Rolf Degen summarizing: Although people tend to forego larger future rewards in order to gain immediate pleasure, they sometimes willingly cherish the delay

Deliberating trade-offs with the future. Adam Bulley & Daniel L. Schacter. Nature Human Behaviour volume 4, pages238–247(2020), Mar 17. https://www.nature.com/articles/s41562-020-0834-9

Abstract: Many fundamental choices in life are intertemporal: they involve trade-offs between sooner and later outcomes. In recent years there has been a surge of interest into how people make intertemporal decisions, given that such decisions are ubiquitous in everyday life and central in domains from substance use to climate change action. While it is clear that people make decisions according to rules, intuitions and habits, they also commonly deliberate over their options, thinking through potential outcomes and reflecting on their own preferences. In this Perspective, we bring to bear recent research into the higher-order capacities that underpin deliberation—particularly those that enable people to think about the future (prospection) and their own thinking (metacognition)—to shed light on intertemporal decision-making. We show how a greater appreciation for these mechanisms of deliberation promises to advance our understanding of intertemporal decision-making and unify a wide range of otherwise disparate choice phenomena.

How do teenagers perceive their intelligence? Narcissism, intellect, well-being and gender as correlates of self-assessed intelligence among adolescents

How do teenagers perceive their intelligence? Narcissism, intellect, well-being and gender as correlates of self-assessed intelligence among adolescents. Marcin Zajenkowski. Personality and Individual Differences, March 17 2020, 109978. https://doi.org/10.1016/j.paid.2020.109978

Abstract: Self-assessed intelligence (SAI) and its correlates have been extensively studied in adults. However, our understanding of how younger people perceive intelligence is limited. The current study aimed to fill this gap by investigating how SAI is associated with objective intelligence, gender, personality traits, and well-being in a sample (N = 428) of high-school students. The results revealed that SAI was not correlated with objectively measured intelligence (Raven's test); however, it was associated with other constructs. First, there were gender differences, i.e. boys' self-estimates of their intelligence were higher than that of girls. Furthermore, SAI was strongly related to grandiose narcissism and moderately related to the personality trait intellect. Additionally, high SAI was associated with high levels of well-being. Finally, SAI accounted for the link between narcissism and well-being as well as that between intellect and well-being. The lack of correlation between SAI and IQ score is consistent with previous findings suggesting that the conception of intelligence in adolescence differs from academic definitions of cognitive ability. On the other hand, the strong association between SAI and narcissism suggests that the concept of intelligence might primarily be a manifestation of boldness and a narcissistic attitude in adolescence.

4. Discussion

The current study examined how self-assessed intelligence is associated with objective intelligence, gender, personality traits, and well-being in a group of high-school students. The results indicated that most of the SAI-related effects observed previously in adults can also be found in adolescents. However, the most important difference was a lack of correlation between self-assessed and objectively assessed intelligence, given that prior meta-analytic investigation has shown these two constructs to moderately overlap in adult populations (Freund & Kasten, 2012). Moreover, previous studies have also found a positive relation between objective cognitive abilities and self-assessed abilities in children and adolescents (Chamorro-Premuzic et al., 2010; Gold & Kuhn, 2017; Spinath et al., 2006). However, as mentioned above, in these latter studies the participants were asked to self-rate more narrow abilities rather than general intelligence. Additionally, the study by Gold and Kuhn (2017) included a slightly older sample than the one tested here. It should also be acknowledged that in the present research a non-verbal IQ test measuring fluid intelligence was used. According to the aforementioned findings, a mature conception of intelligence as abstract thinking and problem solving with both verbal and non-verbal material is formed later, e.g. around college time (Chen et al., 1988; Nicholls et al., 1986). It is possible then, that our participants' understanding of intelligence differed from adult conceptions of intelligence. Consequently, they may not have considered the skills required to succeed in Raven's test to be key characteristics of intelligence.

