Navigating spaces between conservation research and practice: are we making progress?

1. Despite aspirations for conservation impact, mismatches between research and implementation have limited progress towards this goal. There is, therefore, an urgent need to identify how we can more effectively navigate the spaces between research and practice. 2. In 2014, we ran a workshop with conservation researchers and practitioners to identify mismatches between research and implementation that needed to be overcome to deliver evidence‐informed conservation action. Five mismatches were highlighted: spatial, temporal, priority, communication, and institutional. 3. Since 2014, thinking around the ‘research–implementation gap’ has progressed. The term ‘gap’ has been replaced by language around the dynamic ‘spaces’ between research and action, representing a shift in thinking around what it takes to better align research and practice. 4. In 2019, we ran a follow‐up workshop reflecting on this shift, whether the five mismatches identified in the 2014 workshop were still present in conservation, and whether progress had been made to overcome these mismatches during the past 5 years. We found that while there has been progress, we still have some way to go across all dimensions. 5. Here, we report on the outcomes of the 2019 workshop, reflect on what has changed over the past 5 years, and offer 10 recommendations for strengthening the alignment of conservation research and practice

A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation

Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12–15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols

Activity of cortical and thalamic neurons during the slow (<1 Hz) rhythm in the mouse in vivo

During NREM sleep and under certain types of anaesthesia, the mammalian brain exhibits a distinctive slow (<1 Hz) rhythm. At the cellular level, this rhythm correlates with so-called UP and DOWN membrane potential states. In the neocortex, these UP and DOWN states correspond to periods of intense network activity and widespread neuronal silence, respectively, whereas in thalamocortical (TC) neurons, UP/DOWN states take on a more stereotypical oscillatory form, with UP states commencing with a low-threshold Ca2+ potential (LTCP). Whilst these properties are now well recognised for neurons in cats and rats, whether or not they are also shared by neurons in the mouse is not fully known. To address this issue, we obtained intracellular recordings from neocortical and TC neurons during the slow (<1 Hz) rhythm in anaesthetised mice. We show that UP/DOWN states in this species are broadly similar to those observed in cats and rats, with UP states in neocortical neurons being characterised by a combination of action potential output and intense synaptic activity, whereas UP states in TC neurons always commence with an LTCP. In some neocortical and TC neurons, we observed ‘spikelets’ during UP states, supporting the possible presence of electrical coupling. Lastly, we show that, upon tonic depolarisation, UP/DOWN states in TC neurons are replaced by rhythmic high-threshold bursting at ~5 Hz, as predicted by in vitro studies. Thus, UP/DOWN state generation appears to be an elemental and conserved process in mammals that underlies the slow (<1 Hz) rhythm in several species, including humans

Pathological tau disrupts ongoing network activity

SummaryPathological tau leads to dementia and neurodegeneration in tauopathies, including Alzheimer’s disease. It has been shown to disrupt cellular and synaptic functions, yet its effects on the function of the intact neocortical network remain unknown. Using in vivo intracellular and extracellular recordings, we measured ongoing activity of neocortical pyramidal cells during various arousal states in the rTg4510 mouse model of tauopathy, prior to significant cell death, when only a fraction of the neurons show pathological tau. In transgenic mice, membrane potential oscillations are slower during slow-wave sleep and under anesthesia. Intracellular recordings revealed that these changes are due to longer Down states and state transitions of membrane potentials. Firing rates of transgenic neurons are reduced, and firing patterns within Up states are altered, with longer latencies and inter-spike intervals. By changing the activity patterns of a subpopulation of affected neurons, pathological tau reduces the activity of the neocortical network

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep

Extensive astrocyte synchronization advances neuronal coupling in slow wave activity in vivo

Slow wave activity (SWA) is a characteristic brain oscillation in sleep and quiet wakefulness. Although the cell types contributing to SWA genesis are not yet identified, the principal role of neurons in the emergence of this essential cognitive mechanism has not been questioned. To address the possibility of astrocytic involvement in SWA, we used a transgenic rat line expressing a calcium sensitive fluorescent protein in both astrocytes and interneurons and simultaneously imaged astrocytic and neuronal activity in vivo. Here we demonstrate, for the first time, that the astrocyte network display synchronized recurrent activity in vivo coupled to UP states measured by field recording and neuronal calcium imaging. Furthermore, we present evidence that extensive synchronization of the astrocytic network precedes the spatial build-up of neuronal synchronization. The earlier extensive recruitment of astrocytes in the synchronized activity is reinforced by the observation that neurons surrounded by active astrocytes are more likely to join SWA, suggesting causality. Further supporting this notion, we demonstrate that blockade of astrocytic gap junctional communication or inhibition of astrocytic Ca2+ transients reduces the ratio of both astrocytes and neurons involved in SWA. These in vivo findings conclusively suggest a causal role of the astrocytic syncytium in SWA generation