The Interactive Brain
Juliana E.
MSc Foundations in Clinical Psychology @ Newcastle University | BSc Psychology (Clinical Psychology) (Hons) at Northumbria University
Anatomically, the brain functions by connecting or interacting with different brain regions (Braun et al., 2015). The brain adapts continuously to new functional demands throughout its lifetime and can reallocate functions after injury or illness (Budday & Kuhl., 2020) involving complex interactions between genetics and environment (Lenroot & Giedd., 2008). It is important to note that cognitive operations are neither localized in an area nor a network of regions but are a consequence of dynamic network interactions that are manipulated by the processing requirements of a particular operation (Duncan et al., 1997; Bandura., 1999). Supporting theories include the social cognition and embodied cognition hypotheses which demonstrates interactivity in the brain. However, there are certain theories that suggest that certain abilities occur at birth (Okasha., 2003), and are not acquired, and language is innate as suggested by Fodors' modularity and Chomsky's language theory suggested (Barman., 2014). This essay will provide evidence that the brain is interactive by discussing supporting theories such as the social cognition hypothesis, embodied cognition, and critiquing Chomsky and Fodors' theories.
Social cognition hypothesis is one of the key theories to highlight that the brain and the mind is infact interactive. Social cognition is the ability to participate in collaborative activities with shared intentions and is what differentiates human cognition from that of other species (Beer & Ochsner., 2006; Hunt et al., 2012; Beaudoin & Beauchamp., 2020). Taking part in such activities requires the ability to read, understand cultural (Howard & Renfrow., 2006) and have a strong motivation to interact with others and a unique way of representing psychological states (Smith., 1996). Through participation in these activities, species-specific forms of cultural cognition and evolution are developed (Adolphs., 2001), enabling everything from creating and utilizing linguistic symbols to creating social norms (Fiske., 2000; Miklo?si & Topa?l., 2013) and individual beliefs (Schwarzer., 2001) to establishing social institutions (Damon., 1979; Stryker & Burke., 2000; Tomasello et al., 2005).
Language-specific mechanisms or universal grammar (UG) are not necessary for social cognition (Freyd., 1983). Those who oppose to social cognition may argue that all human languages share UG categories, mechanisms, and constraints, which Chomsky considered to be innate (Chomsky., 1986). Nevertheless, it lacks empirical support (Da?browska., 2015). UG, according to Tomasello (2005), cannot be rationalized and is unnecessary regarding language (Tomasello., 2005b). According to UG, there is no inherent element of linguistic organization, but an innateness of language in general. The argument can also be interpreted in other ways (Da?browska., 2015b).
A good example of how the brain interacts with the environment can be seen in joint attention, which signals coordinated engagement between individuals (Akhtar & Gernsbacher., 2007). It has long been a focus of research and practice to study preverbal communication and joint attention (Bruinsma et al., 2004). Children's first lexicon begins with both attending to social partners and sharing their attention with objects or events (Callaghan et al., 2011; Tomasello., 1992). Additionally, prelinguistic acts as a significant role in socialization (Liszkowski., 2011). Interestingly, in children with autism, they lack joint attention, which has intrigued researchers for use in autism diagnosis and intervention (Mundy., 2003; Stephenson et al., 2021). The concept of joint attention has gained momentum in recent years as a tool not only for diagnosing and treating children with autism, but also as a prognostic indicator (Humphrey & Parkinson., 2006; McCarthy et al., 2013; Moody et al., 2015). As Joint-attentional frames ground words in experience, social cognition has several similarities with embodied cognition (Tomasello et al., 2007; Moll & Tomasello., 2007; Chevalier et al., 2019).
