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2,824 results on '"Burgess, Neil"'

1. Involving citizens in monitoring the Kunming–Montreal Global Biodiversity Framework

Author

Danielsen, Finn, Ali, Natasha, Andrianandrasana, Herizo T., Baquero, Andrea, Basilius, Umai, de Araujo Lima Constantino, Pedro, Despot-Belmonte, Katherine, Frederiksen, Per Ole, Isaac, Maxim, Jakobsen, PâviâraK, Klimmek, Helen, Mapendembe, Abisha, Meng, Han, Schmidt-Vogt, Dietrich, Sophat, Seak, Sulyandziga, Rodion, Virnig, Anne L. S., Zhang, Di, and Burgess, Neil D.

Published
2024
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4. Successor-Predecessor Intrinsic Exploration

Author

Yu, Changmin, Burgess, Neil, Sahani, Maneesh, and Gershman, Samuel J.

Subjects
Computer Science - Machine Learning
Abstract

Exploration is essential in reinforcement learning, particularly in environments where external rewards are sparse. Here we focus on exploration with intrinsic rewards, where the agent transiently augments the external rewards with self-generated intrinsic rewards. Although the study of intrinsic rewards has a long history, existing methods focus on composing the intrinsic reward based on measures of future prospects of states, ignoring the information contained in the retrospective structure of transition sequences. Here we argue that the agent can utilise retrospective information to generate explorative behaviour with structure-awareness, facilitating efficient exploration based on global instead of local information. We propose Successor-Predecessor Intrinsic Exploration (SPIE), an exploration algorithm based on a novel intrinsic reward combining prospective and retrospective information. We show that SPIE yields more efficient and ethologically plausible exploratory behaviour in environments with sparse rewards and bottleneck states than competing methods. We also implement SPIE in deep reinforcement learning agents, and show that the resulting agent achieves stronger empirical performance than existing methods on sparse-reward Atari games.

Published
2023

6. FP8 Formats for Deep Learning

Author

Micikevicius, Paulius, Stosic, Dusan, Burgess, Neil, Cornea, Marius, Dubey, Pradeep, Grisenthwaite, Richard, Ha, Sangwon, Heinecke, Alexander, Judd, Patrick, Kamalu, John, Mellempudi, Naveen, Oberman, Stuart, Shoeybi, Mohammad, Siu, Michael, and Wu, Hao

Subjects
Computer Science - Machine Learning
Abstract

FP8 is a natural progression for accelerating deep learning training inference beyond the 16-bit formats common in modern processors. In this paper we propose an 8-bit floating point (FP8) binary interchange format consisting of two encodings - E4M3 (4-bit exponent and 3-bit mantissa) and E5M2 (5-bit exponent and 2-bit mantissa). While E5M2 follows IEEE 754 conventions for representatio of special values, E4M3's dynamic range is extended by not representing infinities and having only one mantissa bit-pattern for NaNs. We demonstrate the efficacy of the FP8 format on a variety of image and language tasks, effectively matching the result quality achieved by 16-bit training sessions. Our study covers the main modern neural network architectures - CNNs, RNNs, and Transformer-based models, leaving all the hyperparameters unchanged from the 16-bit baseline training sessions. Our training experiments include large, up to 175B parameter, language models. We also examine FP8 post-training-quantization of language models trained using 16-bit formats that resisted fixed point int8 quantization.

Published
2022

7. Structured Recognition for Generative Models with Explaining Away

Author

Yu, Changmin, Soulat, Hugo, Burgess, Neil, and Sahani, Maneesh

Subjects
Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

A key goal of unsupervised learning is to go beyond density estimation and sample generation to reveal the structure inherent within observed data. Such structure can be expressed in the pattern of interactions between explanatory latent variables captured through a probabilistic graphical model. Although the learning of structured graphical models has a long history, much recent work in unsupervised modelling has instead emphasised flexible deep-network-based generation, either transforming independent latent generators to model complex data or assuming that distinct observed variables are derived from different latent nodes. Here, we extend amortised variational inference to incorporate structured factors over multiple variables, able to capture the observation-induced posterior dependence between latents that results from ``explaining away'' and thus allow complex observations to depend on multiple nodes of a structured graph. We show that appropriately parametrised factors can be combined efficiently with variational message passing in rich graphical structures. We instantiate the framework in nonlinear Gaussian Process Factor Analysis, evaluating the structured recognition framework using synthetic data from known generative processes. We fit the GPFA model to high-dimensional neural spike data from the hippocampus of freely moving rodents, where the model successfully identifies latent signals that correlate with behavioural covariates.

