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Longitudinal attentional engagement rescues mice from age-related cognitive declines and cognitive inflexibility
Abstract
Learning, attentional, and perseverative deficits are characteristic of cognitive aging. In this study, genetically diverse CD-1 mice underwent longitudinal training in a task asserted to tax working memory capacity and its dependence on selective attention. Beginning at 3 mo of age, animals were trained for 12 d to perform in a dual radial-arm maze task that required the mice to remember and operate on two sets of overlapping guidance (spatial) cues. As previously reported, this training resulted in an immediate (at 4 mo of age) improvement in the animals' aggregate performance across a battery of five learning tasks. Subsequently, these animals received an additional 3 d of working memory training at 3-wk intervals for 15 mo (totaling 66 training sessions), and at 18 mo of age were assessed on a selective attention task, a second set of learning tasks, and variations of those tasks that required the animals to modify the previously learned response. Both attentional and learning abilities (on passive avoidance, active avoidance, and reinforced alternation tasks) were impaired in aged animals that had not received working memory training. Likewise, these aged animals exhibited consistent deficits when required to modify a previously instantiated learned response (in reinforced alternation, active avoidance, and spatial water maze). In contrast, these attentional, learning, and perseverative deficits were attenuated in aged animals that had undergone lifelong working memory exercise. These results suggest that general impairments of learning, attention, and cognitive flexibility may be mitigated by a cognitive exercise regimen that requires chronic attentional engagement
... Experimental animal studies allow the more detailed investigation of the neural mechanisms that underlie the effects of WM training, which could help us better understand the controversial results of WM training studies. However, the application of similar WM training paradigms in animals, as described previously for humans, has been very limited (Chung et al., 2019;Stavroulaki et al., 2020;Light et al., 2010;Matzel et al., 2011;Waddell and Mooney, 2017). Studies have investigated the changes in neural activity during learning of WM tasks in both non-human primates (Qi and Constantinidis, 2013;Zhou et al., 2016) and rodents (Liu et al., 2014;Kirschmann et al., 2019). ...
... All of the above studies were conducted in young rodents, aged 2 months to 8 months-old. The effect of WM training in aged mice (18-month-old) was also examined and the results showed that long-term WM training from young adulthood reversed the age-induced deficits in reversal learning and selective attention of aged mice (Matzel et al., 2011). ...
... Beneficial effects of WM training in cognitive flexibility are also present in rodents (Light et al., 2010;Stavroulaki et al., 2020) (Fig. 1). Even in older mice, WM training from young adulthood until old age could alleviate or prevent the age-induced deficits in cognitive flexibility (Matzel et al., 2011). Therefore, human, non-human primate and rodent studies are complementary and the field of WM training could significantly benefit from translational studies. ...
Working memory refers to a cognitive function that provides temporary storage and manipulation of the information necessary for complex cognitive tasks. Due to its central role in general cognition, several studies have investigated the possibility that training on working memory tasks could improve not only working memory function but also increase other cognitive abilities or modulate other behaviors. This possibility is still highly controversial, with prior studies providing contradictory findings. The lack of systematic approaches and methodological shortcomings complicates this debate even more. This review highlights the impact of working memory training at different ages on humans. Finally, it demonstrates several findings about the neural substrate of training in both humans and experimental animals, including non-human primates and rodents.
... Similar to humans, rodents show age-related memory decline, specifically in reference memory (RM), a type of long-term memory where information remains constant, and working memory (WM), a type of shortterm memory where information needs to be updated. Numerous studies have demonstrated RM and WM decline with age in rodents (Ando and Ohashi, 1991;Barnes et al., 1980;Bimonte et al., 2003;Chrobak et al., 1995;Frick et al., 1995;Matzel et al., 2011;Pitsikas and Algeri, 1992;Talboom et al., 2008;Wellman and Pelleymounter, 1999). Studies evaluating cognitive practice in animals have demonstrated that male rats receiving practice on the spatial RM Morris maze for five days at 12 months of age performed better at 24 months of age on this practice task, as compared to age-matched controls that had received no practice. ...
... Thus, cognitive practice on multiple WM and RM maze tasks may not protect against age-related WM decline, as tested in the radial-arm maze, for male rats. More recent longitudinal research found that extensive WM practice on a modified radial-arm maze in mice from 3 to 18 months of age conferred an attenuation of age-related learning and attentional deficits evaluated by a battery of tasks when the mice were aged (Matzel et al., 2011). ...
... Rats were tested on the WM land radial-arm maze from 3-11 months of age; when 21.5 months of age, the experienced rats performed as well as young control animals (Bierley et al., 1986). More recent longitudinal research found that extensive WM cognitive practice on a modified radial-arm maze in mice from 3 to 18 months of age conferred an attenuation of age-related learning and attentional deficits evaluated by a battery of tasks when the mice were aged (Matzel et al., 2011). ...
