Two sensory neurons usually display trial-by-trial spike-count correlations given the repeated representations of a stimulus. The effects of such response correlations on population-level sensory coding have been the focal contention in computational neuroscience over the past few years. In the meantime, multivariate pattern analysis (MVPA) has become the leading analysis approach in functional magnetic resonance imaging (fMRI), but the effects of response correlations among voxel populations remain underexplored. Here, instead of conventional MVPA analysis, we calculate linear Fisher information of population responses in human visual cortex (five males, one female) and hypothetically remove response correlations between voxels. We found that voxelwise response correlations generally enhance stimulus information, a result standing in stark contrast to the detrimental effects of response correlations reported in empirical neurophysiological studies. By voxel-encoding modeling, we further show that these two seemingly opposite effects actually can coexist within the primate visual system. Furthermore, we use principal component analysis to decompose stimulus information in population responses onto different principal dimensions in a high-dimensional representational space. Interestingly, response correlations simultaneously reduce and enhance information on higher- and lower-variance principal dimensions, respectively. The relative strength of the two antagonistic effects within the same computational framework produces the apparent discrepancy in the effects of response correlations in neuronal and voxel populations. Our results suggest that multivariate fMRI data contain rich statistical structures that are directly related to sensory information representation, and the general computational framework to analyze neuronal and voxel population responses can be applied in many types of neural measurements.
Experiments reveal that in the dorsal medial superior temporal (MSTd) and the ventral intraparietal (VIP) areas, where visual and vestibular cues are integrated to infer heading direction, there are two types of neurons with roughly the same number. One is “congruent” cells, whose preferred heading directions are similar in response to visual and vestibular cues; and the other is “opposite” cells, whose preferred heading directions are nearly “opposite” (with an offset of 180 degree) in response to visual vs. vestibular cues. Congruent neurons are known to be responsible for cue integration, but the computational role of opposite neurons remains largely unknown. Here, we propose that opposite neurons may serve to encode the disparity information between cues necessary for multisensory segregation. We build a computational model composed of two reciprocally coupled modules, MSTd and VIP, and each module consists of groups of congruent and opposite neurons. In the model, congruent neurons in two modules are reciprocally connected with each other in the congruent manner, whereas opposite neurons are reciprocally connected in the opposite manner. Mimicking the experimental protocol, our model reproduces the characteristics of congruent and opposite neurons, and demonstrates that in each module, the sisters of congruent and opposite neurons can jointly achieve optimal multisensory information integration and segregation. This study sheds light on our understanding of how the brain implements optimal multisensory integration and segregation concurrently in a distributed manner.
ABSTRACT Opposite neurons, found in macaque dorsal medial superior temporal (MSTd) and ventral intraparietal (VIP) areas, combine visual and vestibular cues of self-motion in opposite ways. A neural circuit recently proposed utilizes opposite neurons to perform causal inference and decide whether the visual and vestibular cues in MSTd and VIP should be integrated or segregated. However, it is unclear how these opposite connections can be formed with biologically realistic learning rules. We propose a network model capable of learning these opposite neurons, using Hebbian and Anti-Hebbian learning rules. The learned neurons are topographically organized and have von Mises-shaped feedforward connections, with tuning properties characteristic of opposite neurons. Our purpose is two-fold: on the one hand, we provide a circuit-level mechanism that explains the properties and formation of opposite neurons; on the other hand, we present a way to extend current theories of multisensory integration to account for appropriate segregation of sensory cues.
