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Thread: Model D

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    The ventral attention network: the mirror of the language network in the right brain hemisphere

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    https://www.biorxiv.org/content/10.1....508254v1.full

    The cingulo-opercular (CO) network and its two best studied regions – the dorsal anterior cingulate and anterior insula – have been linked to task control, but also implicated in many additional processes across cognitive, social, and emotional domains. However, most prior work investigating the CO network has used a group-average approach, which may mix signals across nearby regions that vary across individuals. Here, we reevaluate the CO network’s role in task control with both task and rest fMRI, using regions with a high probability of CO network agreement across individuals. Hierarchical clustering analyses suggest heterogeneity in the CO network’s task response properties, with one sub-system (CO1) showing consistency with prior task control characterizations while another sub-system (CO2) has weak task control responses, but preserved ties to pain and motor functions. Resting-state connectivity confirms subtle differences in the architecture of these two sub-systems. This evidence suggests that, when individual variation in network locations is addressed, the CO network includes (at least) two linked sub-systems with differential roles in task control and other cognitive/motor/interoceptive responses, which may help explain varied accounts of its functions. We propose that this fractionation may reflect expansion of primary CO body-oriented control functions to broader domain-general contexts.
    https://www.jneurosci.org/content/39/50/9878.full

    ------

    SN and CON/AMN <--> dACC

    LN (the limbic network) <--> vACC

    SN: Maintains a stable ‘saliency’ or priority map of the visual environment – including surprising stimuli, and stimuli that are pleasurable and rewarding, self-relevant, or emotionally engaging (both appetitive and aversive such as threats).

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    https://www.sciencedirect.com/topics...cutive-network

    The CEN is a fronto-parietal system and is crucial for actively maintaining and manipulating information in working memory, for rule-based problem solving and for decision making in the context of goal-directed behavior.

    [...]

    The CEN is a phylogenetically old network, which can be assumed to be an evolutionary extension of the brain centers that control the SNS. Indeed, a meta-analysis of the central ANS demonstrates that sympathetic control is mediated via the insula and dACC, but also by frontal and parietal centers (Beissner et al., 2013), overlapping with the CEN.

    ------

    https://i.imgur.com/eWm2k14.jpg

    https://i.imgur.com/xCRHgU7.jpg

    ------

    CEN = FPN + CON/AMN

    (?)

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    https://en.wikipedia.org/wiki/Brodmann_area_44

    The presence of mirror neurons in Broca's area suggests language evolved from a gesture imitating system. Broca's area is also involved with theory of mind (ToM), which is the ability to understand the mental state of others through observation, inferring, and projecting.

    (mirror network B)




    https://www2.tulane.edu/~h0Ward/BrLg/Dorsal.html

    The “dorsal language pathway” was further subdivided according to its temporal and frontal sections given their distinct roles in perceptual versus sensorimotor aspects of phonological processing (Restle et al. 2012; Mesgarani et al. 2014; Arsenault and Buchsbaum 2015; Murakami et al. 2015). The temporal region covered the left superior temporal gyrus, encompassing the anterior temporal sulcus up to the planum temporale region. The frontal region covered the pars opercularis, which is located in the posterior part of the inferior frontal gyrus (BA44).

    The “ventral language pathway” was also subdivided as a function of its temporal and frontal components, given their distinct roles in semantic representation and semantic control, respectively (Rissman et al. 2003; Gold et al. 2006; Fiebach et al. 2007; Gagnepain et al. 2008; Sabri et al. 2008; Snijders et al. 2009; Whitney et al. 2011; Visser et al. 2012; Lambon Ralph et al. 2017). The temporal component covered the middle temporal gyrus, encompassing the anterior temporal lobe up to the posterior middle temporal gyrus, including the middle temporal–occipital junction. The frontal component covered the entire pars triangularis, located in the anterior part of the inferior frontal gyrus (BA45).




    https://citeseerx.ist.psu.edu/docume...2bf89214639042

    However, this activation remains localized in the lowest portion of the inferior precentral sulcus dividing BA 6 from BA 44 suggesting that dorsal BA 44 may be specific for action conditions, potentially reflecting the response of mirror neurons. Ventral BA 44, in contrast, may be related to the representation of sequentially structured information, particularly those that are defined by parameters of the voice and that can be transformed into articulatory patterns.




    https://i.imgur.com/OG5YEw1.png

    The anatomical location of 6 subregions of the LIFG, including the dorsal BA 44 (A44d), the ventral BA 44 (A44v), the opercular is part of BA 44 (A44op), the rostral BA 45 (A45r), the caudal BA45 (A45c), and the dorsal IFS. LIFG, left inferior frontal gyrus; IFS, inferior frontal sulcus; BA, Brodmann area.

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    https://pubmed.ncbi.nlm.nih.gov/24770711/

    The complex processing architecture underlying attentional control requires delineation of the functional role of different control-related brain networks. A key component is the cingulo-opercular (CO) network composed of anterior insula/operculum, dorsal anterior cingulate cortex, and thalamus. Its function has been particularly difficult to characterize due to the network's pervasive activity and frequent co-activation with other control-related networks. We previously suggested this network to underlie intrinsically maintained tonic alertness. Here, we tested this hypothesis by separately manipulating the demand for selective attention and for tonic alertness in a two-factorial, continuous pitch discrimination paradigm. The 2 factors had independent behavioral effects. Functional imaging revealed that activity as well as functional connectivity in the CO network increased when the task required more tonic alertness. Conversely, heightened selective attention to pitch increased activity in the dorsal attention (DAT) network but not in the CO network. Across participants, performance accuracy showed dissociable correlation patterns with activity in the CO, DAT, and fronto-parietal (FP) control networks. These results support tonic alertness as a fundamental function of the CO network. They further the characterization of this function as the effortful process of maintaining cognitive faculties available for current processing requirements.

