Predictability of intelligence and age from structural connectomes

In this study, structural images of 1048 healthy subjects from the Human Connectome Project Young Adult study and 94 from ADNI-3 study were processed by an in-house tractography pipeline and analyzed together with pre-processed data of the same subjects from braingraph.org. Whole brain structural connectome features were used to build a simple correlation-based regression machine learning model to predict intelligence and age of healthy subjects. Our results showed that different forms of intelligence as well as age are predictable to a certain degree from diffusion tensor imaging detecting anatomical fiber tracts in the living human brain. Though we did not identify significant differences in the prediction capability for the investigated features depending on the imaging feature extraction method, we did find that crystallized intelligence was consistently better predictable than fluid intelligence from structural connectivity data through all datasets. Our findings suggest a practical and scalable processing and analysis framework to explore broader research topics employing brain MR imaging.

Progression free survival of myeloma patients who become IFE-negative correlates with the detection of residual monoclonal free light chain (FLC) by mass spectrometry

Deeper responses are associated with improved survival in patients being treated for myeloma. However, the sensitivity of the current blood-based assays is limited. Historical studies suggested that normalisation of the serum free light chain (FLC) ratio in patients who were negative by immunofixation electrophoresis (IFE) was associated with improved outcomes. However, recently this has been called into question. Mass spectrometry (MS)-based FLC assessments may offer a superior methodology for the detection of monoclonal FLC due to greater sensitivity. To test this hypothesis, all available samples from patients who were IFE negative after treatment with carfilzomib and lenalidomide-based induction and autologous stem cell transplantation (ASCT) in the Myeloma XI trial underwent FLC-MS testing. FLC-MS response assessments from post-induction, day+100 post-ASCT and six months post-maintenance randomisation were compared to serum FLC assay results. Almost 40% of patients had discordant results and 28.7% of patients with a normal FLC ratio had residual monoclonal FLC detectable by FLC-MS. FLC-MS positivity was associated with reduced progression-free survival (PFS) but an abnormal FLC ratio was not. This study demonstrates that FLC-MS provides a superior methodology for the detection of residual monoclonal FLC with FLC-MS positivity identifying IFE-negative patients who are at higher risk of early progression.

Spatial organisation of the mesoscale connectome: A feature influencing synchrony and metastability of network dynamics

Significant research has investigated synchronisation in brain networks, but the bulk of this work has explored the contribution of brain networks at the macroscale. Here we explore the effects of changing network topology on functional dynamics in spatially constrained random networks representing mesoscale neocortex. We use the Kuramoto model to simulate network dynamics and explore synchronisation and critical dynamics of the system as a function of topology in randomly generated networks with a distance-related wiring probability and no preferential attachment term. We show networks which predominantly make short-distance connections smooth out the critical coupling point and show much greater metastability, resulting in a wider range of coupling strengths demonstrating critical dynamics and metastability. We show the emergence of cluster synchronisation in these geometrically-constrained networks with functional organisation occurring along structural connections that minimise the participation coefficient of the cluster. We show that these cohorts of internally synchronised nodes also behave en masse as weakly coupled nodes and show intra-cluster desynchronisation and resynchronisation events related to inter-cluster interaction. While cluster synchronisation appears crucial to healthy brain function, it may also be pathological if it leads to unbreakable local synchronisation which may happen at extreme topologies, with implications for epilepsy research, wider brain function and other domains such as social networks.

Connectomes: from a sparsity of networks to large-scale databases

The analysis of whole brain networks started in the 1980s when only a handful of connectomes were available. In these early days, information about the human connectome was absent and one could only dream about having information about connectivity in a single human subject. Thanks to non-invasive methods such as diffusion imaging, we now know about connectivity in many species and, for some species, in many individuals. To illustrate the rapid change in availability of connectome data, the UK Biobank is on track to record structural and functional connectivity in 100,000 human subjects. Moreover, connectome data from a range of species is now available: from Caenorhabditis elegans and the fruit fly to pigeons, rodents, cats, non-human primates, and humans. This review will give a brief overview of what structural connectivity data is now available, how connectomes are organized, and how their organization shows common features across species. Finally, I will outline some of the current challenges and potential future work in making use of connectome information.

Closed-loop optogenetic control of the dynamics of neural activity in non-human primates

Electrical neurostimulation is effective in the treatment of neurological disorders, but associated recording artefacts generally limit its applications to open-loop stimuli. Real-time and continuous closed-loop control of brain activity can, however, be achieved by pairing concurrent electrical recordings and optogenetics. Here we show that closed-loop optogenetic stimulation with excitatory opsins enables the precise manipulation of neural dynamics in brain slices from transgenic mice and in anaesthetized non-human primates. The approach generates oscillations in quiescent tissue, enhances or suppresses endogenous patterns in active tissue and modulates seizure-like bursts elicited by the convulsant 4-aminopyridine. A nonlinear model of the phase-dependent effects of optical stimulation reproduced the modulation of cycles of local-field potentials associated with seizure oscillations, as evidenced by the systematic changes in the variability and entropy of the phase-space trajectories of seizures, which correlated with changes in their duration and intensity. We also show that closed-loop optogenetic neurostimulation could be delivered using intracortical optrodes incorporating light-emitting diodes. Closed-loop optogenetic approaches may be translatable to therapeutic applications in humans.

Pathway-Specific Mediation Effect Between Structure, Function, and Motor Impairment After Subcortical Stroke

BACKGROUND AND OBJECTIVE

To investigate the pathway-specific correspondence between structural and functional changes resulting from focal subcortical stroke and their causal influence on clinical symptom.

