Title: Hippocampal and cortico-striatal contributions to spatial learning: early versus late Morris water maze learning
Other Titles: Hippocampale en cortico-striatale bijdragen aan ruimtelijk leren: vroeg versus laat Morris water maze leren
Authors: Laeremans, Annelies
Issue Date: 28-Jun-2012
Abstract: Normal 0 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;}<span style="font-family:"Times New Roman";font-weight:normal">The ability to learn new skills or habitsas a result of practice is one of the most distinguished features of biologicalsystems. Neuroplastic processes and changes in synaptic connections arephenomena at the systems and molecular neuroscience level enabling differentforms of learning and memory. In this dissertation we aimed to elucidate someof these neuroplastic mechanisms associated with early and late complex watermaze learning. The main goal was to visualize possible network activity betweendifferent brain regions for which independent involvement in water mazelearning was already established a priori.<span style="font-family:"Times New Roman";font-weight:normal">The major part of this study comprisedthe quantitative analysis of immediate early gene expression levels in thehippocampus (CA1 and CA3), striatum (DMS, sDMS and DLS) and prefrontal cortex(aCC, PL and IL) by means of in situhybridization experiments for the molecular activity marker zif268 and the molecular plasticitymarkers Homer1a and arc. Through these analyses we soughtto identify learning phase-related differences in the contributions of thesedistinct subregions of the brain. Furthermore, this IEG imaging approach alsoallowed us to characterize the nature of interactions between subregions in theintact mouse brain. With respect to the hippocampus, surface biotinylationassays in acute brain slices (ASBA) combined with Western analysis enabled usto measure modifications in the membrane expression of specific cell surfaceproteins.<span style="font-size:13.0pt;line-height:150%;font-family:"Times New Roman";mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language:AR-SA">In the corticostriatal system, we have found synergisticactivity dynamics (zif268 expression)over the course of learning in the (superior) dorsomedial striatum, theprelimbic and the anterior cingulate cortex, with these regions being mostactive during goal-directed early learning. Also, parallel dynamics in activitywere found in the dorsolateral striatum and infralimbic cortex, with bothregions mediating habitual water maze performance. During early task<br>acquisition, these two corticostriatal circuits were shown to develop simultaneously.However, arc expression levelssuggested that the goal-directed corticostriatal loop controlled behavioraloutput during early spatial learning. Upon overtraining, we demonstrated ashift in behavioral control to the habitual corticostriatal circuit. Withrespect to the hippocampal system, we demonstrated a continuous activation (zif268 expression) during water mazeperformance in CA1, not CA3. However, task-specific engagement in CA1 was only foundduring the goal-directed early learning phase. Since ASBA analysis onlydetected modifications of the NMDAR subunit composition during early learning,we suggest that the hippocampus indeed mediates goal-directed early learning incorrespondence with the corticostriatal circuit comprising the (superior)dorsomedial striatum, the prelimbic and the anterior cingulate cortex.
Table of Contents: Table of Contents i
List of Abbreviations 1
Aim of the study 6
Chapter 1: Learning and memory 10
1. Different learning and memory systems dependent on the type of processed information 10
2. Learning and memory at cellular level 12
2.1. Activity-dependent synaptic plasticity 12
2.2. The molecular and cellular mechanisms substantiating synaptic plasticity and memory consolidation 13
2.2.1. NMDAR-dependent LTP 14
2.2.2. NMDAR-dependent LTD 19
3. Learning-related brain structures/systems involved in the Morris water maze task 21
3.1. The hippocampal system 23
3.1.1 Anatomical structure of the hippocampal system 23
3.1.2 Information transduction pathways of the hippocampal system 23
3.1.3 Memory processing functions of the hippocampal system 25
3.2. The cortico-striatal system 32
3.2.1 Anatomical structure of the basal ganglia 32
3.2.2 Information transduction pathways of the basal ganglia 33
3.2.3 Memory processing functions of the cortico-striatal system 35
Chapter 2: Materials and methods 41
1. Animals 41
2. Behavioral training procedures 41
2.1. Morris water maze training 41
2.2. Experimental conditions 42
2.3. Statistics 44
3. Semi-quantitative in situ hybridization (ISH) to determine zif268, arc, H1a and Pcp4 expression levels 45
3.1. Subjects 45
3.2. Tissue preparation 45
3.3. In situ hybridization 45
3.4. Regions of interest (ROIs) 46
3.4.1. The hippocampus (Learning-related changes in the hippocampus are discussed in chapter 3 and 4) 46
3.4.2. The striatum and the anterior cingulate cortex (aCC) (Learning-related changes in the striatum and the aCC are discussed in chapter 4) 48
3.4.3. The medial prefrontal cortex (Learning-related changes in the medial prefrontal cortex are discussed in chapter 4) 49
3.5. Quantitative analysis 49
3.6. Statistics 50
3.7. Corticosterone levels 51
4. Acute slice biotinylation assay (ASBA) to determine the optical density of glutamate receptor subunits in the hippocampal plasma membrane 52
4.1. Subjects 52
4.2. Tissue preparation 52