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    https://www.sciencedirect.com/topics...marginal-gyrus

    Furthermore, they qualify rehearsal as a process that makes use of components (Fig. 6) also concerned with the planning (i.e., programming in the left premotor cortex) of articulated speech. Finally, from this perspective, phonological memory may be regarded as a component part of the language system.

    The neural correlates of the phonological short-term store–rehearsal system are shown in Fig. 11. The system comprises posterior–inferior parietal and premotor components, concerned with the storage and rehearsal aspects of short-term retention. When subjects are engaged in tasks that require more “executive” processes in addition to storage (e.g., free recall and matching a target one, two, or three back in a sequence), the pattern of activation becomes more anterior, extending to the dorsolateral prefrontal cortex, and bilateral.

    [...]

    Figure 11. The anatomical basis of phonological short-term memory. This system comprises two components: the phonological short-term store (ph STS), whose main neural correlate is the left inferior parietal lobule (supramarginal gyrus, BA 40) at the temporoparietal junction, and the process of “rehearsal,” whose neural basis includes Broca's area (BA 44), the premotor area (BA 6), and the supplementary motor area in the left hemisphere. These two neural short-term memory systems are likely to be connected through the arcuate fasciculus and white matter fiber tracts in the insular region.

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    the anterior intraparietal area (AIP ... shape, size and orientation of objects): a comparison without working memory

    PFC: a comparison with working memory

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    https://en.wikipedia.org/wiki/Logica...ing#Analogical

    Analogical reasoning involves the comparison of two systems in relation to their similarity. It starts from information about one system and infers information about another system based on the resemblance between the two systems.

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    https://academic.oup.com/cercor/arti...94?login=false

    Dissociating Verbal and Spatial Working Memory Using PET

    Three experiments used position emission tomography (PET) to study the neural basis of human working memory. These studies ask whether different neural circuits underly verbal and spatial memory. In Experiment 1, subjects had to retain for 3 sec. either the names of four letters (verbal memory) or the positions of three dots (spatial memory). The PET results manifested a clear cut double dissociation, as the verbal task activated primarily left-hemisphere regions whereas the spatial task activated only right-hemisphere regions. In Experiment 2. the identical sequence of letters was presented in all conditions, and what varied was whether subjects had to remember the names of the letters (verbal memory) or their positions in the display (spatial memory). In the verbal task, activation was concentrated more in the left than the right hemisphere; in the spatial task, there was suhstantial activation in both hemispheres, though in key regions, there was more activation in the right than the left hemisphere. Experiment 3 studied only verbal memory, and showed that a continuous memory task activated the same regions as the discrete verbal task used in Experiment 1. Taken together, these results indicate that verbal and spatial working memory are implemented by different neural structures.




    https://academic.oup.com/scan/article/17/1/109/5865742

    Our results with RT data provide evidence on the role of the left DLPFC in proactive control and suggest that the right DLPFC is implicated in reactive control.




    https://www.rcpsych.ac.uk/docs/defau...n%3Da1e381e1_2

    Reasoning is by no means confined to the left hemisphere, though sequential analysis largely is. Deductive reasoning, many kinds of mathematical procedures and problem-solving, and the phenomenon of sudden insight into the nature of a complex construct, seem to be underwritten by the right hemisphere, in fact by areas that cognitive science tells us are also involved in the ‘processing’ of emotion.
    Last edited by Petter; 02-09-2024 at 07:26 AM.

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    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774752/

    The ‘technological hypothesis’ proposes that gestural language evolved in early hominins to enable the cultural transmission of stone tool-making skills, with speech appearing later in response to the complex lithic industries of more recent hominins. However, no flintknapping study has assessed the efficiency of speech alone (unassisted by gesture) as a tool-making transmission aid. Here we show that subjects instructed by speech alone underperform in stone tool-making experiments in comparison to subjects instructed through either gesture alone or ‘full language’ (gesture plus speech), and also report lower satisfaction with their received instruction. The results provide evidence that gesture was likely to be selected over speech as a teaching aid in the earliest hominin tool-makers; that speech could not have replaced gesturing as a tool-making teaching aid in later hominins, possibly explaining the functional retention of gesturing in the full language of modern humans; and that speech may have evolved for reasons unrelated to tool-making. We conclude that speech is unlikely to have evolved as tool-making teaching aid superior to gesture, as claimed by the technological hypothesis, and therefore alternative views should be considered. For example, gestural language may have evolved to enable tool-making in earlier hominins, while speech may have later emerged as a response to increased trade and more complex inter- and intra-group interactions in Middle Pleistocene ancestors of Neanderthals and Homo sapiens; or gesture and speech may have evolved in parallel rather than in sequence.

