Biophysical parameters control signal transfer in spiking network

Introduction

Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer.

Methods

The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error.

Results

Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates.

Discussion

Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.

Prevalence of pulmonary embolism among patients presenting to emergency department for hemoptysis

Background

Although hemoptysis is a well known symptom of presentation of pulmonary embolism (PE), and it is included in different diagnostic scores for PE, the prevalence of PE in patients with hemoptysis and the yield of evidence based PE diagnostic pathway in these patients has not been specifically investigated.

Objectives

To determine the prevalence of PE and the yield (n° of positive tests/n° of tests), the efficiency (the proportion of patients in whom PE could be considered to be excluded) and the failure rate (the false negative rate) of the classic diagnostic algorithm for PE in patients with hemoptysis.

Methods

Unselected patients presenting with hemoptysis to 7 italian EDs were prospectively enrolled in a diagnostic multicenter study. Pre-test clinical probability for PE was assessed using the 2-level Wells score and the results of D-dimer testing using age-adjusted cutoffs. Presence of PE was evaluated by CT pulmonary angiogram (CTPA), when ordered as part of the clinical assessment by the treating ED physician, or by one month follow-up data.

Results

Out of 327 adult patients presenting to ED with hemoptysis, 15 (4.6%) were excluded because of diagnostic protocol violation and absence of one month follow-up. Among 312 included patients, PE was detected at presentation in 15 patients (4.8%; 95% confidence interval [CI]: 2.72–7.81%). During follow-up, 5 patients died (1.6%; 95% CI: 0.52%-3.7%) not due to PE. Among 165 patients with a “likely” score or a high D-dimer, 13 (7.9%; 95% CI: 4.72–13.8%) had PE. The efficiency was 32.8% and the failure rate was 1.7% in patients tested by D-dimer.

Conclusions

PE seems an uncommon cause of hemoptysis among patients presenting to the ED and the yield of classic diagnostic algorithm is low. PE-screening in patients with hemoptysis deserves further investigation aimed at improving the diagnostic yield.

Funding Acknowledgement

Type of funding sources: None.

Prevalence and features of delirium in older patients admitted to rehabilitation facilities: a multicenter study

BACKGROUND

Delirium is thought to be common across various settings of care; however, still little research has been conducted in rehabilitation.

AIM

We investigated the prevalence of delirium, its features and motor subtypes in older patients admitted to rehabilitation facilities during the three editions of the "Delirium Day project".

METHODS

We conducted a cross-sectional study in which 1237 older patients (age ≥ 65 years old) admitted to 50 Italian rehabilitation wards during the three editions of the "Delirium Day project" (2015 to 2017) were included. Delirium was evaluated through the 4AT and its motor subtype with the Delirium Motor Subtype Scale.

RESULTS

Delirium was detected in 226 patients (18%), and the most recurrent motor subtype was mixed (37%), followed by hypoactive (26%), hyperactive (21%) and non-motor one (16%). In a multivariate Poisson regression model with robust variance, factors associated with delirium were: disability in basic (PR 1.48, 95%CI: 1.17-1.9, p value 0.001) and instrumental activities of daily living (PR 1.58, 95%CI: 1.08-2.32, p value 0.018), dementia (PR 2.10, 95%CI: 1.62-2.73, p value < 0.0001), typical antipsychotics (PR 1.47, 95%CI: 1.10-1.95, p value 0.008), antidepressants other than selective serotonin reuptake inhibitors (PR 1.3, 95%CI: 1.02-1.66, p value 0.035), and physical restraints (PR 2.37, 95%CI: 1.68-3.36, p value < 0.0001).

CONCLUSION

This multicenter study reports that 2 out 10 patients admitted to rehabilitations had delirium on the index day. Mixed delirium was the most prevalent subtype. Delirium was associated with unmodifiable (dementia, disability) and modifiable (physical restraints, medications) factors. Identification of these factors should prompt specific interventions aimed to prevent or mitigate delirium.

The association between low skeletal muscle mass and delirium: results from the nationwide multi-centre Italian Delirium Day 2017

Introduction

Delirium and sarcopenia are common, although underdiagnosed, geriatric syndromes. Several pathological mechanisms can link delirium and low skeletal muscle mass, but few studies have investigated their association. We aimed to investigate (1) the association between delirium and low skeletal muscle mass and (2) the possible role of calf circumference mass in finding cases with delirium.

