Model D

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675579/

Episodic future thinking refers to the capacity to imagine or simulate experiences that might occur in one’s personal future.

[...]

An important observation linking episodic future thinking with memory comes from neuroimaging studies indicating that a common core network of brain regions show increased activity when people remember past experiences and imagine future experiences. This core network, comprising regions in the medial temporal lobe (MTL), the posterior cingulate including retrosplenial cortex, medial prefrontal cortex, and lateral temporal and parietal regions largely corresponds to the well-known default network. Recent meta-analyses have confirmed that the core/default network is engaged during episodic simulation and further that it is jointly engaged during episodic simulation and episodic memory.

[Petter]

3 and 1
2 and 2
1 and 3

------

This is probably enough. (see post #829)

[Petter]

1. people vs. task ... DMN vs. CEN (or FPN) ... This is the main dichotomy.

2. SN (+ DMN) vs. "sensory SN" ... Ne vs. Si

3. the external world vs. the internal world ... CON ext./DAN/VAN vs. CON int./the precuneus

4. DAN/VAN vs. CON ... or mirror network A vs. mirror network B

5. DAN vs. VAN ... or mirror network B vs. CON

6. process information vs. interpret information ... detail-oriented vs. big picture ... the left hemisphere vs. the right hemisphere

7. abstract vs. concrete ... episodic simulation (imagination) vs. episodic memory ... the anterior and the posterior brain vs. the posterior brain

8. decision-making/planning vs. problem-solving ... anterior PFC (BA10) vs. posterior PFC

[Petter]

an EII-like type:

1. 3 and 1
2. 3 and 1
3. 1 and 3
4. 1 and 3
5. 3 and 1
6. 1 and 3
7. 3 and 1
8. 2 and 2




an EIE-like type:

1. 2 and 2
2. 2 and 2
3. 2 and 2
4. 1 and 3
5. 1 and 3
6. 3 and 1
7. 3 and 1
8. 3 and 1

[Petter]

https://en.wikipedia.org/wiki/Frontoparietal_network

The FPN is primarily composed of the rostral lateral and dorsolateral prefrontal cortex (especially the middle frontal gyrus) and the anterior inferior parietal lobule. Additional regions include the middle cingulate gyrus and potentially the dorsal precuneus, posterior inferior temporal lobe, dorsomedial thalamus and the head of the caudate nucleus.

------

only the internal world (?)

[Petter]

https://en.wikipedia.org/wiki/Intraparietal_sulcus

Five regions of the intraparietal sulcus (IPS): anterior, lateral, ventral, caudal, and medial

LIP & VIP: involved in visual attention and saccadic eye movements
VIP & MIP: visual control of reaching and pointing
AIP: visual control of grasping and manipulating hand movements
CIP: perception of depth from stereopsis
All of these areas have projections to the frontal lobe for executive control.

Activity in the intraparietal sulcus has also been associated with the learning of sequences of finger movements.

The dorsal attention network includes the intraparietal sulcus of each hemisphere. The intraparietal sulcus is activated during voluntary orientation of attention.

[Petter]

Noam Chomsky: Inner language is the medium of thought. Outer language is the medium for communication.

the inner language >> the outer language

[Petter]

3. the external world vs. the internal world ... CON ext./DAN/VAN vs. CON int./the precuneus

This is a false dichotomy. The relevance/duration of the external world has to be measured relative to other people instead.

[Petter]

people-oriented vs. task-oriented (DMN, CON and mirror network B vs. FPN, DAN/VAN and mirror network A)

I think this is a correct interpretation, so DMN (3) and CON/mirror network B (1) is not possible.

[Petter]

4. DAN/VAN vs. CON ... or mirror network A vs. mirror network B

This dichotomy is redundant.