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    the left hemisphere:

    tools (incl. details/parts) ---> language

    1. language ---> sequential analysis

    2. tools ---> sequential analysis

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    known/useful objects (food) <--> tools (incl. details/parts) ... focus, the left hemisphere

    unknown objects (predator or enemy) ... vigilance, the right hemisphere

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    e = expressive/quick decisions

    i = inexpressive

    l = the left hemisphere

    r = the right hemisphere

    d = the dorsal stream

    v = the ventral stream

    o = the outer world

    p = precuneus (the inner world)

    m = memory

    w = working memory and memory

    n = imagination/prefrontal synthesis (incl. s/facts)

    s = the sensory cortex

    a = agreeableness (cooperative)

    c = competitive

    x = current strategy

    y = alternative strategies

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    Brian Cox (physicist)

    DMN, FPN/CEN ... 2 and 2

    e, i ... 3 and 1

    l, r ... 1 and 3

    d, v ... 2 and 2

    o, p ... 1 and 3

    m, w ... 1 and 3

    n, s ... 3 and 1

    a, c ... 3 and 1

    x, y ... 1 and 3

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    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811327/

    Numerous studies have suggested that regions across frontal and parietal cortex are important for executive control (e.g., (Corbetta & Shulman, 2002; D’Esposito, et al., 1995; Dosenbach, Fair, Cohen, Schlaggar, & Petersen, 2008; Duncan & Owen, 2000; Hopfinger, Buonocore, & Mangun, 2000; Miller & Cohen, 2001; Moore, 2006)). These areas are among the most commonly engaged across different tasks (Nelson, et al., 2010), especially tasks that require goal-directed processing (Dosenbach, et al., 2006; Duncan & Owen, 2000). Indeed, these “control” regions are especially active during periods of tasks that are tightly associated with task control initiation, maintenance, and modification (Dosenbach, et al., 2006), such as when task instructions are cued, sustained across task execution periods, and when errors are made signaling the need for behavioral adjustments. Although some research has treated these areas as a singular network - e.g., the “multiple demand” or “executive control” network of the brain ((Duncan & Owen, 2000); see also (Miller & Cohen, 2001)) – evidence from resting state functional connectivity (rs-FC) studies suggest that these control regions are decomposable into (at least) two relatively separate networks: the cinguloopercular (CO) and frontoparietal (FP) networks ((Dosenbach, et al., 2007); although we do no focus on them here, in addition to the CO and FP networks, the salience (Seeley, et al., 2007), and dorsal and ventral attention networks (Corbetta & Shulman, 2002) may be considered additional members of this group of control networks; see Box 1 for a description of network nomenclature).

    [...]

    These findings suggest that the CO network is closely tied to functions related to maintaining task sets, whereas the FP network may be more closely tied to moment-to-moment adaptive control needed for implementing specific configurations of the task.

    [...]

    A practical example may help to illustrate the hypothesized distinctions between these two networks. In daily life, we frequently call on different forms of top-down control, including during our engagement in recreational sports. We suggest that within this context, the CO network is important for maintaining a sustained representation of which activity one is playing (e.g., baseball or soccer) and the relevant parameters for that activity (e.g., use your hands to throw the ball vs. use your feet to kick the ball). The FP network, instead, would help to enact processes that are relevant to particular portions of the game (e.g., while batting, it is important to respond to whether the pitcher is throwing fast or curve balls in order to improve your batting percentage, and while playing soccer it is important to detect whether a goalie is shifting left or right when shooting a penalty kick to improve chances of scoring). Thus, the start of the game will be associated with both networks (the CO to maintain the relevant game parameters, the FP to coordinate the specific plays that occur at the start of the game), as well as error signals (the CO to update task representations to improve performance, e.g., if your understanding of one of the game rules or their enforcement by the referee was incorrect; the FP to adjust subsequent actions in response to the consequences of the error). The CO network will more uniquely, however, exhibit sustained activity across the entire game necessary for representing the task-state at hand.

    [...]

    Although these previous findings have provided evidence for distinct functional roles in the CO and FP networks, they did so primarily by contrasting their functions in different task or trial-types. A recent set of studies from our laboratory adopted a specialized “slow reveal” paradigm to investigate whether these networks also had distinct roles, but within a decision-making trial (Gratton, et al., 2017; Ploran, et al., 2007; Wheeler, et al., 2006). In this paradigm, a stimulus is gradually unveiled from behind a noise mask. Participants are asked to respond when they have identified the item (or, in other cases, made a decision about whether they have seen the item before). By examining activation timecourses from trials in which participants responded early or late, we can separate trial-level responses with different characteristics. Interestingly, we found that regions in the CO, L FP, and R FP segregated from one another using a data-driven hierarchical clustering approach (Gratton, et al., 2017). This provides evidence that the CO, as well as the lateralized pieces of the FP network have distinct functional roles within trials. Furthermore, an analysis of the timecourses from the CO and FP networks suggested that these functions are associated with distinct aspects of decision-making: L FP regions had early onsets with gradually increasing responses that peaked around the moment of decision, much like in evidence accumulator models (Gold & Shadlen, 2007), CO regions had transient responses tightly linked to the decision, as would be expected with a performance report measure, and R FP regions had delayed and prolonged responses, primarily occurring after the response, suggesting that they were associated with post-response processing like response re-evaluation and adjustment (Gratton, et al., 2017). A related study from Sestieri and colleagues (Sestieri, Corbetta, Spadone, Romani, & Shulman, 2014) also found the FP and CO had distinct roles in long trials for perceptual and memory tasks, dissociating from one another both by the timecourses of their activity as well as their functional connectivity profiles.

  15. #975
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    https://neuro.psychiatryonline.org/d...np.23.2.jnp121

    Thus, MCC (or dACC) is “cognitive”—involved in conflict-monitoring and response-selection and execution. Within MCC, aMCC is implicated in emotional appraisal, conflict-monitoring, approach–avoidance decisions, and willed control of actions. pMCC is involved in body-orientation and movement-execution. ACC (or vACC) is “affective,”—involved in emotion assessment, emotion-related learning, and autonomic regulation. Within ACC, pACC is implicated in emotional regulation, autonomic integration, and affect related to pain. sACC is implicated in autonomic control, visceral integration, and conditioned learning.

