Re-record VCR tapes using newer versions of libraries

dandi/cli/tests/data/update_dandiset_from_doi/jneurosci.vcr.yaml

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+        for Neuroscience","issue":"31","license":[{"start":{"date-parts":[[2010,2,5]],"date-time":"2010-02-05T00:00:00Z","timestamp":1265328000000},"content-version":"vor","delay-in-days":184,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"published-print":{"date-parts":[[2009,8,5]]},"abstract":"<jats:p>Reinforcement
+        learning theory plays a key role in understanding the behavioral and neural
+        mechanisms of choice behavior in animals and humans. Especially, intermediate
+        variables of learning models estimated from behavioral data, such as the expectation
+        of reward for each candidate choice (action value), have been used in searches
+        for the neural correlates of computational elements in learning and decision
+        making. The aims of the present study are as follows: (1) to test which computational
+        model best captures the choice learning process in animals and (2) to elucidate
+        how action values are represented in different parts of the corticobasal ganglia
+        circuit. We compared different behavioral learning algorithms to predict the
+        choice sequences generated by rats during a free-choice task and analyzed
+        associated neural activity in the nucleus accumbens (NAc) and ventral pallidum
+        (VP). The major findings of this study were as follows: (1) modified versions
+        of an action\u2013value learning model captured a variety of choice strategies
+        of rats, including win-stay\u2013lose-switch and persevering behavior, and
+        predicted rats'' choice sequences better than the best multistep Markov model;
+        and (2) information about action values and future actions was coded in both
+        the NAc and VP, but was less dominant than information about trial types,
+        selected actions, and reward outcome. The results of our model-based analysis
+        suggest that the primary role of the NAc and VP is to monitor information
+        important for updating choice behaviors. Information represented in the NAc
+        and VP might contribute to a choice mechanism that is situated elsewhere.<\/jats:p>","DOI":"10.1523\/jneurosci.6157-08.2009","type":"journal-article","created":{"date-parts":[[2009,8,5]],"date-time":"2009-08-05T17:33:40Z","timestamp":1249493620000},"page":"9861-9874","source":"Crossref","is-referenced-by-count":190,"title":"Validation
+        of Decision-Making Models and Analysis of Decision Variables in the Rat Basal
+        Ganglia","prefix":"10.1523","volume":"29","author":[{"given":"Makoto","family":"Ito","sequence":"first","affiliation":[]},{"given":"Kenji","family":"Doya","sequence":"additional","affiliation":[]}],"member":"393","published-online":{"date-parts":[[2009,8,5]]},"reference":[{"key":"2023041303393959000_29.31.9861.1","doi-asserted-by":"publisher","DOI":"10.1038\/nn1209"},{"key":"2023041303393959000_29.31.9861.2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2006.03.004"},{"key":"2023041303393959000_29.31.9861.3","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2202-6-9"},{"key":"2023041303393959000_29.31.9861.4","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2202-6-37"},{"key":"2023041303393959000_29.31.9861.5","doi-asserted-by":"publisher","DOI":"10.1007\/s00221-001-0918-3"},{"key":"2023041303393959000_29.31.9861.6","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1590-07.2007"},{"key":"2023041303393959000_29.31.9861.7","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2006.03.006"},{"key":"2023041303393959000_29.31.9861.8","doi-asserted-by":"publisher","DOI":"10.1038\/nature04766"},{"key":"2023041303393959000_29.31.9861.9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2004.09.009"},{"key":"2023041303393959000_29.31.9861.10","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(99)00046-5"},{"key":"2023041303393959000_29.31.9861.11","doi-asserted-by":"publisher","DOI":"10.1016\/S0959-4388(00)00153-7"},{"key":"2023041303393959000_29.31.9861.12","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1010-06.2006"},{"key":"2023041303393959000_29.31.9861.13","doi-asserted-by":"crossref","unstructured":"Houk
+        JC Adams JL Barto AG (1995) in Models of information processing in the basal
+        ganglia, A model of how the basal ganglia generate and use neural signals
+        that predict reinforcement, eds Houk JC Davis JL Beiser DG (MIT, Cambridge,