Methods

The analyses were conducted employing the cross-sectional “Delirium Day” initiative, on patient 65 years and older admitted to acute hospital medical wards, emergency departments, rehabilitation wards, nursing homes and hospices in Italy in 2017. Delirium was diagnosed as a 4 + score at the 4-AT scale. Low skeletal muscle mass was operationally defined as calf circumference ≤ 34 cm in males and ≤ 33 cm in females. Logistic regression models were used to investigate the association between low skeletal muscle mass and delirium. The discriminative ability of calf circumference was evaluated using non-parametric ROC analyses.

Results

A sample of 1675 patients was analyzed. In total, 73.6% of participants had low skeletal muscle mass and 24.1% exhibited delirium. Low skeletal muscle mass and delirium showed an independent association (OR: 1.50; 95% CI 1.09–2.08). In the subsample of patients without a diagnosis of dementia, the inclusion of calf circumference in a model based on age and sex significantly improved its discriminative accuracy [area under the curve (AUC) 0.69 vs 0.57, p < 0.001].

Discussion and conclusion

Low muscle mass is independently associated with delirium. In patients without a previous diagnosis of dementia, calf circumference may help to better identify those who develop delirium.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40520-021-01950-8.

Resting-state Functional Connectivity After Occipital Stroke

BACKGROUND

Resting-state functional magnetic resonance imaging (rsfMRI) reflects spontaneous activation of cortical networks. After stroke, these networks reorganize, both due to structural lesion and reorganization of functional connectivity (FC).

OBJECTIVE

We studied FC in chronic phase occipital stroke patients with homonymous visual field defects before and after repetitive transorbital alternating current stimulation (rtACS).

METHODS

This spin-off study, embedded in the randomized, sham-controlled REVIS trial, comprised 16 chronic occipital stroke patients with visual field defect and 12 healthy control subjects. The patients underwent rsfMRI at baseline, after two weeks of rtACS or sham treatment, and after two months of treatment-free follow-up, whereas the control subjects were measured once. We used a multivariate regression connectivity model to determine mutual prediction accuracy between 74 cortical regions of interest. Additionally, the model parameters were included into a graph to analyze average path length, centrality eigenvector, centrality degree, and clustering of the network. The patients and controls at baseline and the two treatment groups were compared with multilevel modeling.

RESULTS

Before treatment, the patients and controls had similar whole-network prediction accuracy and network parameters, whereas centrality eigenvector differed in perilesional regions, indicating local modification in connectivity. In line with behavioral results, neither prediction accuracy nor any network parameter changed systematically as a result of rtACS rehabilitation compared to sham.

CONCLUSIONS

Whole-network FC showed no difference between occipital stroke patients and healthy population, congruent with the peripheral location of the visual network in relation to the high-density cortical core. rtACS treatment in the given setting did not affect FC.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

P6463Prognostic value of respiratory index (RI) in hemodinamically stable patients with acute pulmonary embolism: the RI-MODEL study

Background

The accuracy of the 2014 ESC model to predict 30-day mortality in hemodynamically stable patients with acute pulmonary embolism (PE) is relatively limited.

Purpose

The aims of this study in hemodynamically stable patients with acute PE were i) to evaluate the prognostic value of a novel respiratory index (RI) (oxygen saturation in air to respiratory rate ratio) and ii) to assess the accuracy of the RI-model (simplified Pulmonary Embolism Severity Index [sPESI] + RI), both in predicting 30-day mortality.

Methods

A collaborative database of hemodynamically stable patients with PE was divided into two cohorts (derivation and validation) with equal numbers of patients, based on a temporal criterion. Study outcome was 30-day all-cause-death. Discrimination and calibration were assessed in the derivation and validation cohorts by the c-statistics and by the Hosmer-Lemeshow test, respectively.

Results

30-day all-cause-death occurred in 7.5% of the 319 patients in the derivation cohort (mean age 72 years, females 53%). The RI was an independent predictor of 30-day mortality (p=0.004). A RI ≤3.8 was associated with an increased death rate compared to higher RI values (15.4% vs 5.0%, OR 3.4, 95% CI 1.5–8.1). When the RI≤3.8 was integrated in the sPESI, the novel RI-model showed a good discriminatory power (c-statistics 0.703, 95% CI 0.603–0.803).

In the 319 patients of the validation cohort (30-day mortality 6.9%, mean age 71 years, females 55%) the discriminatory power of the RI-model was confirmed (c-statistics 0.838, 95% CI 0.768–0.907).

The RI-model and the 2014 ESC model had a c-statistics of 0.772 (95% CI 0.709–0.834) and of 0.687 (95% CI 0.620–0.753) in the overall population, respectively.

