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In the human brain, aversive and appetitive processing have been studied with controlled stimuli in rather static settings. In addition, the extent to which aversive- and appetitive-related processing engage distinct or overlapping circuits remains poorly understood. Here, we sought to investigate the dynamics of aversive and appetitive processing while male and female participants engaged in comparable trials involving threat-avoidance or reward-seeking. A central goal was to characterize the temporal evolution of responses during periods ofthreat or reward imminence. For example, in the aversive domain, we predicted that the bed nucleus of the stria terminalis (BST), but not the amygdala, would exhibit anticipatory responses given the role of the former in anxious apprehension. We also predicted that the periaqueductal gray (PAG) would exhibit threat-proximity responses based on its involvement in proximal-threat processes, and that the ventral striatum would exhibit threat-imminence responses given its role in threat escape in rodents. Overall, we uncovered imminence-related temporally increasing (“ramping”) responses in multiple brain regions, including the BST, PAG, and ventral striatum, subcortically, and dorsal anterior insula and anterior midcingulate, cortically. Whereas the ventral striatum generated anticipatory responses in the proximity of reward as expected, it also exhibited threat-related imminence responses. In fact, across multiple brain regions, we observed a main effect of arousal. In other words, we uncovered extensive temporally-evolving, imminence-related processing in both the aversive and appetitive domain, suggesting that distributed brain circuits are dynamically engaged during the processing of biologically relevant information irrespective of valence, findings further supported by network analysis.Significance StatementIn the human brain, aversive and appetitive processing have been studied with controlled stimuli in rather static settings. Here, we sought to investigate the dynamics of aversive/appetitive processing while participants engaged in trials involving threat-avoidance or reward-seeking. A central goal was to characterize the temporal evolution of responses during periods ofthreat or reward imminence. We uncovered imminence-related temporally increasing (“ramping”) responses in multiple brain regions, including the bed nucleus of the stria terminalis, periaqueductal gray, and ventral striatum, subcortically, and dorsal anterior insula and anterior midcingulate, cortically. Overall, we uncovered extensive temporally-evolving, imminence-related processing in both the aversive and appetitive domain, suggesting that distributed brain circuits are dynamically engaged during the processing of biologically relevant information irrespective of valence.

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20–35 Hz) and fast gamma (36–66 Hz) oscillations in subjects (n = 40) (age: 50–88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8–12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification.

Visual stimulus-induced narrowband gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with Mild Cognitive Impairment or Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive and easily accessible biomarker for early diagnosis of AD. However, to use gamma as a biomarker, its characteristics should remain consistent across multiple recordings, even when separated over long intervals. Previous magnetoencephalography studies in young subjects have reported that gamma power remains consistent over recordings separated by a few weeks to months. Here, we assessed the consistency of slow (20-35 Hz) and fast gamma (36-66 Hz) oscillations induced by static full-field gratings in male (N=20) and female (N=20) elderly subjects (>49 years) in EEG recordings separated by more than a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma oscillations had distinct spectral and temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation, ICC of ∼0.7). Alpha oscillations (8-12 Hz) and steady-state-visually-evoked-potentials (SSVEPs) were also found to be reliable. We further tested how EEG features can be used to identify two recordings as belonging to the same versus different subjects and found high classifier performance (area under ROC curve of ∼0.89), with the temporal evolution of slow gamma and spectral profile emerging as the most informative features. These results suggest that EEG gamma oscillations are reliable across recordings and can be used as a clinical biomarker as well as a potential tool for subject identification.Significance statementWe demonstrate the reliability of stimulus-induced gamma oscillations in elderly humans for the first time in EEG. Since gamma has recently been shown to be compromised in patients with Mild Cognitive Impairment or early Alzheimer’s Disease (AD), together these results mark the first steps towards an EEG based clinical biomarker for early diagnosis of AD. We observed high reliability in the power spectrum, gamma power and its temporal characteristics, within the test-retest period of one year. Alpha and steady-state-visually-evoked potential power were also found to be reliable. These spectral and temporal features could also be used to identify EEG recordings as belonging to the same versus different subjects with high performance, suggesting a potentially key role in subject identification also.

Gamma rhythms (∼20-70 Hz) have been reported to be abnormal in mental disorders such as autism and schizophrenia in humans, and Alzheimer’s disease (AD) models in rodents. However, the effect of normal aging on these oscillations is not known, especially for elderly subjects (>49 years) for which AD is most prevalent. In a first large-scale (236 subjects; 104 females) electroencephalogram (EEG) study on gamma oscillations on elderly subjects (aged 50-88 years), we presented full-screen Cartesian gratings that induced two distinct gamma oscillations (slow: 20-34 Hz and fast: 36-66 Hz). Power and centre frequency significantly decreased with age for both slow and fast gamma, but not alpha (8-12 Hz). Reduction was more salient for fast gamma than slow. These results were independent of microsaccades and pupillary reactivity to stimulus, as well as variations in power spectral density with age. Steady-state visual evoked potentials (SSVEPs) also reduced with age. These results are crucial first steps towards using gamma/SSVEPs as biomarkers of cognitive decline in elderly.Significance statementNo study in humans has examined visual narrow-band gamma oscillations with healthy aging in elderly subjects. In a first large-scale (236 subjects) EEG study on stimulus-induced narrow band gamma in cognitively normal elderly (>49 years) humans, we show that both power and centre frequency of slow and fast gamma (20-34 Hz and 36-66 Hz respectively) decrease with age, but alpha power does not. Steady-state visual evoked potential (SSVEPs) in gamma range also decrease with age. Any EEG-based biomarker is accessible and affordable to patients of a wide socio-economic spectrum. Our results are important steps for developing such screening/diagnostic tests for aging-related diseases, like Alzheimer’s disease.