METHODS

In this retrospective, cross-sectional study, we mainly focused on patients with unilateral subcortical chronic stroke with moderate-severe motor impairment assessed by Fugl-Meyer Assessment (upper extremity) and healthy controls. All participants underwent both resting-state fMRI and diffusion tensor imaging. To parse the pathway-specific structure-function covariation, we performed association analyses between the fine-grained corticospinal tracts (CSTs) originating from 6 subareas of the sensorimotor cortex and functional connectivity (FC) of the corresponding subarea, along with the refined corpus callosum (CC) sections and interhemispheric FC. A mediation analysis with FC as the mediator was used to further assess the pathway-specific effects of structural damage on motor impairment.

RESULTS

Thirty-five patients (mean age 52.7 ± 10.2 years, 27 men) and 43 healthy controls (mean age 56.2 ± 9.3 years, 21 men) were enrolled. Among the 6 CSTs, we identified 9 structurally and functionally covaried pathways, originating from the ipsilesional primary motor area (M1), dorsal premotor area (PMd), and primary somatosensory cortex (p < 0.05, corrected). FC for the bilateral M1, PMd, and ventral premotor cortex covaried with secondary degeneration of the corresponding CC sections (p < 0.05, corrected). Moreover, these covarying structures and functions were significantly correlated with the Fugl-Meyer Assessment (upper extremity) scores (p < 0.05, uncorrected). In particular, FC between the ipsilesional PMd and contralesional cerebellum (β = -0.141, p < 0.05, CI = [-0.319 to -0.015]) and interhemispheric FC of the PMd (β = 0.169, p < 0.05, CI = [0.015-0.391]) showed significant mediation effects in the prediction of motor impairment with structural damage of the CST and CC.

DISCUSSIONS

This study reveals causal influence of structural and functional pathways on motor impairment after subcortical stroke and provides a promising way to investigate pathway-specific structure-function coupling. Clinically, our findings may offer a circuit-based evidence for the PMd as a critical neuromodulation target in more impaired patients with stroke and also suggest the cerebellum as a potential target.

Value of functional connectivity in outcome prediction for pallidal stimulation in Parkinson disease

OBJECTIVE

Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction.

METHODS

The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome.

RESULTS

Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = -0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive.

CONCLUSIONS

The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.

Non-optimal component placement of the human connectome supports variable brain dynamics

Neural systems are shaped by multiple constraints, balancing region communication with the cost of establishing and maintaining physical connections. It has been suggested that the lengths of neural projections be minimized, reducing their spatial and metabolic impact on the organism. However, long-range connections are prevalent in the connectomes across various species, and thus, rather than rewiring connections to reduce length, an alternative theory proposes that the brain minimizes total wiring length through a suitable positioning of regions, termed ‘component placement optimization’. Previous studies in non-human primates have refuted this idea by identifying a non-optimal component placement, where a spatial re-arrangement of brain regions in silico lead to a reduced total wiring length. Here, for the first time in humans, we test for component placement optimization. We show a non-optimal component placement for all subjects in our sample from the Human Connectome Project (N = 280; aged 22–30 years; 138 females), suggesting the presence of constraints—such as the reduction of processing steps between regions—which compete with the elevated spatial and metabolic costs. Additionally, by simulating communication between brain regions, we argue that this sub-optimal component placement supports dynamics which benefit cognition.

OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

Computational tools have been widely adopted for strain optimization in metabolic engineering, contributing to numerous success stories of producing industrially relevant biochemicals. However, most of these tools focus on single metabolic intervention strategies (either gene/reaction knockout or amplification alone) and rely on hypothetical optimality principles (e.g., maximization of growth) and precise gene expression (e.g., fold changes) for phenotype prediction. This paper introduces OptDesign, a new two-step strain design strategy. In the first step, OptDesign selects regulation candidates that have a noticeable flux difference between the wild type and production strains. In the second step, it computes optimal design strategies with limited manipulations (combining regulation and knockout), leading to high biochemical production. The usefulness and capabilities of OptDesign are demonstrated for the production of three biochemicals in Escherichia coli using the latest genome-scale metabolic model iML1515, showing highly consistent results with previous studies while suggesting new manipulations to boost strain performance. The source code is available at https://github.com/chang88ye/OptDesign.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

BioDynaMo: a modular platform for high-performance agent-based simulation

MOTIVATION

Agent-based modeling is an indispensable tool for studying complex biological systems. However, existing simulation platforms do not always take full advantage of modern hardware and often have a field-specific software design.

RESULTS

We present a novel simulation platform called BioDynaMo that alleviates both of these problems. BioDynaMo features a modular and high-performance simulation engine. We demonstrate that BioDynaMo can be used to simulate use cases in: neuroscience, oncology and epidemiology. For each use case, we validate our findings with experimental data or an analytical solution. Our performance results show that BioDynaMo performs up to three orders of magnitude faster than the state-of-the-art baselines. This improvement makes it feasible to simulate each use case with one billion agents on a single server, showcasing the potential BioDynaMo has for computational biology research.

AVAILABILITY AND IMPLEMENTATION

BioDynaMo is an open-source project under the Apache 2.0 license and is available at www.biodynamo.org. Instructions to reproduce the results are available in the supplementary information.

SUPPLEMENTARY INFORMATION

Available at https://doi.org/10.5281/zenodo.5121618.

