavioural deficits in stroke reflect both structural damage at the site of injury, and widespread network dysfunction caused by structural, functional, and metabolic disconnection. Two recent methods allow for the estimation of structural and functional disconnection from clinical structural imaging. This is achieved by embedding a patient's lesion into an atlas of functional and structural connections in healthy subjects, and deriving the ensemble of structural and functional connections that pass through the lesion, thus indirectly estimating its impact on the whole brain connectome. This indirect assessment of network dysfunction is more readily available than direct measures of functional and structural connectivity obtained with functional and diffusion MRI, respectively, and it is in theory applicable to a wide variety of disorders. To validate the clinical relevance of these methods, we quantified the prediction of behavioural deficits in a prospective cohort of 132 first-time stroke patients studied at 2 weeks post-injury (mean age 52.8 years, range 22-77; 63 females; 64 right hemispheres). Specifically, we used multivariate ridge regression to relate deficits in multiple functional domains (left and right visual, left and right motor, language, spatial attention, spatial and verbal memory) with the pattern of lesion and indirect structural or functional disconnection. In a subgroup of patients, we also measured direct alterations of functional connectivity with resting-state functional MRI. Both lesion and indirect structural disconnection maps were predictive of behavioural impairment in all domains (0.16 < R2 < 0.58) except for verbal memory (0.05 < R2 < 0.06). Prediction from indirect functional disconnection was scarce or negligible (0.01 < R2 < 0.18) except for the right visual field deficits (R2 = 0.38), even though multivariate maps were anatomically plausible in all domains. Prediction from direct measures of functional MRI functional connectivity in a subset of patients was clearly superior to indirect functional disconnection. In conclusion, the indirect estimation of structural connectivity damage successfully predicted behavioural deficits post-stroke to a level comparable to lesion information. However, indirect estimation of functional disconnection did not predict behavioural deficits, nor was a substitute for direct functional connectivity measurements, especially for cognitive disorders

White matter microstructure of attentional networks predicts attention and consciousness functional interactions

Attention is considered as one of the pre-requisites of conscious perception. Phasic alerting and exogenous orienting improve conscious perception of near-threshold information through segregated brain networks. Using a multimodal neuroimaging approach, combining data from functional MRI (fMRI) and diffusion-weighted imaging (DWI), we investigated the influence of white matter properties of the ventral branch of superior longitudinal fasciculus (SLF III) in functional interactions between attentional systems and conscious perception. Results revealed that (1) reduced integrity of the left hemisphere SLF III was predictive of the neural interactions observed between exogenous orienting and conscious perception, and (2) increased integrity of the left hemisphere SLF III was predictive of the neural interactions observed between phasic alerting and conscious perception. Our results combining fMRI and DWI data demonstrate that structural properties of the white matter organization determine attentional modulations over conscious perception.ABC was supported by a Ramón y Cajal fellowship (RYC-2011-09320) and research project PSI2014-58681-P from the Spanish Ministry of Economy and Competitiveness (MINECO). PMP-A was supported by a Ramón y Cajal fellowship (RYC-2014-15440), and grants PSI2015-65696 and SEV-2015-049 from the MINECO. MTdS received funding from the ‘Agence Nationale de la Recherche’ (Grant number ANR-13-JSV4-0001-01) and “Investissements d’avenir” ANR-10-IAIHU-06. PB received funding from the ‘Agence Nationale de la Recherche’ (Grant number R16139DD)

The impact of early and late literacy on the functional connectivity of vision and

