Deep Ultraviolet Copper(I) Thiocyanate (CuSCN) Photodetectors Based on Coplanar Nanogap Electrodes Fabricated via Adhesion Lithography.

Adhesion lithography (a-Lith) is a versatile fabrication technique used to produce asymmetric coplanar electrodes separated by a <15 nm nanogap. Here, we use a-Lith to fabricate deep ultraviolet (DUV) photodetectors by combining coplanar asymmetric nanogap electrode architectures (Au/Al) with solution-processable wide-band-gap (3.5-3.9 eV) p-type semiconductor copper(I) thiocyanate (CuSCN). Because of the device's unique architecture, the detectors exhibit high responsivity (≈79 A W-1) and photosensitivity (≈720) when illuminated with a DUV-range (λpeak = 280 nm) light-emitting diode at 220 µW cm-2. Interestingly, the photosensitivity of the photodetectors remains fairly high (≈7) even at illuminating intensities down to 0.2 µW cm-2. The scalability of the a-Lith process combined with the unique properties of CuSCN paves the way to new forms of inexpensive, yet high-performance, photodetectors that can be manufactured on arbitrary substrate materials including plastic.

Analysis of Schottky Contact Formation in Coplanar Au/ZnO/Al Nanogap Radio Frequency Diodes Processed from Solution at Low Temperature.

Much work has been carried out in recent years in fabricating and studying the Schottky contact formed between various metals and the n-type wide bandgap semiconductor zinc oxide (ZnO). In spite of significant progress, reliable formation of such technologically interesting contacts remains a challenge. Here, we report on solution-processed ZnO Schottky diodes based on a coplanar Al/ZnO/Au nanogap architecture and study the nature of the rectifying contact formed at the ZnO/Au interface. Resultant diodes exhibit excellent operating characteristics, including low-operating voltages (±2.5 V) and exceptionally high current rectification ratios of >10(6) that can be independently tuned via scaling of the nanogap's width. The barrier height for electron injection responsible for the rectifying behavior is studied using current-voltage-temperature and capacitance-voltage measurements (C-V) yielding values in the range of 0.54-0.89 eV. C-V measurements also show that electron traps present at the Au/ZnO interface appear to become less significant at higher frequencies, hence making the diodes particularly attractive for high-frequency applications. Finally, an alternative method for calculating the Richardson constant is presented yielding a value of 38.9 A cm(-2) K(-2), which is close to the theoretically predicted value of 32 A cm(-2) K(-2). The implications of the obtained results for the use of these coplanar Schottky diodes in radio frequency applications is discussed.

Radio Frequency Coplanar ZnO Schottky Nanodiodes Processed from Solution on Plastic Substrates.

Coplanar radio frequency Schottky diodes based on solution-processed C60 and ZnO semiconductors are fabricated via adhesion-lithography. The development of a unique asymmetric nanogap electrode architecture results in devices with a high current rectification ratio (10(3) -10(6) ), low operating voltage (<3 V), and cut-off frequencies of >400 MHz. Device fabrication is scalable and can be performed at low temperatures even on plastic substrates with very high yield.

Sub-15-nm patterning of asymmetric metal electrodes and devices by adhesion lithography.

Coplanar electrodes formed from asymmetric metals separated on the nanometre length scale are essential elements of nanoscale photonic and electronic devices. Existing fabrication methods typically involve electron-beam lithography--a technique that enables high fidelity patterning but suffers from significant limitations in terms of low throughput, poor scalability to large areas and restrictive choice of substrate and electrode materials. Here, we describe a versatile method for the rapid fabrication of asymmetric nanogap electrodes that exploits the ability of selected self-assembled monolayers to attach conformally to a prepatterned metal layer and thereby weaken adhesion to a subsequently deposited metal film. The method may be carried out under ambient conditions using simple equipment and a minimum of processing steps, enabling the rapid fabrication of nanogap electrodes and optoelectronic devices with aspect ratios in excess of 100,000.

Polymer reinforcement using liquid-exfoliated boron nitride nanosheets.

