An Integrate-and-fire Model of Prefrontal Cortex Neuronal Activity during Performance of Goal-directed Decision Making

Koene, Randal A.; Hasselmo, Michael E.

doi:10.1093/cercor/bhi072

Cited by 39 publications

(38 citation statements)

References 95 publications

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“…The vector a represents units in layer IV of cortical structures, which receive input from thalamic nuclei conveying information about sensory stimuli or proprioceptive feedback about an action, and also receive feedforward connections from cortical areas lower in the sensory hierarchy (Barbas and Pandya, 1989;Felleman and Van Essen, 1991;Scannell et al, 1995). The representations in this model are consistent with data showing that prefrontal cortex neurons respond to a range of behaviorally relevant sensory stimuli, motor outputs and reward (Schoenbaum and Eichenbaum, 1995;Jung et al, 1998;Schoenbaum et al, 1998;Schultz et al, 2000;Wallis et al, 2001;Mulder et al, 2003;Koene and Hasselmo, 2005).…”

Section: Overview Of Network Functionsupporting

confidence: 71%

Section: Equations Of the Modelmentioning

confidence: 99%

“…The threshold is set to 0.7 in the simulations presented here. Because this is a binary threshold function and activity spreads at discrete time steps through the network, this network can be replicated relatively easily with integrate-and-fire neurons, but runs much more slowly and cannot be described with simple equations (Koene and Hasselmo, 2005).Reverse spread from the input g i to the output g o within a minicolumn involves the matrix W ig , which has modifiable all to all connections between g i and g o in each minicolumn. To prevent excessive spread of reverse activity, each minicolumn has inhibitory interneurons responding to the sum of excitatory activity in the input g i which acts on the output g o .…”

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confidence: 99%

“…The population g i in the previous state minicolumn receives subthreshold input from the buffered representation of a(t e -1), and receives subthreshold input from g o across reverse connections W g , which start out with weak initial strength. These two subthreshold inputs cause activity in a single unit in g i which receives both inputs.(E2)In a network with higher time resolution (Koene and Hasselmo, 2005), spiking in g i would follow spiking in g o by a short delay, allowing spike timing dependent Hebbian synaptic plasticity to modify the connections W g according to:(E3)In these simulations, the strength of existing connections started at 0.5 and was limited to a maximum of 1.0, which was reached in a single step when both presynaptic and postsynaptic activity were present. The connectivity of W g has a specific form meant to represent sparse connectivity between cortical columns.…”

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A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior

Hasselmo

2005

Journal of Cognitive Neuroscience

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Many behavioral tasks require goal-directed actions to obtain delayed reward. The prefrontal cortex appears to mediate many aspects of goal-directed function. This paper presents a model of prefrontal cortex function emphasizing the influence of goal related activity on the choice of the next motor output. The model can be interpreted in terms of key elements of Reinforcement Learning theory. Different neocortical minicolumns represent distinct sensory input states and distinct motor output actions. The dynamics of each minicolumn include separate phases of encoding and retrieval. During encoding, strengthening of excitatory connections forms forward and reverse associations between each state, the following action, and a subsequent state, which may include reward. During retrieval, activity spreads from reward states throughout the network. The interaction of this spreading activity with a specific input state directs selection of the next appropriate action. Simulations demonstrate how these mechanisms can guide performance in a range of goal-directed tasks, and provide a functional framework for some of the neuronal responses previously observed in medial prefrontal cortex during performance of spatial memory tasks in rats.Numerous behavioral tasks involve goal-directed behavior based upon a delayed reward. For example, a rat in an instrumental task must generate lever presses to obtain food reward (Corbit and Balleine, 2003;Killcross and Coutureau, 2003;Wyble et al., 2004), and a rat in a T-maze must run down the stem of the maze to obtain food reward in one arm of the maze (Jung et al., 1998;Wood et al., 2000;Baeg et al., 2003;Ferbinteanu and Shapiro, 2003). Lesions of the prefrontal cortex cause impairments in goal-directed behavior (Fuster, 1995;Miller and Cohen, 2001;Corbit and Balleine, 2003;Killcross and Coutureau, 2003), and prefrontal units show firing dependent upon the association of cues and future responses (Miller, 2000). The model presented here addresses how goal directed behavior can be mediated by populations of neurons.An extensive theoretical framework termed Reinforcement Learning (Sutton, 1988;Sutton and Barto, 1998) describes how an agent can generate behaviors for delayed rewards in its environment. Current sensory input to the agent is represented by a "state" vector, and the output of the agent is represented by "actions" which alter the state vector (i.e., moving the agent to a different location). The selection of actions is guided by value functions (associating states with future reward) and state-action-value functions (associating actions in specific states with future reward). These functions are often learned using variants of temporal difference (TD) learning (Sutton, 1988;Sutton and Barto, 1998).Research has focused on the similarity between the error term in TD learning and the activity of dopaminergic neurons (Montague et al., 1996;Schultz et al., 1997). The basal ganglia have been proposed to provide circuitry for computation of TD learning (Houk et al., 1995). A...