Conclusion

In this study, the RI independently predicted 30-day mortality in hemodynamically stable patients with acute PE. A clinical model including RI showed a better discriminatory value than 2014 ESC model and could be used for risk stratification in these patients.

P5588Early versus delayed oral anticoagulation in patients with acute pulmonary embolism: determinants and outcome

Background

Whether early oral anticoagulant treatment is appropriate for patients with acute pulmonary embolism (PE) regardless of PE severity is undefined. The aim of this study in patients with acute PE at intermediate risk of death were: I) to assess the determinants for the use of early vs delayed vs no oral anticoagulants in patients with acute PE and II) to assess the association between timing of oral anticoagulation and in-hospital mortality.

Methods

Prospective cohorts of patients with acute PE at intermediate risk of death according to the European Society of Cardiology Guidelines 2014 were merged in a collaborative database. The initiation of oral anticoagulation was classified as early (≤3 days) or delayed (between day 3 and 10 from diagnosis). Patients treated with parenteral anticoagulants for longer than 10 days were also included. In-hospital death was the primary study outcome.

Results

Overall, 557 patients were included in the study, 23 received thrombolytic treatment during the hospital stay. The mean duration of parenteral anticoagulation was 7±8 days (5 median), 348 patients were initiated on a direct oral anticoagulant and 79 on a vitamin K antagonist during the hospital stay. Initiation of oral anticoagulants occurred early or delayed in 209 (37%) and 218 (39%) patients, respectively and never occurred during the first 30 days in 130 (23%).

Intermediate-low risk patients more commonly received early and intermediate high delayed oral anticoagulation. Simplified PESI score of zero (OR 1.9, 95% CI 1.3–2.7) was independently associated with early oral anticoagulation; among sPESI components absence of cancer (OR 5.9, 95% CI 3.3–10) and heart rate <110 (OR 1.8, 95% CI 1.01–3.16) were independent predictors of early initiation of oral anticoagulants. The presence of both right ventricle dysfunction and injury was associated with delayed initiation of oral anticoagulants.

The incidence of death was 5.5%. Death occurred in 32 patients and was not related to the duration of parenteral anticoagulation (OR 1.01 per day, 95% CI 0.98–1.06) nor to right ventricle dysfunction but to sPESI 1 (OR 3.32, 95% CI 1.14–9.66). These results were partially confirmed in the 435 intermediate risk patients without cancer (OR 1.03, 95% CI 0.99–1.08 for days of parenteral treatment; OR 4.17, 95% CI 0.95–18 for sPESI 1).

Conclusion

The clinical severity of PE and not the timing of initiation of oral anticoagulants are associated with in-hospital death in patients with intermediate risk PE. Randomized studies are needed to definitively assess the role of heparin lead-in in patients with PE at intermediate risk for death.

Controlling Complexity of Cerebral Cortex Simulations-II: Streamlined Microcircuits

Recently, Markram et al. (2015) presented a model of the rat somatosensory microcircuit (Markram model). Their model is high in anatomical and physiological detail, and its simulation requires supercomputers. The lack of neuroinformatics and computing power is an obstacle for using a similar approach to build models of other cortical areas or larger cortical systems. Simplified neuron models offer an attractive alternative to high-fidelity Hodgkin-Huxley-type neuron models, but their validity in modeling cortical circuits is unclear. We simplified the Markram model to a network of exponential integrate-and-fire (EIF) neurons that runs on a single CPU core in reasonable time. We analyzed the electrophysiology and the morphology of the Markram model neurons with eFel and NeuroM tools, provided by the Blue Brain Project. We then constructed neurons with few compartments and averaged parameters from the reference model. We used the CxSystem simulation framework to explore the role of short-term plasticity and GABA <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow/><mml:mi>B</mml:mi></mml:msub></mml:math> and NMDA synaptic conductances in replicating oscillatory phenomena in the Markram model. We show that having a slow inhibitory synaptic conductance (GABA <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mrow/><mml:mi>B</mml:mi></mml:msub><mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math> allows replication of oscillatory behavior in the high-calcium state. Furthermore, we show that qualitatively similar dynamics are seen even with a reduced number of cell types (from 55 to 17 types). This reduction halved the computation time. Our results suggest that qualitative dynamics of cortical microcircuits can be studied using limited neuroinformatics and computing resources supporting parameter exploration and simulation of cortical systems. The simplification procedure can easily be adapted to studying other microcircuits for which sparse electrophysiological and morphological data are available.

