4.7 Editorial Material

Recovery after stroke: not so proportional after all?

Journal

BRAIN
Volume 142, Issue -, Pages 15-22

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/brain/awy302

Keywords

proportional recovery; stroke; methods; statistics; outcomes

Funding

  1. Medical Research Council [MR/M023672/1]
  2. Wellcome [091593/Z/10/Z, 205103/Z/16/Z]
  3. Stroke Association [TSA PDF 2017/02, TSA 2014/02]
  4. MRC [MR/M023672/1] Funding Source: UKRI

Ask authors/readers for more resources

The proportional recovery rule asserts that most stroke survivors recover a fixed proportion of lost function. Reports that the rule accurately predicts empirical recovery are rapidly accumulating. However, Hope et al. show that there is a fallacy at the heart of the rule that confounds many of these results.The proportional recovery rule asserts that most stroke survivors recover a fixed proportion of lost function. To the extent that this is true, recovery from stroke can be predicted accurately from baseline measures of acute post-stroke impairment alone. Reports that baseline scores explain more than 80%, and sometimes more than 90%, of the variance in the patients recoveries, are rapidly accumulating. Here, we show that these headline effect sizes are likely inflated. The key effects in this literature are typically expressed as, or reducible to, correlation coefficients between baseline scores and recovery (outcome scores minus baseline scores). Using formal analyses and simulations, we show that these correlations will be extreme when outcomes are significantly less variable than baselines, which they often will be in practice regardless of the real relationship between outcomes and baselines. We show that these effect sizes are likely to be over-optimistic in every empirical study that we found that reported enough information for us to make the judgement, and argue that the same is likely to be true in other studies as well. The implication is that recovery after stroke may not be as proportional as recent studies suggest.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Psychology, Developmental

Machine learning classification of conduct disorder with high versus low levels of callous-unemotional traits based on facial emotion recognition abilities

Ruth Pauli, Gregor Kohls, Peter Tino, Jack C. Rogers, Sarah Baumann, Katharina Ackermann, Anka Bernhard, Anne Martinelli, Lucres Jansen, Helena Oldenhof, Karen Gonzalez-Madruga, Areti Smaragdi, Miguel Angel Gonzalez-Torres, Inaki Kerexeta-Lizeaga, Cyril Boonmann, Linda Kersten, Aitana Bigorra, Amaia Hervas, Christina Stadler, Aranzazu Fernandez-Rivas, Arne Popma, Kerstin Konrad, Beate Herpertz-Dahlmann, Graeme Fairchild, Christine M. Freitag, Pia Rotshtein, Stephane A. De Brito

Summary: Theoretical links between conduct disorder (CD) with high levels of callous-unemotional traits (CD/HCU) and difficulties with fear and sadness recognition have been mixed, and it is unclear if these difficulties reliably distinguish CD/HCU from CD with low levels of callous-unemotional traits (CD/LCU). This study used univariate analyses and machine learning classifiers to investigate emotion recognition abilities in a large sample. The results suggest that non-specific emotion recognition difficulties are common in CD/HCU, but are not reliable markers of CD/HCU at the individual level.

EUROPEAN CHILD & ADOLESCENT PSYCHIATRY (2023)

Article Neurosciences

Enhanced left superior parietal activation during successful speech production in patients with left dorsal striatal damage and error-prone neurotypical participants

Sharon Geva, Letitia M. Schneider, Shamima Khan, Diego L. Lorca-Puls, Andrea Gajardo-Vidal, Thomas M. H. Hope, David W. Green, Cathy J. Price

Summary: This study investigated the performance of stroke survivors in speech production and found that patients with left dorsal striatal damage showed higher activation during successful speech production. The results also suggest that enhanced activation in the left superior parietal cortex supports speech production in diverse challenging circumstances.

CEREBRAL CORTEX (2023)

Review Biochemistry & Molecular Biology

Computational psychiatry: from synapses to sentience

Karl Friston

Summary: This review explores computational psychiatry from the perspective of pathophysiology, using generative models to explain psychopathology. It discusses the brain from cognitive and computational neuroscience viewpoints, providing a formal description of neuronal message passing, distributed processing, and belief propagation in neuronal networks. It also examines how dysconnections in the brain can lead to abnormal belief updating and false inference, and explores the use of computational models in various psychiatric research areas, including computational neuropsychology, computational phenotyping, and computational nosology.

MOLECULAR PSYCHIATRY (2023)

Article Clinical Neurology

Neurophysiological consequences of synapse loss in progressive supranuclear palsy

Natalie E. Adams, Amirhossein Jafarian, Alistair Perry, Matthew A. Rouse, Alexander D. Shaw, Alexander G. Murley, Thomas E. Cope, W. Richard Bevan-Jones, Luca Passamonti, Duncan Street, Negin Holland, David Nesbitt, Laura E. Hughes, Karl J. Friston, James B. Rowe

Summary: Adams et al. use PET measures of synaptic density to enhance biophysical models of cortical dynamics and demonstrate the link between synaptic loss, neurophysiology, and cognitive deficits. Their inclusion of regional synaptic density in a mesoscale model of human cortical function significantly increases model evidence and predicts individual differences in behavior. This method can be applied to assess the mechanisms of other neurological disorders and test the effects of experimental pharmacology.

