Fluid intelligence and the locus coeruleus-norepinephrine system

Tsukahara and Engle suggest that the cognitive mechanisms of fluid intelligence map onto the locus coeruleus–norepinephrine system. I pass on their introductory paragraph (the link takes you to their abstract, which I think is less informative):

In this article, we outline what we see as a potentially important relationship for understanding the biological basis of intelligence: that is, the relationship between fluid intelligence and the locus coeruleus–norepinephrine system. This is largely motivated by our findings that baseline pupil size is related to fluid intelligence; the larger the pupils, the higher the fluid intelligence. The connection to the locus coeruleus is based on research showing that the size of the pupil can be used as an indicator of locus coeruleus activity. A large body of research on the locus coeruleus–norepinephrine system in animal and human studies has shown how this system is critical for an impressively wide range of behaviors and cognitive processes, from regulating sleep/wake cycles, to sensation and perception, attention, learning and memory, decision making, and more. The locus coeruleus–norepinephrine system achieves this primarily through its widespread projection system throughout the cortex, strong connections with the prefrontal cortex, and the effect of norepinephrine at many levels of brain function. Given the broad role of this system in behavior, cognition, and brain function, we propose that the locus coeruleus–norepinephrine system is essential for understanding the biological basis of intelligence.

What are our brains doing when they are (supposedly) doing nothing?

Pezullo et al. address the question of this post's title in an article in Trends in Cognitive Sciences: "The secret life of predictive brains: what's spontaneous activity for?" (motivated readers can obtain a PDF of the article by emailing me). They suggest an explanation for why brains are constantly active, displaying sophisticated dynamical patterns of spontaneous activity, even when not engaging in tasks or receiving external sensory stimuli. I pass on the article highlights and summary: 

Spontaneous brain dynamics are manifestations of top-down dynamics of generative models detached from action–perception cycles. 

Generative models constantly produce top-down dynamics, but we call them expectations and attention during task engagement and spontaneous activity at rest. 

Spontaneous brain dynamics during resting periods optimize generative models for future interactions by maximizing the entropy of explanations in the absence of specific data and reducing model complexity. 

Low-frequency brain fluctuations during spontaneous activity reflect transitions between generic priors consisting of low-dimensional representations and connectivity patterns of the most frequent behavioral states. 

High-frequency fluctuations during spontaneous activity in the hippocampus and other regions may support generative replay and model learning.

Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between ‘generic priors’ of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.

A test of plasticity-based cognitive training in treating mild traumatic brain injury

A study from Mahncke et al. (open source) shows that using a computerized cognitive training program that I have mentioned in previous MindBlog posts (BrainHQ, Posit Science) improves cognitive function in people with mild traumatic brain injury. Here is their abstract:

Clinical practice guidelines support cognitive rehabilitation for people with a history of mild traumatic brain injury (mTBI) and cognitive impairment, but no class I randomized clinical trials have evaluated the efficacy of self-administered computerized cognitive training. The goal of this study was to evaluate the efficacy of a self-administered computerized plasticity-based cognitive training programmes in primarily military/veteran participants with a history of mTBI and cognitive impairment. A multisite randomized double-blind clinical trial of a behavioural intervention with an active control was conducted from September 2013 to February 2017 including assessments at baseline, post-training, and after a 3-month follow-up period. Participants self-administered cognitive training (experimental and active control) programmes at home, remotely supervised by a healthcare coach, with an intended training schedule of 5 days per week, 1 h per day, for 13 weeks. Participants (149 contacted, 83 intent-to-treat) were confirmed to have a history of mTBI (mean of 7.2 years post-injury) through medical history/clinician interview and persistent cognitive impairment through neuropsychological testing and/or quantitative participant reported measure. The experimental intervention was a brain plasticity-based computerized cognitive training programme targeting speed/accuracy of information processing, and the active control was composed of computer games. The primary cognitive function measure was a composite of nine standardized neuropsychological assessments, and the primary directly observed functional measure a timed instrumental activities of daily living assessment. Secondary outcome measures included participant-reported assessments of cognitive and mental health. The treatment group showed an improvement in the composite cognitive measure significantly larger than that of the active control group at both the post-training [+6.9 points, confidence interval (CI) +1.0 to +12.7, P = 0.025, d = 0.555] and the follow-up visit (+7.4 points, CI +0.6 to +14.3, P = 0.039, d = 0.591). Both large and small cognitive function improvements were seen twice as frequently in the treatment group than in the active control group. No significant between-group effects were seen on other measures, including the directly-observed functional and symptom measures. Statistically equivalent improvements in both groups were seen in depressive and cognitive symptoms.