A systematic review of interventions and outcomes in lung cancer metastases to the spine

Seventy percent of cancer patients will have metastatic bone disease, most commonly in the vertebra. Prognosis of metastatic lung cancer is poor and treatment is mostly palliative. To-date, there is no systematic review on the ideal treatment for lung cancer with spinal metastases in regards to mortality. Literature searches were performed based on PRISMA guidelines for systematic review. Thirty-nine studies comprising 1925 patients treated for spinal metastases of lung cancer met inclusion criteria. All analyses were performed using SAS and SPSS. Data were analyzed for meaningful comparisons of baseline patient characteristics, primary cancer type, metastatic lesion characteristics, treatment modality, and clinical and radiologic outcomes. Significantly greater mean survival length was seen in the non-surgical group (8.5 months, SD 6.6, SEM 0.17) compared to the surgical group (7.5 months, SD 4.5, SEM 0.25; p = 0.013). There was no statistically significant survival difference between different types of primary lung cancer: NSCLC (8.3 months, SD 13.8, SEM 0.91) and SCLC (7.0 months, SD 4.6, SEM 0.46; p = 0.36). Number of vertebral levels involved per lesion also did not exhibit significant difference: single lesion (11.3 months, SD 6.8, SEM 2.2) and multiple lesions (13.8 months, SD 15.7, SEM 3.6; p = 0.64). For patients with symptomatic spinal metastases from lung cancer, non-operative approaches experience significantly better survival outcomes (p = 0.013). Future clinical studies are needed to determine the best treatment algorithm to help maximize outcomes and minimize mortality in metastatic lung cancer.

Oxygen saturation or respiratory rate to improve risk stratification in hemodynamically stable patients with acute pulmonary embolism

Essentials In acute pulmonary embolism (PE), risk stratification is essential to drive clinical management. Improving the 2014-ESC risk stratification strategy is crucial in hemodynamically stable patients. Oxygen saturation and respiratory rate improve risk stratification in hemodynamically stable PE. Simple and routine tests improve risk stratification of hemodynamically stable PE. SUMMARY: Background In patients with acute pulmonary embolism (PE), risk stratification for short-term death is recommended to drive clinical management. A risk stratification strategy combining the simplified Pulmonary Embolism Severity Index (PESI), echocardiography and troponin was proposed by the European Society of Cardiology (ESC) in 2014. The identification of hemodynamically stable patients at increased risk of death by this strategy needs improvement. Objective To assess whether further stratification by serial cut-off values of oxygen saturation or respiratory rate improves the accuracy of the ESC risk stratification strategy in hemodynamically stable PE patients. Methods Prospective cohorts of hemodynamically stable patients with PE were merged in a collaborative database. The accuracy of risk stratification for 30-day mortality by the original and a modified 2014 ESC strategy was assessed. Results Overall, 255 patients (27%) were categorized as low, 510 (54%) as intermediate-low and 181 (19%) as intermediate-high risk according to the original 2014 ESC strategy. Thirty-day mortality was 1.2% in low, 10% in intermediate-low and 11% in intermediate-high-risk patients. By adding oxygen saturation in air of < 88%, the discriminatory power of the 2014 ESC model improved for 30-day mortality (c-statistics, 0.71; 95% confidence interval [CI], 0.65-0.77 vs. 0.63, 95% CI, 0.56-0.69) and for PE-related death (c-statistics, 0.75; 95% CI, 0.69-0.81 vs. 0.63, 95% CI 0.56-0.69). Conclusions Simple and routine tests, such as oxygen saturation or respiratory rate, could be added to the 2014 ESC strategy for risk stratification to identify hemodynamically stable PE patients at increased risk of death who are potentially candidates for more aggressive treatment.

Controlling Complexity of Cerebral Cortex Simulations-I: CxSystem, a Flexible Cortical Simulation Framework

