investigating the roles of parvalbumin and cholecystokinin … · 2018. 11. 19. · assisted in the...

Investigating the Roles of Parvalbumin and Cholecystokinin

Interneurons of the Ventral Hippocampus and Medial Prefrontal

Cortex in Schizophrenia-Related Behaviours

by

Robin Nguyen

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Department of Psychology

University of Toronto

© Copyright by Robin Nguyen 2018

ii

Investigating the Roles of Parvalbumin and Cholecystokinin

Interneurons of the Ventral Hippocampus and Medial Prefrontal Cortex

in Schizophrenia-Related Behaviours

Robin Nguyen

Doctor of Philosophy

Department of Psychology

University of Toronto

2018

Abstract

Schizophrenia is characterized by neuropathological changes in inhibitory GABA interneurons in

the hippocampus (HPC) and medial prefrontal cortex (mPFC) (Benes and Berretta, 2001; Lisman

et al., 2008; Lewis et al., 2012). A diverse population of GABA interneurons participates in

organizing network activity underlying behaviours mediated by the HPC and mPFC

(Klausberger and Somogyi, 2008; Tremblay et al., 2016). Two major classes of perisomatic

interneurons disrupted in schizophrenia, express parvalbumin (PV) or cholecystokinin (CCK)

and differ in their electrophysiological properties, molecular expression, anatomical distribution,

and connectivity (Armstrong and Soltesz, 2012). This raises the important question of whether

PV and CCK interneurons play distinct roles in the sensorimotor and mnemonic functions of the

HPC and mPFC (Freund and Katona, 2007). Using intersectional genetic labeling in combination

with chemogenetics and optogenetics, we evaluated how PV and CCK interneuron dysfunction

in the ventral HPC and mPFC contribute to behavioural abnormalities associated with

schizophrenia. In the ventral HPC, PV and GAD65 interneurons were both involved in working

memory while contributing to different forms of sensorimotor processing. Furthermore, the

CCK-expressing subset of GAD65 interneurons in the vCA1/Sub specifically contributed to

iii

learning context-reward associations, potentially through their interaction with NAc-projecting

neurons. In the mPFC, PV and CCK interneurons played important roles during working

memory depending on task phase. Functional differences in the mPFC were mirrored by

anatomical differences in their laminar distribution, and prominent monosynaptic connections

from CCK interneurons onto PV interneurons. These findings reveal the unique behavioural

functions of PV and CCK interneurons, and elucidate the contribution of their impairment to

specific deficits in schizophrenia.

iv

Acknowledgments

I am fortunate to have had exceptional mentors who have inspired me throughout my training in

science. I would like to express my sincerest gratitude to my supervisor, Dr. Junchul Kim. Thank

you for supporting me at every step during my studies, and ensuring my continual growth

through the many generous opportunities you have provided. Your encouragement, patience, and

wisdom have been deeply appreciated.

I would also like to thank the members of my PhD committee, Dr. Kaori Takehara-Nishiuchi and

Dr. Paul Fletcher. Our meetings and informal discussions were invaluable to my graduate work

and scientific development. Thank you for your time, insights, and guidance.

I am indebted to my undergraduate mentor, Dr. John Yeomans, for giving me my first

opportunity in research. Your scientific enthusiasm and confidence in me helped spark my love

for neuroscience.

Thank you to members of the Kim lab— June Bang, Janine Cajanding, Gustavo Parfitt, Paul

Whissell— for all the scientific advice and help you have provided, and for making it a joy to

come into the lab every day. Thank you also to the dedicated undergraduate students who have

assisted in the projects of this thesis: Lena Soukhov, Chloe Briggs, Waldo Lefever, Cheryl Lau,

Joanna Zhu.

Thank you to OMHF and the Psychology Department for financial support during my graduate

studies.

I also thank my parents and sisters for all their unconditional love and support throughout my

life.

To my husband Oliver, you have been my greatest source of strength. Thank you for always

believing in me, and for encouraging me to pursue my ambitions.

v

Table of Contents

Acknowledgments.......................................................................................................................... iv

Table of Contents .............................................................................................................................v

List of Figures ..................................................................................................................................x

Chapter 1 ..........................................................................................................................................1

General Introduction ...................................................................................................................1 1

1.1 Schizophrenia Core Symptoms ............................................................................................2

1.2 Inhibitory GABA Interneuron Dysfunction .........................................................................4

1.3 Animal Models of GABA Interneuron Dysfunction ...........................................................5

1.4 Role of the Ventral Hippocampus ........................................................................................7

1.4.1 vHPC Involvement in Psychosis and Dopamine System Modulation .....................7

1.4.2 Memory Function of the vHPC..............................................................................10

1.5 Role of the Prefrontal Cortex .............................................................................................13

1.5.1 PFC Involvement in Working Memory Impairments in Schizophrenia ................13

1.5.2 Mechanisms Supporting PFC Delay Activity during Working Memory ..............15

1.5.3 Function of PFC Delay Activity during Working Memory ...................................17

1.5.4 Hippocampus – PFC Circuit in Working Memory ................................................20

1.6 Cognitive and Behavioural Function of GABA Interneurons ...........................................23

1.6.1 Diversity of Inhibitory GABAergic Neurons ........................................................24

1.6.2 Circuit Function of Somatostatin and VIP Interneurons ........................................24

1.6.3 Circuit and Behavioural Function of Parvalbumin Interneurons ...........................25

1.6.4 Circuit and Behavioural Function of Cholecystokinin Interneurons .....................28

1.7 Specific Aims .....................................................................................................................31

vi

1.7.1 Aim I: To compare the role of vHPC PV and GAD65 interneuron activity in behaviours related to core schizophrenia features .................................................31

1.7.2 Aim II: To investigate the role of vHPC CCK interneurons in reward seeking and learning ............................................................................................................32

1.7.3 Aim III: To compare the roles of mPFC PV and CCK interneurons in working memory ..................................................................................................................33

1.7.4 Overview of Experiments ......................................................................................33

Chapter 2 ........................................................................................................................................35

Materials and Methods ..............................................................................................................35 2

2.1 Optogenetic and Chemogenetic Tools for Controlling Neural Activity ............................35

2.2 Animals ..............................................................................................................................36

2.3 Immunohistochemistry ......................................................................................................36

2.4 Optogenetics Apparatus .....................................................................................................37

Chapter 3 ........................................................................................................................................38

Parvalbumin and GAD65 Interneuron Inhibition in the Ventral Hippocampus Induces 3

Distinct Behavioral Deficits Relevant to Schizophrenia ...........................................................38

3.1 Abstract ..............................................................................................................................38

3.2 Introduction ........................................................................................................................39

3.3 Methods..............................................................................................................................40

3.3.1 Animals ..................................................................................................................40

3.3.2 AAV Vector Construction .....................................................................................40

3.3.3 Drugs ......................................................................................................................41

3.3.4 Stereotaxic Surgery ................................................................................................41

3.3.5 Cellular Quantification...........................................................................................41

3.3.6 Behavioural Apparatuses and Testing Procedures .................................................41

3.3.7 Statistical Analysis .................................................................................................44

3.4 Results ................................................................................................................................44

vii

3.4.1 hM4D-mediated inhibition of parvalbumin interneurons in the ventral hippocampus ..........................................................................................................44

3.4.2 Inhibition of parvalbumin interneurons disrupts PPI and spatial working memory ..................................................................................................................46

3.4.3 hM4D expression in GAD65 neurons in the ventral hippocampus .......................50

3.4.4 GAD65 neuron inhibition enhances locomotor activity and disrupts spatial working memory ....................................................................................................52

3.5 Discussion ..........................................................................................................................56

Chapter 4 ........................................................................................................................................61

Cholecystokinin Interneurons of the Ventral Hippocampus Regulate the Formation of 4

Context-Reward Memories .......................................................................................................61

4.1 Abstract ..............................................................................................................................61

4.2 Introduction ........................................................................................................................62

4.3 Materials and Methods .......................................................................................................64

4.3.1 Animals ..................................................................................................................64



4.3.4 Microdialysis and High-Performance Liquid Chromatography for Dopamine .....67

4.3.5 cFos Behavioural Procedures and Analysis ...........................................................68


4.4 Results ................................................................................................................................69

4.4.1 Intersectional genetic targeting of CCK Interneurons ...........................................69

4.4.2 CCK interneuron inhibition does not alter approach-avoidance behaviours .........71

4.4.3 CCK interneuron inhibition does not alter reward seeking behaviours .................72

4.4.4 CCK interneuron inhibition does not alter NAc dopamine levels .........................74

4.4.5 CCK interneuron inhibition enhances sucrose place preference ...........................74

4.4.6 CCK interneuron inhibition does not alter contextual fear memory encoding ......78

4.4.7 CCK interneuron inhibition increased cFos in vSub NAc-projecting cells ...........78

viii

4.5 Discussion ..........................................................................................................................82

Chapter 5 ........................................................................................................................................87

Parvalbumin and Cholecystokinin Interneurons of the Medial Prefrontal Cortex Mediate 5Distinct Working Memory Processes .......................................................................................87