[Effect of a multimodal pain management protocol and age on wound healing after thermal disbudding of female German Holstein calves]

INTRODUCTION

Hot-iron disbudding of calves is a stressful and painful procedure and leaves a burn wound. Pain management procedures and the effects of hot-iron disbudding on biochemical markers of pain perception and stress response have been widely investigated in recent years. The aim of this study was to investigate the potential effects of pain management and age of the calf on the healing of burn wounds caused by disbudding. 327 healthy female German Holstein calves were included in this randomised, triple-blinded, prospective study. Calves were either disbudded at the age of four to 10 or 15 to 28 days using a gas-powered hot iron. Each calf was randomly allocated to one of nine possible treatment groups (BG). All calves received either the active ingredients to be tested (xylazine hydrochloride with 0.2 or 0.05 mg / kg body mass (BM) intramuscular for sedation, procaine hydrochloride (2 %) each 8 ml locally on both sides subcutaneously (SC) to the cornual nerves, meloxicam with 0,5 mg / kg BM SC for anti-inflammatory purposes) or an identical amount of saline solution (placebo). Calves in the group `thermE` and `ScheinE` received only placebo. In group `ScheinE` disbudding was simulated and in `thermE` it was carried out. The calves were clinically monitored starting one day before and ending 28 days after the procedure and the burn wounds were assessed. Both the rectal temperature and parameters of wound healing changed significantly during the study period and had characteristic profiles over time. Wound healing was not influenced by the different analgesic protocols, indicating that a multimodal analgesia does not pose a risk for wound healing after thermal disbudding. There were no observed differences between the age groups. The results of this study show, that disbudding of young calves and a multimodal pain management protocol does not affect wound healing in calves.

[Cortisol concentrations in sheep before, during and after sham foot trimming on a tilt table - the suitability of different matrices]

INTRODUCTION

Matrices that can be collected non-invasively for quantification of a stress response in sheep have received little attention in the veterinary literature. This study examines the suitability of blood, tears and saliva for determining a stress response in sheep undergoing sham foot trimming on a tilt table. The cortisol concentration of blood, tears and saliva and the concentration of cortisol metabolites in faeces were measured in 13 healthy Meat Merino ewes once a day for six days. Sham foot trimming on a tilt table was used as the stressor and was done during a one-hour period on day 4; cortisol concentrations of blood and tears were measured at 0, 10, 20, 30, 40 and 60 minutes. Cortisol concentrations of blood (maximum at 30 minutes) and tears (maximum at 40 minutes) increased during the procedure and then decreased. There were significant correlations between cortisol concentrations of blood and tears (p = 0,04) during sham foot trimming (area under the curve, 0 to 60 minutes). Over the entire 6-day study period, significant correlations were seen between the cortisol concentrations of blood and tears (r = 0,55; p.

Lipödem heute: Zwischen konservativer Therapie, Liposuktion und Adipositaschirurgie

Die zunehmende Prävalenz des Lipödems geht einher mit einer demografischen Zunahme der Adipositas per magna.

Konservative und operative Maßnahmen ermöglichen eine ausgeprägte Befund- und Beschwerdebesserung.

Die exakte Diagnose und Differenzierung zwischen therapiebedürftiger Adipositas und therapiebedürftigem Lipödem entscheiden über Erfolg und Misserfolg der eingeleiteten Therapie.

Nach konservativem Therapieversuch kann die operative Versorgung bei Ausbleiben einer entsprechenden Besserung durch Liposuktion oder adipositaschirurgische Intervention bei einem erheblichen Teil der Betroffenen die konservative Therapie reduzieren bzw. teilweise sogar ganz überflüssig machen.

A Closed-Loop Optogenetic Platform

Neuromodulation is an established treatment for numerous neurological conditions, but to expand the therapeutic scope there is a need to improve the spatial, temporal and cell-type specificity of stimulation. Optogenetics is a promising area of current research, enabling optical stimulation of genetically-defined cell types without interfering with concurrent electrical recording for closed-loop control of neural activity. We are developing an open-source system to provide a platform for closed-loop optogenetic neuromodulation, incorporating custom integrated circuitry for recording and stimulation, real-time closed-loop algorithms running on a microcontroller and experimental control via a PC interface. We include commercial components to validate performance, with the ultimate aim of translating this approach to humans. In the meantime our system is flexible and expandable for use in a variety of preclinical neuroscientific applications. The platform consists of a Controlling Abnormal Network Dynamics using Optogenetics (CANDO) Control System (CS) that interfaces with up to four CANDO headstages responsible for electrical recording and optical stimulation through custom CANDO LED optrodes. Control of the hardware, inbuilt algorithms and data acquisition is enabled via the CANDO GUI (Graphical User Interface). Here we describe the design and implementation of this system, and demonstrate how it can be used to modulate neuronal oscillations in vitro and in vivo.

The functional brain favours segregated modular connectivity at old age unless affected by neurodegeneration

Brain's modular connectivity gives this organ resilience and adaptability. The ageing process alters the organised modularity of the brain and these changes are further accentuated by neurodegeneration, leading to disorganisation. To understand this further, we analysed modular variability-heterogeneity of modules-and modular dissociation-detachment from segregated connectivity-in two ageing cohorts and a mixed cohort of neurodegenerative diseases. Our results revealed that the brain follows a universal pattern of high modular variability in metacognitive brain regions: the association cortices. The brain in ageing moves towards a segregated modular structure despite presenting with increased modular heterogeneity-modules in older adults are not only segregated, but their shape and size are more variable than in young adults. In the presence of neurodegeneration, the brain maintains its segregated connectivity globally but not locally, and this is particularly visible in dementia with Lewy bodies and Parkinson's disease dementia; overall, the modular brain shows patterns of differentiated pathology.

TCERG1L allelic variation is associated with cisplatin-induced hearing loss in childhood cancer, a PanCareLIFE study

In children with cancer, the heterogeneity in ototoxicity occurrence after similar treatment suggests a role for genetic susceptibility. Using a genome-wide association study (GWAS) approach, we identified a genetic variant in TCERG1L (rs893507) to be associated with hearing loss in 390 non-cranial irradiated, cisplatin-treated children with cancer. These results were replicated in two independent, similarly treated cohorts (n = 192 and 188, respectively) (combined cohort: P = 5.3 × 10-10, OR 3.11, 95% CI 2.2-4.5). Modulating TCERG1L expression in cultured human cells revealed significantly altered cellular responses to cisplatin-induced cytokine secretion and toxicity. These results contribute to insights into the genetic and pathophysiological basis of cisplatin-induced ototoxicity.