Cognitive function is multidimensional and complex, and research indicates that it is impacted by age, lifetime experience, and ovarian hormone milieu. One particular domain of cognitive function that is susceptible to age-related decrements is spatial memory. Cognitive practice can affect spatial memory when aged in both males and females, and in females alone ovarian hormones have been found to alter spatial memory via modulating brain microstructure and function in many of the same brain areas affected by aging. The research in this dissertation has implications that promote an understanding of the effects of cognitive practice on aging memory, why males and females respond differently to cognitive practice, and the parameters and mechanisms underlying estrogen’s effects on memory. This body of work suggests that cognitive practice can enhance memory when aged and that estrogen is a probable candidate facilitating the observed differences in the effects of cognitive practice depending on sex. This enhancement in cognitive practice effects via estrogen is supported by data demonstrating that estrogen enhances spatial memory and hippocampal synaptic plasticity. The estrogen-facilitated memory enhancements and alterations in hippocampal synaptic plasticity are at least partially facilitated via enhancements in cholinergic signaling from the basal forebrain. Finally, age, dose, and type of estrogen utilized are important factors to consider when evaluating estrogen’s effects on memory and its underlying mechanisms, since age alters the responsiveness to estrogen treatment and the dose of estrogen needed, and small alterations in the molecular structure of estrogen can have a profound impact on estrogen’s efficacy on memory.
Collectively, this dissertation elucidates many parameters that dictate the outcome, and even the direction, of the effects that cognitive practice and estrogens have on cognition during aging. Indeed, many parameters including the ones described here are important considerations when designing future putative behavioral interventions, behavioral therapies, and hormone therapies. Ideally, the parameters described here will be used to help design the next generation of interventions, therapies, and nootropic agents that will allow individuals to maintain their cognitive capacity when aged, above and beyond what is currently possible, thus enacting lasting improvement in women’s health and public health in general.
... For example, short-term working memory training in young adult mice enhanced selective attention and performance on a battery of tests (Light et al., 2010). Furthermore, long-term cognitive training in rodents benefitted later performance on tasks assessing working and reference memory, as well as selective attention (Bierley et al., 1986;Markowska and Savonenko, 2002;Matzel et al., 2011;Vicens et al., 2003); these effects do not appear to depend on visual acuity or swimming ability (Markowska and Savonenko, 2002), but do transfer to novel and/or untrained tasks and novel cognitive domains (Light et al., 2010;Matzel et al., 2011). Most of this research has evaluated males; in fact, only one rodent study has evaluated females, and there was no male comparison group (Ando and Ohashi, 1991). ...
... For example, short-term working memory training in young adult mice enhanced selective attention and performance on a battery of tests (Light et al., 2010). Furthermore, long-term cognitive training in rodents benefitted later performance on tasks assessing working and reference memory, as well as selective attention (Bierley et al., 1986;Markowska and Savonenko, 2002;Matzel et al., 2011;Vicens et al., 2003); these effects do not appear to depend on visual acuity or swimming ability (Markowska and Savonenko, 2002), but do transfer to novel and/or untrained tasks and novel cognitive domains (Light et al., 2010;Matzel et al., 2011). Most of this research has evaluated males; in fact, only one rodent study has evaluated females, and there was no male comparison group (Ando and Ohashi, 1991). ...
... Therefore, for male and female rats, this study was designed to evaluate the following: (1) whether the effects of cognitive training were due to cognitive demand and/or the procedural components of testing; and (2) whether effects were limited to the trained cognitive domain or if they transferred to an untrained cognitive domain. Two recent studies found that cognitive demand is indeed necessary for the effects of cognitive training to be realized, and that benefits can transfer to novel tasks and novel cognitive domains (Light et al., 2010;Matzel et al., 2011); however, both studies evaluated only male mice. Furthermore, given the human literature suggesting that cognitive ability (Whalley et al., 2000) or cognitive reserve (Snowdon, 2003) impacts cognitive status when aged, we also assessed whether performance during the first cognitive training session when young related to later performance when aged. ...
... For this purpose, we utilized a Dual Radial Arm Maze (DRAM).Fig. 1 provides a detailed description of this apparatus. Training in this task has previously been determined to improve both attentional and general learning performance [23,24]. The DRAM featured 16 arms (length: 40 cm) extending radially from a central hub (diameter: 20 cm). ...
... For instance, Jaeggi et al. [21] reported that training on a complex working memory task yielded improvements in tests of human intelligence performance (also see [22]). In laboratory mice, Light et al. [23] demonstrated that extensive working memory practice promoted an improvement in animals' aggregate performance across a battery of diverse learning tasks, and Matzel et al. observed that chronic (life-long) working memory practice protected animals from normal age-related cognitive declines [24]. Nevertheless, the beneficial effects of working memory training have typically been small and often do not transfer universally to all cognitive tasks (for reviews, see [25,26]), leading to the conclusion that working memory and intelligence should not be considered as synonymous constructs. ...
... Fig. 1 provides a detailed description of this apparatus. Training in this task has previously been determined to improve both attentional and general learning performance [23,24]. The DRAM featured 16 arms (length: 40 cm) extending radially from a central hub (diameter: 20 cm). ...
