Pitch discrimination in optimal and suboptimal acoustic environments: electroencephalographic, magnetoencephalographic, and behavioral evidence

Pitch discrimination is a fundamental property of the human auditory system. Our understanding of pitch-discrimination mechanisms is important from both theoretical and clinical perspectives. The discrimination of spectrally complex sounds is crucial in the processing of music and speech. Current methods of cognitive neuroscience can track the brain processes underlying sound processing either with precise temporal (EEG and MEG) or spatial resolution (PET and fMRI). A combination of different techniques is therefore required in contemporary auditory research. One of the problems in comparing the EEG/MEG and fMRI methods, however, is the fMRI acoustic noise. In the present thesis, EEG and MEG in combination with behavioral techniques were used, first, to define the ERP correlates of automatic pitch discrimination across a wide frequency range in adults and neonates and, second, they were used to determine the effect of recorded acoustic fMRI noise on those adult ERP and ERF correlates during passive and active pitch discrimination. Pure tones and complex 3-harmonic sounds served as stimuli in the oddball and matching-to-sample paradigms. The results suggest that pitch discrimination in adults, as reflected by MMN latency, is most accurate in the 1000-2000 Hz frequency range, and that pitch discrimination is facilitated further by adding harmonics to the fundamental frequency. Newborn infants are able to discriminate a 20% frequency change in the 250-4000 Hz frequency range, whereas the discrimination of a 5% frequency change was unconfirmed. Furthermore, the effect of the fMRI gradient noise on the automatic processing of pitch change was more prominent for tones with frequencies exceeding 500 Hz, overlapping with the spectral maximum of the noise. When the fundamental frequency of the tones was lower than the spectral maximum of the noise, fMRI noise had no effect on MMN and P3a, whereas the noise delayed and suppressed N1 and exogenous N2. Noise also suppressed the N1 amplitude in a matching-to-sample working memory task. However, the task-related difference observed in the N1 component, suggesting a functional dissociation between the processing of spatial and non-spatial auditory information, was partially preserved in the noise condition. Noise hampered feature coding mechanisms more than it hampered the mechanisms of change detection, involuntary attention, and the segregation of the spatial and non-spatial domains of working-memory. The data presented in the thesis can be used to develop clinical ERP-based frequency-discrimination protocols and combined EEG and fMRI experimental paradigms.

Prevention of type 2 diabetes with lifestyle intervention - emphasis on dietary composition and identification of high-risk individuals

