Coordinating actions in the absence of sensory cues

In a nutshell: When people coordinate their actions, they share similar patterns of brain activity and behaviour – even if they can’t see or hear each other.

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Many human behaviours require two or more people to coordinate their actions, such as rowing, dancing or even holding a conversation. Typically, each person modifies their behaviour in response to sensory cues from the others. But can behaviour be coordinated when those cues are absent?

To answer this question, Brain Function CoE researchers David Painter and Jason Mattingley conducted experiments in which pairs of people used a joystick to guide a cursor on a computer screen towards a target location. In separate trials of the task, each person in the pair controlled the cursor either independently or jointly with the other person. Joint action required both people to coordinate their behaviour – without being able to see each other or communicate in any way. During the task, the participants’ behaviour and brain activity were recorded.

The researchers found that participants’ behaviour was different in solo tasks than in joint tasks. This confirmed that the participants took their partner’s actions into account, rather than both members of the pair acting independently at the same time.

Analysis of the brain recordings revealed that participants in each pair had similar patterns of brain activity during the joint task. The similarity peaked when participants successfully reached the target with their cursors. The same patterns were not shared when the participants completed the task individually at the same time.

This coupling of brain activity and behaviour during joint tasks is a sign of real-time coordination. It also reveals that a link between the brain and behaviour underpins coordinated actions – even in the absence of sensory cues.


Reference:
Painter, D. R., Kim, J. J., Renton, A. I., & Mattingley, J. B. (2021). Joint control of visually guided actions involves concordant increases in behavioural and neural coupling. Communications Biology, 4(1), 816. doi: 10.1038/s42003-021-02319-3


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Lipid by-products linked to learning and memory formation

In a nutshell: The brain produces saturated free fatty acids during learning and memory formation, suggesting a previously unknown role for these lipid by-products.

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In response to learned fear, the concentration of saturated free fatty acids (FFAs) increases in certain parts of the brain. Brain Function CoE researchers made this discovery in the first brain-wide study of how FFA levels change in response to learning.

FFAs are derived from phospholipids in the brain. Unsaturated FFAs, such as arachidonic acid, have long been considered beneficial for learning and memory. But precisely how they and other FFAs contribute to these important processes was not known.

A research team led by Brain Function CoE researchers Frédéric Meunier and Pankaj Sah from the Queensland Brain Institute mapped the distribution of 18 saturated and unsaturated FFAs across the rat brain. The highest concentrations of FFAs were found in the amygdala, hippocampus and prefrontal cortex – which are involved in learning and memory. Saturated FFAs were more abundant than unsaturated FFAs across the brain.

To test how the concentration of FFAs changed during learning and memory formation, the researchers conducted an experiment involving auditory fear conditioning. This experiment teaches animals to associate a sound with an unpleasant sensation.

The researchers found that auditory fear conditioning led to an increase in saturated FFAs, mostly myristic and palmitic acids, in the same regions. It also led to a smaller increase in unsaturated FFAs like arachidonic acid. These changes were not seen when memory consolidation was chemically inhibited.

Studies of the brain often focus on the roles of proteins, genes and brain structures. The results of this study demonstrate the importance of studying the roles of phospholipids and FFAs as well.

Next steps:
The team will investigate the mechanisms that contribute to the observed increases in saturated FFAs. They will also study how the saturated FFAs contribute to the changes in brain cells that underpin learning and memory.


Reference:
Wallis, T.P., Venkatesh, B.G., Narayana, V.K., Kvaskoff, D., Ho, A., Sullivan, R.K., Windels, F., Sah, P., & Meunier, F.A. (2021). Saturated free fatty acids and association with memory formation. Nature Communications, 12, 3443. doi: 10.1038/s41467-021-23840-3


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A new maestro in the brain’s orchestra

In a nutshell: A single chandelier neuron can initiate rhythmic electrical activity at specific frequencies in brain circuits formed by thousands of cells.

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Electrical activity in the brain contains rhythmic oscillations at different frequencies ranging from 0.01 Hz to 600 Hz. Like musical notes in a symphony, these electrical rhythms are the result of precisely timed, coordinated activity. They are generated by thousands of brain cells of different type arranged as ensembles.

