Wednesday, September 28, 2016

Peer Reviewed Article Explains How the Brain Works

I have been writing and fine-tuning this manuscript for 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:


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 ( Table 1). 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 coactivityThe 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 [35]. 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 [35]. A neuron may exhibit tonic sustained firing due to temporary changes in the strength of certain synapses (short-term synaptic modification [80]), its intrinsic biophysical properties, extrinsic circuit properties (reverberatory circuits), or dopaminergic innervation [25]. Prolonged activity of neurons in association areas is largely thought to allow the maintenance of specific features, patterns and goals [8].

    Goldman-Rakic [37] and [38] 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 [39] 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 [33] and [34]. 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 [57]. 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 [46]. 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 s, 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.
    In Fig. 1 above, representations B, C, D, and E are active during t1, and C, D, E and F are active during t2. Thus representations C, D, and E demonstrate SSC because they exhibit continuous and uninterrupted activity from t1 through t2. The brain state at t1 and the brain state at t2 share C, D, and E in common and therefore can be expected to share other commonalities such as: similar information processing operations, similar memory search parameters, similar mental imagery, similar cognitive and declarative aspects, and similar experiential and phenomenal characteristics. The active nodes that have demonstrated SSC over any specific time interval can be thought of as constituting a unit with emergent functional properties. Together, these nodes impose sustained information processing demands on the lower-order sensory and motor areas within the reach of their long-range connections. The longer the activity in these higher-order neurons is sustained, the longer they remain engaged in hierarchy-spanning, recurrent (and reentrant) broadcasting throughout the cortex and subcortex.

    Compared to those of other mammals, human association areas contain more neurons, more intrinsic and extrinsic connections, and a higher capacity for sustained firing [33] and [34]. These characteristics presumably permit us to retain more information, for a longer time before it decays. This likely allows humans to better retain elements from recent thoughts, and allows the computational results of previous processes to more thoroughly inform subsequent ones. This once influenced the present author to assume that somehow thoughts are “longer” in humans than they are in other animals; however, if thought has an architectural geometry marked by length, then mustn't it also have starting and stopping points? If persistent activity of individual representations in SSC is staggered and overlapping, then there cannot be objective stopping or starting points of thought. Instead, thought itself must be composed of the startings and stoppings of huge numbers of individual elements that could be depicted graphically in the form of a continuous, stream-like distribution (Fig. 2). Therefore, it is not that human thoughts are somehow longer than in other animals; rather, human thought is composed of larger sets of representations that are capable of remaining coactivated longer [70] and [71].
    The reallocation of processing resources in Fig. 2 is similar to the behavior of treads on a military tank. Individual treads are continually placed on the ground temporarily, and the treads that have sat on the ground for the longest are withdrawn in series. The total set of treads touching the ground in one moment partially overlaps with the total set in the next. Our mental set of active representations may cycle in an analogous, although more flexible and stochastic manner. A more precise analogy and schematic will be introduced in Section 5.
    PFC neurons are likely tuned throughout life to best determine what aspects of the present environment should be maintained in SSC (or released from maintenance) given the current scenario and its preceding circumstances. When confronted with a complex configuration of stimuli, the PFC may select the representations that it “predicts” should be temporarily maintained for their processing utility in the immediate future. This selection process is likely determined by the incoming stimulus configuration itself, prior probability as encoded in the network, and the network-biasing representations already in SSC. Initially during development, the process of selecting neurons for persistent activity may be random and heavily influenced by innate connectivity. The expertise of the PFC is probably garnered slowly, over developmental time, after connections between groups of neurons exhibiting sustained firing are strengthened for their role in mediating task proficiency and reward achievement. The selection process for SSC is perhaps best exemplified by the ability to identify and maintain strategically important representations from a forthcoming scenario. A sentence (spoken or written) is a suitable example. A sentence will be comprehended if: 1) the relevant representations are identified and enter into SSC; 2) all the necessary representations are sustained throughout the duration of the sentence; 3) the network has enough experience with this particular combination of representations to build the appropriate imagery, depicting them in the way they were intended. Most people have had the experience where either the wrong representations were anchored upon, or the right representations could not be maintained for long enough, and the sentence had to be repeated or reread.

    The quantity of SSC can be thought of as directly proportional to the number of sustained nodes and the average length of time of their activity [69], [70] and [71]. It should also be possible, in theory, to quantify icSSC by determining the proportion of previously active neural nodes that have remained active over a given time period. One way to do this would be to determine how long it takes half of the currently firing association neurons to sufficiently reduce their firing. Employing the idea of a “half-life” may be a useful concept even though the “decaying quantity” may not exhibit constant exponential decay, and despite the fact that current scanning and recording methods could not produce the necessary data without significant extrapolation. If the average rate of decay was properly operationally defined and could be measured, then cognitive neuroscientists would be able to discuss the “icSSC half-life” associated with individuals or even species. Would it be informative if it were found that Wistar rats have an average icSSC half-life of, say, one second, macaque monkeys twice this and humans twice that? Even in a single individual, this number is likely to vary depending on the task at hand, level of arousal, motivational state, brain oscillation factors, and brain regions assayed. Moreover, short-term memory/priming would have a much longer half-life than the focus of attention. An SSC/icSSC profile featuring numerous such assays could be computed for an individual based on various standardized criteria. If characterized correctly and averaged meaningfully, these numbers could prove to be consistent and reliable psychometric markers. Tononi [83] developed a method for calculating a measure of “integrated information” within a single, static brain state. The concept of icSSC could be used to expand on this measure in order to calculate the integration of information between two brain states, or across multiple brain states.

    It is not always the case that the majority of representations are conserved from one thought to the next. When they become a lower priority, nearly all items in the focus of attention can be displaced at the same time. This readily happens when we are exposed to a new, salient, perhaps emotionally laden stimulus. Whenever a person loses their train of thought, and forgets what they were just thinking, SSC in the focus of attention (though not necessarily in short-term memory) is interrupted. SSC “jumps,” reallocating attentional resources, and reorienting to the new stimulus configuration and its accompanying set of features. Such a jump would constitute a disruption of, or fluctuation in, mental continuity. The degree of fluctuation in continuity varies depending on the proportion of neural activity that is abruptly deactivated (Fig. 3). Because icSSC is the change in SSC, as attention shifts, SSC decreases, and icSSC increases.
    In the most intelligent mammals, late motor output and early sensory activity are heavily influenced by several seconds of sustained input from association areas. In mammals with smaller association areas, capable of less SSC, motor and sensory output are informed by a much briefer window of continuous activity. High SSC likely allows “behavioral continuity” where sequential behaviors can be complexly interrelated and mutually informed. This can be contrasted with the more isolated and impulsive behaviors seen in individuals with injuries to the PFC (i.e., field-dependent behavior in which the patient's behavior is dictated by incidental cues and distractions). In fact, the temporal extent of SSC may be a major facet of the “general factor” of intelligence. SSC may be related to, and a primary determinant of, attention span, behavioral flexibility, working memory capacity, short-term memory capacity, reasoning ability, and general fluid intelligence. Furthermore, significant individual differences in SSC may exist in humans where deficits in this capacity may map onto a variety of clinical syndromes such as schizophrenia, mental retardation, cognitive aging, chronic stress, various forms of intoxication, and prefrontal injury. Nevertheless, why did SSC and icSSC evolve, what purposes do they serve, and how do they relate to dopaminergic functions? Mammals most likely evolved the capacity to sustain certain representations so that hypothetical groupings of representations could be modeled and systemized.