(DAN <--> mirror network A)

[Petter]

1. people vs. task ... DMN vs. CEN (or FPN) ... This is the main dichotomy. (DMN ---> CON and mirror network B, FPN ---> DAN/VAN and mirror network A)

2. SN (+ DMN) vs. "sensory SN" ... Ne vs. Si

3. the external world: 1, 2 or 3

4. DAN/mirror network A vs. VAN ... or mirror network B vs. CON

5. process information vs. interpret information ... detail-oriented vs. big picture ... the left hemisphere vs. the right hemisphere

6. abstract vs. concrete ... episodic simulation (imagination) vs. episodic memory ... the anterior and the posterior brain vs. the posterior brain

7. decision-making/planning vs. problem-solving ... anterior PFC (BA10) vs. posterior PFC

[Petter]

2. SN (+ DMN) vs. "sensory SN" ... Ne vs. Si ... and Te vs. Si

goals vs. immediate sensory needs

[Petter]

7. decision-making/planning vs. problem-solving ... anterior PFC (BA10) vs. posterior PFC

This dichotomy is redundant as well.

------

SN + the left hemisphere = decision-making

SN + the right hemisphere = questioning decisions

[Petter]

https://en.wikipedia.org/wiki/Brodmann_area_10

Present research suggests that it is involved in strategic processes in memory recall and various executive functions.

[Petter]

1. people vs. task ... DMN vs. CEN (or FPN) ... This is the main dichotomy. (DMN ---> CON and mirror network B, FPN ---> DAN/VAN and mirror network A)


2. SN (+ DMN) vs. "sensory SN" ... Ne vs. Si ... and Te vs. Si


3. the external world: 1, 2 or 3


4. DAN/mirror network A vs. VAN ... or mirror network B vs. CON


5. process information vs. interpret information ... detail-oriented vs. big picture ... the left hemisphere vs. the right hemisphere


6. abstract vs. concrete ... episodic simulation (imagination) vs. episodic memory ... the anterior and the posterior brain vs. the posterior brain


7. current strategy vs. alternative strategies ... medial frontopolar cortex vs. lateral frontopolar cortex ... anti-Ne vs. Ne

[Petter]

3^7 = 2187 types

[Petter]

Bill Gates: (left) medial frontopolar cortex ... anti-Te (see post #833)

[Petter]

6. abstract vs. concrete ... episodic simulation (imagination) vs. episodic memory ... the anterior and the posterior brain vs. the posterior brain

PFC: high activity vs. low activity ... or anterior PFC (not BA10) vs. posterior PFC

[Petter]

8. action vs. perception/interpretation ... the anterior brain vs. the posterior brain ... SEE vs. ESI

------

brain SEE.jpg

brain ESI.jpg

[Petter]

3. the external world: 1, 2 or 3

3. the external world: VN vs. VN + attention networks (incl. mirror networks)

------

VN = visual network

[Petter]

1. people vs. task ... DMN vs. CEN (or FPN) ... This is the main dichotomy. (DMN ---> CON and mirror network B, FPN ---> DAN/VAN and mirror network A)


2. goals vs. immediate sensory needs ... SN (+ DMN) vs. "sensory SN" ... Ne vs. Si ... and Te vs. Si


3. the external world: VN vs. VN + attention networks (incl. mirror networks)


4. DAN/mirror network A vs. VAN ... or mirror network B vs. CON


5. symbolic vs. real ... process information vs. interpret information ... detail-oriented vs. big picture ... the left hemisphere vs. the right hemisphere


6. abstract vs. concrete ... episodic simulation (imagination) vs. episodic memory ... PFC: high activity vs. low activity ... or anterior PFC (not BA10) vs. posterior PFC


7. current strategy vs. alternative strategies ... medial frontopolar cortex vs. lateral frontopolar cortex ... anti-Ne vs. Ne


8. action vs. perception/interpretation ... the anterior brain vs. the posterior brain ... SEE vs. ESI

[Petter]

the external world: VN vs. VN + attention networks (incl. mirror networks)

