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Improper activation of D1 and D2 receptors leads to excess noise in prefrontal cortex.

Avery MC, Krichmar JL - Front Comput Neurosci (2015)

Bottom Line: We developed a model that takes into account the known receptor distributions of D1 and D2 receptors, the changes these receptors have on neuron response properties, as well as identified circuitry involved in working memory.Our model suggests that D1 receptor under-stimulation in supragranular layers gates internal noise into the PFC leading to cognitive symptoms as has been proposed in attention disorders, while D2 over-stimulation gates noise into the PFC by over-activation of cortico-striatal projecting neurons in infragranular layers.We apply this model in the context of a memory-guided saccade paradigm and show deficits similar to those observed in schizophrenic patients.

View Article: PubMed Central - PubMed

Affiliation: Systems Neurobiology Laboratory, Salk Institute for Biological Studies San Diego, CA, USA.

ABSTRACT
The dopaminergic system has been shown to control the amount of noise in the prefrontal cortex (PFC) and likely plays an important role in working memory and the pathophysiology of schizophrenia. We developed a model that takes into account the known receptor distributions of D1 and D2 receptors, the changes these receptors have on neuron response properties, as well as identified circuitry involved in working memory. Our model suggests that D1 receptor under-stimulation in supragranular layers gates internal noise into the PFC leading to cognitive symptoms as has been proposed in attention disorders, while D2 over-stimulation gates noise into the PFC by over-activation of cortico-striatal projecting neurons in infragranular layers. We apply this model in the context of a memory-guided saccade paradigm and show deficits similar to those observed in schizophrenic patients. We also show set-shifting impairments similar to those observed in rodents with D1 and D2 receptor manipulations. We discuss how the introduction of noise through changes in D1 and D2 receptor activation may account for many of the symptoms of schizophrenia depending on where this dysfunction occurs in the PFC.

No MeSH data available.


Related in: MedlinePlus

Individual column architecture and neuromodulatory effects. (A) Within a column in the PFC, neuromodulators were modeled by changing the strength of inputs from non-preferred directions (D1 receptors) between layer 2/3 neurons in different columns and the strength layer 5 neuronal responses (D2 receptors). As in Figure 1, this architecture also shows how layer 5 neurons in each column received input from the MD/SC and output to a non-specific inhibitory group and the basal ganglia in order to clear working memory and update other columns, respectively. (B) Effects of dopamine receptor D1 on layer 3 neurons in the columns of the model. When DA is low (top), connections between columns (non-preferred excitatory inputs) are enhanced, which leads to degradation in spatial tuning. At optimal levels of DA, non-preferred inputs are blocked from other columns, which enhances spatial tuning with the working memory circuits. When DA is high, D1 weakens all inputs to neurons in layer 3 of the cortical columns. (C) This figure illustrates the effects that high D1 receptor activation has on our model. High D1 stimulation blocks all inputs to layer 3 neurons, including recurrent excitatory inputs within a column, lateral excitatory inputs from other columns, and lateral inhibitory inputs from other columns. It should be noted that, even though this is how we implemented this functionally in our model to match physiological data, the details of this mechanism have not been completely resolved experimentally. (D) Plot showing what layer 5 neuron firing rates look like when D2 receptor stimulation is low, optimal, and high during the Fixation (F), Cue (C), Delay (D), and Response (R) phases of the task. Firing rates were smoothed using a moving average.
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Figure 2: Individual column architecture and neuromodulatory effects. (A) Within a column in the PFC, neuromodulators were modeled by changing the strength of inputs from non-preferred directions (D1 receptors) between layer 2/3 neurons in different columns and the strength layer 5 neuronal responses (D2 receptors). As in Figure 1, this architecture also shows how layer 5 neurons in each column received input from the MD/SC and output to a non-specific inhibitory group and the basal ganglia in order to clear working memory and update other columns, respectively. (B) Effects of dopamine receptor D1 on layer 3 neurons in the columns of the model. When DA is low (top), connections between columns (non-preferred excitatory inputs) are enhanced, which leads to degradation in spatial tuning. At optimal levels of DA, non-preferred inputs are blocked from other columns, which enhances spatial tuning with the working memory circuits. When DA is high, D1 weakens all inputs to neurons in layer 3 of the cortical columns. (C) This figure illustrates the effects that high D1 receptor activation has on our model. High D1 stimulation blocks all inputs to layer 3 neurons, including recurrent excitatory inputs within a column, lateral excitatory inputs from other columns, and lateral inhibitory inputs from other columns. It should be noted that, even though this is how we implemented this functionally in our model to match physiological data, the details of this mechanism have not been completely resolved experimentally. (D) Plot showing what layer 5 neuron firing rates look like when D2 receptor stimulation is low, optimal, and high during the Fixation (F), Cue (C), Delay (D), and Response (R) phases of the task. Firing rates were smoothed using a moving average.

