Hierarchical Brain

An explanation of the human brain

First published 1st February 2024. This is version 1.5 published 2nd March 2024.
Three pages are not yet published: sleep, memory and an index.
Copyright © 2024 Email info@hierarchicalbrain.com

Warning - the conclusions of this website may be disturbing for some people without a stable mental disposition or with a religious conviction.


Attention is one of the major facets of consciousness. It feels to me like a spotlight that I can move between things that I want to examine more closely, and the focussing of my conscious thoughts on one thing at a time, applying to perception, memory and action. Research has shown, however, that attention is actually the selection of certain signals over others, driven by a multi-level competition involving relative signal strengths (which are bottom-up, or afferent, influences) and predictions (which are top-down, or efferent, influences). So there is a large explanatory gap between my experience and reality.

The explanation for this gap is that my personal experience of attention is based solely on my brain’s internal model of attention, which is built and maintained by exactly the same hierarchical afferent processing that is used to process sense data. The processing of sense data results in the creation and update of symbol schemas that represent things in the world or in my body; the processing of data related to my internal brain processes (which I call cognoception), in this case the process of attention, results in the creation and update of a symbol schema or model in my self symbol schema that represents the process of attention, and it is only this model that I can be aware of.

Attention is a high-level brain function at level 6 in my seven hierarchical levels of description because it depends on the existence of symbol schemas.

Contents of this page
My personal experiences of attention - a list of how various aspects of attention feel to me.
The science of attention - what science has shown about what attention really is and how it works.
The hierarchical explanation - my explanation of attention.
Differences in attention - changes to and issues with attention (including ADHD).
Additional points - points not covered in the previous sections.
References - references and footnotes.

My personal experiences of attention

What science shows that attention really is

The hierarchical explanation

Differences in attention

Additional points

References For information on references, see structure of this website - references

