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Investigating habits: strategies, technologies and models.

Smith KS, Graybiel AM - Front Behav Neurosci (2014)

Bottom Line: Here we discuss ideas emerging from such approaches.The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models.We explore these new clues as opportunities to refine an understanding of habits.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychological and Brain Sciences, Dartmouth College Hanover, NH, USA.

ABSTRACT
Understanding habits at a biological level requires a combination of behavioral observations and measures of ongoing neural activity. Theoretical frameworks as well as definitions of habitual behaviors emerging from classic behavioral research have been enriched by new approaches taking account of the identification of brain regions and circuits related to habitual behavior. Together, this combination of experimental and theoretical work has provided key insights into how brain circuits underlying action-learning and action-selection are organized, and how a balance between behavioral flexibility and fixity is achieved. New methods to monitor and manipulate neural activity in real time are allowing us to have a first look "under the hood" of a habit as it is formed and expressed. Here we discuss ideas emerging from such approaches. We pay special attention to the unexpected findings that have arisen from our own experiments suggesting that habitual behaviors likely require the simultaneous activity of multiple distinct components, or operators, seen as responsible for the contrasting dynamics of neural activity in both cortico-limbic and sensorimotor circuits recorded concurrently during different stages of habit learning. The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models. We explore these new clues as opportunities to refine an understanding of habits.

No MeSH data available.


Related in: MedlinePlus

Schematic of known habit-related mechanisms using measures of behavioral outcome-sensitivity. At left, diagram of loss-of-function results in which habits are suppressed or blocked following neural interventions. The IL cortex is viewed as necessary for habit expression due to greater outcome-sensitivity in behavior resulting from lesions, temporary pharmacologic or optogenetic inhibition, or manipulations of dopamine-containing input including intra-IL infusion of dopamine, a D1 antagonist, or a D2 agonist (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The DLS is similarly needed for habit expression, as demonstrated through lesions, chemical inhibition, molecular signaling inhibition, gene deletion, and dopaminergic denervation (Yin et al., 2004, 2006; Faure et al., 2005; Yu et al., 2009; Gourley et al., 2013;). Burst firing of dopaminergic neurons is also needed, demonstrated by NMDA-R1 receptor knockout (Wang et al., 2011). Interaction between the CeA and the DLS, through unknown anatomical routes, is required as well (Lingawi and Balleine, 2012). Although lesions confound acquisition and expression phases of habits, a role for IL in habit acquisition specifically has been shown using optogenetics (Smith and Graybiel, 2013a). At right, diagram and list of some key features of IL and DLS neural activity related to habit formation and expression as uncovered from electrical recording and fMRI approaches (Tang et al., 2007; Tricomi et al., 2009; Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). Concomitant to these dynamics are a decline in activity in areas that might oppose habits, including the PL, DMS, and OFC (Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). IL, infralimbic cortex; DLS, dorsolateral striatum; VTA, ventral tegmental area; CeA, central nucleus of the amygdala; PL, prelimbic cortex; DA, dopamine; DMS, dorsomedial striatum; OFC, orbitofrontal cortex.
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Figure 1: Schematic of known habit-related mechanisms using measures of behavioral outcome-sensitivity. At left, diagram of loss-of-function results in which habits are suppressed or blocked following neural interventions. The IL cortex is viewed as necessary for habit expression due to greater outcome-sensitivity in behavior resulting from lesions, temporary pharmacologic or optogenetic inhibition, or manipulations of dopamine-containing input including intra-IL infusion of dopamine, a D1 antagonist, or a D2 agonist (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The DLS is similarly needed for habit expression, as demonstrated through lesions, chemical inhibition, molecular signaling inhibition, gene deletion, and dopaminergic denervation (Yin et al., 2004, 2006; Faure et al., 2005; Yu et al., 2009; Gourley et al., 2013;). Burst firing of dopaminergic neurons is also needed, demonstrated by NMDA-R1 receptor knockout (Wang et al., 2011). Interaction between the CeA and the DLS, through unknown anatomical routes, is required as well (Lingawi and Balleine, 2012). Although lesions confound acquisition and expression phases of habits, a role for IL in habit acquisition specifically has been shown using optogenetics (Smith and Graybiel, 2013a). At right, diagram and list of some key features of IL and DLS neural activity related to habit formation and expression as uncovered from electrical recording and fMRI approaches (Tang et al., 2007; Tricomi et al., 2009; Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). Concomitant to these dynamics are a decline in activity in areas that might oppose habits, including the PL, DMS, and OFC (Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). IL, infralimbic cortex; DLS, dorsolateral striatum; VTA, ventral tegmental area; CeA, central nucleus of the amygdala; PL, prelimbic cortex; DA, dopamine; DMS, dorsomedial striatum; OFC, orbitofrontal cortex.

