On the Inability of Markov Models to Capture Criticality in Human Mobility

We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian nature of mobility was used to establish a theoretical upper bound on the predictability of human mobility (expressed as a minimum error probability limit), based on temporally correlated entropy. Since its inception, this bound has been widely used and empirically validated using Markov chains. We show that recurrent-neural architectures can achieve significantly higher predictability, surpassing this widely used upper bound. In order to explain this anomaly, we shed light on several underlying assumptions in previous research works that has resulted in this bias. By evaluating the mobility predictability on real-world datasets, we show that human mobility exhibits scale-invariant long-range correlations, bearing similarity to a power-law decay. This is in contrast to the initial assumption that human mobility follows an exponential decay. This assumption of exponential decay coupled with Lempel-Ziv compression in computing Fano's inequality has led to an inaccurate estimation of the predictability upper bound. We show that this approach inflates the entropy, consequently lowering the upper bound on human mobility predictability. We finally highlight that this approach tends to overlook long-range correlations in human mobility. This explains why recurrent-neural architectures that are designed to handle long-range structural correlations surpass the previously computed upper bound on mobility predictability

The glyoxal budget and its contribution to organic aerosol for Los Angeles, California, during CalNex 2010

Recent laboratory and field studies have indicated that glyoxal is a potentially large contributor to secondary organic aerosol mass. We present in situ glyoxal measurements acquired with a recently developed, high sensitivity spectroscopic instrument during the CalNex 2010 field campaign in Pasadena, California. We use three methods to quantify the production and loss of glyoxal in Los Angeles and its contribution to organic aerosol. First, we calculate the difference between steady state sources and sinks of glyoxal at the Pasadena site, assuming that the remainder is available for aerosol uptake. Second, we use the Master Chemical Mechanism to construct a two-dimensional model for gas-phase glyoxal chemistry in Los Angeles, assuming that the difference between the modeled and measured glyoxal concentration is available for aerosol uptake. Third, we examine the nighttime loss of glyoxal in the absence of its photochemical sources and sinks. Using these methods we constrain the glyoxal loss to aerosol to be 0-5 × 10-5 s-1 during clear days and (1 ± 0.3) × 10-5 s-1 at night. Between 07:00-15:00 local time, the diurnally averaged secondary organic aerosol mass increases from 3.2 μg m-3 to a maximum of 8.8 μg m -3. The constraints on the glyoxal budget from this analysis indicate that it contributes 0-0.2 μg m-3 or 0-4% of the secondary organic aerosol mass. Copyright 2011 by the American Geophysical Union

Coordinated optimization of visual cortical maps (I) Symmetry-based analysis

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of OP columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about an hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference.Comment: 90 pages, 16 figure

Coordinated optimization of visual cortical maps (II) Numerical studies

It is an attractive hypothesis that the spatial structure of visual cortical architecture can be explained by the coordinated optimization of multiple visual cortical maps representing orientation preference (OP), ocular dominance (OD), spatial frequency, or direction preference. In part (I) of this study we defined a class of analytically tractable coordinated optimization models and solved representative examples in which a spatially complex organization of the orientation preference map is induced by inter-map interactions. We found that attractor solutions near symmetry breaking threshold predict a highly ordered map layout and require a substantial OD bias for OP pinwheel stabilization. Here we examine in numerical simulations whether such models exhibit biologically more realistic spatially irregular solutions at a finite distance from threshold and when transients towards attractor states are considered. We also examine whether model behavior qualitatively changes when the spatial periodicities of the two maps are detuned and when considering more than 2 feature dimensions. Our numerical results support the view that neither minimal energy states nor intermediate transient states of our coordinated optimization models successfully explain the spatially irregular architecture of the visual cortex. We discuss several alternative scenarios and additional factors that may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1102.335

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

Background: The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings: Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance: We propose a new neural model for MT pattern computation and motion disambiguation that i

Prognostic Significance of Age Within the Adolescent and Young Adult Acute Ischemic Stroke Population after Mechanical Thrombectomy: Insights from STAR

Objective: Although younger adults have been shown to have better functional outcomes after mechanical thrombectomy (MT) for acute ischemic stroke (AIS), the significance of this relationship in the adolescent and young adult (AYA) population is not well defined given its undefined rarity. Correspondingly, the goal of this study was to determine the prognostic significance of age in this specific demographic following MT for large-vessel occlusions. Methods: A prospectively maintained international multi-institutional database, STAR (Stroke Thrombectomy and Aneurysm Registry), was reviewed for all patients aged 12-18 (adolescent) and 19-25 (young adult) years. Parameters were compared using chi-square and t-test analyses, and associations were interrogated using regression analyses. Results: Of 7192 patients in the registry, 41 (0.6%) satisfied all criteria, with a mean age of 19.7 ± 3.3 years. The majority were male (59%) and young adults (61%) versus adolescents (39%). The median prestroke modified Rankin Scale (mRS) score was 0 (range 0-2). Strokes were most common in the anterior circulation (88%), with the middle cerebral artery being the most common vessel (59%). The mean onset-to-groin puncture and groin puncture-to-reperfusion times were 327 ± 229 and 52 ± 42 minutes, respectively. The mean number of passes was 2.2 ± 1.2, with 61% of the cohort achieving successful reperfusion. There were only 3 (7%) cases of reocclusion. The median mRS score at 90 days was 2 (range 0-6). Between the adolescent and young adult subgroups, the median mRS score at last follow-up was statistically lower in the adolescent subgroup (1 vs 2, p = 0.03), and older age was significantly associated with a higher mRS at 90 days (coefficient 0.33, p < 0.01). Conclusions: Although rare, MT for AIS in the AYA demographic is both safe and effective. Even within this relatively young demographic, age remains significantly associated with improved functional outcomes. The implication of age-dependent stroke outcomes after MT within the AYA demographic needs greater validation to develop effective age-specific protocols for long-term care across both pediatric and adult centers.info:eu-repo/semantics/publishedVersio