Despite the null correlation with objective intelligence, SAI displayed a pattern of associations with other variables. Specifically, boys self-rated their intelligence higher than girls self-rated theirs, whereas there was no gender difference in objective intelligence. Adult males similarly self-rate their intelligence higher than females self-rate theirs, despite negligible gender differences in objective general intelligence (Szymanowicz & Furnham, 2011). This effect has been described as the “male hubris, female humility” effect (Furnham, 2001). Specifically, it has been proposed that people view intelligence as male-normative and that gender differences in perceived intelligence may stem from the differential socialization of males (encouraged to be bold) and females (encouraged to be submissive) (Furnham, 2001). Studies investigating estimations by individuals' family members support this view. Typically, male family members (grandfathers, fathers, and brothers) are perceived to have higher general intelligence than that of their female counterparts (e.g. Furnham & Rawles, 1995). Moreover, parents tend to rate their sons' IQ as being higher than that of their daughters (Furnham & Gasson, 1998; Furnham, Reeves, & Budhani, 2002). The current results suggest that this effect occurs relatively early and might already be observed among 16-year olds. However, further research is required to establish the exact developmental stage at which gender differences in perceived intelligence are formed. For instance, in a study by Furnham and Budhani (2002) involving only a slightly younger sample (mean age 15.40 years, SD = 0.95) than the one used here, there were no gender differences in self-assessed general intelligence even though male self-estimations were higher than females' on more narrow abilities, i.e. spatial and mathematical ones.

In the present sample, SAI was associated with two personality traits: narcissism and intellect. Furthermore, narcissism explained the highest amount of variance in SAI. This result is in line with recent findings showing narcissism to be the strongest correlate of SAI among personality traits (Howard & Cogswell, 2018; Zajenkowski et al., 2019). The finding is interesting given that narcissism is essentially unrelated to objective IQ (Zajenkowski et al., 2019). Grandiose narcissism is a trait primarily defined by egocentrism, pronounced feelings of importance and entitlement (Campbell & Foster, 2007). People with high grandiose narcissism desire agentic attributes, such as dominance, sense of control, and social status (Campbell & Foster, 2007). Because intelligence is a key asset for the attainment of such attributes, narcissistic individuals are highly concerned with their intelligence (Zajenkowski et al., 2019). It has been shown that positive self-views in the domain of intelligence help them to maintain positive feelings (Zajenkowski et al., 2019). Additionally, narcissistic individuals view intelligence as a crucial factor that influences mainly interpersonal success, i.e. popularity among peers, social status, and relationship satisfaction (Zajenkowski et al., 2019). Thus, intelligence appears to be an important resource in gaining other people's admiration. The current results extend previous findings by showing that the concept of intelligence is an important building block of the narcissistic self-concept in young people. Even though the concept of intelligence is not fully formed in adolescence, it is already linked with a narcissistic attitude. This finding suggests that in people's minds the two phenomena, i.e. thinking positively about one's intelligence and narcissistic grandiosity, go together and that their coexistence occurs at a relatively early developmental stage.

In the present study, SAI was also positively associated with the trait intellect, which is consistent with other research on adults (e.g. Zajenkowski & Matthews, 2019). However, in contrast with previous studies (DeYoung, Quilty, Peterson, & Gray, 2014; Zajenkowski et al., 2019), intellect was unrelated to objective intelligence. According to DeYoung and colleagues (2014), intellect is part of a broader trait of openness/intellect and reflects intellectual engagement with semantic and abstract information, enjoyment of cognitive activity, and one's perceived cognitive abilities. Thus, to some extent intellect overlaps with self-assessed abilities. However, it also contains a more specific element related to intellectual curiosity. Zajenkowski et al. (2019) suggested that this element might differentiate narcissism from intellect in their relations with SAI. This view was supported by the finding that individuals with high intellect report high motivation and concentration on IQ tests, whereas highly narcissistic people do not genuinely engage with demanding cognitive tests (Zajenkowski et al., 2019). Thus, intellect seems to partially reflect a non-narcissistic attitude towards SAI that might be linked with cognitive engagement.

