Novel lists of 7 +/- 2 known items can be reliably stored in an oscillatory short-term memory network: interaction with long-term memory.

Abstract

This paper proposes a model for the short-term memory (STM) of unique fists of known items, as, for instance, a phone number. We show that the ability to accurately store such lists in STM depends strongly on interaction with the preexisting long-term memory (LTM) for individual items (e.g., digits). We have examined this interaction in computer simulations of a network based on physiologically realistic membrane conductances, synaptic plasticity processes, and brain oscillations. In the model, seven STMs can be kept active, each in a different gamma-frequency subcycle of a theta-frequency oscillation. Each STM is maintained and timed by an activity-dependent ramping process. LTM is stored by the strength of synapses in recurrent collaterals. The presence of preexisting LTM for an item greatly enhances the ability of the network to store an item in STM. Without LTM, the precise timing required to keep cells firing within a given gamma subcycle cannot be maintained and STM is gradually degraded. With LTM, timing errors can be corrected and the accuracy and order of items is maintained. This attractor property of STM storage is remarkable because it occurs even though there is no LTM that identifies which items are on the list or their order. Multiple known items can be stored in STM, even though their representation is 1Corresponding author.overlapping. However, multiple, identical memories cannot be stored in STM, consistent with the psychophysical demonstration of repetition blindness. Our results indicate that meaningful computation (memory completion) can occur in the millisecond range during an individual gamma cycle.

Cholinergic Deafferentation of the Entorhinal Cortex in Rats Impairs Encoding of Novel But Not Familiar Stimuli in a Delayed Nonmatch-to-Sample Task

“…In entorhinal cortex slices, acetylcholine causes neurons to respond to a single depolarizing event with sustained spiking activity, resulting from activation of an intrinsic cation current (Klink and Alonso, 1997a;Egorov et al, 2002). Models show how this sustained spiking activity could underlie working memory (Lisman and Idiart, 1995;Jensen and Lisman, 1996;Fransen et al, 2002;Koene et al, 2003), including spiking activity in the EC associated with performance of delayed matching tasks (Suzuki et al, 1997;Young et al, 1997;Fransen et al, 2002). Consistent with this, blockade of muscarinic cholinergic receptors impairs delayed match-to-sample performance (Bartus and Johnson, 1976;Penetar and McDonough, 1983).…”

“…The sustained spiking induced by acetylcholine in entorhinal cortex slices occurs despite blockade of synaptic transmission (Klink and Alonso, 1997a;Egorov et al, 2002). Models show how this allows working memory for novel input patterns (Lisman and Idiart, 1995;Jensen and Lisman, 1996;Fransen et al, 2002;Koene et al, 2003) without the dependence on modified synaptic connections used in models of prefrontal cortex (PFC) working memory for familiar stimuli (Lisman et al, 1998;Durstewitz et al, 2000). This effect of acetylcholine could provide a buffer for novel stimuli in the entorhinal cortex that facilitates long-term encoding in the hippocampus (Jensen and Lisman, 1996;Baddeley, 2000;Koene et al, 2003).…”

Temperature- and concentration-dependence of kainate-induced γ oscillation in rat hippocampal slices under submerged condition

“…Neuronal network oscillations at the gamma frequency band (γ oscillations, 30-80 Hz) generated in the cortex play an important role in learning and memory [1,2] . These oscillations provide a timing mechanism for controlling information processing [1,3] .…”

Spike-timing-dependent learning rule to encode spatiotemporal patterns in a network of spiking neurons

“…The definition of the electric currents I pyr,i (t), I int (t), and I ext,i (t) will be explained in what follows. Note that now we focus on the dynamics of a network of N pyramidal cells and omit describing the detailed dynamics of interneurons [56]. For the dynamics f (V, W 1 , .…”

“…For the sake of brevity, instead of describing the detailed dynamics of interneurons, we simply assume that IPSPs are induced in other pyramidal cells immediately after one of N pyramidal cells fires [56], that is, we assume global inhibition I int (t) of the form…”