Oscillations with different frequencies have different functions depending on the brain region and behavioural state. In the temporal lobe, oscillations called sharp waves and ripples (SWs) occur during sleep to help consolidate memories. SWs are one of the most synchronized brain rhythms, and understanding these rhythms at the cellular level could help to explain how they contribute to memory function and disorders such as epilepsy.

To investigate the origin and generation of SWs, Brain Function CoE researchers examined networks of brain cells in the temporal lobes of rodents. The research was led by Madhusoothanan Perumal in Pankaj Sah’s group at the Queensland Brain Institute.

Using recordings of the electrical activity in different types of brain cells during SWs, the researchers discovered that SWs are initiated by a rare type of brain cell known as a chandelier neuron. These neurons form extensive connections within local regions of the brain. The recordings showed that chandelier neurons orchestrate other cells and their circuits at precise times to generate SWs.

To understand how oscillations are produced at specific frequencies, the researchers built a computational model of a neural network containing microcircuits controlled by chandelier neurons. Simulations using the model generated SWs. They also revealed that interactions between microcircuits and the distribution of connections between neurons in the network produced the distinctive frequencies of SWs.

Next steps:
The simulations predicted a distinctive role for another type of neuron, basket neurons, in stopping brain networks from becoming epileptic. The researchers plan to investigate the different roles that distinct cell types have in generating brain oscillations.


Reference: 

Perumal, M. B., Latimer, B., Xu, L., Stratton, P., Nair, S., & Sah, P. (2021). Microcircuit mechanisms for the generation of sharp-wave ripples in the basolateral amygdala: A role for chandelier interneurons. Cell Reports, 35(6), 109106. doi: 10.1016/j.celrep.2021.109106


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Investigating curious chemical changes to help stroke patients

In a nutshell: Brain damage during a stroke can cause patients to go blind. Recovery was thought to rely on two factors – but researchers have just discovered one more.

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As many as one-third of people who survive a stroke lose their eyesight – and most will not fully recover their vision. Known as ‘cortical blindness’, their loss of vision is the result of damage to the primary visual cortex (V1), which blocks the flow of information from the eyes to the brain. This damage also triggers degeneration in brain regions that send visual information to V1, such as the lateral geniculate nucleus (LGN). However, some LGN cells can survive and retain their visual function.

The potential for recovery from cortical blindness was thought to depend on a balance between degeneration and cell survival. But new research from the Brain Function CoE has found a third, previously unknown factor: changes in the chemical activity in LGN cells after V1 damage. The research was carried out by a team led by Marcello Rosa from Monash University.

Normally, LGN cells that send visual information to the cortex use excitatory neurotransmitters – chemicals that help to transmit signals from one cell to the next. Other LGN cells use inhibitory neurotransmitters, which stop signals from going further. This balance of neurotransmitters helps the brain to prioritise which visual information it processes. But after V1 damage, there is a seven-fold increase in the number of LGN cells producing an inhibitory neurotransmitter called GABA. This includes cells that are expected to make the surviving connections to the cortex.

The researchers aren’t sure why cells that need to transmit information produce a chemical that stops transmission. Perhaps it has a positive effect, somehow helping the surviving cells to make the most of their remaining resources. Or it might have a negative effect, limiting the potential for recovery. Either way, this discovery provides neuroscience researchers with new information for understanding – and maybe eventually treating – cortical blindness.

Next steps:
The researchers are investigating the connections made by the surviving cells to see which brain areas they send information to.


Reference: 

Atapour, N., Worthy, K. H., Rosa, M. G. P. (2021). Neurochemical changes in the primate lateral geniculate nucleus following lesions of striate cortex in infancy and adulthood: implications for residual vision and blindsight. Brain Structure and Function, https://doi.org/10.1007/s00429-021-02257-0


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Attentional lapses are linked to local sleep-like activity in the awake brain

In a nutshell: The presence of slow waves in the awake brain is linked to lapses in attention such as mind-wandering and mind-blanking.