Mentions: A large number of loss-of-function neuroscience experiments supports this framework for interpreting habits as outcome-insensitive S-R near-reflexes (Figure 1). For example, normally outcome-insensitive behaviors can be rendered outcome-guided following disruption (through lesions, chemical inactivation, or gene knockout) of the sensorimotor striatum (called the dorsolateral striatum or DLS). Similar effects are found after disruption of the dopamine-containing input to the DLS from the pars compacta of the substantia nigra, after disconnection of the DLS and the central nucleus of the amygdala (indirectly connected), or after disruption of pallidum-projecting neurons in the striatum in general (Yin et al., 2004; Faure et al., 2005; Yu et al., 2009; Wang et al., 2011; Lingawi and Balleine, 2012). Disruption of the infralimbic subdivision of medial prefrontal cortex (here called the infralimbic (IL) cortex) produces similar effects (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The fact that the IL cortex is not directly connected with the DLS, along with the many other regions implicated, suggests a widespread distribution of habit-promoting regions in the brain.


Investigating habits: strategies, technologies and models.

Smith KS, Graybiel AM - Front Behav Neurosci (2014)

Schematic of known habit-related mechanisms using measures of behavioral outcome-sensitivity. At left, diagram of loss-of-function results in which habits are suppressed or blocked following neural interventions. The IL cortex is viewed as necessary for habit expression due to greater outcome-sensitivity in behavior resulting from lesions, temporary pharmacologic or optogenetic inhibition, or manipulations of dopamine-containing input including intra-IL infusion of dopamine, a D1 antagonist, or a D2 agonist (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The DLS is similarly needed for habit expression, as demonstrated through lesions, chemical inhibition, molecular signaling inhibition, gene deletion, and dopaminergic denervation (Yin et al., 2004, 2006; Faure et al., 2005; Yu et al., 2009; Gourley et al., 2013;). Burst firing of dopaminergic neurons is also needed, demonstrated by NMDA-R1 receptor knockout (Wang et al., 2011). Interaction between the CeA and the DLS, through unknown anatomical routes, is required as well (Lingawi and Balleine, 2012). Although lesions confound acquisition and expression phases of habits, a role for IL in habit acquisition specifically has been shown using optogenetics (Smith and Graybiel, 2013a). At right, diagram and list of some key features of IL and DLS neural activity related to habit formation and expression as uncovered from electrical recording and fMRI approaches (Tang et al., 2007; Tricomi et al., 2009; Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). Concomitant to these dynamics are a decline in activity in areas that might oppose habits, including the PL, DMS, and OFC (Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). IL, infralimbic cortex; DLS, dorsolateral striatum; VTA, ventral tegmental area; CeA, central nucleus of the amygdala; PL, prelimbic cortex; DA, dopamine; DMS, dorsomedial striatum; OFC, orbitofrontal cortex.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
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Figure 1: Schematic of known habit-related mechanisms using measures of behavioral outcome-sensitivity. At left, diagram of loss-of-function results in which habits are suppressed or blocked following neural interventions. The IL cortex is viewed as necessary for habit expression due to greater outcome-sensitivity in behavior resulting from lesions, temporary pharmacologic or optogenetic inhibition, or manipulations of dopamine-containing input including intra-IL infusion of dopamine, a D1 antagonist, or a D2 agonist (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The DLS is similarly needed for habit expression, as demonstrated through lesions, chemical inhibition, molecular signaling inhibition, gene deletion, and dopaminergic denervation (Yin et al., 2004, 2006; Faure et al., 2005; Yu et al., 2009; Gourley et