------

SEE: 1 and 3

IEE: 3 and 1

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107817/

The dorsal network (Fig. 1, blue) is supposed to be organized bilaterally and comprises the intraparietal sulcus (IPS) and the frontal eye fields (FEF) of each hemisphere. These areas are active when attention is overtly or covertly oriented in space (e.g., after a predictive spatial cue [arrow] in Posner’s location-cueing paradigm; Posner 1980). Both IPS and FEF contain areas with retinotopically organized maps of contralateral space (Fig. 2; for a review, see Silver and Kastner 2009), which makes them candidate regions for the maintenance of spatial priority maps for covert spatial attention, saccade planning, and visual working memory (Jerde and others 2012). It has been proposed that the middle third of the IPS represents the human homologue of the monkey lateral intraparietal area LIP (Vandenberghe and Gillebert 2009). Interestingly, the dorsal frontoparietal network is also activated during feature-based attention (e.g., when the color of a target stimulus is precued) and provides a spatial coding in multiple reference frames (see Ptak 2012 for a comprehensive review).

The ventral network comprises the temporoparietal junction (TPJ) and the ventral frontal cortex (VFC) (Fig. 1, orange) and typically responds when behaviorally relevant stimuli occur unexpectedly (e.g., when they appear outside the cued focus of spatial attention). In contrast to the dorsal nodes (FEF and IPS) for which homologue areas are well described in nonhuman primates and which are hence well characterized with regard to their neuronal receptive field properties, the existence of homologue areas of the ventral regions is debated. So far, no standardized anatomical definitions exist for the localization of TPJ and VFC (see also Geng and Vossel unpublished data). Although the cytoarchitectonic parcellation of the posterior parietal cortex has recently been characterized (Caspers and others 2006) and can be used to specify the anatomical localization of fMRI activations, it has also been shown that functional activations do not clearly follow cytoarchitectonic boundaries (Gillebert and others 2013). Furthermore, TPJ might not be a single unitary structure but rather consist of multiple subregions with different connectivity patterns (Mars and others 2011; Mars and others 2012). To date no topographic maps in these ventral areas have been detected, although this might be because of methodological limitations of human neuroimaging experiments (Corbetta and Shulman 2011). However, spatial specificity for the contralateral hemifield has been observed for the right TPJ in a recent transcranial magnetic stimulation (TMS) study (Chang and others 2013).

[Petter]

5. symbolic vs. real ... process information vs. interpret information ... detail-oriented vs. big picture ... the left hemisphere vs. the right hemisphere

expected events vs. unexpected events

------

brain DAN and VAN.jpg

[Petter]

https://en.wikipedia.org/wiki/Inferior_frontal_gyrus

The inferior frontal gyrus contains Broca's area, which is involved in language processing and speech production.




https://en.wikipedia.org/wiki/Temporoparietal_junction

The right temporoparietal junction (rTPJ) is involved in the processing of information in terms of the ability of an individual to orient attention to new stimuli.

[...]

The left temporoparietal junction (lTPJ) contains both Wernicke's area and the angular gyrus, both prominent anatomical structures of the brain that are involved in language cognition, processing, and comprehension of both written and spoken language.

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2845804/

Our results reveal that the RIFG is recruited when important cues are detected, regardless of whether that detection is followed by the inhibition of a motor response, the generation of a motor response, or no external response at all.

[Petter]

8. action vs. perception/interpretation ... the anterior brain vs. the posterior brain ... SEE vs. ESI

short-term memory (in-the-moment processing) vs. long-term memory

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2657600/

What are the differences between long-term, short-term, and working memory?

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term “working memory”) that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1.

