Wednesday, September 28, 2016

Peer Reviewed Article Explains How the Brain Creates Consciousness


I have been writing and fine-tuning this manuscript for more than ten years now and it is finally published. It outlines my model of working memory and my theory of how the brain and the mind are linked. They are linked by a very specific pattern of neural activity that creates the continuity of consciousness.

The open access article is titled:


Incremental Change in the Set of Coactive Cortical Assemblies Enables Mental Continuity


and can be read here for free:



http://www.sciencedirect.com/science/article/pii/S0031938416308289


http://www.sciencedirect.com/science/article/pii/S0031938416308289


Abstract


This opinion article explores how sustained neural firing in association areas allows high-order mental representations to be coactivated over multiple perception-action cycles, permitting sequential mental states to share overlapping content and thus be recursively interrelated. The term “state-spanning coactivity” (SSC) is introduced to refer to neural nodes that remain coactive as a group over a given period of time. SSC ensures that contextual groupings of goal or motor-relevant representations will demonstrate continuous activity over a delay period. It also allows potentially related representations to accumulate and coactivate despite delays between their initial appearances. The nodes that demonstrate SSC are a subset of the active representations from the previous state, and can act as referents to which newly introduced representations of succeeding states relate. Coactive nodes pool their spreading activity, converging on and activating new nodes, adding these to the remaining nodes from the previous state. Thus, the overall distribution of coactive nodes in cortical networks evolves gradually during contextual updating. The term “incremental change in state-spanning coactivity” (icSSC) is introduced to refer to this gradual evolution. Because a number of associated representations can be sustained continuously, each brain state is embedded recursively in the previous state, amounting to an iterative process that can implement learned algorithms to progress toward a complex result. The longer representations are sustained, the more successive mental states can share related content, exhibit progressive qualities, implement complex algorithms, and carry thematic or narrative continuity. Included is a discussion of the implications that SSC and icSSC may have for understanding working memory, defining consciousness, and constructing AI architectures.


    1. Introduction

    The present article will delineate a simplistic but previously overlooked nonlinear dynamic pattern of brain activity. Two hypothetical constructs are introduced to describe this pattern. The first construct is state-spanning coactivity (SSC), which occurs when cortical nodes exhibit sustained coactivity during the span of short-term memory. The gradual evolution of SSC exhibits a distinctive spatiotemporal pattern of turnover as it plays out in real time. The second construct introduced here, incremental change in state-spanning coactivity (icSSC), refers to this pattern of turnover. icSSC conveys that the set of nodes that are simultaneously coactive changes incrementally as newly activated nodes are added and others are deactivated while a distinct subset remains in SSC. Spreading activity from the nodes in SSC select: 1) inactive neural nodes for activation, 2) active nodes for deactivation, and 3) active nodes for sustained activation. Because a distinct subset of nodes is always conserved from one brain state to the next, each state is embedded recursively in the previous state, amounting to an iterative process that has the potential to progress algorithmically toward a complex result. The general intention of the present article is to propose a qualitative model delineating the theoretical functions of SSC and icSSC from the perspective of cognitive neuroscience.
    The term SSC can be used either to denote a property or to designate a set of neurons. icSSC denotes a property or process. Both are related to the construct of working memory, which is defined as a system responsible for the transient holding and processing of attended information. The fundamental assumption made by this article is that the content of working memory can be said to be in SSC; and as working memory progresses over time, the content can be said to exhibit icSSC. This assumption is applied not only to working memory as the same could be said of attention, consciousness or short-term memory. icSSC can be taken to be the underlying neural substrate of mental continuity. As proposed here, mental continuity is a process where a gradually changing collection of mental representations held in attention/working memory emerges from the icSSC of neural nodes. The thematic and narrative quality created by this continuity during internally generated thought may be largely congruent with key facets of conscious experience. In the course of exploring how neural continuity creates mental continuity, this article will attempt to integrate current theoretical approaches while remaining consistent with prevailing knowledge.
    Table 1: Definition of Key Terms
    Instantaneous Coactivity
    The coactivity of a set of cortical nodes in a single instant or state.
    State-spanning Coactivity (SSC)
    Sustained coactivity exhibited by a set of two or more cortical nodes that spans two or more consecutive brain states
    Incremental Change in State-spanning Coactivity (icSSC)
    The process in which a set of three or more neural nodes exhibiting SSC undergoes a shift in group membership, where at least two nodes remain in SSC and at least one is deactivated and replaced by a new node
    Mental Continuity
    The recursive interrelatedness of consecutive mental states made possible by icSSC