As representational and computational theories of mind have increased in popularity in cognitive science, embodied cognition theory (EC) seeks to counteract this trend (Allen & Friston., 2016). In its quest to integrate mind, body, and environment, EC promises to revolutionize long-studied topics such as perception, language acquisition, social interaction, memory, reasoning, and reasoning (Shapiro & Stolz., 2018). Also, EC theories reject the information processing model of the mind, and metaphors of the mind equated to software that manipulates symbols (Borghi & Caruana, 2015). Data supporting EC theory has highlighted significant findings in developmental (Smith & Gasser, 2005), Social cognition (Goldman & de Vignemont., 2009), emotions (Niedenthal et al., 2009), attention (Shapiro., 2007), memory (Sutton., 2006) and language (Lan et al., 2015; Wilson & Golonka., 2013). Studies on embodied cognition have observed that behaviour may change if the brain interacts with the environment (Wilson., 2002). Researchers have shown that social perception is automatically linked to behaviour (Chartrand & Bargh., 1999). It is sometimes called the chameleon effect, which refers to one's nonconscious mimicry of the postures, mannerisms, facial expressions, and other behaviours of others during interactions. By passively and unintentionally changing their behaviour to match those around them (Snyder & Swann., 1978; Chartrand & Bargh., 1999b), one can change one's behaviour. In this type of mimicry, there is no intent to mimic or imitate, and there is no conscious awareness of it (Lakin et al., 2003).
According to embodied emotion theory, emotions are expressed, perceived, processed, and understood in relation to arousal (Wu et al., 2020). Human participants' responses to induced embodiment of emotion in the laboratory are causally influenced by the manipulation of facial expressions and postures. Communicating with congruence between the body language of the recipient and the sender will facilitate understanding, while communicating with incongruence will impair understanding (Niedenthal, 2007; Winkielman et al., 2015). Based on studies of the human amygdala (Adolphs et al., 1995; Samoilov & Goldfried., 2006), Phelps (2006) examined the relationship between emotion and cognition. Throughout early perception and reasoning, human behaviour is influenced by mechanisms that are intertwined with emotion and cognition. This suggests that there may be no need to divide emotion and cognition and that understanding human cognition requires consideration of emotion (Phelps., 2006; Ziemke & Lowe., 2009). In neuropsychological studies Croze et al. (2022) is reported that Alzheimer’s Disease and Parkinson’s Disease patients retained the enactment effect and the emotion effect on memory (Croze et al., 2022).
In embodied music cognition, music is processed (such as learning, memory use, prediction, etc.) through corporeally mediated interactions (Leman et al., 2018). Actions resulting from music cognition are embedded in an environment (Leman., 2007). Hodges (2014) was one of the many researchers who studied body responses to music, including physiological and physical processes, and concluded that expressed body movements and music are inseparable. They found that smiling during music listening may indicate a positive emotional response (Hodges., 2014). They suggested that future research should explore naturalistic settings as well as musical excerpts of varying lengths and complexity (Hodges., 2014).
A theory that stems off embodied cognition is the common coding theory, which suggests that people perform the same motor plans in response to viewing an action as if they were performing it (Prinz., 1997; Tye-Murray et al., 2012). In common coding, both action and perception elements are encoded in an artificial neural network, in which activating one type of element automatically triggers another (associative priming), like connectionist implementations of semantic priming (Cree et al., 1999; Chandrasekharan., 2009). A prime example is, when people think about "drinking coffee," they activate codes that often occur together, like objects (e.g., coffee cup, coffee beans), motor plans (e.g., how we like to hold our cup), and sensory states (e.g., coffee's colour, smell, and taste), biasing subsequent processing (Hala?sz & Cunnington., 2012). Supporting data on this theory has suggested that the common coding theory is a concept that underlies the mirror neuron paradigm (Barakova & Lourens., 2009).