Creative Destruction: A Basic Computational Model of Cortical Layer Formation

One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus, and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multiscale, agent-based model, comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure. Importantly, apoptosis allows for changing the thickness of one layer without automatically affecting other layers. Therefore, apoptosis increases the flexibility for evolutionary change in layer architecture. Notably, slightly changed gene regulatory dynamics recapitulate the characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.

Treatment-related fertility impairment in long-term female childhood, adolescent and young adult cancer survivors: investigating dose-effect relationships in a European case-control study (PanCareLIFE)

STUDY QUESTION

Which chemotherapeutic agents and body site-specific radiation fields are dose-dependently associated with an increased risk of fertility impairment in long-term female childhood, adolescent and young adulthood (CAYA) cancer survivors?

SUMMARY ANSWER

Busulfan, lower abdominal radiotherapy (RT) and total body irradiation (TBI) seem to be associated with fertility impairment at any dose, whereas gonadotoxicity of melphalan and procarbazine is suggested at medium/high (>140 mg/m2) or high dose (>5600 mg/m2) therapy, respectively.

WHAT IS KNOWN ALREADY

Several treatment-related fertility deficits, as assessed by both self-reported outcomes and hormonal markers are known to occur following treatment of CAYA cancer. However, knowledge regarding precise dose-related estimates of these treatment-related risks are scarce.

STUDY DESIGN, SIZE, DURATION

The current case-control study was nested within the PanCareLIFE cohort study. In total, 1332 CAYA survivors from 8 countries, 9 institutions and 11 cohorts, participated in and contributed data to the study.

PARTICIPANTS/MATERIALS, SETTING, METHODS

All participants were female 5-year CAYA cancer survivors. In total, 450 cases (fertility impaired survivors) and 882 matched controls (not fertility impaired survivors) were included. Fertility impairment was defined using both questionnaire data (primary or secondary amenorrhea; use of artificial reproductive techniques; unfulfilled wish to conceive) and hormonal data (FSH and anti-Müllerian hormone (AMH)). Multivariable logistic regression models were used to investigate the effect of (i) alkylating agent exposure, and (ii) dose categories for individual chemotherapeutic agents and for RT-exposed body sites.

MAIN RESULTS AND THE ROLE OF CHANCE

A positive dose-effect relationship between cyclophosphamide equivalent dose (CED) score and fertility impairment was found, with survivors with a CED score > 7121 mg/m2 being at a significantly increased risk of fertility impairment (odds ratio (95% CI) = 2.6 (1.9-3.6) P < 0.001). Moreover, cumulative dose variables of the following treatments were significantly associated with fertility impairment: busulfan, carmustine, cyclophosphamide, melphalan, procarbazine, lower abdominal RT and TBI. Busulfan, lower abdominal RT and TBI seem to be associated with fertility impairment at any dose, whereas gonadotoxicity of melphalan and procarbazine is suggested at medium/high (>140 mg/m2) or high dose (>5600 mg/m2) therapy, respectively.

LIMITATIONS, REASONS FOR CAUTION

Our study may have been subject to selection bias since data from about half of the original base cohorts were available for the current study. This could impact the generalizability of our study results.

WIDER IMPLICATIONS OF THE FINDINGS

We identified survivors at high risk for fertility impairment and, consequently, for a reduced or even absent reproductive life span. Both girls and young women who are about to start anti-cancer treatment, as well as adult female survivors, should be counselled about future parenthood and referred to a reproductive specialist for fertility preservation, if desired.

STUDY FUNDING/COMPETING INTEREST(S)

This study has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 602030. There are no competing interests.

TRIAL REGISTRATION NUMBER

n/a.

Connectivity within regions characterizes epilepsy duration and treatment outcome

Finding clear connectome biomarkers for temporal lobe epilepsy (TLE) patients, in particular at early disease stages, remains a challenge. Currently, the whole-brain structural connectomes are analyzed based on coarse parcellations (up to 1,000 nodes). However, such global parcellation-based connectomes may be unsuitable for detecting more localized changes in patients. Here, we use a high-resolution network (~50,000-nodes overall) to identify changes at the local level (within brain regions) and test its relation with duration and surgical outcome. Patients with TLE (n = 33) and age-, sex-matched healthy subjects (n = 36) underwent high-resolution (~50,000 nodes) structural network construction based on deterministic tracking of diffusion tensor imaging. Nodes were allocated to 68 cortical regions according to the Desikan-Killany atlas. The connectivity within regions was then used to predict surgical outcome. MRI processing, network reconstruction, and visualization of network changes were integrated into the NICARA (https://nicara.eu). Lower clustering coefficient and higher edge density were found for local connectivity within regions in patients, but were absent for the global network between regions (68 cortical regions). Local connectivity changes, in terms of the number of changed regions and the magnitude of changes, increased with disease duration. Local connectivity yielded a better surgical outcome prediction (Mean value: 95.39% accuracy, 92.76% sensitivity, and 100% specificity) than global connectivity. Connectivity within regions, compared to structural connectivity between brain regions, can be a more efficient biomarker for epilepsy assessment and surgery outcome prediction of medically intractable TLE.

Understanding neural flexibility from a multifaceted definition

Flexibility is a hallmark of human intelligence. Emerging studies have proposed several flexibility measurements at the level of individual regions, to produce a brain map of neural flexibility. However, flexibility is usually inferred from separate components of brain activity (i.e., intrinsic/task-evoked), and different definitions are used. Moreover, recent studies have argued that neural processing may be more than a task-driven and intrinsic dichotomy. Therefore, the understanding to neural flexibility is still incomplete. To address this issue, we propose a multifaceted definition of neural flexibility according to three key features: broad cognitive engagement, distributed connectivity, and adaptive connectome dynamics. For these three features, we first review the advances in computational approaches, their functional relevance, and their potential pitfalls. We then suggest a set of metrics that can help us assign a flexibility rating to each region. Subsequently, we present an emergent probabilistic view for further understanding the functional operation of individual regions in the unified framework of intrinsic and task-driven states. Finally, we highlight several areas related to the multifaceted definition of neural flexibility for future research. This review not only strengthens our understanding of flexible human brain, but also suggests that the measure of neural flexibility could bridge the gap between understanding intrinsic and task-driven brain function dynamics.

Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression

Late-life depression (LLD) may increase the risk of Alzheimer's dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and may be associated with distinct cognitive symptoms. We recruited 26 and 27 depressed mild cognitive impairment (MCI) patients with (LLD-MCI-A(+)) and without amyloid accumulation (LLD-MCI-A(-)), respectively, and 21 normal controls. We extracted structural brain networks using their diffusion-weighted images. We aimed to compare the distinct network deterioration in LLD-MCI with and without amyloid accumulation and the relationship with their distinct cognitive decline. Thus, we performed a group comparison of the network topological measures and investigated any correlations with neurocognitive testing scores. Topological features of brain networks were different according to the presence of amyloid accumulation. Disrupted network connectivity was highly associated with impaired recall and recognition in LLD-MCI-A(+) patients. Inattention and dysexecutive function were more influenced by the altered networks involved in fronto-limbic circuitry dysfunction in LLD-MCI-A(-) patients. Our results show that alterations in brain network topology may reflect different cognitive dysfunction depending on amyloid accumulation in depressed older adults with MCI.

Towards simulations of long-term behavior of neural networks: Modeling synaptic plasticity of connections within and between human brain regions

Simulations of neural networks can be used to study the direct effect of internal or external changes on brain dynamics. However, some changes are not immediate but occur on the timescale of weeks, months, or years. Examples include effects of strokes, surgical tissue removal, or traumatic brain injury but also gradual changes during brain development. Simulating network activity over a long time, even for a small number of nodes, is a computational challenge. Here, we model a coupled network of human brain regions with a modified Wilson-Cowan model representing dynamics for each region and with synaptic plasticity adjusting connection weights within and between regions. Using strategies ranging from different models for plasticity, vectorization and a different differential equation solver setup, we achieved one second runtime for one second biological time.

NIHBA: a network interdiction approach for metabolic engineering design

MOTIVATION

Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solutions in a single run.

RESULTS

Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users' production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ∼1 h, e.g. studied in this article).

AVAILABILITY AND IMPLEMENTATION

Source code implemented in the MATALAB Cobratoolbox is freely available at https://github.com/chang88ye/NIHBA.

CONTACT

math4neu@gmail.com or natalio.krasnogor@ncl.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Reliability and comparability of human brain structural covariance networks

Structural covariance analysis is a widely used structural MRI analysis method which characterises the co-relations of morphology between brain regions over a group of subjects. To our knowledge, little has been investigated in terms of the comparability of results between different data sets of healthy human subjects, as well as the reliability of results over the same subjects in different rescan sessions, image resolutions, or FreeSurfer versions. In terms of comparability, our results show substantial differences in the structural covariance matrix between data sets of age- and sex-matched healthy human adults. These differences persist after univariate site correction, they are exacerbated by low sample sizes, and they are most pronounced when using average cortical thickness as a morphological measure. Down-stream graph theoretic analyses further show statistically significant differences. In terms of reliability, substantial differences were also found when comparing repeated scan sessions of the same subjects, image resolutions, and even FreeSurfer versions of the same image. We could further estimate the relative measurement error and showed that it is largest when using cortical thickness as a morphological measure. Using simulated data, we argue that cortical thickness is least reliable because of larger relative measurement errors. Practically, we make the following recommendations (1) combining subjects across sites into one group should be avoided, particularly if sites differ in image resolutions, subject demographics, or preprocessing steps; (2) surface area and volume should be preferred as morphological measures over cortical thickness; (3) a large number of subjects (n≫30 for the Desikan-Killiany parcellation) should be used to estimate structural covariance; (4) measurement error should be assessed where repeated measurements are available; (5) if combining sites is critical, univariate (per ROI) site-correction is insufficient, but error covariance (between ROIs) should be explicitly measured and modelled.

[Thermographic monitoring of skin surface temperature associated with hot-iron disbudding in calves]

INTRODUCTION

The goal of this study was to determine the skin surface temperatures of the head using thermography in 28 German Holstein heifer calves at the time of hot iron disbudding. Calves were divided into group 1 (hot-iron disbudding, n = 14) and 2 (sham disbudding, n = 14). Thermographic measurements were made at eight locations of the head (area surrounding both horn buds, both horn buds, muzzle, mucous membranes of the muzzle, both eyes) at nine time points (- 60 min (basal value), time of disbudding, 5, 30, 60, 90, 120, 240 and 480 min after disbudding) using a high-end thermographic camera (ThermoPro TP8, Firma DIAS Infrared GmbH). The rectal temperature was measured 60 min before and 5, 240 and 480 min after disbudding. The statistical software SAS version 9.4 was used for analysis. Skin surface temperatures and rectal temperature correlated at several locations (rp ≥ 0.45; p ≤ 0.05). The maximum temperature (approx. 67 ºC) was measured at the horn buds immediately after the hot-iron procedure. By five and 30 min after hot-iron disbudding, the temperature of the horn buds had decreased by up to 50%, whereas the temperatures at the other locations had increased significantly (p.

Prevalence of insulin as a first-line therapy and associated factors in people with type 2 diabetes in German primary care practices

AIM

To evaluate how many people with type 2 diabetes receive a treatment regimen with insulin as a first-line therapy and the factors associated with this.

METHODS

This retrospective study was based on data from the Disease Analyzer database and included 10 497 people with type 2 diabetes with an initial prescription of anti-hyperglycaemic therapy from 859 general and diabetologist practices in Germany between January 2014 and December 2018. The main outcome of the study was the prevalence of insulin as a first-line therapy. A multivariable logistic regression model was performed to investigate the association between predefined variables and the probability of receiving insulin as a first-line therapy.