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Burkart et al.'s impressive synthesis will serve as a valuable resource for intelligence research. Despite its strengths, the target article falls short of offering compelling explanations for the evolution of intelligence. Here, we outline its shortcomings, illustrate how these can lead to misguided conclusions about the evolution of intelligence, and suggest ways to address the article's key questions.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Here, we specifically discuss why and to what extent we agree with Burkart et al. about the coexistence of general intelligence and modular cognitive adaptations, and why we believe that the distinction between primary and secondary modules they propose is indeed essential.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
We welcome the cross-disciplinary approach taken by Burkart et al. to probe the evolution of intelligence. We note several concerns: the uses of g and G , rank-ordering species on cognitive ability, and the meaning of general intelligence. This subject demands insights from several fields, and we look forward to cross-disciplinary collaborations.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Are the mechanisms underlying variations in the performance of animals on cognitive test batteries analogous to those of humans? Differences might result from procedural inconsistencies in test battery design, but also from differences in how animals and humans solve cognitive problems. We suggest differentiating associative-based ( learning ) from rule-based ( knowing ) tasks to further our understanding of cognitive evolution across species.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
The goal of our target article was to lay out current evidence relevant to the question of whether general intelligence can be found in nonhuman animals in order to better understand its evolution in humans. The topic is a controversial one, as evident from the broad range of partly incompatible comments it has elicited. The main goal of our response is to translate these issues into testable empirical predictions, which together can provide the basis for a broad research agenda.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Burkart et al. present a paradox – general factors of intelligence exist among individual differences ( g ) in performance in several species, and also at the aggregate level ( G ); however, there is ambiguous evidence for the existence of g when analyzing data using a mixed approach, that is, when comparing individuals of different species using the same cognitive ability battery. Here, we present an empirical solution to this paradox.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
The authors evaluate evidence for general intelligence ( g ) in nonhumans but lean heavily toward mammalian data. They mention, but do not discuss in detail, evidence for g in nonmammalian species, for which substantive material exists. I refer to a number of avian studies, particularly in corvids and parrots, which would add breadth to the material presented in the target article.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Across taxonomic subfamilies, variations in intelligence ( G ) are sometimes related to brain size. However, within species, brain size plays a smaller role in explaining variations in general intelligence ( g ), and the cause-and-effect relationship may be opposite to what appears intuitive. Instead, individual differences in intelligence may reflect variations in domain-general processes that are only superficially related to brain size.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
Conceptualizing intelligence in its biological context, as the expression of manifold adaptations, compels a rethinking of measuring this characteristic in humans, relying also on animal studies of analogous skills. Mental manipulation , as an extension of object manipulation, provides a continuous, biologically based concept for studying G as it pertains to individual differences in humans and other species.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination, and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention Matzel et al. 2011a) and working memory (particularly working memory capacity: Kolata et al. 2005;Matzel et al. 2008;Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). ...
... For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping": Wass et al. 2012). Working memory training did increase g Matzel et al. 2011a), mainly through its positive effect on selective attention ; see also Sauce et al. 2014). Importantly, g did not simply capture fear and stress reactivity (Matzel et al. 2006), anxiety (Galsworthy et al. 2002), or other lower-level biological processes such as sensory or motor abilities (Matzel et al. 2006). ...
... Working memory and general intelligence are highly co-regulated (Engle et al. 1999; Conway et al. 2003; Colom et al. 2004), but the mechanisms that underlie this co-regulation have been difficult to assess in humans (Jensen 1998; Deary et al. 2009, 2010). Much like humans, the efficacy of an animal's working memory is correlated with, and may be a causal determinant of, general cognitive abilities (GCAs) (Kolata et al. 2007; Light et al. 2010; Matzel et al. 2011). Here we assessed whether innate GCA (as determined by an animal's aggregate performance across a diverse set of five learning tasks) and the beneficial influence of working memory training (WMT) on GCA shared a common substrate and target. ...
... Furthermore, it has been suggested that working memory training (with high attentional demands) can positively impact an individual's performance on tests of fluid intelligence (Jaeggi et al. 2008; Tang and Posner 2009; Buschkuehl and Jaeggi 2010), and can produce functional changes in D1 dopaminergic binding in the prefrontal cortex (Olesen et al. 2004; McNab et al. 2009; Fischer et al. 2010). Although the interpretation of " working memory training " studies is highly controversial (Chooi and Thompson 2012; Shipstead et al. 2012; Redick et al. 2013), we have repeatedly observed that training procedures that tax working memory capacity and selective attention reliably improve the attentional performance of mice (Light et al. 2010; Matzel et al. 2011), and this facilitation of attention can promote performance on at least some of the tests that comprise our learning battery (see below). ...
A common source of variance (i.e., "general intelligence") underlies an individual's performance across diverse tests of cognitive ability, and evidence indicates that the processing efficacy of working memory may serve as one such source of common variance. One component of working memory, selective attention, has been reported to co-vary with general intelligence, and dopamine D1 signaling in prefrontal cortex can modulate attentional abilities. Based on their aggregate performance across five diverse tests of learning, here we characterized the general cognitive ability (GCA) of CD-1 outbred mice. In response to a D1 agonist (SKF82958, 1 mg/kg), we then assessed the relationship between GCA and activation of D1 receptor (D1R)-containing neurons in the prelimbic region of the medial prefrontal cortex, the agranular insular cortex, and the dorsomedial striatum. Increased activation of D1R-containing neurons in the prelimbic cortex (but not the agranular insular cortex or dorsomedial striatum) was observed in animals of high GCA relative to those of low GCA (quantified by c-Fos activation in response to the D1 agonist). However, a Western blot analysis revealed no differences in the density of D1Rs in the prelimbic cortex between animals of high and low GCA. Last, it was observed that working memory training promoted an increase in animals' GCA and enhanced D1R-mediated neuronal activation in the prelimbic cortex. These results suggest that the sensitivity (but not density) of D1Rs in the prelimbic cortex may both regulate GCA and be a target for working memory training.
