Page 16 - The 'X' Chronicles Newspaper - September 2023
P. 16

16                            Brains May Predict The Future





             To Make Sense of the

              Present, Brains May

               Predict The Future




          A controversial theory suggests
          that perception, motor control,

              memory and other brain
               functions all depend on
           comparisons between ongoing

             actual experiences and the
           brain’s modeled expectations.



                by Jordana Cepelewicz


         Some neuroscientists favor a predictive
          coding explanation for how the brain

            works, in which perception may be
                thought of as a “controlled
         hallucination.” This theory emphasizes          situation, it will be less surprised.”           College       London,        a     renowned
         the brain’s expectations and predictions                                                         neuroscientist and one of the pioneers of
            about reality rather than the direct         Neuroscientists have long suspected that the predictive coding hypothesis.
        sensory evidence that the brain receives.        a similar mechanism drives how the brain
                                                         works. (Indeed, those speculations are Over the past decade, cognitive scientists,
        In mid-2018, the artificial intelligence         part of what inspired the GQN team to philosophers and psychologists have
        company DeepMind introduced new                  pursue this approach.) According to this taken up predictive coding as a
        software that can take a single image of a       “predictive coding” theory, at each level compelling              idea,     especially      for
        few objects in a virtual room and, without       of a cognitive process, the brain describing how perception works, but

        human guidance, infer what the three-            generates models, or beliefs, about what also as a more ambitious, all-
        dimensional scene looks like from                information it should be receiving from encompassing theory about what the
        entirely new vantage points. Given just a        the level below it.  These beliefs get entire brain is doing. Experimental tools
        handful of such pictures, the system,            translated into predictions about what have only recently made it possible to
        dubbed the Generative Query Network,             should be experienced in a given start directly testing specific mechanisms
        or GQN, can successfully model the               situation, providing the best explanation of the hypothesis, and some papers
        layout of a simple, video game-style             of what’s out there so that the experience published in the past two years have
        maze.                                            will make sense. The predictions then get provided striking evidence for the theory.
                                                         sent down as feedback to lower-level Even so, it remains controversial, as is

        There      are    obvious      technological     sensory regions of the brain.  The brain perhaps best evidenced by a recent debate
        applications for GQN, but it has also            compares its predictions with the actual over whether some landmark results were
        caught the eye of neuroscientists, who are       sensory input it receives, “explaining replicable.
        particularly interested in the training          away”      whatever       differences,      or
        algorithm it uses to learn how to perform        prediction errors, it can by using its Coffee, Cream and Dogs
        its tasks. From the presented image, GQN         internal models to determine likely
        generates predictions about what a scene         causes for the discrepancies. (For               “I take coffee with cream and ____.” It
        should look like — where objects should          instance, we might have an internal              seems only natural to fill in the blank
        be located, how shadows should fall              model of a table as a flat surface               with “sugar.” That’s the instinct cognitive
        against surfaces, which areas should be          supported by four legs, but we can still         scientists Marta Kutas and Steven
        visible or hidden based on certain               identify an object as a table even if            Hillyard of the University of California,

        perspectives — and uses the differences          something else blocks half of it from            San Diego, were banking on in 1980
        between those predictions and its actual         view.)                                           when they performed a series of
        observations to improve the accuracy of                                                           experiments in which they presented the
        the predictions it will make in the future.      The prediction errors that can’t be              sentence to people, one word at a time on
        “It was the difference between reality and       explained away get passed up through             a screen, and recorded their brain activity.
        the prediction that enabled the updating         connections to higher levels (as                 Only, instead of ending with “sugar,”
        of the model,” said Ali Eslami, one of the       “feedforward” signals, rather than               when the last word popped into place, the
        project’s leaders.                               feedback), where they’re considered              sentence read: “I take coffee with cream
                                                         newsworthy, something for the system to          and dog.”

        According to Danilo Rezende, Eslami’s            pay attention to and deal with
        co-author and DeepMind colleague, “the           accordingly. “The game is now about                                 (Continued on Page 17)
        algorithm changes the parameters of its          adjusting the internal models, the brain
        [predictive] model in such a way that            dynamics, so as to suppress prediction           CHECKOUT ALL THE GREAT XZBN
        next time, when it encounters the same           error,” said Karl Friston of University               SHOWS AT WWW.XZBN.NET
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