Combining structural and functional neuroimaging data for studying brain connectivity: A review

2008 ◽  
Vol 45 (2) ◽  
pp. 173-187 ◽  
Author(s):  
Elena Rykhlevskaia ◽  
Gabriele Gratton ◽  
Monica Fabiani
2018 ◽  
Vol 2 ◽  
pp. 239821281775272 ◽  
Author(s):  
Nitin Williams ◽  
Richard N. Henson

Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.


2011 ◽  
Vol 26 (S2) ◽  
pp. 1149-1149
Author(s):  
U. Moser ◽  
M. Savli ◽  
R. Lanzenberger ◽  
S. Kasper

IntroductionDeep brain stimulation (DBS) is a promising therapy option for otherwise treatment-resistant neuropsychiatrie disorders, especially in obsessive-compulsive disorder (OCD), major depression (TRD) and Tourette's Syndrome (TS).ObjectiveThe brain coordinates of the DBS targets are mainly reported using measurements in original, unnormalized brains. In the neuroimaging community stereotactic data are mainly indicated in the standardized Montreal Neurological Institute (MNI) space, i.e. a three-dimensional proportional grid system.AimsImproved comparability between targets in DBS studies and molecular and functional neuroimaging data from PET, SPECT, MRI, fMRI, mostly published with stereotactic data.MethodsA comprehensive and systematic literature search for published DBS case reports or studies in TRD, OCD and TS was performed. We extracted the tip positions of electrode leads as provided in the publications or by the authors, and transferred individual coordinates to the standard brain in the MNI space.Results46 publications fulfilled the inclusion criteria. The main targets for the specific disorders and one or two examples of their calculated MNI coordinates are indicated in the table:[MNI coordinates of the main DBS targets]ConclusionsWe provide DBS data of neuropsychiatrie disorders in the MNI space, improving the comparability to molecular, functional and structural neuroimaging data.


2013 ◽  
Vol 25 (6) ◽  
pp. 834-842 ◽  
Author(s):  
Joseph M. Moran ◽  
Jamil Zaki

Functional imaging has become a primary tool in the study of human psychology but is not without its detractors. Although cognitive neuroscientists have made great strides in understanding the neural instantiation of countless cognitive processes, commentators have sometimes argued that functional imaging provides little or no utility for psychologists. And indeed, myriad studies over the last quarter century have employed the technique of brain mapping—identifying the neural correlates of various psychological phenomena—in ways that bear minimally on psychological theory. How can brain mapping be made more relevant to behavioral scientists broadly? Here, we describe three trends that increase precisely this relevance: (i) the use of neuroimaging data to adjudicate between competing psychological theories through forward inference, (ii) isolating neural markers of information processing steps to better understand complex tasks and psychological phenomena through probabilistic reverse inference, and (iii) using brain activity to predict subsequent behavior. Critically, these new approaches build on the extensive tradition of brain mapping, suggesting that efforts in this area—although not initially maximally relevant to psychology—can indeed be used in ways that constrain and advance psychological theory.


eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Tatiana Lau ◽  
Samuel J Gershman ◽  
Mina Cikara

Humans form social coalitions in every society, yet we know little about how we learn and represent social group boundaries. Here we derive predictions from a computational model of latent structure learning to move beyond explicit category labels and interpersonal, or dyadic, similarity as the sole inputs to social group representations. Using a model-based analysis of functional neuroimaging data, we find that separate areas correlate with dyadic similarity and latent structure learning. Trial-by-trial estimates of ‘allyship’ based on dyadic similarity between participants and each agent recruited medial prefrontal cortex/pregenual anterior cingulate (pgACC). Latent social group structure-based allyship estimates, in contrast, recruited right anterior insula (rAI). Variability in the brain signal from rAI improved prediction of variability in ally-choice behavior, whereas variability from the pgACC did not. These results provide novel insights into the psychological and neural mechanisms by which people learn to distinguish ‘us’ from ‘them.’


2012 ◽  
Vol 24 (8) ◽  
pp. 1742-1752 ◽  
Author(s):  
Bryan T. Denny ◽  
Hedy Kober ◽  
Tor D. Wager ◽  
Kevin N. Ochsner

The distinction between processes used to perceive and understand the self and others has received considerable attention in psychology and neuroscience. Brain findings highlight a role for various regions, in particular the medial PFC (mPFC), in supporting judgments about both the self and others. We performed a meta-analysis of 107 neuroimaging studies of self- and other-related judgments using multilevel kernel density analysis [Kober, H., & Wager, T. D. Meta-analyses of neuroimaging data. Wiley Interdisciplinary Reviews, 1, 293–300, 2010]. We sought to determine what brain regions are reliably involved in each judgment type and, in particular, what the spatial and functional organization of mPFC is with respect to them. Relative to nonmentalizing judgments, both self- and other judgments were associated with activity in mPFC, ranging from ventral to dorsal extents, as well as common activation of the left TPJ and posterior cingulate. A direct comparison between self- and other judgments revealed that ventral mPFC as well as left ventrolateral PFC and left insula were more frequently activated by self-related judgments, whereas dorsal mPFC, in addition to bilateral TPJ and cuneus, was more frequently activated by other-related judgments. Logistic regression analyses revealed that ventral and dorsal mPFC lay at opposite ends of a functional gradient: The z coordinates reported in individual studies predicted whether the study involved self- or other-related judgments, which were associated with increasingly ventral or dorsal portions of mPFC, respectively. These results argue for a distributed rather than localizationist account of mPFC organization and support an emerging view on the functional heterogeneity of mPFC.


Sign in / Sign up

Export Citation Format

Share Document