Published
2022

8. SEREN: Knowing When to Explore and When to Exploit

Author

Yu, Changmin, Mguni, David, Li, Dong, Sootla, Aivar, Wang, Jun, and Burgess, Neil

Subjects
Computer Science - Machine Learning
Abstract

Efficient reinforcement learning (RL) involves a trade-off between "exploitative" actions that maximise expected reward and "explorative'" ones that sample unvisited states. To encourage exploration, recent approaches proposed adding stochasticity to actions, separating exploration and exploitation phases, or equating reduction in uncertainty with reward. However, these techniques do not necessarily offer entirely systematic approaches making this trade-off. Here we introduce SElective Reinforcement Exploration Network (SEREN) that poses the exploration-exploitation trade-off as a game between an RL agent -- \exploiter, which purely exploits known rewards, and another RL agent -- \switcher, which chooses at which states to activate a pure exploration policy that is trained to minimise system uncertainty and override Exploiter. Using a form of policies known as impulse control, \switcher is able to determine the best set of states to switch to the exploration policy while Exploiter is free to execute its actions everywhere else. We prove that SEREN converges quickly and induces a natural schedule towards pure exploitation. Through extensive empirical studies in both discrete (MiniGrid) and continuous (MuJoCo) control benchmarks, we show that SEREN can be readily combined with existing RL algorithms to yield significant improvement in performance relative to state-of-the-art algorithms., Comment: arXiv admin note: text overlap with arXiv:2112.02618, arXiv:2103.09159, arXiv:2110.14468

Published
2022

9. Inequitable Gains and Losses from Conservation in a Global Biodiversity Hotspot

Author

Platts, Philip J., Schaafsma, Marije, Turner, R. Kerry, Burgess, Neil D., Fisher, Brendan, Mbilinyi, Boniface P., Munishi, Pantaleo K. T., Ricketts, Taylor H., Swetnam, Ruth D., Ahrends, Antje, Ashagre, Biniam B., Bayliss, Julian, Gereau, Roy E., Green, Jonathan M. H., Green, Rhys E., Jeha, Lena, Lewis, Simon L., Marchant, Rob, Marshall, Andrew R., Morse-Jones, Sian, Mwakalila, Shadrack, Njana, Marco A., Shirima, Deo D., Willcock, Simon, and Balmford, Andrew

Published
2023
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10. Learning State Representations via Retracing in Reinforcement Learning

Author

Yu, Changmin, Li, Dong, Hao, Jianye, Wang, Jun, and Burgess, Neil

Subjects
Computer Science - Machine Learning
Abstract

We propose learning via retracing, a novel self-supervised approach for learning the state representation (and the associated dynamics model) for reinforcement learning tasks. In addition to the predictive (reconstruction) supervision in the forward direction, we propose to include "retraced" transitions for representation / model learning, by enforcing the cycle-consistency constraint between the original and retraced states, hence improve upon the sample efficiency of learning. Moreover, learning via retracing explicitly propagates information about future transitions backward for inferring previous states, thus facilitates stronger representation learning for the downstream reinforcement learning tasks. We introduce Cycle-Consistency World Model (CCWM), a concrete model-based instantiation of learning via retracing. Additionally we propose a novel adaptive "truncation" mechanism for counteracting the negative impacts brought by "irreversible" transitions such that learning via retracing can be maximally effective. Through extensive empirical studies on visual-based continuous control benchmarks, we demonstrate that CCWM achieves state-of-the-art performance in terms of sample efficiency and asymptotic performance, whilst exhibiting behaviours that are indicative of stronger representation learning.

