Learning environmental clues in the KIV model of the cortico-hippocampal formation

Robert Kozma, Walter J. Freeman, Derek Wong, P. Érdi

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Previous studies on the KIV model outlined a general architecture of modeling sensory-perceptual-intentional action cycle in the primordial vertebrate forebrain using nonlinear dynamical principles. KIV consists of three KIII units representing aperiodic/chaotic dynamics in sensory cortex, hippocampal formation, and midline forebrain, respectively. The sensory cortex has demonstrated excellent performance as a pattern recognition and classification device. In this work, the behavior of the hippocampal formation is studied as part of the KIV system. We elaborate a reinforcement algorithm to learn goal-oriented behavior based on global orientation beacons, biased by local sensory information provided by visual or infra-red sensors. We illustrate the operation of the KIV model using the multiple T-maze navigation problem.

Original languageEnglish
Pages (from-to)721-728
Number of pages8
JournalNeurocomputing
Volume58-60
DOIs
Publication statusPublished - Jun 2004

Fingerprint

Prosencephalon
Pattern recognition
Hippocampus
Learning
Vertebrates
Reinforcement
Navigation
Infrared radiation
Equipment and Supplies
Sensors
Recognition (Psychology)
Reinforcement (Psychology)

Keywords

  • Cortex
  • Hippocampal formation
  • KIII and KIV models
  • Spatio-temporal neurodynamics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Learning environmental clues in the KIV model of the cortico-hippocampal formation. / Kozma, Robert; Freeman, Walter J.; Wong, Derek; Érdi, P.

In: Neurocomputing, Vol. 58-60, 06.2004, p. 721-728.

Research output: Contribution to journalArticle

Kozma, Robert ; Freeman, Walter J. ; Wong, Derek ; Érdi, P. / Learning environmental clues in the KIV model of the cortico-hippocampal formation. In: Neurocomputing. 2004 ; Vol. 58-60. pp. 721-728.
@article{bada7b88eea34a8ea9982cf56c00edb5,
title = "Learning environmental clues in the KIV model of the cortico-hippocampal formation",
abstract = "Previous studies on the KIV model outlined a general architecture of modeling sensory-perceptual-intentional action cycle in the primordial vertebrate forebrain using nonlinear dynamical principles. KIV consists of three KIII units representing aperiodic/chaotic dynamics in sensory cortex, hippocampal formation, and midline forebrain, respectively. The sensory cortex has demonstrated excellent performance as a pattern recognition and classification device. In this work, the behavior of the hippocampal formation is studied as part of the KIV system. We elaborate a reinforcement algorithm to learn goal-oriented behavior based on global orientation beacons, biased by local sensory information provided by visual or infra-red sensors. We illustrate the operation of the KIV model using the multiple T-maze navigation problem.",
keywords = "Cortex, Hippocampal formation, KIII and KIV models, Spatio-temporal neurodynamics",
author = "Robert Kozma and Freeman, {Walter J.} and Derek Wong and P. {\'E}rdi",
year = "2004",
month = "6",
doi = "10.1016/j.neucom.2004.01.119",
language = "English",
volume = "58-60",
pages = "721--728",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",

}

TY - JOUR

T1 - Learning environmental clues in the KIV model of the cortico-hippocampal formation

AU - Kozma, Robert

AU - Freeman, Walter J.

AU - Wong, Derek

AU - Érdi, P.

PY - 2004/6

Y1 - 2004/6

N2 - Previous studies on the KIV model outlined a general architecture of modeling sensory-perceptual-intentional action cycle in the primordial vertebrate forebrain using nonlinear dynamical principles. KIV consists of three KIII units representing aperiodic/chaotic dynamics in sensory cortex, hippocampal formation, and midline forebrain, respectively. The sensory cortex has demonstrated excellent performance as a pattern recognition and classification device. In this work, the behavior of the hippocampal formation is studied as part of the KIV system. We elaborate a reinforcement algorithm to learn goal-oriented behavior based on global orientation beacons, biased by local sensory information provided by visual or infra-red sensors. We illustrate the operation of the KIV model using the multiple T-maze navigation problem.

AB - Previous studies on the KIV model outlined a general architecture of modeling sensory-perceptual-intentional action cycle in the primordial vertebrate forebrain using nonlinear dynamical principles. KIV consists of three KIII units representing aperiodic/chaotic dynamics in sensory cortex, hippocampal formation, and midline forebrain, respectively. The sensory cortex has demonstrated excellent performance as a pattern recognition and classification device. In this work, the behavior of the hippocampal formation is studied as part of the KIV system. We elaborate a reinforcement algorithm to learn goal-oriented behavior based on global orientation beacons, biased by local sensory information provided by visual or infra-red sensors. We illustrate the operation of the KIV model using the multiple T-maze navigation problem.

KW - Cortex

KW - Hippocampal formation

KW - KIII and KIV models

KW - Spatio-temporal neurodynamics

UR - http://www.scopus.com/inward/record.url?scp=2542421110&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=2542421110&partnerID=8YFLogxK

U2 - 10.1016/j.neucom.2004.01.119

DO - 10.1016/j.neucom.2004.01.119

M3 - Article

VL - 58-60

SP - 721

EP - 728

JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

ER -