Mirror neurons have provided insight into behaviour, especially in the field of music cognition, where it is essential to explain how these neurons interact with organism components responsible for social interaction (Matyja., 2015). In addition, research has shown that perception and action are equivalently and simultaneously represented in the mirror neuron system (Iacoboni & Dapretto., 2006; Tononi et al., 1994; Friston et al., 2011). Revolutionary research looking into artificial intelligence by Barakova et al., (2014) explored how mirror neurons could facilitate robot-robot communication. The mirror neuron system can synchronize neuron groups in different structures because of interaction behaviour. Simulations of robots were used in research to illustrate several interactions. Mirror neuron paradigm shows potential for designing socially meaningful behaviours through synchronization and turn-taking (Barakova et al., 2014).
Another key study was one by Mu?sseler et al (2000), which varied the response code in blindness to response-compatible stimuli. According to the common coding theory, the planned action establishes the code for its execution and sensory consequences since it shares common encoding with the perceived action. Due to this already represented code, the congruent visual stimulus is less accessible to perception when it appears (Mu?sseler et al., 2000).
Using brain imaging technology like a CCT, there are valuable insights about the brain's interactivity that have been uncovered. Using electroencephalography (EEG), Ko?nig et al (2018) resolved the dynamics of face processing with high temporal resolution. A few functional modules participated in both sensory and motor processing. According to their findings, some independent components of cognitive tasks such as tri-modal variants of Stroop tasks that require recognition, decision-making, and motor responses systematically relate to sensory processing and action execution. Sensorimotor coupling is correlated with EEG in humans, supporting theories such as embodied cognition, common coding, and sensorimotor contingency that do not sequentially separate motor and sensory functions. This means understanding cognitive processes requires considering interactions within a natural environment (Ko?nig et al., 2018).
Animal studies have highlighted significant findings in favour of the common coding theory. For example, when the monkey grasps or manipulates objects, or observes its experimenter doing similar actions, neurons in the rostral region of its ventral premotor cortex discharge (Nelissen., 2005). The Broca's area may also contain a mirror system for gesture recognition in humans as demonstrated by transcranial magnetic stimulation and positron emission tomography (Rizzolatti & Arbib., 1998; Gallese et al., 1996). In previous studies, it has been demonstrated that patients with brain damage who find it difficult to grasp objects are unable to reconcile their neurophysiological findings (Carey., 1995; Cisek & Kalaska., 2010). A patient's lesions appear to be concentrated in areas that are not involved in grasping- related visuomotor transformations in monkeys (Castiello., 2005).
As for the developmental evidence of the common coding theory, it is established that foetuses open and close their mouths in utero and protrude their tongues (Thill., 2021; Jain & Rathee., 2020). As a result, these gestures are already a part of a Newborn's behavioural repertoire when he is born. Furthermore, the evidence suggests that neonates are more likely to mimic a modelled gesture after some time has passed, rather than immediately (Simpson et al., 2013; Jones., 2009). According to this finding, activation would be expected to increase gradually as a gesture is observed under a motor simulation explanation, as opposed to an explanation predicting an immediate response due to the availability of higher-level processes from birth (Bertenthal., 2008).
According to Piaget's A not B paradigm, Longo & Bertenthal (2006) observed nine-month-old infants acting. When infants reached the mysterious midline barrier, they showed an ipsilateral bias (Boyer & Bertenthal., 2015) and persisted only after observing actions that they themselves could do, suggesting they coded others' actions using motor simulation (Longo & Bertenthal., 2006; Bertenthal & Boyer., 2011).