How our brain cortex changes in the transition from childhood to adolescence.

This open source article from Dong et al. has some excellent summary graphics:  

Significance

Here, we describe age-dependent shifts in the macroscale organization of cortex in childhood and adolescence. The characterization of functional connectivity patterns in children revealed an overarching organizational framework anchored within the unimodal cortex, between somatosensory/motor and visual regions. Conversely, in adolescents, we observed a transition into an adult-like gradient, situating the default network at the opposite end of a spectrum from primary somatosensory/motor regions. This spatial framework emerged gradually with age, reaching a sharp inflection point at the transition from childhood to adolescence. These data reveal a developmental change from a functional motif first dominated by the distinction between sensory and motor systems and then balanced through interactions with later-maturing aspects of association cortex that support more abstract cognitive functions.

Abstract

The transition from childhood to adolescence is marked by pronounced shifts in brain structure and function that coincide with the development of physical, cognitive, and social abilities. Prior work in adult populations has characterized the topographical organization of the cortex, revealing macroscale functional gradients that extend from unimodal (somatosensory/motor and visual) regions through the cortical association areas that underpin complex cognition in humans. However, the presence of these core functional gradients across development as well as their maturational course have yet to be established. Here, leveraging 378 resting-state functional MRI scans from 190 healthy individuals aged 6 to 17 y old, we demonstrate that the transition from childhood to adolescence is reflected in the gradual maturation of gradient patterns across the cortical sheet. In children, the overarching organizational gradient is anchored within the unimodal cortex, between somatosensory/motor and visual territories. Conversely, in adolescence, the principal gradient of connectivity transitions into an adult-like spatial framework, with the default network at the opposite end of a spectrum from primary sensory and motor regions. The observed gradient transitions are gradually refined with age, reaching a sharp inflection point in 13 and 14 y olds. Functional maturation was nonuniformly distributed across cortical networks. Unimodal networks reached their mature positions early in development, while association regions, in particular the medial prefrontal cortex, reached a later peak during adolescence. These data reveal age-dependent changes in the macroscale organization of the cortex and suggest the scheduled maturation of functional gradient patterns may be critically important for understanding how cognitive and behavioral capabilities are refined across development.

Graphic depictions of an integrative model of mind

To hopefully enhance the chance that you will pay attention to the creative and seminal thinking in the open source Laukkonen and Slagter review article whose abstract I passed on in my July 21 post,  I now pass on their striking concluding statement and then  two graphics whose legends summarize the main ideas presented. I think this work offers a plausible and appealing integration of neuroscience and meditative traditions.  

We have taken on the daunting task of providing a theory for understanding the effects of meditation within the predictive processing framework. Contemplative science is a young field and predictive processing is a new theory, although both have roots going much farther back. All theories are subject to change, but perhaps particularly so for such new domains of enquiry. Nevertheless, we think the conditions are suitable for a more overarching theory that may also thwart further siloing and fragmentation of scientific research, as has been commonplace among the mind-sciences. A strength of our framework is its simplicity: Being in the here and now reduces predictive processing. And yet, this basic idea can explain how each meditation technique uniquely deconstructs the minds tendency to project the past onto the present, how certain insights may arise, the nature of hierarchical self-processing, and the plasticity of the human mind. There is scope here, we think, to eventually reveal what makes a meditator an expert, why meditation has such broad clinical effects, and how we might begin mitigating some of the negative consequences of meditation. Last but not least, our framework seems to bring ancient Eastern and modern scientific ideas closer together, showing how the notion of conditioned experience in Buddhism aligns with the notion of the experience-dependent predictive brain.

Fig. 1. Here we use the Pythagoras Tree to provide an intuitive illustration of how organisms represent the world with increasing counterfactual depth or abstraction. The tree is constructed using squares that are scaled down by the square root of 2 divided by 2 and placed such that the corners of the squares meet and form a triangle between them, recursively. Analogously, the brain constructs experience from temporally precise and unimodal models of present-moment sensory representations and input (e.g., pixels on a screen), into ever more abstract, transmodal, and temporally deep models (e.g., a theory paper). Meditation brings one increasingly into the present moment, thus reducing the tendency to conceptualize away from the here and now, akin to observing the pixels rather than the words. This reduction of conceptualization ought to also have profound effects on the sense of self, which also relies on abstract model building, and ultimately is said to reveal an underlying seemingly “unconditioned” state of consciousness as such (like the white background underlying the pixels).

