Keywords

1 Introduction

For a long time it was believed that mind is an “exclusive ability” of human beings. Surprisingly, it was found that many animals possess excellent perceptual and cognitive skills. For example, sensory abilities such as sight in golden eagle, hearing in elephant, and smell in bear are much better developed than in humans. To determine the roots of cognition in animals it is a very challenging task that employs both facets of knowledge (learned and unlearned) to orient perception, learning, and the encoding of environmental features. A top ten of the most intelligent animals with high cognitive abilities has been compiled (see some of their brains in Fig.~31.1) (Mota and Herculano-Houzel 2015). Such animal list must begin with nonhuman primates (orangutans, chimps, and monkeys). Monkeys are able to solve certain problems and are able to have emotions, too. Next, in the list are: elephant, dolphin/whale, crow, parrot, pig, dog/wolf/fox, cat, squirrel, and octopus. The elephant can learn how to paint and seems to cry when any member of the herd dies. The dolphin makes various “pranks like other animals” for their own fun. The whale has the largest brain and may feel anxiety, joy, and parental love. Dogs can count up to five, they are jealous and never forget if one hurts them. They can understand human language and even respond to some questions by mastering some suggestive gestures (Cheney and Seyfarth 1998). The pig loves to listen to music and performs well in video games. Crows can use different tools to obtain food (Amant and Horton 2008). The parrot can answer you when you ask him if he wants food or water. The wolves have a hierarchical society with alpha male and female in leading roles. Foxes are cunning, having a reputation for being very intelligent. Cats like to be independent and show caution before crossing the street Amant and Horton (2008). The squirrels have very good memory and make traps for thieves. Thus, in the fall, squirrels bury the nuts in hundred places and during winter they easily remember where the nuts were hidden. Octopuses can memorize different shapes and even can open a jar.

Fig. 31.1
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Mammalian representation of brain size. Brain size varies over 5 orders of magnitude (With permission from Herculano-Houzel 2009)

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To understand animal’s mind, we start with the first step by looking into the animal’s brain structure (Herculano-Houzel 2011) (anatomy: brain size, connectome, and modularity, i.e. lamination and minicolumns (Mountcastle 1997; DeFelipe 2011) and function (cognition and mind) perspectives (Goldman-Rakic 1996; Arnsten 2013; Opris and Casanova 2014).

1.1 Anatomical Substrate of Animals Mind

The anatomical organization of animal’s brain can be discussed in several steps. First, many anatomical investigations provide data about brain size, from the smallest to the largest animal on the Earth (DeFelipe 2011; Herculano-Houzel 2011). In these animal brains, the existence of connection pathways between brain regions is examined in vivo by using either traditional tracing methods or diffusion-based imaging (Shanahan 2012). These data provide information for a connectivity matrix covering the major cortical areas of the animal’s neocortex, or even the entire forebrain. This connectivity matrix is, in fact, the animal’s brain structural connectome (Beul et al. 2015). The resulting connectivity matrix is then analyzed using advanced mathematical concepts to characterize brain’s complex networks (i.e. graphs), in order to reveal its large-scale interconnections. A number of topological features of such networks include the sparse network and the meso-level microcircuits defining cortical modularity (Opris and Casanova 2014; Sporns and Betzel 2016). A modular network (dealing with the local processing) can be partitioned into subsets of nodes (modules) that are densely connected internally but only sparsely to other subsets (Chunga et al. 2016). Cortical modules betray the existence of a functional specialization.

1.2 Animal’s Cognition

What Is Cognition in Animals?

The concept of cognition in animals was introduced in neuroscience (through comparative psychology) to characterize the mental (memory, emotion, behavior) abilities of animals (Kandel 2007). It includes studies of operant conditioning and learning in animals, but has also been strongly influenced by research in ethology and behavioral ecology.

Do Animals Have Cognitive Abilities?

Cognitive abilities are mental skills required by the animal to carry out a given behavioral task. These abilities deal more with the mechanisms of how animals learn, remember, pay attention, rather than with the actual knowledge. Animal cognition is the label given to a modern approach to the mental capacities of non-human animals.

Do Animals Have Feelings?