Published
2021

11. Integrated modeling of nature’s role in human well-being: A research agenda

Author

Chaplin-Kramer, Rebecca, Polasky, Stephen, Alkemade, Rob, Burgess, Neil D., Cheung, William W.L., Fetzer, Ingo, Harfoot, Mike, Hertel, Thomas W., Hill, Samantha L.L., Andrew Johnson, Justin, Janse, Jan H., José v. Jeetze, Patrick, Kim, HyeJin, Kuiper, Jan J., Lonsdorf, Eric, Leclère, David, Mulligan, Mark, Peterson, Garry D., Popp, Alexander, Roe, Stephanie, Schipper, Aafke M., Snäll, Tord, van Soesbergen, Arnout, Soterroni, Aline C., Stehfest, Elke, van Vuuren, Detlef P., Visconti, Piero, Wang-Erlandsson, Lan, Wells, Geoff, and Pereira, Henrique M.

Published
2024
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12. Prediction and Generalisation over Directed Actions by Grid Cells

Author

Yu, Changmin, Behrens, Timothy E. J., and Burgess, Neil

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Machine Learning
Abstract

Knowing how the effects of directed actions generalise to new situations (e.g. moving North, South, East and West, or turning left, right, etc.) is key to rapid generalisation across new situations. Markovian tasks can be characterised by a state space and a transition matrix and recent work has proposed that neural grid codes provide an efficient representation of the state space, as eigenvectors of a transition matrix reflecting diffusion across states, that allows efficient prediction of future state distributions. Here we extend the eigenbasis prediction model, utilising tools from Fourier analysis, to prediction over arbitrary translation-invariant directed transition structures (i.e. displacement and diffusion), showing that a single set of eigenvectors can support predictions over arbitrary directed actions via action-specific eigenvalues. We show how to define a "sense of direction" to combine actions to reach a target state (ignoring task-specific deviations from translation-invariance), and demonstrate that adding the Fourier representations to a deep Q network aids policy learning in continuous control tasks. We show the equivalence between the generalised prediction framework and traditional models of grid cell firing driven by self-motion to perform path integration, either using oscillatory interference (via Fourier components as velocity-controlled oscillators) or continuous attractor networks (via analysis of the update dynamics). We thus provide a unifying framework for the role of the grid system in predictive planning, sense of direction and path integration: supporting generalisable inference over directed actions across different tasks., Comment: In Proceedings of ICLR 2021

Published
2020

18. Probabilistic Successor Representations with Kalman Temporal Differences

Author

Geerts, Jesse P., Stachenfeld, Kimberly L., and Burgess, Neil

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Machine Learning
Abstract

The effectiveness of Reinforcement Learning (RL) depends on an animal's ability to assign credit for rewards to the appropriate preceding stimuli. One aspect of understanding the neural underpinnings of this process involves understanding what sorts of stimulus representations support generalisation. The Successor Representation (SR), which enforces generalisation over states that predict similar outcomes, has become an increasingly popular model in this space of inquiries. Another dimension of credit assignment involves understanding how animals handle uncertainty about learned associations, using probabilistic methods such as Kalman Temporal Differences (KTD). Combining these approaches, we propose using KTD to estimate a distribution over the SR. KTD-SR captures uncertainty about the estimated SR as well as covariances between different long-term predictions. We show that because of this, KTD-SR exhibits partial transition revaluation as humans do in this experiment without additional replay, unlike the standard TD-SR algorithm. We conclude by discussing future applications of the KTD-SR as a model of the interaction between predictive and probabilistic animal reasoning., Comment: Conference on Cognitive Computational Neuroscience

Published
2019
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22. Anatomo‐functional changes in neural substrates of cognitive memory in developmental amnesia: Insights from automated and manual Magnetic Resonance Imaging examinations.

Author

Chareyron, Loïc J., Chong, W. K. Kling, Banks, Tina, Burgess, Neil, Saunders, Richard C., and Vargha‐Khadem, Faraneh

Subjects
RECOLLECTION (Psychology), BRAIN damage, MAGNETIC resonance imaging, EPISODIC memory, SHORT-term memory
Abstract