Type 2 diabetes is an increasing, serious, and costly public health problem. The increase in the prevalence of the disease can mainly be attributed to changing lifestyles leading to physical inactivity, overweight, and obesity. These lifestyle-related risk factors offer also a possibility for preventive interventions. Until recently, proper evidence regarding the prevention of type 2 diabetes has been virtually missing. To be cost-effective, intensive interventions to prevent type 2 diabetes should be directed to people at an increased risk of the disease. The aim of this series of studies was to investigate whether type 2 diabetes can be prevented by lifestyle intervention in high-risk individuals, and to develop a practical method to identify individuals who are at high risk of type 2 diabetes and would benefit from such an intervention. To study the effect of lifestyle intervention on diabetes risk, we recruited 522 volunteer, middle-aged (aged 40 - 64 at baseline), overweight (body mass index > 25 kg/m2) men (n = 172) and women (n = 350) with impaired glucose tolerance to the Diabetes Prevention Study (DPS). The participants were randomly allocated either to the intensive lifestyle intervention group or the control group. The control group received general dietary and exercise advice at baseline, and had annual physician's examination. The participants in the intervention group received, in addition, individualised dietary counselling by a nutritionist. They were also offered circuit-type resistance training sessions and were advised to increase overall physical activity. The intervention goals were to reduce body weight (5% or more reduction from baseline weight), limit dietary fat (< 30% of total energy consumed) and saturated fat (< 10% of total energy consumed), and to increase dietary fibre intake (15 g / 1000 kcal or more) and physical activity (≥ 30 minutes/day). Diabetes status was assessed annually by a repeated 75 g oral glucose tolerance testing. First analysis on end-points was completed after a mean follow-up of 3.2 years, and the intervention phase was terminated after a mean duration of 3.9 years. After that, the study participants continued to visit the study clinics for the annual examinations, for a mean of 3 years. The intervention group showed significantly greater improvement in each intervention goal. After 1 and 3 years, mean weight reductions were 4.5 and 3.5 kg in the intervention group and 1.0 kg and 0.9 kg in the control group. Cardiovascular risk factors improved more in the intervention group. After a mean follow-up of 3.2 years, the risk of diabetes was reduced by 58% in the intervention group compared with the control group. The reduction in the incidence of diabetes was directly associated with achieved lifestyle goals. Furthermore, those who consumed moderate-fat, high-fibre diet achieved the largest weight reduction and, even after adjustment for weight reduction, the lowest diabetes risk during the intervention period. After discontinuation of the counselling, the differences in lifestyle variables between the groups still remained favourable for the intervention group. During the post-intervention follow-up period of 3 years, the risk of diabetes was still 36% lower among the former intervention group participants, compared with the former control group participants. To develop a simple screening tool to identify individuals who are at high risk of type 2 diabetes, follow-up data of two population-based cohorts of 35-64 year old men and women was used. The National FINRISK Study 1987 cohort (model development data) included 4435 subjects, with 182 new drug-treated cases of diabetes identified during ten years, and the FINRISK Study 1992 cohort (model validation data) included 4615 subjects, with 67 new cases of drug-treated diabetes during five years, ascertained using the Social Insurance Institution's Drug register. Baseline age, body mass index, waist circumference, history of antihypertensive drug treatment and high blood glucose, physical activity and daily consumption of fruits, berries or vegetables were selected into the risk score as categorical variables. In the 1987 cohort the optimal cut-off point of the risk score identified 78% of those who got diabetes during the follow-up (= sensitivity of the test) and 77% of those who remained free of diabetes (= specificity of the test). In the 1992 cohort the risk score performed equally well. The final Finnish Diabetes Risk Score (FINDRISC) form includes, in addition to the predictors of the model, a question about family history of diabetes and the age category of over 64 years. When applied to the DPS population, the baseline FINDRISC value was associated with diabetes risk among the control group participants only, indicating that the intensive lifestyle intervention given to the intervention group participants abolished the diabetes risk associated with baseline risk factors. In conclusion, the intensive lifestyle intervention produced long-term beneficial changes in diet, physical activity, body weight, and cardiovascular risk factors, and reduced diabetes risk. Furthermore, the effects of the intervention were sustained after the intervention was discontinued. The FINDRISC proved to be a simple, fast, inexpensive, non-invasive, and reliable tool to identify individuals at high risk of type 2 diabetes. The use of FINDRISC to identify high-risk subjects, followed by lifestyle intervention, provides a feasible scheme in preventing type 2 diabetes, which could be implemented in the primary health care system.

Essays on socially optimal phosphorus policies in crop production

Phosphorus is a nutrient needed in crop production. While boosting crop yields it may also accelerate eutrophication in the surface waters receiving the phosphorus runoff. The privately optimal level of phosphorus use is determined by the input and output prices, and the crop response to phosphorus. Socially optimal use also takes into account the impact of phosphorus runoff on water quality. Increased eutrophication decreases the economic value of surface waters by Deteriorating fish stocks, curtailing the potential for recreational activities and by increasing the probabilities of mass algae blooms. In this dissertation, the optimal use of phosphorus is modelled as a dynamic optimization problem. The potentially plant available phosphorus accumulated in soil is treated as a dynamic state variable, the control variable being the annual phosphorus fertilization. For crop response to phosphorus, the state variable is more important than the annual fertilization. The level of this state variable is also a key determinant of the runoff of dissolved, reactive phosphorus. Also the loss of particulate phosphorus due to erosion is considered in the thesis, as well as its mitigation by constructing vegetative buffers. The dynamic model is applied for crop production on clay soils. At the steady state, the analysis focuses on the effects of prices, damage parameterization, discount rate and soil phosphorus carryover capacity on optimal steady state phosphorus use. The economic instruments needed to sustain the social optimum are also analyzed. According to the results the economic incentives should be conditioned on soil phosphorus values directly, rather than on annual phosphorus applications. The results also emphasize the substantial effects the differences in varying discount rates of the farmer and the social planner have on optimal instruments. The thesis analyzes the optimal soil phosphorus paths from its alternative initial levels. It also examines how erosion susceptibility of a parcel affects these optimal paths. The results underline the significance of the prevailing soil phosphorus status on optimal fertilization levels. With very high initial soil phosphorus levels, both the privately and socially optimal phosphorus application levels are close to zero as the state variable is driven towards its steady state. The soil phosphorus processes are slow. Therefore, depleting high phosphorus soils may take decades. The thesis also presents a methodologically interesting phenomenon in problems of maximizing the flow of discounted payoffs. When both the benefits and damages are related to the same state variable, the steady state solution may have an interesting property, under very general conditions: The tail of the payoffs of the privately optimal path as well as the steady state may provide a higher social welfare than the respective tail of the socially optimal path. The result is formalized and an applied to the created framework of optimal phosphorus use.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Liver fat in the metabolic syndrome and type 2 diabetes