Another important finding of the current study concerns the positive link between SAI and well-being. The authors of a recent meta-analysis of SAI correlates have suggested that SAI could be regarded as a specific form of self-efficacy (Howard & Cogswell, 2018). Because modern jobs and work success rely on cognitive competence, intelligence has become a highly valued characteristic in society and one's self-worth is becoming increasingly dependent on one's intellectual abilities. This line of reasoning may also be relevant to the school environment, where the evaluation of cognitive performance is an essential part of the education system. Thus, SAI appears to play a central role in modern society and because of that may have an influence on self-esteem and well-being. Certainly, the present study indicates that the concept of intelligence is an important source of life satisfaction among high-school students. Additionally, SAI also accounted for the associations between narcissism and well-being and between intellect and well-being. The mechanisms underlying both findings might be different. Specifically, intellect, high intelligence might facilitate cognitive engagement and because of that be a source of pleasant feelings. In case of narcissism, it has been shown that grandiose narcissists pursue agentic goals such as high social status and believe that intelligence is a key attribute in attaining such goals (Zajenkowski et al., 2019). Therefore, intelligence inflated self-views enable grandiose narcissists to experience positive feelings. It is possible that high cognitive ability is linked to the sense of agency and social position already among adolescent narcissists and because of that, it increases their well-being. This hypothesis could be further examine by investigating how narcissistic students are perceived by their peers. Specifically, it would be interesting to explore whether one's popularity depends on how other students evaluate his/her intelligence.

The present study is not free of limitations. First, it used only one measure of objective intelligence. Future research should therefore include a wider range of IQ tests capturing other aspects of cognitive ability (e.g. verbal) to deepen our knowledge of adolescents' insight into their intelligence. In a similar vein, the measurement of SAI could be extended to include more narrow abilities. Previous studies on SAI using a multiple intelligence measures approach have produced interesting and more nuanced findings on adolescents (Furnham & Budhani, 2002). Finally, the current study had more female than male participants; future samples should be more balanced in terms of gender.

Bilateral neural interactions, excitatory & inhibitory, are present across the motor network during unimanual movements; an increase in task difficulty requires more efficient communication between hemispheres

Are unimanual movements bilateral? Sabrina Chettouf et al. Neuroscience & Biobehavioral Reviews, Volume 113, June 2020, Pages 39-50, https://doi.org/10.1016/j.neubiorev.2020.03.002

Highlights
• Bilateral neural interactions, excitatory and inhibitory, are present across the motor network during unimanual movements.
• An increase in task difficulty requires more efficient communication between hemispheres.
• Anatomical properties of transcallosal fiber tracts enable essential interhemispheric information exchange.
• Left (pre)motor areas play a key role in complex motor tasks.

Abstract: Motor control is a fundamental challenge for the central nervous system. In this review, we show that unimanual movements involve bi-hemispheric activation patterns that resemble the bilateral neural activation typically observed for bimanual movements. For unimanual movements, the activation patterns in the ipsilateral hemisphere arguably entail processes that serve to suppress interhemispheric cross-talk through transcallosal tracts. Improper suppression may cause involuntary muscle co-activation and as such it comes as no surprise that these processes depend on the motor task. Identifying the detailed contributions of local and global excitatory and inhibitory cortical processes to this suppression calls for integrating findings from various behavioral paradigms and imaging modalities. Doing so systematically highlights that lateralized activity in left (pre)motor cortex modulates with task complexity, independently of the type of task and the end-effector involved. Despite this lateralization, however, our review supports the idea of bi-hemispheric cortical activation being a fundamental mode of upper extremity motor control.

Keywords: UnimanualInterhemisphericMotor cortexMotor coordinationCorpus callosumBilateral activationElectroencephalography (EEG)Magnetoencephalography (MEG)Transcranial magnetic stimulation (TMS)Functional magnetic resonance imaging (fMRI)Structural MRI

4. Discussion

The question whether unimanual movements have a bilateral neural representation comes with quite some history. For many years it has been considered textbook knowledge that movement execution with one hand is characterized by largely – if not entirely – contralateral activation in the brain. This idea dates back to the nineteenth century and is based on early studies on animal brains and/or human pathology using invasive electrical stimulation (Jackson et al., 1870; Schiff, 1859). Gustav Fritsch together with Eduard Hitzig (1870) and, independently, David Ferrier (1873) stimulated the cortex surface of different (anesthetized) mammals and evoked movements in different parts of the contralateral side of the body. These studies allowed researchers to identify ordered motor maps within this contralateral hemisphere, in particular by Clinton Woolsey and Wilder Penfield in non-human mammals and in humans, respectively (Penfield and Boldrey, 1937; Woolsey and Fairman, 1946). In fact, Penfield and Boldrey (1937) identified the human motor homunculus just anterior to central sulcus (M1), i.e. the representation of body parts in brain areas containing an ensemble of neurons that, when activated, result in motor output. Especially in finely controlled limb muscles (fingers, hands, arms, legs), but also in the tongue, are these areas relatively large. These seminal studies were followed by studies on the SMA, where muscle activation on the contralateral side of the body could be evoked through electrical stimulation, much like stimulation of M1 (Woolsey, 1952).