Despite bilateral hippocampal damage dating to the perinatal or early childhood period and severely impaired episodic memory, patients with developmental amnesia continue to exhibit well‐developed semantic memory across the developmental trajectory. Detailed information on the extent and focality of brain damage in these patients is needed to hypothesize about the neural substrate that supports their remarkable capacity for encoding and retrieval of semantic memory. In particular, we need to assess whether the residual hippocampal tissue is involved in this preservation, or whether the surrounding cortical areas reorganize to rescue aspects of these critical cognitive memory processes after early injury. We used voxel‐based morphometry (VBM) analysis, automatic (FreeSurfer) and manual segmentation to characterize structural changes in the brain of an exceptionally large cohort of 23 patients with developmental amnesia in comparison with 32 control subjects. Both the VBM and the FreeSurfer analyses revealed severe structural alterations in the hippocampus and thalamus of patients with developmental amnesia. Milder damage was found in the amygdala, caudate, and parahippocampal gyrus. Manual segmentation demonstrated differences in the degree of atrophy of the hippocampal subregions in patients. The level of atrophy in CA‐DG subregions and subicular complex was more than 40%, while the atrophy of the uncus was moderate (−24%). Anatomo‐functional correlations were observed between the volumes of residual hippocampal subregions in patients and selective aspects of their cognitive performance, viz, intelligence, working memory, and verbal and visuospatial recall. Our findings suggest that in patients with developmental amnesia, cognitive processing is compromised as a function of the extent of atrophy in hippocampal subregions. More severe hippocampal damage may be more likely to promote structural and/or functional reorganization in areas connected to the hippocampus. In this hypothesis, different levels of hippocampal function may be rescued following this variable reorganization. Our findings document not only the extent, but also the limits of circuit reorganization occurring in the young brain after early bilateral hippocampal damage. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Behavioral Evidence for Pattern Separation in Human Episodic Memory

Author

Zotow, Ewa, Bisby, James A., and Burgess, Neil

Abstract

An essential feature of episodic memory is the ability to recall the multiple elements relating to one event from the multitude of elements relating to other, potentially similar events. Hippocampal pattern separation is thought to play a fundamental role in this process, by orthogonalizing the representations of overlapping events during encoding, to reduce interference between them during the process of pattern completion by which one or other is recalled. We introduce a new paradigm to test the hypothesis that similar memories, but not unrelated memories, are actively separated at encoding. Participants memorized events which were either unique or shared a common element with another event (paired "overlapping" events). We used a measure of dependency, originally devised to measure pattern completion, to quantify how much the probability of successfully retrieving associations from one event depends on successful retrieval of associations from the same event, an unrelated event or the overlapping event. In two experiments, we saw that within event retrievals were highly dependent, indicating pattern completion; retrievals from unrelated events were independent; and retrievals from overlapping events were antidependent (i.e., less than independent), indicating pattern separation. This suggests that representations of similar (overlapping) memories are actively separated, resulting in lowered dependency of retrieval performance between them, as would be predicted by the pattern separation account.

Published
2020
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26. Global metrics for terrestrial biodiversity

Author

Burgess, Neil, primary, Ali, Natasha, additional, Bedford, Jacob, additional, Bhola, Nina, additional, Brooks, Sharon, additional, Cierna, Alena, additional, Correa, Roberto, additional, Harris, Matthew, additional, Hargey, Ayesha, additional, Hughes, Jonathan, additional, McDermott-Long, Osgur, additional, Miles, Lera, additional, Ravilious, Corinna, additional, Rodrigues, Ana, additional, van Soesbergen, Arnout, additional, Shivonen, Heli, additional, Seager, Aimee, additional, Swindell, Luke, additional, Vukelic, Matea, additional, Durán, América, additional, Green, Jonathan, additional, West, Christopher, additional, Weatherdon, Lauren, additional, Hawkins, Frank, additional, Brooks, Thomas, additional, Kingston, Naomi, additional, and Butchart, Stuart, additional

Published
2024
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31. Areas of global importance for conserving terrestrial biodiversity, carbon and water

