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2 Animal Models on the rCPT: Parallels with Human CPT Data

2 Animal Models on the rCPT: Parallels with Human CPT Data

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Cognitive Translation Using the Rodent Touchscreen Testing …


mouse models, thereby demonstrating the tasks’ construct validity. For example,

conditional knockout of the NR1 subunit in corticolimbic GABAergic neurons

(Belforte et al. 2009) induces an acquisition deficit when the attentional load is

manipulated through shorter stimulus durations in the CPT (Hvoslef-Eide et al.

2013). Moreover, a chromosomal microdeletion at locus 22q11.2 is associated with

a high risk of developing schizophrenia (Schneider et al. 2014) and extensive

attentional deficits (Sobin et al. 2004) including CPT impairments (Shashi et al.

2010, 2012; Hooper et al. 2013; Harrell et al. 2013; Schoch et al. 2014). Hit

rate-related measures in the CPT can also predict the onset of prodromal psychotic

symptoms in individuals with 22q11.2 deletion syndrome (Antshel et al. 2010).

Critically, the Df(h22q11)/+ mouse model of the 22q11.2 microdeletion syndrome

shows a touchscreen CPT deficit that parallels the deficits of 22q11.2 deletion

syndrome patients. These impairments can be expressed on measures of hit rate, d’,

and c challenged with decreased stimulus presentation duration increased

inter-stimulus intervals, and extended session length (Nilsson et al. in preparation).

Thus, the observation of hit rate impairments in the Df(h22q11)/+ mutant parallels

the dysfunction of 22q11.2 deletion syndrome patients as measured by CPTs,

indicating translational validity of the task for assessing attentional functioning.


Vigilance Decrement in the rCPT

Human CPTs measure vigilance as observed by performance decrements across

session length (Rosvold et al. 1956; Nuechterlein 1983; Mass et al. 2000). Although

not often seen in the 5-CSRTT (but see Romberg et al. 2011), within-session performance decrements have been reported for alternative rodent–human translational

paradigms such as the 5-choice continuous performance task (Young et al. 2009a)

and the sustained attention task (Peters et al. 2011), and are also observed in mice

when using the rCPT (Kim et al. 2015). In mice with a C57BL/6 background, hit rates

and false alarms typically decrease with session length, which produce an elevated

response criterion towards the end of the session (Kim et al. 2015; Nilsson et al. in

prep). In mice with a DB2/2J background, hit rates have been found to decrease with

session length, while false alarm rate remains constant (Kim et al. 2015). Thus,

similar to humans, mice show decreased hit rates as a function of session length,

which suggests that the rCPT has translational utility as a measure of vigilance.


Relationship Between Task Parameters

and Performance Consistent Across Species

Manipulations of several task parameters have similar effects on CPT performance

in humans and mice. For example, manipulations of target probability (Berwid et al.


M. Hvoslef-Eide et al.

2005) and inter-stimulus intervals (Conners et al. 2003; Hervey et al. 2006; Epstein

et al. 2007) in human CPTs suggest that these parameters positively correlate with

false alarms rates and hit rates and hence have more pronounced effects on measures of response criterion (e.g. c) relative to discrimination sensitivity (e.g. d’;

Macmillan and Creelman 2004). Conversely, stimulus degradation manipulations

can produce larger perceptual sensitivity decrements relative to measures of

response criterion (Nuechterlein 1983; Chee et al. 1989; Mass et al. 2000).

Importantly, similar parametric manipulations of inter-stimulus intervals, stimulus

contrasts, stimulus duration, and target probabilities in the rCPT have comparable

effects on the performance of mice and rats (Kim et al. 2015; Nilsson et al. in prep;

Mar et al. in prep), which indicate that the parametric variables have comparable

relationships with performance measures across species. To summarise, performance of both rCPT and human CPT is sensitive to mPFC lesions and prefrontal

GABAergic dysfunction, dependent on the 22q11.2 chromosomal locus (or its

orthologous region in the mouse), and is influenced by manipulations of attentional

and perceptual load.

5 Reversal Learning









intradimensional/extradimensional (ID/ED) protocol in the CANTAB battery,

which has been used to generate a wealth of data in neurodegenerative and neuropsychiatric patients (Downes et al. 1989; Hughes et al. 1994; Pantelis et al. 1999;

Kempton et al. 1999; Shamay-Tsoory et al. 2007: Ceaser et al. 2008; Leeson et al.

2009). In reversal learning, subjects first learn a two-choice simultaneous discrimination and then, the stimulus contingencies are reversed (the correct stimulus

becomes the incorrect stimulus, and vice versa). Whereas reversal learning in

human and non-human primates most often is assessed using touchscreen methods

with visual stimuli (Dias et al. 1996; Bussey et al. 2001; Clarke et al. 2004; Leeson

et al. 2009), prevalent rodent analogues typically employ non-visual olfactory,

somatosensory (Schoenbaum and Chiba 1999; Birrell and Brown 2000; McAlonan

and Brown 2003), or spatial cues (Becker et al. 1981; Boulougouris et al. 2007).

Although non-touchscreen visual reversal learning tasks have been used with

rodents, these tests are typically non-automated (Gardner and Coate 1965; Stevens

and Fechter 1968; Sasaki 1969; Mullins and Winefield 1979; Mason et al. 1980) or

dependent on brightness discriminations (Abdul-Monim et al. 2003; Floresco et al.