[Petter]

a new dichotomy:


15. current strategy vs. alternative strategies ... medial frontopolar cortex vs. lateral frontopolar cortex ... anti-Ne vs. Ne

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4677979/

Functional Segregation of the Human Dorsomedial Prefrontal Cortex

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.




https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3665907/

Segregation of the human medial prefrontal cortex in social cognition

While the human medial prefrontal cortex (mPFC) is widely believed to be a key node of neural networks relevant for socio-emotional processing, its functional subspecialization is still poorly understood. We thus revisited the often assumed differentiation of the mPFC in social cognition along its ventral-dorsal axis. Our neuroinformatic analysis was based on a neuroimaging meta-analysis of perspective-taking that yielded two separate clusters in the ventral and dorsal mPFC, respectively. We determined each seed region's brain-wide interaction pattern by two complementary measures of functional connectivity: co-activation across a wide range of neuroimaging studies archived in the BrainMap database and correlated signal fluctuations during unconstrained (“resting”) cognition. Furthermore, we characterized the functions associated with these two regions using the BrainMap database. Across methods, the ventral mPFC was more strongly connected with the nucleus accumbens, hippocampus, posterior cingulate cortex, and retrosplenial cortex, while the dorsal mPFC was more strongly connected with the inferior frontal gyrus, temporo-parietal junction, and middle temporal gyrus. Further, the ventral mPFC was selectively associated with reward related tasks, while the dorsal mPFC was selectively associated with perspective-taking and episodic memory retrieval. The ventral mPFC is therefore predominantly involved in bottom-up-driven, approach/avoidance-modulating, and evaluation-related processing, whereas the dorsal mPFC is predominantly involved in top–down-driven, probabilistic-scene-informed, and metacognition-related processing in social cognition.

[...]

Moreover, the vmPFC and dmPFC were both significantly associated with social, emotional, and facial processing in the present study. This indicates that the vmPFC and dmPFC are not functionally dissociable by selective involvement in social, emotional, or facial processing, although this is frequently proposed. However, the dmPFC, but not vmPFC, was congruently associated with more complex social-cognitive tasks across forward and reverse functional decoding, including perspective-taking and episodic memory retrieval. While the former imposes an other-focused mind set, the latter inherently entails a self-focused mind set (obviously, one can only recall scenes from one's own personal experience). Quantitative functional profiling of the dmPFC therefore indicates that the dmPFC is involved in both self- and other-oriented processing, analogous to the vmPFC. Importantly, the frequently proposed vmPFC-dmPFC distinction as self versus other is challenged by our conclusions.

[...]

In particular, consistent with present functional decoding, neural activity in the dmPFC, rather than vmPFC, has been consistently interpreted to underlie inference, representation, and assessment of one's own and others' mental states in functional neuroimaging research (Gusnard et al., 2001; Gallagher and Frith, 2003; Amodio and Frith, 2006; Gilbert et al., 2006; Ochsner, 2008; Van Overwalle, 2009; Bzdok et al., 2012b; Moran et al., 2012). For instance, dmPFC (but not vmPFC) activity was related to the proficiency decline of mental state inference in elderly (Moran et al., 2012), cognitive regulation of one's own emotional states (Ochsner et al., 2004b) and inference of another person's emotional states (Ochsner et al., 2004a), as well as self-reported (Wagner et al., 2011) and experimentally measured (Zaki et al., 2009) proficiency in emotional state inference. Notably, such self- and other-related conceptualizations cannot be made based on sensory information or general knowledge about the physical world (cf. Premack and Woodruff, 1978; Leslie, 1987; Carruthers, 2009). Thus, mental state inference necessarily relies on the generation of probabilistic internal information. Supported by dmPFC's functional association with episodic memory retrieval, such prima vista non-mnemonic construction processes are likely to be subserved by the neural network underlying retrieval of past and imagination of future scenes as indicated by recent neuroimaging experiments and meta-analyses (Schacter et al., 2007; Spreng et al., 2009; Andrews-Hanna et al., 2010; Rabin et al., 2010; Bzdok et al., 2012c). Constructing such probabilistic scenes is further believed to necessarily drawn on semantic knowledge retrieval (Binder et al., 1999; Bar, 2007; Suddendorf and Corballis, 2007; Carruthers, 2009; Bzdok et al., 2012c). This would be in line with left lateralization of the dmPFC subnetwork typical of semantic processing (Binder et al., 2009). The conjunction of previous functional neuroimaging findings and present neuroinformatic findings congruently characterizes the dmPFC as a “mental sketchpad” (Goldman-Rakic, 1996) potentially implicated in modeling and binding plausible self- and other-related scenarios instructed by semantic concepts in social cognition. Again, such sensory-independent de novo generation of meaning representations can only be expected from highly associative, integrative brain areas such as those of the dmPFC subnetwork (Mesulam, 1998), as opposed to the vmPFC subnetwork.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675579/