Author

Jung, Martin, Arnell, Andy, de Lamo, Xavier, García-Rangel, Shaenandhoa, Lewis, Matthew, Mark, Jennifer, Merow, Cory, Miles, Lera, Ondo, Ian, Pironon, Samuel, Ravilious, Corinna, Rivers, Malin, Schepaschenko, Dmitry, Tallowin, Oliver, van Soesbergen, Arnout, Govaerts, Rafaël, Boyle, Bradley L., Enquist, Brian J., Feng, Xiao, Gallagher, Rachael, Maitner, Brian, Meiri, Shai, Mulligan, Mark, Ofer, Gali, Roll, Uri, Hanson, Jeffrey O., Jetz, Walter, Di Marco, Moreno, McGowan, Jennifer, Rinnan, D. Scott, Sachs, Jeffrey D., Lesiv, Myroslava, Adams, Vanessa M., Andrew, Samuel C., Burger, Joseph R., Hannah, Lee, Marquet, Pablo A., McCarthy, James K., Morueta-Holme, Naia, Newman, Erica A., Park, Daniel S., Roehrdanz, Patrick R., Svenning, Jens-Christian, Violle, Cyrille, Wieringa, Jan J., Wynne, Graham, Fritz, Steffen, Strassburg, Bernardo B. N., Obersteiner, Michael, Kapos, Valerie, Burgess, Neil, Schmidt-Traub, Guido, and Visconti, Piero

Published
2021
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33. Scientific foundations for an ecosystem goal, milestones and indicators for the post-2020 global biodiversity framework

Author

Nicholson, Emily, Watermeyer, Kate E., Rowland, Jessica A., Sato, Chloe F., Stevenson, Simone L., Andrade, Angela, Brooks, Thomas M., Burgess, Neil D., Cheng, Su-Ting, Grantham, Hedley S., Hill, Samantha L., Keith, David A., Maron, Martine, Metzke, Daniel, Murray, Nicholas J., Nelson, Cara R., Obura, David, Plumptre, Andy, Skowno, Andrew L., and Watson, James E. M.

Published
2021
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34. High aboveground carbon stock of African tropical montane forests

Author

Cuni-Sanchez, Aida, Sullivan, Martin J. P., Platts, Philip J., Lewis, Simon L., Marchant, Rob, Imani, Gérard, Hubau, Wannes, Abiem, Iveren, Adhikari, Hari, Albrecht, Tomas, Altman, Jan, Amani, Christian, Aneseyee, Abreham B., Avitabile, Valerio, Banin, Lindsay, Batumike, Rodrigue, Bauters, Marijn, Beeckman, Hans, Begne, Serge K., Bennett, Amy C., Bitariho, Robert, Boeckx, Pascal, Bogaert, Jan, Bräuning, Achim, Bulonvu, Franklin, Burgess, Neil D., Calders, Kim, Chapman, Colin, Chapman, Hazel, Comiskey, James, de Haulleville, Thales, Decuyper, Mathieu, DeVries, Ben, Dolezal, Jiri, Droissart, Vincent, Ewango, Corneille, Feyera, Senbeta, Gebrekirstos, Aster, Gereau, Roy, Gilpin, Martin, Hakizimana, Dismas, Hall, Jefferson, Hamilton, Alan, Hardy, Olivier, Hart, Terese, Heiskanen, Janne, Hemp, Andreas, Herold, Martin, Hiltner, Ulrike, Horak, David, Kamdem, Marie-Noel, Kayijamahe, Charles, Kenfack, David, Kinyanjui, Mwangi J., Klein, Julia, Lisingo, Janvier, Lovett, Jon, Lung, Mark, Makana, Jean-Remy, Malhi, Yadvinder, Marshall, Andrew, Martin, Emanuel H., Mitchard, Edward T. A., Morel, Alexandra, Mukendi, John T., Muller, Tom, Nchu, Felix, Nyirambangutse, Brigitte, Okello, Joseph, Peh, Kelvin S.-H., Pellikka, Petri, Phillips, Oliver L., Plumptre, Andrew, Qie, Lan, Rovero, Francesco, Sainge, Moses N., Schmitt, Christine B., Sedlacek, Ondrej, Ngute, Alain S. K., Sheil, Douglas, Sheleme, Demisse, Simegn, Tibebu Y., Simo-Droissart, Murielle, Sonké, Bonaventure, Soromessa, Teshome, Sunderland, Terry, Svoboda, Miroslav, Taedoumg, Hermann, Taplin, James, Taylor, David, Thomas, Sean C., Timberlake, Jonathan, Tuagben, Darlington, Umunay, Peter, Uzabaho, Eustrate, Verbeeck, Hans, Vleminckx, Jason, Wallin, Göran, Wheeler, Charlotte, Willcock, Simon, Woods, John T., and Zibera, Etienne