We have exfoliated hexagonal boron nitride by ultrasonication in solutions of polyvinylalcohol in water. The resultant nanosheets are sterically stabilised by adsorbed polymer chains. Centrifugation-based size-selection was used to give dispersions of nanosheets with aspect ratio (length/thickness) of ∼1400. Such dispersions can be used to produce polyvinylalcohol-BN composite films. Helium ion microscopy of fracture surfaces shows the nanosheets to be well dispersed and the composites to fail by pull-out. We find both modulus, Y, and strength, σ(B), of these composites to increase linearly with volume fraction, V(f), up to V(f)∼ 0.1 vol% BN before falling off. The rates of increase are extremely high; dY/dV(f) = 670 GPa and dσ(B)/dV(f) = 47 GPa. The former value matches theory based on continuum mechanics while the latter value is consistent with remarkably high polymer-filler interfacial strength. However, because the mechanical properties increase over such a narrow volume fraction range, the maximum values of both modulus and strength are only ∼40% higher than the pure polymer. This phenomenon has also been observed for graphene-filled composites and represents a serious hurdle to the production of high performance polymer-nanosheet composites.

Differential cognitive deterioration in dementia: a two year longitudinal study.

The ability to predict cognitive deterioration in patients with dementia holds valuable potential for clinical trials and early intervention. This study identified cognitive domains deteriorating differentially over time as well as baseline predictors of subsequent cognitive decline in patients referred to a memory clinic. Twenty-six subjects with Alzheimer's disease (AD) and 43 subjects with Subjective Memory Impairment (SMI) were entered into a longitudinal study in which cognitive function was assessed at baseline and at 8-monthly intervals for 2 years, using a range of well-validated measures. Thirty-seven patients with depression and 39 healthy controls were also longitudinally assessed. AD was associated with disproportionate deterioration over time on general measures of cognitive function, multiple measures of mnemonic processing, mental fluency (letter and category), and aspects of motor speed. SMI showed restricted relative cognitive deterioration on general measures of cognitive function, on a subset of memory measures, and on letter but not category fluency. Secondary analysis showed that earliest detectable ADAS-cog and MMSE decline in AD was at 16 months, while several specific neuropsychological indices were sensitive as early as 8 months (graded naming test, semantic naming, and the category/letter fluency tests). In combination, baseline/early changes in cognitive performance, alongside clinical measures, predicted 48% of disease progression over two years in memory impaired patients as a whole. These findings have implications for identifying patients likely to benefit from disease modifying agents, and for designing, powering, enriching, and implementing future clinical trials. Follow-up studies in independent populations are needed to validate predictive algorithms identified.

Does ketamine mimic aspects of schizophrenic speech?

Speech disturbances are well-known symptoms contributing to the diagnosis of schizophrenia. Subanesthetic doses of the N-methyl-D-aspartate (NMDA) antagonist ketamine have been reported to produce positive and negative symptoms and cognitive impairments consistent with those seen in schizophrenia. Insofar as this is true, it constitutes evidence that the NMDA system is involved in schizophrenia. It is therefore of interest to know whether ketamine produces speech disturbances like those of schizophrenia. Quantitative computer-aided analysis of apparently normal speech can detect clinically relevant changes and differences that are not noticeable to the human observer. Accordingly, in this study, speech samples were analysed for repetitiousness, idea density, and verb density using software developed by the authors. The samples came from two experiments, a within-subjects study of healthy volunteers given intravenous ketamine versus placebo, and a between-groups study of patients diagnosed with schizophrenia and comparable healthy controls.Our primary hypothesis was that in both schizophrenia and ketamine, repetitiousness would increase, since perserverative speech is a well-known symptom of schizophrenia. Our secondary hypotheses were that in both schizophrenia and ketamine, idea density and verb density would decrease as indicators of cognitive impairment. The primary hypothesis was confirmed in the schizophrenia experiment (between groups) and the ketamine experiment (within subjects). The secondary hypotheses were disconfirmed except that in the ketamine experiment, verb density was significantly lowered. Reduced use of verbs apparently reflects a cognitive impairment of a different type than repetitiousness, and further investigation is needed to determine whether this impairment occurs in psychosis.

Schizophrenia and the structure of language: the linguist's view.