 

Fig. 2. In this schematic we illustrate two aspects of the many-to-(n)one model. The first and most foundational proposal is that meditation gradually flattens the predictive hierarchy or ‘prunes the counterfactual tree’, by bringing the meditator into the here and now, illustrated in the left figure. Thus, meditative depth is defined by the extent that the organism is not constructing temporally thick predictions. In the right figure, we dissect the predictive hierarchy into three broad levels. We propose that thinking (and therefore the narrative self [NS]) sits at the top of the predictive hierarchy (Carhart-Harris and Friston, 2010, 2019). Sensing and perceiving and therefore the embodied experiencing self [ES] sits below it (Gallagher, 2000; Seth, 2013). Finally, a basal form of self-hood characterized by the subject-object [S/O] duality sits at the earliest level. FA brings the practitioner out of the narrative self and into a more experiencing and embodied mode of being. Then, through dereification from present moment experience (including bodily sensations) OM brings the practitioner more into a state where contents of experience are treated equally, and one is able to experience non-judgmentally (sensing without appraisal), but even in very advanced states, a subject-object duality remains. During OM, certain epistemic discoveries or insights about the nature and behavior of generative models may occur. Finally, through ND practices the subject-object distinction may fall away and the background or “groundless ground” of all experience—awareness itself—can be uncovered. Another way to characterize this process is as follows: FA employs regular (conditional) attention to an object of sensing, OM employs bare (unconditional) attention, and ND practice employs reflexive awareness that permits the non-dual witnessing of the subject-object dichotomy and finally pure or non-dual awareness by releasing attention altogether.

 

 

From many to (n)one: Meditation and the plasticity of the predictive mind

I had a chat with my former University of Wisconsin colleague Richard Davidson during my visit to Madison, WI last week, and he pointed me to an excellent open source review article by Laukkonen and Slagter, From many to (n)one: Meditation and the plasticity of the predictive mind. They offer an integrated predictive processing account of three main styles of meditation. I just finished reading through their lucid account and plan to carefully re-read it several times. I pass on the summary points and abstract: 

Highlights

• Predictive processing provides a novel theoretical window on meditation. 

• Deconstructive meditations progressively reduce temporally deep processing. 

• Insight experiences arise during meditation due to Bayesian model reduction 

• Meditation deconstructs self models by reducing abstract processing. 

• Non-dual awareness or pure consciousness is the ‘here and now’.

Abstract

How profoundly can humans change their own minds? In this paper we offer a unifying account of deconstructive meditation under the predictive processing view. We start from simple axioms. First, the brain makes predictions based on past experience, both phylogenetic and ontogenetic. Second, deconstructive meditation brings one closer to the here and now by disengaging anticipatory processes. We propose that practicing meditation therefore gradually reduces counterfactual temporally deep cognition, until all conceptual processing falls away, unveiling a state of pure awareness. Our account also places three main styles of meditation (focused attention, open monitoring, and non-dual) on a single continuum, where each technique relinquishes increasingly engrained habits of prediction, including the predicted self. This deconstruction can also permit certain insights by making the above processes available to introspection. Our framework is consistent with the state of empirical and (neuro)phenomenological evidence and illuminates the top-down plasticity of the predictive mind. Experimental rigor, neurophenomenology, and no-report paradigms are needed to further understanding of how meditation affects predictive processing and the self.

Psilocybin induces rapid and persistent growth of dendritic spines in frontal cortex in vivo

Interesting results from Shao et al.: 

 Highlights

• Psilocybin ameliorates stress-related behavioral deficit in mice 

• Psilocybin increases spine density and spine size in frontal cortical pyramidal cells 

• Psilocybin-evoked structural remodeling is persistent for at least 1 month 

• The dendritic rewiring is accompanied by elevated excitatory neurotransmission

Summary

Psilocybin is a serotonergic psychedelic with untapped therapeutic potential. There are hints that the use of psychedelics can produce neural adaptations, although the extent and timescale of the impact in a mammalian brain are unknown. In this study, we used chronic two-photon microscopy to image longitudinally the apical dendritic spines of layer 5 pyramidal neurons in the mouse medial frontal cortex. We found that a single dose of psilocybin led to ∼10% increases in spine size and density, driven by an elevated spine formation rate. The structural remodeling occurred quickly within 24 h and was persistent 1 month later. Psilocybin also ameliorated stress-related behavioral deficit and elevated excitatory neurotransmission. Overall, the results demonstrate that psilocybin-evoked synaptic rewiring in the cortex is fast and enduring, potentially providing a structural trace for long-term integration of experiences and lasting beneficial actions.