Mentions: The dlPFC portion of the model contained four, two layer cortical columns representing visuospatial working memory circuits, in which each column had a preferred saccade direction of 0, 90, 180, or 270° (Figure 1A). The two layers make up the deep supragranular (layer 3) and upper infragranular (layer 5) layers. Our current understanding of the microcircuitry of the dlPFC suggests that the supragranular layers are where working memory related activity takes place and the infragranular layers are where response-related activity takes place (Arnsten et al., 2012). The supragranular layers of each of the four columns receive visual input from four different parietal cortex (PC 7a) layers and from lateral excitatory and inhibitory connections within the PFC as shown by the purple arrows in Figure 1A (Goldman-Rakic, 1995). These neurons fire in response to the stimulus, hold delay related activity in working memory, and are modulated by D1 receptors (Figures 2A, 3). Each supragranular layer in a column is also involved in biasing motor outputs through projections to four motor (MOT) areas, which accumulate evidence in order to make a saccade direction decision (Schall et al., 2011). Lateral inhibition between MOT neurons was added to promote competition.


Improper activation of D1 and D2 receptors leads to excess noise in prefrontal cortex.

Avery MC, Krichmar JL - Front Comput Neurosci (2015)

Individual column architecture and neuromodulatory effects. (A) Within a column in the PFC, neuromodulators were modeled by changing the strength of inputs from non-preferred directions (D1 receptors) between layer 2/3 neurons in different columns and the strength layer 5 neuronal responses (D2 receptors). As in Figure 1, this architecture also shows how layer 5 neurons in each column received input from the MD/SC and output to a non-specific inhibitory group and the basal ganglia in order to clear working memory and update other columns, respectively. (B) Effects of dopamine receptor D1 on layer 3 neurons in the columns of the model. When DA is low (top), connections between columns (non-preferred excitatory inputs) are enhanced, which leads to degradation in spatial tuning. At optimal levels of DA, non-preferred inputs are blocked from other columns, which enhances spatial tuning with the working memory circuits. When DA is high, D1 weakens all inputs to neurons in layer 3 of the cortical columns. (C) This figure illustrates the effects that high D1 receptor activation has on our model. High D1 stimulation blocks all inputs to layer 3 neurons, including recurrent excitatory inputs within a column, lateral excitatory inputs from other columns, and lateral inhibitory inputs from other columns. It should be noted that, even though this is how we implemented this functionally in our model to match physiological data, the details of this mechanism have not been completely resolved experimentally. (D) Plot showing what layer 5 neuron firing rates look like when D2 receptor stimulation is low, optimal, and high during the Fixation (F), Cue (C), Delay (D), and Response (R) phases of the task. Firing rates were smoothed using a moving average.
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Figure 2: Individual column architecture and neuromodulatory effects. (A) Within a column in the PFC, neuromodulators were modeled by changing the strength of inputs from non-preferred directions (D1 receptors) between layer 2/3 neurons in different columns and the strength layer 5 neuronal responses (D2 receptors). As in Figure 1, this architecture also shows how layer 5 neurons in each column received input from the MD/SC and output to a non-specific inhibitory group and the basal ganglia in order to clear working memory and update other columns, respectively. (B) Effects of dopamine receptor D1 on layer 3 neurons in the columns of the model. When DA is low (top), connections between columns (non-preferred excitatory inputs) are enhanced, which leads to degradation in spatial tuning. At optimal levels of DA, non-preferred inputs are blocked from other columns, which enhances spatial tuning with the working memory circuits. When DA is high, D1 