... " Whereas humans regularly use working memory in their day-to-day lives (thus minimizing the impact of laboratory manipulations), laboratory animals lead sterile lives (less dependent on working memory) and can be exposed to intense levels of training. To assess the causal relationship between working memory and general learning abilities in mice, we (Light et al., 2010;Matzel et al., 2011) provided mice with working-memory " exercise " by training them (over a period of weeks) in the dual-maze task described in the last paragraph. This training promoted an improvement in working memory, attention, and aggregate performance across a six-task learning battery. ...
... In biological associations, from left to right: imaging represents studies in humans in which working-memory performance and performance on IQ tests commonly activate the prefrontal cortex (Cohen et al., 1997 ;Gazzaley, Cooney, McEvoy, Knight, & D'Esposito, 2005 ;Rowe, Toni, Josephs, Frackowiak, & Passingham, 2000); modeling represents computer models suggesting that dopaminergic inputs in the prefrontal cortex protect activity ( " stored information " ) from interference during working-memory tasks (Durstewitz et al., 2000); microarray shows that high-intelligence mice have increased expression in the prefrontal cortex of the gene Drd1a that codes for dopamine D1 receptors (Kolata et al., 2010); immunohistochemistry shows that high-intelligence mice have increased neuronal activity in the prefrontal cortex induced by D1 agonists ( C. D.Wass et al., in press). The top panels represent influences from working memory, which include controversial studies of working-memory training in humans (represented with a dashed line;Buschkuehl & Jaeggi, 2010 ;Jaeggi, Buschkuehl, Jonides, & Perrig, 2008 ;Jaeggi, Buschkuehl, Jonides, & Shah, 2011 ;Tang & Posner, 2009), as well as evidence from mice indicating that working-memory training promotes attention, which in some instances positively affects learning performance (Light et al., 2010 ;Matzel et al., 2011). memory are engaged by many of the same tasks used to estimate intelligence. ...
An individual’s performance across multiple cognitive tests tends to co-vary. This ubiquitous observation suggests that various cognitive domains are regulated in common, and this co-variance underlies the interpretation of many quantitative tests of “intelligence”. As in humans, we find that differences in intelligence exist across genetically heterogeneous mice. Specifically, we have observed a co-variance in the performance of mice across diverse tests of learning, reasoning, and attention. As in humans, the processing efficacy of working memory is both correlated with animals’ general cognitive ability and may in some instances serve to regulate behaviors indicative of intelligence. Beyond its axiomatic significance in demonstrating the evolutionary conservation of a cognitive trait, studies of mice may provide unique opportunities to assess the molecular (e.g., brain-specific RNA expression; transgenics) and neuroanatomic substrates for intelligence. One such approach will be briefly described here, with which we have determined that the signaling efficacy of the dopamine D1 receptor in the prefrontal cortex is one potential link between performance on both working memory tasks and tests of intelligence. In combination, studies of both humans and non-human animals provide converging lines of evidence that might evade either approach in isolation.
... This procedure, called reversal, was sufficient to uncover a deficit in flexibility in mutant adult mice as they were unable to adapt their strategy. This deficit was also evident when mice were retested at middle age, indicating that the early deficit of Vangl2 is consistent with an advanced onset of a decrease in flexibility otherwise observed with normal aging in mice (Matzel et al., 2011;Yang et al., 2019), rats (Mota et al., 2019), non-human primates (Joly et al., 2014) and humans (van Boxtel et al., 1998). It is also interesting to highlight that although repeated training improved performances in control mice, mutant mice did not benefit from this previous training suggesting that they did not remember the task. ...
Decline in episodic memory is one of the hallmarks of aging and represents one of the most important health problems facing western societies. A key structure in episodic memory is the hippocampal formation and the dentate gyrus in particular, as the continuous production of new dentate granule neurons in this brain region was found to play a crucial role in memory and in age-related decline in memory. As such, understanding the molecular processes that regulate the relationship between adult neurogenesis and aging of memory function holds great therapeutic potential. Recently, we found that Vang-gogh like 2 (Vangl2), a core component of the planar cell polarity signaling pathway, is enriched in the dentate gyrus of adult mice. In this context, we sought to evaluate the involvement of this effector of the Wnt/PCP pathway in both adult neurogenesis and memory abilities in adult and middle-aged mice. Using a heterozygous mouse model carrying a dominant negative mutation in Vangl2 gene, we show that alteration in Vangl2 expression decreases the survival of adult-born granule cells and advances the onset of decrease in cognitive flexibility. Inability of mutant mice to erase old irrelevant information to the benefit of new relevant ones highlights a key role of Vangl2 in interference-based forgetting. Taken together, our findings show for the first that Vangl2 activity may constitute an interesting target to prevent age-related decline in hippocampal plasticity and memory.
... Those data will not be reported here). These tasks are described in detail elsewhere (Matzel et al., 2003;Matzel et al., 2006;Matzel et al., 2011), and will be described in brief below. ...