Graphical Abstract:

Seven nuggets on how we confuse ourselves about our brains and our world.

In a series of posts starting on Nov. 27, 2020 I attempted to abstract and condense the ideas in Lisa Feldman Barrett’s 2017 book “How Emotions Are Made: The Secret Life of the Brain”. That book is a hard slog, as was my series of posts on its contents. Barrett also did her own condensation in her followup book, “Seven and a Half Lessons About the Brain,” that appeared in late 2020 at the same time as my posts, and I’ve finally gotten around to scanning through it. I want to pass on her brief epilogue that extracts a few crisp nuggets from her lessons:

ONCE UPON A TIME, you were a little stomach on a stick, floating in the sea. Little by little, you evolved. You grew sensory systems and learned that you were part of a bigger world. You grew bodily systems to navigate that world efficiently. And you grew a brain that ran a budget for your body. You learned to live in groups with all the other little brains-in-bodies. You crawled out of the water and onto land. And across the expanse of evolutionary time - with the innovation that comes from trial and error and the deaths of trillions of animals - you ended up with a human brain. A brain that can do so many impressive things but at the same time severely misunderstands itself.

-A brain that constructs such rich mental experiences that we feel like emotion and reason wrestle inside us 

-A brain that’s so complex that we describe it by metaphors and mistake them for knowledge 

-A brain that’s so skilled at rewiring itself that we think we’re born with all sorts of things that we actually learn 

-A brain that’s so effective at hallucinating that we believe we see the world objectively, and so fast at predicting that we mistake our movements for reactions 

-A brain that regulates other brains so invisibly that we presume we’re independent of each other 

-A brain that creates so many kinds of minds that we assume there’s a single human nature to explain them all 

-A brain that’s so good at believing its own inventions that we mistake social reality for the natural world

We know much about the brain today, but there are still so many more lessons to learn. For now, at least, we’ve learned enough to sketch our brain’s fantastical evolutionary journey and consider the implications for some of the most central and challenging aspects of our lives.

Our kind of brain isn’t the biggest in the animal kingdom, and it’s not the best in any objective sense. But it’s ours. It’s the source of our strengths and our foibles. It gives us our capacity to build civilizations and our capacity to tear down each other. It makes us simply, imperfectly, gloriously human.

In our brains everything changes

Sometimes learning the hard neuroscience of how our brains work leaves me feeling a bit queasy. The first time this happened was when I learned about the Libet experiments that showed that cells in our motor cortex start a movement well before we ‘decide’ to initiate it. “We” think we are initiating a movement when in fact “it” (those brain cells) are already well on their way to doing it. So what happened to my ‘free will’? Well...there is a work around for that problem that I explain in my “I Illusion” and subsequent web lectures. 

 A further uncomfortable jolt comes on seeing evidence the brain cells that become active during a familiar experience can change over time. Each instance of the recall of an important event can recruit a different group of nerve cells, because each time the memory is fetched from the neuronal ‘library’ it gets put back, sometimes slightly altered, in different nerve cell collections and connections. A very striking example of this has been provided by Schoonover et al. Who show that the network of nerve cells active when a particular smell triggers a specific behavior changes over time, moving to different brain areas. This is an example of ‘representational plasticity’ which is discussed in a review article by Rule et al. 

This conflicts with our common sense view of how our minds should work. If you have an experience and then later remember it, you must have put it somewhere in your brain’s library of nerve cell connections, like a book on a library shelf, so that all you have to do to remember something is go fetch it. If the experience is an emotional one it couples with a hard wired circuit for that emotion. This essentialist view of how our minds work is being thoroughly displaced as experimental evidence continues to accumulate showing that in each moment we are constructing our experience anew - reminding of the Buddhist saying that the river you view flowing past is never the same twice. The series of MindBlog posts (starting here) on the work and ideas of Barrett covers this material. 