weakens all inputs to neurons in layer 3 of the cortical columns. (C) This figure illustrates the effects that high D1 receptor activation has on our model. High D1 stimulation blocks all inputs to layer 3 neurons, including recurrent excitatory inputs within a column, lateral excitatory inputs from other columns, and lateral inhibitory inputs from other columns. It should be noted that, even though this is how we implemented this functionally in our model to match physiological data, the details of this mechanism have not been completely resolved experimentally. (D) Plot showing what layer 5 neuron firing rates look like when D2 receptor stimulation is low, optimal, and high during the Fixation (F), Cue (C), Delay (D), and Response (R) phases of the task. Firing rates were smoothed using a moving average.
Mentions: The dlPFC portion of the model contained four, two layer cortical columns representing visuospatial working memory circuits, in which each column had a preferred saccade direction of 0, 90, 180, or 270° (Figure 1A). The two layers make up the deep supragranular (layer 3) and upper infragranular (layer 5) layers. Our current understanding of the microcircuitry of the dlPFC suggests that the supragranular layers are where working memory related activity takes place and the infragranular layers are where response-related activity takes place (Arnsten et al., 2012). The supragranular layers of each of the four columns receive visual input from four different parietal cortex (PC 7a) layers and from lateral excitatory and inhibitory connections within the PFC as shown by the purple arrows in Figure 1A (Goldman-Rakic, 1995). These neurons fire in response to the stimulus, hold delay related activity in working memory, and are modulated by D1 receptors (Figures 2A, 3). Each supragranular layer in a column is also involved in biasing motor outputs through projections to four motor (MOT) areas, which accumulate evidence in order to make a saccade direction decision (Schall et al., 2011). Lateral inhibition between MOT neurons was added to promote competition.

Bottom Line: We developed a model that takes into account the known receptor distributions of D1 and D2 receptors, the changes these receptors have on neuron response properties, as well as identified circuitry involved in working memory.Our model suggests that D1 receptor under-stimulation in supragranular layers gates internal noise into the PFC leading to cognitive symptoms as has been proposed in attention disorders, while D2 over-stimulation gates noise into the PFC by over-activation of cortico-striatal projecting neurons in infragranular layers.We apply this model in the context of a memory-guided saccade paradigm and show deficits similar to those observed in schizophrenic patients.

View Article: PubMed Central - PubMed

Affiliation: Systems Neurobiology Laboratory, Salk Institute for Biological Studies San Diego, CA, USA.

ABSTRACT
The dopaminergic system has been shown to control the amount of noise in the prefrontal cortex (PFC) and likely plays an important role in working memory and the pathophysiology of schizophrenia. We developed a model that takes into account the known receptor distributions of D1 and D2 receptors, the changes these receptors have on neuron response properties, as well as identified circuitry involved in working memory. Our model suggests that D1 receptor under-stimulation in supragranular layers gates internal noise into the PFC leading to cognitive symptoms as has been proposed in attention disorders, while D2 over-stimulation gates noise into the PFC by over-activation of cortico-striatal projecting neurons in infragranular layers. We apply this model in the context of a memory-guided saccade paradigm and show deficits similar to those observed in schizophrenic patients. We also show set-shifting impairments similar to those observed in rodents with D1 and D2 receptor manipulations. We discuss how the introduction of noise through changes in D1 and D2 receptor activation may account for many of the symptoms of schizophrenia depending on where this dysfunction occurs in the PFC.

No MeSH data available.


Related in: MedlinePlus