Simulation of the cerebral cortex requires a combination of extensive domain-specific knowledge and efficient software. However, when the complexity of the biological system is combined with that of the software, the likelihood of coding errors increases, which slows model adjustments. Moreover, few life scientists are familiar with software engineering and would benefit from simplicity in form of a high-level abstraction of the biological model. Our primary aim was to build a scalable cortical simulation framework for personal computers. We isolated an adjustable part of the domain-specific knowledge from the software. Next, we designed a framework that reads the model parameters from comma-separated value files and creates the necessary code for Brian2 model simulation. This separation allows rapid exploration of complex cortical circuits while decreasing the likelihood of coding errors and automatically using efficient hardware devices. Next, we tested the system on a simplified version of the neocortical microcircuit proposed by Markram and colleagues ( 2015 ). Our results indicate that the framework can efficiently perform simulations using Python, C <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>+</mml:mo><mml:mo>+</mml:mo></mml:mrow></mml:math> , and GPU devices. The most efficient device varied with computer hardware and the duration and scale of the simulated system. The speed of Brian2 was retained despite an overlying layer of software. However, the Python and C <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>+</mml:mo><mml:mo>+</mml:mo></mml:mrow></mml:math> devices inherited the single core limitation of Brian2. The CxSystem framework supports exploration of complex models on personal computers and thus has the potential to facilitate research on cortical networks and systems.

Museum samples could help to reconstruct the original distribution of Salmo trutta complex in Italy

Partial D-loop sequences of museum specimens of brown trout and marble trout (Salmo trutta species complex) collected from Mediterranean rivers in the late 19th century were analysed to help to describe the native distribution of these species. All the individuals studied carried native haplotypes, the geographic distribution of which is consistent with published data. These results indicate that museum specimens from the 19th century could represent an opportunity to get a picture of the original genetic diversity distribution of this species complex.

From evoked potentials to cortical currents: Resolving V1 and V2 components using retinotopy constrained source estimation without fMRI

Despite evoked potentials' (EP) ubiquity in research and clinical medicine, insights are limited to gross brain dynamics as it remains challenging to map surface potentials to their sources in specific cortical regions. Multiple sources cancellation due to cortical folding and cross-talk obscures close sources, e.g. between visual areas V1 and V2. Recently retinotopic functional magnetic resonance imaging (fMRI) responses were used to constrain source locations to assist separating close sources and to determine cortical current generators. However, an fMRI is largely infeasible for routine EP investigation. We developed a novel method that replaces the fMRI derived retinotopic layout (RL) by an approach where the retinotopy and current estimates are generated from EEG or MEG signals and a standard clinical T1-weighted anatomical MRI. Using the EEG-RL, sources were localized to within 2 mm of the fMRI-RL constrained localized sources. The EEG-RL also produced V1 and V2 current waveforms that closely matched the fMRI-RL's (n = 2) r(1,198)  = 0.99, P < 0.0001. Applying the method to subjects without fMRI (n = 4) demonstrates it generates waveforms that agree closely with the literature. Our advance allows investigators with their current EEG or MEG systems to create a library of brain models tuned to individual subjects' cortical folding in retinotopic maps, and should be applicable to auditory and somatosensory maps. The novel method developed expands EP's ability to study specific brain areas, revitalizing this well-worn technique. Hum Brain Mapp 37:1696-1709, 2016. © 2016 Wiley Periodicals, Inc.

Radial Frequency Analysis of Contour Shapes in the Visual Cortex

Cumulative psychophysical evidence suggests that the shape of closed contours is analysed by means of their radial frequency components (RFC). However, neurophysiological evidence for RFC-based representations is still missing. We investigated the representation of radial frequency in the human visual cortex with functional magnetic resonance imaging. We parametrically varied the radial frequency, amplitude and local curvature of contour shapes. The stimuli evoked clear responses across visual areas in the univariate analysis, but the response magnitude did not depend on radial frequency or local curvature. Searchlight-based, multivariate representational similarity analysis revealed RFC specific response patterns in areas V2d, V3d, V3AB, and IPS0. Interestingly, RFC-specific representations were not found in hV4 or LO, traditionally associated with visual shape analysis. The modulation amplitude of the shapes did not affect the responses in any visual area. Local curvature, SF-spectrum and contrast energy related representations were found across visual areas but without similar specificity for visual area that was found for RFC. The results suggest that the radial frequency of a closed contour is one of the cortical shape analysis dimensions, represented in the early and mid-level visual areas.

Contextual Modulation is Related to Efficiency in a Spiking Network Model of Visual Cortex

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response.

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals.

Feedback to distal dendrites links fMRI signals to neural receptive fields in a spiking network model of the visual cortex

The blood oxygenation level-dependent (BOLD) response has been strongly associated with neuronal activity in the brain. However, some neuronal tuning properties are consistently different from the BOLD response. We studied the spatial extent of neural and hemodynamic responses in the primary visual cortex, where the BOLD responses spread and interact over much longer distances than the small receptive fields of individual neurons would predict. Our model shows that a feedforward-feedback loop between V1 and a higher visual area can account for the observed spread of the BOLD response. In particular, anisotropic landing of inputs to compartmental neurons were necessary to account for the BOLD signal spread, while retaining realistic spiking responses. Our work shows that simple dendrites can separate tuning at the synapses and at the action potential output, thus bridging the BOLD signal to the neural receptive fields with high fidelity.

