Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Modeling the Brain Functionality of Consciousness

Neurocomputational models enable the single neuron level of analysis to be linked to the level of large-scale neuronal networks and the interactions between them, so that large-scale processes such as memory retrieval, object recognition, attention, and decision-making can be understood. (Rolls; Memory, Attention, and Decision-Making, 3)

Neural network models are needed in order to provide a basis for understanding the processing and memory functions performed by neuronal networks in the brain. (Rolls; Memory, Attention, and Decision-Making, 543)

Neural network simulation of biologically plausible pattern association memories such as may be present in orbitofrontal cortex and amygdala and autoassociation or attractor networks. (Rolls; Emotion Explained, 454)

Brain Modeling Efforts

Diffusion magnetic resonance imaging is beginning to provide much insight into the brain’s neural network.

Human Connectome Project. NIH has funded a Human Connectome Project (HCP) to map the brain's long-distance communications network.

President Obama’s The Brain Initiative. The Obama administration is planning a decade-long scientific effort to examine the workings of the human brain and build a comprehensive Brain Activity Map. Current status of President Obama’s Neurotechnologies (BRAIN) Initiative.

The Allen Mouse and Human Brain Atlases are projects within the Allen Institute for Brain Science which seek to combine genomics with neuroanatomy by creating gene expression maps for the mouse and human brain. Researching the mouse cerebral cortex will provide fundamental biological information applicable to the human neural network.

European Human Brain Project. Redirection of the European Human Brain Project.

Link to — Brain Modeling by a Collaboration

A further discussion of the Brain Activity Map Project Proposal.

Recent work in the Human Brain Model Ultrahigh-Resolution.

Research study — Brain Transcriptome Atlas (Allen Human Brain Atlas)

Research Study — Brain Connectome, Mesoscale Connectome of Mouse Brain

Research Study — Big Data Functional Interactions in Human Brain

Biological Models of Brain Functionality

Much of the most exciting current progress in cognitive science combines experimental studies of the brain with computational models of how it works. (Thagard; Brain and the Meaning of Life, 63)

Eric Kandel won a Nobel Prize for his research on how learning works in the sea slug, Aplysia. (Thagard; Brain and the Meaning of Life, 49)

Research Study — Computer Simulation of Thalamocortical System — Gerald Edelman’s Large-scale Model of mammalian Thalamocortical System

Research Study — Supercomputer Simulation of Brain Functionality

Research Study — Brain Model via Cerebral Organoids

Research Study — Synaptic Architecture 3D Model

Link to — Consciousness-Models Diagrams

Consciousness

Edelman’s Primary (Core) Consciousness Diagram

Edelman’s Primary Consciousness Model

Building Blocks of Consciousness

Wakeful Consciousness Information Flow

Self

Three Stages of the Self

Neural Network Models

By being able to capture much of the intrinsic electrophysiology of neurons in relatively simple models, it becomes possible to simulate large networks of neurons on a parallel computer. (Traub; Cortical Oscillations, 182)

Simulation of a population of 15,000 cells, with multiple functional subclasses, is readily possible. (Traub; Cortical Oscillations, 182)

A model is proposed in which the feedback pathways serve to modify afferent sensory stimuli in ways that enhance and complete sensory input patterns, suppress irrelevant features, and generate quasi-sensory patterns when afferent stimulation is weak or absent. (Mumford; Thalamus, 982)

Realistic simulations of cortical neurons showed that sparse excitatory connectivity between distant populations of neurons can produce synchronization within one or two cycles, but only if the long-range connections are made on inhibitory as well as excitatory neurons. (Sejnowski; Thalamocortical Oscillations, 980)

Brain Stem Nuclei Involved in Homeostasis

Convergence-Divergence Zones Architecture

Functionality Diagram of Damasio’s Convergence-Divergence Architecture

Hierarchical Organization Diagram

Cortical Layers Diagram

Research Study — Model of the Functioning Brain

The observed network heterogeneity may be crucial for the integration and separation of spatial patterns, properties that have been attributed to the dentate gyrus. Their low activation threshold and low input specificity make immature GCs appropriate substrates for pattern integration—a feature that has been proposed in computational models of adult neurogenesis. (Hippocampal Neurogenesis in Adult)

With the help of the neural network model we can more clearly described the computations that the circuit structure might exert upon thalamic-column interactions, and thereby begin to understand how the entire thalamic circuit might function as a mechanism of attention. (LaBerge; Attentional Processing, 179)

Speed of Processing of a Four Layer Hierarchical Network with Integrate-and-Fire Attractor Dynamics in Each Layer

The visual system has a whole series of cortical areas organized predominantly hierarchically (e.g. V1 to V2 to V4 to.inferior temporal cortex); the rapid information processing that can be performed for object recognition is predominantly feedforward. (Rolls; Memory, Attention, and Decision-Making, 616)

An analysis of response latencies indicates that there is sufficient time for only 10-20 ms per processing stage in the visual system. (Rolls; Memory, Attention, and Decision-Making, 616)

Memory

Computational models have assisted our understanding of the neural bases of learning and memory. (Gluck & Myers; Gateway to Memory, 350)

Covering a range of models from a variety of researchers, makes it possible for different models to capture different aspects of anatomy and physiology and different kinds of behavior, and in many cases these models complement each other. (Gluck & Myers; Gateway to Memory, 350)

Short-Term Memory

There are a number of different short-term memory systems, each implemented in a different cortical area. Short-term memory may be implemented by subpopulations of neurons that show maintained activity while the stimulus or event is being remembered. These memories may operate as autoassociative attractor networks. The autoassociation could be implemented by associatively modifiable synapses between connected pyramidal cells within an area, or by the forward and backward connections between adjacent cortical areas in a hierarchy. (Rolls; Memory, Attention, and Decision-Making, 375)

There are many at least partially independent modules are short-term memory functions in prefrontal cortex. (Rolls; Memory, Attention, and Decision-Making, 383)

Autoassociation or Attractor Memory

Autoassociative memories or attractor neural networks, store memories, each one of which is represented by a pattern of neural activity. They memories are stored in the recurrent synaptic connections of the neurons of the network. (Rolls; Memory, Attention, and Decision-Making, 360)

Marr (1971) proposed a theory for how the hippocampus could function as an associative memory. From this proposal have followed many extensions, usually focusing on the role of the CA3 recurrent collaterals. (Burgess; Hippocampus Spatial Models, 469)

And autoassociation memory can be used as a short-term memory, in which iterative processing around the recurrent collateral connection loop keeps a representation active by continuing neuronal firing. (Rolls; Memory, Attention, and Decision-Making, 360)

Link to — Autoassociation Diagram

Link to — Working Memory Model (Covington)

Emotion

Limbic System Diagram

Movement

Basal Ganglia -- Multiple Parallel Loops

Cerebellum -- Multiple Parallel Loops

Parallel Circuit of Basal Ganglia

Dual Routes of Responses

Voluntary Movement Diagram

Perception

Neuronal Response to Faces

Motivation

Pain and Pleasure Systems

Music Processing Modular Model

Attention and Memory information processing

Sleep and Dreaming

Allan Hobson’s AIM Sleep Model

Sleep Stages Diagram

Modular Brain

Brodmann Areas

Homunculus (Topographic) Diagram

Subcortical Parallel Loops

Thalamus Diagram

Neuron Pulse

Neural Basis of Economic Decision-Making

Behavioral Models

Descriptive models

Animal Models

The anatomy of the visual system has been studied extensively in the macaque monkey, whose visual system is believed to be very similar to that of humans. (Lund; Visual Cortex Cell Types, 1016)

Link to — Consciousness Subject Outline