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

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 interneurontargeting (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. S ynaptic inhibition is of paramount importance to cortical recurrent dynamics, sensory processing, and memory function. The complex inhibitory operation is likely to be accomplished by coordinated action of many subtypes of GABAergic (GABA, ␥-aminobutyric acid) interneurons present in the cortex. Recent years have witnessed a dramatic accumulation of our knowledge about these inhibitory cells, their morphology, physiology, chemical markers, synaptic connections, short-term plasticity, and molecular characteristics (1-6). On the other hand, little is known about specific computations by the diverse interneuron subtypes in animal behavior.To elucidate distinct operations performed by diverse interneurons, we have investigated a cortical microcircuit model that incorporates three interneuron subpopulations. Specifically, we report here a recurrent network model for working memory in the prefrontal cortex (PFC). PFC is a brain system critical to working memory, the ability to hold information actively in the mind for a short period of time (7,8). Understanding the cellular and circuit mechanisms of stimulus-selective persistent activity associated with working memory is a subject of intense current experimental and computational research (9, 10). More generally, persistent activity is believed to be a hallmark of strong recurrency in a cortical microcircuit, therefore modeling a working memory circuit represents a testbed for our investigation of cortical organization and functions. MethodsModel Architecture. The network model represents a local circuit of dorso-lateral prefrontal cortex in monkey. There are four cell populations: pyramidal (P) neurons and three subpopulations of inhibitory cells. Perisoma-targeting, dendrite-targeting, and interneuron-targeting interneurons are assumed to express parvalbumin (PV), calbindin (CB), and calretinin (CR) calcium-binding proteins, respectively (Fig. 1). P cells are four times more numerous than interneurons, and half of...

Monkey Prefrontal Cortical Pyramidal and Putative Interneurons Exhibit Differential Patterns of Activity Between Prosaccade and Antisaccade Tasks

“…Previous models of the interactions between pyramidal neurons and inhibitory interneurons (Compte et al, 2000;Wang et al, 2004;Fusi et al, 2007) have made basic assumptions that are in partial agreement with our data. Such models assume that the activity of inhibitory interneurons is driven by pyramidal cell input, is broadly tuned, and is not task selective.…”

“…Electrophysiological studies have exploited known differences between the duration of the extracellularly recorded action potential waveforms of inter and pyramidal neurons to separate these two classes (Mountcastle et al, 1969;Connors and Gutnick, 1990;Markram et al, 2004). In the PFC, such studies in monkeys have implicated interneurons in tuning of spatial memory fields (Wilson et al, 1994;Rao et al, 1999Rao et al, , 2000Constantinidis and Goldman-Rakic, 2002;Wang et al, 2004) and abstract numerical categories (Diester and Nieder, 2008). Such an approach has also been successful in somatosensory (Mountcastle et al, 1969;Simons, 1978;McCormick et al, 1985), motor (Merchant et al, 2008), and visual cortex (Gur et al, 1999;Mitchell et al, 2007).…”

Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala

“…The massive terminations from the amygdala in cortical layers 1 and 2 intermingled with the distinct neurochemical class of calbindin positive inhibitory neurons, whose activity has been associated with focusing attention on relevant features and suppressing distractors (Wang et al, 2004). This widespread pathway from the amygdala to prefrontal cortices may have a prominent role in focusing attention on motivationally relevant stimuli, consistent with the role of the amygdala in emotional alertness and vigilance [reviewed in (Gallagher and Holland, 1994;LeDoux, 2000;Davis and Whalen, 2001;Zald, 2003)].…”

Computational modeling and exploration of contour integration for visual saliency

“…Further, they have been found to modulate pyramidal neuronal activity directly (Gao and Goldman-Rakic 2003), which are the type of neurons we have constructed our corresponding group from. A gradient-based suppression could be attained by having a second slow interneuron inhibit the first interneuron, this may be plausible since interneuron to interneuron connections are well known (Wang et al 2004). If the activity of the first interneuron levels off, the second interneuron will catch up and suppress the first completely.…”