Zero-mode waveguides (ZMWs) are nanostructures that drastically reduce the effective optical observation volume beyond the diffraction limit, thereby permitting the use of higher concentrations of fluorescently tagged molecules for single-molecule studies. This work presents the fabrication technology of quartz plasma etching to create tapered sidewalls for the application in ZMWs, utilizing an inductively coupled plasma (ICP) reactive ion etching tool. This method involves a meticulously designed two-step etching process to achieve quartz cavities with a minimum sidewall angle of approximately 60 deg. Initially, the process involves altering the photoresist pattern from a vertical to a tapered form, facilitated by the use of CF4/O2/Ar plasma at elevated radio frequency power settings. Subsequently, the quartz material is etched utilizing CF4 based plasma, with the tapered photoresist serving as a mask. This innovative approach allows for the successful transference of the tapered photoresist structure onto the quartz material, culminating in the formation of uniform and symmetrical tapered quartz cavities. Most importantly, the surface roughness (Rq) of the tapered quartz, measured to be around 3 nm, is extremely low and meets the stringent requirements for optical devices.
Human telomeric G-quadruplex is a four-stranded structure folded by guanines (G) via Hoogsteen hydrogen bonding. The ligands which stabilize the G-quadruplex are often telomerase inhibitors and may become antitumor agents. Here, the interaction between a lignan derivative liliflorin A and human telomeric sequence dGGG (TTAGGG)3G-quadruplex HTG21 were examined by CD, FRET, and NMR spectroscopic methods. In addition, Molecular Docking was used to study the binding of liliflorin A to dTAGGG (TTAGGG)3 G-quadruplex HTG23. The CD data showed that liliflorin A enhanced HTG21 T(m). The T(m) value of G-quadruplex was enhanced 3.2 degrees C by 4.0 μmol x L(-1) liliflorin A in FRET. The NMR spectra of HTG21 showed vivid alteration after reacting with liliflorin A in 3 hours. Molecular Docking suggested liliflorin A bound to the wide groove of HTG23 at G9, G10, G16 and G17. Liliflorin A was the first lignan derivative that could stabilize HTG21 selectively and provided a new candidate for antitumor drug design targeting on human telomeric G-quadruplex.
Abstract Background : To explore the relationships between serum procalcitonin (PCT) level, severity and different stresses of non-septic critically ill patients. Materials and Methods : Patients were divided into traumatic stress, stroke-induced stress and non-infectious inflammatory stress groups. According to 28-day prognosis, they were divided into survival and death groups. The factors affecting prognosis were studied by multivariate logistic regression analysis. Results : PCT level was significantly positively correlated with Acute Physiology and Chronic Health Evaluation II (APACHE II) and sequential organ failure assessment (SOFA) scores (P=0.001). The PCT level and abnormality rate of the traumatic stress group significantly exceeded those of other groups (P---lt---0.05). The APACHE II score, SOFA score and 28-day mortality rate of traumatic stress and stroke-induced stress groups significantly exceeded those of the non-infectious inflammatory stress group (P---lt---0.05). The PCT level, APACHE II score and SOFA score of the death group significantly surpassed those of the survival group (P---lt---0.05). With rising PCT level, APACHE II score, SOFA score and 28-day mortality rate all increased, with significant intergroup differences (P---lt---0.01). Multivariate logistic analysis showed that serum PCT level, APACHE II score and SOFA score were independent risk factors for prognosis. The area under ROC curve for prognosis evaluated by PCT level was 0.797 (95%CI = 0.710~0.878, P=0.000). At a 4.3 μg/L cut-off, the sensitivity and specificity for predicting 28-day mortality were 87.4% and 78.1%, respectively. Conclusion : The serum PCT level of non-septic critically ill patient was positively correlated with severity, which was more likely elevated by traumatic stress than other stresses.
Owing to its many computationally desirable properties, the model of continuous attractor neural networks (CANNs) has been successfully applied to describe the encoding of simple continuous features in neural systems, such as orientation, moving direction, head direction, and spatial location of objects. Recent experimental and computational studies revealed that complex features of external inputs may also be encoded by low-dimensional CANNs embedded in the high-dimensional space of neural population activity. The new experimental data also confirmed the existence of the M-shaped correlation between neuronal responses, which is a correlation structure associated with the unique dynamics of CANNs. This body of evidence, which is reviewed in this report, suggests that CANNs may serve as a canonical model for neural information representation.
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