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ICOSR 2011—Searching for the Brain Activation Patterns of Schizophrenia

As part of our ongoing coverage of the 2011 International Congress on Schizophrenia Research (ICOSR), held 2-6 April in Colorado Springs, Colorado, we bring you session summaries from some of the Young Investigator travel award winners. For this report, we thank Brandon Abbs of Brigham and Women’s Hospital (Harvard Medical School), Boston, Massachusetts.

25 May 2011. One of the Monday, 4 April, afternoon sessions was entitled “Functional Neuroimaging: Novel Analyses of Dysfunctional Neural Circuitry in Individuals With Schizophrenia and at-Risk Populations,” chaired by Daphne Holt of Massachusetts General Hospital, Boston.

Half of the session focused on “resting-state” analyses of brain networks (i.e., when no task is being performed) using functional magnetic resonance imaging (fMRI) data, which measure blood flow in the brain over time. This type of analysis has been rising in popularity over the past few years in cognitive and psychiatric neuroscience, and is now being applied to schizophrenia. Part of its allure is that there is no task performance to control; in fact, what participants do while resting (e.g., daydream, plan the rest of their day, worry, etc.) is not considered in the analysis. However, this does not mean the analysis is limited to studying the default-mode network that is active when the brain is at rest; brain networks involved in attention, memory, language, etc., can all be examined because their activity remains tightly correlated even if they are not engaged in a task. Consequently, researchers can also study how the brain “turns off,” or suppresses, the default-mode network and “turns on,” or activates, other networks when more specific information processing is needed to complete a task.

Neil Woodward of Vanderbilt University, Nashville, Tennessee, found that the default-mode, dorsal-attention, and executive-control networks were different in patients with schizophrenia. There were stronger correlations among regions (also known as connectivity) in the default network and weaker correlations in the other two networks. Moreover, there was evidence that the decreased connectivity in the attention and executive-control networks was due, in part, to reduced interhemispheric connectivity among homologous brain regions. Overall, his results suggest that normal processes of internetwork integration and segregation, which occur during development, may be disrupted in schizophrenia.

Danielle Bassett of the University of California, Santa Barbara, used a set of analyses to demonstrate the power of a combination of approaches covering multiple scales of function: univariate entropy, bivariate correlation, and multivariate network properties. She found that univariate measures were the least sensitive to disease state, while bivariate and multivariate measures could be used to discriminate between the two groups with 75 percent classification accuracy. This suggests that connectivity is more affected in schizophrenia than absolute activity, and higher-order statistics may be more diagnostic; specifically, weak connections discriminate groups better than strong connections.

Chair Daphne Holt had a more specific target of her analysis than these first two presenters. She focused on the medial prefrontal cortex (mPFC), a region that is central to affective regulation and part of the default-mode network, and addressed the question of whether these dysfunctions are a trait of schizophrenia or part of the state when patients are scanned. Previous studies have found dysfunction across a wide area of the mPFC, including the ventral and dorsal mPFC. Holt noted that there are dense, short-range connections between different areas within mPFC and long-range connections between other brain areas in the same network, such as the hippocampus and amygdala. Her analysis used precise spatial localization of regions of interest within the mPFC, based on previous research, and related it to a common symptom of schizophrenia—delusional thinking—that can also be evaluated in a comparison group without schizophrenia. She found that reduced connectivity between a more posterior portion of ventral mPFC (Brodmann area 25), a subgenual portion, and a rostral portion, correlated with more delusional thinking, even in controls. Connectivity between the mPFC and amygdala related more to the anxiety of the person being scanned. The results within ventral mPFC in patients were not related to medication, which, together with the finding in controls, suggests that this may be a brain dysfunction that is a relatively stable trait of schizophrenia.

Avinash Hosanger of the University of Michigan, Ann Arbor, also looked at dysfunction in the affective system but tied it to dysfunction in areas that also have high levels of dopamine neurotransmission. This system is also implicated in schizophrenia, and he found greater connectivity between a dopaminergic region, the caudate, and the thalamus and frontal pole. He also found greater connectivity between the ventral tegmental area and thalamus. In the affective system, he found greater connectivity between the amygdala and insula and cingulate. Lauren Moran of the Maryland Psychiatric Research Center, Baltimore, looked at similar brain regions during rest in relation to smoking addiction because of the role the regions play in learning and addiction. Moran distinguished between the brain activity in anterior and posterior insula and dorsal anterior cingulate cortex (dACC) using the participants’ own structural scans, and then looked at their connectivity to other brain regions. She found decreased connectivity related to increased addiction severity in connections among the left dACC-striatum, dACC-insula, and right insula-left somatosensory, with the first two connections explaining 43 percent of the variance in severity. Connectivity was different elsewhere in schizophrenia, but not related to addiction, suggesting that there are some brain dysfunctions that are specific to addiction in schizophrenia.