5.1 Abstract ..............................................................................................................................87

5.2 Introduction ........................................................................................................................88

5.3 Materials and Methods .......................................................................................................90

5.3.1 Animals ..................................................................................................................90

5.3.2 Drugs ......................................................................................................................90


5.3.4 Pseudotyped Rabies Virus Transsynaptic Tracing ................................................91

5.3.5 Cellular Quantification...........................................................................................91



5.4 Results ................................................................................................................................95

5.4.1 Intersectional genetic targeting of CCK Interneurons ...........................................95

5.4.2 CCK interneurons are differentially distributed from PV interneurons in the mPFC .....................................................................................................................95

5.4.3 Selective ArchT expression in CCK Interneurons .................................................97

5.4.4 Working memory testing in the olfactory DNMS task ..........................................99

5.4.5 Acquisition of olfactory DNMS performance for optogenetic testing ................101

5.4.6 CCK and PV interneuron inhibition produces distinct changes in working memory performance ...........................................................................................102

5.4.7 CCK and PV interneuron inhibition does not disrupt Go/No-go olfactory discrimination ......................................................................................................104

5.4.8 CCK interneurons comprise a major inhibitory input to PV interneurons ..........106

5.5 Discussion ........................................................................................................................109

General Discussion..................................................................................................................113 6

ix

6.1 Overview and Implications for Schizophrenia ................................................................113

6.1.1 vHPC Perisomatic Interneurons and Sensorimotor Processing ...........................113

6.1.2 vHPC Perisomatic Interneurons and Contextual Learning ..................................114

6.1.3 vHPC and mPFC Perisomatic Interneurons and Working Memory ....................117

6.2 Limitations and Future Directions ...................................................................................121

6.3 Conclusions ......................................................................................................................124

References ....................................................................................................................................125

x

List of Figures

Chapter 3 – Figure 1. Inhibition of PV interneurons in the vHPC using hM4D

Chapter 3 – Figure 2. vHPC PV interneuron inhibition did not affect spontaneous or

amphetamine-induced locomotor activity

Chapter 3 – Figure 3. vHPC PV interneuron inhibition reduced percent PPI, startle amplitude,

and spontaneous alternation, but did not affect social interaction

Chapter 3 – Figure 4. Expression of hM4D in GAD65 neurons in the vHPC

Chapter 3 – Figure 5. vHPC GAD65 interneuron inhibition enhanced spontaneous and

amphetamine-induced locomotor activity.

Chapter 3 – Figure 6. vHPC GAD65 interneuron inhibition impaired spontaneous alternation but

did not affect percent PPI, startle amplitude, or social interaction

Chapter 4 – Figure 1. Intersectional genetic expression of ArchT in vHPC CCK interneurons

Chapter 4 – Figure 2. vHPC CCK interneuron inhibition did not alter anxiety or real-time place

avoidance/preference

Chapter 4 – Figure 3. vHPC CCK interneuron inhibition did not alter reward seeking,

exploration, or social behaviours

Chapter 4 – Figure 4. Microdialysis measurement of NAc dopamine concentration with

simultaneous vHPC CCK interneuron inhibition

Chapter 4 – Figure 5. vHPC CCK interneuron inhibition during training enhanced sucrose place

preference behaviour

Chapter 4 – Figure 6. vHPC CCK interneuron inhibition during training without sucrose did not

alter place preference behaviour

Chapter 4 – Figure 7. vHPC CCK interneuron inhibition did not affect contextual fear memory

encoding

xi

Chapter 4 – Figure 8. vHPC cFos expression following CCK interneuron inhibition during

context-reward exposure

Chapter 4 – Figure 9. vHPC cFos expression in CTBNAc- positive cells following CCK

interneuron inhibition during context-reward exposure

Chapter 5 – Figure 1. Intersectional genetic labeling and mPFC distribution of CCK and PV

interneurons

Chapter 5 – Figure 2. Intersectional genetic expression of ArchT selectively in CCK interneurons

Chapter 5 – Figure 3. Olfactory DNMS performance and disruption after systemic WIN55212-2

Chapter 5 – Figure 4. ArchT expression in CCK or PV interneurons and acquisition of DNMS

performance

Chapter 5 – Figure 5. Phase-specific inhibition of mPFC CCK or PV interneurons during DNMS

performance

Chapter 5 – Figure 6. Phase-specific inhibition of mPFC CCK or PV interneurons during Go/No-

go odour discrimination performance

Chapter 5 – Figure 7. Pseudotyped rabies retrograde tracing from PV interneurons of the mPFC

1

Chapter 1

General Introduction 1

Schizophrenia is a psychiatric illness involving pathological alterations at the anatomical,

neurophysiological, and molecular levels, and diverse clinical features that include perceptual,

emotional, and cognitive disturbances (Cannon, 2015). A prominent theory of schizophrenia

pathophysiology has emerged in recent decades positing the central role of dysfunctional

inhibitory GABA interneurons (Lewis et al., 2012). The resulting disruption in network

excitatory/inhibitory balance, particularly in the hippocampus (HPC) and medial prefrontal

cortex (mPFC), may lead to the development of psychosis and cognitive processing deficits in

schizophrenia (Benes and Berretta, 2001; Lisman et al., 2008; Krystal et al., 2017). A

heterogeneous population of GABA interneurons participates in organizing network activity

underlying behaviours mediated by the HPC and mPFC (Klausberger and Somogyi, 2008;

Tremblay et al., 2016). This observation has led to the hypothesis that particular interneuron cell

types may differentially contribute to particular features of schizophrenia depending on their

intrinsic and extrinsic properties. Two major classes of perisomatic interneurons disrupted in

schizophrenia, expressing parvalbumin (PV) or cholecystokinin (CCK), differ in their

electrophysiological properties, molecular expression, anatomical distribution, and connectivity

(Armstrong and Soltesz, 2012). This has raised the important question of whether PV and CCK

interneurons play distinct roles in the sensorimotor and mnemonic functions of the HPC and

mPFC that are disrupted in schizophrenia (Freund and Katona, 2007). In this review, I will first

introduce the defining symptoms of schizophrenia and discuss evidence of inhibitory interneuron

dysfunction in patients and animal models. The HPC and mPFC are two structures with

prominent reductions in GABA interneuron markers. I will therefore describe the link between

the ventral HPC (vHPC) and mPFC to particular schizophrenia-related behaviours. The role of

the vHPC in psychosis-related behaviours and memory will be reviewed, followed by a

discussion of the essential role of the mPFC in working memory. I will then describe the

neuronal properties of PV and CCK interneurons in turn, and the behavioural functions each

have been implicated in. Finally, I will outline the overall objective of my thesis and the specific

experimental aims to achieve this objective.

2

1.1 Schizophrenia Core Symptoms

Schizophrenia is a debilitating chronic mental illness involving severe perceptual, emotional, and

cognitive disturbances. Affecting approximately 1% of the population in North America (Hafner

et al., 1997), it poses significant strain on health services, and results in $4.83 billion of lost

productivity annually due to morbidity (Goeree et al., 2005). Importantly, schizophrenia patients

experience a diminished quality of life as a result of the persistent and distressing features (Eack

and Newhill, 2007). Schizophrenia symptoms typically emerge during late adolescence or early

adulthood in males and a few years later in females (Hafner, 1997). As outlined in the Diagnostic

and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V), patients diagnosed with

schizophrenia have at least two of the following characteristics: hallucinations, delusions,

disorganized speech, grossly disorganized or catatonic behaviour, and negative symptoms

(Tandon et al., 2013). The core symptoms may be categorized into three domains: positive,

negative, and cognitive.

Positive symptoms are named for their presence in schizophrenia patients while being absent in

the healthy population, and thus, may be considered excesses in function. Hallucinations and

delusions, which together are referred to as psychosis, are defining features of this category.

Hallucinations are vivid perceptions, most commonly auditory, that are not reflective of the

external world. Similarly, delusions are thoughts and beliefs that are not supported by evidence

from reality. Both conditions may relate to errors in inference and likely share a common

underlying neurophysiological dysfunction (Fletcher and Frith, 2009; Kapur, 2003).

Accordingly, hallucinations and delusions may both be treated with typical antipsychotic drugs

which act as antagonists at the dopamine D2 receptor (Creese et al., 1976). Consistent with the

action of antipsychotics in reducing dopamine signalling, psychostimulants which increase

synaptic dopamine levels can induce psychosis. Together, these findings have led to the theory of

hyperdopaminergia in schizophrenia (Carlsson and Lindqvist, 1963), specifically in the

mesolimbic dopamine circuit between the ventral tegmental area (VTA) and nucleus accumbens

(NAc). Positron emission tomography (PET) and single photon emission tomography (SPECT)

imaging have revealed a number of changes in dopamine transmission in schizophrenia. These

studies have shown enhanced dopamine synthesis capacity based on elevated uptake of the

precursor L-DOPA (Howes et al., 2012). The increased synthesis of dopamine can result in a

greater dopamine release. Accordingly, schizophrenia patients exhibit increased release of

3

dopamine in the striatum upon administration of psychostimulants such as amphetamine, as

inferred by the reduction in binding of radiolabelled competitive antagonists of the D2 receptor

(Laruelle and Abi-Dargham, 1999; Abi-Dargham et al., 2009). Increased dopamine release is

correlated with psychosis severity and is consistent with studies that have found a worsening of

psychosis following administration of dopamine enhancing drugs (van Kammen et al., 1982;

Lieberman et al., 1987). In addition to enhanced evoked dopamine release, there is also evidence

of higher synaptic dopamine concentration at baseline (Kegeles et al., 2010).