Contributions of the vmPFC to episodic simulation

The vmPFC is part of the core network involved in episodic simulation (47), yet relatively little is known about the exact processes supported by this region. The vmPFC has been implicated in various different functions, including memory but also the representation of value and affect (98). Recent evidence suggests that during episodic simulation, vmPFC may support the intersection of those functions. Activation in rostral and ventral mPFC signals the emergent affective value of an imagined episode, and this value signal is difficult to account for by the nominal values of the individual elements that make up the episode (e.g., its location and present people or objects; 99–100). By signaling the anticipated value of an event, the vmPFC can mediate farsighted decisions (68–69).

Importantly, the contribution of the vmPFC is insufficiently characterized as valuating imagined scenarios because it also plays a role in constructing such scenarios. Lesions to this region can reduce the episodic detail and coherence of imagined events (101–102). This impairment seems to be particularly pronounced when patients have to imagine a broad scenario (e.g., hosting a dinner), because such patients have been shown to perform within the normal range of healthy controls when they are instructed to focus on a circumscribed moment within such a scenario (e.g., cutting vegetables; 25). However, there were also other important differences between the aforementioned studies, such as center of lesion overlap, etiology, and amnesic status of the patients. Nonetheless, the pattern suggests that the vmPFC supports access to schemata or conceptual knowledge of the respective scenarios that then foster the ability to construct specific episodes (101; see also 103). Consistent with this interpretation, fMRI data indicate that the vmPFC particularly supports simulations that can draw on rich knowledge (99) and that a more dorsal part of the mPFC is similarly more strongly engaged during simulations of episodes that are part of the same event cluster (42).

Taken together, the evidence suggests that the contribution of the vmPFC to episodic simulation may be twofold: accessing schematic knowledge and processing anticipated affect. Further research is needed to examine interactions between the two.





https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707083/

On the Role of the Ventromedial Prefrontal Cortex in Self-Processing: The Valuation Hypothesis

With the development of functional neuroimaging, important progress has been made in identifying the brain regions involved in self-related processing. One of the most consistent findings has been that the ventromedial prefrontal cortex (vMPFC) is activated when people contemplate various aspects of themselves and their life, such their traits, experiences, preferences, abilities, and goals. Recent evidence suggests that this region may not support the act of self-reflection per se, but its precise function in self-processing remains unclear. In this article, I examine the hypothesis that the vMPFC may contribute to assign personal value or significance to self-related contents: stimuli and mental representations that refer or relate to the self tend to be assigned unique value or significance, and the function of the vMPFC may precisely be to evaluate or represent such significance. Although relatively few studies to date have directly tested this hypothesis, several lines of evidence converge to suggest that vMPFC activity during self-processing depends on the personal significance of self-related contents. First, increasing psychological distance from self-representations leads to decreased activation in the vMPFC. Second, the magnitude of vMPFC activation increases linearly with the personal importance attributed to self-representations. Third, the activity of the vMPFC is modulated by individual differences in the interest placed on self-reflection. Finally, the evidence shows that the vMPFC responds to outer aspects of self that have high personal value, such as possessions and close others. By assigning personal value to self-related contents, the vMPFC may play an important role in the construction, stabilization, and modification of self-representations, and ultimately in guiding our choices and decisions.

