Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory - PubMed (original) (raw)

Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory

X-J Wang et al. Proc Natl Acad Sci U S A. 2004.

Abstract

A conspicuous feature of cortical organization is the wide diversity of inhibitory interneurons; their differential computational functions remain unclear. Here we propose a local cortical circuit in which three major subtypes of interneurons play distinct roles. In a model designed for spatial working memory, stimulus tuning of persistent activity arises from the concerted action of widespread inhibition mediated by perisoma-targeting (parvalbumin-containing) interneurons and localized disinhibition of pyramidal cells via interneuron-targeting (calretinin-containing) interneurons. Moreover, resistance against distracting stimuli (a fundamental property of working memory) is dynamically controlled by dendrite-targeting (calbindin-containing) interneurons. The experimental observation of inverted tuning curves of monkey prefrontal neurons recorded during working memory supports a key model prediction. This work suggests a framework for understanding the division of labor and cooperation among different inhibitory cell types in a recurrent cortical circuit.

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Figures

Fig. 1.

Fig. 1.

Schematic architecture of the biophysically based cortical network model. Pyramidal (P) neurons are arranged according to their preferred cues (0–360°). There are localized recurrent excitatory connections and broad inhibitory projections from perisoma-targeting (PV) fast-spiking neurons to P cells. Within a column, CB interneurons target the dendrites of P neurons, whereas CR interneurons preferentially project to CB cells. Excitation of a group of P cells locally recruits CR neurons, which sends enhanced inhibition to CB neurons, leading to dendritic disinhibition of the same P cells. STC, perisoma-targeting cell (PV); DTC, peridendrite-targeting cell (CB); ITC, interneuron-targeting cell (CR).

Fig. 3.

Fig. 3.

Comparison between the model and recorded PFC neuronal tuning curves. (a) Rastergrams for the P and the three (PV, CB, and CR) inhibitory neuron populations during the cue and delay periods. Instantaneous firing rates are color-coded. (b) Observed neuronal tuning curves (solid lines) during the delay period in the model simulations. Eight different cue positions are used. Dashed lines, spontaneous firing rate during the resting state. Parameter values that differ from the reference parameter set are formula image, σE→PV = 162°, and formula image. (c) Three kinds of recorded tuning curves in dorsolateral PFC during an oculomotor delayed response task, with the same conventions as in b. Solid line, the best Gaussian fit; dotted line, average firing rate during the last second of fixation. Note that the fast-spiking putative PV cell (Center) has a higher spontaneous firing rate and wider tuning than the regular-spiking putative P cell (Left), similar to what is found in the network simulations (b). An example of the inverted tuning curve is shown (Right). (Left and Center) Based on data from ref. .

Fig. 2.

Fig. 2.

Working memory behavior of the biophysically based network model. (a) Single-cell firing patterns: distinct response to an injected current pulse for each of the four neuron types, in agreement with physiological data. PV neurons are fast-spiking, CB interneurons show spike-frequency adaptation, and CR interneurons display irregular firing patterns. (b) Network simulation of the visuospatial working memory task. (Upper) Rastergram for the P cell population. A tick corresponds to an action potential from a P cell indexed by its preferred cue (0–360°) (along the y axis) at time (along the x axis). C, cue; D, delay period; R, response. A transient cue stimulus (0.5 μ_A_/cm2, 250 ms) induces a spatially localized persistent activity pattern during the delay period. At the end of the trial, the network is switched back to the resting state, and the memory is erased by a transient nonspecific current injection to neurons. (Lower) Sample voltage traces from three P neurons.

Fig. 4.

Fig. 4.

Inverted tuning of monkey prefrontal neurons recorded during spatial working memory. (a) An example of a neuron (same as in Fig. 3_c_) with inverted tuning during the delay period. Rasters represent responses for the eight cue locations, arranged to indicate the location of the corresponding cue. The polar plot in the center depicts the average delay period firing rate for each location; the dotted circle represents the average firing rate during the last second of fixation. (b) Population poststimulus time histogram, averaging responses from 24 of 526 (4.5%) neurons with inverted tuning curves. (Left) Responses for the location with the lowest (most-inhibited) delay period activity for each neuron. (Right) Responses for the location with the highest delay-period activity. (c) Spike-width distribution of neurons with inverted tuning curves during the delay period. The solid line represents the average spike width; dotted lines represent the average spike widths of the fast- and regular-spiking neuron distributions in our database.

Fig. 5.

Fig. 5.

Mexican-hat-type connectivity depends on dendritic disinhibition of P cells. (a) Average synaptic currents of different types to P neurons in a bell-shaped persistent activity pattern. Recurrent excitation from P cells is localized; recurrent inhibition from PV neurons is maximal, whereas inhibition from CB neurons shows a dip at the center of the bump. (b) Summation of synaptic currents from P and PV cells is almost flat. (c) When the synaptic contribution from CB neurons is also included, the total synaptic current shows a Mexican-hat-type shape, with local excitation and lateral inhibition. (d) The average membrane potential of a conductance-based P cell increases with its firing rate. Therefore, the driving force (_V_P – _E_inh) of the inhibitory synaptic current mediated by PV cells and the current itself (as shown in a) is about twice as large at the peak of the bump (where neurons fire at ≈30 Hz) than on the sides (where neurons are inactive).

Fig. 6.

Fig. 6.

Robustness against distracting stimuli is enhanced by an increased ratio of the dendritic/somatic inhibition. (a and b) Simulation protocol. A transient cue (0.8 μ_A_/cm2, 250 ms) elicits a spatially localized persistent activity pattern, which is resistant (a) to a weak distractor (1.125 μ_A_/cm2, 250 ms) but not (b) when the distractor (2.25 μ_A_/cm2), is stronger than a distraction threshold. _I_CB/(_I_CB + _I_PV) is 8%. (c) Increased resistance against distractors with a larger dendritic/somatic inhibition ratio (_I_CB/(I_CB + I_PV)). (d) Input–output relation for an isolated P neuron, in response to current inputs to distal dendrite and in the presence of dendritic inhibition mediated by CB interneurons. The amount of inhibition from CB neurons was estimated from the network simulation, when the remembered stimulus is opposite from the preferred cue of the cell, either for the resting state (upper curve) (–0.529μ_A/cm2 to both dendritic compartments, d1 and d2) or the delay period (lower curve) (–0.845 μ_A/cm2). Two examples with the same input current intensity but two different levels of dendritic inhibition are shown in e and f. The P cell's responsiveness is greatly reduced during the delay period because of enhanced dendritic inhibition, which provides a mechanism for filtering out distractor stimuli.

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