4.1. Crossed and uncrossed fibers

By now, pyramidal tracts are the best-studied efferent pathways of the cortical motor system (Davidoff, 1990; Nyberg‐Hansen and Rinvik, 1963; Woolsey et al., 1972). Most of these tracts are bilaterally symmetrical and the bulk of fibers cross over to the opposite side at the pyramidal decussation – figures vary between about 70%–90% that undergo this crossing but the majority of studies tend towards higher percentages though this depends on the end-effector under study. For example, primates’ hand and finger muscles seem to have more uncrossed fibers (Al Masri, 2011; Hong et al., 2010; Nathan et al., 1990)). The remaining fibers (∼10-30 %) do not cross before they reach the spinal cord (Carson, 2005). The presence of these non-crossing fibers underlies the appealing idea that the ipsilateral hemisphere is involved in movements not only at the contralateral side of the body, but also at the ipsilateral side as extensively outlined here. An example for a possible model including ipsilateral control, i.e. an alternative to the combination of interhemispheric excitation and intrahemispheric inhibition, is shown in Fig. 1, panel A. Interestingly, in a very recent paper Bundy and Leuthardt (2019) discussed the functional role of the ipsilateral hemisphere in motor control. They argued that the descending pathways primarily elicit movements and speculated about how the interaction through the CC may facilitate unimanual movements. And, they concluded that a balance between the excitatory and inhibitory function of interhemispheric interactions is mandatory for proper motor function. Our systematic review confirms these suggestions but also highlights that the story is not that simple. Our reading of the literature has identified three key findings that seem to underlie the hypothesized excitatory and inhibitory bilateral neural interactions, namely (a) the increase in task complexity of the unimanual task under investigation requires more efficient communication between hemispheres, (b) the anatomical properties of transcallosal fiber tracts enable this interhemispheric information exchange, and (c) the left (pre)motor areas play a key role when performing more complex motor tasks, irrespective of whether the left or right hand is being used.

In Fig. 1, we also depict another alternative, namely possible inhibitory cortico-cortical projections from S1 to M1 within a hemisphere (panel C). We added this model because of culminating evidence for synchronized or fine-tuned interactions between the periphery and S1 via feedback afferent pathways (see, e.g., Baker (2007) and references therein). Discussing this and other related animal studies in more detail is, however, beyond the scope of the current review.

4.2. Bilateral interaction

When executing a unimanual movement the human motor network shows consistent bilateral activation. This finding has been confirmed with all neuroimaging modalities reviewed here. It hence seems likely that inhibitory and faciliatory processes are needed to suppress the outflow of activity in the ipsilateral hemisphere to avoid bimanual motor (co-) activation.

TMS studies have revealed both an increase and a decrease in IHI. These conflicting IHI patterns might be explained by differences in experimental settings, especially the type of conditioning stimuli. The intensity of the stimuli could be adjusted to compensate for the increased MEP amplitude induced at the stimulus side because of the unimanual movements (Nelson et al., 2009; Sattler et al., 2012) and may hence yield a reduced IHI. By contrast, when conditioning stimuli are not adjusted to compensate for the stimulus-induced increase in MEP amplitude, IHI may increase (Hinder et al., 2010a, b; Liang et al., 2014; Uehara et al., 2014; Vercauteren et al., 2008). According to Brocke et al. (2008) these inhibitory processes are accompanied by measurable changes in the local neurovascular signal. As we summarized, unimanual movements are associated with BOLD activation in the contralateral and deactivation in the ipsilateral sensorimotor cortices. It has been suggested that this deactivation in the ipsilateral hemisphere could be caused by transcallosal inhibition involving GABAergic interneurons (Matsumura et al., 1992), an idea that might deserve future exploration.