    ------

    SN and CON <--> dACC

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    the right hemisphere + the medial frontopolar cortex (current strategy) ---> perfectionism

  17. #977
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    https://www.researchgate.net/figure/...fig1_337634232

    Components of the triple network model. (A) The default mode network is mainly composed of the medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus (PCC/PCu), and the temporal cortex (TC), hippocampus formation (HF) and inferior parietal lobule (IPL) are also closely related to this network. (B) The central executive network (CEN) is mainly composed of the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC), dorsolateral prefrontal cortex (DMPFC) and frontal eye field (FEF). (C) The salience network is composed of the insular cortex (IC), dorsal anterior cingulate cortex (dACC), temporal pole (TP) and amygdala (Amy).



    https://www.researchgate.net/figure/...fig2_359750403

    The salience network (SN) plays a central role in switching between the default mode network (DMN) and central executive network (CEN) ...

    ------

    (SN, not CON)

  18. #978
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    a new dichotomy:

    11. problem-solving vs. decision-making (FPN vs. FPN + CON/SN)

  19. #979
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    https://www.sciencedirect.com/scienc...53811923004652

    Cortical task control networks, including the cingulo-opercular (CO) network play a key role in decision-making across a variety of functional domains. In particular, the CO network functions in a performance reporting capacity that supports successful task performance, especially in response to errors and ambiguity. In two studies testing the contribution of the CO network to ambiguity processing, we presented a valence bias task in which masked clearly and ambiguously valenced emotional expressions were slowly revealed over several seconds. This slow reveal task design provides a window into the decision-making mechanisms as they unfold over the course of a trial. In the main study, the slow reveal task was administered to 32 young adults in the fMRI environment and BOLD time courses were extracted from regions of interest in three control networks. In a follow-up study, the task was administered to a larger, online sample (n = 81) using a more extended slow reveal design with additional unmasking frames. Positive judgments of surprised faces were uniquely accompanied by slower response times and strong, late activation in the CO network. These results support the initial negativity hypothesis, which posits that the default response to ambiguity is negative and positive judgments are associated with a more effortful controlled process, and additionally suggest that this controlled process is mediated by the CO network. Moreover, ambiguous trials were characterized by a second CO response at the end of the trial, firmly placing CO function late in the decision-making process.





    https://pubmed.ncbi.nlm.nih.gov/26582792/

    Dorsal anterior cingulate cortex (dACC) activation is commonly observed in studies of pain, executive control, conflict monitoring, and salience processing, making it difficult to interpret the dACC's specific psychological function. Using Neurosynth, an automated brainmapping database [of over 10,000 functional MRI (fMRI) studies], we performed quantitative reverse inference analyses to explore the best general psychological account of the dACC function P(Ψ process|dACC activity). Results clearly indicated that the best psychological description of dACC function was related to pain processing--not executive, conflict, or salience processing. We conclude by considering that physical pain may be an instance of a broader class of survival-relevant goals monitored by the dACC, in contrast to more arbitrary temporary goals, which may be monitored by the supplementary motor area.





    https://journals.sagepub.com/doi/10....67702620959341

    Rapid instructed task learning (RITL) is the uniquely human ability to transform task information into goal-directed behavior without relying on trial-and-error learning. RITL is a core cognitive process supported by functional brain networks. In patients with schizophrenia, RITL ability is impaired, but the role of functional network connectivity in these RITL deficits is unknown. We investigated task-based connectivity of eight a priori network pairs in participants with schizophrenia (n = 29) and control participants (n = 31) during the performance of an RITL task. Multivariate pattern analysis was used to determine which network connectivity patterns predicted diagnostic group. Of all network pairs, only the connectivity between the cingulo-opercular network (CON) and salience network (SAN) during learning classified patients and control participants with significant accuracy (80%). CON-SAN connectivity during learning was significantly associated with task performance in participants with schizophrenia. These findings suggest that impaired interactions between identification of salient stimuli and maintenance of task goals contributes to RITL deficits in participants with schizophrenia.






    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962782/

    Relative to the FPN, activation in the CON was particularly pronounced during transitions into and out of particular control demands. Moreover, the relationship of each CON subnetwork to behavior was mediated by a respective FPN subnetwork. Such data are consistent with the idea that the CON motivates the FPN, which, in turn, drives behavior. Within the CON, the dorsomedial prefrontal cortex (dmPFC) mediated the relationship between the anterior insula and FPN, suggesting that the dmPFC acts as the crux that links the CON to the FPN. Collectively, these data indicate that parallel CON–FPN subnetworks mediate controlled behaviors at distinct timescales/mediums.

    [...]

    One barrier toward understanding the CON is that prior theories have presented conflicting accounts. On the one hand, the CON has been hypothesized to play a sustained role. For example, the CON has been proposed to sustain stable set control (Dosenbach et al., 2006, 2007) and to maintain tonic alertness (Sadaghiani and D'Esposito, 2015). These sustained processes are in contrast to phasic “rapid adaptive control” initiation by the FPN (Dosenbach et al., 2008). Other accounts propose that CON areas perform more transient processes. For example, one model proposes that cingulo-opercular areas initiate dynamic switching between the internally related default mode network (DMN) and the externally driven FPN (Menon and Uddin, 2010). Furthermore, a transient role in cognition is often attributed to the anterior cingulate cortex (ACC) of the CON in signaling conflict (Botvinick et al., 2001), prediction errors (Alexander and Brown, 2011), and the expected value of control (Shenhav et al., 2013). In these models, transient ACC signals are thought to drive adjustments in the sustained control processes instantiated by the FPN. Hence, different models conflict with their attribution of transient versus sustained roles to the CON versus FPN.

