Decoding Continuous Variables from Neuroimaging Data: Basic and Clinical Applications

The application of statistical machine learning techniques to neuroimaging data has allowed researchers to decode the cognitive and disease states of participants. The majority of studies using these techniques have focused on pattern classification to decode the type of object a participant is viewing, the type of cognitive task a participant is completing, or the disease state of a participant's brain. However, an emerging body of literature is extending these classification studies to the decoding of values of continuous variables (such as age, cognitive characteristics, or neuropsychological state) using high-dimensional regression methods. This review details the methods used in such analyses and describes recent results. We provide specific examples of studies which have used this approach to answer novel questions about age and cognitive and disease states. We conclude that while there is still much to learn about these methods, they provide useful information about the relationship between neural activity and age, cognitive state, and disease state, which could not have been obtained using traditional univariate analytical methods

Decoding Developmental Differences and Individual Variability in Response Inhibition Through Predictive Analyses Across Individuals

Response inhibition is thought to improve throughout childhood and into adulthood. Despite the relationship between age and the ability to stop ongoing behavior, questions remain regarding whether these age-related changes reflect improvements in response inhibition or in other factors that contribute to response performance variability. Functional neuroimaging data shows age-related changes in neural activity during response inhibition. While traditional methods of exploring neuroimaging data are limited to determining correlational relationships, newer methods can determine predictability and can begin to answer these questions. Therefore, the goal of the current study was to determine which aspects of neural function predict individual differences in age, inhibitory function, response speed, and response time variability. We administered a stop-signal task requiring rapid inhibition of ongoing motor responses to healthy participants aged 9–30. We conducted a standard analysis using GLM and a predictive analysis using high-dimensional regression methods. During successful response inhibition we found regions typically involved in motor control, such as the ACC and striatum, that were correlated with either age, response inhibition (as indexed by stop-signal reaction time; SSRT), response speed, or response time variability. However, when examining which variables neural data could predict, we found that age and SSRT, but not speed or variability of response execution, were predicted by neural activity during successful response inhibition. This predictive relationship provides novel evidence that developmental differences and individual differences in response inhibition are related specifically to inhibitory processes. More generally, this study demonstrates a new approach to identifying the neurocognitive bases of individual differences

Memory systems in schizophrenia: Modularity is preserved but deficits are generalized

OBJECTIVE: Schizophrenia patients exhibit impaired working and episodic memory, but this may represent generalized impairment across memory modalities or performance deficits restricted to particular memory systems in subgroups of patients. Furthermore, it is unclear whether deficits are unique from those associated with other disorders. METHOD: Healthy controls (n=1101) and patients with schizophrenia (n=58), bipolar disorder (n=49) and attention-deficit-hyperactivity-disorder (n=46) performed 18 tasks addressing primarily verbal and spatial episodic and working memory. Effect sizes for group contrasts were compared across tasks and the consistency of subjects\u27 distributional positions across memory domains was measured. RESULTS: Schizophrenia patients performed poorly relative to the other groups on every test. While low to moderate correlation was found between memory domains (r=.320), supporting modularity of these systems, there was limited agreement between measures regarding each individual\u27s task performance (ICC=.292) and in identifying those individuals falling into the lowest quintile (kappa=0.259). A general ability factor accounted for nearly all of the group differences in performance and agreement across measures in classifying low performers. CONCLUSIONS: Pathophysiological processes involved in schizophrenia appear to act primarily on general abilities required in all tasks rather than on specific abilities within different memory domains and modalities. These effects represent a general shift in the overall distribution of general ability (i.e., each case functioning at a lower level than they would have if not for the illness), rather than presence of a generally low-performing subgroup of patients. There is little evidence that memory impairments in schizophrenia are shared with bipolar disorder and ADHD

Predicting risky choices from brain activity patterns

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights

Dietary patterns, foods, and food groups : relation to late-life cognitive disorders

The limited efficacy of disease-modifying therapeutic strategies for mild cognitive impairment (MCI) and Alzheimer\u2019s dementia (AD) underscores the need for preventive measures to reduce the burden of late-life cognitive impairment. The aim of the present review article was to investigate the relationship among dietary patterns, foods, and food groups and late-life cognitive disorders considering the results of observational studies published in the last three years (2014-2016). In the last decade, the association between diet and cognitive function or dementia has been largely investigated. However, more recently, the National Institute on Aging-Alzheimer\u2019s Association guidelines for AD and cognitive decline due to AD pathology introduced some evidence suggesting a direct relation between diet and changes in the brain structure and activity. Several studies focused on the role of the dietary patterns on late-life cognition, with accumulating evidence that combinations of foods and nutrients into certain patterns may act synergistically to provide stronger health effects than those conferred by their individual dietary components. In particular, higher adherence to a Mediterranean-type diet was associated with decreased cognitive decline, although the Mediterranean diet (MeDi) combines several foods, micronutrients, and macronutrients already separately proposed as potential protective factors against dementia and MCI. Moreover, also other emerging healthy dietary patterns such as the Dietary Approach to Stop Hypertension (DASH) and the Mediterranean-DASH diet Intervention for Neurodegenerative Delay (MIND) diets were associated with slower rates of cognitive decline and significant reduction in AD rate. Furthermore, some foods or food groups traditionally considered harmful such as eggs and red meat have been partially rehabilitated, while there is still a negative correlation of cognitive functions with added sugars and trans fatty acids, nutrients also increasing the cardiovascular risk. This would suggest a genesis for the same damage for aging brain

Nutritional interventions in patients with Alzheimer’s disease and other late-life cognitive disorders