Published
2021
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35. Spatially Periodic Cells Are Neither Formed From Grids Nor Poor Isolation

Author

Krupic, Julija, Burgess, Neil, and O'Keefe, John

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Grid cells recorded in the parahippocampal formation of freely moving rodents provide a strikingly periodic representation of self-location whose underlying mechanism has been the subject of intense interest. Our previous work(1) showed that grid cells represent the most stable subset of a larger continuum of spatially periodic cells (SPCs) which deviate from the hexagonal symmetry observed in grid cells. Recently Navratilova et al(2) suggested that our findings reflected poor isolation of the spikes from multiple grid cells, rather than the existence of actual non-grid SPCs. Here we refute this suggestion by showing that: (i) most SPCs cannot be formed from hexagonal grids; (ii) all standard cluster isolation measures are similar between recorded grid cells and non-grid SPCs, and are comparable to those reported in other laboratories; (iii) the spikes from different fields of band-like SPCs do not differ. Thus the theoretical implications of the presence of cells with spatially periodic firing patterns that diverge from perfect hexagonality need to be taken seriously, rather than explained away on the basis of hopeful but unjustified assumptions., Comment: 20 pages, 6 figures, 2 tables

Published
2015

37. A metric for spatially explicit contributions to science-based species targets

Author

Mair, Louise, Bennun, Leon A., Brooks, Thomas M., Butchart, Stuart H. M., Bolam, Friederike C., Burgess, Neil D., Ekstrom, Jonathan M. M., Milner-Gulland, E. J., Hoffmann, Michael, Ma, Keping, Macfarlane, Nicholas B. W., Raimondo, Domitilla C., Rodrigues, Ana S. L., Shen, Xiaoli, Strassburg, Bernardo B. N., Beatty, Craig R., Gómez-Creutzberg, Carla, Iribarrem, Alvaro, Irmadhiany, Meizani, Lacerda, Eduardo, Mattos, Bianca C., Parakkasi, Karmila, Tognelli, Marcelo F., Bennett, Elizabeth L., Bryan, Catherine, Carbone, Giulia, Chaudhary, Abhishek, Eiselin, Maxime, da Fonseca, Gustavo A. B., Galt, Russell, Geschke, Arne, Glew, Louise, Goedicke, Romie, Green, Jonathan M. H., Gregory, Richard D., Hill, Samantha L. L., Hole, David G., Hughes, Jonathan, Hutton, Jonathan, Keijzer, Marco P. W., Navarro, Laetitia M., Nic Lughadha, Eimear, Plumptre, Andrew J., Puydarrieux, Philippe, Possingham, Hugh P., Rankovic, Aleksandar, Regan, Eugenie C., Rondinini, Carlo, Schneck, Joshua D., Siikamäki, Juha, Sendashonga, Cyriaque, Seutin, Gilles, Sinclair, Sam, Skowno, Andrew L., Soto-Navarro, Carolina A., Stuart, Simon N., Temple, Helen J., Vallier, Antoine, Verones, Francesca, Viana, Leonardo R., Watson, James, Bezeng, Simeon, Böhm, Monika, Burfield, Ian J., Clausnitzer, Viola, Clubbe, Colin, Cox, Neil A., Freyhof, Jörg, Gerber, Leah R., Hilton-Taylor, Craig, Jenkins, Richard, Joolia, Ackbar, Joppa, Lucas N., Koh, Lian Pin, Lacher, Jr, Thomas E., Langhammer, Penny F., Long, Barney, Mallon, David, Pacifici, Michela, Polidoro, Beth A., Pollock, Caroline M., Rivers, Malin C., Roach, Nicolette S., Rodríguez, Jon Paul, Smart, Jane, Young, Bruce E., Hawkins, Frank, and McGowan, Philip J. K.

Published
2021
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38. Global Metrics for Terrestrial Biodiversity.