    [...]

    Prior work has suggested that parallel medial-to-lateral PFC systems are organized by a control process whereby medial areas send motivational incentives to lateral areas to exert top-down control (Kouneiher et al., 2009). Alexander and Brown (2018) computationally formalized and extended this idea, suggesting that signals from parallel medial-to-lateral PFC areas reflect prediction errors more broadly that serve to update lateral PFC representations. Based on these works, we hypothesized that the role of the medial PFC may extend to the CON more generally, and the role of the lateral PFC may extend to the FPN more generally. If so, one would predict that the CON drives the FPN, which, in turn, drives controlled behavior.





    https://link.springer.com/content/pd...BF03331976.pdf





    https://www.biorxiv.org/content/10.1...772v1.full.pdf

    see figure 3

    the Action CON subnetwork was most closely linked to motor networks, the Decision CON subnetwork was most closely linked to the Salience network, and the Feedback CON subnetwork was most closely linked to the Dorsal Attention Networks (Figure 4B)





    https://acris.aalto.fi/ws/portalfile..._psychosis.pdf





    https://www.colelab.org/pubs/SchultzItoCole_2022.pdf

    see figure 1 ... CON: it is not medial frontopolar cortex





    https://www.jneurosci.org/content/43/7/1225





    https://europepmc.org/article/MED/17403644





    https://psychology.unl.edu/Neta%20Ne...sen%202016.pdf

    The cingulo-opercular network (including the dorsal anterior cingulate and bilateral anterior insula) shows 3 distinct task-control signals across a wide variety of tasks, including trial-related signals that appear to come online at or near the end of the trial. Previous work suggests that there are separable responses in this network for errors and ambiguity, implicating multiple types of processing units within these regions.

    [...]

    Extant work using mixed block/event-related designs, which allow for the modeling of both sustained and transient signals during a task, have demonstrated that a set of regions in the cingulo-opercular network (including the dorsal anterior cingulate/medial superior frontal cortex; dACC/msFC, and bilateral anterior insula/frontal operculum; aI/fO) show 3 distinct task-control signals across a wide variety of tasks...





    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135913/

    CON: L parietal operculum, L temporal occipital, L frontal operculum insula, L lateral prefrontal cortex, L medial/anterior cingulate, R temporal occipital parietal, R precentral, R frontal operculum insula, R ventral prefrontal cortex, R lateral prefrontal cortex, R medial/anterior cingulate

    FPCN: L parietal, L temporal, L dorsal prefrontal cortex, L lateral prefrontal cortex, L orbital frontal cortex, L ventral prefrontal cortex, L precuneus, L cingulate, L medial posterior prefrontal cortex, R parietal, R temporal, R ventral prefrontal cortex, R lateral prefrontal cortex, R precuneus, R cingulate, R medial posterior prefrontal cortex





    https://www.sciencedirect.com/scienc...13158220300516

    CON: dorsal anterior cingulate cortex, anterior prefrontal cortex, anterior insula etc

    The CO network has an important role in error monitoring, and initiating and adapting control, while the FP network enables goal-directed behavior and flexibility.


    ------


    SN drives CON, and CON drives FPN (?)
    Last edited by Petter; 02-11-2024 at 05:20 PM.

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    CON <--> medial frontopolar cortex

    FPN <--> lateral frontopolar cortex

    (?)

    ------

    large-scale brain networks 2.png

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    11. problem-solving vs. decision-making (FPN vs. FPN + CON/SN)
    ... or dlPFC vs. dmPFC

    ------

    dmPFC and dlPFC.jpg

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    https://www.biorxiv.org/content/10.1....561772v1.full

    Substructure of the brain’s Cingulo-Opercular network

    The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

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    Brain-Based Mechanisms Underlying Causal Reasoning ... J.A. Fugelsang and K.N. Dunbar

    They found significant activations in V5, medial, and superior temporal lobes bilaterally, as well as regions in the left superior temporal and intraparietal sulcus. As these regions are strongly implicated in tasks involving complex visual analyses, they argued that the visual system is specifically designed to recover the causal structure of dynamic visual events in the environment. In a related study, Fugelsang et al. (2005) examined the extent to which causal stimuli differentially recruit neural regions associated with spatial and temporal contiguity when those cues to causality are manipulated. Consistent with Blakemore et al. (2001) and Fonlupt (2003), we found similar activations in the temporal lobes when contrasting the causal stimuli to the stimuli with a spatial gap. When causal stimuli were contrasted with stimuli containing a temporal gap, however, activations were predominantly in the frontal and parietal cortices. Importantly, when causal stimuli were contrasted with both noncausal stimuli (those containing spatial and temporal gaps), activations were predominantly found in the frontal and parietal cortices in the right hemisphere (Fig. 3). The frontal activity found is consistent with the frontal activity found by Fonlupt (2003).