Most quantifiable traits exhibit some degree of heritability. The heritability of physical traits is often high, but
the heritability of some personality traits and intelligence can also be highly heritable. Importantly, estimates of
heritability can change dramatically depending on such variables as the age or the environmental history of the
sample from which the estimate is obtained. Interpretation of these changing estimates is complicated in studies
of humans, where (based on correlational observations) environmental variables are hard to directly control or
specify. Using laboratory mice, here we could control specific environmental variables. We assessed 58 groups of
four full sibling male CD-1 genetically heterogeneous mice (n=232). Using a standard full-sibling analysis,
physical characteristics (body weight and brain weight) were highly heritable (h of body weight=0.66 on a 0–1
scale), while behaviors indicative of a personality trait (exploration/boldness) and learning abilities (in a passive
avoidance and egocentric maze task) were weakly-to-moderately heritable. Half of the siblings from each set of
four were housed in an “enriched” environment, which provided extensive and varied opportunities for exploration.
This enrichment treatment promoted improvements in learning and a shift toward a more bold personality
type. Relative to animals in control (“impoverished” environments), the history of enrichment had
significant impact on estimates of heritability. In particular, the heritability of behaviors related to the personality
trait (exploration/boldness) more than doubled, and a similar increase was observed for learning (in the
passive avoidance task). Physical traits (brain and body weight), however, were insensitive to environmental
history (where in both environments, animals received the same diet). These results indicate that heritable traits
can be responsive to variations in the environment, and moreover, that estimates of heritability of learning and
personality traits are strongly influenced by environments that modulate those traits.
... This possibility is particularly exciting in light of evidence that rate of receptor turnover is use-dependent, and can thus account for the effects on D1 receptor sensitivity of working memory training (e.g. 36 ), which can be effective as a means to mitigate cognitive aging 37,38 . ...
In both humans and mice, performance on tests of intelligence or general cognitive ability (GCA) is related to dopamine D1 receptor-mediated activity in the prelimbic cortex, and levels of DRD1 mRNA predict the GCA of mice. Here we assessed the turnover rate of D1 receptors as well as the expression level of the D1 chaperone protein (DRiP78) in the medial PPC (mPFC) of mice to determine whether rate of receptor turnover was associated with variations in the GCA of genetically heterogeneous mice. Following assessment of GCA (aggregate performance on four diverse learning tests) mice were administered an irreversible dopamine receptor antagonist (EEDQ), after which the density of new D1 receptors were quantified. GCA was positively correlated with both the rate of D1 receptor recovery and levels of DRiP78. Additionally, the density of D1 receptors was observed to increase within 60 min (or less) in response to intense demands on working memory, suggesting that a pool of immature receptors was available to accommodate high cognitive loads. These results provide evidence that innate general cognitive abilities are related to D1 receptor turnover rates in the prefrontal cortex, and that an intracellular pool of immature D1 receptors are available to accommodate cognitive demands.
... Thus, although it is indisputable that aging is associated with a decline in general cognitive capacity, it is interesting to speculate that some of the age-related decline in cognitive capacity can be overcome by "cognitive training" and other environmental manipulations. While direct evidence with humans is still incomplete ( Kramer et al., 2004), supporting experimental evidence has been obtained with laboratory animals ( Markowska & Savonenko, 2002a, 2002bMatzel et al., 2011;Matzel, Wass, Kolata, Light, & Colas, 2009;Tranter & Koutstaal, 2008). ...
Intelligence can have an extremely high heritability, but also be malleable; a paradox that has been the source of continuous controversy. Here we attempt to clarify the issue, and advance a frequently overlooked solution to the paradox: Intelligence is a trait with unusual properties that create a large reservoir of hidden gene–environment (GE) networks, allowing for the contribution of high genetic and environmental influences on individual differences in IQ. GE interplay is difficult to specify with current methods, and is underestimated in standard metrics of heritability (thus inflating estimates of “genetic” effects). We describe empirical evidence for GE interplay in intelligence, with malleability existing on top of heritability. The evidence covers cognitive gains consequent to adoption/immigration, changes in IQ’s heritability across life span and socioeconomic status, gains in IQ over time consequent to societal development (the Flynn effect), the slowdown of age-related cognitive decline, and the gains in intelligence from early education. The GE solution has novel implications for enduring problems, including our inability to identify intelligence-related genes (also known as IQ’s “missing heritability”), and the loss of initial benefits from early intervention programs (such as “Head Start”). The GE solution can be a powerful guide to future research, and may also aid policies to overcome barriers to the development of intelligence, particularly in impoverished and underprivileged populations.
... It is indeed paralleled by improvement in other cognitive functions, even fluid intelligence, and allows moving the acquired skills from training to other contexts (Jaeggi et al., 2008;Sternberg, 2008). Nevertheless, studies on animals showed that task based on memory induced better learning in mice under novel training conditions in the future (Light et al., 2010), and if practiced during lifespan protects animals from typical age-related cognitive decline (Matzel et al., 2011). Several data suggest that this process has a positive impact on neuronal survival after training in central cerebral region, mainly in the hippocampus (Shors et al., 2012). ...