al., 2013;). Burst firing of dopaminergic neurons is also needed, demonstrated by NMDA-R1 receptor knockout (Wang et al., 2011). Interaction between the CeA and the DLS, through unknown anatomical routes, is required as well (Lingawi and Balleine, 2012). Although lesions confound acquisition and expression phases of habits, a role for IL in habit acquisition specifically has been shown using optogenetics (Smith and Graybiel, 2013a). At right, diagram and list of some key features of IL and DLS neural activity related to habit formation and expression as uncovered from electrical recording and fMRI approaches (Tang et al., 2007; Tricomi et al., 2009; Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). Concomitant to these dynamics are a decline in activity in areas that might oppose habits, including the PL, DMS, and OFC (Thorn et al., 2010; Gremel and Costa, 2013; Smith and Graybiel, 2013a). IL, infralimbic cortex; DLS, dorsolateral striatum; VTA, ventral tegmental area; CeA, central nucleus of the amygdala; PL, prelimbic cortex; DA, dopamine; DMS, dorsomedial striatum; OFC, orbitofrontal cortex.
Mentions: A large number of loss-of-function neuroscience experiments supports this framework for interpreting habits as outcome-insensitive S-R near-reflexes (Figure 1). For example, normally outcome-insensitive behaviors can be rendered outcome-guided following disruption (through lesions, chemical inactivation, or gene knockout) of the sensorimotor striatum (called the dorsolateral striatum or DLS). Similar effects are found after disruption of the dopamine-containing input to the DLS from the pars compacta of the substantia nigra, after disconnection of the DLS and the central nucleus of the amygdala (indirectly connected), or after disruption of pallidum-projecting neurons in the striatum in general (Yin et al., 2004; Faure et al., 2005; Yu et al., 2009; Wang et al., 2011; Lingawi and Balleine, 2012). Disruption of the infralimbic subdivision of medial prefrontal cortex (here called the infralimbic (IL) cortex) produces similar effects (Coutureau and Killcross, 2003; Killcross and Coutureau, 2003; Hitchcott et al., 2007; Smith et al., 2012; Barker et al., 2013). The fact that the IL cortex is not directly connected with the DLS, along with the many other regions implicated, suggests a widespread distribution of habit-promoting regions in the brain.

Bottom Line: Here we discuss ideas emerging from such approaches.The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models.We explore these new clues as opportunities to refine an understanding of habits.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychological and Brain Sciences, Dartmouth College Hanover, NH, USA.

ABSTRACT
Understanding habits at a biological level requires a combination of behavioral observations and measures of ongoing neural activity. Theoretical frameworks as well as definitions of habitual behaviors emerging from classic behavioral research have been enriched by new approaches taking account of the identification of brain regions and circuits related to habitual behavior. Together, this combination of experimental and theoretical work has provided key insights into how brain circuits underlying action-learning and action-selection are organized, and how a balance between behavioral flexibility and fixity is achieved. New methods to monitor and manipulate neural activity in real time are allowing us to have a first look "under the hood" of a habit as it is formed and expressed. Here we discuss ideas emerging from such approaches. We pay special attention to the unexpected findings that have arisen from our own experiments suggesting that habitual behaviors likely require the simultaneous activity of multiple distinct components, or operators, seen as responsible for the contrasting dynamics of neural activity in both cortico-limbic and sensorimotor circuits recorded concurrently during different stages of habit learning. The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models. We explore these new clues as opportunities to refine an understanding of habits.

No MeSH data available.


Related in: MedlinePlus