------

brain22.png

[Petter]

https://www.sciencedirect.com/topics...frontal-cortex

The VLPFC controls encoding of mappings between knowledge stored in posterior areas and decision processes in frontal areas and subsequent retrieval. The human lateral prefrontal cortex (PFC) is organized functionally along a gradient from abstract decision and action planning processes in more rostral parts (e.g., VLPFC) to increasingly more concrete response-related processes in more caudal parts (e.g., premotor cortex (PM)). This prefrontal system maintains patterns of activity for various types of information (e.g., linguistic, visuospatial, object, rules) in functionally distinct neural populations. Each influences (controls) other areas to accomplish a mental or overt action. For example, to decide the category of a visual object, dorsolateral PFC (DLPFC) and PM accumulate and compare visual evidence obtained from the occipitotemporal cortex to compute a decision according to a rule that determines the choice, which involves more rostral frontopolar (BA 10) areas. In the parietal lobe, the intraparietal sulcus (IPS) also accumulates evidence, consistent with its strong bidirectional connections with some decision-making regions. The VLPFC has an important role in disambiguating knowledge, as when multiple interpretations of the input result from initial processing (e.g., ambiguous figures, impoverished percepts, multiple alternative meanings or knowledge types are competing), and it interacts reciprocally with DLPFC and PM to recruit working memory resources to resolve uncertainty.

[Petter]

dmPFC and dlPFC.jpg

PFC 2.jpg

[Petter]

https://pubmed.ncbi.nlm.nih.gov/23418505/

The involvement of frontopolar cortex in mediating prospective memory processes has been evidenced by various studies, mainly by means of neuroimaging techniques. Recently, one transcranial magnetic stimulation study documented that transient inhibition of left Brodmann Area (BA) 10 impaired verbal prospective memory. This result raises the issue of whether the BA 10 involvement in prospective memory functioning may be modulated by the physical characteristics of the stimuli used. The present study aimed to investigate the role of the frontopolar cortex in visual-spatial PM by means of the application of inhibitory theta-burst stimulation. Twelve volunteers were evaluated after inhibitory theta-burst stimulation over left BA 10, right BA10 and CZ (control condition). In the prospective memory procedure, sequences of four spatial positions (black squares) each were presented. During the inter-sequence delay, subjects had to reproduce the sequence in the observed order (ongoing task forward) or the reverse order (backward). At the occurrence of a target position, subjects had to press a key on the keyboard (prospective memory score). Recall and recognition of the target positions were also tested. We found that prospective memory accuracy was lower after theta-burst stimulation over right BA10 than CZ (p<0.01), whereas it was comparable in left BA10 and CZ conditions. No significant difference was found among the three conditions on recall and recognition of target positions and on ongoing task performance. Our findings provide a novel strong evidence for a specific involvement of right frontopolar cortex in visual-spatial prospective memory. In the context of previous data providing evidence for left BA 10 involvement in verbal prospective memory, our results also suggest material-specific lateralization of prospective memory processes in BA 10.

[Petter]

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897366/

Left Brain, Right Brain: Facts and Fantasies

Handedness and brain asymmetry are widely regarded as unique to humans, and associated with complementary functions such as a left-brain specialization for language and logic and a right-brain specialization for creativity and intuition. In fact, asymmetries are widespread among animals, and support the gradual evolution of asymmetrical functions such as language and tool use. Handedness and brain asymmetry are inborn and under partial genetic control, although the gene or genes responsible are not well established. Cognitive and emotional difficulties are sometimes associated with departures from the “norm” of right-handedness and left-brain language dominance, more often with the absence of these asymmetries than their reversal.

[...]

One myth that persists even in some scientific circles is that asymmetry is uniquely human. Left–right asymmetries of brain and behavior are now known to be widespread among both vertebrates and invertebrates, and can arise through a number of genetic, epigenetic, or neural mechanisms. Many of these asymmetries parallel those in humans, or can be seen as evolutionary precursors. A strong left-hemispheric bias for action dynamics in marine mammals and in some primates and the left-hemisphere action biases in humans, perhaps including gesture, speech, and tool use, may derive from a common precursor. A right-hemisphere dominance for emotion seems to be present in all primates so far investigated, suggesting an evolutionary continuity going back at least 30 to 40 million years. A left-hemisphere dominance for vocalization has been shown in mice and frogs, and may well relate to the leftward dominance for speech—although language itself is unique to humans and is not necessarily vocal, as sign languages remind us. Around two-thirds of chimpanzees are right-handed, especially in gesturing and throwing, and also show left-sided enlargement in two cortical areas homologous to the main language areas in humans—namely, Broca's area and Wernicke's area (see Figure 1). These observations have been taken as evidence that language did not appear de novo in humans, as argued by Chomsky and others, but evolved gradually through our primate lineage. They have also been interpreted as evidence that language evolved not from primate calls, but from manual gestures.