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    12. structure vs. cause and effect ... the parietal lobe vs. the temporal lobe (a new dichotomy)

    ------

    https://i.imgur.com/sqHQMJB.jpg

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    4. the dorsal stream vs. the ventral stream ... "how"/"where" vs. "what" ... spatial relationships vs. patterns ... unambiguous vs. ambiguous (vlPFC, heuristic)

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    https://www.sciencedirect.com/scienc...68010219301762

    Allocentric representations of space in the hippocampus

    The hippocampal-entorhinal system is essential for navigation and memory. The first description of spatially tuned place cell activity in area CA1 of the hippocampus suggested that spatial representations are not centered on self, but are rather allocentric. This idea is supported by extensive neurophysiological data, including temporally coordinated sequential activity during theta phase precession and sharp wave ripples. CA1 pyramidal neurons represent other information as well, such as objects, time, and events. Additionally, our recent research revealed that CA1 place cells jointly represent the spatial location of self and a conspecific, further supporting the idea of allocentric spatial representations by CA1 place cells. The neural mechanisms underlying CA1 spatial representations have long remained a mystery, but recent research examining circuit dynamics and synaptic plasticity suggests that the temporal relationships of inputs from entorhinal cortex layer III and CA3 could be critical for generating spatially tuned CA1 activity. Here, I review studies of the hippocampal representations of space and other features, and discuss the related networks and synaptic mechanisms supporting the representations of these features.

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    functions (method 1)

    Sldp, Sldt, Slvx, Slvy, Srdp, Srdt, Srvx, Srvy

    N, T, F



    l = the left hemisphere

    r = the right hemisphere

    d = the dorsal stream

    v = the ventral stream

    p = the parietal lobe

    t = the temporal lobe

    x = problem-solving

    y = decision-making



    attitudes

    E = expressive/quick decisions

    I = inexpressive

    L = alternative strategies ... lateral frontopolar cortex

    M = current strategy ... medial frontopolar cortex

    C = competitive

    A = agreeableness (cooperative)

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    a physicist

    1. people-oriented vs. task-oriented ... 1 and 3

    2. the external world vs. the internal world ... 1 and 3

    3. expressive/quick decisions vs. inexpressive ... 1 and 3

    4. the dorsal stream vs. the ventral stream ... 2 and 2

    5. the left hemisphere vs. the right hemisphere ... 1 and 3

    6. competitive vs. cooperative ... 2 and 2

    7. logical reasoning vs. habits, facts, size/shape ... 3 and 1

    8. imagination/prefrontal synthesis vs. memory recall ... 3 and 1

    9. current strategy vs. alternative strategies ... 2 and 2

    10. (long-term) goals vs. immediate sensory needs ... 3 and 1

    11. problem-solving vs. decision-making ... 3 and 1

    12. structure vs. cause and effect ... 1 and 3

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    a chess player

    1. people-oriented vs. task-oriented ... 1 and 3

    2. the external world vs. the internal world ... 1 and 3

    3. expressive/quick decisions vs. inexpressive ... 1 and 3

    4. the dorsal stream vs. the ventral stream ... 2 and 2

    5. the left hemisphere vs. the right hemisphere ... 2 and 2

    6. competitive vs. cooperative ... 3 and 1

    7. logical reasoning vs. habits, facts, size/shape ... 3 and 1

    8. imagination/prefrontal synthesis vs. memory recall ... 3 and 1

    9. current strategy vs. alternative strategies ... 3 and 1

    10. (long-term) goals vs. immediate sensory needs ... 3 and 1

    11. problem-solving vs. decision-making ... 2 and 2

    12. structure vs. cause and effect ... 1 and 3

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    a chess player

    3. expressive/quick decisions vs. inexpressive ... 1 and 3
    There are lots of quick decisions in blitz chess, though. This dichotomy is about impulsiveness (dopamine) rather than fast thinking, so I should probably exclude it.

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    a mathematician

    1. people-oriented vs. task-oriented ... 1 and 3

    2. the external world vs. the internal world ... 1 and 3

    3. expressive/impulsive vs. inexpressive ... 1 and 3

    4. the dorsal stream vs. the ventral stream ... 3 and 1

    5. the left hemisphere vs. the right hemisphere ... 2 and 2

    6. competitive vs. cooperative ... 2 and 2

    7. logical reasoning vs. habits, facts, size/shape ... 3 and 1

    8. imagination/prefrontal synthesis vs. memory recall ... 3 and 1

    9. current strategy vs. alternative strategies ... 1 and 3

    10. (long-term) goals vs. immediate sensory needs ... 3 and 1

    11. problem-solving vs. decision-making ... 3 and 1

    12. structure vs. cause and effect ... 3 and 1

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    9. current strategy vs. alternative strategies
    ... or task, goal




    the right hemisphere + the medial frontopolar cortex (current strategy) ---> perfectionism
    ... and single-tasking

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    Furthermore, an analysis of the timecourses from the CO and FP networks suggested that these functions are associated with distinct aspects of decision-making: L FP regions had early onsets with gradually increasing responses that peaked around the moment of decision, much like in evidence accumulator models (Gold & Shadlen, 2007), CO regions had transient responses tightly linked to the decision, as would be expected with a performance report measure, and R FP regions had delayed and prolonged responses, primarily occurring after the response, suggesting that they were associated with post-response processing like response re-evaluation and adjustment (Gratton, et al., 2017). A related study from Sestieri and colleagues (Sestieri, Corbetta, Spadone, Romani, & Shulman, 2014) also found the FP and CO had distinct roles in long trials for perceptual and memory tasks, dissociating from one another both by the timecourses of their activity as well as their functional connectivity profiles.
    decision-making <--> the left hemisphere

    response re-evaluation and adjustment <--> the right hemisphere

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    https://www.christofflab.ca/wp-conte...bstraction.pdf