Animals do have feelings because they can be trained to do some peculiar tasks. The foundation of training animals is based on mixing negative emotions with unwanted behavior and positive emotions with wanted behavior.

How Do Animals Think?

Thinking ability refers to the use of mental activities and skills to perform tasks involving learning, remembering, making decisions or paying attention, and more. Most animals have the ability to perceive their environment and to experience pleasure and suffering, although they may interpret/understand these features in various ways (Grieves and Jeffery 2017). Animals are ‘conscious’ just like humans, meaning that, they are aware of their surroundings (Duncan 2006). Animals have different “levels of consciousness”, some animals having “higher levels” of thinking/planning ability than others (Dawkins 2014). For example, the crows from New Caledonian are able to learn how to make and use various tools and, when given the choice, select the ones appropriate for a given task (Kenward et al. 2006). Lower “levels of consciousness allow species to experience sensations and emotions, without being aware of concepts like time and space.

Below are some examples of ways that “animals can think differently” than people:

  • When an animal is injured, it may react in a different way than when it is healthy. For example, mice can hide their pain, because when “showing weakness” it may mean they “could get eaten” by an eagle (Martinez et al. 1999).

  • An animal “may not be able to explain uncomfortable experiences to itself”, in the way that humans can. This means that they “may feel more frightened and unsure” about experiences, “similar to how a child may react when it gets hurt” (Bearzi and Stanford 2008).

  • Animals can enjoy similar types of experiences like humans do. For example, a mother deer may enjoy time with its new born calf, or a dog feels comfortable when lying down in the sunshine!

Although it was previously assumed that only humans possess the ability to think, science discovered the impressive cognitive abilities of animals. Animals as diverse as apes, dolphins, and birds use tools to acquire food and water (Boesch and Boesch 1990). Apes, dolphins, dogs and parrots “can understand some basic human language” (Shettleworth 2010). Other animals “demonstrate empathy and altruism”. Some animals have even “demonstrated a degree of self- awareness”, i.e. knowing that they are individuals that are “separated from others and from the environment (Couchman et al. 2010). Apes, elephants, and dolphins can all recognize, that “the image in the mirror is a reflection of their own body” (Prior et al. 2008).

We may not understand precisely how an animal thinks, but what is important is to appreciate that many of these animal species, are conscious, being capable to feel emotions such as pleasure or pain. The Cambridge Declaration on Consciousness states that: “The absence of a neocortex does not appear to preclude an organism from experiencing affective states. Convergent evidence indicates that non-human animals have the neuroanatomical, neurochemical, and neurophysiological substrates of conscious states along with the capacity to exhibit intentional behaviors. Consequently, the weight of evidence indicates that humans are not unique in possessing the neurological substrates that generate consciousness. Non-human animals, including all mammals and birds, and many other creatures, including octopuses, also possess these neurological substrates” (Bekoff 2012).

2 The Anatomy of Animal Brains

Do All Animals have a Neocortex?

The six-layer microarchitecture of the cortex appears to be a distinguishing feature of mammals, but it is not present in any other animals. There is some debate, however, as to the cross-species nomenclature for neocortex.

2.1 Brain and Size

The increase in the size and complexity of animal (especially in mammals) (Herculano-Houzel 2011) and human brains opened the gate to a grandiose development of mental skills. This “expansion of the brain allowed the addition of neuronal microcircuits” with a “similar basic structure”, which “enhanced the complexity of the human brain” and contributed to its unique abilities (DeFelipe 2011). However, there are fundamental differences even between distinct mammalian species.