https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561660/

The authors suggest the interesting hypothesis that the hemispheres differ in their sensitivity for allocentric processing irrespective of differences for egocentric processing. They suggest that while the left hemisphere process the right side of objects, the right hemisphere process the left side of objects independent of the hemi-space the objects is seen in.





https://www.sciencedirect.com/scienc...2839329500077G

Two types of image generation: Evidence for left and right hemisphere processes

The results from seven experiments provide evidence that visual mental images can be generated by either the left or right cerebral hemisphere, but in different ways. Subjects were cued to form images within a grid or within a set of four corner brackets; a single X mark was enclosed within each stimulus, and the subjects were to determine whether the X mark would have fallen on an imaged pattern. When subjects memorized descriptions of how parts were arranged, they could later form images of the composite pattern when cued in the right visual field (left hemisphere) more accurately than when they were cued in the left visual field (right hemisphere). In contrast, when subjects memorized individual segments on a screen, and ‘mentally glued’ them into a single pattern, they later could form images more accurately, at least in some circumstances, when cued in the left visual field. These results were predicted by the theory that images are built up by arranging parts, and that two different processes can be used to arrange them. One process uses stored descriptions to arrange parts, and is more effective in the left cerebral hemisphere; the other process uses stored memories of metric positions to arrange parts, and is more effective in the right cerebral hemisphere. Convergent evidence was obtained by having subjects memorize letters in grids (which are easily encoded using descriptions of the positions of segments) or within a space delineated by four brackets (which require memorizing the precise positions of the segments). Subjects were relatively more accurate when cued in the left visual field with bracket stimuli, but tended to be relatively more accurate when cued in the right visual field with grids stimuli. Control experiments showed that this finding was not due to hemispheric differences in the ease of forming images at different sizes or differences in the ease of perceptually encoding the probes.





https://www.frontiersin.org/articles...012.00028/full

Numerous studies of healthy individuals as well as patients with neurological damage suggest that the right hemisphere is biased toward global information whereas the left hemisphere appears to be more specialized for local information, as observed following stroke or hemispherectomy (see Yovel et al., 2001 for a review). Classically, these studies have used compound hierarchical figures (Navon, 1977), where small letters are grouped to form a larger letter, with individuals with right hemisphere injury being particularly impaired with recognizing the larger letter whereas right injury impairs performance with local items. These findings have been taken to suggest that left hemisphere is biased toward processing high spatial frequencies, while the right is biased toward low spatial frequencies (Sergent, 1982)

While Sergent (1982) suggests a static model for hemispheric specialization, some evidence suggests that the calibration of “local” and “global” scale is dynamic and is determined by the task at hand (Robertson and Ivry, 2000). For example, Shulman and Wilson (1987) presented individuals with hierarchical figures while also detecting low contrast sinusoidal gratings. They found that when individuals were asked to attend to the global letters, they were more sensitive to detect the low frequency gratings. On the other hand, attending to the local letters improved detection of the high frequency gratings. Flevaris et al. (2010) recently demonstrated that this can be reversed and lateralized: attending the high frequency gratings improves sensitivity to the local elements especially for items in the right hemifield while attending low spatial frequency gratings reduces errors for global targets but more so for items presented in the left hemifield.