  1. ^ ^ Impact of Distracted Driving on Safety and Traffic Flow - Stavrinos et al. 2013
    doi: 10.1016/j.aap.2013.02.003 downloadable here or see GoogleScholar.
    Page 2, beginning of first paragraph: “With advancing technology, the number of distractions to which motor vehicle drivers are exposed continues to increase. This increase in availability of distractions has most likely attributed to the 30% increase in the number of motor vehicle collisions (MVCs) in the United States from 2005 to 2008 related to distraction. One of the most common distractions in which motor vehicle drivers engage is using a cell phone.”
    Page 4, end of first paragraph: “drivers who are distracted navigate at slower speeds, leave larger intervals between their own vehicle and the vehicle in front of them, and have reduced reaction times.”
  2. ^ ^ The attention schema theory: a mechanistic account of subjective awareness - Webb and Graziano 2015
    doi:10.3389/fpsyg.2015.00500 downloadable here or see GoogleScholar.
    Pages 3-4 under the heading “Attention”: “Because the amount of information with which our senses are bombarded is typically far too vast to deeply process in its entirety, some mechanism must exist to determine or 'select' which information to process deeply. Much work in cognitive psychology and neuroscience over the past half century has focused on which factors determine this 'selection' process and how the brain accomplishes such an operation.
    An influential theory put forward by Desimone and Duncan, the 'biased competition' theory, characterizes attention as a signal competition within the brain. Signals compete in order to be more deeply processed and ultimately to influence and guide behavior. This signal competition emerges at the earliest stages of processing in the nervous system and is present at every stage. ...Different factors can influence or 'bias' the outcome of this competition. One such factor has to do with the saliency of the stimulus. Especially intense or salient stimuli can 'grab' attention in a bottom-up, stimulus-driven manner.
    As signals progress through the nervous system, they are increasingly subject to the influence of top-down, biasing signals. By this method, attention can be internally directed, slanting the outcome of this signal competition in a goal-directed manner based on the demands of the current task. Signals that correspond to current goals can be boosted and irrelevant signals can be suppressed.”
  3. ^ ^ A selective review of selective attention research from the past century - Driver 2010
    doi: 10.1348/000712601162103 downloadable here or see GoogleScholar.
    This useful review focuses on work from the 1950s onwards, mostly cognitive neuroscience in Britain.
    Page 72, under the heading “Future attention research”:
    “I hope that this rather idiosyncratic review has illustrated the tremendous progress made in selective attention research in the second half of the 20th century, and also the substantial contribution from British psychology.”
  4. ^ Is Attentional Resource Allocation Across Sensory Modalities Task-Dependent - Wahn and Konig 2017
    doi: 10.5709/acp-0209-2 downloadable here or see GoogleScholar.
    Beginning of abstract, page 83: “Human information processing is limited by attentional resources. That is, via attentional mechanisms, humans select a limited amount of sensory input to process while other sensory input is neglected.”
  5. ^ Working memory and attention - a conceptual analysis and review - Oberauer 2019
    doi: 10.5334/joc.58 downloadable here or see GoogleScholar.
    Page 3, under the heading “Attention as a Resource”: “The idea of attention as a resource is that the cognitive system has a limited resource that can be used for carrying out so-called attention-demanding processes. The resource is assumed to be a continuous quantity that can be split arbitrarily and allotted to different processes, depending on task demands.”
  6. ^ What is attention? - Krauzlis, Wang, Yu and Katz 2021
    doi: 10.1002/wcs.1570 download not available, but see GoogleScholar.
    This starts with the most general definition of attention. Beginning of abstract, page 1: “We define attention as 'the set of evolved brain processes that leads to adaptive and effective behavioral selection.'”
    It goes on to make some useful points. Second paragraph of introduction, page 1: “... we hold attention to be synonymous with a particular set of brain processes. This might seem obvious, but it is not unusual to see attention described as though it were some sort of agent acting on the brain (e.g., 'attention increases the firing rates of neurons'), rather than a set of processes within the brain.”
    Page 5, 4th paragraph, under the heading “An evolutionary perspective”: “...attention emerged as a set of brain functions that helped match the flexibility and selectivity of the animal’s behavioral repertoire to the affordances of their ever-changing environment. These brain functions do not generate the behavior; instead, they help ensure that the appropriate information is ready at each moment to select and guide the next behavioral response. This perspective also provides an answer to the question 'why is there attention?'. Attention is often described as necessary for managing limited resources, but the arguments tend to focus on internal resources: energy consumption and computing capacity in the brain. We agree these internal limitations are important, but we suggest that attention evolved primarily to address a different limited resource that is external to the animal: the fleeting opportunities to extract value from the environment.”
  7. ^ ^ Attention and platypuses - Shomstein, Zhang and Dubbelde - 2023
    doi: 10.1002/wcs.1600 downloadable here or see GoogleScholar.
    The reference to “platypuses” is an allusion to biological taxonomy where the platypus does not fit into either mammal or bird categories. This paper proposes a new model called “dynamically weighted prioritization”, which is based on, and similar to, the “multi-level system of weights and balances” in reference 10 below. It then gives examples of some phenomena that have been uncovered by attention research that do not fit neatly into other attentional models; these are what they refer to as platypuses. It does briefly cover prediction (without using the word) by referencing Karl Friston’s work on the free energy principle, and says a Bayesian framework is helpful.
  8. ^ ^ Neural mechanisms of selective visual attention - Desimone and Duncan 1995
    doi: 10.1146/annurev.ne.18.030195.001205 downloadable here or see GoogleScholar.
    Page 194, first and second paragraphs: “At some point (or several points) between input and response, objects in the visual input compete for representation, analysis, or control. The competition is biased, however, towards information that is currently relevant to behavior. ... the model we develop is that attention is an emergent property of many neural mechanisms working to resolve competition for visual processing and control of behavior.”
  9. ^ Top-down and bottom-up mechanisms in biasing competition in the human brain - Beck and Kastner 2009
    doi:10.1016/j.visres.2008.07.012 downloadable here or see GoogleScholar.