2008) with limited resemblance to the automated tasks with complex visual stimuli

used with human and non-human primate subjects. To address these concerns, we

have developed a suite of rodent touchscreen reversal learning tasks and evaluated

their neurocognitive validity on anatomical, pharmacological, and genetic levels.

Here, we provide a few examples.

Cognitive Translation Using the Rodent Touchscreen Testing …



Orbitofrontal and Dorsal Striatal Perturbations Cause

Impairments of Touchscreen Reversal Learning

in Rodents, Non-Human Primates, and Humans

The orbitofrontal cortex (OFC) has been implicated in touchscreen reversal learning

in the mouse (Graybeal et al. 2011), rat (Chudasama and Robbins 2003; Izquierdo

et al. 2013; Alsiö et al. 2015), and non-human primate (Dias et al. 1996), mirroring

the findings of human imaging studies (Cools et al. 2002; Hampshire and Owen

2006; Clatworthy et al. 2009; Robinson et al. 2010; Hornak et al. 2004).

Chudasama and Robbins (2003) showed that quinolinic OFC lesions impair

touchscreen reversal learning in the rat by increasing the number of early errors.

Similarly, Alsiö and colleagues showed that temporary OFC inactivation impairs

touchscreen visual reversal learning in the rat by selectively increasing the number

of early errors and early response omissions (Alsiö et al. 2015). OFC lesions in the

rat also impair touchscreen reversal learning, and this deficit was interpreted as

more prominent when the animal had to adjust to negative feedback (Izquierdo

et al. 2013). In terms of the dorsal striatum, both mouse and human studies have

found the region to be critical for reversal learning (Graybeal et al. 2011; Robinson

et al. 2010).

It is important to note that OFC dependency in the rodent has also been observed

using more traditional tasks (Birrell and Brown 2000; Schoenbaum et al. 2002;

McAlonan and Brown 2003; Kim and Ragozzino 2005; Boulougouris et al. 2007;

Ghods-Sharifi et al. 2008; Bissonette et al. 2008; Castañé et al. 2010). This illustrates an important point: we are not arguing that it is impossible to achieve

effective translation using non-touchscreen tests in rodents. However, we do believe

that using similar, validated, and more reproducible tests across species can make

successful translation much more likely.


Serotonergic Manipulations Affect Both Rodent

and Human Touchscreen Reversal Learning

Demonstrations of cross-species parallels within reversal learning are not restricted

to the involvement of specific brain regions, but extend to a variety of signalling

systems (Frank and O’Reilly 2006; Robbins and Roberts 2007), perhaps most

notably serotonin (5-hydroxytryptamine, or 5-HT; Daw et al. 2002; Roberts 2011).

Acute tryptophan depletions in healthy subjects can impair touchscreen reversal

learning (Park et al. 1994; Rogers et al. 1999; but see Evers et al. 2005; Talbot et al.

2005; Finger et al. 2007; Cools et al. 2008), and behavioural genetic studies suggest

that 5-HT signalling efficacy is bidirectionally related to reversal learning performance in humans (den Ouden et al. 2013). Comparable effects have been observed

in non-touchscreen assays in the rodent with systemic pharmacological manipulations to 5-HT levels affecting bowl-digging (Lapiz-Bluhm et al. 2009), go/no-go


M. Hvoslef-Eide et al.

(Masaki et al. 2006), and spatial probabilistic reversal learning (Bari et al. 2010) in

the rat.

As in human studies, rodent touchscreen reversal learning has been shown to be

sensitive to pharmacological and genetic manipulations of 5-HT levels. In the

mouse, hetero- and homozygous deletions of the 5-HT transporter cause

dose-dependent elevations in cortical and striatal 5-HT levels (Mathews et al. 2004;

Daws 2006) and induce parallel dosage-dependent improvements in touchscreen

reversal learning observed as decreases in trials and errors to criterion (Brigman

et al. 2010). Moreover, pharmacologically induced elevation of cortical 5-HT

through subchronic fluoxetine treatment (Cryan et al. 2004) decreases trials and

incorrect responses to criterion during the early phase of learning when responding

is biased towards the previously correct stimulus (Brigman et al. 2010). Taken

together, there are clear demonstrations of translation between the rodent, monkey,

and human with regard to both specific regions and neurotransmitter systems

central for reversal learning.


Cross-Species Impairments in Touchscreen Reversal

Learning Following a Disc Large 2 Mutation

As part of the touchscreen test battery assessment of the Dlg2 gene knockout mouse

previously mentioned, visual reversal learning was assessed (Nithianantharajah

et al. 2012a, b). In a clear example of cross-species translation, both human carriers

of the Dlg2 mutation and Dlg2−/− mice showed comparable deficits in touchscreen

visual reversal learning, observed as a decrease in accuracy during early sessions,

suggesting impairments in behavioural inhibition/cognitive flexibility

(Nithianantharajah et al. 2012a, b).

6 Limitations and Challenges

These examples demonstrate how touchscreen behavioural paradigms can be

readily translatable between human participants and rodents. Like any method,

these protocols nevertheless contain limitations—many of which are the focus of

refinement in ongoing experiments. For example, some rodent touchscreen tasks

may require extensive training (e.g. PAL, 5-CSRTT). However, many

non-touchscreen tasks of complex cognition also require lengthy training, and

furthermore, touchscreen automation allows the parallel testing of numerous animals at once, mitigating the time cost of extensive training. A major challenge for

touchscreen translation is to experimentally demonstrate neurocognitive validity for

every rodent touchscreen test and its human counterpart—but again, this challenge

is not specific to touchscreens, and validation of the touchscreen tests is ongoing.

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