Patients with schizophrenia often display unusual language impairments. This is a wide ranging critical review of the literature on language in schizophrenia since the 19th century. We survey schizophrenic language level by level, from phonetics through phonology, morphology, syntax, semantics, and pragmatics. There are at least two kinds of impairment (perhaps not fully distinct): thought disorder, or failure to maintain a discourse plan, and schizophasia, comprising various dysphasia-like impairments such as clanging, neologism, and unintelligible utterances. Thought disorder appears to be primarily a disruption of executive function and pragmatics, perhaps with impairment of the syntax-semantics interface; schizophasia involves disruption at other levels. Phonetics is also often abnormal (manifesting as flat intonation or unusual voice quality), but phonological structure, morphology, and syntax are normal or nearly so (some syntactic impairments have been demonstrated). Access to the lexicon is clearly impaired, manifesting as stilted speech, word approximation, and neologism. Clanging (glossomania) is straightforwardly explainable as distraction by self-monitoring. Recent research has begun to relate schizophrenia, which is partly genetic, to the genetic endowment that makes human language possible.

Improving the prediction of final infarct size in acute stroke with bolus delay-corrected perfusion MRI measures.

PURPOSE: To investigate whether bolus delay-corrected dynamic susceptibility contrast (DSC) perfusion MRI measures allowed a more accurate estimation of eventual infarct volume in 14 acute stroke patients using a predictive tissue classifier algorithm. MATERIALS AND METHODS: Tissue classification was performed using a expectation maximization and k-means clustering algorithm utilizing diffusion and T2 measures (diffusion-weighted imaging [DWI], apparent diffusion coefficient [ADC], and T2) combined with uncorrected perfusion measures cerebral blood flow ((CBF) and mean transit time [MTT]), bolus delay-corrected perfusion measures (cCBF and cMTT), and bolus delay-corrected perfusion indices (cCBF and cMTT with bolus delay). RESULTS: The mean similarity index (SI), a kappa-based correlation statistic reflecting the pixel-by-pixel classification agreement between predicted and 30-day T2 lesion volumes, were 0.55 +/- 0.19, 0.61 +/- 0.15 (P < 0.02) and 0.60 +/- 0.17 (P <0.03), respectively. Spearman's correlation coefficients, comparing predicted and final lesion volumes were 0.56 (P < 0.05), 0.70 (P < 0.01), and 0.84 (P < 0.001), respectively. We found a more significant correlation between predicted infarct volumes derived from bolus delay-corrected perfusion measures than from conventional perfusion measures when combined with diffusion measures and compared with final lesion volumes measured on 30-day T2 MRI scans. CONCLUSION: Bolus delay-corrected perfusion measures enable an improved prediction of infarct evolution and evaluation of the hemodynamic status of neuronal tissue in acute stroke.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia.

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood- and adult-onset schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages.

Mapping hippocampal and ventricular change in Alzheimer disease.

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Correlation of quantitative EEG in acute ischemic stroke with 30-day NIHSS score: comparison with diffusion and perfusion MRI.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI) methods such as diffusion- (DWI) and perfusion-weighted (PWI) imaging have been widely studied as surrogate markers to monitor stroke evolution and predict clinical outcome. The utility of quantitative electroencephalography (qEEG) as such a marker in acute stroke has not been intensively studied. The aim of the present study was to correlate ischemic cortical stroke patients' clinical outcomes with acute qEEG, DWI, and PWI data. MATERIALS AND METHODS: DWI and PWI data were acquired from 11 patients within 7 and 16 hours after onset of symptoms. Sixty-four channel EEG data were obtained within 2 hours after the initial MRI scan and 1 hour before the second MRI scan. The acute delta change index (aDCI), a measure of the rate of change of average scalp delta power, was compared with the National Institutes of Health Stroke Scale scores (NIHSSS) at 30 days, as were MRI lesion volumes. RESULTS: The aDCI was significantly correlated with the 30-day NIHSSS, as was the initial mean transit time (MTT) abnormality volume (rho=0.80, P<0.01 and rho=0.79, P<0.01, respectively). Modest correlations were obtained between the 15-hour DWI lesion volume and both the aDCI and 30-day NIHSSS (rho=0.62, P<0.05 and rho=0.73, P<0.05, respectively). CONCLUSIONS: In this small sample the significant correlation between 30-day NIHSSS and acute qEEG data (aDCI) was equivalent to that between the former and MTT abnormality volume. Both were greater than the modest correlation between acute DWI lesion volume and 30-day NIHSSS. These preliminary results indicate that acute qEEG data might be used to monitor and predict stroke evolution.

Detecting dementia: novel neuropsychological markers of preclinical Alzheimer's disease.