Introduction: The epidemic of obesity has been accompanied by an increase in the prevalence of the metabolic syndrome, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). However, not all obese subjects develop these metabolic abnormalities. Hepatic fat accumulation is related to hepatic insulin resistance, which in turn leads to hyperglycemia, hypertriglyceridemia, and a low HDL cholesterol con-centration. The present studies aimed to investigate 1) how intrahepatic as compared to intramyocellular fat is related to insulin resistance in these tissues and to the metabolic syndrome (Study I); 2) the amount of liver fat in subjects with and without the metabolic syndrome, and which clinically available markers best reflect liver fat content (Study II); 3) the effect of liver fat on insulin clearance (Study III); 4) whether type 2 diabetic patients have more liver fat than age-, gender-, and BMI-matched non-diabetic subjects (Study IV); 5) how type 2 diabetic patients using exceptionally high doses of insulin respond to addition of a PPARγ agonist (Study V). Subjects and methods: The study groups consisted of 45 (Study I), 271 (Study II), and 80 (Study III) non-diabetic subjects, and of 70 type 2 diabetic patients and 70 matched control subjects (Study IV). In Study V, a total of 14 poorly controlled type 2 diabetic patients treated with high doses of insulin were studied before and after rosiglitazone treatment (8 mg/day) for 8 months. In all studies, liver fat content was measured by proton magnetic resonance spectroscopy, and sub-cutaneous and intra-abdominal fat content by MRI. In addition, circulating markers of insulin resistance and serum liver enzyme concentrations were determined. Hepatic (i.v. insulin infusion rate 0.3 mU/kg∙min combined with [3-3H]glucose, Studies I, III, and V) and muscle (1.0 mU/kg min, Study I) insulin sensitivities were measured by the euglycemic hyperinsulinemic clamp technique. Results: Fat accumulation in the liver rather than in skeletal muscle was associated with features of insulin resistance, i.e. increased fasting serum (fS) triglycerides and decreased fS-HDL cholesterol, and with hyperinsulinemia and low adiponectin concentrations (Study I). Liver fat content was 4-fold higher in subjects with as compared to those without the metabolic syndrome, independent of age, gender, and BMI. FS-C-peptide was the best correlate of liver fat (Study II). Increased liver fat was associated with both impaired insulin clearance and hepatic insulin resistance independent of age, gender, and BMI (Study III). Type 2 diabetic patients had 80% more liver fat than age-, weight-, and gender-matched non-diabetic subjects. At any given liver fat content, S-ALT underestimated liver fat in the type 2 diabetic patients as compared to the non-diabetic subjects (Study IV). In Study V, hepatic insulin sensitivity increased and glycemic control improved significantly during rosiglitazone treatment. This was associated with lowering of liver fat (on the average by 46%) and insulin requirements (40%). Conclusions: Liver fat is increased both in the metabolic syndrome and type 2 diabetes independent of age, gender, and BMI. A fatty liver is associated with both hepatic insulin resistance and impaired insulin clearance. Rosi-glitazone may be particularly effective in type 2 diabetic patients who are poorly controlled despite using high insulin doses.