    The prefrontal cortex (PFC) plays a crucial role in cognitive control and higher mental functions by maintaining working memory representations of currently relevant information, thereby inducing a mindset that facilitates the processing of such information. Using fMRI, we examined how the human PFC implements mindsets for information at varying levels of abstraction. Subjects solved anagrams grouped into three kinds of blocks (concrete, moderately abstract, and highly abstract) according to the degree of abstraction of their solutions. Mindsets were induced by cuing subjects at the beginning of every block as to the degree of abstraction of solutions they should look for. Different levels of abstraction were matched for accuracy and reaction time, allowing us to examine the effects of varying abstraction in the absence of variations in cognitive complexity. Mindsets for concrete, moderately abstract, and highly abstract information were associated with stronger relative recruitment of ventrolateral, dorsolateral, and rostrolateral PFC regions, respectively, suggesting a functional topography whereby increasingly anterior regions are preferentially associated with representations of increasing abstraction. Rather than being a structural property of the neurons in different prefrontal subregions, this relative specialization may reflect one of the principles according to which lateral PFC adaptively codes and organizes task-relevant information.

    [...]

    This topography was hypothesized to hold in both hemispheres, consistent with previous findings (Deglin and Kinsbourne, 1996; Goel and Dolan, 2001; Binder et al., 2005; Allen et al., 2007; Studer and Hubner, 2008) demonstrating that the processing of abstract and concrete information is either bilaterally distributed or lateralized to either hemisphere in a task dependent manner.

    [...]

    The present results bear implications for understanding the functions of the most anterior lateral PFC region, the RLPFC, whose role in human cognition continues to pose challenges to our neuroscientific theories. RLPFC recruitment has been linked to conditions of high task complexity more consistently than any other PFC subregion (Christoff and Owen, 2006). It is activated during some of the most complex forms of human cognition, including inductive and deductive inferences during reasoning (e.g., Christoff et al., 2001; Monti et al., 2007), hypothesis testing and set shifting during problem solving (Berman et al., 1995; Goel and Vartanian, 2005), and subgoal processing during planning and coordination of multiple tasks (e.g., Koechlin et al., 1999; Braver and Bongiolatti, 2002; Ramnani and Owen, 2004). The link between RLPFC recruitment and task complexity is so consistent that its sensitivity to cognitive complexity has been proposed to represent one of the defining features of its functions (Christoff and Owen, 2006; Gilbert et al., 2006). Perhaps the biggest paradox of RLPFC functions, however, is presented by findings of its activation not only during highly complex tasks, but also during conditions of “rest” when tasks are altogether absent (Shulman et al., 1997; Christoff et al., 2004; Christoff et al., in press) and by mind wandering, especially when individuals are unaware of the fact that they are mind wandering (Christoff et al., 2009).

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    https://royalsocietypublishing.org/d...rstb.2017.0122

    Neuroimaging and neuropsychological research has consistently suggested that abstract and concrete concepts differ. The particular brain regions involved and the reasons for these differences remain controversial, but the existence of differences is consistent. Neuropsychological double dissociations have pointed to reliance of concrete concepts on featural or taxonomic, and that of abstract concepts on associative or thematic (see [8] for a discussion). With regard to neuroanatomy, a meta-analysis of 19 studies found that two regions were consistently activated for abstract over concrete words or sentences: the left anterior temporal lobe (ATL) and the inferior frontal gyrus (IFG). This contrasts with the findings for concrete concepts, which revealed a more extensive network that includes bilateral angular gyrus (AG), posterior lateral, medial and ventral temporal lobe, and posterior cingulate (pCi) and precuneus.

    These findings are consistent with both of the classical theories of abstract/concrete concept representation. According to the Context Availability Theory abstract words are more reliant on the context in which they occur. Abstract word processing requires greater activation of, and integration with, the context. This is consistent with the left IFG activation, which is associated with strategic semantic access and integration. The Dual Coding Theory posits that only concrete concepts have a direct connection to image-based or visual representations, while abstract concepts are represented only through verbal associations. Activation of a number of areas associated with higher-order visual processing, such as the parahippocampal gyrus, fusiform gyrus and middle occipital gyrus (MOG), as well as greater bilateral activation, supports this view. Left lateralized activation for abstract concepts, including the traditional language processing area of IFG, also supports the notion of importance of verbal associations for abstract concepts.

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    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427149/

    These results confirm the hypothesis that L-aPFC is causally and selectively involved in the integration of information in working memory. They additionally suggest that pre-integration loading and post-integration unloading of information involving this area may be active and resource-consuming processes.





    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3128701/


    Prospective memory is defined as the ability to carry out a delayed intended action. It refers to a type of memory that allows maintaining and retrieving future plans, goals and activities, which is a crucial ability for human everyday life. Two types of prospective memory can be considered: time-based and event-based (Harris, 1984; Kvavilashvili & Ellis, 1996; for a review see McDaniel & Einstein, 2007). Time-based prospective memory consists of remembering to do something at a particular time, for example remember the meeting with Paul at 5 pm. Event-based prospective memory consists of remembering to do something in a particular situation. For instance, remember to ask Paul for his book next time I meet him.

    [...]

    the right polar prefrontal region (in Brodmann area 10) were specifically associated with a deficit in time-based prospective memory tasks for both words and pictures.

    [...]

    The same region was found to be involved using both words and pictures, suggesting that right rostral PFC plays a material nonspecific role in prospective memory.





    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630805/

    Here, we provide convergent evidence from fMRI and TMS that RLPFC is necessary to resolve task-position uncertainty while performing internally-monitored task sequences (Schneider and Logan, 2006). In other words, RLPFC provides a momentary check necessary to keep us “on track” during performance of a sequence.





    https://www.jneurosci.org/content/39/8/1471

    They suggest that sequential control processes are integral to the dynamics of RLPFC activity. Advancing knowledge of the neural bases of sequential control is crucial for our understanding of the sequential processes that are necessary for daily living.