The results of a previous study have suggested that impaired performance on one neuropsychological test, CANTAB Paired Associates Learning (PAL), may serve as a marker for preclinical Alzheimer's disease (AD). In a group of individuals with 'questionable dementia', the baseline PAL performance was found to correlate significantly with subsequent deterioration in global cognitive function over an 8-month period. The present paper reports diagnostic outcome data for the same individuals 32 months after the first assessment and evaluates the predictive diagnostic utility of baseline neuropsychological measures. Thirty-two months after joining the study, 11 of the 43 'questionable dementia' patients met the criteria for probable AD diagnosis ('converters') and 29 remained free from AD ('non-converters'). Logistic regression analysis revealed that two tests of memory, in combination, could be used to predict a later diagnosis of probable AD with a high level of accuracy [chi(2)(3) = 47.054, p < 0.0001]. As predicted, these tests are measures of visuospatial learning (CANTAB PAL) and, also, semantic memory (Graded Naming Test). These two tests in combination appear to be highly accurate in detecting cognitive dysfunction characteristic of preclinical AD. Using these tests, a simple algorithm is described for calculating, with 100% accuracy for this sample of 40 patients, the probability that an individual with mild memory impairments will go on to receive a diagnosis of probable AD.

Dynamics of gray matter loss in Alzheimer's disease.

We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimer's disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere > right hemisphere) and correlated with progressively declining cognitive status (p < 0.0006). Novel brain mapping methods allowed us to visualize dynamic patterns of atrophy in 52 high-resolution magnetic resonance image scans of 12 patients with AD (age 68.4 +/- 1.9 years) and 14 elderly matched controls (age 71.4 +/- 0.9 years) scanned longitudinally (two scans; interscan interval 2.1 +/- 0.4 years). A cortical pattern matching technique encoded changes in brain shape and tissue distribution across subjects and time. Cortical atrophy occurred in a well defined sequence as the disease progressed, mirroring the sequence of neurofibrillary tangle accumulation observed in cross sections at autopsy. Advancing deficits were visualized as dynamic maps that change over time. Frontal regions, spared early in the disease, showed pervasive deficits later (>15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 +/- 2.3% per year in AD v 0.9 +/- 0.9% per year in controls) were faster in the left hemisphere (p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.

MR image-based measurement of rates of change in volumes of brain structures. Part II: application to a study of Alzheimer's disease and normal aging.

We present global and regional rates of brain atrophy measured on serially acquired T1-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

Paired associate performance in the early detection of DAT.

Subjects underwent longitudinal neuropsychological assessment in order to retrospectively determine which measures of cognitive function best predicted later development of dementia of the Alzheimer type (DAT). Three groups of subjects were studied: normal controls, patients with early DAT, and questionable dementia subjects (QD). All subjects were assessed using a battery of standard neuropsychological measures and two subtests from the Cambridge Neuropsychological Test Automated Battery (CANTAB), paired associate learning and delayed matching to sample. A structured interview was also used to elicit a profile of the subject's daily functioning. Subjects were assessed every 6 months for 2 years. At the 6 month assessment, almost half of the QD group exhibited significant deterioration in scores on the computerized paired associate learning subtest, while maintaining their scores on standard measures. At the conclusion of the study, all of this QD subgroup fulfilled the NINCDS-ADRDA criteria for probable DAT pertaining to significant cognitive and functional deterioration. Performance on the C

DETECTING DYNAMIC AND GENETIC EFFECTS ON BRAIN STRUCTURE USING HIGH-DIMENSIONAL CORTICAL PATTERN MATCHING.

We briefly describe a set of algorithms to detect and visualize effects of disease and genetic factors on the brain. Extreme variations in cortical anatomy, even among normal subjects, complicate the detection and mapping of systematic effects on brain structure in human populations. We tackle this problem in two stages. First, we develop a cortical pattern matching approach, based on metrically covariant partial differential equations (PDEs), to associate corresponding regions of cortex in an MRI brain image database (N=102 scans). Second, these high-dimensional deformation maps are used to transfer within-subject cortical signals, including measures of gray matter distribution, shape asymmetries, and degenerative rates, to a common anatomic template for statistical analysis. We illustrate these techniques in two applications: (1) mapping dynamic patterns of gray matter loss in longitudinally scanned Alzheimer's disease patients; and (2) mapping genetic influences on brain structure. We extend statistics used widely in behavioral genetics to cortical manifolds. Specifically, we introduce methods based on h-squared distributed random fields to map hereditary influences on brain structure in human populations.