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Throughout the day, our attention fluctuates widely. Even in the midst of a task, we can find our minds wandering – or even going blank. In fact, research has shown that we spend up to half our waking lives not paying attention to our surroundings or the task at hand. But what happens in the brain during these attentional lapses?

To find out, a team led by Brain Function CoE researchers Thomas Andrillon and Naotsugu Tsuchiyafrom Monash University analysed the behaviour, subjective experience and brain activity of healthy participants performing a ‘go / no go’ task. By requiring participants to pay close attention, respond quickly to ‘go’ instructions, and ignore ‘no go’ instructions, this task tests response speed and accuracy.

During the task, the participants were randomly interrupted and asked to indicate their mental state: task-focused, mind-wandering or mind-blanking. Electroencephalography (EEG) was used to measure the participants’ brain activity.

The EEG recordings revealed the presence of ‘slow waves’ in the brain. They are similar to the brain waves commonly observed after the onset of sleep, although smaller in amplitude and less widespread. The researchers found that these slow waves increased in number when the participants’ behaviour indicated that their attention lapsed or just before participants reported their minds wandering or going blank. The presence of these slow waves in the awake brain could indicate that parts of the brain have transitioned to a brief and local episode of sleep.

The researchers also found that the location of these slow waves could lead to different behaviours. Slow waves towards the front of the brain led to impulsivity: faster responses on the ‘go / no go’ task, more false alarms, and more mind-wandering. By contrast, slow waves at the back of the brain were linked to sluggish responses, more misses on the task and more mind-blanking.

These results suggest that attentional lapses, despite their diversity, could share a common physiological origin: the emergence of local sleep-like activity within the awake brain.

Next steps:
The researchers plan to manipulate the number of attentional lapses that healthy people experience while awake, either by disrupting their sleep using noises or by administering drugs. They want to study adults and children with ADHD to see if attentional disorders can be explained by more sleep intrusions during the day.


Reference: 

Andrillon, T., Burns, A., MacKay, T., Windt, J., & Tsuchiya, N. (2021). Predicting lapses of attention with sleep-like slow waves. Nature Communications, 12, 3657. doi: 10.1038/s41467-021-23890-7


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Overcoming bias when analysing transcriptomics data

In a nutshell: A common method for linking gene expression with brain structure and function is affected by substantial bias. A new software toolbox can help researchers overcome them.

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In recent years, efforts to understand the brain have been enhanced by transcriptomic profiling – a measure of the expression levels of every gene in a genome, in every cell or tissue across the brain. This information helps to link the brain’s molecular activity with observable measures relating to its structure or function (known as ‘phenotypes’).

New research from the Brain Function CoE shows that a common method for discovering the links between gene expression and phenotype is affected by substantial bias.

To link gene expression to a brain phenotype, researchers use an approach called gene category enrichment analysis (GCEA). GCEA uses statistical methods to score how well the expression of each gene correlates to a particular phenotype. The genes are then grouped together by category, and their scores are combined. GCEA measures the statistical significance of each category’s cumulative score, which identifies the gene category most strongly related to a particular phenotype.

Brain Function CoE researchers Ben Fulcher and Alex Fornito, together with Aurina Arnatkeviciute from Monash University, examined the statistical biases involved in using GCEA with transcriptomic data. They found that the rate at which a particular gene category is linked to a random phenotype is much higher than would be expected by chance. This leads to false positives – associations reported where there really are none. For some gene categories, the researchers found that more than 20% of associations were false positives.

After identifying the causes of this false-positive bias, the researchers designed a new GCEA approach to overcome the bias. It uses a different method to measure statistical significance. Their software toolbox, which can be used to perform conventional GCEA and their new approach, is freely available online.

Next steps:
The team has no plans to do more work in this research area.


Reference: 

Fulcher, B. D., Arnatkeviciute, A., & Fornito, A. (2021). Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data. Nature Communications, 12, 2669. doi: 10.1038/s41467-021-22862-1


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Deciphering claustrum connectivity

In a nutshell: A new model suggests that connectivity between the claustrum and cortex is organised by function, not location.