    Beginning of abstract: “The biased competition theory of selective attention has been an influential neural theory of attention, motivating numerous animal and human studies of visual attention and visual representation. There is now neural evidence in favor of all three of its most basic principles: that representation in the visual system is competitive; that both top-down and bottom-up biasing mechanisms influence the ongoing competition; and that competition is integrated across brain systems.”
    And from conclusions on page 11: “The first principle of competition now seems well established; multiple stimuli presented simultaneously in the visual field compete for representation in visual cortex by mutually suppressing neural responses. Moreover, evidence suggests that this competition is greatest at the level of the RF [Receptive Field]. There is also now an increasing body of evidence in favor of the second principle of control, suggesting that competition can be biased by both top-down and bottom-up factors. The finding that the stimulus-driven factor of stimulus similarity also affects competition is particularly interesting, as it opens a new avenue of investigation into influences on competition.”
  10. ^ Attention as a multi-level system of weights and balances - Narhi-Martinez, Dube and Golomb 2022
    doi: 10.1002/wcs.1633 downloadable here or see GoogleScholar.
    This paper first tries to give a definition of attention. Second sentence of abstract, page 1: “Despite the word’s place in the common vernacular, a satisfying definition for 'attention' remains elusive. Part of the challenge is there exist many different types of attention, which may or may not share common mechanisms. Here we review this literature and offer an intuitive definition that draws from aspects of prior theories and models of attention but is broad enough to recognize the various types of attention and modalities it acts upon: attention as a multi-level system of weights and balances. While the specific mechanism(s) governing the weighting/balancing may vary across levels, the fundamental role of attention is to dynamically weigh and balance all signals - both externally-generated and internally-generated - such that the highest weighted signals are selected and enhanced. Top-down, bottom-up, and experience-driven factors dynamically impact this balancing, and competition occurs both within and across multiple levels of processing.”
    The introduction (pages 1-2) is an excellent summary of definitions of attention and previous research on “What is attention?”. However, this paper has no mention of the multiple levels being hierarchical, no mention of prediction as the major top-down influence, and also no mention of the difference (or explanatory gap) between the personal experience of attention and the neurological explanation of what it is.
  11. ^ Cognitive Neuroscience: The Biology of the Mind - Gazzaniga, Ivry and Mangun, Fourth Edition 2014 Norton & Company USA
    Page 285, under the heading “Take-home messages” at the end of the section on “Models of attention”: “Attention involves both top-down (voluntary), goal-directed processes and bottom-up (reflexive), stimulus-driven mechanisms.”
  12. ^ YouTube video - “Ransom & Fazelpour’s Intro to 'Three Problems For Predictive Coding Theory Of Attention'” - Ransom and Fazelpour 2016
    The summary of Predictive Processing is taken partly from this video, which is an accompaniment to the online paper Three Problems for the Predictive Coding Theory of Attention - Ransom and Fazelpour 2015. The video contains a useful introduction to the theory, as well as a description of a possible problem with the theory, and the online paper has a number of thoughts and answers at the end.
    The following quote is from the a slide on the YouTube video at 4' 45":
    “Attention is the process of selecting the prediction error expected to be most precise and revising perceptual hypotheses on this basis.”
  13. ^ Whatever next? Predictive brains, situated agents, and the future of cognitive science - Andy Clark 2013
    doi: 10.1017/S0140525X12000477 downloadable here or see GoogleScholar.
    Beginning of abstract: “Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success.”
  14. ^ The free-energy principle: a rough guide to the brain? - Friston 2009
    doi: 10.1016/j.tics.2009.04.005 downloadable here or see GoogleScholar.
    Page 299, under the heading “Attention and precision”, second paragraph: “...attention is simply the process of optimising precision [of prediction errors] during hierarchical perceptual inference.”
  15. ^ Reconciling predictive coding and biased competition models of cortical function - Spratling 2008
    doi: 10.3389/neuro.10.004.2008 downloadable here or see GoogleScholar.
    Beginning of conclusion on page 8: “At first sight the biased competition and predictive coding theories seem to be diametrically opposed: one requires cortical feedback to be excitatory while the other proposes that feedback is suppressive. The predictive coding and biased competition models have therefore been considered as distinct theories of cortical function. However, a simple variation on the conventional neural network implementation of the biased competition model has been shown to be identical to the linear predictive coding model. Hence, a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to linear predictive coding. These previously distinct, rival, theories of cortical function can thus be united.”
  16. ^ Cultural variation in management of attention by children and their caregivers - Chavajay and Rogoff 1999
    doi: 10.1037/0012-1649.35.4.1079 downloadable here or see GoogleScholar.
    Page 1089, last paragraph: “In conclusion, the findings of the present research provide insight into processes of human attention across communities. Our research suggests that simultaneous attention may be practiced in some cultural groups much more commonly than in others. This may relate to cultural expectations regarding what are considered appropriate and desirable ways to attend to others in social interactions rather than to variation in skill.”
  17. ^ Principles of Neural Science Fifth edition - Kandel et al. McGraw-Hill US 2012
    Page 619, third paragraph, relating to attention: “Our sense that we identify multiple objects simultaneously is illusory. Instead, we serially process objects in rapid succession by shifting attention from one to the next.”
  18. ^ The Emperor’s New Mind - Penrose Oxford University Press 1989, also see The Emperor’s New Mind
    Pages 514-5, in chapter 9 “Real brains and model brains”, under the heading “Parallel computers and the 'Oneness' of consciousness”: “A characteristic feature of conscious thought ... is its 'oneness' - as opposed to a great many independent activities going on at once. Utterances like 'How can you expect me to think of more than one thing at a time?' are commonplace. Is it possible at all to keep separate things going on in one’s consciousness simultaneously? Perhaps one can keep a few things going on at once, but this seems to be more like continual flitting backwards and forwards between the various topics than actually thinking about them simultaneously, consciously, and independently. If one were to think consciously about two things quite independently it would be more like having two separate consciousnesses, even if only for a temporary period, while what seems to be experienced (in a normal person, at least) is a single consciousness which may be vaguely aware of a number of things, but which is concentrated at any one time on only one particular thing. Of course, what we mean by 'one thing' here is not altogether clear.”

Page last uploaded Fri Mar 1 09:07:50 2024 MST