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Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence.

Kerr RR, Grayden DB, Thomas DA, Gilson M, Burkitt AN - Front Neural Circuits (2014)

Bottom Line: We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units.With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation.Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

View Article: PubMed Central - PubMed

Affiliation: NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, The University of Melbourne Melbourne, VIC, Australia ; Centre for Neural Engineering, The University of Melbourne Melbourne, VIC, Australia ; NICTA, Victoria Research Lab, The University of Melbourne Melbourne, VIC, Australia.

ABSTRACT
The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

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Basic Logic Motifs. From top to bottom, motifs in which the output units compute the operations “X1 or X2,” “X3 and not X4,” and “X5 and X6,” respectively. Arrows correspond to feedforward (blue) and feedback (red) connections with short (dashed and shorter length) and long (solid and longer length) time lags. Arrows are also shown connecting the input units to lower-level units (not shown) and connecting the output units to higher-level units (not shown) as these motifs function as circuits in a larger network.
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Figure 3: Basic Logic Motifs. From top to bottom, motifs in which the output units compute the operations “X1 or X2,” “X3 and not X4,” and “X5 and X6,” respectively. Arrows correspond to feedforward (blue) and feedback (red) connections with short (dashed and shorter length) and long (solid and longer length) time lags. Arrows are also shown connecting the input units to lower-level units (not shown) and connecting the output units to higher-level units (not shown) as these motifs function as circuits in a larger network.

Mentions: We consider examples of simple subnetworks, or motifs, in order to illustrate the functional roles of different types of connections. Shown in Figure 3, these motifs perform simple logic operations when initiated by external feedback. The output units, Y1, Y2, and Y3, send feedback activity to input units, X1, X2, X3, X4, X5, and X6, and become activated if they receive feedforward activity in return. Y1 (“X1 or X2”) becomes activated if either X1 or X2 receives coherent, feedforward input, which, because of the long time lag of the connections, must be out-of-phase with the activity of Y1 so that they can provide returning feedforward activity that is coherent with Y1's activity. Y2 (“X3 and not X4”) becomes activated only if X3 receives coherent, feedforward input and X4 (which makes a short feedforward connection onto Y2) does not, as activity from this unit would arrive out-of-phase with Y2's activity. In the last motif, the unit in the intermediate layer performs the same operation (“AND NOT”) on its inputs as Y2. Y3 (“X5 and X6”), in turn, also performs the same (“AND NOT”) operation as Y2 except that the intermediate unit is initiated in phase with Y3 and so the time lags of the connections between them are reversed.


Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence.

Kerr RR, Grayden DB, Thomas DA, Gilson M, Burkitt AN - Front Neural Circuits (2014)

Basic Logic Motifs. From top to bottom, motifs in which the output units compute the operations “X1 or X2,” “X3 and not X4,” and “X5 and X6,” respectively. Arrows correspond to feedforward (blue) and feedback (red) connections with short (dashed and shorter length) and long (solid and longer length) time lags. Arrows are also shown connecting the input units to lower-level units (not shown) and connecting the output units to higher-level units (not shown) as these motifs function as circuits in a larger network.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126059&req=5

Figure 3: Basic Logic Motifs. From top to bottom, motifs in which the output units compute the operations “X1 or X2,” “X3 and not X4,” and “X5 and X6,” respectively. Arrows correspond to feedforward (blue) and feedback (red) connections with short (dashed and shorter length) and long (solid and longer length) time lags. Arrows are also shown connecting the input units to lower-level units (not shown) and connecting the output units to higher-level units (not shown) as these motifs function as circuits in a larger network.
Mentions: We consider examples of simple subnetworks, or motifs, in order to illustrate the functional roles of different types of connections. Shown in Figure 3, these motifs perform simple logic operations when initiated by external feedback. The output units, Y1, Y2, and Y3, send feedback activity to input units, X1, X2, X3, X4, X5, and X6, and become activated if they receive feedforward activity in return. Y1 (“X1 or X2”) becomes activated if either X1 or X2 receives coherent, feedforward input, which, because of the long time lag of the connections, must be out-of-phase with the activity of Y1 so that they can provide returning feedforward activity that is coherent with Y1's activity. Y2 (“X3 and not X4”) becomes activated only if X3 receives coherent, feedforward input and X4 (which makes a short feedforward connection onto Y2) does not, as activity from this unit would arrive out-of-phase with Y2's activity. In the last motif, the unit in the intermediate layer performs the same operation (“AND NOT”) on its inputs as Y2. Y3 (“X5 and X6”), in turn, also performs the same (“AND NOT”) operation as Y2 except that the intermediate unit is initiated in phase with Y3 and so the time lags of the connections between them are reversed.

Bottom Line: We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units.With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation.Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

View Article: PubMed Central - PubMed

Affiliation: NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, The University of Melbourne Melbourne, VIC, Australia ; Centre for Neural Engineering, The University of Melbourne Melbourne, VIC, Australia ; NICTA, Victoria Research Lab, The University of Melbourne Melbourne, VIC, Australia.

ABSTRACT
The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

Show MeSH