Only Ayna Nejad of the Danish Research Centre for Magnetic Resonance, Hvidovre, Denmark, looked at the suppression of default-mode network activity when performing some other task. Her work looked at the 2-back task (a working memory task), and found that the default-mode network was not deactivated as much in schizophrenia patients when the working memory load was high. This was especially true in the superior temporal gyrus (STG). She suggested that this activation reflected attention processing, and that schizophrenia brains were not adequately redirecting attention under more difficult working memory conditions.

The rest of the session consisted of reports on at-risk populations and genetic neuroimaging. Susanna Fryer of the University of California, San Francisco, looked at cognitive control in a go/no-go, or response inhibition, paradigm. She reported that clinical high-risk subjects identified through symptom questionnaires and early-intervention programs were not less accurate on a task requiring inhibition compared to their low-risk (i.e., asymptomatic) peers but were slower and had a different pattern of brain activity: decreased ACC, dorsal lateral PFC, inferior frontal gyrus (IFG), and insula. Moreover, brain activity in the PFC and left frontal-temporal regions did relate to the display of positive and negative symptoms in the at-risk group. Larry Seidman of Beth Israel Deaconess Medical Center, Boston, Massachusetts, used relatives of patients with schizophrenia as a high-risk group. They processed semantically related and unrelated words in a lexical decision task, which captures both lexical processing (deciding whether a word is real) and semantic facilitation (deciding whether a word is real after being primed with a phonologically similar real word). When highly related words were shown, they showed no activation in the left inferior temporal area, a decrease in frontal areas, and an increase in hippocampal areas, suggesting semantic hyperactivity. When less highly related words were shown, high-risk subjects exhibited lower activation in all of the same areas as those with no risk. Together, these studies suggest that the brain in people showing prodromal symptoms of schizophrenia or related to people with schizophrenia has difficulty inhibiting behavior when there is a bias toward a particular response or regulating brain activity when given related/conflicting task-irrelevant information, but they are also less influenced by information that is not as strongly related.

On the genetics front, Alessandro Bertolino of the University of Bari, Italy, took a novel approach to hippocampal function in schizophrenia by looking at processing in this region as a function of risk for schizophrenia and COMT genotype, which is typically related to dopamine neurotransmission, not hippocampal function. However, Bertolino pointed out that dopamine does modulate the hippocampus and parahippocampus during episodic memory encoding, which is impaired in schizophrenia. He looked at memory encoding in patients with schizophrenia, their siblings, and an unrelated comparison group during fMRI. He found poorer memory in schizophrenia, but this was not related to COMT genotype. However, in another sample of the same groups of subjects, the activation of the hippocampus was related to COMT genotype. In the unrelated group, those with the Met/Met genotype showed the greatest activation in the hippocampus, but in schizophrenia patients and relatives, they showed the lowest. Moreover, the Val/Val genotype showed the most hippocampal activation in schizophrenia patients and relatives. These data demonstrate that hippocampal function is heritable, not state-related, and more functional than behavioral. Schizophrenia patients and their siblings showed a different pattern of brain activity as a function of genotype, but did not show a difference in their memory ability. Moreover, the genotype was not related to memory ability; it was related to brain activity.

Lastly, Marco Picchioni of St. Andrew’s Academic Centre, Northampton, United Kingdom, looked at verbal fluency as an endophenotype of schizophrenia by studying twins discordant for the disorder (one has schizophrenia and one does not) and their ability to generate words in response to a cue. During fMRI, he found hyperactivity in the left IFG, STG, and insula in schizophrenia patients. It should be noted that during this task, participants had to vocalize their responses, which were fed back to them through headphones, so any activity in auditory regions (such as STG) may be related to this vocalization. Nevertheless, they also showed hypoactivity in the left parahippocampus and right STG. The monozygotic twins showed this effect to a lesser degree in the left STG and IFG. Picchioni argued that there is shared genetic risk for hypoactivation of left temporal regions for which the IFG may be compensating. Activation in other areas, like the insula, may have less of a genetic component and more of an environmental one.

All together, these studies show how far psychiatric neuroimaging has come in schizophrenia, and the exciting new ways it is being used to understand the specificity, heritability, and predictability of brain dysfunction in schizophrenia, even when overt behavioral differences cannot be seen.—Brandon Abbs.

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