Fodors' modulation theory is another opposing theory against the idea that the brain is interactive. The concept of modulation describes the various components of cognition as independent modules (Fodor., 1983). Fodor claims that certain aspects of neural processing are domain specialized (Spunt & Adolphs., 2017). It is important to note, however, that domain generality opposes this concept. It refers to the ability to communicate between different domains (Johnson., 2011) to gain access to information that influences behaviour in a variety of situations and tasks (Lerche et al., 2020; Chiappe & MacDonald., 2005). The integration of domain-general representations has been demonstrated in previous literature as a key component of cognitive processes, including reasoning (Sternberg., 2011), decision-making (George & Sunny., 2019; Crawford et al., 2022) and working memory (Li et al., 2014; Cowan et al., 2011). A variety of other evidence exists, including spatial visualization (Downing et al., 2005) and rapid automated naming (Denckla & Cutting., 1999; Zhang et al., 2017). Researchers have shown that different brain structures interact rather than being domain-specific using imaging technology. When making decisions, for example, prefrontal cortex and hippocampus communicate and are connected through neural connections (Saberi Moghadam et al., 2019; Tavares & Tort., 2021; Brockmann et al., 2011). In working memory, there are also overlapping brain regions which are activated as part of working memory (Awh & Jonides., 2001; LaBar et al., 1999), including the prefrontal, cingulate, and parietal cortices (Chai et al., 2018) which interact with each other.
Piaget's theory on cognitive development (Huitt, W., & Hummel, J., 2003), emphasized the domain- general constraints of reasoning structures. During the course of intellectual development, through development there are a series of constructions and general stages that follow an invariant sequence (Inagaki.,1992), such as in sensorimotor, preoperational, concrete-operational, and formal-operational stages. Throughout these stages, different thinking structures or logical-mathematical structures are evident, which are considered uniformly applicable to individuals (Ole?ron et al., 2014; Carey et al., 2015). Supporting research has shown that infants and children can perform complex visual tasks (Barry et al., 2015) and discriminating phonemic perception (Trehub & Hannon., 2006), visual language (Fisher et al., 2020) and face perception (Pascalis., 2002; Pascalis et al., 2005). The development of facial processing is sensitive during the first year of life, according to this study (Pascalis et al., 2005). The temporal lobe, hippocampus, and amygdala record these face-selective responses, which facilitate encoding, storage, and retrieval of long-term and short-term memories (Simons & Spiers., 2003).
Conversely, in cognitive science, there is an assumption that domain specificity is intrinsically linked to innateness (Khalidi., 2001). Nevertheless, researchers have found that the medial prefrontal cortex also participates in classical fear conditioning based on neuroanatomical research. In rat fear learning and expression, Corcoran & Quirk (2007) used the sodium channel blocker tetrodotoxin to inactivate Prelimbic (PL). When PL was inactivated, freezing to both a tone and context associated with foot shock was reduced (learned fear), but freezing to cats was not affected (innate fear). For this reason, PL activity is key to expressing learned fears, but not to acquiring them. As a result of projections to the basal nucleus of the amygdala, PL integrates information from auditory and contextual inputs (Corcoran & Quirk., 2007; Ribeiro et al., 2011). Regarding number cognition, Left-to-right mental number line (MNL) is located bilaterally within the human intraparietal sulcus, yet recent studies indicate that the MNL is not innate (Nez., 2011).
Before proceeding to the conclusion, it is important to discuss the future direction of research in cognitive science. Artificial intelligence is the future, one key issue that is necessary to address is domain general intelligence. To solve novel problems, domain-general mechanisms interact with domain- specific, information-encapsulated modules in numerous ways, which include manipulating information obtained from various modules (Clowes., 2006; Fornito et al., 2016). Analogical reasoning as well as decontextualization processes are mediated by mechanisms of general intelligence, particularly working memory (Carriedo et al., 2016; Chiappe & Gardner., 2011; Heitz et al., 2005). Learning can be achieved by making novel associations with environmental cues using domain-general mechanisms (Chiappe & MacDonald., 2005) despite the existence of a variety of evolved, special-purpose learning mechanisms.
In conclusion, embodied cognitive processes as well as social cognition illustrates the interaction between the brain and other cognitive areas. It is reductive of what the brain can do to suggest it is modular because brain areas are specialized mental systems (Fatima., 2020). Both opposing theories are unable to discredit the overwhelming amount of research illustrating the brains interactivity. Future research in artificial intelligence would be a fruitful area for further work as studies on address domain intelligence is necessary to evolve Artificial Intelligence and our understanding of processing.
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