Distinctive retinal peri-arteriolar versus peri-venular amyloid plaque distribution correlates with the cognitive performance.

Introduction: The vascular contribution to Alzheimer's disease (AD) is tightly connected to cognitive performance across the AD continuum. We topographically describe retinal perivascular amyloid plaque (AP) burden in subjects with normal or impaired cognition. Methods: Using scanning laser ophthalmoscopy, we quantified retinal peri-arteriolar and peri-venular curcumin-positive APs in the first, secondary and tertiary branches in twenty-eight subjects. Perivascular AP burden among cognitive states was correlated with neuroimaging and cognitive measures. Results: Peri-arteriolar exceeded peri-venular AP count (p<0.0001). Secondary branch AP count was significantly higher in cognitively impaired (p<0.01). Secondary small and tertiary peri-venular AP count strongly correlated with clinical dementia rating, hippocampal volumes, and white matter hyperintensity count. Discussion: Our topographic analysis indicates greater retinal amyloid accumulation in the retinal peri-arteriolar regions overall, and distal peri-venular regions in cognitively impaired individuals. Larger longitudinal studies are warranted to understand the temporal-spatial relationship between vascular dysfunction and perivascular amyloid deposition in AD. Highlights: Retinal peri-arteriolar region exhibits more amyloid compared with peri-venular regions.Secondary retinal vascular branches have significantly higher perivascular amyloid burden in subjects with impaired cognition, consistent across sexes.Cognitively impaired individuals have significantly greater retinal peri-venular amyloid deposits in the distal small branches, that correlate with CDR and hippocampal volumes.

Retinal Venular Tortuosity Jointly with Retinal Amyloid Burden Correlates with Verbal Memory Loss: A Pilot Study.

INTRODUCTION: Retinal imaging is a non-invasive tool to study both retinal vasculature and neurodegeneration. In this exploratory retinal curcumin-fluorescence imaging (RFI) study, we sought to determine whether retinal vascular features combined with retinal amyloid burden correlate with the neurocognitive status. METHODS: We used quantitative RFI in a cohort of patients with cognitive impairment to automatically compute retinal amyloid burden. Retinal blood vessels were segmented, and the vessel tortuosity index (VTI), inflection index, and branching angle were quantified. We assessed the correlations between retinal vascular and amyloid parameters, and cognitive domain Z-scores using linear regression models. RESULTS: Thirty-four subjects were enrolled and twenty-nine (55% female, mean age 64 ± 6 years) were included in the combined retinal amyloid and vascular analysis. Eleven subjects had normal cognition and 18 had impaired cognition. Retinal VTI was discriminated among cognitive scores. The combined proximal mid-periphery amyloid count and venous VTI index exhibited significant differences between cognitively impaired and cognitively normal subjects (0.49 ± 1.1 vs. 0.91 ± 1.4, p = 0.006), and correlated with both the Wechsler Memory Scale-IV and SF-36 mental component score Z-scores (p < 0.05). CONCLUSION: This pilot study showed that retinal venular VTI combined with the proximal mid-periphery amyloid count could predict verbal memory loss. Future research is needed to finesse the clinical application of this retinal imaging-based technology.

Sectoral segmentation of retinal amyloid imaging in subjects with cognitive decline.

INTRODUCTION: Despite advances in imaging retinal amyloidosis, a quantitative and topographical investigation of retinal amyloid beta burden in patients with cognitive decline has never been reported. METHODS: We used the specific amyloid-binding fluorophore curcumin and laser ophthalmoscopy to assess retinal amyloid imaging (RAI) in 34 patients with cognitive decline. We automatically quantified retinal amyloid count (RAC) and area in the superotemporal retinal sub-regions and performed correlation analyses with cognitive and brain volumetric parameters. RESULTS: RAC significantly and inversely correlated with hippocampal volume (HV; r = -0.39, P = .04). The proximal mid-periphery (PMP) RAC and RA areas were significantly greater in patients with Montreal Cognitive Assessment (MOCA) score < 26 (P = .01; Cohen d = 0.83 and 0.81, respectively). PMP showed significantly more RAC and area in subjects with amnestic mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared to cognitively normal (P = .04; Cohen d = 0.83). CONCLUSION: Quantitative RAI is a feasible technique and PMP RAC may predict HV. Future larger studies should determine RAI's potential as a biomarker of early AD.

Efficient sample density estimation by combining gridding and an optimized kernel.