Given the impact of nutrition on neuroprotection largely investigated in observational studies, in the present article, we reviewed evidence from randomized clinical trials (RCTs) published in the last three years (2014-2016) exploring nutritional intervention efficacy in slowing cognitive impairment progression and achieving cognitive-related outcomes in patients aged 60 years and older with mild cognitive impairment (MCI), preclinical Alzheimer\u2019s disease (AD), prodromal AD, AD, unspecified dementia, and vascular dementia using different levels of investigation (i.e., medical food/nutraceutical supplementation/multidomain approach and dietary food/macro-and micronutrient approaches). From the reviewed RCTs, there was emerging evidence that nutritional intervention through medical food/nutraceutical supplementation (Fortasyn Connect\uae and another similar nutraceutical formulation) and multidomain approach improved magnetic resonance imaging findings and other cognitive-related biomarkers, but without clear effect on cognition in mild AD and MCI. Moreover, there was some evidence of a positive effect of antioxidant-rich foods (nuts) in improving specific cognitive domains and cognitive-related outcomes in MCI and mild-to-moderate dementia, but only in small samples. There was also convincing evidence for fatty acid supplementation, mainly n-3 polyunsaturated fatty acids (PUFAs), in improving specific cognitive domains and/or cognitive-related biomarkers in MCI and AD. Furthermore, antioxidant vitamin and trace element supplementations improved only cognitive-related outcomes and biomarkers, without effect on cognitive function in AD and MCI patients. Finally, high-dose B vitamin supplementation in AD and MCI patients improved cognitive outcomes but only in the subjects with a high baseline plasma n-3 PUFA, while folic acid supplementation had positive impact on specific cognitive domains

Dietary intervention and prevention of cognitive-related outcomes in healthy older adults without cognitive dysfunction

In the last decade, the association between diet and cognitive function/dementia has been largely investigated in observational studies, while there was a lack of evidence from randomized clinical trials (RCTs) on the prevention of late-life cognitive disorders though dietary intervention in cognitively healthy older adults. In the present article, we reviewed RCTs published in the last three years (2014-2016) exploring nutritional intervention efficacy in preventing the onset of late-life cognitive disorders and dementia in cognitively healthy subjects aged over 60 years using different levels of investigation (i.e., dietary pattern changes/ medical food/nutraceutical supplementation/multidomain approach and dietary macro-and micronutrient approaches). From the included RCTs, there was moderate evidence that intervention through dietary pattern changes, medical food/nutraceutical supplementation, and multidomain approach improved specific cognitive domains or cognitive-related blood biomarkers. Moreover, there was high evidence that protein supplementation improved specific cognitive domains. For fatty acid supplementation, mainly long-chain polyunsaturated fatty acids, there was emerging evidence suggesting an impact of this approach in improving specific cognitive domains, MRI findings, and/or cognitive-related biomarkers also in selected subgroups of older subjects although some results were conflicting. Moreover, there was convincing evidence of an impact of non-flavonoid polyphenol and flavonoid supplementations in improving specific cognitive domains and/or MRI findings. Finally, there was only low evidence suggesting efficacy of intervention with homocysteine-related vitamins in improving cognitive functions, dementia incidence, or cognitive-related biomarkers in cognitively healthy older subjects

Neurocognitive and Neuroimaging Predictors of Clinical Outcome in Bipolar Disorder

Historically, bipolar disorder has been conceptualized as a disease involving episodic rather than chronic dysfunction. However, increasing evidence indicates that bipolar disorder is associated with substantial inter-episode psychosocial and vocational impairment. Here we review the contributions of neurocognitive deficits and structural and functional neuroanatomic alterations to the observed functional impairments. In particular, compelling evidence now suggests that neurocognitive impairments, particularly in the areas of attention, processing speed, and memory, are associated with functional outcome. Although investigation of the neural correlates of functional disability in bipolar disorder is only in its nascent stages, preliminary evidence suggests that white matter abnormalities may be predictive of poor outcome. A better understanding of the relationship between neurocognitive and neuroimaging assays and functional outcome has the potential to improve current treatment options and provide targets for new treatment strategies in bipolar disorder

Evaluation of the performance of Dutch Lipid Clinic Network score in an Italian FH population: The LIPIGEN study

Background and aims: Familial hypercholesterolemia (FH) is an inherited disorder characterized by high levels of blood cholesterol from birth and premature coronary heart disease. Thus, the identification of FH patients is crucial to prevent or delay the onset of cardiovascular events, and the availability of a tool helping with the diagnosis in the setting of general medicine is essential to improve FH patient identification.Methods: This study evaluated the performance of the Dutch Lipid Clinic Network (DLCN) score in FH patients enrolled in the LIPIGEN study, an Italian integrated network aimed at improving the identification of patients with genetic dyslipidaemias, including FH.Results: The DLCN score was applied on a sample of 1377 adults (mean age 42.9 +/- 14.2 years) with genetic diagnosis of FH, resulting in 28.5% of the sample classified as probable FH and 37.9% as classified definite FH. Among these subjects, 43.4% had at least one missing data out of 8, and about 10.0% had 4 missing data or more. When analyzed based on the type of missing data, a higher percentage of subjects with at least 1 missing data in the clinical history or physical examination was classified as possible FH (DLCN score 3-5). We also found that using real or estimated pre-treatment LDL-C levels may significantly modify the DLCN score.Conclusions: Although the DLCN score is a useful tool for physicians in the diagnosis of FH, it may be limited by the complexity to retrieve all the essential information, suggesting a crucial role of the clinical judgement in the identification of FH subjects