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Investigating the mechanisms that underpin human learning, perception and cognition, headed by Chris Summerfield

Oxford University
humaninformationprocessing.com
Vrijeme pridruživanja: siječanj 2013.

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    1. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      Our #openaccess paper with @vickielcl just got published in @PNAS. We ask in this paper: Can the effects of #distraction (‘irrelevant information’) across different types of decisions (perceptual, cognitive, value-based) be explained by one unified theory? [1/n]pic.twitter.com/zBJIPF7O0y

      62 proslijeđena tweeta 130 korisnika označava da im se sviđa
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    2. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      * @vickieCL_Li

      1 reply 0 proslijeđenih tweetova 3 korisnika označavaju da im se sviđa
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    3. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      The #tilt-illusion is 1 e.g. of the influence of irrelevant info. The image shows a central stimulus (‘Gabor’) surrounded by 8 (task-irrelevant) Gabors. Can you see that the central stimulus appears tilted away from horizontal? Yet in reality, it’s completely flat. [2/n]pic.twitter.com/gkvlCl3WXH

      1 reply 0 proslijeđenih tweetova 4 korisnika označavaju da im se sviđa
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    4. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      Researchers have shown that the extent and direction of this erroneously-perceived tilt is determined by the surrounding, irrelevant Gabors. (Both figures reprinted from Solomon & Morgan, 2006). [3/n]pic.twitter.com/5D76CJ0SIQ

      1 reply 0 proslijeđenih tweetova 2 korisnika označavaju da im se sviđa
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    5. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      In a different setting, your performance is slowed when the irrelevant information is associated with a competing response from the relevant information (RI vs CO condition; the ’conflict effect’). Figure reprinted from van Veen et al. (2001) [4/n]pic.twitter.com/uyms2Fdl40

      1 reply 0 proslijeđenih tweetova 3 korisnika označavaju da im se sviđa
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    6. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      In value-based choices, your preference can be influenced by a 3rd, inferior (i.e. irrelevant) option. This figure is reprinted from Louie et al. (2012). The y axis shows choice efficiency, illustrating a non-monotonic effect on choice according to the distractor value [5/n]pic.twitter.com/jGqeGXR4eN

      1 reply 0 proslijeđenih tweetova 4 korisnika označavaju da im se sviđa
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    7. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      Our new paper proposes that the effect of distraction can be explained by a previously described framework –the adaptive gain model, where neural resources are dynamically allocated to features consistent with the local context.(c.f. Cheadle et al, Summerfield & @Tsetsos [6/n]pic.twitter.com/2DMoleYWeo

      0 proslijeđenih tweetova 3 korisnika označavaju da im se sviđa
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    8. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      We describe a version of the adaptive gain model where the irrelevant information provides contextual signals that sharpen the tuning curves of decision neurons that have a consistent preference for decision-relevant features. [7/n]pic.twitter.com/WlUQdTL9dl

      1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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    9. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      (illustration 2):pic.twitter.com/NzEzRQGf55

      1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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    10. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      We extended our simulations to the #multiattribute #multialternative case where options are characterised with more than one dimension (e.g. price and quality). [9/n]pic.twitter.com/Xgk9jvKQ7K

      1 reply 3 proslijeđena tweeta 4 korisnika označavaju da im se sviđa
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      summerfieldlab‏ @summerfieldlab 4. ruj 2018.
      • Prijavi Tweet

      There are 3 types of decoy effects – compromise, attraction and similarity – which are determined by the attribute values of the decoys themselves (green dots). Our model accounts for all 3 effects. [10/n]pic.twitter.com/LW514FoyI3

      04:25 - 4. ruj 2018.
      • 1 oznaka „sviđa mi se”
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      1 reply 0 proslijeđenih tweetova 1 korisnik označava da mu se sviđa
        1. Novi razgovor
        2. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          It turns out participants do not always exhibit all three decoy effects and have stereotypical intercorrelation pattern on the decoy effects. Our model is able to replicate the effect. Panel A-D reprinted from Berkowitsch et al. (2014) [11/n]pic.twitter.com/8uqdcveLwH

          1 reply 0 proslijeđenih tweetova 1 korisnik označava da mu se sviđa
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        3. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          When participants are given less time to deliberate, they tend to make more “suboptimal” decisions – i.e. more influenced by the decoy. Our model is also able to account for this effect. 1st&3rd column reprinted from Pettibone (2012) and Trueblood et al. (2014) [12/n]pic.twitter.com/aL57cwCUHV

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        4. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          One key feature of our model is that the degree of neural sharpening depends on info variability. Therefore, we devised a flanker task (pps respond to target tilt, ignoring the irrelevant flankers) where the surrounding flankers can be non-identical. [13/n]pic.twitter.com/GGHwJD0kBR

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        5. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          In this task, we sampled the flanker tilts from a normal distribution with different dispersions. [14/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        6. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          Our model correctly predicts that the conflict effect disappears when the flankers are variable (Blue & Green lines). This effect is driven by congruent trials (‘cong’; when target and flankers agree). [15/n]pic.twitter.com/bXWT7ImaNE

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        7. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          In other words, having consistent, congruent flankers brings a relative benefit on performance (red lines). [16/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        8. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          We moved to a more complex design in which the strength of the decision-relevant information (target orientations) and the strength of the decision irrelevant information (flanker mean orientations) vary independently. [17/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        9. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          Our model counterintuitively predicts that under certain circumstances, there is a reversal of the conflict effect – that is, you are slower on congruent rather than incongruent trials (top-left corner).[18/n]pic.twitter.com/UEtIECZZM9

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        10. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          Previous work showed that the #dACC is involved in many things, such as conflict monitoring, signalling the proximity of the decision value from the category boundary, the relative value of the unchosen to the chosen option, the value of switching into a new context. [19/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        11. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          Therefore, we ask what is the role of dACC and interconnected regions in adaptive gain control. We conducted an #fMRI study using the more complex flanker task (where target and distractor strength and variance changed between each trial) [20/n]pic.twitter.com/OfbfnthNAe

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        12. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          We found that the BOLD signal in dACC, AIC and SPL were best explained by the context-modulated decision variable predicted by our model (compared to alternative models). This remains true after we partial out the influence of RT on BOLD signal. [21/n]pic.twitter.com/Xy6JbjpaiW

          1 reply 0 proslijeđenih tweetova 1 korisnik označava da mu se sviđa
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        13. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          So in summary: irrelevant information influences decisions in multiple ways. Our adaptive gain model accounts for all of these different effects. Neurally, signals in several brain regions reflect the predictions of the model. [22/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        14. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          The adaptive gain model emphasises the benefit of having consistent context (relevant or irrelevant info). This is consistent to the view that our neural system code efficiently to maximises sensitivity towards expected features like the Efficient Coding hypothesis [23/n]

          1 reply 0 proslijeđenih tweetova 0 korisnika označava da im se sviđa
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        15. summerfieldlab‏ @summerfieldlab 4. ruj 2018.
          • Prijavi Tweet

          To find out more details, check out the open access paper here: http://www.pnas.org/content/early/2018/08/29/1805224115 … [24/24]

          0 replies 0 proslijeđenih tweetova 4 korisnika označavaju da im se sviđa
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