RESULTS

A total of 7.1% of participants received insulin as a first-line therapy. Diabetologist practice [odds ratio (OR) 2.71, 95% confidence interval (CI) 1.81-4.06], age > 80 years (OR 2.35, 95% CI 1.20-4.61) compared with age ≤ 40 years, HbA_1c ≥ 86 mmol/mol (10%) (OR 2.99, 95% CI 1.81-4.95) compared with HbA_1c < 48 mmol/mol (6.5%), renal complications (OR 1.91, 95% CI 1.29-2.81), peripheral artery disease (OR 1.94, 95% CI 1.30-2.81), neurological complications (OR 1.45, 95% CI 1.00-2.09), Charlson Comorbidity Index (OR 1.16, 95% CI 1.08-1.25) and higher number of different drugs prescribed within 12 months prior-the index date (OR 1.09, 95% CI 1.05-1.12) were significantly associated with the probability of receiving insulin as a first-line therapy.

CONCLUSION

Insulin is rarely used as a first-line therapy in people with type 2 diabetes. Furthermore, a person's likelihood of receiving insulin as a first-line therapy is significantly influenced by diabetologist practice, age, HbA_1c ≥ 86 mmol/mol (10%), renal, neurological and vascular complications, higher multimorbidity, and polypharmacy.

A Scalable Test Suite for Continuous Dynamic Multiobjective Optimization

Dynamic multiobjective optimization (DMO) has gained increasing attention in recent years. Test problems are of great importance in order to facilitate the development of advanced algorithms that can handle dynamic environments well. However, many of the existing dynamic multiobjective test problems have not been rigorously constructed and analyzed, which may induce some unexpected bias when they are used for algorithmic analysis. In this paper, some of these biases are identified after a review of widely used test problems. These include poor scalability of objectives and, more important, problematic overemphasis of static properties rather than dynamics making it difficult to draw accurate conclusion about the strengths and weaknesses of the algorithms studied. A diverse set of dynamics and features is then highlighted that a good test suite should have. We further develop a scalable continuous test suite, which includes a number of dynamics or features that have been rarely considered in literature but frequently occur in real life. It is demonstrated with empirical studies that the proposed test suite is more challenging to the DMO algorithms found in the literature. The test suite can also test algorithms in ways that existing test suites cannot.

[Thermographic examination of head surface temperatures of calves under field conditions]

INTRODUCTION

Thermographic examination of 157 German Holstein heifer calves was performed to investigate the feasibility of this technique for on-farm recording of surface temperature of the head and to examine potential factors that affect the recordings. Baseline values were obtained from six defined locations on the head including both eyes, both horn buds, the muzzle and the mucous membrane of the muzzle using a high-end thermographic camera (ThermoPro TP8, Firma DIAS Infrared GmbH). Evaluation of the influence of various factors on thermographic measurements showed that ambient temperature had the largest effect on surface temperature of the head (regression coefficient, 0.10 to 0.32, p ≤ 0.01) whereas humidity had no effect (in t-test p ≥ 0.33 over all locations). There was a no correlation between rectal temperature and surface temperature (rp ≤ 0.05). The surface temperature decreased with increasing age of the calves (regression coefficient, - 0.42 to - 0.14, p ≤ 0.01). The agreement between double readings made shortly after one another was excellent at all locations (r ≥ 0.95). The emission of infrared energy varied among different locations; the most infrared energy was emitted by the eyes and the least by the muzzle. Paired locations (eyes and horn buds) had symmetric emission patterns of infrared energy. Measuring the surface temperature of the head of calves in their normal barn environment using a standardised protocol was feasible and thus could potentially be used for monitoring calves under field conditions.

Divisive gain modulation enables flexible and rapid entrainment in a neocortical microcircuit model

Neocortical circuits exhibit a rich dynamic repertoire, and their ability to achieve entrainment (adjustment of their frequency to match the input frequency) is thought to support many cognitive functions and indicate functional flexibility. Although previous studies have explored the influence of various circuit properties on this phenomenon, the role of divisive gain modulation (or divisive inhibition) is unknown. This gain control mechanism is thought to be delivered mainly by the soma-targeting interneurons in neocortical microcircuits. In this study, we use a neural mass model of the neocortical microcircuit (extended Wilson-Cowan model) featuring both soma-targeting and dendrite-targeting interneuronal subpopulations to investigate the role of divisive gain modulation in entrainment. Our results demonstrate that the presence of divisive inhibition in the microcircuit, as delivered by the soma-targeting interneurons, enables its entrainment to a wider range of input frequencies. Divisive inhibition also promotes a faster entrainment, with the microcircuit needing less time to converge to the fully entrained state. We suggest that divisive inhibition, working alongside subtractive inhibition, allows for more adaptive oscillatory responses in neocortical circuits and, thus, supports healthy brain functioning.NEW & NOTEWORTHY We introduce a computational neocortical microcircuit model that features two inhibitory neural populations, with one providing subtractive and the other divisive inhibition to the excitatory population. We demonstrate that divisive inhibition widens the range of input frequencies to which the microcircuit can become entrained and diminishes the time needed to reach full entrainment. We suggest that divisive inhibition enables more adaptive oscillatory activity, with important implications for both normal and pathological brain function.

