One of the key challenges hindering the clinical intervention against brain cancer is defined by the inability to detect brain tumors at an early enough stage to permit effective therapy. Furthermore, the rapid growth and severe lethality of this form of cancer predicate the vital importance of monitoring the development of the pathology and its outcome after therapeutic intervention.
PURPOSE: Tumor resistance to chemotherapeutic drugs is one of the major obstacles in the treatment of glioblastoma multiforme (GBM). In this study, we attempted to modulate tumor response to chemotherapy by combination treatment that included experimental (small interference RNA (siRNA), chlorotoxin) and conventional (temozolomide, TMZ) therapeutics.
The sixth meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) consortium was focused on selecting promising imaging biomarker measures for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of working memory (WM), the 2 constructs of interest were "goal maintenance" and "interference control." CNTRICS received 7 task nominations for goal maintenance and 3 task nominations for interference control.
Working memory (WkM) is a fundamental cognitive process that serves as a building block for higher order cognitive functions. While studies have shown that children and adolescents utilize similar brain regions during verbal WkM, there have been few studies that evaluate the developmental differences in brain connectivity. Our goal was to study the development of brain connectivity related to verbal WkM in typically developing children and adolescents.
A number of recent studies have combined multiple experimental paradigms and modalities to find relevant biological markers for schizophrenia. In this study, we extracted fMRI features maps from the analysis of three experimental paradigms (auditory oddball, Sternberg item recognition, sensorimotor) for a large number (n=154) of patients with schizophrenia and matched healthy controls. We used the general linear model (GLM) and independent component analysis (ICA) to extract feature maps (i.e.
Impairment of working memory (WM) performance in schizophrenia patients (SZ) is well-established. Compared to healthy controls (HC), SZ patients show aberrant blood oxygen level dependent (BOLD) activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI) data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP) at three WM load levels.
BACKGROUND: Working memory studies in schizophrenia (SZ), using functional magnetic resonance imaging (fMRI) and univariate analyses, have led to observations of hypo- or hyperactivation of discrete cortical regions and subsequent interpretations (e.g. neural inefficiencies). We employed a data-driven, multivariate analysis to identify the patterns of brain-behavior relationships in SZ during working memory.
We investigated whether a nonspatial working memory (WM) task would activate dorsolateral prefrontal cortex (DLPFC) and whether activation would be correlated with WM load. Using functional magnetic resonance imaging we measured regional brain signal changes in 12 normal subjects performing a continuous performance, choice reaction time task that requires WM. A high WM load condition was compared with a non-WM choice reaction time control condition (WM effect) and a low WM load condition (load effect).
Two patients are described with the social emotional processing disorder, a developmental syndrome usually ascribed to right hemisphere dysfunction. In these two patients however, neurological examinations, EEG, and neuroimaging studies were all consistent with left hemisphere dysfunction. Both patients were left handed and had findings suggestive of anomalous dominance for language.
Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs.