BOLD changes of bilateral premotor areas seem strongly correlated with each other, as well as with the changes in M1 contralateral to the moving hand. This agrees with EEG and MEG assessments that revealed a decrease in both alpha and beta power, and an increase in coherence between bilateral premotor and sensorimotor cortices when performing unimanual movements. This bilateral coupling becomes more pronounced with increasing task complexity. There, symmetry appears broken in that left PM is especially active during both left- and right-hand complex movements. This is particularly interesting in view of the so-called ‘motor dominance theory’ that suggests that the left hemisphere is more capable than the right one to support motor activity; it hence might always be involved in motor execution, be that with the right or the left hand (Callaert et al., 2011; Ziemann and Hallett, 2001).

4.3. Task dependency

The direction and location of both inhibition and facilitation appears to depend on the motor task that is performed. Overall, an experimentally induced increase in task complexity, in particularly an increase in motor timing requirements, seems to be accompanied with more (efficient) communication between hemispheres. For unimanual movements we envision the following scenario when task complexity increases: Inhibition of the ipsilateral hemisphere likely increases, while inhibition of the contralateral hemisphere likely reverses into facilitation when the motor task becomes more challenging. Several research groups forwarded the idea that activation patterns of complex motor control operate at a ‘high level’ (Donoghue and Sanes, 1994; Gerloff et al., 1998a; Hummel et al., 2003; Manganotti et al., 1998; Sadato et al., 1996), but this level remains ill defined. Hummel et al. (2003) suggested that a task-complexity related increase in ipsilateral activation is not caused by motor memory load but by processing increasingly difficult transitions between movements. Interestingly, however, task-dependent activations, both excitatory and inhibitory, are not restricted to bilateral M1s, but are also present in other parts of the motor network, in particular in SMA and PM (Andres and Gerloff, 1999). The role of SMA in the preparation and performance of sequential movements has been demonstrated by, e.g., Gerloff et al. (1997), where stimulation with rTMS over SMA induced errors in motor performance in the more complex sequences. And, the role of left PM has been discussed above.

4.4. Outlook

4.4.1. Multimodal approaches

As highlighted in the Introduction, the CC is the main gateway for interhemispheric communication. A positive correlation was reported between the callosal thickness of the CC and the hand performance of the (right) dominant hand, but not of the (left) non-dominant hand (Kurth et al., 2013; Sehm et al., 2016). According to the aforementioned motor dominance theory one might speculate that this pattern of results will also be observed with left-handed participants. One could then assume that the left hemisphere is more involved in the support of motor activity and that the thickness of the CC is mainly related to the passage from left to right M1.

Stronger structural connectivity (higher FA) is associated with the reduction of unwanted mirror movements. Likewise, age-related atrophy implies weaker structural connectivity yielding stronger functional connectivity and poorer performance (Fling et al., 2012; Langan et al., 2010; Sullivan et al., 2010).

Earlier work investigated whether the CC exerts an inhibitory or excitatory role in the interhemispheric communication and concluded that there is evidence in the literature for both outcomes, although most studies support the excitatory function of the CC in interhemispheric communication (Bloom and Hynd, 2005; Carson, 2005; van der Knaap and van der Ham, 2011). As likewise hypothesized in the introduction, if transcallosal pathways are primarily excitatory and if the motor network shows (almost) symmetric, bilateral activation patterns while moving unimanually, then this indicates some type of intrahemispheric inhibition mediated through intrahemispheric pathways probably involving the premotor areas (Daffertshofer et al., 2005; Stinear and Byblow, 2002).

Combining the findings of multimodal approaches to study unimanual movements may help indeed to better understand how the brain enables the fine-tuned motor coordination that we are capable of. Still, several questions concerning the control of unilateral hand movements remain unanswered. Based on this review, we suggest that future research should investigate the role of the left hemisphere in greater detail, in particular the left PM. There is some evidence that this area plays a key role in the control of unimanual movements, but more research is needed, specifically with both left- and right-handed participants, to confirm this.

Only a few studies linked structural and functional connectivity in one experiment while performing unimanual movements (cf. Supplementary Material S2, Table 5). This is unfortunate because – as we outlined here – unimanual movements are likely to rely on the interhemispheric cross-talk through transcallosal tracts. We do suggest to intensify the research that combines different modalities as this may be key to unravel all the factors involved in unimanual motor control.

4.4.2. Integrating other populations

Our main aim was to specify the determinants and functional role of the often reported, bilateral activation patterns in the cortex during normal unimanual motor control in healthy humans. For this review we only included non-invasive studies, since invasive approaches may alter the normally functioning brain and, by this, the normal control of unimanual behavior. Yet, there is much to learn by combining our finding with the plenitude of studies in non-human primates, let alone studies on impaired motor control as observed in, e.g., stroke patients. For instance, Grefkes and Ward (2014) identified that lesions in M1 can lead to proportional changes in ventral PM activity. In fact, they argued that inactivation of either ipsi- or contralateral M1 or contralateral ventral PM deteriorates hand function recovery post stroke (there experimentally induced macaque monkeys). Interestingly, studies on partly hemiparetic stroke patients revealed unimanual movement of the affected (contralesional) side to display clearly bilateral neural activity. While this may indicate the ‘emergence’ of ipsilateral control to compensate motor impairment post stroke, one has to realize that motor learning of the non-affected side can limit the recovery of the affected one (Boddington and Reynolds, 2017; Dodd et al., 2017), which arguably speaks for a (dis-)balance of interhemispheric excitation versus intrahemispheric inhibition (Grefkes and Ward, 2014; Koch et al., 2016), as advocated here.

Biochemichemistry & behavioral decision-making in flies: When consensus of neurons in a network is reached, the network is pushed chemically, transforming deliberation into an all-or-nothing output

Biochemical computation underlying behavioral decision-making. Stephen C Thornquist, Maximilian J Pitsch, Charlotte S Auth, Michael A. Crickmore. bioRxiv Mar 15 2020. https://doi.org/10.1101/2020.03.14.992057

Abstract: Computations in the brain are broadly assumed to emerge from patterns of fast electrical activity. Challenging this view, we show that a male fly's decision to persist in mating, even through a potentially lethal threat, hinges on biochemical computations that enable processing over minutes to hours. Each neuron in a recurrent network measuring time into mating contains slightly different internal molecular estimates of elapsed time. Protein Kinase A (PKA) activity contrasts this internal measurement with input from the other neurons to represent evidence that the network's goal has been achieved. When consensus is reached, PKA pushes the network toward a large-scale and synchronized burst of calcium influx, which we call an eruption. The eruption functions like an action potential at the level of the network, transforming deliberation within the network into an all-or-nothing output, after which the male will no longer sacrifice his life to continue mating. We detail the continuous transformation between interwoven molecular and electrical information over long timescales in this system, showing how biochemical activity, invisible to most large scale recording techniques, is the key computational currency directing a life-or-death decision.

Predictions drive neural representations of visual events ahead of incoming sensory information

Predictions drive neural representations of visual events ahead of incoming sensory information. Tessel Blom, Daniel Feuerriegel, Philippa Johnson, Stefan Bode, and Hinze Hogendoorn. Proceedings of the National Academy of Sciences, March 16, 2020. https://doi.org/10.1073/pnas.1917777117

Significance: Visual information takes time to travel from the retina and through the visual system, such that the sensory information available to the brain lags behind events in the present moment. Prediction has long been considered a fundamental principle in neuroscience. Using time-resolved EEG decoding, we show that predictive mechanisms are sufficient to activate sensory-like neural representations of anticipated future events, and that these representations are activated before the arrival of afferent sensory information. This reveals that predictive neural mechanisms might allow the visual system to overcome its neural processing delays and interact with our environment in real time.

Abstract: The transmission of sensory information through the visual system takes time. As a result of these delays, the visual information available to the brain always lags behind the timing of events in the present moment. Compensating for these delays is crucial for functioning within dynamic environments, since interacting with a moving object (e.g., catching a ball) requires real-time localization of the object. One way the brain might achieve this is via prediction of anticipated events. Using time-resolved decoding of electroencephalographic (EEG) data, we demonstrate that the visual system represents the anticipated future position of a moving object, showing that predictive mechanisms activate the same neural representations as afferent sensory input. Importantly, this activation is evident before sensory input corresponding to the stimulus position is able to arrive. Finally, we demonstrate that, when predicted events do not eventuate, sensory information arrives too late to prevent the visual system from representing what was expected but never presented. Taken together, we demonstrate how the visual system can implement predictive mechanisms to preactivate sensory representations, and argue that this might allow it to compensate for its own temporal constraints, allowing us to interact with dynamic visual environments in real time.

Keywords: predictionneural delaystime-resolved decodingvisual system