Brain Size and Intellectual Capabilities

The absolute brain size of great apes has increased more three times-from an average of 450 cm3 in Australopithecus to 1345 cm3 in Homo sapiens (DeFelipe 2011). Human encephalization can be evaluated quantitatively by an “encephalization quotient (EQ)” (Jerison 1977, 1985). This is a ratio calculated based on evaluations of brain and body weight compared to the expected brain weight, using the cat as the “standard” for mammals (EQ = 1) (Herculano-Houzel 2011). Thus, EQ values bellow or above 1 indicate a relative brain size that is less or more what would be expected. Using this EQ measure in fossil specimens, values of 2.5 (for Australopithecus afarensis more than 3 million years old) and respectively 6 (Homo sapiens, more than 200,000 years old) have been calculated (Marino 1998). The EQ of modern humans is between 7.4 and 7.8, being the highest EQ of all the mammals. Accordingly, it is assumed that the EQ is a good predictor of intelligence. Nevertheless, there are many exceptions, like dogs (relatively intelligent creatures) and squirrels that have very similar EQs (1.1 and 1.2, respectively). Similarly, New World capuchin monkeys have EQs (2.4–4.8) higher than chimpanzees (2.2–2.5) and gorillas (1.5–1.8) but their intelligence is less (Roth and Dicke 2005).

2.1.1 Some Features of Cortical Circuits

Comparative Studies

Knowing that brain’s architecture consists of different functional modules whose size varies based on species-specific behavior, the allometric relationship of brain parts to the overall size provides some insight into how the brain scales across species (see for a review DeFelipe 2011). As expected, there is huge variability in brain size across different mammalian species (Fig.~31.2). This variability ranges from the smallest mammal’s brain on Earth (insectivorous pygmy shrew and the bumblebee bat, both with a similar body weight of 2–3 g) that weighs approximately 0.06 g, up to 9.2 kg for the brain size of the sperm whale (50,000 kg body weight). Moreover, animals with similar brain weight (blue whale, 6 kg, elephant, 5 kg) have huge body weight difference: the blue whale (Balaenoptera musculus; the largest animal on Earth) weighs 100,000 kg, compared to the Indian elephant (Elephas indicus), that weight only 5000 kg. By contrast, animals with similar body weight (gorilla, 160 kg vs. dolphin, 150 kg), have major brain size differences: the brain of gorilla weighs only 0.5 kg compared to the brain of the striped dolphin (Stenella coeruleoalba) that weighs 1.2 kg.

Fig. 31.2
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Relationship between brain size and body weight (With permission from Dicke and Roth 2016)

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2.2 Brain Lamination

Despite the broad variability in brain size across mammalian species, “there is little variation in the thickness of the cerebral cortices” that varies relatively little between brains of different sizes. The variation observed within a given brain is “similar to that found between species of different brain size” (DeFelipe 2011). In a valiant effort, Javier DeFelipe compared the thickness of lamination (see Fig.~31.3) of frontal, parietal, and occipital cortices across nine species, including the mouse, rat, rabbit, goat, cat, cheetah, lion, dog, and human. As pointed out by DeFelipe (2011), the thickest part of the cerebral cortex is in the human motor cortex, which can reach up to 4.5 mm, in striking contrast with cortex in the depths of the fissures that may only be 1 mm thick. Also, there are marked differences across brain areas where, for example, the thickness of dog’s frontal cortex is 0.8 mm, while the thickness in parietal cortex is 1.6 mm. Regardless of the several thousand times difference between the brain size of whales and that of pygmy shrew, there seems to be no difference in the basic lamination pattern of cerebral cortex in the pygmy shrew (0.4 mm thickness), and in whales (less than 2 mm thick). Furthermore, the appearance of the cellular components in Nissl-stained sections is generally similar in all cortices. Another observation stemming from the lamination thickness of frontal cortex is that the supra-granular layers in humans are the thickest across all species shown in Fig.~31.3. Altogether, these observations suggest that the increased brain size may be regarded as the main developmental drive across species.

Fig. 31.3
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Cortical lamination in animal brains (With permission from DeFelipe 2011)

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2.3 Animal Brain Connectome

A connectome is a structural map of the “wiring diagram” of neural connections in the animal brain (DeFelipe 2010). More broadly, an animal connectome would include the mapping of all neural connections within an animal’s nervous system. The visualization of the detailed anatomic structures of the mouse brain is obtained from a diffusion MRI tractography of the mouse brain and comparison with neuronal tracer data in Fig.~31.4.