The cognitive impairment characterizing the phenotype of older adults has been related to the efficiency of the antioxidant system. This study aimed at investigating the effect of memory training (MT) on memory, global cognitive functioning, and the oxidant and antioxidant capacity of plasma. We recruited 52 healthy subjects aged over 60. Twenty-nine subjects were submitted to 6-months of MT (Experimental Group, EG), and 23 were used as a Control Group (CG). Global cognitive functioning was assessed by the Mini-Mental State Examination (MMSE) and Short and Long Term Memory (STM and LTM, respectively) by the Rey Auditory Verbal Learning Test (RAVLT) at baseline (T0) and after 6-months (T1). Meanwhile, Reactive Oxygen Metabolites derivative compounds (d-ROMs), Biological Antioxidant Potential (BAP), and their ratio were evaluated on plasma. Results showed that the MMSE and RAVLT scores improved in EG at T1. At the same time, the d-ROMs levels significantly decreased, while the BAP and BAP/d-ROMs ratio showed an opposite trend. In both groups, the MMSE and LTM scores were negatively associated with d-ROMs levels, and positively correlated with BAP levels and the BAP/d-ROMs ratio. When we considered the Δvalue (Δvariable=variable post-MT minus variable pre-MT) in EG, the ΔMMSE and ΔLTM scores were negatively associated to Δd-ROMs, and positively to ΔBAP and ΔBAP/dROM. In conclusion, our results suggest that MT improves memory and global cognitive functioning. These processes were significantly associated to increase in resistance against oxidative stress at the plasma level in healthy older adults.
... However, in the largest human brain-training study of its kind on over 11,400 participants, Owen et al. (2010) showed that, whereas a subject's performance on a trained CGT improved over a six-week period, their performance did not transfer to similar untrained CGTs. In animals, Matzel et al. (2011) found that general cognitive decline in aging mice was reduced by life-long working memory exercises (navigation of 3D mazes). Most cognitive tasks provided to rats and dogs have been spatial (i.e., mazes and obstacle courses); therefore, it is difficult to determine whether cognitive performance in these cases is enhanced by "using the body" or "using the brain", or indeed both. ...
“Cognitive enrichment” is a subset of enrichment that has gained interest from researchers over the past decade, particularly those working in zoos. This review explores the forms of cognitive enrichment that have been attempted for laboratory, farmed and zoo animals with a focus on the latter, including various definitions, aims, and approaches. This review reveals the fundamental theoretical and practical problems associated with cognitive enrichment, leading to recommendations for further research in this field. Critically, more research is needed to elucidate what makes challenges appropriate for certain taxa, acknowledging that individual differences exist. Going forward, we should be prepared to incorporate more computer technology into cognitive tasks, and examine novel welfare indicators such as flow, competence, and agency.
... Cognitive flexibility is acquired in infancy and continues to be critical for cognitive functions throughout life. While the precise etiology of impaired cognitive flexibility, i.e., cognitive inflexibility, is not known, it can occur with aging and also as a result of drug abuse and addiction [6][7][8] . Additionally, cognitive inflexibility is a key symptom of neuropsychiatric conditions of developmental origin including schizophrenia, autism spectrum disorder, attention deficit hyperactivity disorder, and obsessive compulsive disorder [3,4,[9][10][11] . ...
Prenatal cocaine exposure remains a major public health concern because of its adverse impact on cognitive function in children and adults. We report that prenatal cocaine exposure produces significant deficits in reversal learning, a key component of cognitive flexibility, in a mouse model. We used an olfactory reversal learning paradigm and found that the prenatally cocaine-exposed mice showed a marked failure to learn the reversed paradigm. Because brain-derived neurotrophic factor (BDNF) is a key regulator of cognitive functions, and because prenatal cocaine exposure increases the expression of BDNF and the phosphorylated form of its receptor, tyrosine kinase B (TrkB), we examined whether BDNF-TrkB signaling is involved in mediating the reversal learning deficit in prenatally cocaine-exposed mice. Systemic administration of a selective TrkB receptor antagonist restored normal reversal learning in prenatally cocaine-exposed mice, suggesting that increased BDNF-TrkB signaling may be an underlying mechanism of reversal learning deficits. Our findings provide novel mechanistic insights into the reversal learning phenomenon and may have significant translational implications because impaired cognitive flexibility is a key symptom in psychiatric conditions of developmental onset.
... Test batteries often include typical, rather basic learning tasks, such as associative fear conditioning, operant avoidance, path integration, odor discrimination and spatial navigation. Nevertheless, as in humans, the derived g factors have been shown to covary with executive functions, such as selective attention (Kolata et al. 2007; Matzel, Light, Wass, Colas-Zelin, Denman-Brice, Waddel & Kolata 2011) and working memory (in particular working memory capacity: Kolata et al. 2005; Matzel et al. 2008; Sauce et al. 2014) as well as performance in tests of reasoning. For instance, g derived from a standard mouse test battery predicted performance in inductive (finding efficient search strategies in a complex maze) and deductive reasoning (inferring the meaning of a novel item by exclusion, i.e. " fast mapping " : Wass et al. 2012). ...
The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this puzzle, and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals (rodents and primates). However, the interpretation of a psychometric g-factor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength.
... The flexibility in decision-making in this study was not affected by any characteristics of the participants, even age or quantity of clinical experience. In general, more experience may be expected to facilitate inflexible thinking, due to the way it strengthens restrictions on one's decision-making domain [18]. However, in this study, the older participants demonstrated flexibility in their decision-making based on information received in lectures, with no significant difference observed in this parameter relative to the younger group. ...