Introduction: Learning to read leads to functional and structural changes in the cortical regions related to vision and language. The visual word-form area (VWFA) is though to play a key role in the interaction between these two systems (Dehaene et al. 2015). For instance, the VWFA is activated not only from bottom-up during reading but also in a top-down manner during speech listening without visual stimulation (Dehaene et al. 2010). The objective of this study was twofolded: how literacy acquisition affects four intrinsic functional connectivity networks related to vision and language (a dorsal language [DLN], a bilateral auditory [AN], a low-level [LLVN] and a high-level visual [HLVN] networks); and to explore the role of the VWFA as an interface between high-level vision and language functions. Methods: Independent component analysis (ICA) was applied to functional magnetic resonance imaging data from 40 adult participants with variable levels of literacy (illiterate, late literate and early literate). The four functional connectivity networks were compared across groups using dual-regression (Filippini et al. 2009). In addition, we directly explored the functional connectivity between the VWFA and each of the studied networks. Finally, the strengh of connectivity between the VWFA and each network was compared across groups and correlated with individual reading fluency scores. Results: ICA produced 40 networks, and spatial crosscorrelation was used to identify the four networks of interest. Literacy was positively correlated with increased connectivity within the four networks. A major difference separating early literate from illiterate and late literate subjects was found. The connectivity between the VWFA and the DLN increased with literacy. Conversely, the strength of connectivity between the VWFA and the HLVN correlated negatively with literacy. Finally, , the HLVN-VWFA connectivity was negatively correlated with reading scores while the connectivity between the DLN-VWFA was positively correlated with reading scores. Discussion:Literacy has a strong influence on the visual and language functional networks. Literacy modifies the VWFA connectivity, by making it functionally closer to the language system, and more distinct from other associative visual areas that do not contribute to the reading process. The current results suggest that early acquisition of literacy plays a critical role for the tuning of the functional brain architecture. References: -Dehaene S et al. Nat Rev Neurosci.(2015)16:234 244 -Dehaene S et al. Science.(2010)330:1359–1364 -Filippini N et al. PNAS.(2009)106, 7209–7214Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Compressed representation of brain genetic transcription

The architecture of the brain is too complex to be intuitively surveyable without the use of compressed representations that project its variation into a compact, navigable space. The task is especially challenging with high-dimensional data, such as gene expression, where the joint complexity of anatomical and transcriptional patterns demands maximum compression. Established practice is to use standard principal component analysis (PCA), whose computational felicity is offset by limited expressivity, especially at great compression ratios. Employing whole-brain, voxel-wise Allen Brain Atlas transcription data, here we systematically compare compressed representations based on the most widely supported linear and non-linear methods-PCA, kernel PCA, non-negative matrix factorization (NMF), t-stochastic neighbour embedding (t-SNE), uniform manifold approximation and projection (UMAP), and deep auto-encoding-quantifying reconstruction fidelity, anatomical coherence, and predictive utility with respect to signalling, microstructural, and metabolic targets. We show that deep auto-encoders yield superior representations across all metrics of performance and target domains, supporting their use as the reference standard for representing transcription patterns in the human brain.Comment: 21 pages, 5 main figures, 1 supplementary figur

A framework for focal and connectomic mapping of transiently disrupted brain function

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective anatomical information with focal disruption of function are needed to disambiguate local from global neural dependence, and critical from merely coincidental activity. Here we present a comprehensive framework for focal and connective spatial inference based on sparse disruptive data, and demonstrate its application in the context of transient direct electrical stimulation of the human medial frontal wall during the pre-surgical evaluation of patients with focal epilepsy. Our framework formalizes voxel-wise mass-univariate inference on sparsely sampled data within the statistical parametric mapping framework, encompassing the analysis of distributed maps defined by any criterion of connectivity. Applied to the medial frontal wall, this transient dysconnectome approach reveals marked discrepancies between local and distributed associations of major categories of motor and sensory behaviour, revealing differentiation by remote connectivity to which purely local analysis is blind. Our framework enables disruptive mapping of the human brain based on sparsely sampled data with minimal spatial assumptions, good statistical efficiency, flexible model formulation, and explicit comparison of local and distributed effects

Spatial attention: differential shifts in pseudoneglect direction with time-on-task and initial bias support the idea of observer subtypes

&lt;p&gt;Asymmetry in human spatial attention has long been documented. In the general population the majority of individuals tend to misbisect horizontal lines to the left of veridical centre. Nonetheless in virtually all previously reported studies on healthy participants, there have been subsets of people displaying rightward biases.&lt;/p&gt; &lt;p&gt;In this study, we report differential time-on task effects depending on participants' initial pseudoneglect bias: participants with an initial left bias in a landmark task (in which they had to judge whether a transection mark appeared closer to the right or left end of a line) showed a significant rightward shift over the course of the experimental session, whereas participants with an initial right bias shifted leftwards.&lt;/p&gt; &lt;p&gt;We argue that these differences in initial biases as well as the differential shifts with time-on task reflect genuine observer subtypes displaying diverging behavioural patterns. These observer subtypes could be driven by differences in brain organisation and/or lateralisation such as varying anatomical pathway asymmetries. &lt;/p&gt