Fig. 31.4
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(continued) is +0.5. The exemplified hrFM were reconstructed at 15.6 × 15.6 × 50 μm3 resolution, matching the thickness of the histological tissue slices. Acronyms: aca anterior commissure anterior part, cg cingulum, cc corpus callosum, CPu caudate putamen, ec external capsule, lo lateral olfactory tract. With permission from Laura-Adela Harsan et al. PNAS 2013, 110: E1797-E1806. The connectome in the rodent brain. A probabilistic tractography connectivity matrix for the mouse brain. Relative connectivity estimates that 148 anatomic regions are displayed with a log10 scale color map (top left). Tractography seeds (rows) and targets (columns) are organized based on their developmental origins as indicated by colored surface renderings of parent structures along the top and left side of the figure (With permission from Chen et al. 2015)

(a, b). Living mouse brain connectional anatomy. High-resolution fiber maps (hrFM) generated from the global fiber tracking data and their qualitative comparison with immunofluorescent myelin staining. High qualitative resemblance of hrFM with myeloarchitecture is observed at three different rostro-caudal positions across the mouse brain. (A,B) Distance from bregma

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3 Animal Cognition

3.1 Rationale

Looking from a historic perspective to understand animal cognition, Descartes argued that all animals behave like “machines” (i.e. “simple reflex devices”) that do not think because they lack language ability (Rumbaugh et al. 1996). From another perspective, Darwin came up with a totally different view on animal behavior, by defending their ability to think, even in the absence of language (Thierry 2010). Contrary to Descartes’s view, today it is well documented, that “animals use their thinking ability to represent events and objects in their environments” (Grieves and Jeffery 2017). Surprising insights into the animals mind and their communication abilities provide “ample evidence that animals do think” (Larkin 2013). If animals think, the next question to ask is: what does this imply about their brains? “If an animal turns out to think in a similar way as we do, did the animal develop a brain similar to humans? Or is the animal able to come up with the same kind of thought but with a completely different brain?” (Prior et al. 2008).

3.2 Animals Cognitive Functions

The spectrum of animal cognitive functions is quite broad. Here, are shown some examples of such functions with the neural correlates of animal’s mind.

3.2.1 Human Face Recognition in Dog

Dogs have a complex social relationship with humans. One fundamental clue in support of this claim is the manner in which dogs pay close attention to human faces in order to guide their behavior. For example, they recognize their owner’s emotional state using visual cues (Cuaya et al. 2016). To understand how dogs’ brains perceive human faces, Cuaya and his colleagues trained seven dogs to remain awake, still, and unrestrained inside an MRI scanner (Fig.~31.5), while their brain was scanned using functional magnetic resonance imaging (fMRI).

Fig. 31.5
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Left: A dog trained in the fMRI scanner. Right: Location of the most sensitive region for faces in the temporal cortex (With permission from Cuaya et al. 2016)

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A visual stimulation paradigm was used to compare animal’s brain activity elicited by human faces versus everyday objects. Cuaya’s experimental results are showing significant brain activation related to the perception of faces, mainly in the bilateral temporal cortex, with no significant brain activity change to everyday objects. Cuaya’s results are consistent with reports in humans and other animals like primates and sheep that suggest a high degree of conservation of ventral visual pathway for face processing. This study confirms the role of the temporal cortex as node in the circuitry of social cognition in dogs (Cuaya et al. 2016).

3.2.2 Elephant’s Memory

A question like: Do elephants never forget? may be an exaggeration, but nevertheless, the elephants rank among the smartest animals on the planet. Elephants have the largest brains of all terrestrial mammals, weighing around 5 kg (see Fig.~31.6) for an adult animal (Conger 2017; Shoshani et al. 2006).

Fig. 31.6
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The neural substrate of elephant’s mind. (a) Elephant and calf. (b, c) Elephant brain: superior (b) and c inferior (c) views of the elephant brain illustrating the relative position of sampled tissue blocks (shaded areas) for the occipital and frontal regions, respectively. Scale bar 5 cm. (d) Social behavior of elephants (Redrawn from Jeffrey 2017). (f, g) Photomicrographs of Nissl-stained cortex from frontal (b) and occipital (c) cortex with labeled layers. Note that the elephant appears to lack a well-developed layer IV. Scale bar 1 mm (Adapted from Jacobs et al. 2010)

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Although the brain size alone cannot tell us how effectively the brain works, nevertheless, it can provide a salient hint about the power of elephant’s memory.