Adipose tissue inflammation, liver fat and insulin resistance in humans

BACKGROUND: Obesity is closely associated with insulin resistance, which is a pathophysiologic condition contributing to the important co-morbidities of obesity, such as the metabolic syndrome and type 2 diabetes mellitus. In obese subjects, adipose tissue is characterized by inflammation (macrophage infiltration, increased expression insulin resistance genes and decreased expression of insulin sensitivity genes). Increased liver fat, without excessive alcohol consumption, is defined as non-alcoholic fatty liver disease (NAFLD) and also associated with obesity and insulin resistance. It is unknown whether and how insulin resistance is associated with altered expression of adipocytokines (adipose tissue-derived signaling molecules), and whether adipose tissue inflammation and NAFLD coexist independent of obesity. Genetic factors could explain variation in liver fat independent of obesity but the heritability of NAFLD is unknown. AIMS: To determine whether acute regulation of adipocytokine expression by insulin in adipose tissue is altered in obesity. To investigate the relationship between adipose tissue inflammation and liver fat content independent of obesity. To assess the heritability of serum alanine aminotransferase (ALT) activity, a surrogate marker of liver fat. METHODS: 55 healthy normal-weight and obese volunteers were recruited. Subcutaneous adipose tissue biopsies were obtained for measurement of gene expression before and during 6 hours of euglycemic hyperinsulinemia. Liver fat content was measured by proton magnetic resonance spectroscopy, and adipose tissue inflammation was assessed by gene expression, immunohistochemistry and lipidomics analysis. Genetic factors contributing to serum ALT activity were determined in 313 twins by statistical heritability modeling. RESULTS: During insulin infusion the expression of insulin sensitivity genes remains unchanged, while the expression of insulin resistance genes increases in obese/insulin-resistant subjects compared to insulin-sensitive subjects. Adipose tissue inflammation is associated with liver fat content independent of obesity. Adipose tissue of subjects with high liver fat content is characterized infiltrated macrophages and increased expression of inflammatory genes, as well as by increased concentrations of ceramides compared to equally obese subjects with normal liver fat. A significant heritability for serum ALT activity was verified. CONCLUSIONS: Effects of insulin infusion on adipose tissue gene expression in obese/insulin-resistant subjects are not only characterized by hyporesponse of insulin sensitivity genes but also by hyperresponse of insulin resistance and inflammatory genes. This suggests that in obesity, the impaired insulin action contributes or self-perpetuates alterations in adipocytokine expression in adipose tissue. Adipose tissue inflammation is increased in subjects with high liver fat compared to equally obese subjects with normal liver fat content. Concentrations of ceramides, the putative mediators of insulin resistance, are increased in adipose tissue in subjects with high liver fat. Genetic factors contribute significantly to variation in serum ALT activity, a surrogate marker of liver fat. These data imply that adipose tissue inflammation and increased liver fat content are closely interrelated, and determine insulin resistance even independent of obesity.

Optimal Risk Adoption: A Real Options Approach

This study develops a real options approach for analyzing the optimal risk adoption policy in an environment where the adoption means a switch from one stochastic flow representation into another. We establish that increased volatility needs not decelerate investment, as predicted by the standard literature on real options, once the underlying volatility of the state is made endogenous. We prove that for a decision maker with a convex (concave) objective function, increased post-adoption volatility increases (decreases) the expected cumulative present value of the post-adoption profit flow, which consequently decreases (increases) the option value of waiting and, therefore, accelerates (decelerates) current investment.

Bank Run Risk and Optimal Reserves

We characterize the optimal reserves, and the generated probability of a bank run, as a function of the penalty imposed by the central bank, the probability of depositors’ liquidity needs, and the return on outside investment opportunities.

The Effect of Obesity on Wages and Employment: The Difference Between Having a High BMI and Being Fat

In this paper, we re-examine the relationship between overweight and labour market success, using indicators of individual body composition along with BMI (Body Mass Index). We use the dataset from Finland in which weight, height, fat mass and waist circumference are not self-reported, but obtained as part of the overall health examination. We find that waist circumference, but not weight or fat mass, has a negative effect on wages for women, whereas all measures of obesity have negative effects on women’s employment probabilities. For men, the only obesity measure that is significant for men’s employment probabilities is fat mass. One interpretation of our findings is that the negative wage effects of overweight on wages run through the discrimination channel, but that the negative effects of overweight on employment have more to do with ill health. All in all, measures of body composition provide a more refined picture about the effects of obesity on wages and employment.