    ------

    the left hemisphere + rlPFC (BA10) ---> planning
    Last edited by Petter; 02-19-2024 at 10:03 AM.

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    https://link.springer.com/content/pd...BF03198724.pdf

    Thomas and Weaver's (1975) model for time perception is applied to the data, and it is suggested that the left hemisphere relies on a timer to estimate duration, while the right hemisphere relies on a visual information processor to estimate duration.





    https://www.sciencedirect.com/scienc...082?via%3Dihub

    Right ear superiority was found for two groups of 24 subjects on a dichotic listening test of melodies each differing only in rhythm. In addition, no ear difference was found in the same two groups for a dichotic melodies test differing only in pitch or pitch pattern. Finally, the usual left ear superiority was seen far dichotic presentation of chords and the usual right ear superiority was seen for the dichotic presentation of digits.

    The results imply that in neither of the non-verbal (melodies) tests was the right hemisphere superior to the left. In fact for one test the reverse was true: the left hemisphere was superior to the right for melody recognition based on a rhythm cue.

    The apparent conflict between this and previous studies is explained by the notion that it is not the stimuli per se that govern hemispheric dominance, but rather the cognitive functioning required by the left and right hemispheres in order to process them.





    https://www.nature.com/articles/s41597-022-01645-3

    Probabilistic atlas for the language network based on precision fMRI data from >800 individuals





    https://hbr.org/1976/07/planning-on-...g-on-the-right

    In the left hemisphere of most people’s brains (lefthanders largely excepted) the logical thinking processes are found. It seems that the mode of operation of the brain’s left hemisphere is linear; it processes information sequentially, one bit after another, in an ordered way. Perhaps the most obvious linear faculty is language. In sharp contrast, the right hemisphere is specialized for simultaneous processing; that is, it operates in a more holistic, relational way, Perhaps its most obvious faculty is comprehension of visual images.

    [...]

    What does this specialization of the brain mean for the way people function? Speech, being linear, is a left-hemispheric activity, but other forms of human communication, such as gesturing, are relational rather than sequential and tend to be associated with the right hemisphere. Imagine what would happen if the two sides of a human brain were detached so that, for example, in reacting to a stimulus, a person’s words would be separate from his gestures. In other words, the person would have two separate brains—one specialized for verbal communication, and the other for gestures—that would react to the same stimulus.





    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3294255/

    In general, auditory stimuli that are broad-band, rapidly-changing or temporally complex, including speech and noise signals, are preferentially processed in auditory areas of the left hemisphere while slowly changing or steady state, narrow-band or tonal stimuli, including music, are primarily processed in the right hemisphere (Tervaniemi & Hugdahl, 2003; Zatorre, Belin, & Penhune, 2002; Tervaniemi & Hugdahl, 2003; Zatorre et al., 2002).
    Last edited by Petter; 02-20-2024 at 07:00 AM.

  38. #998
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    https://www.cell.com/fulltext/S0896-6273(03)00123-5

    In contrast, a relational memory account states that the MTL is critically involved in associative processes that bind multiple aspects of stimulus events into memory (Cohen and Eichenbaum 1993, Wallenstein et al. 1998). Relational memory accounts thus expect the MTL to be involved in sequence learning whenever complex stimulus-stimulus associations are encoded, regardless of whether learning is explicit or implicit. Explicit-implicit and relational memory accounts thus diverge principally over MTL involvement in implicit learning.

    [...]

    Explicit Sequence blocks were also contrasted across runs. Table 2 shows that activation in Sequence blocks was greater during the first than the last two runs in the right MTL, bilateral DLPFC, and bilateral caudate.

  39. #999
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    https://www.researchgate.net/publica...ft_Right_Brain

    Origins of the Left & Right Brain

  40. #1000
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    https://academic.oup.com/cercor/arti...4/1186/6555902

    Although hemispheric lateralization of creativity has been a longstanding topic of debate, the underlying neurocognitive mechanism remains poorly understood. Here we designed 2 types of novel stimuli—“novel useful and novel useless,” adapted from “familiar useful” designs taken from daily life—to demonstrate how the left and right medial temporal lobe (MTL) respond to novel designs of different usefulness. Taking the “familiar useful” design as a baseline, we found that the right MTL showed increased activation in response to “novel useful” designs, followed by “novel useless” ones, while the left MTL only showed increased activation in response to “novel useful” designs. Calculating an asymmetry index suggests that usefulness processing is predominant in the left MTL, whereas the right MTL is predominantly involved in novelty processing. Moreover, the left parahippocampal gyrus (PHG) showed stronger functional connectivity with the anterior cingulate cortex when responding to “novel useless” designs. In contrast, the right PHG showed stronger connectivity with the amygdala, midbrain, and hippocampus. Critically, multivoxel representational similarity analyses revealed that the left MTL was more effective than the right MTL at distinguishing the usefulness differences in novel stimuli, while representational patterns in the left PHG positively predicted the post-behavior evaluation of “truly creative” products. These findings suggest an apparent dissociation of the left and right MTL in integrating the novelty and usefulness information and novel associative processing during creativity evaluation, respectively. Our results provide novel insights into a longstanding and controversial question in creativity research by demonstrating functional lateralization of the MTL in processing novel associations.




    https://www.bu.edu/mdrc/files/2017/0...TImeReview.pdf

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