The reconstruction of non-Cartesian k-space trajectories often requires the estimation of nonuniform sampling density. Particularly for 3D, this calculation can be computationally expensive. The method proposed in this work combines an iterative algorithm previously proposed by Pipe and Menon (Magn Reson Med 1999;41:179-186) with the optimal kernel design previously proposed by Johnson and Pipe (Magn Reson Med 2009;61:439-447). The proposed method shows substantial time reductions in estimating the densities of center-out trajectories, when compared with that of Johnson. It is demonstrated that, depending on the trajectory, the proposed method can provide reductions in execution time by factors of 12 to 85. The method is also shown to be robust in areas of high trajectory overlap, when compared with two analytical density estimation methods, producing a 10-fold increase in accuracy in one case. Initial conditions allow the proposed method to converge in fewer iterations and are shown to be flexible in terms of the accuracy of information supplied. The proposed method is not only one of the fastest and most accurate algorithms, it is also completely generic, allowing any arbitrary trajectory to be density compensated extemporaneously. The proposed method is also simple and can be implemented on parallel computing platforms in a straightforward manner.

A new design and rationale for 3D orthogonally oversampled k-space trajectories.

A novel center-out 3D trajectory for sampling magnetic resonance data is presented. The trajectory set is based on a single Fermat spiral waveform, which is substantially undersampled in the center of k-space. Multiple trajectories are combined in a "stacked cone" configuration to give very uniform sampling throughout a "hub," which is very efficient in terms of gradient performance and uniform trajectory spacing. The fermat looped, orthogonally encoded trajectories (FLORET) design produces less gradient-efficient trajectories near the poles, so multiple orthogonal hub designs are shown. These multihub designs oversample k-space twice with orthogonal trajectories, which gives unique properties but also doubles the minimum scan time for critical sampling of k-space. The trajectory is shown to be much more efficient than the conventional stack of cones trajectory, and has nearly the same signal-to-noise ratio efficiency (but twice the minimum scan time) as a stack of spirals trajectory. As a center-out trajectory, it provides a shorter minimum echo time than stack of spirals, and its spherical k-space coverage can dramatically reduce Gibbs ringing.

Rigid body motion compensation for spiral projection imaging.

Spiral projection imaging (SPI) is a 3D, spiral based magnetic resonance imaging (MRI) acquisition scheme that allows for self-navigated motion estimation of all six degrees-of-freedom. The trajectory, a set of spiral planes, is enhanced to accommodate motion tracking by adding orthogonal planes. Rigid-body motion tracking is accomplished by comparing the overlapping data and deducing the motion that is consistent with the comparisons. The accuracy of the proposed method is quantified for simulated data and for data collected using both a phantom and a volunteer. These tests were repeated to measure the effect of off-resonance blurring, coil sensitivity, gradient warping, undersampling, and nonrigid motion (e.g., neck). The artifacts of off-resonance, coils sensitivity, and gradient warping impose an unnotable effect on the accuracy of motion estimation. The worst mean accuracy is 0.15° and 0.20 mm for the phantom while the worst mean accuracy is 0.48° and 0.34 mm when imaging a brain, indicating that the nonrigid component in human subjects slightly degrades accuracy. When applied to in vivo motion, the proposed technique considerably reduces motion artifact.

Convolution kernel design and efficient algorithm for sampling density correction.

Sampling density compensation is an important step in non-cartesian image reconstruction. One of the common techniques to determine weights that compensate for differences in sampling density involves a convolution. A new convolution kernel is designed for sampling density attempting to minimize the error in a fully reconstructed image. The resulting weights obtained using this new kernel are compared with various previous methods, showing a reduction in reconstruction error. A computationally efficient algorithm is also presented that facilitates the calculation of the convolution of finite kernels. Both the kernel and the algorithm are extended to 3D.

Automated optimal detection and classification of neural action potentials in extra-cellular recordings.

Determination of single unit spikes from multiunit spike trains plays a critical role in neurophysiological coding studies which require information about the precise timing of events underlying the neural codes that are the basis of behavior. Searching for optimal spike detection strategies has therefore been the focus of many studies over the past two decades. In this study we describe and implement an algorithm for the optimal real time detection and classification of neural spikes. The algorithm consists of three steps: noise analysis, template generation and real time detection and classification. The first step involves estimating the background noise statistics. In this step, a "cap-fitting" algorithm is used to automatically detect a spike free segment and then the mean, standard deviation and autocorrelation function of the noise are computed. The second step involves generating optimal templates of the spikes from a segment containing both noise and multiunit activity. In this step, a generalized matched filter is used to isolate a set of preliminary spikes from the noise. The first principal component of previously recorded templates is used as the deterministic signal. The preliminary spikes are then clustered in a sub-space spanned by the first three principal components to form new templates. The third step uses these templates for the real time spike detection and classification. In this step the incoming data are projected into a lower dimensional space that is designed to maximally separate the signal from the noise energy. This algorithm provides an accurate estimate of the signal to noise ratio and provides an accurate estimate of spike times and spike shapes.

