Humans stand out among animals for their unique capacities in domains such as language, culture and imitation, yet it has been difficult to identify cognitive elements that are specifically human. Most research has focused on how information is processed after it is acquired, e.g. in problem solving or 'insight' tasks, but we may also look for species differences in the initial acquisition and coding of information. Here, we show that non-human species have only a limited capacity to discriminate ordered sequences of stimuli. Collating data from 108 experiments on stimulus sequence discrimination (1540 data points from 14 bird and mammal species), we demonstrate pervasive and systematic errors, such as confusing a red-green sequence of lights with green-red and green-green sequences. These errors can persist after thousands of learning trials in tasks that humans learn to near perfection within tens of trials. To elucidate the causes of such poor performance, we formulate and test a mathematical model of non-human sequence discrimination, assuming that animals represent sequences as unstructured collections of memory traces. This representation carries only approximate information about stimulus duration, recency, order and frequency, yet our model predicts non-human performance with a 5.9% mean absolute error across 68 datasets. Because human-level cognition requires more accurate encoding of sequential information than afforded by memory traces, we conclude that improved coding of sequential information is a key cognitive element that may set humans apart from other animals.
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http://dx.doi.org/10.1098/rsos.161011 | DOI Listing |
BJS Open
December 2024
Institute of Cardiovascular Sciences, University College London, London, UK.
Background: While most thyroid nodules are benign, 7-15% are malignant. Patients with indeterminate thyroid nodules (specifically Bethesda IV/Thy3f) often undergo diagnostic hemithyroidectomy to reach a diagnosis on final histology. The aim of this study was to assess the feasibility of circulating large extracellular vesicles as diagnostic biomarkers in patients presenting with Thy3f thyroid nodules.
View Article and Find Full Text PDFBackground: Magnetization transfer (MT) MRI is sensitive to the presence of macromolecules, including amyloid-beta, and previous work suggests that it may be useful for discriminating patients with Alzheimer's disease (AD) from healthy controls. In this study, we investigated if quantitative MT (qMT) is capable of detecting the amyloid concentration in a preclinical cohort.
Method: We recruited 14 subjects with a clinical dementia rating of 0 from NYU's ADRC cohort (7 male, mean age 74, 6 amyloid-negative).
Background: Two main risk factors of Alzheimer's disease (AD) are aging and APOE-ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered "cognitively resilient".
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.
Background: Hippocampal atrophy is an established biomarker of neurodegeneration in Alzheimer's disease, affecting specific subfields (De Flores, La Joie and Chételat, 2015). In this study, we used 7T MRI and advanced diffusion MRI (dMRI) to investigate the relationship between hippocampal subfield volumes and microstructure and assess their sensitivity to cognitive impairment.
Method: Seventeen cognitively impaired (CI; age: 69±8, M/F: 12/5, MMSE: 28) and 22 cognitively unimpaired subjects (CU; age: 62±10, M/F: 6/16) were recruited in the context of the COSCODE project (Ribaldi et al.
Alzheimers Dement
December 2024
NYU Grossman School of Medicine, New York, NY, USA.
Background: Magnetization transfer (MT) MRI is sensitive to the presence of macromolecules, including amyloid-beta, and previous work suggests that it may be useful for discriminating patients with Alzheimer's disease (AD) from healthy controls. In this study, we investigated if quantitative MT (qMT) is capable of detecting the amyloid concentration in a preclinical cohort.
Method: We recruited 14 subjects with a clinical dementia rating of 0 from NYU's ADRC cohort (7 male, mean age 74, 6 amyloid-negative).
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