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Impact of canine epilepsy on judgement and attention biases.

ABSTRACT: Idiopathic epilepsy (IE) is the most common chronic neurological condition in dogs, characterised by recurrent seizure activity and associated with negative behavioural and cognitive changes. We hypothesised that IE would negatively impact putative affective state, with dogs with IE exhibiting a more pessimistic judgement bias and more negative attention bias than controls. Dogs were tested in a previously-validated spatial judgement bias task, and a novel auditory attention bias task testing attention to sounds with different valence or salience (neutral, novel pre-habituated, threatening). Sixty-eight dogs (IE?=?33, Control?=?35) were tested, of which n?=?37 acquired the spatial discrimination and responses to judgement bias probes were tested (IE?=?19, Control?=?18), and n?=?36 were tested for responses to sounds (IE?=?20, Control?=?16). Study groups did not significantly differ by age, sex, breed or neuter-status (p?>?0.05). Main effects of study group were not significant in judgement bias (F1,102?=?0.20, p?=?0.658) or attention bias tasks (F3,102?=?1.64, p?=?0.184). In contrast with our hypotheses, there was no evidence that IE altered cognitive biases in this study population; however, dogs with IE were significantly more likely to be unable to learn the spatial discrimination task (p?=?0.019), which may reflect IE-related cognitive deficits. Developing methods to test affective state without excluding cognitively impaired individuals is a future challenge for animal welfare science.

SUBMITTER: Hobbs SL

PROVIDER: S-EPMC7576193 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Impact of canine epilepsy on judgement and attention biases.

Hobbs Sarah L SL Law Tsz Hong TH Volk Holger A HA Younis Chantal C Casey Rachel A RA Packer Rowena M A RMA

Scientific reports 20201020 1

Idiopathic epilepsy (IE) is the most common chronic neurological condition in dogs, characterised by recurrent seizure activity and associated with negative behavioural and cognitive changes. We hypothesised that IE would negatively impact putative affective state, with dogs with IE exhibiting a more pessimistic judgement bias and more negative attention bias than controls. Dogs were tested in a previously-validated spatial judgement bias task, and a novel auditory attention bias task testing at ...[more]

PMID: 33082493

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Project description:BackgroundClinical decisions are made based on Cochrane reviews, but the implementation of results of evidence syntheses such as Cochrane reviews is problematic if the evidence is not prepared consistently. All systematic reviews should assess the risk of bias (RoB) in included studies, and in Cochrane reviews, this is done by using Cochrane RoB tool. However, the tool is not necessarily applied according to the instructions. In this study, we aimed to determine the types of bias and their corresponding judgements noted in the 'other bias' domain of Cochrane RoB tool.MethodsWe analyzed Cochrane reviews that included randomized controlled trials (RCTs) and extracted data regarding 'other bias' from the RoB table and accompanying support for the judgment. We categorized different types of other bias.ResultsWe analyzed 768 Cochrane reviews that included 11,369 RCTs. There were 602 (78%) Cochrane reviews that had 'other bias' domain in the RoB tool, and they included a total of 7811 RCTs. In the RoB table of 337 Cochrane reviews for at least one of the included trials it was indicated that no other bias was found and supporting explanations were inconsistently judged as low, unclear or high RoB. In the 524 Cochrane reviews that described various sources of other bias, there were 5762 individual types of explanations which we categorized into 31 groups. The judgments of the same supporting explanations were highly inconsistent. We found numerous other inconsistencies in reporting of sources of other bias in Cochrane reviews.ConclusionCochrane authors mention a wide range of sources of other bias in the RoB tool and they inconsistently judge the same supporting explanations. Inconsistency in appraising risk of other bias hinders reliability and comparability of Cochrane systematic reviews. Discrepant and erroneous judgments of bias in evidence synthesis may hinder implementation of evidence in routine clinical practice and reduce confidence in otherwise trustworthy sources of information. These results can help authors of Cochrane and non-Cochrane reviews to gain insight into various sources of other bias that can be found in trials, and also to help them avoid mistakes that were recognized in published Cochrane reviews.

Project description:SEE MORMANN AND ANDRZEJAK DOI101093/BRAIN/AWW091 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE : Accurate forecasting of epileptic seizures has the potential to transform clinical epilepsy care. However, progress toward reliable seizure forecasting has been hampered by lack of open access to long duration recordings with an adequate number of seizures for investigators to rigorously compare algorithms and results. A seizure forecasting competition was conducted on kaggle.com using open access chronic ambulatory intracranial electroencephalography from five canines with naturally occurring epilepsy and two humans undergoing prolonged wide bandwidth intracranial electroencephalographic monitoring. Data were provided to participants as 10-min interictal and preictal clips, with approximately half of the 60 GB data bundle labelled (interictal/preictal) for algorithm training and half unlabelled for evaluation. The contestants developed custom algorithms and uploaded their classifications (interictal/preictal) for the unknown testing data, and a randomly selected 40% of data segments were scored and results broadcasted on a public leader board. The contest ran from August to November 2014, and 654 participants submitted 17 856 classifications of the unlabelled test data. The top performing entry scored 0.84 area under the classification curve. Following the contest, additional held-out unlabelled data clips were provided to the top 10 participants and they submitted classifications for the new unseen data. The resulting area under the classification curves were well above chance forecasting, but did show a mean 6.54 ± 2.45% (min, max: 0.30, 20.2) decline in performance. The kaggle.com model using open access data and algorithms generated reproducible research that advanced seizure forecasting. The overall performance from multiple contestants on unseen data was better than a random predictor, and demonstrates the feasibility of seizure forecasting in canine and human epilepsy.media-1vid110.1093/brain/aww045_video_abstractaww045_video_abstract.

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Impact of canine epilepsy on judgement and attention biases.

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Impact of canine epilepsy on judgement and attention biases.

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