+        MA).","DOI":"10.7551\/mitpress\/4708.001.0001"},{"key":"2023041303393959000_29.31.9861.14","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00310.2007"},{"key":"2023041303393959000_29.31.9861.15","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.3060-07.2007"},{"key":"2023041303393959000_29.31.9861.16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2008.02.021"},{"key":"2023041303393959000_29.31.9861.17","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.1523\/JNEUROSCI.16-05-01936.1996","article-title":"A
+        framework for mesencephalic dopamine systems based on predictive Hebbian learning","volume":"16","author":"Montague","year":"1996","journal-title":"J
+        Neurosci"},{"key":"2023041303393959000_29.31.9861.18","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00657.2003"},{"key":"2023041303393959000_29.31.9861.19","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00658.2003"},{"key":"2023041303393959000_29.31.9861.20","doi-asserted-by":"publisher","DOI":"10.1126\/science.1094285"},{"key":"2023041303393959000_29.31.9861.21","doi-asserted-by":"publisher","DOI":"10.1016\/S0896-6273(03)00169-7"},{"key":"2023041303393959000_29.31.9861.22","doi-asserted-by":"publisher","DOI":"10.1196\/annals.1390.022"},{"key":"2023041303393959000_29.31.9861.23","doi-asserted-by":"publisher","DOI":"10.1088\/0954-898X\/7\/1\/006"},{"key":"2023041303393959000_29.31.9861.24","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.3745-06.2007"},{"key":"2023041303393959000_29.31.9861.25","unstructured":"Paxinos
+        G Watson C (1998) The rat brain in stereotaxic coordinates (Academic, San
+        Diego), Ed 4.."},{"key":"2023041303393959000_29.31.9861.26","doi-asserted-by":"publisher","DOI":"10.1038\/22268"},{"key":"2023041303393959000_29.31.9861.27","unstructured":"Samejima
+        K Doya K Ueda Y Kimura M (2004) in Advances in neural information processing
+        systems, Estimating internal variables and parameters of a learning agent
+        by a particle filter, eds Thrun S Saul LK Sholkopf B (MIT, Cambridge, MA)."},{"key":"2023041303393959000_29.31.9861.28","doi-asserted-by":"publisher","DOI":"10.1126\/science.1115270"},{"key":"2023041303393959000_29.31.9861.29","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1523\/JNEUROSCI.19-05-01876.1999","article-title":"Neural
+        encoding in orbitofrontal cortex and basolateral amygdala during olfactory
+        discrimination learning","volume":"19","author":"Schoenbaum","year":"1999","journal-title":"J
+        Neurosci"},{"key":"2023041303393959000_29.31.9861.30","doi-asserted-by":"publisher","DOI":"10.1126\/science.275.5306.1593"},{"key":"2023041303393959000_29.31.9861.31","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.2369-07.2007"},{"key":"2023041303393959000_29.31.9861.32","doi-asserted-by":"publisher","DOI":"10.1016\/S0896-6273(03)00264-2"},{"key":"2023041303393959000_29.31.9861.33","doi-asserted-by":"publisher","DOI":"10.1126\/science.1094765"},{"key":"2023041303393959000_29.31.9861.34","doi-asserted-by":"crossref","unstructured":"Sutton
+        RS Barto AG (1998) Reinforcement learning (MIT, Cambridge, MA).","DOI":"10.1016\/S1474-6670(17)38315-5"},{"key":"2023041303393959000_29.31.9861.35","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.2007.140236"},{"key":"2023041303393959000_29.31.9861.36","doi-asserted-by":"publisher","DOI":"10.1038\/nn1279"},{"key":"2023041303393959000_29.31.9861.37","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1437-03.2004"},{"key":"2023041303393959000_29.31.9861.38","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00068.2006"},{"key":"2023041303393959000_29.31.9861.39","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF00992698","article-title":"Q-learning","volume":"8","author":"Watkins","year":"1992","journal-title":"Mach
+        Learn"},{"key":"2023041303393959000_29.31.9861.40","doi-asserted-by":"publisher","DOI":"10.1111\/j.1460-9568.2004.03747.x"},{"key":"2023041303393959000_29.31.9861.41","doi-asserted-by":"publisher","DOI":"10.1152\/jn.01332.2004"},{"key":"2023041303393959000_29.31.9861.42","doi-asserted-by":"publisher","DOI":"10.1111\/j.1460-9568.2005.04218.x"}],"container-title":"The
+        Journal of Neuroscience","original-title":[],"language":"en","link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1523\/JNEUROSCI.6157-08.2009","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T19:29:13Z","timestamp":1681414153000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jneurosci.org\/lookup\/doi\/10.1523\/JNEUROSCI.6157-08.2009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,8,5]]},"references-count":42,"journal-issue":{"issue":"31","published-online":{"date-parts":[[2009,8,5]]},"published-print":{"date-parts":[[2009,8,5]]}},"alternative-id":["10.1523\/JNEUROSCI.6157-08.2009"],"URL":"http:\/\/dx.doi.org\/10.1523\/JNEUROSCI.6157-08.2009","relation":{},"ISSN":["0270-6474","1529-2401"],"subject":["General
+        Neuroscience"],"container-title-short":"J. Neurosci.","published":{"date-parts":[[2009,8,5]]}}'
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