[Is there unused capacity in our brain?]

Although a great deal of research has been performed on special abilities occurring in connection with developmental disorders and injuries, their biological background remains unknown. It is tempting to think that understanding of the mechanism of generation of special ability would help each of us to liberate our brain capacity and direct it in a desired manner. Poor knowledge of the general functioning principle of the brain remains an essential restriction against establishing whether there is extra capacity in the brain and whether its liberation is possible now or in the near future. Model-based brain research is rising to the central position in understanding the functional principle.

Visual interactions conform to pattern decorrelation in multiple cortical areas

Neural responses to visual stimuli are strongest in the classical receptive field, but they are also modulated by stimuli in a much wider region. In the primary visual cortex, physiological data and models suggest that such contextual modulation is mediated by recurrent interactions between cortical areas. Outside the primary visual cortex, imaging data has shown qualitatively similar interactions. However, whether the mechanisms underlying these effects are similar in different areas has remained unclear. Here, we found that the blood oxygenation level dependent (BOLD) signal spreads over considerable cortical distances in the primary visual cortex, further than the classical receptive field. This indicates that the synaptic activity induced by a given stimulus occurs in a surprisingly extensive network. Correspondingly, we found suppressive and facilitative interactions far from the maximum retinotopic response. Next, we characterized the relationship between contextual modulation and correlation between two spatial activation patterns. Regardless of the functional area or retinotopic eccentricity, higher correlation between the center and surround response patterns was associated with stronger suppressive interaction. In individual voxels, suppressive interaction was predominant when the center and surround stimuli produced BOLD signals with the same sign. Facilitative interaction dominated in the voxels with opposite BOLD signal signs. Our data was in unison with recently published cortical decorrelation model, and was validated against alternative models, separately in different eccentricities and functional areas. Our study provides evidence that spatial interactions among neural populations involve decorrelation of macroscopic neural activation patterns, and suggests that the basic design of the cerebral cortex houses a robust decorrelation mechanism for afferent synaptic input.

Brightness and transparency in the early visual cortex

Several psychophysical studies have shown that transparency can have drastic effects on brightness and lightness. However, the neural processes generating these effects have remained unresolved. Several lines of evidence suggest that the early visual cortex is important for brightness perception. While single cell recordings suggest that surface brightness is represented in the primary visual cortex, the results of functional magnetic resonance imaging (fMRI) studies have been discrepant. In addition, the location of the neural representation of transparency is not yet known. We investigated whether the fMRI responses in areas V1, V2, and V3 correlate with brightness and transparency. To dissociate the blood oxygen level-dependent (BOLD) response to brightness from the response to local border contrast and mean luminance, we used variants of White's brightness illusion, both opaque and transparent, in which luminance increments and decrements cancel each other out. The stimuli consisted of a target surface and a surround. The surround luminance was always sinusoidally modulated at 0.5 Hz to induce brightness modulation to the target. The target luminance was constant or modulated in counterphase to null brightness modulation. The mean signal changes were calculated from the voxels in V1, V2, and V3 corresponding to the retinotopic location of the target surface. The BOLD responses were significantly stronger for modulating brightness than for stimuli with constant brightness. In addition, the responses were stronger for transparent than for opaque stimuli, but there was more individual variation. No interaction between brightness and transparency was found. The results show that the early visual areas V1-V3 are sensitive to surface brightness and transparency and suggest that brightness and transparency are represented separately.

Fovea-periphery axis symmetry of surround modulation in the human visual system

A visual stimulus activates different sized cortical area depending on eccentricity of the stimulus. Here, our aim is to understand whether the visual field size of a stimulus or cortical size of the corresponding representation determines how strongly it interacts with other stimuli. We measured surround modulation of blood-oxygenation-level-dependent signal and perceived contrast with surrounds that extended either towards the periphery or the fovea from a center stimulus, centered at 6° eccentricity. This design compares the effects of two surrounds which are identical in visual field size, but differ in the sizes of their cortical representations. The surrounds produced equally strong suppression, which suggests that visual field size of the surround determines suppression strength. A modeled population of neuronal responses, in which all the parameters were experimentally fixed, captured the pattern of results both in psychophysics and functional magnetic resonance imaging. Although the fovea-periphery anisotropy affects nearly all aspects of spatial vision, our results suggest that in surround modulation the visual system compensates for it.

