Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing.

Background and purpose Functional neurological disorder (FND) is common, and symptoms can be severe. There have been no international large‐scale studies of patient experiences of FND. Methods A patient questionnaire was created to assess FND patient characteristics, symptom comorbidities and illness perceptions. Respondents were recruited internationally through an open access questionnaire via social media and patient groups over a month‐long period. Results In total, 1048 respondents from 16 countries participated. Mean age was 42 years (86% female). Median FND symptom duration was 5 years, and median time from first symptom to diagnosis was 2 years. Mean number of current symptoms (core FND and associated) was 9.9. Many respondents had associated symptoms, for example fatigue (93%), memory difficulties (80%) and headache (70%). Self‐reported psychiatric comorbidities were relatively common (depression, 43%; anxiety, 51%; panic, 20%; and post‐traumatic stress disorder, 22%). Most respondents reported that FND had multiple causes, including physical and psychological. Conclusions This large survey adds further evidence that people with FND typically have high levels of multiple symptom comorbidity with resultant distress. It also supports the notion that associated physical symptoms are of particular clinical significance in FND patients. Dualistic ideas of FND were not supported by respondents, who generally preferred to conceptualize the disorder as one at the interface of mind and brain. The need for a broad approach to this poorly served patient group is highlighted. Potential selection and response biases due to distribution of the survey online, mostly via FND patient groups, are a key limitation.

Objective: Diagnostic screening for functional neurological disorders (FNDs) continues to pose a challenge. Simple symptom counts fail clearly to discriminate patients with FND but are useful diagnostically during face-to-face assessments. A self-completed screening questionnaire evaluating specific features of FNDs would be useful for screening purposes in clinical and research settings. Methods: The Edinburgh Neurosymptoms Questionnaire (ENS) is a 30-item survey of presence and nature of: blackouts, weakness, hemisensory syndrome, memory problems, tremor, pain, fatigue, globus, multiple medical problems, and operations constructed via literature review and expert consensus. We conducted a pilot of the ENS on new general neurology clinic attendees at a large regional neuroscience centre. Patients were grouped according to consultant neurologist impression Not at " L or C This classification was compared against ???? Results: Blackouts, weakness and memory questions provided reasonable diagnostic utility (AUROC = 0.94, 0.71, 0.74 respectively) in single symptom analysis. All other symptoms lacked discriminating features. A multivariate linear model with all symptoms predicted functional classification with moderate diagnostic utility (AUROC = 0.83), specificity of 0.97, sensitivity of 0.47. Pain and blackout scores provided the most accurate predictor of functional classification. Conclusion: The diagnosis of functional neurological disorders is difficult using unguided, self-reported questions. Our results suggest some promise however for differentiation of functional/dissociative blackouts from other causes, and further refinements could lead to a more useful clinical screening tool for other symptoms.

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