Editorial group: Cochrane Eyes and Vision Group. Publication status and date: New search for studies and content updated (no change to conclusions), published in Issue 8, 2015.

Students perceive a number of key barriers to research involvement and pursuit of research-orientated careers. Programmes designed to engage students with research should focus on overcoming identified barriers. Greater effort is needed to engage female students who report more significant barriers and less desire to follow research-orientated careers.

Enlarged perivascular spaces (EPVS), visible in brain MRI, are an important marker of small vessel disease and neuroinflammation. We systematically evaluated the literature up to June 2012 on possible methods for their computational assessment and analyzed confounds with lacunes and small white matter hyperintensities. We found six studies that assessed/identified EPVS computationally by seven different methods, and four studies that described techniques to automatically segment similar structures and are potentially suitable for EPVS segmentation. T2-weighted MRI was the only sequence that identified all EPVS, but FLAIR and T1-weighted images were useful in their differentiation. Inconsistency within the literature regarding their diameter and terminology, and overlap in shape, intensity, location, and size with lacunes, conspires against their differentiation and the accuracy and reproducibility of any computational segmentation technique. The most promising approach will need to combine various MR sequences and consider all these features for accurate EPVS determination.

Graphical abstract

Epilepsy is well-recognized as a disorder of brain networks. There is a growing body of research to identify critical nodes within dynamic epileptic networks with the aim to target therapies that halt the onset and propagation of seizures. In parallel, intracranial neuromodulation, including deep brain stimulation and responsive neurostimulation, are well-established and expanding as therapies to reduce seizures in adults with focal epilepsy; and there is emerging evidence for their efficacy in children and generalized seizure disorders. The convergence of these advancing fields is driving an era of ‘network-guided neuromodulation’ for epilepsy. In this review we distil the current literature on network mechanisms underlying neurostimulation for epilepsy. We discuss the modulation of key propagation points in the epileptogenic network, focusing primarily on thalamic nuclei targeted in current clinical practice. These include (a) the anterior nucleus of thalamus, now a clinically approved and targeted site for open loop stimulation, and increasingly targeted for responsive neurostimulation; and (b) the centromedian nucleus of the thalamus, a target for both deep brain stimulation and responsive neurostimulation in generalized-onset epilepsies. We discuss briefly the networks associated with other emerging neuromodulation targets, such as the pulvinar of the thalamus, piriform cortex, septal area, subthalamic nucleus, cerebellum and others. We report synergistic findings garnered from multiple modalities of investigation that revealed structural and functional networks associated with these propagation points – including scalp and invasive electroencephalography, diffusion and functional magnetic resonance imaging. We also report on intracranial recordings from implanted devices which provide us data on the dynamic networks we are aiming to modulate. Finally, we review the continuing evolution of network-guided neurostimulation for epilepsy to accelerate progress towards two major goals: (1) to use pre-surgical network analyses to determine patient candidacy for neurostimulation for epilepsy by providing network biomarkers that predict efficacy; and (2) to deliver precise, personalized and effective antiepileptic stimulation to prevent and arrest seizures, limit seizure propagation through mapping and modulation of each patients’ individual epileptogenic networks.