A dense array stimulator to generate arbitrary spatio-temporal tactile stimuli.

The generation and presentation of tactile stimuli presents a unique challenge. Unlike vision and audition, in which standard equipment such as monitors and audio systems can be used for most experiments, tactile stimuli and/or stimulators often have to be tailor-made for a given study. Here, we present a novel tactile stimulator designed to present arbitrary spatio-temporal stimuli to the skin. The stimulator consists of 400 pins, arrayed over a 1cm(2) area, each under independent computer control. The dense array allows for an unprecedented number of stimuli to be presented within an experimental session (e.g., up to 1200 stimuli per minute) and for stimuli to be generated adaptively. The stimulator can be used in a variety of modes and can deliver indented and scanned patterns as well as stimuli defined by mathematical spatio-temporal functions (e.g., drifting sinusoids). We describe the hardware and software of the system, and discuss previous and prospective applications.

Dynamic gain changes during attentional modulation.

Attention causes a multiplicative effect on firing rates of cortical neurons without affecting their selectivity (Motter, 1993; McAdams & Maunsell, 1999a) or the relationship between the spike count mean and variance (McAdams & Maunsell, 1999b). We analyzed attentional modulation of the firing rates of 144 neurons in the secondary somatosensory cortex (SII) of two monkeys trained to switch their attention between a tactile pattern recognition task and a visual task. We found that neurons in SII cortex also undergo a predominantly multiplicative modulation in firing rates without affecting the ratio of variance to mean firing rate (i.e., the Fano factor). Furthermore, both additive and multiplicative components of attentional modulation varied dynamically during the stimulus presentation. We then used a standard conductance-based integrate-and-fire model neuron to ascertain which mechanisms might account for a multiplicative increase in firing rate without affecting the Fano factor. Six mechanisms were identified as biophysically plausible ways that attention could modify the firing rate: spike threshold, firing rate adaptation, excitatory input synchrony, synchrony between all inputs, membrane leak resistance, and reset potential. Of these, only a change in spike threshold or in firing rate adaptation affected model firing rates in a manner compatible with the observed neural data. The results indicate that only a limited number of biophysical mechanisms can account for observed attentional modulation.

The Helix: a multi-modal tactile stimulator for human functional neuroimaging.

In order to expand the repertoire of somatosensory functions that can be effectively studied through functional MRI, we have developed a tactile stimulator which can deliver rich and varied combinations of stimulation that simulate natural tactile exploration. The system is computer controlled and compatible with an MRI environment. Complex aspects of somesthesis can thus be studied independent of confounds introduced by motor activity or problems with precision, accuracy or reproducibility of stimulus delivery.

Spatiotemporal receptive fields of peripheral afferents and cortical area 3b and 1 neurons in the primate somatosensory system.

Neurons in area 3b have been previously characterized using linear spatial receptive fields with spatially separated excitatory and inhibitory regions. Here, we expand on this work by examining the relationship between excitation and inhibition along both spatial and temporal dimensions and comparing these properties across anatomical areas. To that end, we characterized the spatiotemporal receptive fields (STRFs) of 32 slowly adapting type 1 (SA1) and 21 rapidly adapting peripheral afferents and of 138 neurons in cortical areas 3b and 1 using identical random probe stimuli. STRFs of peripheral afferents consist of a rapidly appearing excitatory region followed by an in-field (replacing) inhibitory region. STRFs of SA1 afferents also exhibit flanking (surround) inhibition that can be attributed to skin mechanics. Cortical STRFs had longer time courses and greater inhibition compared with peripheral afferent STRFs, with less replacing inhibition in area 1 neurons compared with area 3b neurons. The greater inhibition observed in cortical STRFs point to the existence of underlying intracortical mechanisms. In addition, the shapes of excitatory and inhibitory lobes of both peripheral and cortical STRFs remained mostly stable over time, suggesting that their feature selectivity remains constant throughout the time course of the neural response. Finally, the gradual increase in the proportion of surround inhibition from the periphery to area 3b to area 1, and the concomitant decrease in response linearity of these neurons indicate the emergence of increasingly feature-specific response properties along the somatosensory pathway.

A continuum mechanical model of mechanoreceptive afferent responses to indented spatial patterns.

Information about the spatial structure of tactile stimuli is conveyed by slowly adapting type 1 (SA1) and rapidly adapting (RA) afferents innervating the skin. Here, we investigate how the spatial properties of the stimulus shape the afferent response. To that end, we present an analytical framework to characterize SA1 and RA responses to a wide variety of spatial patterns indented into the skin. This framework comprises a model of the tissue deformation produced by any three-dimensional indented spatial pattern, along with an expression that converts the deformation at the receptor site into a neural response. We evaluated 15 candidate variables for the relevant receptor deformation and found that physical quantities closely related to local membrane stretch were most predictive of the observed afferent responses. The main outcome of this study is an accurate working model of SA1 and RA afferent responses to indented spatial patterns.