Purpose:
Decision-making by dental and medical experts can be influenced by their biases, interests, and experiences, and academic arguments about controversial issues may additionally be considered indirect experiences capable of affecting decision-making. This study reports on the use of interactive communication devices to evaluate preferences and flexibility in decision-making among dental care providers who attended two distinct academic conferences.
Methods:
Two debates were presented by a team of two lecturers at two academic conferences (focusing on periodontology and implant dentistry, respectively) and the audience members of each session were surveyed. Before each lecture, two case modules about the diagnosis and treatment of multirooted molar lesions were provided, and interactive communication devices were used to collect responses about decision-making preferences in treatment planning immediately before and after a debate about treatment strategies.
Results:
In total, 81 and 84 completed answers from both conferences were obtained for the first and second case modules, respectively. The preferred treatment plan differed significantly according to the focus of the conference, and a tendency emerged for the clinicians participating in each conference to express uniform preferences. However, attending the debates resulted in significant changes in decision-making preferences regardless of the conference focus or the characteristics of the participants.
Conclusions:
Our findings suggest that providing continuing education via debates on controversial issues may be effective in widening conceptual knowledge and reducing biases among experts in the dental and medical fields.
... Multimodal studies that incorporate numerous methodologies could help ameliorate some of these problems, although these would still be associational studies. The development of human laboratory studies (Sinha, in press), animal models of mindfulness (seeMatzel et al., 2011for a description of an animal model of " attentional engagement " ), and longitudinal, randomized, clinical trials that include pre-and postmultimodal imaging and psychophysiological assessments are all needed to test the hypothesized neurobiological mechanisms proposed in the current review. Unpacking the brain– behavior mechanisms of change following mindfulness training will require research that addresses the ongoing debate on how to operationalize mindfulness, particularly as it relates to the treatment of addiction (seeDiClemente, 2010). ...
Addiction has generally been characterized as a chronic relapsing condition (Leshner, 1999). Several laboratory, preclinical, and clinical studies have provided evidence that craving and negative affect are strong predictors of the relapse process. These states, as well as the desire to avoid them, have been described as primary motives for substance use. A recently developed behavioral treatment, mindfulness-based relapse prevention (MBRP), was designed to target experiences of craving and negative affect and their roles in the relapse process. MBRP offers skills in cognitive-behavioral relapse prevention integrated with mindfulness meditation. The mindfulness practices in MBRP are intended to increase discriminative awareness, with a specific focus on acceptance of uncomfortable states or challenging situations without reacting "automatically." A recent efficacy trial found that those randomized to MBRP, as compared with those in a control group, demonstrated significantly lower rates of substance use and greater decreases in craving following treatment. Furthermore, individuals in MBRP did not report increased craving or substance use in response to negative affect. It is important to note, areas of the brain that have been associated with craving, negative affect, and relapse have also been shown to be affected by mindfulness training. Drawing from the neuroimaging literature, we review several plausible mechanisms by which MBRP might be changing neural responses to the experiences of craving and negative affect, which subsequently may reduce risk for relapse. We hypothesize that MBRP may affect numerous brain systems and may reverse, repair, or compensate for the neuroadaptive changes associated with addiction and addictive-behavior relapse. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
... In humans, working memory training has been shown to improve cognition. We have recently developed a working memory training regimen in mice that has been shown to successfully increase both selective attention and general learning performance [35,95]. Thus it is conceivable that working memory training administered either before or after social stress might prevent or alleviate the negative effects on learning which result from subordination. ...
Imposed social subordination, such as that which accompanies physical defeat or alienation, has been associated with impaired cognitive function in both human and non-human animals. Here we examined whether domain-specific and/or domain-general learning abilities (c.f. general intelligence) are differentially influenced by the imposition of social subordination. Furthermore, we assessed whether the impact of subordination on cognitive abilities was the result of imposed subordination per se, or if it reflected deficits intrinsically expressed in subjects that are predisposed to subordination. Subordinate and dominant behaviors were assessed in two groups of CD-1 male mice. In one group (Imposed Stratification), social stratification was imposed (through persistent physical defeat in a colonized setting) prior to the determination of cognitive abilities, while in the second group (Innate Stratification), an assessment of social stratification was made after cognitive abilities had been quantified. Domain-specific learning abilities were measured as performance on individual learning tasks (odor discrimination, fear conditioning, spatial maze learning, passive avoidance, and egocentric navigation) while domain-general learning abilities were determined by subjects' aggregate performance across the battery of learning tasks. We observed that the imposition of subordination prior to cognitive testing decreased exploratory tendencies, moderately impaired performance on individual learning tasks, and severely impaired general cognitive performance. However, similar impairments were not observed in subjects with a predisposition toward a subordinate phenotype (but which had not experienced physical defeat at the time of cognitive testing). Mere colonization, regardless of outcome (i.e., stratification), was associated with an increase in stress-induced serum corticosterone (CORT) levels, and thus CORT elevations were not themselves adequate to explain the effects of imposed stratification on cognitive abilities. These findings indicate that absent the imposition of subordination, individuals with subordinate tendencies do not express learning impairments. This observation could have important ramifications for individuals in environments where social stratification is prevalent (e.g., schools or workplace settings).