Alzheimer’s Disease (AD) in elderly adds substantially to socio-economic burden necessitating early diagnosis. While recent studies in rodent models of AD have suggested diagnostic and therapeutic value for gamma rhythms in brain, the same has not been rigorously tested in humans. We recruited a large population (N=247; 106 females) of elderly (>49 years) individuals from the community, who viewed large gratings that induced strong gamma oscillations in their electroencephalogram (EEG). These individuals were classified as healthy (N=227), mild-cognitively-impaired (MCI; 14) or AD (6) based on clinical history and Clinical Dementia Rating scores. Surprisingly, stimulus-induced gamma rhythms, but not alpha or steady-state-visually-evoked-responses, were significantly lower in both MCI and AD patients compared to their age and gender matched controls. This reduction was not due to differences in eye movements or baseline power. Our results suggest that gamma could be used as potential diagnostic tool for MCI/AD in humans.One Sentence SummaryA large double-blinded EEG study suggests that narrow-band visual gamma rhythms are weaker in MCI/AD patients compared to cognitively healthy controls.

Recent studies have shown the existence of two gamma rhythms in the hippocampus subserving different functions but, to date, primate studies in primary visual cortex have reported a single gamma rhythm. Here, we show that large visual stimuli induce a slow gamma (25–45 Hz) in area V1 of two awake adult female bonnet monkeys and in the EEG of 15 human subjects (7 males and 8 females), in addition to the traditionally known fast gamma (45–70 Hz). The two rhythms had different tuning characteristics for stimulus orientation, contrast, drift speed, and size. Further, fast gamma had short latency, strongly entrained spikes and was coherent over short distances, reflecting short-range processing, whereas slow gamma appeared to reflect long-range processing. Together, two gamma rhythms can potentially provide better coding or communication mechanisms and a more comprehensive biomarker for diagnosis of mental disorders.SIGNIFICANCE STATEMENTGamma rhythm has been associated with high-level cognitive functions such as attention and feature binding and has been reported to be abnormal in brain disorders such as autism and schizophrenia. Unlike previous studies that have shown a single gamma rhythm in the primate visual cortex, we found that large visual gratings induce two distinct gamma oscillations in both monkey LFP and human EEG. These rhythms, termed slow (25–45 Hz) and fast (45–70 Hz), exhibited distinct tuning preferences, latencies, and coherence profiles, potentially reflecting processing at two different ranges. Multiple gamma oscillations in visual cortex may provide a richer representation of external visual stimuli and could be used for developing brain–machine interfacing applications and screening tests for neuropsychiatric disorders.

Wind energy conversion systems have become a focal point in the research of renewable energy sources. This is in no small part due to the rapid advances in the size of wind generators as well as the development of power electronics and their applicability in wind energy extraction. This paper provides a comprehensive review of past and present converter topologies applicable to permanent magnet generators, induction generators, synchronous generators and doubly fed induction generators. The many different generator–converter combinations are compared on the basis of topology, cost, efficiency, power consumption and control complexity. The features of each generator–converter configuration are considered in the context of wind turbine systems. &nbsp

Reproductive factors are not considered to play a significant role in the aetiology of breast cancer in low incidence regions like Gujarat, although it is well established that they exert a major influence on such tumours in the western developed world. Women in the western Indian region have a very low prevalence of smoking, alcohol consumption but a high prevalence of vegetarianism. Noting the changes in the life style practices with increasing affluence is likely to yield several interesting findings in such a population. Physical activity and dietary factors have emerged as important parameters and their lack may contribute significantly to the risk of breast cancers. The breast cancer risk significantly increased with higher consumption of total fat (25% of total calories), frequent intake of fried foods and sweets. A significant protection was offered by frequent consumption of green yellow leafy vegetables, foods rich in b-carotene and isoflavonoids. The present study demonstrated a good protective effect of dietary intake of antioxidant vitamins. The breast cancer risk increases with elevation of circulating lipid components except HDL-cholesterol.

Real-time (RT) simulation is a highly reliable simulation method that is mostly based on electromagnetic transient simulation of complex systems comprising many domains. It is increasingly used in power and energy systems for both academic research and industrial applications. Due to the evolution of the computing power of RT simulators in recent years, new classes of applications and expanded fields of practice could now be addressed with RT simulation. This increase in computation power implies that models can be built more accurately and the whole simulation system gets closer to reality. This Task Force paper summarizes various applications of digital RT simulation technologies in the design, analysis, and testing of power and energy systems.

This task force paper summarizes the state-of-the-art real-time digital simulation concepts and technologies that are used for the analysis, design, and testing of the electric power system and its apparatus. This paper highlights the main building blocks of the real-time simulator, i.e., hardware, software, input-output systems, modeling, and solution techniques, interfacing capabilities to external hardware and various applications. It covers the most commonly used real-time digital simulators in both industry and academia. A comprehensive list of the real-time simulators is provided in a tabular review. The objective of this paper is to summarize salient features of various real-time simulators, so that the reader can benefit from understanding the relevant technologies and their applications, which will be presented in a separate paper.