It is from constant change and flux in our evolved neuroendocrine circuitry that we generate the illusion of certainty or constancy - expectations of selves, rules, objects, and emotions that stay in place. We model the world we expect to see before each moment we are about to enter. If our expectations are not met, then our brains perk up to adjust them appropriately.  

 

Lack of mathematical education impacts brain development and future attainment

From Zacharopoulos et al.:  

 Significance

Our knowledge of the effect of a specific lack of education on the brain and cognitive development is currently poor but is highly relevant given differences between countries in their educational curricula and the differences in opportunities to access education. We show that within the same society, adolescent students who specifically lack mathematical education exhibited reduced brain inhibition levels in a key brain area involved in reasoning and cognitive learning. Importantly, these brain inhibition levels predicted mathematical attainment ∼19 mo later, suggesting they play a role in neuroplasticity. Our study provides biological understanding of the impact of the lack of mathematical education on the developing brain and the mutual play between biology and education.

Abstract

Formal education has a long-term impact on an individual’s life. However, our knowledge of the effect of a specific lack of education, such as in mathematics, is currently poor but is highly relevant given the extant differences between countries in their educational curricula and the differences in opportunities to access education. Here we examined whether neurotransmitter concentrations in the adolescent brain could classify whether a student is lacking mathematical education. Decreased γ-aminobutyric acid (GABA) concentration within the middle frontal gyrus (MFG) successfully classified whether an adolescent studies math and was negatively associated with frontoparietal connectivity. In a second experiment, we uncovered that our findings were not due to preexisting differences before a mathematical education ceased. Furthermore, we showed that MFG GABA not only classifies whether an adolescent is studying math or not, but it also predicts the changes in mathematical reasoning ∼19 mo later. The present results extend previous work in animals that has emphasized the role of GABA neurotransmission in synaptic and network plasticity and highlight the effect of a specific lack of education on MFG GABA concentration and learning-dependent plasticity. Our findings reveal the reciprocal effect between brain development and education and demonstrate the negative consequences of a specific lack of education during adolescence on brain plasticity and cognitive functions.

How LSD tweaks our brain synapses to promote social behavior.

For the subset of MindBlog readers that is into the detailed Neuroscience of our behavior, I pass on an interesting article by De Gregorio et al. who use a mouse model to probe LSD's reported enhancement of empathy and social behavior in humans. Here is their significance statement, which is quite technical. If that's not enough for you, click on the link.

Social behavior (SB) is a fundamental hallmark of human interaction. Repeated administration of low doses of the 5-HT2A agonist lysergic acid diethylamide (LSD) in mice enhances SB by potentiating 5-HT2A and AMPA receptor neurotransmission in the mPFC via an increasing phosphorylation of the mTORC1, a protein involved in the modulation of SB. Moreover, the inactivation of mPFC glutamate neurotransmission impairs SB and nullifies the prosocial effects of LSD. Finally, LSD requires the integrity of mTORC1 in excitatory glutamatergic, but not in inhibitory neurons, to produce prosocial effects. This study unveils a mechanism contributing to the role of 5-HT2A agonism in the modulation of SB.

Environmental noise degrades learning and memory

Sobering observations from Zhang et al on our hippocampus-related learning and memory:

Significance

The noise pollution accompanying industrialization is a risk factor to human health. Here, we show in a rodent model that even moderate-level noise at ∼65 dB SPL that has little effect on stress status can substantially impair hippocampus-related learning and memory by altering the plasticity of synaptic transmission. It is possible that because moderately loud noise does not affect peripheral hearing per se, the negative impacts of chronic exposure to such noise are currently not well characterized. Our results indicate the importance of more thoroughly defining these possibly hitherto unappreciated hazards of noise pollution in modern human environments.

Abstract

The neural mechanisms underlying the impacts of noise on nonauditory function, particularly learning and memory, remain largely unknown. Here, we demonstrate that rats exposed postnatally (between postnatal days 9 and 56) to structured noise delivered at a sound pressure level of ∼65 dB displayed significantly degraded hippocampus-related learning and memory abilities. Noise exposure also suppressed the induction of hippocampal long-term potentiation (LTP). In parallel, the total or phosphorylated levels of certain LTP-related key signaling molecules in the synapses of the hippocampus were down-regulated. However, no significant changes in stress-related processes were found for the noise-exposed rats. These results in a rodent model indicate that even moderate-level noise with little effect on stress status can substantially impair hippocampus-related learning and memory by altering the plasticity of synaptic transmission. They support the importance of more thoroughly defining the unappreciated hazards of moderately loud noise in modern human environments.