Fingertip skin conformance accounts, in part, for differences in tactile spatial acuity in young subjects, but not for the decline in spatial acuity with aging.

The ability of the skin to conform to the spatial details of a surface or an object is an essential part of our ability to discriminate fine spatial features haptically. In this study, we examined the extent to which differences in tactual acuity between subjects of the same age and between younger and older subjects can be accounted for by differences in the properties of the skin. We did so by measuring skin conformance and tactile spatial acuity in the glabrous skin at the fingertip in 18 younger (19-36 years old) and 9 older (61-69 years old) subjects. Skin conformance was measured as the degree to which the skin invaded the spaces in the psychophysical stimuli. There were several findings. First, skin conformance accounted for 50% of the variance in our measure of tactile spatial acuity (the threshold for grating orientation discrimination) between the younger subjects. The subjects with more compliant skin had substantially lower thresholds than did the subjects with stiffer skin. Second, the skin of the younger subjects was more compliant across than along the skin ridges, and this translated into significantly greater performance when the gratings were oriented along than when oriented across the skin. Third, skin conformance was virtually identical in the younger and the older subjects. Consequently, skin conformance cannot account for the loss of spatial acuity reported in earlier studies and confirmed in this study. We infer that the loss must be neural in origin.

Receptive field structure in cortical area 3b of the alert monkey.

More than 350 neurons with fingerpad receptive fields (RFs) were studied in cortical area 3b of three alert monkeys. Random dot patterns, which contain all stimulus patterns with equal probability, were scanned across these RFs at three velocities and eight directions to reveal the RFs' spatial and temporal structure. Area 3b RFs are characterized by three components: (1) a single, central excitatory region of short duration, (2) one or more inhibitory regions, also of short duration, that are adjacent to and nearly synchronous with the excitation, and (3) a region of inhibition that overlaps the excitation partially or totally and is temporally delayed with respect to the first two components. As a result of these properties, RF spatial structure depends on scanning direction but is virtually unaffected by changes in scanning velocity. This RF characterization, which is derived solely from responses to scanned random-dot patterns, predicts a neuron's responses to random patterns accurately, as expected, but it also predicts orientation sensitivity and preferred orientation measured with a scanned bar. Both orientation sensitivity and the ratio of coincident inhibition (number 2 above) to excitation are stronger in the supra- and infragranular layers than in layer IV.

Spatial acuity after digit amputation.

Digit amputation in human and non-human primates results in reorganization of somatosensory cortex in which the representations of adjacent, intact digits expand to fill the cortical region previously devoted to the amputated digits. Whether this expanded representation results in improved sensory performance has not been determined. Consequently, we measured the ability to recognize small objects (raised letters) with a digit adjacent to the amputation and the same digit on the normal, contralateral hand in 15 amputees. The same digits were also tested in 15 age-matched, amputation-free subjects. There was no significant difference in recognition scores between digits in the amputees or between amputees and control subjects. More detailed analyses of specific confusion patterns and of the improvement with practice showed no significant differences. As far as we could determine, the cortical expansion that is presumed to accompany digit amputation had no effect on tactile pattern recognition performance.

Synchrony: a neuronal mechanism for attentional selection?

Attentional selection involves brain processes that select and control the flow of information into the mechanisms that underlie perception and consciousness. One theory proposes that the neural activity that represents the stimuli or events to be attended to is selected through modification of its synchrony. Recent experimental evidence supports this theory, by showing that changes in attentional focus increase the synchrony of neural firing in some neuron pairs and decrease it in others.

Neural coding and the basic law of psychophysics.

There have been three main ideas about the basic law of psychophysics. In 1860, Fechner used Weber's law to infer that the subjective sense of intensity is related to the physical intensity of a stimulus by a logarithmic function (the Weber-Fechner law). A hundred years later, Stevens refuted Fechner's law by showing that direct reports of subjective intensity are related to the physical intensity of stimuli by a power law. MacKay soon showed, however, that the logarithmic and power laws are indistinguishable without examining the underlying neural mechanisms. Mountcastle and his colleagues did so, and, on the basis of transducer functions obeying power laws, inferred that subjective intensity must be related linearly to the neural coding measure on which it is based. In this review, we discuss these issues and we review a series of studies aimed at the neural mechanisms of a very complex form of subjective experience-the experience of roughness produced by a textured surface. The results, which are independent of any assumptions about the form of the psychophysical law, support the idea that the basic law of psychophysics is linearity between subjective experience and the neural activity on which it is based.