Adherence to Combination Prophylaxis for Prevention of Mother-to-Child-Transmission of HIV in Tanzania

BACKGROUND: Since 2008, Tanzanian guidelines for prevention of mother-to-child-transmission of HIV (PMTCT) recommend combination regimen for mother and infant starting in gestational week 28. Combination prophylaxis is assumed to be more effective and less prone to resistance formation compared to single-drug interventions, but the required continuous collection and intake of drugs might pose a challenge on adherence especially in peripheral resource-limited settings. This study aimed at analyzing adherence to combination prophylaxis under field conditions in a rural health facility in Kyela, Tanzania. METHODS AND FINDINGS: A cohort of 122 pregnant women willing to start combination prophylaxis in Kyela District Hospital was enrolled in an observational study. Risk factors for decline of prophylaxis were determined, and adherence levels before, during and after delivery were calculated. In multivariate analysis, identified risk factors for declining pre-delivery prophylaxis included maternal age below 24 years, no income-generating activity, and enrolment before 24.5 gestational weeks, with odds ratios of 5.8 (P = 0.002), 4.4 (P = 0.015) and 7.8 (P = 0.001), respectively. Women who stated to have disclosed their HIV status were significantly more adherent in the pre-delivery period than women who did not (P = 0.004). In the intra- and postpartum period, rather low drug adherence rates during hospitalization indicated unsatisfactory staff performance. Only ten mother-child pairs were at least 80% adherent during all intervention phases; one single mother-child pair met a 95% adherence threshold. CONCLUSIONS: Achieving adherence to combination prophylaxis has shown to be challenging in this rural study setting. Our findings underline the need for additional supervision for PMTCT staff as well as for clients, especially by encouraging them to seek social support through status disclosure. Prophylaxis uptake might be improved by preponing drug intake to an earlier gestational age. Limited structural conditions of a healthcare setting should be taken into serious account when implementing PMTCT combination prophylaxis

Corticofugal Modulation of Initial Neural Processing of Sound Information from the Ipsilateral Ear in the Mouse

Background: Cortical neurons implement a high frequency-specific modulation of subcortical nuclei that includes the cochlear nucleus. Anatomical studies show that corticofugal fibers terminating in the auditory thalamus and midbrain are mostly ipsilateral. Differently, corticofugal fibers terminating in the cochlear nucleus are bilateral, which fits to the needs of binaural hearing that improves hearing quality. This leads to our hypothesis that corticofugal modulation of initial neural processing of sound information from the contralateral and ipsilateral ears could be equivalent or coordinated at the first sound processing level. Methodology/Principal Findings: With the focal electrical stimulation of the auditory cortex and single unit recording, this study examined corticofugal modulation of the ipsilateral cochlear nucleus. The same methods and procedures as described in our previous study of corticofugal modulation of contralateral cochlear nucleus were employed simply for comparison. We found that focal electrical stimulation of cortical neurons induced substantial changes in the response magnitude, response latency and receptive field of ipsilateral cochlear nucleus neurons. Cortical stimulation facilitated auditory response and shortened the response latency of physiologically matched neurons whereas it inhibited auditory response and lengthened the response latency of unmatched neurons. Finally, cortical stimulation shifted the best frequencies of cochlear neurons towards those of stimulated cortical neurons

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

BACKGROUND: In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). METHODOLOGY: The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. CONCLUSIONS: Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward interdependency in the brain

Looking the Part: Social Status Cues Shape Race Perception

It is commonly believed that race is perceived through another's facial features, such as skin color. In the present research, we demonstrate that cues to social status that often surround a face systematically change the perception of its race. Participants categorized the race of faces that varied along White–Black morph continua and that were presented with high-status or low-status attire. Low-status attire increased the likelihood of categorization as Black, whereas high-status attire increased the likelihood of categorization as White; and this influence grew stronger as race became more ambiguous (Experiment 1). When faces with high-status attire were categorized as Black or faces with low-status attire were categorized as White, participants' hand movements nevertheless revealed a simultaneous attraction to select the other race-category response (stereotypically tied to the status cue) before arriving at a final categorization. Further, this attraction effect grew as race became more ambiguous (Experiment 2). Computational simulations then demonstrated that these effects may be accounted for by a neurally plausible person categorization system, in which contextual cues come to trigger stereotypes that in turn influence race perception. Together, the findings show how stereotypes interact with physical cues to shape person categorization, and suggest that social and contextual factors guide the perception of race