As shown in Sect. 31.2, an animal’s intelligence has been related to it’s encephalization quotient (EQ). Thus, the higher the ratio of brain-to-body-mass, the smarter the animal is supposed to be and vice versa. For example, humans have an average EQ above 7, elephants of 1.88 and pigs around 0.27 (Shoshani et al. 2006). Female elephants, as the leaders of matriarchal elephant herds, show signs of better memory, alerting their herd if a potential danger arises or if a feeding ground is recognized (Herculano-Houzel et al. 2014; McComb et al. 2011). An elephant’s memory encodes information necessary for survival, such as foraging locations and family members identification, in the same manner that human working memory systems selectively discard or transfer data for long-term memory storage (or future retrieval) (Hart et al. 2008). There is clear evidence that elephants have an excellent ability to remember relevant spatial details about their environment for a very long time.

3.2.3 Executive Decision Making in Sheep and Goat

The Sheep

Compared to macaque monkeys, the sheep seems to have a similar brain size, but not the same level of intelligence, and therefore, sheep is not typically used for testing in pre-clinical cognitive studies (Morton and Avanzo 2011). However, because cognitive decline is a key therapeutic target in Huntington Disease (HD), the sheep model of HD needs to be evaluated with feasible testing with cognitive function. Morton and Avanzo (2011) tested sheep’s ability to perform cognitive tasks (discrimination learning, reversal learning, and attentional set-shifting) involving the executive function. The significant findings show that, sheep not only could perform tests of discrimination learning and reversals, but they could also perform the set-shifting tasks that are relevant for cognitive dysfunction in humans. Sheep performance on the set-shifting task mirrored that seen in humans and macaques, demonstrating that this animal can perform cognitive tasks that are useful for HD testing (Fig.~31.7).

Fig. 31.7
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Left: Performance of sheep in the two choice discrimination task. Each point represents the mean (± SEM) number of correct choices made in each set of eight discriminations. Where points are joined by solid lines, the sets of discriminations were tested on the same day. Where points are joined by dotted lines, testing was conducted on a different day. SD  simple discrimination, SR simple discrimination reversal, Ret1  first retention trial, CD  compound discrimination IDS  intradimensional shift, IDR  intradimensional shift reversal, EDS  extradimensional shift, EDR  extradimensional shift reversal. Right: Comparison of number of trials to reach criterion in different stages of the task (With permission from Morton and Avanzo 2011)

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The Goat

In certain situations, animals can use their environments to decide/select based on particular sources of information (personal or social). Animals living in groups may benefit from information based on the behavior of other individuals. Indeed, social information is obtained much faster and at low cost compared to personal information, thus increasing foraging efficiency (Baciadonna et al. 2013). However, individual information becomes more reliable than social information when food locations change during the season or when food is randomly distributed. When testing in goats (Capra hircus) the use of conflicting information (personal versus social), during a foraging task, it was found that goats relied more on personal than social information (when both types of information were available and in conflict). This implies that goats are selective herbivores that rely on personal rather than social information to find randomly distributed resources in highly changing environments.

3.2.4 The Bird’s Mind

The cognitive faculty of humans is not the exclusive ability of mammals, but also of the birds (Fig.~31.8) that seem to be endowed with memory, face recognition, and executive control functions, as recent research highlights in corvidae and gray parrots (Seyfarth and Cheney 1997; Pepperberg 2002, 2013; Marzluff et al. 2012; Veit and Nieder 2013; Veit et al. 2015; Bolhuis and Gahr 2006).

  1. (a)

    Working memory . The concept of working memory dealing with the ability of brain to retain past information for online processing, in order to guide goal-directed behavior was recently tested in corvidae (Veit et al. 2015).