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The claustrum is a small structure in the temporal lobe that sits just underneath the cerebral cortex – the thick, folded layer of cells that covers the brain’s surface. It forms extensive connections with every area of the cortex. This unusually widespread connectivity has prompted various hypotheses about the claustrum’s function. For example, it might be key to integrating conscious perceptions. Or it could be involved in changing the brain from one mode to another – such as when we switch from concentrating to relaxing, or shift our attention between different problems.

Determining the function of the claustrum requires an understanding of how its connectivity is organised. In the prevailing model, connectivity is based on anatomical location: areas of the claustrum that are close together connect with areas of the cortex that are close together, while distant areas in the claustrum connect to distant areas of the cortex.

The results of a new study from Brain Function CoE researchers argue against this model. Instead, they support a new model in which similar functions dictate which cells in the claustrum connect to which parts of the cortex. The study was carried out by an international group of researchers led by investigator Marcello Rosa.

The researchers conducted experiments on the brain to get a more precise view of how the claustrum connects to the cortex. They focused on the cortex of the parietal lobe, which is responsible for behaviours such as visually guiding movement, feeling sensations, sensing position and movement, and some aspects of visual navigation.

The researchers mapped areas of the parietal lobe cortex with similar functions and traced their connections back to the claustrum. Even if these cortical areas were far apart, they received connections from the same region of the claustrum. The researchers also discovered that the regions of connectivity within the claustrum are much more extensive than previously thought.

Organising connectivity in this way could allow the brain to integrate functions for similar types of tasks, while also allowing it to switch resources from one type of task to another when needed.

Next steps:
The researchers plan to create an even more comprehensive map of the brain, including areas in the frontal, temporal and occipital lobes. They will use this model to further investigate the role of the claustrum.


Reference: 

Gamberini, M., Passarelli, L., Impieri, D., Montanari, G., Diomedi, S., Worthy, K. H., Burman, K. J., Reser, D. H., Fattori, P., Galletti, C., Bakola, S., & Rosa, M. G. P. (2021) Claustral input to the macaque medial posterior parietal cortex (superior parietal lobule and adjacent areas). Cerebral Cortex, doi: 10.1093/cercor/bhab108


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A salience misattribution model for addictive-like behaviours

In a nutshell: Assigning too much importance to drug-related stimuli could be one driver of addictive behaviours, according to a new theory.

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Our survival depends on the brain’s ability to adapt to changing circumstances. It does this by creating internal models of our environment, which are constantly updated with new information. These models help us to make predictions based on past experiences and to adapt our behaviour accordingly.

Studies have shown that the anterior cingulate cortex (ACC) and dopamine systems in the brain are involved in updating our internal models. Now, Brain Function CoE researchers present a theory of how dysfunction in the ACC and dopamine systems could be involved in addiction. The work was led by Shivam Kalhan, a PhD student in the lab of Marta Garrido at the University of Melbourne.

In a review of the literature, the researchers describe how the ACC and dopamine systems are involved in extracting relevant information from the huge volume of sensory input to the brain.

They also discuss the empirical evidence suggesting that in people who have an addiction, the ACC and dopamine systems often function abnormally.

Based on this evidence, the researchers propose that when the ACC and dopamine systems are dysfunctional, some information is considered more important, or salient, than it really is. For example, the brain might mistakenly attribute higher relevance to the sight of cigarettes or a lighter than to other reward-inducing stimuli, such as the sight of exercise equipment. This leads to the production of inaccurate internal models, which drive decisions that reinforce addictive-like behaviours.

The researchers believe that incorrect updating of internal models is one of many possible mechanisms causing abnormal decision-making in people with an addiction.

Next steps:
The researchers plan to develop a mathematical model of their theory and test it in experiments with healthy people and those with drug addiction.


Reference: 

Kalhan, S., Redish, A. D., Hester, R., & Garrido, M. I. (2021). A Salience misattribution model for addictive-like behaviors. Neuroscience & Biobehavioral Reviews, 125, 466-477. doi: 10.1016/j.neubiorev.2021.02.039


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Brain changes across the psychosis continuum

In a nutshell: The severity of psychotic experiences, regardless of a schizophrenia diagnosis, is linked to altered brain connections during sensory learning.