In contrast to positive symptoms, negative symptoms are characterized by losses in normal

function and encompass a broader scope of functions. These include avolition, social withdrawal,

anhedonia, and diminished emotional expression such as alogia and blunted affect (Strauss et al.,

2013). These symptoms may be caused by independent psychopathological processes, and tend

to cluster along two distinct dimensions—motivation and affect (Blanchard and Cohen, 2006;

Strauss et al., 2013). Negative symptoms can be moderately treated with atypical antipsychotic

drugs that act on a range of neurotransmitter symptoms, particularly on serotonin,

norepinephrine, and cholinergic receptors (Leucht et al., 1999).

Although not part of the DSM-V characteristics for the diagnosis of schizophrenia, deficits in

cognition are widely observed (Schaefer et al., 2013). Relative to positive and negative

symptoms, cognitive symptoms are highly predictive of functional outcome (Green et al., 2000),

but are less amenable to treatment with typical and atyptical antipsychotics (Keefe et al., 2007).

Schizophrenia patients exhibit cognitive impairments associated with the medial temporal lobe

and prefrontal cortex including deficits in episodic memory, verbal memory, verbal fluency,

processing speed, attention, executive functioning, and working memory (Ranganath et al., 2008;

Hoff et al., 1992; Riley et al., 2000). Cognitive deficits have been strongly related to

neurodevelopmental alterations as they are often present during adolescence and prior to

diagnosis (Jones et al., 1994; Reichenberg et al., 2010; MacCabe et al., 2013; Gur et al., 2014).

Longitudinal studies have indicated that cognitive decline within individuals between puberty

and early adulthood predicts the onset of psychosis (MacCabe et al., 2013; Vorstman et al.,

2015). Therefore, an argument has been made for cognitive dysfunction as being the core feature

of schizophrenia (Elvevag and Goldberg, 2000). The aetiology of neurodevelopmental changes

in schizophrenia that may disrupt cognition is not well understood, however several

susceptibility factors have been implicated, including the presence of predisposing genes

4

(Arnedo et al., 2015; Sekar et al., 2016), maternal prenatal infection (Brown and Derkits, 2010),

and environmental exposures during adolescence such as cannabis use (van Os et al., 2010).

Importantly, these factors appear to affect a common neural substrate, the GABAergic system.

1.2 Inhibitory GABA Interneuron Dysfunction

Cognitive processing in schizophrenia is marked by aberrant network activity, which has been

hypothesized to relate to the disruption of GABA interneuron function (Uhlhaas and Singer,

2015; Lewis et al., 2012), leading to disturbances in network excitatory/inhibitory balance

(Krystal et al., 2017). Substantial evidence from postmortem studies points to neuropathological

changes in the cortical GABAergic system in schizophrenia (Benes and Berretta, 2001; Lisman

et al., 2008; Lewis et al., 2012). Molecular alterations have been observed including decreased

expression of the alpha-1 subunit of the GABAA receptor in pyramidal neurons (Akbarian et al,

1995; Beneyto et al, 2011; Hashimoto et al, 2008a), and of the GABA-membrane transporter

GAT1 (Volk et al., 2001; Hashimoto et al, 2008a; Glausier and Lewis, 2011). Moreover, in vivo

magnetic resonance spectroscopy in schizophrenia patients has revealed lower levels of GABA

transmission in the PFC, with no significant differences in glutamate levels (Marsman et al.,

2014).

The most consistent evidence of GABA dysfunction has been the finding of reduction in the

GABA synthesizing enzyme glutamic acid decarboxylase (GAD). Both isoforms of this enzyme,

GAD67 and GAD65, show decreased mRNA and protein levels primarily in the prefrontal cortex

and hippocampus (Guidotti et al., 2000; Benes et al., 2007; Wang et al., 2011; Davis et al.,

2016). In postmortem schizophrenia tissue, a 30 to 50% reduction in both the levels and density

of neurons expressing GAD67 mRNA is observed across cortical layers in the dorsolateral

prefrontal cortex (dlPFC) (Akbarian et al., 1995; Volk et al., 2000). In the hippocampus, mRNA

levels of both GAD isoforms are downregulated (Benes et al., 2007). Furthermore, GAD65

levels have been correlated with antipsychotic drug dose, with the lowest mRNA expression

found among unmedicated patients (Todtenkopf and Benes, 1998).

The reductions in GAD have been found in only a subset of GABA interneurons (Volk et al.,

2000), consistent with the hypothesis that specific subtypes may be affected in schizophrenia. A

large body of work points to alterations in GABA interneurons containing the calcium-binding

protein parvalbumin (PV). There is a decrease in the density of PV-immunoreactive neurons and

5

varicosities in layers III and IV of the PFC (Beasley and Reynolds, 1997; Lewis et al., 2001;

Hashimoto et al., 2003), and in all subfields of the hippocampus including the subiculum, with

no change in the calcium-binding protein calretinin (Zhang and Reynolds, 2002; Wang et al.,

2011). Notably, patients with major depressive disorder do not show a similar loss in PV

interneurons (Zhang and Reynolds, 2002). Furthermore, there were approximately 50% fewer

PV neurons that express GAD67 and the NR2A subunit of the N-methyl-D-aspartate receptor

(NMDAR) (Hashimoto et al., 2003; Curley et al., 2011; Bitanihirwe et al., 2009), indicating an

impairment in GABA transmission and glutamatergic drive to PV interneurons. Though

relatively unexplored, deficits in other subtypes of GABA interneurons containing neuropeptides

have also been observed in both the PFC and hippocampus, such as somatostatin (SOM),

vasoactive-intestinal-peptide (VIP), neuropeptide Y, and cholecystokinin (CCK) interneurons

(Hashimoto et al., 2003; Wang et al., 2011; Konradi et al., 2011; Morris et al., 2008; Morris et

al., 2009; Fung et al., 2014; Hashimoto et al., 2008b; Fung et al., 2010).

Changes to the glutamatergic system may also underlie schizophrenia pathophysiology.

Genome-wide association studies have revealed susceptibility genes involved in plasticity and

signalling at glutamatergic synapses (Schizophrenia Working Group of the Psychiatric Genomics

Consortium, 2014; Hall et al., 2015). Furthermore, the density and distribution of the NR1

subunit of the NMDA receptor is reduced in postmortem tissues (Sokolov, 1998; Hammond et

al., 2014). These alterations are hypothesized to interact with the GABAergic system through

decreased excitatory drive to GABA interneurons (Bitanihirwe et al., 2009), resulting in a

compensatory downregulation of GABAergic signalling (Cohen et al., 2015; Krystal et al., 2017;

Hoftman et al., 2017).

1.3 Animal Models of GABA Interneuron Dysfunction

A variety of schizophrenia animal models exhibit alteration to the GABAergic system. These

include models that incorporate genetic or environmental risk factors, and those that directly

induce schizophrenia symptom-like behaviours through pharmacological or neuromodulatory

disruptions. Transgenic mice with mutations in the Disrupted in Schiziphrenia-1 gene (DISC1),

linked to schizophrenia susceptibility (St. Clair et al., 1990; Hovatta et al., 1999), exhibit reduced

PV-immunoreactivity in the medial PFC (mPFC) and hippocampus (Hikida et al., 2007; Shen et

al., 2008). Similarly, PV is reduced in these regions in prenatal infection models, such as the

6

polyribocytidilic acid (polyIC) model (Meyer et al., 2008). Prenatal treatment with polyIC in

pregnant mice mimics maternal immune activation following viral infection, an event associated

with the increased risk of offspring developing schizophrenia (Meyer et al., 2007, 2009; Boksa,

2010). Following prenatal polyIC treatment, Canetta et al. (2016) found impaired GABA

transmission in PV interneurons in offspring due to lowered GABA release probability. This

deficit in synaptic transmission of GABA may result from the reduction of GAD67 in PV

interneurons (Brown et al., 2015; Fujihara et al., 2015). An environmental factor that has been

associated with the increased risk of developing psychosis is cannabinoid use during adolescence

(Moore et al., 2007). Cannabinoids exert their psychotropic effects through binding of the CB1

receptor (Devane et al., 1988). Adolescent cannabinoid use has been modelled in rodents by

chronic administration of CB1 receptor agonists delta-9-tetrahydrocannabinol and WIN55212-2

during adolescence (Gleason et al., 2012; Zamberletti et al., 2014), and has been found to cause

reduced GAD67 expression in PV and CCK interneurons in the mPFC (Zamberletti et al., 2014).