Fig. 31.8
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Upper left: Gray parrot on a perch with colored objects in front of it. Upper right: Schematic diagrams of parasagittal view of the songbird brain. Songbirds have an elaborate network of interconnected forebrain nuclei that form an interface between auditory input (which converges on field L, the primary auditory projection region in the avian forebrain) and vocal output, which is produced in the syrinx, the avian vocal organ. The network of forebrain nuclei includes DLM nucleus dorsolateralis anterior, pars medialis, DM dorsomedial nucleus of the midbrain nucleus intercollicularis, HVC high vocal center, lMAN lateral magnocellular nucleus of the anterior nidopallium, mMAN medial magnocellular nucleus of the anterior nidopallium, NIF nucleus interface of the nidopallium, nXIIts tracheosyringeal portion of the nucleus hypoglossus, RA robust nucleus of the arcopallium, RAm nucleus retroambigualis, rVRG rostro–ventral respiratory group, X Area X (Adapted, with permission, from Bolhuis et al. Nature Reviews Neuroscience 7, 347–357 (2006))

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Corvidae songbirds have remarkable high-level cognitive capabilities (Veit et al. 2015). To demonstrate that neurons in the avian brain process working memory in a behaviorally relevant manner, Veit and his colleagues trained four carrion crows (Corvus corone) on a delayed match-to-sample task that required the birds to remember a visual stimulus for a delayed comparison (Veit et al. 2015). The activity of bird’s neurons in the nidopallium caudolaterale (NCL, a pallial association area of the avian endbrain) was recorded while the birds performed the cognitive task. Many NCL neurons encode visual stimuli in “sustained” delayed activity and store this information after the stimulus disappeared. Such selective delay activity suggests that NCL neurons in corvidae brain encode visual working memory for short-term processing of visual information.

  1. (b)

    Rule based decisions. Veit and Nieder (2013) tested corvidae in flexible rule-based decisions by recording single-unit activity from NCL neurons. The widespread firing activity in NCL represents the behavioral rules, becoming weaker in error trials, thus predicting the crows’ behavioral decisions. This suggests that NCL cells are “mirroring the executive control functions of primate prefrontal cortex” (Veit and Nieder 2013).

  2. (c)

    Human face perception . Crows can remember certain human faces for years after just one encounter. Marzluff‘s and colleagues have shown via in vivo imaging of crow’s brain the circuits underlying the perception of human faces (Marzluff et al. 2012). Such findings demonstrate that, similar to humans, crows use visual mechanisms to recognize human faces by integrating visual information with emotion.

  3. (d)

    Abstract representation in parrot. Research in the gray parrot (Psittacus erithacus), demonstrated that one male parrot, named Alex, understood number symbols as abstract representations, in ways comparable to those of apes and young human children (Pepperberg 2013). The parrot appeared to learn these concepts in ways more similar to humans than to apes. According to Pepperberg (2002, 2013), the parrot Alex, “labeled more than 50 different objects, 7 colors, 5 shapes, about 6 quantities, 3 categories (color, shape, material) and uses ‘no’, ‘come here’, ‘wanna go X’ and ‘want Y’ (X and Y being appropriate location or item labels)”. The parrot combined the above labels to “identify, request, comment upon or refuse more than 100 items and to alter his environment”. This unique parrot exhibits capacities that were “presumed” to be limited to humans or nonhuman primates (Pepperberg 2002, 2013).

3.2.5 Cognitive Abilities of Dolphins and Whales

Dolphins

The dolphins are well-documented as intelligent animals. Dolphin’s large brain (Fig.~31.9) is structured for awareness and emotion. From structural perspective, the dolphin brain seems even more complex than the human brain (Bearzi and Stanford 2008; Marino et al. 2007). Folding is more, but this does not make it more complex). Dolphins are capable of mimicry and spontaneous imitation of humans (Kuczaj and Yeater 2006). An adult dolphin male copied the diver who came to clean the water tank portholes by picking up a seagull feather in the tank and stroking the glass with it. A calf dolphin, when he saw a man smoking on the other side of the glass, swam back to her mother, took a mouthful of milk, returned to the porthole and blew a cloud of milk towards the window, exactly replicating the cigarette smoke (Safina 2015). Surviving skills like dolphin calves copying their mother’s feeding techniques closely in the wild are not surprising.