BRAIN (2023)

Article Computer Science, Artificial Intelligence

Small steps for mankind: Modeling the emergence of cumulative culture from joint active inference communication

Natalie Kastel, Casper Hesp, K. Richard Ridderinkhof, Karl J. Friston

Summary: This paper proposes a testable deep active inference formulation of social behavior and conducts simulations of cumulative culture. By considering cultural transmission as a bi-directional process of communication and social exchange as a process of active inference, the study discovers that cumulative culture emerges from belief updating through a joint minimization of uncertainty.

FRONTIERS IN NEUROROBOTICS (2023)

Article Public, Environmental & Occupational Health

Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK

Cam Bowie, Karl Friston

Summary: This study analyzed the COVID-19 epidemic in the past 12 months and made predictions for the next year based on this analysis. It found that changes in transmissibility and public behavior led to an underestimation of the severity of the epidemic in previous predictions. The projections indicate that the number of infections in the coming year will be three times larger than last year, leading to more deaths and economic consequences.

FRONTIERS IN PUBLIC HEALTH (2023)

Article Physics, Multidisciplinary

A Variational Synthesis of Evolutionary and Developmental Dynamics

Karl Friston, Daniel A. Friedman, Axel Constant, V. Bleu Knight, Chris Fields, Thomas Parr, John O. Campbell

Summary: This paper presents a variational formulation of natural selection, focusing on the nature of 'things' and how different 'kinds' of 'things' are individuated from each other and influence each other. Bayesian mechanics is used to understand the relationship between slow phylogenetic processes and fast phenotypic processes. The main result is the formulation of adaptive fitness as a phenotypic fitness path integral. Paths of least action at both phenotypic and phylogenetic scales can be seen as inference and learning processes respectively.

ENTROPY (2023)

Letter Clinical Neurology

Testing the disconnectome symptom discoverer model on out-of-sample post-stroke language outcomes

Thomas M. H. Hope, Douglas Neville, Lia Talozzi, Chris Foulon, Stephanie J. Forkel, Michel Thiebaut de Schotten, Cathy J. Price

BRAIN (2023)

Review Clinical Neurology

Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception

Achim Schilling, William Sedley, Richard Gerum, Claus Metzner, Konstantin Tziridis, Andreas Maier, Holger Schulze, Fan-Gang Zeng, Karl J. Friston, Patrick Krauss

Summary: This article reviews recent work at the intersection of artificial intelligence, psychology, and neuroscience, using tinnitus as an example of auditory phantom perception. The authors discuss the reasons behind the emergence of auditory phantom perceptions and their crucial role in healthy auditory perception. They propose that neural noise along the auditory pathway is generated as a compensatory mechanism and can be misinterpreted as auditory input, leading to tinnitus. The principles of predictive coding and adaptive stochastic resonance are identified as the most explanatory factors for phantom perceptions and may also improve machine learning techniques.

BRAIN (2023)

Letter Clinical Neurology

Principal component analysis-based latent-space dimensionality under-estimation, with uncorrelated latent variables

Thomas M. H. Hope, Ajay Halai, Jenny Crinion, Paola Castelli, Cathy J. Price, Howard Bowman

BRAIN (2023)

Article Psychology, Experimental

Relative fluency (unfelt vs felt) in active inference

Denis Brouillet, Karl Friston

Summary: The brain is known to be a predictive organ that predicts sensory content and the accuracy of its predictions. It must infer the reliability of its own beliefs in order to predict the precision of its predictions. This recognition process leads to the concept of "fluency", which is the perception of having a precise understanding of sensory processes. Changes in fluency, from unfelt to felt, are recognized and realized when updating predictions about accuracy.

CONSCIOUSNESS AND COGNITION (2023)

Article Audiology & Speech-Language Pathology

More than one way to improve a CAT: Outcomes and reflections on two iterations of the Queen Square Intensive Comprehensive Aphasia Programme

Alexander Leff, Catherine Doogan, John Bentley, Bani Makkar, Luisa Zenobi-Bird, Amy Sherman, Simon Grobler, Jennifer Crinion

Summary: The field of human expert performance teaches us that high quality, high-dose guided practice is required to make large gains in cognitively driven acts. The same seems to be true for people with acquired brain injury. Intensive Comprehensive Aphasia Programmes (ICAPs) are one way to address the chronic under-dosing of therapy that most people with aphasia experience.

APHASIOLOGY (2023)

Review Biology

Path integrals, particular kinds, and strange things

Karl Friston, Lancelot Da Costa, Dalton A. R. Sakthivadivel, Conor Heins, Grigorios A. Pavliotis, Maxwell Ramstead, Thomas Parr

Summary: This paper introduces a path integral formulation of the free energy principle to describe the trajectories of particles over time. By employing the principle of least action, it is possible to simulate the behavior of particles in exchange with their external environment. The paper discusses various types of particles and their different levels of inference or sentience.

PHYSICS OF LIFE REVIEWS (2023)

Meeting Abstract Clinical Neurology

Effect of the Queen Square Intensive Comprehensive Aphasia Programme on Carer-Assessed Mood in People with post-stroke Aphasia

L. Taylor, J. Bentley, A. Sherman, B. Makkar, L. Zenobi-Bird, C. Doogan, J. Crinion, A. Leff

INTERNATIONAL JOURNAL OF STROKE (2023)

Meeting Abstract Mathematical & Computational Biology

Is catastrophic forgetting Bayes-optimal?

Noor Sajid, Laura Convertino, Victorita Neacsu, Thomas Parr, Karl Friston

JOURNAL OF COMPUTATIONAL NEUROSCIENCE (2023)

No Data Available