Alterations in cortical GABA marker have also been observed in neurodevelopmental and

pharmacological models with prominent dopaminergic system dysfunction. Neonatal ventral

hippocampal lesions (NVHL) produce reductions in GAD67 mRNA levels in the mPFC (Lipska

et al., 2003), and prenatal administration of the DNA synthesis inhibiting agent

methylazoxymethanol (MAM) results in the loss of PV interneurons in the ventral hippocampus

(vHPC) of adult offspring (Lodge et al., 2009). Both acute and chronic administration of

NMDAR antagonists in neonatal and adult rodents leads to the reduction of PV expression in the

hippocampus and mPFC (Keilhoff et al., 2004; Nakatani-Pawlak et al., 2009; Romón et al.,

2011; Jenkins et al., 2010). The above models contain alterations in specific interneuron

populations in the hippocampus and mPFC, and exhibit disruptions in schizophrenia-related

behaviours mediated by these structures. In addition to GABA dysfunction, NVHL, MAM, and

NMDAR models display dopamine system dysfunction as indicated by increased locomotor

activity in response to psychostimulants such as amphetamine (Mandillo et al., 2003; Tseng et

al., 2009; Lodge and Grace, 2007), as well as deficits in prepulse inhibition (PPI), latent

inhibition, cognitive flexibility, and spatial working memory (Inan et al., 2013; Nakazawa et al.,

2011; Meyer et al., 2008). Of note, direct and selective impairment of PV interneuron function in

the mPFC has also produced spatial working memory deficits. Murray et al. (2015) found

chronic disruption of PV interneuron transmission through the expression of tetanus toxin light

7

chain impaired spontaneous alternation and delayed-match-to-place performance in the Y-maze.

Together, these findings have led to the hypothesis that dysfunction in particular GABAergic

interneuron cell types may be associated with specific features of schizophrenia depending on

structural location (Grace, 2010; Lewis et al., 2012).

1.4 Role of the Ventral Hippocampus

1.4.1 vHPC Involvement in Psychosis and Dopamine System Modulation

The loss of GABA interneuron function in the vHPC could diminish inhibitory tone, and

therefore lead to local increases in excitatory transmission (Behrens and Sejnowski, 2009; Lodge

et al., 2009; Grace, 2011). Findings from neuroimaging studies of aberrant hyperactivity in the

vHPC of schizophrenia patients lend support to this theory (Schobel et al., 2009, 2013). In

particular, magnetic resonance imaging (MRI) of schizophrenia patients experiencing delusions

have revealed increased baseline activity, measured as cerebral blood volume, in the anterior

hippocampus (equivalent to the vHPC of rodents) (Schobel et al., 2009, 2013). This increased

activity was localized to the anterior CA1 and subiculum and correlated with the emergence and

severity of psychosis, as well as with the reduction in hippocampal volume at psychosis onset

(Schobel et al., 2009, 2013). Since psychosis is a symptom linked to enhanced mesolimbic

dopamine activity (Carlsson and Lindqvist, 1963; Seeman, 2006), its association with vHPC

hyperactivity suggests that the vHPC may influence mesolimbic dopamine activity. This

hypothesis provides an explanation as to the lack of primary anatomical pathology in the

dopamine system despite alterations in transmission in schizophrenia (Laruelle and Abi-

Dargham, 1999; Abi-Dargham et al., 2009; Kegeles et al., 2010). Instead, diffuse

neuroanatomical changes outside the striatal dopamine system have been found, including a

reduction in volume and disorganization of the hippocampus and frontal cortex (Gothelf et al.,

2000). Thus, it has been proposed that enhanced mesolimbic dopamine activity may result from

dysfunctional regulation by the vHPC (Grace, 2010).

The vHPC may interact with the mesolimbic dopamine system through its dense connections

with the NAc (Witter and Groenwegen, 1987), a limbic-motor interface for goal-directed

behaviour that receives prominent dopaminergic innervation from the VTA (Mogenson et al.,

1980). As with its other cortical and subcortical afferents, the CA1 and subiculum sends

8

glutamatergic projections topographically to the NAc (Gaykema et al., 1991). While the ventral

region innervates the caudomedial NAc or shell region, projections from progressively dorsal

regions extend rostrolaterally in the NAc to its core region (Swanson and Cowan, 1977; Kelley

and Domesick, 1982; Witter and Groenwegen, 1987; Witter et al., 1990; Brog et al., 1993; Papp

et al., 2012). Electrophysiological recordings have also provided evidence for direct modulation

of NAc activity by the vHPC. Optogenetic activation with channelrhodopsin-2 (ChR2) of vHPC

terminals in the NAc evokes EPSCs in NAc medium spiny neurons (MSNs) as measured by

whole cell patch clamp recordings in slice (Britt et al., 2012; Pascoli et al., 2014; Bagot et al.,

2014). Anaesthetized recordings in rats have shown that single pulse stimulation of the vHPC

can evoke spike firing (Yang and Mogenson, 1984; Boeijinga 1990; Taeparvarapruk et al.,

2008), while tetanic stimulation results in long-term potentiation of evoked potentials in the NAc

(Boeijinga 1993; Belujon and Grace, 2008). Furthermore, vHPC activity is strongly correlated

with the depolarization state of NAc MSNs (O‘Donnell and Grace, 1995; Goto and O‘Donnell,

2001; Goto and Grace, 2008). Electrical stimulation of the vHPC induces membrane potential

shifts from a highly hyperpolarized DOWN state to a slightly depolarized UP state (O‘Donnell

and Grace, 1995), and negative fluctuations in the vHPC local field potential are highly

correlated with transitions to the UP state in NAc neurons. These electrophysiological findings

have revealed that activity in the NAc is strongly controlled by excitatory inputs arriving from

the vHPC and can occur in synchrony with vHPC activity.

Microdialysis experiments have also confirmed that the vHPC affects dopamine transmission in

the NAc. Enhancing excitatory signalling in the vHPC by the GABAA receptor antagonist

bicuculline, electrical stimulation, or NMDA infusion results in increased NAc dopamine release

(Brudzynski and Gibson, 1997; Blaha et al., 1997; Legault et al., 1999; Mitchell, 2000;

Taepavarapruk et al., 2001; Moss et al., 2003). However, the precise mechanism of this effect

has not been determined and may involve monosynaptic and multisynaptic circuits. In the NAc,

glutamate released from vHPC terminals may act presynaptically on dopaminergic terminals

from the VTA (Seesak and Pickel, 1990; Blaha et al., 1997; Taepavarapruk et al., 2000). This

view is supported by anatomical evidence that hippocampal and dopaminergic axonal boutons

converge onto single neurons in the NAc and are in close apposition to each other (Seesak and

Pickel, 1990). Multisynaptic mechanisms involving the VTA may also contribute to vHPC-

evoked dopamine release. Taepavarapruk et al. (2008) found the increased dopamine

9

concentration in the NAc following electrical stimulation of the vHPC was substantially reduced

by VTA lidocaine infusions. The NAc sends prominent monosynaptic inhibitory projections to

the VTA (Watabe-Uchida et al., 2012; Menegas et al., 2015), synapsing with both GABAergic

and dopaminergic neurons (Edwards et al., 2017). However, the functional consequences of

NAc-VTA pathway activity is still under debate with studies proposing a disinhibition of

dopaminergic neuron activity and therefore striatal dopamine release (Xi et al., 2011; Bocklisch

et al., 2013), as well as its direct inhibition (Edwards et al., 2017). The NAc also provides

afferents to the ventral pallidum (VP) which strongly inhibits the VTA (Grace and Bunney,

1985). A circuit involving the vHPC-NAc-VP-VTA has been proposed whereby glutamatergic

inputs from the vHPC excite NAc MSNs which in turn inhibit GABAergic projection neurons of

the VP, thereby disinhibiting dopaminergic neurons in the VTA (Floresco et al., 2001, 2003).

Dopamine neurons in the VTA exhibit 3 distinct activity states: nonfiring, tonically firing, and

burst firing (Grace, 2011). Spontaneously active dopamine neurons display slow tonic firing

generated by endogenous pacemaker conductances (Grace and Bunney, 1984a; Grace, 1991;

Grillner and Mercuri, 2002). Burst firing activity is observed as high frequency action potentials

riding on a depolarizing wave and is associated with phasic dopamine release during reward

signalling (Grace and Bunney, 1984b; Grillner and Mercuri, 2002; Hollerman et al., 1998). Due

to magnesium blockade of the NMDA receptor at hyperpolarized membrane potentials, only

depolarized tonically firing dopamine neurons can be made to burst fire (Lodge and Grace, 2006;

Grace, 2011). It is through the control of the number of tonically active dopamine neurons in the

VTA that the vHPC is believed to modulate dopamine system activity. Consistently, NMDA

activation of the vHPC was found to increase the proportion of tonically firing dopamine neurons

in the VTA, which was abolished by VP bicuculline activation (Floresco et al., 2001, 2003).