Tipsy microglia binge on synapses - another reason to cut down on the booze

Socodato et al. find that binge-level alcohol intake (about five drinks for an average person) over 10 consecutive days enhances Src-to–tumor necrosis factor (TNF) signaling in prefrontal cortex microglia, which boosts their engulfment capacity and leads to aberrant synaptic pruning, culminating in synapse loss and anxiety-like behavior. Overall, their data suggest that aberrant synaptic pruning by microglia might play an important role in the synaptic transmission deficits elicited by alcohol abuse. Their abstract:

Alcohol abuse adversely affects the lives of millions of people worldwide. Deficits in synaptic transmission and in microglial function are commonly found in human alcohol abusers and in animal models of alcohol intoxication. Here, we found that a protocol simulating chronic binge drinking in male mice resulted in aberrant synaptic pruning and substantial loss of excitatory synapses in the prefrontal cortex, which resulted in increased anxiety-like behavior. Mechanistically, alcohol intake increased the engulfment capacity of microglia in a manner dependent on the kinase Src, the subsequent activation of the transcription factor NF-κB, and the consequent production of the proinflammatory cytokine TNF. Pharmacological blockade of Src activation or of TNF production in microglia, genetic ablation of Tnf, or conditional ablation of microglia attenuated aberrant synaptic pruning, thereby preventing the neuronal and behavioral effects of the alcohol. Our data suggest that aberrant pruning of excitatory synapses by microglia may disrupt synaptic transmission in response to alcohol abuse.

Getting the rhythm to suppress Alzheimer's

An interesting brief open source review by Lynne Peeples in PNAS describes experiments on mice and humans showing that visual and sound stimulation in the e.e.g gamma frequency range (30-80 Hertz, or cycles/sec, peaking at 40 Hz) elicits gamma frequency brain oscillation, enhance cognition, and diminishes levels of the amyloid plaques and tau protein tangles associated with Alzheismer's. The article is worth a read, and I pass on just a bit of a background paragraph:

Brain rhythms are known to participate in all forms of cognition. And changes of brain rhythms appear to be implicated in all forms of neurological disease...Growing evidence indicates that neurons in many animals, including humans, can strongly synchronize in the gamma range of frequencies—between 30 and 80 hertz, and peaking around 40 hertz. As far back as a 1955 study of meditating yogis, researchers have associated gamma waves with peak concentration and high levels of cognitive functioning. Studies in the last decade that manipulated brain rhythms in lab animals and humans have confirmed the impact of those rhythms on cognition and disease. Researchers have also found that fewer neurons fire together at this rate in patients with Alzheimer’s disease or other neurological conditions, suggesting that gamma rhythms may play a role in the cognitive impairments associated with such disorders.

How we get stronger.

Gretchen Reynolds points to studies on weight lifting monkeys that show weight training initially prompts increases in muscle strength by increasing neural input to muscles via the reticulospinal tract. Only later do the muscles actually start to grow.

Significance Statement

We provide the first report of a strength training intervention in non-human primates. Our results indicate that strength training is associated with neural adaptations in intracortical and reticulospinal circuits, whilst corticospinal and motoneuronal adaptations are not dominant factors.

Abstract

Following a program of resistance training, there are neural and muscular contributions to the gain in strength. Here, we measured changes in important central motor pathways during strength training in two female macaque monkeys. Animals were trained to pull a handle with one arm; weights could be added to increase load. On each day, motor evoked potentials in upper limb muscles were first measured after stimulation of the primary motor cortex (M1), corticospinal tract (CST) and reticulospinal tract (RST). Monkeys then completed 50 trials with weights progressively increased over 8-9 weeks (final weight ∼6kg, close to the animal’s body weight). Muscle responses to M1 and RST stimulation increased during strength training; there were no increases in CST responses. Changes persisted during a two-week washout period without weights. After a further three months of strength training, an experiment under anesthesia mapped potential responses to CST and RST stimulation in the cervical enlargement of the spinal cord. We distinguished the early axonal volley and later spinal synaptic field potentials, and used the slope of the relationship between these at different stimulus intensities as a measure of spinal input-output gain. Spinal gain was increased on the trained compared to the untrained side of the cord within the intermediate zone and motor nuclei for RST, but not CST, stimulation. We conclude that neural adaptations to strength training involve adaptations in the RST, as well as intracortical circuits within M1. By contrast, there appears to be little contribution from the CST.