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We use sensory learning to process information about our surroundings and predict what is likely to happen. Recent theories propose that an impaired ability to make these predictions could be a cause of psychotic experiences. Instead of reliably predicting future events based on past experiences of their sensory environment, some people might assign too much importance to irrelevant sensory information. This could explain why people with schizophrenia, for example, can experience delusions and perceive the world differently than others.

Brain Function CoE researchers tested these theories by measuring people’s ability to judge simple sound patterns. The research team was led by Ilvana Dzafic and Marta Garrido at the University of Melbourne.

The team recruited 66 participants across the psychosis continuum – from healthy people who had experienced psychotic-like symptoms to people with schizophrenia experiencing severe psychosis. The participants completed an auditory oddball task, which tests how the brain responds to unexpected sounds. Their brain activity was recorded during the task using electroencephalography (EEG).

By analysing the EEG recordings, the researchers found that the brain responses to unexpected sounds were smaller in participants with schizophrenia than in those without the disorder.

The researchers also used EEG recordings to measure connectivity between different regions of the brain. In people with schizophrenia, altered connectivity is known to affect brain responses to unexpected sounds.

The researchers found that the participants who had experienced the most severe psychotic symptoms – regardless of a schizophrenia diagnosis – had weaker connectivity within the right inferior frontal gyrus (IFG). Decreased activity in this region was also linked to impaired sensory learning.

Moreover, participants who had experienced more psychotic symptoms showed stronger connectivity from the left IFG to a region called the superior temporal gyrus (STG). By contrast, participants with more severe hallucinations had weaker connectivity from the left STG to the IFG. This indicates that sensory information may be suppressed, relative to previous predictions about the environment, in people who experience psychosis.

These findings suggest that weaker connectivity in the IFG may underlie an impaired ability to make judgments about the sensory world in people experiencing psychosis.

Next steps:
The research team would like to study participants over longer time periods, including people who are at ultra-high risk of developing psychosis or have recently experienced their first episode of psychosis. This would help them to see when the relevant changes in the brain emerge.


Reference:

Dzafic, I., Larsen, K. M., Darke, H., Pertile, H., Carter, O., Sundram, S., & Garrido, M.I. (2021). Stronger top-down and weaker bottom-up frontotemporal connections during sensory learning are associated with severity of psychotic phenomena. Schizophrenia Bulletin, sbaa188. doi: 10.1093/schbul/sbaa188


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Spatial navigation beyond the hippocampus

In a nutshell: Brain imaging has expanded our understanding of the regions responsible for spatial navigation.

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Spatial navigation is a crucial everyday skill. We use it to find our way around, follow directions and avoid getting lost. If we lose this ability, our quality of life decreases significantly.

In humans, functional magnetic resonance imaging (fMRI) has provided extensive insights into the role of different brain regions in various tasks and behaviours. Most studies of spatial navigation in humans have focused on the hippocampus, a region of the brain involved in learning and memory. But by imaging the entire brain, fMRI studies have also implicated brain regions other than the hippocampus.

In a review of recent research, Brain Function CoE researchers Oliver Baumann and Jason Mattingley have examined the contribution of these other brain regions to spatial cognition. They focus on four regions that are most consistently linked with spatial cognition: the parahippocampal cortex, the retrosplenial complex, the dorsal striatum, and the posterior parietal cortex.

The researchers show that these four brain regions function in ways that complement the hippocampus. The parahippocampal cortex pre-processes visual information about spatial layouts. The retrosplenial complex plays roles in representing relevant landmarks and directions and in maintaining long-term spatial knowledge. The dorsal striatum is involved in learning habits – such as following the same route to work each day. And the posterior parietal cortex provides a body-centred reference frame for guiding our movements.

Importantly, these regions must all work together to enable successful spatial navigation.

Next steps:
Oliver Baumann is now investigating the effects of spatial environments on cognition and emotion. More specifically, he is studying which features of natural and built environments allow us to function and feel our best.


Reference:
Baumann, O., & Mattingley, J. B. (2021). Extrahippocampal contributions to spatial navigation in humans: A review of the neuroimaging evidence. Hippocampus, doi: 10.1002/hipo.23313


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