Weighted network measures reveal differences between dementia types: An EEG study

The diagnosis of dementia with Lewy bodies (DLB) versus Alzheimer's disease (AD) can be difficult especially early in the disease process. However, one inexpensive and non‐invasive biomarker which could help is electroencephalography (EEG). Previous studies have shown that the brain network architecture assessed by EEG is altered in AD patients compared with age‐matched healthy control people (HC). However, similar studies in Lewy body diseases, that is, DLB and Parkinson's disease dementia (PDD) are still lacking. In this work, we (a) compared brain network connectivity patterns across conditions, AD, DLB and PDD, in order to infer EEG network biomarkers that differentiate between these conditions, and (b) tested whether opting for weighted matrices led to more reliable results by better preserving the topology of the network. Our results indicate that dementia groups present with reduced connectivity in the EEG α band, whereas DLB shows weaker posterior–anterior patterns within the β‐band and greater network segregation within the θ‐band compared with AD. Weighted network measures were more consistent across global thresholding levels, and the network properties reflected reduction in connectivity strength in the dementia groups. In conclusion, β‐ and θ‐band network measures may be suitable as biomarkers for discriminating DLB from AD, whereas the α‐band network is similarly affected in DLB and PDD compared with HC. These variations may reflect the impairment of attentional networks in Parkinsonian diseases such as DLB and PDD.

Periodic Operation of a Dynamic DNA Origami Structure Utilizing the Hydrophilic-Hydrophobic Phase-Transition of Stimulus-Sensitive Polypeptides

Dynamic DNA nanodevices are designed to perform structure-encoded motion actuated by a variety of different physicochemical stimuli. In this context, hybrid devices utilizing other components than DNA have the potential to considerably expand the library of functionalities. Here, the reversible reconfiguration of a DNA origami structure using the stimulus sensitivity of elastin-like polypeptides is reported. To this end, a rectangular sheet made using the DNA origami technique is functionalized with these peptides and by applying changes in salt concentration the hydrophilic-hydrophobic phase transition of these peptides actuate the folding of the structure. The on-demand and reversible switching of the rectangle is driven by externally imposed temperature oscillations and appears at specific transition temperatures. Using transmission electron microscopy, it is shown that the structure exhibits distinct conformational states with different occupation probabilities, which are dependent on structure-intrinsic parameters such as the local number and the arrangement of the peptides on the rectangle. It is also shown through ensemble fluorescence resonance energy transfer spectroscopy that the transition temperature and thus the thermodynamics of the rectangle-peptide system depends on the stimuli salt concentration and temperature, as well as on the intrinsic parameters.

Structural correlates of attention dysfunction in Lewy body dementia and Alzheimer's disease: an ex-Gaussian analysis

BACKGROUND

Lewy body dementia (LBD) and Alzheimer's disease (AD) are common forms of degenerative dementia. While they are characterized by different clinical profiles, attentional deficits are a common feature. The objective of this study was to investigate how attentional problems in LBD and AD differentially affect different aspects of reaction time performance and to identify possible structural neural correlates.

METHODS

We studied reaction time data from an attention task comparing 39 LBD patients, 28 AD patients, and 22 age-matched healthy controls. Data were fitted to an ex-Gaussian model to characterize different facets of the reaction time distribution (mean reaction time, reaction time variability, and the subset of extremely slow responses). Correlations between ex-Gaussian parameters and grey and white matter volume were assessed by voxel-based morphometry.

RESULTS

Both dementia groups showed an increase in extremely slow responses. While there was no difference between AD and controls with respect to mean reaction time and variability, both were significantly increased in LBD patients compared to controls and AD. There were widespread correlations between mean reaction time and variability and grey matter loss in AD, but not in LBD.

CONCLUSIONS

This study shows that different aspects of reaction time performance are differentially affected by AD and LBD, with a difference in structural neural correlates underlying the observed behavioural deficits. While impaired attentional performance is linked to brain atrophy in AD, in LBD it might be related to functional or microstructural rather than macrostructural changes.

Dysfunctional brain dynamics and their origin in Lewy body dementia

Lewy body dementia includes dementia with Lewy bodies and Parkinson's disease dementia and is characterized by transient clinical symptoms such as fluctuating cognition, which might be driven by dysfunction of the intrinsic dynamic properties of the brain. In this context we investigated whole-brain dynamics on a subsecond timescale in 42 Lewy body dementia compared to 27 Alzheimer's disease patients and 18 healthy controls using an EEG microstate analysis in a cross-sectional design. Microstates are transiently stable brain topographies whose temporal characteristics provide insight into the brain's dynamic repertoire. Our additional aim was to explore what processes in the brain drive microstate dynamics. We therefore studied associations between microstate dynamics and temporal aspects of large-scale cortical-basal ganglia-thalamic interactions using dynamic functional MRI measures given the putative role of these subcortical areas in modulating widespread cortical function and their known vulnerability to Lewy body pathology. Microstate duration was increased in Lewy body dementia for all microstate classes compared to Alzheimer's disease (P < 0.001) and healthy controls (P < 0.001), while microstate dynamics in Alzheimer's disease were largely comparable to healthy control levels, albeit with altered microstate topographies. Correspondingly, the number of distinct microstates per second was reduced in Lewy body dementia compared to healthy controls (P < 0.001) and Alzheimer's disease (P < 0.001). In the dementia with Lewy bodies group, mean microstate duration was related to the severity of cognitive fluctuations (ρ = 0.56, PFDR = 0.038). Additionally, mean microstate duration was negatively correlated with dynamic functional connectivity between the basal ganglia (r = - 0.53, P = 0.003) and thalamic networks (r = - 0.38, P = 0.04) and large-scale cortical networks such as visual and motor networks in Lewy body dementia. The results indicate a slowing of microstate dynamics and disturbances to the precise timing of microstate sequences in Lewy body dementia, which might lead to a breakdown of the intricate dynamic properties of the brain, thereby causing loss of flexibility and adaptability that is crucial for healthy brain functioning. When contrasted with the largely intact microstate dynamics in Alzheimer's disease, the alterations in dynamic properties in Lewy body dementia indicate a brain state that is less responsive to environmental demands and might give rise to the apparent slowing in thinking and intermittent confusion which typify Lewy body dementia. By using Lewy body dementia as a probe pathology we demonstrate a potential link between dynamic functional MRI fluctuations and microstate dynamics, suggesting that dynamic interactions within the cortical-basal ganglia-thalamic loop might play a role in the modulation of EEG dynamics.

Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease

We studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) compared to controls, how it differs between the two dementia subtypes, and a possible relation between dynamic connectivity alterations and temporally transient clinical symptoms in DLB. Resting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analyzed using dual regression to determine between-network functional connectivity. Subsequently, we used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity. Dynamic connectivity measures that showed significant group differences were tested for correlations with clinical symptom severity. Our results show that AD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. There were no significant correlations between dynamic connectivity measures and clinical symptom severity. An inability to switch out of states of low inter-network connectivity into more highly and specifically connected network configurations might be related to the presence of dementia in general as it was observed in both AD and DLB. In contrast, the loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to cognitive slowing and an inability to respond appropriately to situational demands.

The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX) Version 2.0: Modelling in vitro electrical stimulation of brain tissue

Neuronal circuits can be modelled in detail allowing us to predict the effects of stimulation on individual neurons. Electrical stimulation of neuronal circuits in vitro and in vivo excites a range of neurons within the tissue and measurements of neural activity, e.g the local field potential (LFP), are again an aggregate of a large pool of cells. The previous version of our Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX) allowed for the simulation of the LFP generated by a patch of brain tissue. Here, we extend VERTEX to simulate the effect of electrical stimulation through a focal electric field. We observe both direct changes in neural activity and changes in synaptic plasticity. Testing our software in a model of a rat neocortical slice, we determine the currents contributing to the LFP, the effects of paired pulse stimulation to induce short term plasticity (STP), and the effect of theta burst stimulation (TBS) to induce long term potentiation (LTP).

Structural connectivity centrality changes mark the path toward Alzheimer's disease

Introduction

The pathophysiological process of Alzheimer's disease is thought to begin years before clinical decline, with evidence suggesting prion-like spreading processes of neurofibrillary tangles and amyloid plaques.

Methods

Using diffusion magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative database, we first identified relevant features for dementia diagnosis. We then created dynamic models with the Nathan Kline Institute-Rockland Sample database to estimate the earliest detectable stage associated with dementia in the simulated disease progression.

Results

A classifier based on centrality measures provides informative predictions. Strength and closeness centralities are the most discriminative features, which are associated with the medial temporal lobe and subcortical regions, together with posterior and occipital brain regions. Our model simulations suggest that changes associated with dementia begin to manifest structurally at early stages.

Discussion

Our analyses suggest that diffusion magnetic resonance imaging–based centrality measures can offer a tool for early disease detection before clinical dementia onset.

Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy

Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence diagnosis based on MRI is challenging. Anatomical abnormalities underlying brain dysfunctions in IGE are unclear and their relation to the pathomechanisms of epileptogenesis is poorly understood.

In this study, we applied connectometry, an advanced quantitative neuroimaging technique for investigating localised changes in white-matter tissues in vivo. Analysing white matter structures of 32 subjects we incorporated our in vivo findings in a computational model of seizure dynamics to suggest a plausible mechanism of epileptogenesis.

Patients with IGE have significant bilateral alterations in major white-matter fascicles. In the cingulum, fornix, and superior longitudinal fasciculus, tract integrity is compromised, whereas in specific parts of tracts between thalamus and the precentral gyrus, tract integrity is enhanced in patients. Combining these alterations in a logistic regression model, we computed the decision boundary that discriminated patients and controls. The computational model, informed with the findings on the tract abnormalities, specifically highlighted the importance of enhanced cortico-reticular connections along with impaired cortico-cortical connections in inducing pathological seizure-like dynamics.

We emphasise taking directionality of brain connectivity into consideration towards understanding the pathological mechanisms; this is possible by combining neuroimaging and computational modelling. Our imaging evidence of structural alterations suggest the loss of cortico-cortical and enhancement of cortico-thalamic fibre integrity in IGE. We further suggest that impaired connectivity from cortical regions to the thalamic reticular nucleus offers a therapeutic target for selectively modifying the brain circuit for reversing the mechanisms leading to epileptogenesis.

•

Significant focal alterations along major white-matter fascicles in IGE patients are characterised.

•

Increased white matter integrity found in thalamo-cortical connections.

•

Decreased white matter integrity found in cortico-cortical connections.

•

Disease mechanism is investigated by combining the neuroimaging findings with a dynamical model of seizure activity.

•

Model implicates cortical projections to the thalamic reticular nucleus in IGE.

Structural Brain Correlates of Attention Dysfunction in Lewy Body Dementias and Alzheimer's Disease

Lewy body dementia (LBD) and Alzheimer's disease (AD) are common forms of dementia that have different clinical profiles but are both commonly associated with attentional deficits. The aim of this study was to investigate efficiency of different attentional systems in LBD and AD and its association with brain structural abnormalities. We studied reaction time (RT) data from 45 LBD, 31 AD patients and 22 healthy controls (HCs) using the Attention Network Test (ANT) to assess the efficiency of three different attentional systems: alerting, orienting and executive conflict. Voxel-based morphometry (VBM) was used to investigate relations between different attention components and cortical volume. Both dementia groups showed slower overall RTs than controls, with additional slowing in LBD relative to AD. There was a significant alerting effect in controls which was absent in the dementia groups, the executive conflict effect was greater in both dementia groups compared to controls, but the orienting effect did not differ between groups. Mean RT in AD was negatively correlated with occipital gray matter (GM) volume and in LBD orienting efficiency was negatively related to occipital white matter (WM) volume. Given that previous studies in less impaired patients suggest a maintenance of the alerting effect, the absent alerting effect in our study suggests a loss of alerting efficiency with dementia progression. While orienting was largely preserved, it might be related to occipital structural abnormalities in LBD. Executive function was markedly impaired in both dementia groups, however, the absence of relations to brain volume suggests that it might be more related to functional rather than macrostructural pathophysiological changes.