The molecular choreography of acute exercise

Reynolds points to work of Contrepois et al, who had 36 volunteers, age range 40-75, complete a standard treadmill endurance test, running at an increasing intensity until exhaustion, usually after about nine or 10 minutes of exercise. Blood was drawn before, immediately after, and again 15, 30 and 60 minutes later. The measured the levels of 17,662 different molecules. Of these, 9,815 — or more than half — changed after exercise, compared to their levels before the workout.

Highlights

• Time-series analysis reveals an orchestrated molecular choreography of exercise

• Multi-level omic associations identify key biological processes of peak VO 2

• Prediction models highlight resting blood biomarkers of fitness

• Exercise omics provides insights into the pathophysiology of insulin resistance

Summary

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

An explanation for human synesthesia

Fascinating work from Maurer et al.:

Synesthesia is a neurologic trait in which specific inducers, such as sounds, automatically elicit additional idiosyncratic percepts, such as color (thus “colored hearing”). One explanation for this trait—and the one tested here—is that synesthesia results from unusually weak pruning of cortical synaptic hyperconnectivity during early perceptual development. We tested the prediction from this hypothesis that synesthetes would be superior at making discriminations from nonnative categories that are normally weakened by experience-dependent pruning during a critical period early in development—namely, discrimination among nonnative phonemes (Hindi retroflex /d̪a/ and dental /ɖa/), among chimpanzee faces, and among inverted human faces. Like the superiority of 6-mo-old infants over older infants, the synesthetic groups were significantly better than control groups at making all the nonnative discriminations across five samples and three testing sites. The consistent superiority of the synesthetic groups in making discriminations that are normally eliminated during infancy suggests that residual cortical connectivity in synesthesia supports changes in perception that extend beyond the specific synesthetic percepts, consistent with the incomplete pruning hypothesis.

Closing the gap between mind and brain - The dynamic connectome and psilocybin

Quiroga summaries elegant work by Kringelbach et al.,

...who provide a framework for incorporating into the connectome the dynamic variations caused by neuromodulatory systems...The main tenet of [their work] is that neurotransmitters’ systems can modulate the connectome over time, thus enabling a plethora of behaviors with the same underlying structural connectivity. To this end, a modeling approach is presented, in which the structural connectivity is estimated through diffusion MRI, and is coupled to the neurotransmitter system, estimated from positron electron tomography data. Both systems are portrayed by a set of mutually coupled dynamic equations, which are used to fit the functional connectivity, obtained from functional MRI. This approach was tested by exploring the effects that a psychedelic drug (psilocybin) had on neuronal activity, showing that the dynamically coupled neuronal and neuromodulatory systems give a significantly better fit to the measured data, compared to alternative models in which both systems were uncoupled, or in which the neuromodulatory system, rather than being dynamically updated, was frozen in time.

I pass on the Kringelbach et al. significance statement (not distinguished by its modesty) and abstract. The article is open source,and has excellent graphics and figures.  

Significance

In a technical tour de force, we have created a framework demonstrating the underlying fundamental principles of bidirectional coupling of neuronal and neurotransmitter dynamical systems. Specifically, in the present study, we combined multimodal neuroimaging data to causally explain the functional effects of specific serotoninergic receptor (5-HT2AR) stimulation with psilocybin in healthy humans. Longer term, this could provide a better understanding of why psilocybin is showing considerable promise as a therapeutic intervention for neuropsychiatric disorders including depression, anxiety, and addiction.

Abstract

Remarkable progress has come from whole-brain models linking anatomy and function. Paradoxically, it is not clear how a neuronal dynamical system running in the fixed human anatomical connectome can give rise to the rich changes in the functional repertoire associated with human brain function, which is impossible to explain through long-term plasticity. Neuromodulation evolved to allow for such flexibility by dynamically updating the effectivity of the fixed anatomical connectivity. Here, we introduce a theoretical framework modeling the dynamical mutual coupling between the neuronal and neurotransmitter systems. We demonstrate that this framework is crucial to advance our understanding of whole-brain dynamics by bidirectional coupling of the two systems through combining multimodal neuroimaging data (diffusion magnetic resonance imaging [dMRI], functional magnetic resonance imaging [fMRI], and positron electron tomography [PET]) to explain the functional effects of specific serotoninergic receptor (5-HT2AR) stimulation with psilocybin in healthy humans. This advance provides an understanding of why psilocybin is showing considerable promise as a therapeutic intervention for neuropsychiatric disorders including depression, anxiety, and addiction. Overall, these insights demonstrate that the whole-brain mutual coupling between the neuronal and the neurotransmission systems is essential for understanding the remarkable flexibility of human brain function despite having to rely on fixed anatomical connectivity.