Author

Burgess, Neil D., Ali, Natasha, Bedford, Jacob, Bhola, Nina, Brooks, Sharon, Cierna, Alena, Correa, Roberto, Harris, Matthew, Hargey, Ayesha, Hughes, Jonathan, McDermott-Long, Osgur, Miles, Lera, Ravilious, Corinna, Rodrigues, Ana Ramos, van Soesbergen, Arnout, Sihvonen, Heli, Seager, Aimee, Swindell, Luke, Vukelic, Matea, and Durán, América Paz

Subjects
*GENETIC variation, *DATABASES, *CIVIL society, *ECOSYSTEMS, *DECISION making
Abstract

Biodiversity metrics are increasingly in demand for informing government, business, and civil society decisions. However, it is not always clear to end users how these metrics differ or for what purpose they are best suited. We seek to answer these questions using a database of 573 biodiversity-related metrics, indicators, indices, and layers, which address aspects of genetic diversity, species, and ecosystems. We provide examples of indicators and their uses within the state–pressure–response–benefits framework that is widely used in conservation science. Considering complementarity across this framework, we recommend a small number of metrics considered most pertinent for use in decision-making by governments and businesses. We conclude by highlighting five future directions: increasing the importance of national metrics, ensuring wider uptake of business metrics, agreeing on a minimum set of metrics for government and business use, automating metric calculation through use of technology, and generating sustainable funding for metric production. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Increased memory confidence and delusions in Alzheimer's disease: a preliminary study.

Author

McLachlan, Emma, Liu, Kathy, Huzzey, Lauren, Burgess, Neil, Reeves, Suzanne, and Howard, Robert

Subjects
RECOGNITION (Psychology), ALZHEIMER'S disease, METACOGNITION, PEOPLE with schizophrenia, WORD recognition, DELUSIONS, FALSE memory syndrome
Abstract

There is uncertainty about whether delusion formation in Alzheimer's disease (AD) can be explained by false memories. "Metamemory," the ability to self-evaluate memory and identify memory errors, is impaired in people with delusions in schizophrenia. Our objective was to investigate whether false memory and metamemory were associated with delusions in AD. Participants with mild AD, with and without delusions, completed a computerized word recognition task and a metamemory measure. Group differences were compared using independent-samples t-tests or Mann Whitney tests. Significant findings were explored through binary logistic regression modeling. Participants with delusions (n = 10) gave more high confidence responses, significantly so for correct responses; percentage of high confidence correct responses for those with delusions (mean (SD)) was 69.7% (31.0%) and for those without (n = 14) was 43.5% (29.9%); t22 = -2.09, p =.049. This remained significant when sex was included in regression modeling; for each 1.0% increase in high confidence correct responses, participants were 5.4% more likely to have delusions (Exp(β) 1.054, 95% CI 1.007–1.105, p =.025). Findings provide tentative support for a link between metamemory and delusions in AD. This should be explored in a larger sample as it has potential implications for treatment. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Nature Forest Reserves in Tanzania and their importance for conservation

Author

Ract, Claire, primary, Burgess, Neil D., additional, Dinesen, Lars, additional, Sumbi, Peter, additional, Malugu, Isaac, additional, Latham, Julia, additional, Anderson, Lucy, additional, Gereau, Roy E., additional, Gonçalves de Lima, Marcelo, additional, Akida, Amina, additional, Nashanda, Evarist, additional, Shabani, Zainabu, additional, Tango, Yusuph, additional, Mteleka, Someni, additional, Santos Silayo, Dos, additional, Mwangi, Juma, additional, Lyatuu, Gertrude, additional, Platts, Philip J., additional, and Rovero, Francesco, additional

Published
2024
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45. Inter-colony variation in predation, mercury burden and adult survival in a declining seabird

Author

Calvert, Anna M., primary, Gutowsky, Sarah E., additional, Fifield, David A., additional, Burgess, Neil M., additional, Bryant, Rachel, additional, Fraser, Gail S., additional, Gjerdrum, Carina, additional, Hedd, April, additional, Jones, Patricia L., additional, Mauck, Robert A., additional, McFarlane Tranquilla, Laura, additional, Montevecchi, William A., additional, Pollet, Ingrid L., additional, Ronconi, Robert A., additional, Rock, Jennifer C., additional, Russell, Janet, additional, Wilhelm, Sabina I., additional, Wong, Sarah N.P., additional, and Robertson, Gregory J., additional

Published
2024
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