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Glossary

A comprehensive reference of terms used in Brain Visualizer and FEAGI.

A​

Afferent Connection

  • An incoming neural connection
  • Connections from other cortical areas that send signals TO the current area
  • Also called "input connections"
  • See also: Efferent Connection, Mapping

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B​

Brain Circuit

  • Organizational container for grouping related cortical areas and sub-circuits
  • Creates hierarchical structure in complex genomes
  • Formerly called "Brain Region"
  • Can contain cortical areas, other brain circuits, or both
  • See also: Genome, Cortical Area

Brain Monitor

  • The 3D visualization tool in Brain Visualizer
  • Shows cortical areas as colored 3D volumes
  • Displays real-time neural activity
  • Provides spatial understanding of genome structure
  • See also: Circuit Builder

Brain Visualizer (BV)

  • Interactive 3D visualization and editing client for FEAGI
  • Provides tools for creating, modifying, and monitoring neural genomes
  • Includes Circuit Builder (2D) and Brain Monitor (3D) views

Burst

  • One cycle of neural processing in FEAGI
  • The fundamental time unit for neural computation
  • Neural activity, firing, and timing are measured in bursts
  • Burst rate (Hz) indicates processing frequency

C​

Circuit Builder

  • The 2D node-based graph editor in Brain Visualizer
  • Displays cortical areas as colored boxes with connection lines
  • Primary tool for building and organizing neural circuits
  • See also: Brain Monitor, Cortical Area Node

Connectivity Rule

  • Template defining the shape and properties of neural connections
  • Formerly called "Morphology"
  • Includes patterns like All-to-All, Block-to-Block, Lateral
  • Determines how neurons in one area connect to neurons in another
  • See also: Mapping

Core Area

  • Special system cortical areas built into FEAGI
  • Cannot be deleted or have dimensions changed
  • Position and connections can be modified
  • Most parameters are read-only
  • Identified by Dark Blue color in Circuit Builder

Cortical Area

  • A volume of neurons that processes information
  • The fundamental building block of FEAGI genomes
  • Has dimensions (X, Y, Z) that determine neuron count
  • Has a type: IPU, OPU, Memory, Custom, or Core
  • Can connect to other cortical areas via mappings
  • See also: IPU, OPU, Neuron, Voxel

Cortical Area Details Window

  • Comprehensive properties window for cortical areas
  • Contains multiple sections: Summary, Neuron Firing, Memory, PSP, etc.
  • Supports single-select (full features) and multi-select (batch editing)
  • Most complex window in Brain Visualizer
  • See also: Cortical Area

Cortical Area Node

  • Visual representation of a cortical area in Circuit Builder
  • Shows as colored rectangular box with title and ports
  • Color indicates type (IPU, OPU, Memory, Custom, Core)
  • Ports allow creating connections
  • See also: Circuit Builder

Cortical ID

  • Unique identifier for each cortical area
  • Generated by FEAGI
  • Base64-encoded string
  • Used internally for all API operations
  • Read-only, cannot be changed by user

Custom Area

  • Cortical area type for internal processing
  • Not directly connected to external inputs/outputs
  • Used for intermediate computation, pattern recognition, decision making
  • Shown in Blue color in Circuit Builder
  • See also: Cortical Area

D​

Degeneracy Coefficient

  • Rate at which synaptic connections weaken over time
  • Part of Post-Synaptic Potential parameters
  • 0 = no decay (permanent connections)
  • Higher values = faster forgetting
  • Implements synaptic homeostasis

Dimensions

  • The X, Y, Z size of a cortical area in voxels
  • Determines total neuron count
  • Total neurons = X × Y × Z × neurons per voxel
  • Larger dimensions = more neurons = more processing capacity
  • See also: Voxel, Neuron

E​

Efferent Connection

  • An outgoing neural connection
  • Connections from the current area that send signals TO other areas
  • Also called "output connections"
  • See also: Afferent Connection, Mapping

F​

FEAGI

  • Framework for Evolutionary Artificial General Intelligence
  • The backend neural simulation system
  • Simulates neurons, synapses, and neural dynamics
  • Brain Visualizer is a client that connects to FEAGI

Fire Threshold

  • The membrane potential level at which a neuron fires
  • Part of neuron firing parameters
  • Lower values = neurons fire more easily
  • Higher values = neurons require stronger input
  • Critical for controlling cortical area sensitivity

G​

Genome

  • The complete neural architecture in FEAGI
  • Contains all cortical areas, brain circuits, and connections
  • Equivalent to a "brain" or "neural network"
  • Can be saved, loaded, and shared

I​

InfluxDB

  • Time-series database for logging neural activity
  • Required for membrane potential and synaptic monitoring
  • Stores historical data for analysis
  • Optional component of FEAGI system

IPU (Input Processing Unit)

  • Cortical area type that receives data from outside FEAGI
  • Connected to sensors, cameras, text input, etc.
  • Uses neural coding to convert external data to neural activity
  • Shown in Dark Gray color in Circuit Builder
  • See also: Cortical Area, OPU