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Section: Overview Of Network Functionsupporting

confidence: 71%

Section: Equations Of the Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior

Hasselmo

2005

Journal of Cognitive Neuroscience

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“…It may, as suggested by a model proposed by Mazurek et al (2003), reflect the integration of evidence from earlier stages of processing. Alternatively, it could be at the core of the goal-directed decision-making process (Koene and Hasselmo, 2005) or could represent the behavioral output of the decision in the form of a motor plan.…”

Section: Comparison Decisions and The Representation Of Behavioral mentioning

confidence: 99%

Directional Signals in the Prefrontal Cortex and in Area MT during a Working Memory for Visual Motion Task

Zaksas¹,

Pasternak²

2006

J. Neurosci.

221

194

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Neurons in the middle temporal visual area (MT) have been implicated in the perception of visual motion, whereas prefrontal cortex (PFC) neurons have been linked to temporary storage of sensory signals, attentional and executive control of behavior. Using a task that placed demands on both sets of neurons, we investigated their contribution to working memory for visual motion. Monkeys compared the direction of two moving random-dot stimuli, sample and test, separated by a brief memory delay. Neurons in both areas showed robust direction-selective activity during all phases of the task. During the sample, ϳ60% of task-related PFC neurons were direction selective, and this selectivity emerged 40 ms later than in MT. Unlike MT, the PFC responses to sample did not correlate with behavioral choices, but their selectivity was modulated by task demands and diminished on error trials. Reliable directional signals were found in both areas during the memory delay, but these signals were transient rather than sustained by neurons of either area. Responses to the test in both areas were modulated by the remembered sample direction, decreasing when the test direction matched the sample. This decrease arose in the PFC 100 ms later than in MT and was predictive of the forthcoming decision. Our data suggest that neurons in the two regions are functionally connected and make unique contributions to different task components. PFC neurons reflect task-related information about visual motion and represent decisions that may be based, in part, on the comparison in MT between the remembered sample and test.

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Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior

et al. 2005

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Both the hippocampus and the medial prefrontal cortex are essential for successful performance in learning- and memory-related tasks. Within the hippocampus the theta rhythm plays an integral role in the timing of action potentials of hippocampal neurons responding to elements of any given task. Medial prefrontal cortex (mPFC) neurons display firing rate changes to specific facets of behavioral tasks (Jung et al., 1998. Cereb Cortex 8:437--450). We recorded units in the mPFC and field potentials in the hippocampus to determine whether behaviorally correlated mPFC cells fired with phase relationships to the hippocampal theta rhythm. In two different behavioral tasks (running a linear track and foraging in two distinct environments) we found mPFC cells that alternated between theta entrained firing and nonphasic firing depending on the ongoing behavior, while other cells were modulated during all conditions in both tasks. The majority of the mPFC cells with a significant correlation of firing rate changes with behavior were entrained to hippocampal theta. Cells that fired to specific events during only one direction of running were predisposed to theta modulation only in that direction. mPFC neurons have the capability to respond to behaviorally relevant elements by dynamically alternating between hippocampal theta entrained and nonphasic firing.

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An Integrate-and-fire Model of Prefrontal Cortex Neuronal Activity during Performance of Goal-directed Decision Making

Cited by 39 publications

References 95 publications

A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior

A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior

Directional Signals in the Prefrontal Cortex and in Area MT during a Working Memory for Visual Motion Task

Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior

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