    Animals are information-processing agents. They receive unprocessed data through sensory receptors, expose it to a massively parallel network of nodes and channels, and allow the interaction between the activity and the existing network to determine behavior. Even small invertebrates with elementary nervous systems exhibit ongoing, internally generated neural activity that temporarily biases the network weights. Because it involves mechanisms that include sustained firing, this continuous endogenous processing constitutes a fleeting form of SSC, even in animals like the nematode and fruit fly. In vertebrates, however, SSC involves the coactivation of high-level representations from long-term memory within a single, massively interconnected representational network (telencephalon). Each such representation is a record of the distribution of past neural activity corresponding to a recognizable stimulus or motor pattern. An instantaneous attentional state is composed of a novel combination of these template-like representations which together create contextual, cognitive content. The mammalian neocortex can hold a number of such mnemonic representations coactive for hundreds of milliseconds, using them to make predictions by allowing them to spread their activation energy together, throughout the thalamocortical network. This activation energy converges on the inactive representations in long-term memory that are the most closely connected with the current group of active representations, making them active and pulling them into SSC. Thus, new representations join the representations that recruited them, are incorporated into the set of coactive parameters in SSC and used in subsequent searches.
    When the activity of certain nodes can be sustained for several seconds at a time, as in primate association cortex, the complexity of search in such a system increases. Highly sustained activity allows prioritized representations to act as search parameters for multiple perception-action cycles. This permits more dynamic icSSC, whereby goal-relevant representations can be held constant as others are allowed to change. The icSSC taking place in association areas allows task-pertinent representations to be maintained over multiple cycles, in order to direct complex sequences of interrelated mental states. The individual states in a sequence of such states can be considered interrelated because they share representational content. The associations linking these sequences are saved to memory, impacting future searches and ultimately permitting semantic knowledge, planning, and systemizing. 

    2. Sustained firing, attentional updating, and memory decay

    Mammals regularly encounter scenarios involving sets of stimuli that may remain present (or relevant) throughout the experience. In order to systemize such a scenario, it may be necessary to maintain mental representations of the pertinent contextual stimuli during the experience, and even afterward. Mammalian brains are well-equipped to do exactly this. The glutamatergic pyramidal neurons in the prefrontal cortex (PFC), parietal cortex, and other association cortices, are specialized for sustained firing, allowing them to generate action potentials at elevated rates for several seconds at a time (Fuster, 2009). In contrast, neurons in other brain areas, including cortical sensory areas, often remain persistently active for periods of mere milliseconds unless sustained input from either the environment or association areas makes their continued activity possible (Fuster, 2009). A neuron may exhibit tonic sustained firing due to temporary changes in the strength of certain synapses (short-term synaptic modification (Stokes, 2015)), its intrinsic biophysical properties, extrinsic circuit properties (reverberatory circuits), or dopaminergic innervation (Durstewitz & Seamans, 2002). Prolonged activity of neurons in association areas is largely thought to allow the maintenance of specific features, patterns and goals (Baddeley, 2007).
    Goldman-Rakic (1987; 1990) first suggested that the phenomenon of sustained firing in the PFC is responsible for the information maintenance capabilities of the temporary storage buffers of working memory. Goldman-Rakic (1995) also proposed that the PFC is parceled into several specialized regions, each of which is responsible for detecting, representing and sustaining a different extraction of multimodal information. Since then, the PFC, along with a number of association areas, has been divided into increasingly smaller modules, each with unique receptive/projective fields and functional properties including faculties such as short-term spatial memory, short-term semantic memory, response switching, error detection, reward anticipation, impulse suppression, and many others. Working memory, executive processing and cognitive control are now widely thought to stem from the active maintenance of patterns of activity in the PFC, especially the dorsolateral PFC, that correspond to goal-relevant features  and patterns (Fuster, 2002). The temporary persistence of these patterns ensures that they continue to transmit their effects on network weights as long as they remain active, biasing ongoing processing, and affecting the interpretation of stimuli that occur during their episode of continual firing (Miller & Cohen, 2001). This persistence ensures that context from the recent past is taken into account during action selection.
    During any experience, some neural nodes exhibit more prolonged sustained firing than others. I will assume that in general the most enduringly active nodes correspond to what attention is most focused on, or the underlying theme that remains most constant as other contextual features change. From subjective introspection we know that when we envision a scenario in our mind’s eye, we often notice it transform into a related but distinctly different scenario (James, 1978). These two scenarios are related because our brain is capable of icSSC. In other words, the distribution of active neurons in the brain transfigures incrementally from one configuration to another, instead of changing all at once. If it were not for the phenomenon of icSSC, instantaneous information processing states would be time-locked and isolated (as in most serial and parallel computing architectures), rather than continuous with the states before and after them.
    These observations point to the notion that every cortical state is composed of a subset of elements from the previous state, and also composed of increasingly smaller subsets of elements of states directly before that. In fact, when comparing successive cortical states, the shorter the time difference between two states (on the order of seconds to fractions of milliseconds), the more similar in composition the two states will be. For instance, over the span of 10 milliseconds, a relatively large proportion of nodes will exhibit uninterrupted coactivity; however, over 10 seconds, this proportion will be much smaller. Here, we will be concerned with neural nodes exhibiting SSC at two distinct levels: A) short-term memory/priming, i.e., elements of long-term memory activated above baseline (for seconds to minutes); and B) the focus of attention/immediate memory, i.e., a small, perhaps more active subset of A (for milliseconds to a few seconds). Items in SSC within the focus of attention likely demonstrate active neural binding whereas items in SSC within short-term memory may not.
    Mental continuity and icSSC require a densely interconnected representational system such as a neural network that is capable of holding two or more representations (each specifying discrete and separate informational content) active over the course of two or more points in time (Fig. 1). The sustained activity of a single representation over time does not provide any context or associative/relational content, and so should not be taken to be sufficient for mental continuity. More than one representation is needed. Although its limits are presently being debated, the human neocortex is clearly capable of holding numerous representations active over numerous points in time.

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