Dopamine release from the VTA into the NAc is a necessary mechanism underlying the

reinforcement of behaviours (Carr and White, 1983; Baker et al., 1998; Tsai et al., 2009).

Dopamine transmission in the NAc is thought to be a reward predictive signal critical for

incentive salience, the ability of unconditioned and conditioned stimuli to drive goal-directed

reward seeking behaviours (Robinson and Berridge, 1993). Spatial cues in reward-associated

environments may gain incentive salience through glutamatergic input from the HPC to the NAc

(Ito et al., 2008; Britt et al., 2012; Pascoli et al., 2014; Loureiro et al., 2016; Sjulson et al., 2017).

Aberrant activity in the vHPC may therefore lead to abnormal glutamate and dopamine

10

signalling in the NAc which could impair reinforcement learning or result in salience attribution

to inappropriate stimuli (Waltz et al., 2007; Roiser et al., 2009; Grace, 2010), a process

hypothesized to drive delusions in psychosis (Kapur, 2003; Howes and Murray, 2014).

The vHPC-mediated activation of the NAc and VTA dopamine neurons may be an important

mechanism for modulating dopamine system responsiveness to salient cues as animals navigate

through the environment (Grace, 2010). Taepavarapruk et al. (2000) found electrical stimulation

of the vHPC increased dopamine efflux in the NAc, which positively correlated with the amount

of locomotor activity. Furthermore, evidence has been put forth in support of vHPC participation

in spatial navigation and learning (Ruediger et al., 2012; Kjelstrup et al., 2008; Hinman et al.,

2011; Patel et al., 2012). Similar to the dHPC, the frequency of theta oscillations in the vCA1 is

positively correlated with the speed of locomotion during maze navigation (Hinman et al., 2011;

Furhmann et al., 2015). Moreover, Ruediger et al. (2012) found a specialized function for the

vHPC in mediating searching behaviour in the Morris water maze, specifically during initial

learning of the platform location. Given the function of the vHPC in navigation and learning of

the environment, locomotion elicited by the vHPC is likely a result of sensorimotor integration

rather than involuntary motor induction (O‘Keefe and Nadel, 1978; Bland and Oddie, 2001; Bast

et al., 2003; Hinman et al., 2011). Therefore, the HPC may be unitarily involved in processing

high-level representations of environmental stimuli, and in exerting top-down control over

adaptive behavioural responses such as exploration, approach, and avoidance (Bast, 2003).

As discussed above, deficits in vHPC GABA interneuron function may cause local increases in

excitability. The reduction in GABAergic transmission in the vHPC may increase outflow to the

NAc leading to a hyperdopaminergic state relevant to psychosis (Grace, 2010). Manipulations

that decrease vHPC GABAergic transmission affect sensorimotor processes, namely locomotor

activity and sensorimotor gating (Bast et al., 2001a; Zhang et al., 2002; Peterschmitt et al., 2008;

Braff and Geyer, 1990). Under natural conditions, however, activity in the vHPC could facilitate

both learned and innate adaptive responses to the environment.

1.4.2 Memory Function of the vHPC

While the hippocampus plays an essential role in spatial learning and memory (Bird and

Burgess, 2008), its contribution to these processes differs depending on its subregion. Multiple

lines of evidence support a functional segregation in the hippocampal formation along the dorsal-

11

ventral axis. Regionally specific gene expression patterns have been found in the CA3 and CA1,

with molecularly distinct subdomains in the dorsal and ventral poles (Leonardo et al., 2006;

Thompson et al., 2008; Dong et al., 2009; Cembrowski et al., 2016). These expression patterns in

pyramidal cells may relate to their efferent connections (Dong et al., 2009; Cembrowski et al.,

2016) and to their electrophysiological properties such as intrinsic excitability which gradually

increases toward the ventral pole (Dougherty et al., 2012; Malik et al., 2015). Pyramidal neurons

in the CA1 of the dHPC and vHPC exhibit largely non-overlapping projection patterns,

suggesting the information they supply may serve unique purposes. The dHPC has been found to

preferentially target cortical and sensory areas such as the retrosplenial cortex, nucleus reunions,

and anterior thalamic nuclei which mediate spatial navigation and cognitive processing (van

Groen et al., 2004; Cenquizca and Swanson, 2007). Meanwhile, the vHPC sends prominent

projections to cortical and subcortical limbic structures pointing to its involvement in emotion

(Swanson and Cowan, 1977).

While the dHPC has been strongly implicated in spatial processing and navigation, support for

the involvement of the vHPC in this function has been limited (Moser and Moser, 1998; O‘Mara,

2005; Dong and Fanselow, 2010). Lesion studies in rodents have indicated that the integrity of

the dHPC is necessary for spatial memory in tasks such as the Morris Water maze (Moser et al.,

1993; Moser et al., 1995; Zhang et al., 2004). Lesions damaging as little as 30-40% of the dHPC

significantly impair spatial learning (Moser et al., 1993; Moser et al., 1995; Richmond et al.,

1999; Bannerman et al., 1999; Pothuizen et al., 2004; Broadbent et al., 2004; Dillon et al., 2008).

In contrast, most vHPC lesion studies have found minor deficits, if any, on spatial location tasks

(Gross et al., 1965; Riegert et al., 2004; Broadbent et al., 2004; Ruediger et al., 2012; Moser et

al., 1993; Richmond et al., 1999; Bannerman et al., 1999; Pothuizen et al., 2004). Further

evidence for differences between the dHPC and vHPC in spatial processing has come from

electrophysiological recordings in behaving animals. Analysis of neuronal firing during the

performance of spatial tasks has revealed differences in the place fields of pyramidal neurons in

the dHPC and vHPC (Jung et al., 1994, Kjelstrup et al., 2008). Although place cells are found

along the entire longitudinal extent of the CA3 and CA1, the vHPC contains fewer place cells

with poorer spatial specificity compared to the dHPC (Jung et al., 1994). Kjelstrup et al. (2008)

reported a topographical gradient in the scale of spatial representation along the dorsal-ventral

axis, with place fields of a diameter smaller than 1 metre located in the dorsal pole, and as large

12

as 10 metres in the ventral pole. Thus, compelling evidence exists for a preferential role of the

dHPC over the vHPC in processing detailed spatial representations for learning and memory.

Meanwhile, the broader spatial representations in the vHPC may be better suited to processing

spatially large-scale or generalizable representations of the environment over precise locations.

Relative to the dHPC, few electrophysiological recordings have been made from the vHPC

during contextual learning. Komorowski et al. (2013) compared the activity of vCA3 and dCA3

cells during a context-dependent rule retrieval task, in which context was used to indicate which

of two objects was associated with food reward. Unlike cells in the dorsal CA3, ventral CA3

cells displayed context selectivity, preferentially firing to one of two contexts in which reward

had been presented, but not to the precise location or object marking the site of reward

presentation. Interestingly, context-selectivity emerged later in learning when animals reached

high levels of performance, suggesting vHPC activity may support successful context

discrimination and retrieval of the associated rule. In a subsequent study (Place et al., 2016), this

process was found to involve theta frequency synchronization between the vCA1 and mPFC as

rats explored the conditioned context, while application of the context-specific rule to perform an

object discrimination involved theta frequency synchronization between the mPFC and dHPC.

Furthermore, the findings of Riaz et al. (2017) support the critical role of the vHPC over the

dHPC in context-dependent rule retrieval, which was tested in a context-specific auditory

discrimination task. After learning, inactivation of the vHPC with GABAA and GABAB receptor

agonists significantly impaired performance, while dHPC inactivation did not. Since the relevant

contextual information to perform the task were proximal cues such as odours and chamber size,

the authors propose the vHPC may be particularly important for encoding cues in the proximal

environment. However, this idea requires further investigation by testing the role of the vHPC in

context-dependent rule retrieval tasks in which context is defined exclusively by distal cues.

The fine-grained spatial representations within the dHPC are suited for the association of discrete

events with specific locations. On the other hand, the broad contextual representations of the

vHPC may allow discrete events, as well as continuous events such as odours or internal

homeostatic and emotional responses, to be associated with the general environment. The

potential association of contextual information with odour and emotion by the vHPC is indicated

by its major innervation of olfactory and limbic projection targets, which include the olfactory

bulb and anterior olfactory nucleus for control of odour sensitivity (Aqrabawi et al., 2017), the

13

basolateral amygdala for contextual fear memory (Richmond et al., 1999; Bannerman et al.,

1999; Hale et al., 2008; Biedenkapp and Rudy, 2009; Xu et al., 2016; Jimenez et al., 2018), the

mPFC, lateral septum, and lateral hypothalamus for anxiety (Adhikari et al., 2010; Adhikari et

al., 2011; Padilla-Coreanu et al., 2016; Parfitt et al., 2017; Jimenez et al., 2018), the anterior

hypothalamus for inhibitory control over autonomic and neuroendocrine responses (Henke,

1990; Lowry, 2002; Mueller et al., 2004; Herman and Mueller, 2006), and the nucleus

accumbens (NAc) for goal-directed behaviour (Groenewegen and Witter, 1987; Cooper et al.,

2006; Grace et al., 2007). Interestingly, Ciocchi et al. (2015) found that vCA1 pyramidal neurons

are preferentially recruited to represent particular contexts depending on the emotional relevance

of the context and the neuron‘s projection target. Neurons projecting to the mPFC, and not to the

amygdala or NAc, were recruited during anxiety testing in the elevated plus maze (EPM),

specifically during open arm exploration. On the other hand, neurons doubly projecting to the

mPFC and the NAc exhibited preferential firing as rats approached reward-associated locations

in a plus maze, while amygdala-projecting neurons showed low activity in both of these tasks.

