Volumetric Display of Brain Function and Brain Anatomy

Author(s):  
D. J. Valentino ◽  
P. D. Cutler ◽  
J. C. Mazziotta ◽  
H. K. Huang ◽  
R. A. Drebin ◽  
...  
1988 ◽  
Author(s):  
D. J. Valentino ◽  
J. C. Mazziotta ◽  
H. K. Huang
Keyword(s):  

2021 ◽  
Author(s):  
Alessandra Griffa ◽  
Enrico Amico ◽  
Raphael Liegeois ◽  
Dimitri Van De Ville ◽  
Maria Giulia Preti

Brain signatures of functional activity have shown promising results in both decoding brain states; i.e., determining whether a subject is at rest or performing a given task, and fingerprinting, that is identifying individuals within a large group. Importantly, these brain signatures do not account for the underlying brain anatomy on which brain function takes place. Here, we leveraged brain structure-function coupling as a new imaging-based biomarker to characterize tasks and individuals. We used multimodal magnetic resonance imaging and the recently introduced Structural-Decoupling Index (SDI) to quantify regional structure-function interplay in 100 healthy volunteers from the Human Connectome Project, both during rest and seven different tasks. SDI allowed accurate classifications for both decoding and fingerprinting, outperforming functional signatures. Further, SDI profiles in resting-state correlated with individual cognitive traits. These results show that brain structure-function interplay contains unique information which provides a new class of signatures of brain organization and cognition.


2018 ◽  
Author(s):  
Alice Patania ◽  
Pierluigi Selvaggi ◽  
Mattia Veronese ◽  
Ottavia Dipasquale ◽  
Paul Expert ◽  
...  

AbstractUnderstanding how gene expression translates to and affects human behaviour is one of the ultimate aims of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to produce and analyze genes co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas, and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene-set and find that co-expression networks produced by Mapper returned a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that topological network descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenge.


F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 805 ◽  
Author(s):  
Lutz Jäncke

In this mini-review, I summarize and interpret the current status of sex/gender differences in terms of brain anatomy, brain function, behavior, and cognition. Based on this review and the reported findings, I conclude that most of these sex/gender differences are not large enough to support the assumption of sexual dimorphism in terms of brain anatomy, brain function, cognition, and behavior. Instead, I suggest that many brain and cognitive features are modulated by environment, culture, and practice (and several other influences). These influences interact with the menstrual cycle, the general hormone level, and current gender stereotypes in a way that has not yet been fully understood.


2005 ◽  
Vol 360 (1457) ◽  
pp. 1043-1050 ◽  
Author(s):  
P. A Robinson ◽  
C. J Rennie ◽  
D. L Rowe ◽  
S. C O'Connor ◽  
E Gordon

A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained.


2019 ◽  
Vol 3 (3) ◽  
pp. 744-762 ◽  
Author(s):  
Alice Patania ◽  
Pierluigi Selvaggi ◽  
Mattia Veronese ◽  
Ottavia Dipasquale ◽  
Paul Expert ◽  
...  

Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.


2009 ◽  
Vol 80 (2) ◽  
pp. 256-259 ◽  
Author(s):  
David Bartrés-Faz ◽  
Cristina Solé-Padullés ◽  
Carme Junqué ◽  
Lorena Rami ◽  
Beatriz Bosch ◽  
...  

2020 ◽  
Vol 43 ◽  
Author(s):  
Martina G. Vilas ◽  
Lucia Melloni

Abstract To become a unifying theory of brain function, predictive processing (PP) must accommodate its rich representational diversity. Gilead et al. claim such diversity requires a multi-process theory, and thus is out of reach for PP, which postulates a universal canonical computation. We contend this argument and instead propose that PP fails to account for the experiential level of representations.


Author(s):  
C. S. Potter ◽  
C. D. Gregory ◽  
H. D. Morris ◽  
Z.-P. Liang ◽  
P. C. Lauterbur

Over the past few years, several laboratories have demonstrated that changes in local neuronal activity associated with human brain function can be detected by magnetic resonance imaging and spectroscopy. Using these methods, the effects of sensory and motor stimulation have been observed and cognitive studies have begun. These new methods promise to make possible even more rapid and extensive studies of brain organization and responses than those now in use, such as positron emission tomography.Human brain studies are enormously complex. Signal changes on the order of a few percent must be detected against the background of the complex 3D anatomy of the human brain. Today, most functional MR experiments are performed using several 2D slice images acquired at each time step or stimulation condition of the experimental protocol. It is generally believed that true 3D experiments must be performed for many cognitive experiments. To provide adequate resolution, this requires that data must be acquired faster and/or more efficiently to support 3D functional analysis.


2005 ◽  
Vol 38 (24) ◽  
pp. 18
Author(s):  
MARY ELLEN SCHNEIDER
Keyword(s):  

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