Robertson and Ivry (2000) provide a model to interpret these findings. They hypothesize that that the visual system employs an initial spatial frequency filter based on the task at hand. If accurate, this suggests that blocked studies may be manipulating low level perception (with filter optimized in anticipation of upcoming target scale), as well as higher-level processing. Robertson and Ivry (2000) describe a thought-experiment where participants are shown a hierarchical figure, but do not know whether the target will be defined at the global or local level. They propose that in this case the initial filter would be set broadly, allowing each hemisphere to exhibit its preference (e.g., left hemisphere showing a local benefit, while the right hemisphere exhibits a global preference).





https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3335342/

A quintessential example of hemispheric specialization in the human brain is that the right hemisphere is specialized for face perception. However, because the visual system is organized contralaterally, what happens when faces appear in the right visual field and are projected to the nonspecialized left hemisphere? We used divided field presentation and fMRI adaptation to test the hypothesis that the left hemisphere can recognize faces, but only with support from the right hemisphere. Consistent with this hypothesis, facial identity adaptation was observed in the left fusiform face area when a face had previously been processed by the right hemisphere, but not when it had only been processed by the left hemisphere. These results imply that facial identity information is transferred from the right hemisphere to the left hemisphere, and that the left hemisphere can represent facial identity but is less efficient at extracting this information by itself.





https://www.sciencedirect.com/scienc...78262607001170

The left perceptual bias, particularly for emotion judgments, is a robust phenomenon and obtained under a variety of conditions. A moderate test–retest correlation (r = .63) between perceptual asymmetry scores on an emotion judgment chimeric faces task over a two-year period has been found, which suggests that the bias is reasonably stable (Wirsen, Klinteberg, Levander, & Schalling, 1990). The left bias for emotion judgments has also been shown to occur across all ages (Levine & Levy, 1986) and is present regardless of the emotion used for the emotion judgment task (e.g., happy, sad and neutral; Christman & Hackworth, 1993) or the mood of the viewer (David, 1989). The left perceptual bias for chimeric faces is not confined to emotion judgments or facial identity and has also been found in right-handers performing a gender decision with a male/female chimera task (Luh et al., 1994, Luh et al., 1991).





https://www.cogneurosociety.org/behrmann_qa/

Taken together, these findings are consistent with the account that prior to the onset of reading, there is no pressure for face recognition to occur on one or the other hemisphere. It is only once a child starts reading, and there is a need to have the visual information be in close proximity to the language information in the brain, that the left hemisphere becomes increasingly – but not exclusively – tuned for word recognition.

Because words and faces are so different from each other and it is unlikely that the same area of the brain can represent both classes efficiently, the right hemisphere becomes increasingly (again, but not exclusively) tuned for face recognition.

[Petter]

5. the left hemisphere vs. the right hemisphere: detail-oriented vs. big picture ... or fine motor skills vs. gross motor skills

(not symbolic vs. real ... even though language is processed in the left hemisphere)

[Petter]

7. current strategy vs. alternative strategies ... medial frontopolar cortex vs. lateral frontopolar cortex ... anti-Ne vs. Ne

lateral, left: many strategies (or goals/objects) ... He zooms in on one strategy and ignores the others. (he makes a decision)


medial, left: one strategy ... He zooms in on the details and criticizes the strategy.


lateral, right: many strategies ... He zooms out and sees all the alternative strategies.


medial, right: one strategy ... He keeps one strategy and occasionally compares it to other strategies. (this is also critique)

[Petter]

3. the external world: VN vs. VN + attention networks (incl. mirror networks)

free (an Se type) vs. currently occupied

[Petter]

... or the premotor cortex vs. PFC

[Petter]

3. the external world vs. the internal world ... attention networks, mirror networks, the premotor cortex vs. the precuneus (and the temporal lobe, hippocampus etc) ... practical vs. theoretical/fact-based

[Petter]

14. visuospatial attention vs. external logic (DAN/VAN >> FPN vs. DAN/VAN+FPN) ... action-oriented doer vs. designer/builder (DAN) ... observer/explorer vs. organizer (VAN)

The difference between an SeTi type and a TiSe type is liveliness (expressive vs. inexpressive ... quick decisions/logic vs. careful logic).