Thus, unlike the dHPC, the primary function of the vHPC may not be in the formation of

detailed spatial representations. Rather, the vHPC may represent broad spatial contexts with

emotional relevance. This function of the vHPC may relate to its role in behaviours relevant to

the cognitive and negative symptoms of schizophrenia, including spatial working memory, latent

inhibition, impulsivity, sociability, and behavioural despair (Wilkerson and Levin, 1999; Pouzet

et al., 2004; Abela et al., 2013; Felix-Ortiz and Tye, 2014; Bagot et al., 2014; Corbett et al.,

1999).

1.5 Role of the Prefrontal Cortex

1.5.1 PFC Involvement in Working Memory Impairments in Schizophrenia

The PFC has been proposed to play a role in the top-down control of sensory, motor, emotional,

and cognitive processing based on adaptive rules and goals (Miller, 2000; Miller and Cohen,

2001). This broad function may explain its involvement in a variety of cognitive behaviours

including attention, cognitive flexibility, decision-making, and working memory (Dalley et al.,

2004; Riga et al., 2014). The disruption of these behaviours in schizophrenia likely relates to

structural and cytoarchitectural abnormalities particularly in the dorsolateral PFC (dlPFC). This

region exhibits a slight reduction in grey matter volume of between 9-12% (Gur et al., 2000;

14

Hirayasu et al., 2001; Volpe et al., 2012). However, there does not appear to be a significant

decrease in the overall number of cells, and often, neuronal density is increased (Selemon et al.,

1995). The reduced volume and increased cell packing may be explained by the observed

reduction in neuropil. Dendritic spines (Glantz and Lewis, 2000), as well as pyramidal cell

terminals on GABAergic interneurons are reduced particularly in layer III (Bitanihirwe et al.,

2009; Arion et al., 2015). These morphological changes may underlie network activity

dysfunction, such as reduced PFC activity during cognitive performance (Glahn et al., 2005;

Yoon et al., 2008; Minzenberg et al., 2009).

Impaired working memory is a core cognitive deficit in schizophrenia. Being an important

component of many cognitive functions, deficits in working memory may underlie disturbances

observed in other cognitive domains such as planning, language, decision-making, and thought

organization (Perlstein et al., 2001; Silver et al., 2003; Johnson et al., 2013). Working memory is

defined as the short-term storage and manipulation of task-relevant information (Baddeley,

1992). This multi-component process may be parsed into distinct phases, namely the acquisition

of stimulus properties, the generation and maintenance of internal stimulus representations, and

the usage of such representations to guide goal-directed behaviour. Schizophrenia patients often

commit more errors on working memory tests which may be attributable to reduced working

memory capacity and increased susceptibility to interference during the maintenance period

(Gold et al., 2010; Anticevic et al., 2011). Poor working memory performance in schizophrenia

has been found across a variety of test paradigms and stimulus modalities (Forbes et al., 2009),

indicating dysfunction in a common underlying neural substrate.

While a distributed network of structures participates in working memory, the prefrontal cortex

acts as a central node (Curtis and D‘Esposito, 2003). In the Baddeley model of working memory,

the PFC acts as the central executive during information maintenance, directing the processing of

content in sensory stores such as the visuospatial sketchpad for visual and spatial information

and the phonological loop for auditory information (Baddeley, 1986). The importance of the PFC

is supported by lesion studies which have found impairments in working memory performance in

humans (Muller et al., 2002; Tsuchida and Fellows, 2009; Voytek and Knight, 2010), monkeys

(Fuster and Alexander, 1971; Bauer and Fuster, 1976; Funahashi et al., 1993), and rodents

(Granon et al., 1994; Kesner et al., 1996; Ragozzino et al., 1998; Rossi et al., 2012). Evidence for

the role of the PFC in working memory first came from the discovery of delay-related activity

15

(Fuster and Alexander, 1971). Persistent activity in the PFC is robustly elicited during the delay

period of working memory tasks at both the neuronal and population level, bridging the gap

between stimulus presentation and usage of the stimulus representation for adaptive responding

(Fuster and Alexander, 1971; Curtis and D‘Esposito, 2003). Functional MRI measurements

reveal delay activity to be highly correlated with working memory demand. It is sustained

throughout the entire delay interval, and is more strongly activated with greater memory load,

such as increasing number of items to be remembered (Courtney et al., 1998; Jha and McCarthy,

2000; Howard et al., 2003). Higher memory load also leads to bilateral recruitment of the PFC

(Holler-Wallscheid et al., 2017), which may reflect the distribution of task demands between

PFC hemispheres (Reuter-Lorenz and Cappell, 2008). In schizophrenia, task-related PFC activity

is markedly decreased throughout the working memory task (Haenschel et al., 2009; Senkowski

and Gallinat, 2015), failing to exhibit demand-dependent recruitment (Andreasen et al., 1992;

Carter et al., 1998; Meyer-Lindenberg et al., 2005; Dreisen et al., 2008). Patients also exhibit

bilateral recruitment of the PFC at demand levels in which activity is lateralized among healthy

controls (Manoach et al., 2000; Lee et al., 2008). Reduced activations of the PFC in

schizophrenia are accompanied by abnormal oscillations. Specifically, the magnitude of gamma

and theta frequency oscillations is diminished throughout the encoding, maintenance, and

retrieval phases of working memory (Haenschel et al., 2009; Senkowski and Gallinat, 2015).

Gamma oscillations are hypothesized to reflect local processing and have been strongly

associated with cognitive performance (Fries, 2009; Buzsaki and Wang, 2012). Gamma band

power increases with working memory load, both as a function of the number of items-to-be-

remembered and retention interval length (Howard et al., 2003; Roux et al., 2012; Honkanen et

al., 2015; Kornblith et al., 2015). Therefore, reduced gamma band power in schizophrenia may

relate to impairments in working memory capacity (Gold et al., 2010). Theta oscillations may

underlie the long-range synchronization between structures, and the organization of information

into coherent representations (Buzsaki, 2002; 2010). Abnormal oscillations in particular

frequency bands may indicate dysfunctions that are localized to precise neural circuits.

1.5.2 Mechanisms Supporting PFC Delay Activity during Working Memory

The mechanisms underlying delay-related activations in the PFC are better understood by

examining neurophysiological recordings in animals. These recordings have revealed mPFC

delay activity across a variety of stimulus modalities including spatial, olfactory, motor, and

16

auditory (Bolkan et al., 2017; Liu et al., 2014; Schmitt et al., 2017; Sakurai et al., 1990). As

animals perform delayed matching/non-matching- to sample (DMS/DNMS) tasks of working

memory, neurons in the DLPFC in monkeys and the mPFC in rodents show increases in firing

rate during the delay period (Fuster and Alexander, 1971; Fuster, 1973; Funahashi et al., 1989;

Jung et al., 1998; Liu et al., 2014; Bolkan et al., 2017). This neural activity persists throughout

the entire delay interval and is correlated with successful working memory performance, with

diminished activity during incorrect trials. While delay activity is sustained throughout the entire

interval at the population level, individual neurons show brief sequential increases in firing that

together tile the delay interval (Jung et al., 1998; Baeg, et al., 2003; Fujisawa et al., 2008; Harvey

et al., 2012; Bolkan et al., 2017; Schmitt et al., 2017).