Fig. 31.9
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Left . Representative image of a long-finned pilot whale brain center: Laminar organization of the whale’s neocortex. Right: Dolphin brain. Acronym (wm = white matter) (With permission from Mortensen et al. 2014)

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Whales

During courtship and migration, male whales sing songs which can be heard over dozens of kilometers. In the South Pacific, whales regularly alter their songs, with novelties moving eastward over time. A song that appears 1 year among whales feeding near eastern Australia will be heard the next year around New Caledonia (1500 km to the east). The year after the whale song gets to Tonga, and so on until it reaches French Polynesia that is 6000 km away. Another song will be started in Australia, in the meantime. There seems to be no environmental or genetic underpinning for this, the succession of songs seems a matter of fashion, or whale’s “cultural change on a vast scale” (Derbyshire 2011).

4 Insights into the Animal’s Mind

4.1 Transfer of Memory in Rats

A unique feature of memory-transfer in rats was demonstrated by Deadwyler et al. (2013) when patterns of successful information encoding were derived online from well-trained animals (“donor”) during long-delay memory trials and delivered via online electrical stimulation to synchronously tested naïve animals (“recipient”), never before exposed to the memory delay feature of the task (Fig.~31.10). By transferring such memory trained (donor) animal hippocampal firing patterns via stimulation to coupled naïve recipient animals, their task performance was facilitated in a direct “donor-recipient” manner. This provides the basis for utilizing extracted appropriate neural information from one brain to induce, recover, or enhance memory related processing in the brain of another subject.

Fig. 31.10
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Transfer of memory from one well trained rat (donor) to a naïve rat (recipient). Recordings were obtained online from donor rats with validated effective stimulation patterns in CA1. Naïve animals (recipients) were only trained to perform the memory task in sequence without exposure to extended delay intervals interposed between task phases requiring completion of the nose poke response on the opposite wall (red middle diagram) (With permission from Deadwyler et al. 2013)

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4.2 Social Cognition in Animals

Social behavior is perceived as a “set of interactions” among the individuals of the same group/species. A rich spectrum of social behaviors occurs among animals. One reason of “why do animals help others at the potential cost of their own survival and reproduction?” is that social behavior is “adaptive”, meaning that social behavior ultimately enhances an animal’s “chances to survival and fitness”, including its lifetime reproductive success (McGlynn 2010) One example of how social behavior is adaptive is “aggregation against predators”. Living in groups involves a balance of conflict and cooperation, which is mediated by the costs and benefits associated with living socially. From the Neuroeconomics perspective, one can predict that “social cooperation” will be favored when the benefits of living socially exceed the costs and risks of social life. Two features of social behavior are beneficial: altruism and reciprocity, and both of which involve synergy (McGlynn 2010).

Social groups are formed to increase the probability of survival and reproduction of group/species members. One can distinguish two categories (Fig.~31.11) of social animals: a) highly social animals, such as packs of wolves, school of fish, and herds of herbivores, and b) asocial animals, like polar bears, that rarely interact to each other.

Fig. 31.11
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Social groups which have formed to improve the probability of survival and reproduction of individual members: pack of wolves (a) and school of fish (b) (With permission from McGlynn (2010))

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An altruistic act of one member of the group increases the welfare of another member at the cost of the member who performs the act. For example, ground squirrels, may warn other members of their group about a predator, with the risk to attract predator’s attention upon the member giving the warning call. Such risky behavior benefits other members of the squirrel’s group. Reciprocity assumes a permutation of altruism act by other members, and in fact, enables the existence of altruism. The long term benefit of altruistic behavior can outweigh its costs, being ultimately measured in on an animal’s lifetime reproductive success.

Conclusion

To conclude, contrary to expectations, animals possess excellent perceptual and cognitive skills that sometimes surpass those of humans. This is likely because animal cognition in mammals relies on the modular arrangement of the neurons in the cerebral cortex that allow the emergence of various aspects of the mind (attention, memory, decision making or motor planning). Moreover, animals are capable of using tools, to live in hierarchical society, and to develop empathy towards animals from different species. Comparing social interaction of individuals with the interaction of molecules one can easily realize that the species that have a hierarchy are more advanced than those that do not have a social interaction. The physics of the mind of animals captures the unique organization across many scales of living and nonliving matter emerging from the low molecular level to the cellular, systems/cognitive and social levels.