L​

Leak Coefficient

  • How quickly neurons lose accumulated charge
  • Part of neuron firing parameters
  • 0% = no leak, perfect integration
  • 100% = rapid decay, short-term only
  • Determines temporal integration window

Lifespan (Neuron)

  • How long a memory trace persists in Memory cortical areas
  • Increases when memory is accessed (consolidation)
  • Can become permanent when reaching long-term threshold
  • Measured in bursts

M​

Mapping

  • A neural connection between two cortical areas
  • Defines how neurons in source area connect to neurons in destination area
  • Uses a connectivity rule to determine connection pattern
  • Can be afferent, efferent, or recursive
  • See also: Connectivity Rule, Afferent Connection, Efferent Connection

Membrane Potential

  • The accumulated electrical charge in a neuron
  • Increases with excitatory input
  • Decreases with inhibitory input and leak
  • Neuron fires when threshold is reached
  • See also: Fire Threshold

Memory Area

  • Cortical area type specialized for storing and recalling patterns
  • Has memory-specific parameters: lifespan, consolidation, temporal depth
  • Neurons can become permanent (long-term memory)
  • Shown in Dark Red color in Circuit Builder
  • See also: Cortical Area

N​

Neuron

  • The fundamental computational unit in FEAGI
  • Accumulates membrane potential from inputs
  • Fires when threshold is reached
  • Has refractory period after firing
  • Multiple neurons exist in each voxel

Neuron Coding

  • How data is encoded/decoded between external format and neural activity
  • For IPU: converts sensor data to firing patterns
  • For OPU: converts firing patterns to actuator commands
  • Includes signage (positive/negative/both), behavior (rate/phase/burst), type (intensity/position/motion)
  • See also: IPU, OPU

Neurons Per Voxel

  • How many neurons exist in each voxel of a cortical area
  • Typically 1 for most areas
  • Higher values increase processing density
  • Not applicable to IPU/OPU areas
  • See also: Voxel

O​

OPU (Output Processing Unit)

  • Cortical area type that sends data outside FEAGI
  • Connected to motors, displays, text output, etc.
  • Uses neural coding to convert neural activity to external data
  • Shown in Orange color in Circuit Builder
  • See also: Cortical Area, IPU

P​

Position

  • The X, Y, Z coordinates of a cortical area in 3D space
  • Used for visual organization only
  • Does not affect neural processing
  • Helps understand spatial relationships in genome

Post-Synaptic Potential (PSP)

  • The strength of a synaptic connection
  • Determines how much influence one neuron has on another
  • Can be uniform or vary per connection
  • Can degenerate over time
  • Part of connection weight and plasticity system

Q​

Quick Menu

  • Context-sensitive right-click menu in Brain Visualizer
  • Shows different options based on what's selected
  • Provides quick access to common operations
  • Options include: Details, Quick Connect, Clone, Delete, etc.

R​

Recursive Connection

  • A connection from a cortical area to itself
  • Allows iterative processing and feedback
  • Used for pattern completion, temporal integration, attractor dynamics
  • Special port (top) in Circuit Builder for recursive connections

Refractory Period

  • Time a neuron cannot fire after firing
  • Prevents continuous firing
  • Creates temporal spacing between spikes
  • Measured in bursts
  • Part of neuron firing parameters

S​

Snooze Period

  • Rest time after a neuron reaches consecutive fire limit
  • Longer than refractory period
  • Prevents neuron exhaustion
  • Encourages distributed activation across area
  • Part of neuron firing parameters

Split View

  • Feature allowing side-by-side or stacked windows
  • Can display Circuit Builder and Brain Monitor simultaneously
  • Supports horizontal and vertical splits
  • Independent camera and navigation per view

Synapse

  • Connection from one neuron to another
  • Carries signal between neurons
  • Has strength (post-synaptic potential)
  • Can strengthen or weaken over time
  • Total synapse count tracked in top bar

Synaptic Attractivity

  • How attractive a cortical area is for incoming connections
  • Affects automatic synapse formation
  • Higher values encourage more connections
  • Range typically 1-100

T​

Temporal Depth

  • How far back in time a Memory area can recall
  • Memory buffer size
  • Larger values = longer temporal window
  • Affects sequence learning capacity
  • Measured in bursts

V​

Visualization Voxel Granularity

  • Controls rendering detail in Brain Monitor
  • Higher values = coarser visualization, better performance
  • Lower values = finer detail, more GPU load
  • Does not affect neural computation
  • Only affects 3D rendering

Voxel

  • A 3D pixel, the basic spatial unit in a cortical area
  • Contains one or more neurons
  • Cortical area dimensions are measured in voxels
  • Each voxel has a position (X, Y, Z) within its cortical area
  • See also: Dimensions, Neurons Per Voxel

W​

WebSocket

  • Communication protocol between Brain Visualizer and FEAGI
  • Provides real-time updates of neural activity
  • Enables live visualization and monitoring
  • Alternative to SHM (Shared Memory) mode

Z​

ZMQ (ZeroMQ)

  • Message transport layer used by FEAGI
  • Handles communication between FEAGI components
  • Brain Visualizer connects via ZMQ endpoints
  • Configured in FEAGI settings

For detailed information on specific topics, see: