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...........Read moreChildhood is becoming more and more digitized. Though still not clear, there may be developmental and health risks with excessive screen-based media use. These risks include language delay, impaired executive function, poor sleep, impaired general cognition, decreased parent-child engagement, and possibly neurobiological risks.
Childhood is becoming more and more digitized. Though still not clear, there may be developmental and health risks with excessive screen-based media use. These risks include language delay, impaired executive function, poor sleep, impaired general cognition, decreased parent-child engagement, and possibly neurobiological risks.
Diffusion tensor imaging (DTI) is a technology to quantify white matter integrity in the brain and its various factors. Parameters of DTI include fractional anisotropy (FA) and radial diffusivity (RD), scalar values associated with microstructural organization, and myelination of white matter tracts.
A cross-sectional study revealed the following results:
Increased use of screen-based media was associated with lower microstructual integrity of brain white matter tracts that support language, executive functions, and emergent literacy skills. Screen use was also associated with lower scores on corresponding behavioral measures.
Article summary with Autism as an adaptive common variant pathway for human brain development by Johnson - 2017
...........Read moreThere is a rapid and massive increase in the total brain volume during the first year. The elaboration of cortical gyrification continues. Some histogenetic processes rapidly increase in intensity (such as synaptogenesis and dendritic differentiation), while others follow a steady pace (such as cytoarchitectonig development, neurochemical maturation, and myelination). There is a decline in the growth of axonal pathways.
The cerebral hemispheres continue to grow. The most intense histogenetic and neurogenetic events during this period are morphological differentiation of neurons and dendrites, synaptogenesis, myelination, and changes in cortical cytoarchitectonics.
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...........Read morePoor self-regulation in childhood has been linked to various problems later in life. An integrated account in which longitudinal data on brain, behavior, and environment are all taken into consideration should help to understand causal relationships in terms of specific, well-defined mechanisms and develop interventions for when development goes wrong. An integrated account could help understand how effects of early problems can be prevented or minimized.
Self-regulation refers to the ability to monitor and modulate our emotions, behavior, and cognition to allow us to achieve our goals and adapt to changing circumstances. Self-regulation develops in interaction with the environment in complex ways that result in positive or negative developmental cascades. Low levels of self-regulation early on in life can impede self-regulation development later in life. Unlike some other factors that may cause adverse outcomes, self-regulation may be quite malleable and be a good target for intervention.
Effortful control refers to lower-level self-regulation. It involves the use of relatively simple executive functions, such as response inhibition or attention. It focuses on responding to the immediate situation. It can refer to both a trait and a type of process. Strategic control refers to the use of higher-order executive functions to achieve more sophisticated forms of self-regulation, such as planning. Different levels of self-regulation arise at different developmental periods.
Self-regulation develops in interaction with a maturing brain. The emergence of brain networks and the quality of their connections, among other developments, dictate the possibilities and limits for self-regulation abilities. In turn, self-regulation abilities, learning, and adapting to new experiences affect subsequent brain development. Brain development is not a linear process. Maturation occurs in distinct developmental periods which can be distinguished by the onset or end of specific neural processes. Neuroimaging measures may improve our understanding of how self-regulation develops.
Effortful control refers to the top-down control over bottom-up processes for purposes of self-regulation. The low-level executive functions that are fundamental to early life self-regulation begin to emerge in the first year of life. In early stages of development, self-regulation involves only effortful control and associated low-level executive functions. In later stages of development, age-appropriate self-regulation can involve different and more complex cognitive processes. The development of more complex self-regulation is parallel by the development of the orienting-attention network that enables children to orient to stimuli and to shift attention from one stimulus to another, and subsequently the executive attention network.
High-level executive functions build on the integration of the low-level executive functions that have developed in infancy. Brain development early in life can be characterized by volume expansion, neuron growth, and synapse formation. Then, during childhood, gray matter volume starts to shrink. Myelination of white matter nerve fibers and synaptic pruning combine to form brain networks that support the shift from low-level to high-level executive functions.
Strategic control requires goal-directed coordination of previously acquired low- and high-level executive functions. It is a level of self-regulation that emerges during adolescence due to the effective integration and coordination of executive functions. It co-occurs with the improvement of the quality of connections between cortical and subcortical regions, facilitated by the increase in myelination of white-matter tracts connecting these regions, allowing for faster and more precise neural signaling.
Adolescence is associated with behaviors such as increased risk taking, heightened sensitivity to social cues, and impulsivity. These indicators of reduced self-regulation capacity appear to be related to a developmental, transient imbalance between frontal lobe control and subcortical reward processing. There are regional differences in maturation speed across the brain, with the frontal cortex developing the slowest.
Poor self-regulation in childhood has been linked to various problems later in life. An integrated account in which longitudinal data on brain, behavior, and environment are all taken into consideration should help to understand causal relationships in terms of specific, well-defined mechanisms and develop interventions for when development goes wrong. An integrated account could help understand how effects of early problems can be prevented or minimized.
The CID combines a series of integrated large-scale, multi-modal, longitudinal studies and uses the same instrument in all cohorts, addresses a range of essential factors in the development of self-regulation, and allows for the analysis of the same concept measured in a comparable way. It researches different cohorts and taps into different environmental factors and brain and behavioral measures throughout childhood and adolescence, with repeated neuroimaging measurements.
In graph theoretical modeling, a network is composed of a certain number of nodes that are connected by weighted or un-weighted edges. A graph can be classified as a director or undirected type, depending on the existence or absence of directional information associated with the edges. In human brain development studies, the macro-scale network is often used. It is a model that can record the inter-regional connections in the whole brain in vivo through neuroimaging data. Network modes in this model are usually defined by brain partitions that are previously assigned, and the edges are determined by the structural or functional interactions between the separate brain regions.
In graph theoretical modeling, a network is composed of a certain number of nodes that are connected by weighted or un-weighted edges. A graph can be classified as a director or undirected type, depending on the existence or absence of directional information associated with the edges. In human brain development studies, the macro-scale network is often used. It is a model that can record the inter-regional connections in the whole brain in vivo through neuroimaging data. Network modes in this model are usually defined by brain partitions that are previously assigned, and the edges are determined by the structural or functional interactions between the separate brain regions.
Acquiring network nodes relies on neuroimaging. In EEG, fNIRS, and MEG studies, nodes are determined by using their derived cortical locations of electrodes, detectors, or sensors. In MRI studies, a parcellation scheme or atlas is needed to divide the brain into different regions of interest which are defined based on anatomical or functional information or on a random algorithm. Different parcellations capture different patterns of structural or functional pathways. The number of nodes significantly influences the absolute value of topological attributes.
Brain regions are structurally connected through a large number of fiber bundles that provide biological pathways for information transfer. Through dMRI-based tractography, these fiber tracts can be reconstructed and then used to define edges of the structural connectivity network. The number of reconstructed streamlines or averaged informative diffusion indexes of the connection can be used as the edge weight.
Before obtaining the brain network, a thresholding step is usually performed to define the edges to be used in the subsequent graph theoretical analysis, though some studies use the raw weighted network without thresholding. There are different ways of doing this:
The topology of a brain network can be characterized in terms of its global and nodal aspects. The global attributes measure the architecture of the whole network graph. The nodal attributes measure topological features of a single node.
The segregation of a network refers to the ability of local information processing that is responsible for specialized functions. The clustering coefficient and modularity are two attributes that provide a quantitative measurement of the segregation capacity of brain network.
The clustering coefficient of a node refers to the tendency to which the neighboring nodes of a node are interconnected. It reflects the density of local clusters. The clustering coefficient of a network refers to the average nodal clustering coefficients across all nodes in the network.
Network integration refers to the ability of parallel communication with distributed nodes which can be quantitatively measured by the characteristic path length or global efficiency. The characteristic path length of a network can be calculated by averaging the shortest path lengths between each pair of nodes in the network. A path represents a route of edges that connect one node with others. Its length is defined as the sum of the number or weights of the edges. The global efficiency of a network is the inverse of the average values of the shortest path length between any two nodes. A high degree of network integration is seen in a network that has high global efficiency and the low shortest path length has high global information transfer efficiency.
A small-world network possesses a shorter characteristic path length than a regular network and a higher clustering coefficient than a random network, to guarantee high capacity for local and global information transfer networks. It is an optimized topology that balanced between a regular and a random network. A regular network has a high clustering coefficient and long characteristic path length. A random network has a low clustering coefficient and a short characteristic path length.
Nodal degree is the most direct nodal metric, referring to the number of edges linking to a node. High degree nodes function as hubs in information transmission. The degree distribution of a network indicated the proportion of nodes that have a certain degree, which can be an indication of the resilience of the network. Rich-club organization refers to highly connected hubs, indicating that the hub nodes tend to be more densely interconnected with each other than by random chance would be expected.
The network edges can be classified into three types:
The prenatal structural network already shows broadly adult-like topological structures. The network is already highly efficient at local and global information transfers, possessing the specialized local communities for segregation and the high-cost backbones for integration. Increased normalized clustering coefficient, stable normalized shortest path length, and increasing small-worldness with development indicate that the shaping of the network seems to lean toward segregation enforcement during the prenatal stage. Short-range connections develop fast, hub regions expand into the inferior frontal cortex and insula regions and develop fast on their nodal connectivity and nodal betweenness centrality.
Structural segregation appears to be decreasing while structural integration is increasing, as can be seen by decreased modularity and characteristic path length and increased number of inter-module connectors and global efficiency. During early postnatal life there is dynamic regional reshaping in the structural network, as expressed by upgrades in network robustness and the left anterior cingulate gyrus and left superior occipital gyrus which become hubs. Neonatal functional brain networks maintain highly efficient small-world and modularity structure. The dorsal attention network and default mode network mature at one year of life, whereas the salience network and bilateral frontoparietal network are still developing at that time.
With regards to the structural network, the hypothesis is that the structural network is well-established at the time of birth, with many local connections within modules and several major distant connections between modules. With development, the network becomes more segregated with enhancement of local clusters during prenatal development. Then it becomes more integrated with increasing inter-module connections during postnatal development. With regards to the functional network, the hypothesis is that it is still immature and incomplete at birth. With development, the network shows enhanced segregation during prenatal development. Then the emergence and increase of long connections intensify the integrated ability of networks.
Preterm growth is the most common type of early atypical growth. It involves the sudden interruption of typical development processes as a result of complex genetic and environmental processes. The abnormal brain topology is characterized by disruptions in cortical-subcortical connectivity and short-distance cortico-cortical connections, as well as reduced edge strengths in widespread tracts, increased clustering coefficient, and increased nodal clustering coefficients located at the lateral parietal, ventral, and lateral frontal cortices. The changes in brain network caused by preterm birth continue into later life.
Attention deficit/hyperactivity disorder (ADHD) is one of the most common found disorders in children. Characterized by inattention and hyperactivity, ADHD is primarily an inherited disorder. Treatment usually involves methylphenidate (MPH), which works by regulating the dopamine system. This often results in a decrease in impulsivity, hyperactivity, and inattention. Despite this, children on MPH still experience deficits in cognitive faculties. Other studies have shown that children with ADHD perform differently depending on the length of a stimulus they are exposed to. If the stimulus is a short interstimulus interval (ISI), the children experience a more positive performance in comparison to a long ISI. A short ISI has been shown to improve memory recognition, vigilance, motor timing, and more. It is thought that both MPH and a short ISI act upon the dopamine levels in the brain. It is proposed that having both of these working at the same time may over-activate the system and lead to detrimental effects. The goal of this study was to measure the isolated and combined effect of MPH and ISI on mean response times and errors of commission.
For this study the sample consisted of 13 children (10 boys; 3 girls) diagnosed with ADHD. During the time of the study, MPH was gradually introduced for a two week period, either adjusting to a higher or lower dosage. After the children had been on MPH for 4 weeks, they were tested twice, once after the administration of MPH, and once after a placebo. The task which the participants engaged in was a computer based reaction time test known as Go/No-Go test. This involved pressing a button when the letter Q appeared onscreen and press nothing when the letter O appeared. If the participant responded to the letter O, this was recorded as an error of commission.
The results from the study indicate:
Children respond faster on MPH than not on MPH
Children respond faster in a condition with a short ISI rather than a long ISI
The interaction of ISI and MPH was not significant
Children on MPH made more errors of commission during the condition with a short ISI
Children on the placebo made fewer errors of commission during the condition with a short ISI
This study set out to ascertain whether children with ADHD were able to inhibit responses when they are in a state of over-activation. The findings of the study indicate that children perform better with either MPH or in the presence of a short ISI in comparison with a long ISI. When MPH and a short ISI are combined, they have detrimental effects. The stimulus shift hypothesis is supported by this outcome. This outcome calls into question the optimal dosage levels when treating ADHD.
Throughout past research, weak motivation has been shown to be a factor involved in ADHD. Two models exist to try and explain this deficit. The response inhibition model hypothesizes that the majority of problems related to ADHD can be explained by impaired response inhibition. The state regulation model, in contrast, associates ADHD with a motivation deficit which then results in negative outcomes for social functioning and cognition. In the more recent years, studies have investigated the effects of incentives, noise, and the rates of the presentation of stimuli.
Studies on the effect of incentives on response inhibition have produced mixed results. Some studies have shown that incentives increase response inhibition, others found the opposite. The authors suggest the following as possible reasons for these mixed results:
Variation in the presentation of the rewards
Effort allocation will only take place when arousal deviates from its basic state.
Incentives act as signals; an increase in signals means an increase in motor activation
In accordance with the state regulation model, noise could activate the arousal system. One study showed that white noise was beneficial for the cognitive performance of children with ADHD, but was detrimental to control groups. The explanation for this result is the under-arousal found in ADHD.
The state regulation model dictates that motor activation is effected by the presentation rate of a stimulus. Research has shown that children presented with a fast stimulus presentation rate perform better than when presented with a slow presentation rate. Very few studies have disputed this.
From the studies conducted on reaction time and stimuli presentation rate, we see an interaction between motor activation and its control by effort. The researchers question whether this is due to a bottom up deficit in motor activation which in turn is hard to control by the top down effort mechanism, or actually the motor activation mechanism is functional and it is the effort mechanism which is not sufficiently in control. A suggestion is presented to examine the possibilities: to investigate the combined and individual effects of stimuli presentation rates and incentives on reaction time performance.
The following are findings from research conducted:
Psychophysiological indices, under slow presentation rates of stimuli, support the hypothesis that ADHD is associated with an effort deficit
Response impairments have been associated with either too high or too low levels of dopamine.
Results of fMRI research show that ADHD participants use widespread frontostriatal activity, including the thalamus and the cingulate, when involved in accurate response inhibition
Cortical excitability in adults is optimized by self chosen stimulation
Effort allocation and boredom are negatively correlated
There is a growing accumulation of evidence supporting that cognitive performance of children with ADHD is associated with weak state regulation. The state regulation model is far from perfect. The plausibility of either a top-down or bottom-up deficit must be examined further.
In accordance with the state regulation deficit (SRD) model, individuals with ADHD have difficulty applying mental effort in situations which are suboptimal i.e. when there are either very fast or very slow event rates (ERs). In addition, ADHD has been shown to be associated with a deficit in suppression of the default mode network (DMN) and detriments to performance in tasks requiring effortful engagement. The authors of the study hypothesize that individuals with ADHD would show reduced deactivation in DMN when compared to controls in the tasks. They also predict a failure to modulate DMN activity as a part of ER by the ADHD participants.
The sample consisted of 20 adults with ADHD and a control sample of 20 age and gender matched adults. The task to be performed was a simple computer based response task. The task was kept simple to maximize the amount of trials which could be used for the characterization of DMN analysis. During the experiment, fMRI was used to monitor brain activity.
This study presents evidence for a disparity in the modulation of activity in specific DMN areas by event response in ADHD. Over-activity of DMN was observed only at ER extremes, no group differences were observed at a moderate level. This is in line with the SRD model. Further studies are necessary to test the hypothesis of whether or not individuals with ADHD have problems focusing effort on suppressing DMN interference when in less than ideal or energetically orientated conditions and also to investigate the role of effort allocation impairment on inattention and mind wandering.
Little is known about the underlying neural developmental defects which result in the emergence of autistic behavior during the early years of life. The frontal lobe has been identified as the most likely region to be involved, and yet little is known about it. The frontal lobe plays a key role in higher order language, cognitive, emotional, and social faculties, each one affected by autism. This has provided support for the frontal lobe hypothesis of autism. Through the collection of data from MRI and postmortem anatomical, and also already existing neurofunctional, postmortem, and MRI results from more mature autistic patients, the authors find two suggestions:
In patients with autism, the frontal cortex is poor at interacting with other cortical regions
During early development, the frontal cortex appears to be irregularly over-connected with itself
Brain growth of patients with autism is normal at birth, ranging from average to slightly smaller than average. However this is followed by a period of excessive growth which results in an enlarged brain volume at the toddler age. Investigations into which brain regions cause this growth indicate the frontal lobes to be at the site of peak growth. Grey and white matter in the frontal lobes are both disparately deviant in regards to other cortical regions. While several studies have shown that primary sensory cortices in autism function normally, the same cannot be said for the frontal lobes. The deficient functionality found in the frontal lobe is hypothesized as being a factor which disrupts the frontal lobes interaction with other areas of the brain. It is unknown whether autism is to be classified as disorder of overconnectivity, underconnectivity, or a combination of the two.
There remains a lack of knowledge on the microstructural abnormalities that disrupt frontal neural circuit development, facilitate the macroscopic overgrowth of frontal white and grey matter, and facilitate abnormal frontal mediated behavior. Where the link exists between abnormal neuroinflammatory response and initial brain overgrowth in autism is a mystery. It has been suggested that activated glia could be a reflection of a fetal state or development. When it comes to cerebral cortical information processing, a cortical minicolumn is an essential component. Studies have shown that minicolumns and their surrounding neuropil space are unusually small in children with autism throughout the frontal cortex, but not the occipital cortex. One older study found an increased neuron density and reduced neuron size within the frontal cingulate cortex in a number of autistic cases. It is suggested that these glial and neuronal abnormalities are in some way connected.
This is the first time that studies have shown early developmental abnormalities at the microscopic level and the macroscopic level and the presence of the frontal lobes as the peak of cerebral pathology. The work of abnormal processes (neuroinflammation, migration defects, excess cerebral neurogenesis) cause deformity, which leads to the malfunction of frontal minicolumn micro-circuitry. This in turn leads to reduced connectivity effectiveness between brain regions.
It has long been the goal of many researchers to investigate the number of impairments that underlie the symptoms which characterize Autism Spectrum Disorder (ASD). Through the use of the executive functioning criteria, studies on ASD have highlighted planning, cognitive flexibility, and working memory to be areas which are weak in individuals with the disorder. The area of response inhibition is what the authors chose to focus on. More specifically, the study aimed to use an immediate arousal task to examine inhibition of responses in children with high functioning autism (HFA), and to look for an association with impulsivity, hyperactivity, or inattention.
Participants for the study consisted of 39 children with HFA and a control group of 29 average functioning children. Once written permission was obtained from the parents, questionnaires were sent to the children to ascertain their suitability and possible comorbid disorders. The task consisted of a computer based reaction test. Participants were instructed in condition A to press a response button as quickly as they could upon the appearance of a white cross onscreen. In condition B they were instructed to wait for an acoustic signal before reacting as fast as they could to a white cross onscreen. The speed of the presentation rate was varied. An A-B-B-A style of sequencing of conditions was used.
The aim of the study was to examine whether or not there existed a response inhibition deficit in children with HFA. The presentation of an auditory signal and a visual stimulus produced an arousal effect which resulted in an increase in error rate and a decrease in reaction time. It was hypothesized that this effect would be strongest in children with HFA. Inhibition errors did increase with the addition of the auditory signal, however this was not unique to the HFA group. The results of this study suggest that children with HFA don’t have a deficit in the inhibition system. This result is in dispute of some studies.
Researchers are agreed that both social inadequacy and a deficit in executive functioning are both large factors which encompass autism. The main aim of this study focuses on investigating cognitive flexibility, more specifically response inhibition, set shifting, and motor presetting in regards to autism. Additionally a priori analysis was conducted by investigating the effects of the stimulus probability on performance. The authors mention the failure of previous studies in this area. Earlier studies failed to mention the patient’s medication status and thus failed to control for it. Additionally, these earlier studies often used experiment groups with varying age ranges. The authors generate four questions:
Is HPA associated with problems presetting the motor system in favor of the most common response type
Is HPA associated with weak set shifting
Is HPA associated with weak response inhibition
Is HPA associated with sensitivity for the given stimulus probability
The sample consisted of 23 adults with HFA, and a control group of 32 typically functional individuals. The task consisted of a computer based variant of the Sternberg reaction time paradigm. The task presented participants with a set of letters to be memorized and then another set was displayed. If the participant recognized an item from the memory set in the display set, they gave a ‘yes’ response, otherwise they gave a ‘no’ response. The baseline condition consisted of 50% of the trials requiring a ‘no’ response; the response bias condition consisted of 75% of trials requiring a ‘no’ response. Each condition consisted of 64 trials.
The aim of this study was to examine elements of cognitive flexibility, mainly set shifting, response inhibition, presetting, and a priori planning in individuals with HFA. Results show that participants with HFA experienced no deficit in response inhibition and the ability to change the response set. Despite this, there was a slow speed of performance found in participants with HFA, in particular those on medication. This slowness in speed may have been a contributing factor to cognitive flexibility deficit found in earlier studies which did not control for it. The study identifies a possible ceiling effect caused by an overall slowness of responses.
Cognitive control is an executive process which can be vital to the maintenance and monitoring of long term goal oriented behavior. In the past, the development of cognitive control has been explained as a growth from infancy to adulthood. The role of context on cognitive control impacts one’s behavioral regulation abilities, for example in a stressful context one may experience diminished control. Recent studies suggest that cognitive control capacity is impacted by specific periods of development whereby one is more susceptible to incentive based modulation.
When examining studies on cognitive control performed in a controlled laboratory settings, we see a relatively stable improvement in cognitive control capacity from infants progressing to adults. However, outside of the laboratory setting, this is often not the case. This is particularly true for adolescence, who experience a reduced capacity for cognitive control when exposure to potentially risky behavior is at its peak. These fluctuations in behavior give evidence of dynamic maturation of the brain mechanisms responsible for motivation and cognitive processes. Two areas of the brain are highlighted for their importance in cognitive and motivational processes: the prefrontal cortex (essential for cognitive control) and the striatum (important for identifying interesting cues in an environment).
Recently, research on the development of adolescences has focused on comparing cognitive capacity in neutral settings as opposed to motivational contexts. This research has implied that there exists a unique influence of motivation on cognition during the adolescent period, and that sensitivity to environmental cues (in particular incentive cues) changes at various points in development.
The behavior of adolescents has been shown to be differentially biased in motivational contexts. Studies have shown that motivational cues of potential reward are especially salient and potentially lead to the engagement in risky behavior and the further weakening of goal-orientated behavior.
This has led to the development of a neurobiological model of motivational and cognitive processes which aims to explain the behavior of adolescents outside of a laboratory context. Working with this model leads to the suggestion linear development of top down prefrontal regions relative to a n-shaped function for the development of bottom-up striatal regions involved in detecting particularly interesting cues in the environment.
The findings of Pasupathy and Miller indicate that the interactions between brain areas (especially within frontostriatal circuitry) is essential in the development of a model of motivational and cognitive control. Further studies have highlighted the important role of signaling inside corticostriatal circuitry for supporting the capacity to employ effective cognitive control. Further evidence for the theory that cognitive maturation occurs in the connectivity of structures rather than in unitary structures was found by examining the interactions between a frontoparietal network and cingulate-lateral prefrontal network. Works by Ernst, Galvan, Luna and Crone have been seminal in response to incentives, striatal responses follow an inverted U function across development. In contexts where a reward or incentive is present, the effect on cognitive control behavior is greater in adolescents than in adults.
Studies in cognitive and motivational processes are experiencing a bountiful period by focusing on adolescent development. Findings suggest that depending on whether a situation calls for suppression or attention to motivational cues, the cognitive control of adolescents can improve or diminish.
Adolescence is a period of development characterized by intense fluctuations in both physical and hormonal change. Research has been sparse in this area, empirical research on neural and cognitive development is still lacking. For such a period that reflects the growth of cognitive flexibility, self-consciousness and changes in identity, the need for further research is apparent.
Through studies on animals, we have seen that specific sensory regions of the brain go through sensitive periods starting after birth, in which environmental stimulation seems to be crucial fro the normal development of the brain and perceptual capabilities. Experiments suggest that while this is true for animals, it may also be true for humans. During the 1970’s and 1970’s, it was demonstrated that certain brain areas, especially the prefrontal cortex develop far beyond early childhood. Further studies in the decades that followed showed that during the period of puberty and adolescence, the structure of the prefrontal cortex goes through substantial changes. Two important changes highlighted are:
Synaptogenesis was first found in 1975 within experiments using cats and was further researched using rhesus monkeys. Synaptic pruning (a period of synaptic destruction) and synaptogenesis in the brain area the prefrontal cortex exist on a differential time line. Proliferation of synapses occurs in the prefrontal cortex during childhood and once again during puberty, however this is followed by a stagnant period and elimination and reorganization of prefrontal synaptic connections following puberty.
An overall decrease in synaptic density as a result of synaptic pruning in the frontal lobes ensues during adolescence. This process is thought to be essential for refining the effectiveness of neural networks. This is especially true when given the sensitive case of sound recognition development.
Through the implementation of modern technology, it has become possible to view the brain of living specimens. With the introduction of magnetic resonance imaging, we can non-invasively view the human brain in a detailed three-dimensional visual. This has been instrumental in the furthering of research on the maturation of the frontal cortex of adolescence and onwards into adulthood.
Over the past years, researchers have found one consistent outcome across MRI studies: during adolescence and childhood there is a steady increase in white matter located in certain brain regions. One study found a significant between the white and grey matter levels between two age groups. This increase in white matter has been suggested to be the result of developmental changes by some studies. One study found an increase in white matter in the right internal capsule and left arcuate fasciculus. Both regions are associated with speech so it was hypothesized that the increase in white matter was due to speech development.
Grey matter, in contrast to white matter, does not seem to follow a linear pattern. Rather it seems to follow a region specific, non-linear pattern. Research has shown that grey matter follows an inverted-U shape in certain brain regions. Studies suggest that grey matter volume in the frontal lobe reaches its peak during puberty, which is then followed by a stagnation period and a steady decline until though adolescence until early adulthood. MRI research on the decline of grey matter throughout adolescence has two explanations:
Research has shown that there exists a significant difference in the amount of grey and white matter found in males and females. This was particularly true in the area known as the inferior frontal gyrus (IFG). Researchers corrected for the possible confound of total cerebral volume but still they found that males had a significantly higher amount of grey matter. Some researchers believe this difference is a result of differential steroid levels, others believe it may be due to greater hemispheric specialization found in males. As of current research, more study is needed to examine variability in frontal cortex anatomy.
Recent research using MRI suggests that the period at which the brain reaches maturity could be later than the end of adolescence. This change is seen especially in the frontal and parietal cortices following post-mortem cellular examinations of human brains which support an extended period of development. The adolescent brain appears to develop in a dynamic nature when looking at the growth of white and grey matter.
Executive functioning refers to a set of cognitive mechanisms which govern how well we control and coordinate our behavior and cognition. Lesion studies have shown that many of the skills involved in executive functioning are dependent on the frontal lobes. Given that changes occur in the frontal cortex during adolescence, executive functioning might be expected to improve during this period. Behavioral studies have shown that inhibitory control, processing speed, working memory, and decision making continue to develop throughout adolescence.
Evidence suggests that the prefrontal cortex is associated with many high level cognitive functions, such as self-awareness and theory of the mind. In tandem with this neural development, puberty marks a great period of change for hormonal development. These two factors combined mark a significant change in social cognition. Research concerning the effects of puberty on social cognition capacitates has been limited.
The act of perspective taking refers to putting oneself in another’s shoes and it is an essential component for effective social communication. This act of estimating what another individual is thinking is related to the first-order theory of mind. It is an area of much theoretical debate. One view surmises that we understand others by simulating their actions and cognitions. In support of this, research has shown that similar brain areas are activated when we perform an action and when we see another perform the same action. This is in line with the function of mirror neurons.
With the introduction of fMRI, we have a safe and effective way to examine brain regions. As an example, through the use of fMRI we were able to examine how response inhibition has developed in addition to examining the structure supporting its development. During studies involving inhibition of a normal response, it was shown that activation of certain brain regions was for the most part the same across age groups. An exception was a significantly larger volume of activation in the prefrontal of children. In contrast to this, adults showed higher activation in the ventral region of the prefrontal cortex. One suggested reason for this is that children have a heftier dependence on this area than adults.
An issue which has been found when conducting fMRI is that of confounding effect of task performance. If there is a difference in the performance between two groups i.e. one outperforms the other, the results are often difficult to interpret.
In terms of brain regions, the amygdala is an area which has repeatedly been shown to have a high functioning role in facial recognition and emotional processing. Though research in this area has been investigated with adolescents, still little is known about the continued development of facial recognition. Studies have shown that children may identify neutral faces as being more ambiguous than fearful faces, resulting in an increase in activation in the amygdala.
puberty marks a period of synaptic reorganization, and as a result can be more susceptible to experiential input, in particular regarding social cognition and executive functioning. Further studies are needed to examine the further development of brain maturation beyond childhood and the implications this has on cognition. The authors specify questions into which skills undergo perturbation, sensitive periods for improvement and how does the environmental quality impact the changes which occur in the brain.
The term cerebral palsy is used to define a number of disorders which affect posture and movement. Cerebral palsy is attributed to damage or abnormal development in the developing brain of fetus’s or infants. Though there are many contributing factors to cerebral palsy, one of particular note are infarcts (tissue death as a result of lack of oxygen) which lead to lesions in white and grey matter tracts. These lesions to white matter tracts are detrimental to executive functioning which has been proven when testing youths with cerebral palsy against a control group without.
The question posed by this study is whether youths with mild spastic cerebral palsy are aware of their errors when carrying out tasks requiring executive functioning.
It has often been the findings of neurocognitive research that poor motor preparation precedes error making. Error detection and the adjustments which follow are measured in this case using response-locked error-related negativity. The brain potential for incorrect responses is markedly higher than those following correct responses.
Participants consisted of 11 patients, with a mean age of 14 years, diagnosed with mild cerebral palsy and a control group of 12 youths without cerebral palsy, with a mean age of 14, recruited from the same city. Though the intelligent quotient of some of the youths with mild cerebral palsy was within the range of learning disabilities, none were classified as being mentally retarded, as their daily lives were intact.
A computer based stimulus recognition task and electroencephalograms were used to record brain activity in the study. The task used was comparable to the Sternberg short-term memory paradigm. Participants were presented with 2 letters to be memorized, then were subsequently shown 4 letters, one or none of which were the letters which were memorized. Using two response buttons, participants would indicate either yes or no whether they identified there target letters in the new set. Reaction time was measured starting when the new set appeared until a button was pressed. Total time for the experiment was about 15 minutes.
The results of the experiment find that the control group made more correct responses and less error responses than the experiment group. In addition, the patient group reacted slower on average than the control group. Error responses were also shown to be slower than correct responses, which proved true for both groups.
Given the findings of the study, poor motor preparation appears to be associated with error responses. This is especially salient in the patient group. Error detection was found in both groups and went on to predict better performance. A key point given by the authors is that error monitoring and the adjustment in performance which follows are essential to learning. The research conducted here implies that this process is thankfully present in the patient group. Additionally, it is proposed that the patient group was more sensitive to their error making than the control group. This suggests that motivation may also be a key to learning in the patient group.
This leads to the suggestion that the patient group possesses an intact top-down capacity for executive functioning in tandem with a diminished motor action system. This calls for further investigation into the period preceding the execution of an action (i.e. pushing the button) to pinpoint the origin of error making in youths with mild cerebral palsy.
It must be noted that the study contained a rather small sample size and should be treated as preliminary research.
While the previous article focused on whether youths with mild cerebral palsy were aware of their own error making and what adjustments they made to avoid future error, the following article asks whether error making is preceded by attentional lapses, by poor motor preparation, or both.
As mentioned in the previous article, the term cerebral palsy is used to define a number of disorders which affect posture and movement. When addressing the subject of quality of life, how well one has a capacity for executive functioning is a relevant question. The term executive functions encompasses a wide range of cognitive faculties including attention control, inhibitory control, and cognitive control. Taken as a whole, executive functioning governs ones capacity to function effectively in life. Recent research indicates that reduced capabilities towards executive functioning has been found in youths with cerebral palsy. This hypothesis is limited, however, for two reasons. Firstly, poor effectiveness by patients with cerebral palsy on executive functioning tasks may be due to their diminished motor system as opposed to deficiencies in cognition. Secondly, weak cognitive skills on cognitive tasks are measured by high error count and slow reaction speed.
Given the previous research conducted by the authors on event-related potential, they propose that it is the poor motor preparation preceding a stimulus which is casually associated with error making in individuals with cerebral palsy. In accordance to this, the aim of this study was to measure what happens in the brain preceding errors in both the control and patient groups. To accomplish this, 3 event-related potential elements were recorded:
Participants consisted of 11 patients with cerebral palsy and an average age of 15, and 12 youths with an average age of 14 as a control group. The study design did not differ from that of the previous study. Again, the computer task was administered and responses were recorded as the interval between the new display set and the button press. However the authors were only interested in the 3 successive correct responses preceding an error.
Overall, the patient group had fewer sequences of 3 correct trial than the control group (patient group 41 sequences; control group 47). Both accuracy of responses and reaction speed were not found to be of a significant difference between the groups. It was found that contingent negative variation (motor preparation) was weakened for the patient group preceding an error. Attention (P300) levels preceding error making were shown to be low, however this was true for both groups. In the case of response evaluation (error preceding positivity), the groups did not show a difference in their level of performance monitoring preceding an error.
The results of the study show a strong indication that youths with mild cerebral palsy experience poor motor preparation not only preceding an error, but already one trial before the error occurs. Given that the control group and patient group did not differ on the amplitude of the parietal P300, the authors conclude that the cognitions responsible for response monitoring were similar in both groups. During the trials the patient group showed high levels of cognition control both preceding and following error making. Despite this however, they still made more errors than the control group. The authors propose that the poor motor preparation could be an indicator of a conflict between motor and cognitive exertion.
Ultimately, the goal of the study was to find out if error making in the patient group was associated with weak cognitive abilities. Given that the results indicate the source of error as a weakened motor system, they hypothesize that weak cognitive abilities can be dismissed as the source of error.
As with the previous study, the sample size was small. As such it should be taken as a preliminary study. Additionally, the generalizability is questionable, as it only deals with patients with mild cerebral palsy. Other measures of executive functioning would also be an improvement.
An inborn, inherited, error of metabolism, phenylketonuria (PKU) is a rare, highly treatable disease. In contrast to its relatively treatable nature, when left untreated, PKU can result in seizures, intellectual disability, and further medical issues. The most common method for prevention is the early introduction of a strict diet highlighting the restriction of phenylalanine (Phe). Despite its treatability, patients with PKU show an average 8-10 points lower than normal in addition to underperforming in neuropsychological tests.
Cognitive impairments have been associated with concurrent blood Phe levels, and even more so with lifetime blood Phe levels. The question being raised by the authors concerns whether or not the recommend Phe level for patients with PKU is too high. Currently, from the age of 0-10, this level varies between 240 and 360 micromolars/L. The drawback is that this range is not the result of studies comparing outcomes at Phe levels <240 micromolar/L, between 240 and 360 micromolar/L, and >360 micromolar/L.
Current treatment advises an absolute upper target level for Phe levels, not taking into account possible fluctuations of Phe values and the phenylalanine:tyrosine ratio (Phe:Tyr). This feeds into the second area of question the authors pose: what are the effects of lifetime Phe, concurrent Phe, variation in lifetime Phe levels, and lifetime and concurrent Phe:Tyr in predicting cognitive outcome in early and continuously treated children and adolescents with PKU
Participants consisted of 67 patients with PKU with a mean age of 10.8, and a control group of 73 participants with a mean age of 10.9 recruited from friends and families of patients and also local newspaper advertisements. Of the patients with PKU, 27 had pretreatment Phe levels of > 1200, 18 had pretreatment Phe levels between 600-1200, and 18 had pretreatment Phe levels <600, and 12 patients had pretreatment Phe levels <360. To test for concurrent Phe and Tyr levels, a blood sample was taken in the morning following an overnight fast. This was also used to test for lifetime Phe level. Through a series of computer based neuropsychological tests, executive functions inhibitory control and motor control were measured.
Patients with Phe levels >360 differed in 2 of 3 inhibition tasks, motor control, and cognitive flexibility. Controls performed notably more accurately than patients with Phe levels between 240-360. A key finding was that patients with Phe levels <240 performed no different to the control group. Additionally, patients with Phe levels <240 outperformed those with Phe levels between 240-360.
It was found that Phe variation, lifetime and concurrent Phe, and lifetime and concurrent Phe:Tyr were significantly related to speed and accuracy on numerous cognitive tests and also to each other.
The two major findings of this study are:
As mentioned in previous studies examined, phenylketonuria (PKU) is an inherited metabolic disorder. In the case of someone with the disease, there is a deficiency in the phenylalanine hydroxylase enzyme and as a result, phenylalanine (Phe) cannot be converted into tyrosine (Tyr). This excess of Phe, in combination with a lack of Tyr can lead to shortages of important neurotransmitters such as serotonin and dopamine. Serotonin is linked to cognitive functioning and a lack of it can result in decreased cognitive functioning. Dopamine is associated with the executive functioning primarily in the prefrontal cortex. There is a considerate lack of studies concerning behavioral problems and social skills for those with PKU. The aim of the study presented here is to explain a new Dutch multicenter study, namely the PKU-COBESO study. The primary goal of the PKU-COBESO study is to examine the behavioral problems, social functioning, cognitive functioning, and executive functioning in both continuous and early treatment patients principally in regards to their metabolic control.
The experiment sample for the study consisted of young adult patients with PKU who had beforehand participated in a neuropsychological study 10-15 years previous, and another group of patients who did not participate in the previous neuropsychological study. In the control group, participants were recruited from either the families and friends of the patients, or from non-family participants.
The study itself consisted of a neuropsychological assessment, questionnaires, and an analysis of the PKU patients’ metabolic control. The neurological assessment comprised of a combination of either the WISCIII or WAISCIII (depending on the participants age) and the ANT (Amsterdam Neuropsychological Tasks), and numerous paper and pencil tasks. The aim of the neuropsychological component was to measure:
Executive functions
Social cognitive skills
Motor control
The questionnaires aimed to ascertain:
General demographic information
Executive functioning throughout daily life
Social functioning
Mental health/behavioral problems
Blood samples were taken from the PKU patients in order to determine concurrent Phe and Tyr levels, and the levels of other metabolic features.
In the preliminary analysis, results showed that adult PKU patients differed on ‘internalizing problems’, reported more ‘avoidant personality problems’, scored worse on ‘relationships’ and also ‘self care’. Additionally, the concurrent Phe levels of adults with PKU were not significantly related to social skills and behavioral problems. Childhood Phe levels were shown to be significantly related to ‘thinking problems’ and ‘somatic problems’.
The PKU-COBESO study has two main questions it seeks to answer:
How does leniency of diet in early stages of PKU go on to influence cognitive and behavioral functioning, and the potential for an adult to thrive in life.
To what extent do Phe influenced cognitive problems manifest in the daily living of PKU patients.
The results of the study should be considered preliminary. Having said that, the results are complimentary to the expected findings and provide evidence for the importance of further study focusing on the mental health and social functioning in early treated PKU.
The origins, effects, and treatment of PKU have been discussed previously. The following article focuses on the effects PKU has on executive functioning specifically. To ascertain these effects the implementation of the Behavior Rating Inventory of Executive Functioning (BRIEF) is proposed. This is an easily applied standardized questionnaire which can also be employed by non-psychologists. However, the accuracy of the BRIEF has been called in to question. To address this, the authors also use the Amsterdam Neuropsychological Tasks (ANT) measure, which has been used several times in the past to ascertain the neurocognitive functioning of PKU patients of various ages and early and continued treatment. Using the two tests, the authors attempt to investigate whether the BRIEF-A (adult version) is a useful instrument in the screening of patients with PKU during their daily living.
The sample for this study consisted of 55 Dutch adult patients with PKU. Additionally, this study was a part of the PKU-COBESO mentioned in the previous article. The BRIEF-A test consisted of 75 questions 9 subdomains related to executive functioning, 4 subdomains which determine the Behavioral Regulation Index (BRI). The overall executive functioning in daily life score is denoted as the Global Executive Composite (GEC).
For the ANT, three tests were used to measure executive functioning: Shifting Attentional Set Visual (SSV), Sustained Attention Dots (SAD), and Feature Identification (FI).
Of the 55 patients, 23 scored within the borderline/clinical range of the BRIEF-A. Patients showed problems in the domains of cognitive flexibility and inhibitory control when compared to the healthy population. Subsequently, two groups were formed on the basis of BRIEF-A GEC scores using a cutoff T-score of >= 60 (>1 SD above the mean). No significant differences were found between the groups on the basis of gender, age, and IQ. Additionally, no significant differences were found between the two groups on concurrent and historical Phe concentration levels. There was found to be some agreement between the BRIEF and the ANT indicating that the null hypothesis could not be rejected.
The fact that patients with PKU still face problems in attention and learning was the driving factor for this investigation into the efficacy of the BRIEF as a tool for monitoring patients. The results show that 42% of patients scored in the borderline/clinical range. Despite this, only 11% of patients showed scores greater than 1 SD. From the results of the ANT, we see that PKU patients had problems with inhibitory control and cognitive flexibility. The BRIEF-A appears to identify executive dysfunction across studies.
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