Ben Krasnow

Bio: Ben Krasnow is an academic researcher from Stanford University. The author has contributed to research in topics: Working memory & Functional magnetic resonance imaging. The author has an hindex of 5, co-authored 5 publications receiving 6098 citations.

Functional connectivity in the resting brain: A network analysis of the default mode hypothesis

Abstract: Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.

Regional analysis of hippocampal activation during memory encoding and retrieval: fMRI study.

Abstract: Investigators have recently begun to examine the differen- tial role of subregions of the hippocampus in episodic memory. Two distinct models have gained prominence in the field. One model, outlined by Moser and Moser (Hippocampus 1998;8:608 - 619), based mainly on animal studies, has proposed that episodic memory is subserved by the posterior two-thirds of the hippocampus alone. A second model, derived by Lepage et al. (Hippocampus 1998;8:313-322) from their review of 52 PET studies, has suggested that the anterior hippocampus is activated by memory encoding while the posterior hippocampus is activated by mem- ory retrieval. Functional magnetic resonance imaging (fMRI) studies have tended to show limited activation in the anteriormost regions of the hippocampus, providing support for the Moser and Moser model. A potential confounding factor in these fMRI studies, however, is that susceptibility artifact may differentially reduce signal in the anterior versus the posterior hippocampus. In the present study, we examined activation differences between hippocampal subregions during encoding and retrieval of words and interpreted our findings within the context of these two models. We also examined the extent to which susceptibility artifact affects the analysis and interpretation of hippocampal activation by demonstrating its differential effect on the anterior versus the posterior hippocampus. Both voxel-by-voxel and region-of-interest analyses were conducted, allowing us to quantify differences between the anterior and posterior aspects of the hippocampus. We detected significant hippocam- pal activation in both the encoding and retrieval conditions. Our data do not provide evidence for regional anatomic differences in activation between encoding and retrieval. The data do suggest that, even after accounting for susceptibility artifact, both encoding and retrieval of ver- bal stimuli activate the middle and posterior hippocampus more strongly than the anterior hippocampus. Finally, this study is the first to quantify the effects of susceptibility-induced signal loss on hip- pocampal activation and suggests that this artifact has significantly biased the interpretation of earlier fMRI studies. Hippocampus 2003;13:164 -174.

Investigation of White Matter Structure in Velocardiofacial Syndrome: A Diffusion Tensor Imaging Study

Abstract: OBJECTIVE: Velocardiofacial syndrome, caused by a deletion on chromosome 22q11.2, is often accompanied by cognitive, behavioral, and psychiatric impairments. Specifically, velocardiofacial syndrome has been proposed as a disease model for a genetically mediated subtype of schizophrenia. Velocardiofacial syndrome is also known to affect brain structure. The most prominent structural findings in velocardiofacial syndrome are reduced white matter volumes. However, the structure of white matter and extent of specific regional involvement in this syndrome have never been investigated. The current study used diffusion tensor imaging to investigate white matter structure in children and young adults with velocardiofacial syndrome. METHOD: Nineteen participants with velocardiofacial syndrome and 19 age- and gender-matched comparison subjects underwent diffusion-weighted magnetic resonance imaging scans. Whole brain voxel-by-voxel analyses were conducted to investigate white matter fractional anisotropy difference...

Complex brain networks: graph theoretical analysis of structural and functional systems

Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

Abstract: Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

The Brain's Default Network Anatomy, Function, and Relevance to Disease

Abstract: Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations These two subsystems converge on important nodes of integration including the posterior cingulate cortex The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

Abstract: During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.