4.3. Acute slice biotinylation assay 53
4.4. Isolation of membrane proteins 53
4.5. Western Blotting 54
4.6. Quantitative analysis 55
4.7. Statistics 55
Chapter 3: Hippocampal contributions to spatial learning: early versus late Morris water maze learning 56
1. Introduction 56
2. Materials and methods 58
3. Results 59
3.1. Behavioral learning profile 59
3.2. Initial acquisition but not consolidation of spatial memory is reflected in changed hippocampal IEG expression patterns 60
3.2.1 Zif268 expression 60
3.2.2 Homer1a (H1a) expression 61
3.3. Correlation between IEG expression and performance 62
3.4. Glutamate receptor subunit expression on the plasma membrane of hippocampal cells 63
4. Discussion 66
4.1. Differential zif268 and H1a expression patterns in CA1 and CA3 over the course of MWM training 66
4.2. No changes in the total number of AMPARs inserted into the plasma membrane of hippocampal cells upon MWM training 69
4.3. A constant number of NMDARs but an altered NMDAR subunit composition accompanies early spatial learning in the MWM 69
Chapter 4: Cortico-striatal contributions to spatial learning: early versus late Morris water maze learning 72
1. Introduction 72
2. Materials and methods 75
3. Results 76
3.1. Behavioral learning profile 76
3.2. Concomitant learning phase-specific changes of IEG expression in distinct cortico-striatal circuits enable mastering of MWM performance 77
3.2.1 The (superior) dorsomedial and dorsolateral striatum: goal-directed versus habitual learning 78
3.2.2 Interaction between the anterior cingulate and prelimbic prefrontal cortices and the (superior) dorsomedial striatum: goal-directed learning 84
3.2.3 Interaction between the infralimbic prefrontal cortex and the dorsolateral striatum: habitual learning 91
4. Discussion 93
4.1. The hippocampus and (superior) dorsomedial striatum versus the dorsolateral striatum: goal-directed versus habitual learning 93
4.1.1. The (superior) dorsomedial striatum versus the dorsolateral striatum: goal-directed versus habitual learning 93
So what about the dorsomedial striatum? 95
This observation raised the question whether the dorsomedial and dorsolateral striatal subdivisions both contributed to the early learning phase and what the functional specificity was of each subregion? 97
If both systems develop in parallel during early learning, how are they interacting to control behavior? 99
If the less energy consuming response strategy is already operational during early learning, why is it not controlling behavior? 100
4.1.2. The hippocampus and (superior) dorsomedial striatum: goal-directed learning 101
If both the hippocampus and the dorsomedial striatum are part of the same goal-directed circuit, what are their respective functions in relation to spatial learning and how do they interact? 101
If not the acquisition of spatial information, then what is the function of the dorsomedial striatum in spatial learning? 102
4.2. Interaction between the anterior cingulate and prelimbic prefrontal cortices and the (superior) dorsomedial striatum: goal-directed learning 103
In relation to the dorsomedial striatum and hippocampus (§ 4.1.2.), what is the specific function of the prelimbic and anterior cingulate prefrontal cortical areas during goal-directed early spatial learning? What is their contribution to action-outcome contingency learning, the dominant type of information processing governed by the associative corticostriatal circuit during the early stage of task acquisition? And, what is the functional implication of the distinct hippocampal innervation? 105
If the PL is not the locus of action-outcome encoding, then what is its function in goal-directed learning? 105
How does the prelimbic cortex contribute to path planning? 107
How does this theory fit into the context of our experimental water maze setup? 108
If both strategies continuously exist in parallel, why is the anterior cingulate cortex not active anymore during late learning to guide effort-based decision making and establish a bias towards response learning? Thus, why is activation of the anterior cingulate cortex no longer required after extensive training? 109
4.3. Interaction between the infralimbic prefrontal cortex and the dorsolateral striatum: habitual learning 110
4.4. Interaction between the prelimbic and infralimbic cortex: goal-directed versus habitual learning 112
How is the infralimbic cortex enabling the habitual system to override the goal-directed system? 112
Chapter 5: General discussion and future perspectives 114
1. Concluding remarks about the differential contribution of distinct cortical and subcortical regions to Morris water maze learning: from goal-directed to habitual control 114
2. Parallel findings from within the KU Leuven consortium 117
3. What type of navigation strategy actually reflects goal-directed and habitual performance? 118
4. Are free-swimming controls a suitable control condition? Are their alternatives? 120
5. Future perspectives 121
5.1. Medial prefrontal cortex: prelimbic and infralimbic cortex 121
5.2. ASBA AMPA1 122

Summary 124

Samenvatting 126

Appendix 1 128

List of References 131

List of Publications 160
ISBN: 978-90-8649-544-3
Publication status: published
KU Leuven publication type: TH
Appears in Collections:Animal Physiology and Neurobiology Section - miscellaneous
Research Group Neuroplasticity and Neuroproteomics (-)

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