Seeing mathematics: perceptual experience and brain activity in acquired synesthesia

We studied the patient JP who has exceptional abilities to draw complex geometrical images by hand and a form of acquired synesthesia for mathematical formulas and objects, which he perceives as geometrical figures. JP sees all smooth curvatures as discrete lines, similarly regardless of scale. We carried out two preliminary investigations to establish the perceptual nature of synesthetic experience and to investigate the neural basis of this phenomenon. In a functional magnetic resonance imaging (fMRI) study, image-inducing formulas produced larger fMRI responses than non-image inducing formulas in the left temporal, parietal and frontal lobes. Thus our main finding is that the activation associated with his experience of complex geometrical images emerging from mathematical formulas is restricted to the left hemisphere.

Refractive surgery in anisometropic adult patients induce plastic changes in primary visual cortex

PURPOSE

To prospectively study the effect of refractive surgery in the primary visual cortex of adult anisometropic and isometropic myopic patients.

METHODS

Two anisometropic and two isometropic myopic patients were examined with multifocal functional magnetic resonance imaging technique (mffMRI) before refractive surgery and at 3, 6, 9 and 12 months postoperatively. Two controls without refractive surgery were also examined with mffMRI in the beginning and in the end of the study. Anisometropic patients had only their more myopic eye operated to correct the anisometropia. The myopic isometropic patients had their both eyes operated.

RESULTS

Operated anisometropic eyes showed 65% reduced amount of active voxels in foveal data at 12 months postoperatively compared with the preoperative situation. In unoperated anisometropic eyes, the corresponding value was 86% and in myopic patients and controls 31% and 1%, respectively. To confirm this finding, the number of activated voxels representing the innermost ring of the stimulus was also calculated, and an exactly similar phenomenon was encountered in the anisometropic patients. Both anisometropic patients improved the best-spectacle-corrected visual acuity in the operated eye after refractive surgery.

CONCLUSION

Our results suggest that plastic changes may take place in the primary visual cortex of anisometropic adult patients after refractive surgery.

A closer look into G protein coupled receptor activation: X-ray crystallography and long-scale molecular dynamics simulations

G protein coupled receptors (GPCRs) are a large eukaryotic protein family of transmembrane receptors that react to a signal coming from the extracellular environment to generate an intracellular response through the activation of a signal transduction pathway mediated by a heterotrimeric G protein. Their diversity, dictated by the multiplicity of stimuli to which they respond and by the variety of intracellular signalling pathways they activate, make them one of the most prominent families of validated pharmacological targets in biomedicine. In recent years, major breakthroughs in structure determination of GPCRs have given new stimuli to the exploration of the biology of these proteins, providing a structural basis to understand the molecular origin of GPCR mechanisms of action. Based on the information coming from these structural studies, a number of recent in silico investigations used molecular dynamics (MD) simulations to contribute to our knowledge of GPCRs. In this review, we will focus on investigations that, taking advantage of the tremendous progress in both hardware and software, made testable hypotheses that have been validated by subsequent structural studies. These stateof- the-art molecular simulations highlight the potential of microsecond MD simulations as a valuable tool in GPCR structural biology and biophysics.

Retinotopic maps, spatial tuning, and locations of human visual areas in surface coordinates characterized with multifocal and blocked FMRI designs

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies.

Is selective primary visual cortex stimulation achievable with TMS?

The primary visual cortex (V1) has been the target of stimulation in a number of transcranial magnetic stimulation (TMS) studies. In this study, we estimated the actual sites of stimulation by modeling the cortical location of the TMS-induced electric field when participants reported visual phosphenes or scotomas. First, individual retinotopic areas were identified by multifocal functional magnetic resonance imaging (mffMRI). Second, during the TMS stimulation, the cortical stimulation sites were derived from electric field modeling. When an external anatomical landmark for V1 was used (2 cm above inion), the cortical stimulation landed in various functional areas in different individuals, the dorsal V2 being the most affected area at the group level. When V1 was specifically targeted based on the individual mffMRI data, V1 could be selectively stimulated in half of the participants. In the rest, the selective stimulation of V1 was obstructed by the intermediate position of the dorsal V2. We conclude that the selective stimulation of V1 is possible only if V1 happens to be favorably located in the individual anatomy. Selective and successful targeting of TMS pulses to V1 requires MRI-navigated stimulation, selection of participants and coil positions based on detailed retinotopic maps of individual functional anatomy, and computational modeling of the TMS-induced electric field distribution in the visual cortex. It remains to be resolved whether even more selective stimulation of V1 could be achieved by adjusting the coil orientation according to sulcal orientation of the target site.

Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER

In this article we introduce the DRIFTER algorithm, which is a new model based Bayesian method for retrospective elimination of physiological noise from functional magnetic resonance imaging (fMRI) data. In the method, we first estimate the frequency trajectories of the physiological signals with the interacting multiple models (IMM) filter algorithm. The frequency trajectories can be estimated from external reference signals, or if the temporal resolution is high enough, from the fMRI data. The estimated frequency trajectories are then used in a state space model in combination of a Kalman filter (KF) and Rauch-Tung-Striebel (RTS) smoother, which separates the signal into an activation related cleaned signal, physiological noise, and white measurement noise components. Using experimental data, we show that the method outperforms the RETROICOR algorithm if the shape and amplitude of the physiological signals change over time.

Comparison of two prognostic models for acute pulmonary embolism: clinical vs. right ventricular dysfunction-guided approach

BACKGROUND

Recently, some prognostic models for acute pulmonary embolism (PE) have been proposed. We investigated whether the Pulmonary Embolism Severity Index (PESI) and the European Society of Cardiology (ESC) prognostic approaches result in different prognoses.

METHODS

Consecutive adult patients with acute PE were included. According to the ESC guidelines, high-risk patients were identified by the presence of shock/hypotension, intermediate-risk patients by elevated troponin I or right ventricular dysfunction as assessed by echocardiography, and low-risk patients by the absence of any of the above. In the PESI model, 11 clinical variables, easily accessible at the bedside, were used to generate three risk classes. The main outcomes were all-cause and PE-related in-hospital mortality.

RESULTS

Forty-one patients (8%, 95% confidence interval [CI] 5.8-10.8) of 510 died. According to the ESC model, 40% were at low risk of short-term mortality, 54% at intermediate risk, and 6% at high risk. The distribution according to the PESI model was 31% (P < 0.05 vs. ESC), 49% and 20% (P < 0.05 vs. ESC), respectively. Mortality increased through the risk classes (P < 0.01), without significant differences between the models. The ESC model identified with higher accuracy than the PESI model both high-risk and low-risk patients (P < 0.05 for both). When patients with shock/hypotension were excluded, the PESI model stratified patients into classes with increasing PE-related mortality (0.7%, 4.3%, and 11.6%, P < 0.05). Troponin I and right ventricular dysfunction added incremental prognostic value to the PESI model, particularly in normotensive patients at intermediate risk.

CONCLUSIONS

The ESC model showed higher accuracy than the PESI model in identifying high-risk and low-risk patients. In normotensive patients, the PESI model could guide clinical management as well as troponin I and echocardiography testing.

Diagnostic accuracy of 64-slice CT in evaluating coronary artery bypass grafts and of the native coronary arteries

PURPOSE

Our aim was to evaluate the accuracy, sensitivity and specificity of 64-slice multidetector computed tomography (MDCT) in the assessment of occlusions and stenoses of arterial and venous bypass grafts and disease progression in the native vessels distal to the graft, and to compare the results with those of conventional coronary angiography.

MATERIALS AND METHODS

We enrolled 78 individuals (45 men, 33 women; mean age 59) and evaluated 213 bypass grafts using a 64-slice MDCT scanner. All patients underwent conventional coronary angiography with a mean time interval between the two examinations of 2 days.

RESULTS

One patient was excluded due to arrhythmia during the examination. The 212 bypass grafts in the remaining 77 patients (98.7%) consisted of 115 (54%) venous grafts and 97 (46%) arterial grafts. In the 115 venous grafts, MDCT showed a sensitivity, specificity and accuracy of 100% in evaluating occluded grafts and a sensitivity of 94.4%, specificity of 98.4% and accuracy of 96.9% in evaluating significant stenoses. In evaluating occluded arterial grafts, sensitivity was 83.3%, specificity 100% and accuracy 98.9%, whereas in evaluating stenoses of arterial grafts, sensitivity was 100%, specificity 97.7% and accuracy 98%.

CONCLUSIONS

Sensitivity, specificity and accuracy in evaluating native coronary vessels distal to the graft allow for a complete assessment of the surgical and native circulation. The examination appears therefore to be exhaustive in ruling out or confirming the presence of diseased vessels in the postoperative follow-up.