Non-invasive DIY brain stimulators are a bad idea.

I must admit that I've been sorely tempted to have a try with one of the transcranial magnetic or direct current stimulators, easily ordered from web vendors, whose use is claimed to enhance your smarts or chill you out. A meta-analysis by Smits et al. casts cold water on the prospects of these working as advertised.

Excessive emotional responses to stressful events can detrimentally affect psychological functioning and mental health. Recent studies have provided evidence that non-invasive brain stimulation (NBS) targeting the prefrontal cortex (PFC) can affect the regulation of stress-related emotional responses. However, the reliability and effect sizes have not been systematically analyzed. In the present study, we reviewed and meta-analyzed the effects of repetitive transcranial magnetic (rTMS) and transcranial direct current stimulation (tDCS) over the PFC on acute emotional stress reactivity in healthy individuals. Forty sham-controlled single-session rTMS and tDCS studies were included. Separate random effects models were performed to estimate the mean effect sizes of emotional reactivity. Twelve rTMS studies together showed no evidence that rTMS over the PFC influenced emotional reactivity. Twenty-six anodal tDCS studies yielded a weak beneficial effect on stress-related emotional reactivity (Hedges’ g = −0.16, CI95% = [−0.33, 0.00]). These findings suggest that a single session of NBS is insufficient to induce reliable, clinically significant effects but also provide preliminary evidence that specific NBS methods can affect emotional reactivity. This may motivate further research into augmenting the efficacy of NBS protocols on stress-related processes.

Changes in cerebral cortex functional organization in healthy elderly.

Sigh.... Chong et al. offer a picture of how my 78 year old brain is more muddled than that of a ~23 year old male.

SIGNIFICANCE STATEMENT

Cross-sectional studies have demonstrated age-related reductions in the functional segregation and distinctiveness of brain networks. However, longitudinal aging-related changes in brain functional modular architecture and their links to cognitive decline remain relatively understudied. Using graph theoretical and community detection approaches to study task-free functional network changes in a cross-sectional young and longitudinal healthy elderly cohort, we showed that aging was associated with global declines in network segregation, integration, and module distinctiveness, and specific declines in distinctiveness of higher-order cognitive networks. Further, such functional network deterioration was associated with poorer cognitive performance cross-sectionally. Our findings suggest that healthy aging is associated with system-level changes in brain functional modular organization, accompanied by functional segregation loss particularly in higher-order networks specialized for cognition.

Abstract

Healthy aging is accompanied by disruptions in the functional modular organization of the human brain. Cross-sectional studies have shown age-related reductions in the functional segregation and distinctiveness of brain networks. However, less is known about the longitudinal changes in brain functional modular organization and their associations with aging-related cognitive decline. We examined age- and aging-related changes in functional architecture of the cerebral cortex using a dataset comprising a cross-sectional healthy young cohort of 57 individuals (mean ± SD age, 23.71 ± 3.61 years, 22 males) and a longitudinal healthy elderly cohort of 72 individuals (mean ± baseline age, 68.22 ± 5.80 years, 39 males) with 2–3 time points (18–24 months apart) of task-free fMRI data. We found both cross-sectional (elderly vs young) and longitudinal (in elderly) global decreases in network segregation (decreased local efficiency), integration (decreased global efficiency), and module distinctiveness (increased participation coefficient and decreased system segregation). At the modular level, whereas cross-sectional analyses revealed higher participation coefficient across all modules in the elderly compared with young participants, longitudinal analyses revealed focal longitudinal participation coefficient increases in three higher-order cognitive modules: control network, default mode network, and salience/ventral attention network. Cross-sectionally, elderly participants also showed worse attention performance with lower local efficiency and higher mean participation coefficient, and worse global cognitive performance with higher participation coefficient in the dorsal attention/control network. These findings suggest that healthy aging is associated with whole-brain connectome-wide changes in the functional modular organization of the brain, accompanied by loss of functional segregation, particularly in higher-order cognitive networks.