Delay activity is likely mediated by recurrent excitation in layers II/III of pyramidal cells that

form cortico-cortical connections, allowing for reverberation of activity within the PFC

(Goldman-Rakic, 1995; Constantindis and Wang, 2004). It is dependent on glutamatergic

signalling primarily through NMDA receptors, and relies less on AMPA receptors (Moghaddam

and Adams, 1998; Wang et al., 2013). Computational models suggest the slow kinetics of

NMDA receptors, particularly those containing the NR2B subunit, allow for sustained

depolarization and therefore persistent activity (Lisman et al., 1998; Compte et al., 2000; Wang

et al., 2001; Wang et al., 2002; Wang et al., 2013). Disruption of NMDA receptor function via

microinfusion of NMDA receptor antagonists into the PFC of primates and rodents impairs

working memory (Wang et al., 2013; Moghaddam and Adams, 1998). Long-lasting

neuromodulatory signals have also been implicated in working memory, particularly dopamine

transmission via mesocortical afferents from the VTA. During working memory performance,

dopamine levels increase in the PFC (Watanabe et al., 1997; Phillips et al., 2004; Rossetti and

Carboni, 2005), and critically act on D1 receptors. While the importance of D2 receptor activity

for working memory is less clear (Sawaguchi and Goldman-Rakic, 1997; Seamans et al., 1998;

Aultman and Moghaddam, 2001; Wang et al., 2004), D1 receptor signalling has been proven

essential, as both D1 receptor agonists and antagonists delay dependently impair performance

(Sawaguchi and Goldman-Rakic, 1991; Broerson et al., 1995; Murphy et al., 1996; Sawaguchi

and Goldman-Rakic, 1997; Zarht et al., 1997). The comparable effects of D1 agonists and

antagonists points to an inverse U function of dopamine in working memory, with an optimal

level of D1 receptor signalling for successful performance (Williams and Castner, 2005;

17

Floresco and Magyar, 2006; Vijayraghavan et al., 2007). Dopamine concentration has been

correlated with the accuracy of performance, with greater dopamine levels during low load/high

accuracy trials relative to high load/low accuracy trials (Phillips et al., 2004). Increasing D1

receptor activity during low accuracy trials improves performance, whereas doing so during high

accuracy trials impairs performance, suggesting an ideal amount of dopamine for accurate

performance and increasing levels beyond that is disadvantageous (Zahrt et al., 1997; Floresco

and Phillips, 2001; Chudasama and Robbins, 2004). This model is supported at the neuronal

level in primates, where PFC microinfusion of low doses of D1 receptor agonists enhances the

tuning of delay cells to task-relevant information, whereas higher doses broadly attenuate

activity (Aultman and Moghaddam, 2001; Vijayraghavan et al., 2007). D1 receptor antagonist

application has a similar effect to high dose D1 receptor agonists, reducing delay activity

(Sawaguchi et al., 1988; Williams and Goldman-Rakic, 1995). Taken together, NMDA receptor

signalling is essential for sustaining persistent delay activity during working memory (Wang et

al., 2013), while mesocortical dopamine acting through the D1 receptor serves to sharpen this

activity thereby enhancing representations of task-relevant information (Aultman and

Moghaddam, 2001; Vijayraghavan et al., 2007; Jacob et al., 2016). These two systems may

interact, with dopamine increasing signal gain by potentiating NMDA-evoked activity (Seamans

et al., 2001; Chen et al., 2004; Thurley et al., 2008). Schizophrenia patients exhibit dopaminergic

dysfunction in the PFC including a reduction of dopaminergic afferents (Akil et al., 1999),

decreased dopamine release capacity (Slifstein et al., 2015), and increased D1 receptor

availability which may relate to a compensatory change (Abi-Dargham et al., 2002; Abi-

Dargham et al., 2012). Thus, it has been proposed that the dysregulation in mesocortical

dopamine may underlie PFC hypoactivity and working memory impairment (Williams and

Castner, 2006; Nyberg et al., 2014; Arnsten et al., 2015). This hypoactivity may be due to a

flattening of the inverse-U recruitment of the PFC with increasing memory loads compared to

healthy controls (Shohamy et al., 2016; Van Snellenberg et al., 2016).

1.5.3 Function of PFC Delay Activity during Working Memory

There is considerable debate as to whether delay activity in the PFC itself stores sensory

information in working memory, or whether it serves as a top-down signal priming internal

representations of sensory stimuli in individual sensory cortices (Pasternak and Greenlee, 2005;

Riley and Constantinidis, 2015; Lara and Wallis, 2015). Studies in monkeys have revealed the

18

coding of mnemonic information by delay activity. During the oculomotor delayed-response

spatial working memory task, a visual stimulus is presented in a given location and after a delay

interval, the subject makes a saccade to the cued location (DMS) or to a non-matching location

(DNMS). The majority of delay cells in this task exhibit preferential firing for the cued location

which is suggestive of the maintenance of retrospective location information (Funahashi et al.,

1989; Funahashi et al., 1993; Takeda and Funahashi, 2002). A much smaller population of delay

cells may be involved in prospective memory, showing tuning to the upcoming choice location

(Funahashi et al., 1993; Takeda and Funahashi, 2002). However, delay activity during working

memory is not unique to the PFC, and has been observed in several sensory cortices across

different modalities in monkeys (Miyashita and Chang, 1988; Gottlieb et al., 1989; Fuster, 1990;

Miller et al., 1993; Zhou and Fuster, 1996; Bisley et al., 2004) and rodents (Sakurai, 1990a). For

example, primates performing tactile working memory tasks involving texture or vibrational cues

display delay cell activity in the somatosensory cortex (Zhou and Fuster, 1996; Zhou and Fuster,

2000; Romo et al., 2002). Stimulus representations within sensory cortices may also be more

precise, as these delay cells show greater selective tuning to the sample stimulus (Ku et al.,

2015).

In rodents, the coding of mnemonic information by PFC delay cells has been observed primarily

in working memory tasks involving non-spatial cues (Ramus and Eichenbaum, 2000; Liu et al.,

2014; Schmitt et al., 2017). Spatial working memory in rodents is frequently tested in the T-maze

delayed-non-match-to-position task which requires the subject to maintain memory for the

previously visited goal arm and choose to enter the unvisited arm. Rodents readily acquire

performance on this task, and are extremely adept, with percentage correct choice typically

above 90% when the delay interval is 10 seconds or less, and remains above chance-level with

delay intervals up to 10 minutes (Dudchenko, 2001). The high level of performance on this task

indicates low working memory demand. Delay cell activity during spatial working memory has

been reported by several studies (Jung et al., 1998; Baeg et al., 2003; Spellman et al., 2015;

Bolkan et al., 2017). Importantly, however, these delay cells do not show preferential firing for a

particular sample location or a particular choice location, indicating the delay activity does not

represent task-relevant spatial information (Jung et al., 1998; Spellman et al., 2015; Bolkan et al.,

2017). One explanation that may reconcile the differences between findings in primates and

rodents, is the episodic-like nature of maze tests which involve encoding environmental cues

19

through exploration (Snigdha et al., 2013). This is not the case in primate working memory tests

where spatial cues tend to be discrete in nature (Carlson et al., 1997). Consistent with primate

studies, in a non-spatial DNMS task using discrete odour cues, Liu and colleagues (2014) found

population activity during the delay interval was distinct for different sample odours. Separation

between odour representations during the delay period was found only on correct trials. This

finding indicates mPFC delay activity carries odour information that is relevant for successful

working memory performance.

Thus, it is possible that during the delay period of spatial working memory tasks, spatial

information is maintained, not in the PFC, but in specialized structures such as the hippocampus.

In contrast, in non-spatial working memory tasks, stimulus representations may be accessed

within the delay activity of the mPFC, but higher-fidelity stimulus representations are ensured by

the delay activity of cortices involved in sensory processing (Pasternak and Greenlee, 2005; Lara

and Wallis, 2015). The function of mPFC delay activity may not be the maintenance of working

memory content per se.

Another important function of the PFC associated with working memory is to maintain selective

attention to task-relevant information (Curtis and D‘Esposito, 2003). PFC delay activity has been

found to reflect the use of attention (Lebedev et al., 2004; Gregoriou et al., 2009; Baluch and Itti,

2011; Stokes et al., 2013; Lara and Wallis, 2014; Kim et al., 2016). In the three-choice serial

reaction time task, which requires animals to maintain attention across a seconds long delay

interval to detect the presentation of a light cue, persistent delay activity has been observed in the

mPFC (Kim et al., 2016). The persistent activity during attention may involve similar neural

substrates as during working memory (Gazzaley and Nobre, 2012; Kerkoerle et al., 2017).

Furthermore, PFC delay activity during working memory has been found to be resistant to

distractors (Miller et al., 1996; Qi et al., 2010; Suzuki and Gottlieb, 2013) unlike that in sensory

cortices (Miller et al., 1993), a property critical for sustained attention. Furthermore, a lack of

delay activity in the mPFC has been observed when attentional demand is low during working

memory testing, such as in the case of overtraining (Liu et al., 2014). During learning of a

DNMS task, mPFC delay activity is present, however, after animals are well-trained, performing

above 90%, delay activity is no longer observed (Liu et al., 2014). It is possible that with

overtraining, flexible behaviour and attention are no longer required and performance becomes

habitual, depending more on dorsal striatal circuits and less on the mPFC (Smith and Graybiel,

20

2013). An alternative role for PFC delay activity may be in the maintenance of task rules

(Schmitt et al., 2017). In the two-alternative forced choice test (Wimmer et al., 2015), in which a

cue presented during sample indicates the rule for behavioral responding, mPFC cells show

preferential firing for a given rule during the brief delay (Schmitt et al., 2017).

Altogether, these findings suggest PFC delay activity may serve working memory maintenance,

by acting as a top-down mechanism to control processing in cortical structures that handle

sensory information. In addition to the delay period, increased PFC neural activity is observed

during stimulus sampling and behavioural responding (Jones and Wilson, 2005). Therefore,

deficits in these processes could also lead to working memory impairments.

1.5.4 Hippocampus – PFC Circuit in Working Memory

Interactions between the PFC and the HPC have been implicated in distinct working memory

phases. To understand the cause of working memory impairments in schizophrenia, it is critical

to consider the long-range PFC circuits supporting each working memory phase. The

hippocampus is a key structure supporting working memory and has been found to communicate

with the PFC during this process (Wang and Cai, 2006; Yoon et al., 2008). Lesions and

pharmacological manipulations of both the dHPC (Hock and Bunsey, 1998; Hampson et al.,

1999; McHugh et al., 2008), and vHPC (Floresco et al., 1997; Wilkerson and Levin, 1999; Levin

et al., 2002; Wang and Cai, 2006), impair working memory in rodents. However, a greater

number of studies measuring activity during working memory have focused on the dHPC.

The dHPC has been implicated in working memory involving spatial cues (Wible et al., 1986;

Hampson et al., 1993; Wiebe and Staubli, 1999), as well as non-spatial cues such as objects

(Macdonald et al., 2011), and odours (Hampson et al., 1999; Otto and Eichenbaum, 1992; Wood

et al., 1999; Macdonald et al., 2013). Neurons in the hippocampus exhibit cue-selective increases

in firing rate throughout the sample, delay, and response phases (Otto and Eichenbaum, 1992;

Hampson et al., 1999; Cahusac et al., 1989; Colombo and Gross, 1994; Wiebe and Staubli, 1999;

Wood et al., 1999; Macdonald et al., 2011). During the delay period in tasks in which rats remain

in a fixed location, activity in the dCA1 robustly codes for time (Pastalkova et al., 2008;

Macdonald et al., 2011; 2013; Kraus et al., 2013; Robinson et al., 2017). The activity of time

cells resembles mPFC delay activity in that single neurons fire briefly at a preferred temporal

distance from the start of the interval in a sequential order that as a population covers the entire

21

interval length (Pastalkova et al., 2008; Macdonald et al., 2011). Time cell activity during the

delay has been found to represent working memory content (Macdonald et al., 2011; Macdonald

et al., 2013), and is required for intact working memory performance (Robinson et al., 2017).

During the response phase, animals are required to retrieve the sample stimulus representation

from working memory and perform a match/nonmatch evaluation of the internal stimulus

representation against the external sensory stimulus. Therefore, cells that increase their activity

during the response period, selectively on either match or nonmatch trials, would likely play an

important role in the retrieval of working memory. Such cells have been observed in the dHPC,

and furthermore, their activity discriminates correct and incorrect trials (Sakurai, 1990b; Otto

and Eichenbaum, 1992; Wood et al., 1999; Wiebe and Staubli, 1999; Macdonald et al., 2013). A

specialized role for the dHPC in working memory retrieval is also supported by studies using T-

maze delayed-nonmatch-to-position (DNMP). LFP recordings in the CA1 have revealed an

increase in the power of gamma frequency oscillations selectively as animals approach the

choice point during the response phase but only during correct trials (Yamamoto et al., 2014).

Optogenetic inhibition (with ArchT) of medial entorhinal cortex (EC) projections in the dCA1

both attenuated this activity and impaired performance when inhibition took place during the

response phase and not during the sample phase. Thus, EC input to the dCA1 may allow these

structures to synchronize their activity at gamma frequency to support the retrieval of working

memory. Cells in the lateral EC also show selective firing for particular odours throughout the

sample, delay, and response phases of working memory (Young et al., 1997). This sensory

tuning suggests a role for the EC in maintaining and conveying stimulus representations that are

used by the hippocampus during encoding, maintenance, and retrieval (Young et al., 1997;

Wiebe and Staubli, 1999; Yamamoto et al., 2014; Robinson et al., 2017).

Studies examining synchronization between the hippocampus and PFC during working memory,

have found evidence for a critical interaction during the response phase. Both local mPFC theta

oscillations and phase-locking of neurons in the mPFC become synchronized with the dHPC

theta oscillation at the choice point (Jones and Wilson, 2005; Sigurdsson et al., 2010; O‘Neill et

al., 2013). This interaction is also stronger on correct trials when working memory is

appropriately used (Jones and Wilson, 2005; Sigurdsson et al., 2010; Hyman et al., 2010). HPC-

mPFC theta frequency synchronization has also been observed in maze tasks involving long-term

memory retrieval (Preston and Eichenbaum, 2013). During cue-reward or response direction

22

learning in the Y-maze, theta frequency coherence increases between the dHPC and PFC at the

choice point and correlates with task performance, similar to what is observed during working

memory in the T-maze (Benchenane et al., 2010). Therefore, HPC-mPFC theta frequency

synchronization at the choice point may generally reflect the retrieval of task-relevant

representations used to guide decision-making. Since major direct connections do not exist

between the dHPC and PFC (Degenetais et al., 2003; Hoover and Vertes, 2007; however see,

Barker et al., 2017), the functional connectivity between these structures during working

memory is likely facilitated by an intermediary structure, such as the EC, nucleus reunions of the

thalamus, or vHPC (Moser, 2010; Hoover and Vertes, 2012; Ito et al., 2015; Hallock et al., 2016;

O‘Neill et al., 2013).

Pyramidal cells in the vCA1 directly project to the mPFC (Jay and Witter, 1991; Hoover and

Vertes, 2007), where they synapse on pyramidal neurons and PV interneurons (Gabbot et al.,

2002). Activity along this pathway may reflect the delivery of spatial information regarding the

animal‘s current environment to the mPFC which then adjusts behaviour based on adaptive

goals. This function may account for findings of vHPC-mPFC communication during both

anxiety and working memory. Anxiety is commonly tested in the EPM, a task involving the

avoidance of open spaces and preference for closed protected spaces. In the EPM, theta power

synchronization between the vHPC and mPFC increases as animals decide to enter safe closed

arms and decreases in aversive open arms (Adhikari et al., 2010). Furthermore, vHPC cells that

project to the mPFC exhibit higher firing rates in the open arms (Ciocchi et al., 2015). Similarly,

cells in the mPFC exhibit task-related spatial correlates, preferentially firing in either the closed

or open arms (Adhikari et al., 2011). These task-modulated cells likely receive vHPC input since

they show significant phase-locking to vHPC theta oscillations, and inhibition of vHPC

projections in the mPFC abolished spatial tuning in the EPM (Adhikari et al., 2011; Padilla-

Coreano et al., 2016). These findings suggest representations of safe and aversive space in the

mPFC are mediated by input arriving from the vHPC. The vHPC may contribute in a similar

manner during spatial working memory in the T-maze. In this task, a significant proportion of

mPFC cells fire preferentially to the right or left goal arms (Spellman et al., 2015; Bolkan et al.,

2017). vHPC projections to the mPFC are critical for this spatial tuning during the sample phase,

as cells exhibiting spatial selectivity fire phase-locked to vHPC gamma oscillations and terminal

pathway inhibition disrupts mPFC spatial selectivity (Spellman et al., 2015; Bolkan et al., 2017).

23

Interestingly, during the response phase, spatially selective increases in the firing rate of mPFC

cells are observed at the choice point in anticipation of the animal‘s arm entry, however, this

activity is independent of the vHPC (Fujisawa et al., 2008; Bolkan et al., 2017; Spellman et al.,

2015). Therefore, the vHPC may be involved in relaying spatial information to the mPFC during

working memory encoding, while retrieval of spatial representations relies on mPFC interactions

with other structures such as the dHPC. This dynamic is supported by phase synchronization of

theta frequency oscillations between the dHPC, vHPC, and mPFC, as indicated by recordings

during a context-dependent rule retrieval task (Place et al., 2016). The vHPC likely does not

deliver purely spatial information to the mPFC, but instead conveys contextual information

processed for emotional behavioural relevance (Komorowski et al., 2013; Ciocchi et al., 2015;

Padilla-Coreano et al., 2016). A general function of the vHPC-mPFC circuit may be the use of

contextual information to guide behavioural strategies that satisfy the animal‘s current goal state

(Miller and Cohen, 2001), which may be seeking safety in the EPM or reward in the T-maze

DNMP.

Dysfunctional interactions between the hippocampus and PFC have been reported in

schizophrenia and in animal models of the disease (Uhlhaas and Singer, 2010; Sigurdsson and

Duvarci, 2016). Their functional connectivity both at rest (Zhou et al., 2008), and during

working memory testing have been found to be disrupted in schizophrenia (Meyer-Lindenberg et

al., 2005; Rassetti et al., 2011), with weaker connectivity correlating with poorer performance

and more severe symptoms (Henseler et al., 2010). Genetic and environmental models of

schizophrenia that involve microdeletions at the 22q11.2 locus, maternal immune activation, and

prenatal MAM treatment exhibit alterations in hippocampal-PFC synchrony (Sigurdsson et al.,

2010; Mukai et al., 2015; Dickerson et al., 2010; Phillips et al., 2017; Tamura et al., 2017),

which is also associated with working memory impairments (Sigurdsson et al., 2010; Mukai et

al., 2015).

1.6 Cognitive and Behavioural Function of GABA Interneurons

As reviewed thus far, diverse long-range interac

investigating the roles of parvalbumin and cholecystokinin … · 2018. 11. 19. · assisted in the...

Documents