MODULATION OF ASSOCIATIVE MEMORY FUNCTION IN A BIOPHYSICAL SIMULATION OF RAT PIRIFORM CORTEX

被引:72
作者
BARKAI, E
BERGMAN, RE
HORWITZ, G
HASSELMO, ME
机构
[1] HARVARD UNIV,DEPT PSYCHOL,CAMBRIDGE,MA 02138
[2] HARVARD UNIV,PROGRAM NEUROSCI,CAMBRIDGE,MA 02138
关键词
D O I
10.1152/jn.1994.72.2.659
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
1. Associative memory function was analyzed in a realistic biophysical simulation of rat piriform (olfactory) cortex containing 240 pyramidal cells and 58 each of two types of inhibitory interneurons. Pyramidal cell simulations incorporated six different intrinsic currents and three different synaptic currents. We investigated the hypothesis that acetylcholine sets the appropriate dynamics for learning within the network, whereas removal of cholinergic modulation sets the appropriate dynamics for recall. The associative memory function of the network was tested during recall after simulation of the cholinergic suppression of intrinsic fiber synaptic transmission and the cholinergic suppression of neuronal adaptation during learning. 2. Hebbian modification of excitatory synaptic connections between pyramidal cells during learning of patterns of afferent activity allowed the model to show the basic associative memory property of completion during retail in response to degraded versions of those patterns, as evaluated by a performance measure based on normalized dot products. 3. During learning of multiple overlapping patterns of afferent activity, recall of previously learned patterns interfered with the learning of new patterns. As more patterns were stored this interference could lead to the exponential growth of a large number of excitatory synaptic connections within the network. This runaway synaptic modification during learning led to excessive excitatory activity during recall, preventing the accurate recall of individual patterns. 4. Runaway synaptic modification of excitatory intrinsic connections could be prevented by selective suppression of synaptic transmission at these synapses during learning. This allowed effective recall of single learned afferent patterns in response to degraded versions of those patterns, without interference from other learned patterns. 5. During learning, cholinergic suppression of neuronal adaptation enhanced the activity of cortical pyramidal cells in response to afferent input, compensating for decreased activity due to suppression of intrinsic fiber synaptic transmission. This modulation of adaptation led to more rapid learning of afferent input patterns, as demonstrated by higher values of the performance measure. 6. During recall, when suppression of excitatory intrinsic synaptic transmission was removed, continued cholinergic suppression of neuronal adaptation led to the spread of excessive activity. More stable activity patterns during recall could be obtained when the cholinergic suppression of neuronal adaptation was removed at the same time as the cholinergic suppression of synaptic transmission. 7. A realistic biophysical simulation of the effects of acetylcholine on synaptic transmission and neuronal adaptation in the piriform cortex shows that these effects act together to set the appropriate dynamics for learning, whereas removal of both effects sets the appropriate dynamics for recall.
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页码:659 / 677
页数:19
相关论文
共 87 条
  • [1] REALISTIC SYNAPTIC INPUTS FOR MODEL NEURAL NETWORKS
    ABBOTT, LF
    [J]. NETWORK-COMPUTATION IN NEURAL SYSTEMS, 1991, 2 (03) : 245 - 258
  • [2] ABBOTT LF, 1992, NEURLA NETWORKS BIOL
  • [3] COMPARISON OF THE EFFECTS OF SCOPOLAMINE ADMINISTERED BEFORE AND AFTER ACQUISITION IN A TEST OF VISUAL RECOGNITION MEMORY IN MONKEYS
    AIGNER, TG
    WALKER, DL
    MISHKIN, M
    [J]. BEHAVIORAL AND NEURAL BIOLOGY, 1991, 55 (01): : 61 - 67
  • [4] SIMULATION OF PALEOCORTEX PERFORMS HIERARCHICAL-CLUSTERING
    AMBROSINGERSON, J
    GRANGER, R
    LYNCH, G
    [J]. SCIENCE, 1990, 247 (4948) : 1344 - 1348
  • [5] Attractor neural networks with biological probe records
    Amit, Daniel J.
    Evans, M. R.
    Abeles, M.
    [J]. NETWORK-COMPUTATION IN NEURAL SYSTEMS, 1990, 1 (04) : 381 - 405
  • [6] Amit DJ., 1988, MODELING BRAIN FUNCT
  • [7] ANDERSON J A, 1972, Mathematical Biosciences, V14, P197, DOI 10.1016/0025-5564(72)90075-2
  • [8] COGNITIVE AND PSYCHOLOGICAL COMPUTATION WITH NEURAL MODELS
    ANDERSON, JA
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1983, 13 (05): : 799 - 815
  • [9] The Topographical and Neuroanatomical Distribution of Neurofibrillary Tangles and Neuritic Plaques in the Cerebral Cortex of Patients with Alzheimer's Disease
    Arnold, Steven E.
    Hyman, Bradley T.
    Flory, Jill
    Damasio, Antonio R.
    Van Hoesen, Gary W.
    [J]. CEREBRAL CORTEX, 1991, 1 (01) : 103 - 116
  • [10] MODULATION OF THE INPUT/OUTPUT FUNCTION OF RAT PIRIFORM CORTEX PYRAMIDAL CELLS
    BARKAI, E
    HASSELMO, ME
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 1994, 72 (02) : 644 - 658