Substantial improvements in factors such as microbiological quality have been noted in laboratory rodent (mouse [Mus musculus] and rat [Rattus norvegicus]) populations over the last 140 years, since domestication of laboratory strains started. These environmental improvements may have caused Flynn effect-like cognitive changes to occur in these populations, perhaps if these improvements enhanced cognitive plasticity and, consequently, learning potential. While lack of relevant data precludes cross-temporal comparison of cognitive performance means of laboratory rodent populations, it is possible to estimate changes in the proportion of cognitive performance variance attributable to general cognitive ability (GCA) over time. This “differentiation effect” has been found to occur along with the Flynn effect in human populations, suggesting that environmental factors, possibly mediated by their effects on life history speed, may weaken the manifold of GCA across time, allowing for greater cultivation of specialized abilities. Meta-analysis of the literature on mouse and rat cognition yielded 25 mouse studies from which 28 GCA effect sizes could be estimated, and 10 rat studies from which 11 effect sizes could be estimated. Cross-temporal meta-analysis yielded evidence of significant “differentiation effects” spanning approximately a century in both mice and rats, which were independent of age, sex, factor estimation technique, and task number in the case of the mice, and both factor estimation technique and task number in the case of the rats. These trends were also independent of the random effect of strain in both cases. While this is suggestive of the presence of the Flynn effect in captive populations of non-human animals, there are still factors that might be confounding these results. This meta-analysis should be followed up with experimental investigation.
The typical practice of averaging group performance during extinction gives the impression that responding declines gradually and homogeneously. However, previous studies of extinction in human infants have shown that some individuals persist in responding, whereas others abruptly cease responding. As predicted by theories of control, the infants who quickly resign typically display signs of sadness and despair when the expected reward is omitted. Using genetically diverse mice, here we observed a similar pattern of individual differences and the associated phenotypes. After learning to approach a food reward, upon extinction, some animals rapidly abandoned approach to the goal box, whereas other animals persisted in entering and searching the goal box. Interestingly, the persistent mice were slower to “give up” when confined to an inescapable pool of water (a test asserted to be indicative of susceptibility to depression) and exhibited a more extensive pattern of search for omitted rewards. Thus, extinction reveals a continuum in persistence, in which low values might reflect a susceptibility to the negative effects of stress and might predispose individuals to depression.
In this chapter, we present a lifespan agenda for research on adult human plasticity. Informed by the work of Takao Hensch and colleagues, we stress the need to linking research on adult plasticity to research on sensitive periods in childhood. We note that mammalian brains evolve through cycles of plasticity and stability, with a general trend towards stability. As a complement to plasticity, we point to the notion of flexibility, defined as the adaptive use and reconfiguration of the existing behavioral repertoire in the absence of macroscopic structural change. We then elaborate on three propositions that jointly characterize the operation of plasticity and flexibility in adulthood and old age. We note that flexibility maps nicely onto the Gc component of Gf-. Gc theory. In contrast, plasticity maps onto theoretical definitions of Gf but not on its psychometric operationalization, which confounds plasticity with flexibility. We end by discussing avenues for future research, and conclude that the description, mechanistic explanation, and modification of plasticity in human adulthood require a conceptual and empirical approach that integrates evidence across different life periods and species.
Species-level research on animal behavior is decades old and very well described, but individual differences in cognition has only gained momentum much more recently. Although there have been some studies of individual differences in cognition in primates, the new research has mainly focused on general cognitive ability (g) in mice. Fortunately, the timing is right for combining our understanding of the genetics and neuroscience of intelligence in humans with genetic manipulation models of learning and memory in mice. This will help forge deeper understanding of human intelligence and mental cognitive disorders such as retardation and Alzheimer Disease. In this chapter, we survey the academic literature associated with g in animals, with discussions of links with genetics, cross-species comparisons and neuroscience. We then focus on mice to describe the rapidly-growing genetic manipulation models of learning, memory and cognitive dysfunction. Ultimately, we believe that cognitive test batteries for mice, in combination with exploring the structure of cognition from the individual differences perspective, creates a useful framework for describing the effects of cognition-related genes and extrapolating these up to the human brain and experience.
Contemporary descriptions of human intelligence hold that this trait influences a broad range of cognitive abilities, including learning, attention, and reasoning. Like humans, individual genetically heterogeneous mice express a "general" cognitive trait that influences performance across a diverse array of learning and attentional tasks, and it has been suggested that this trait is qualitatively and structurally analogous to general intelligence in humans. However, the hallmark of human intelligence is the ability to use various forms of "reasoning" to support solutions to novel problems. Here, we find that genetically heterogeneous mice are capable of solving problems that are nominally indicative of inductive and deductive forms of reasoning, and that individuals' capacity for reasoning covaries with more general learning abilities. Mice were characterized for their general learning ability as determined by their aggregate performance (derived from principal component analysis) across a battery of five diverse learning tasks. These animals were then assessed on prototypic tests indicative of deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping") and inductive reasoning (execution of an efficient search strategy in a binary decision tree). The animals exhibited systematic abilities on each of these nominal reasoning tasks that were predicted by their aggregate performance on the battery of learning tasks. These results suggest that the coregulation of reasoning and general learning performance in genetically heterogeneous mice form a core cognitive trait that is analogous to human intelligence.
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