Reblog: The Firefly Scanner is Featured on the BBC

Below is a blog post I wrote for our group after the Firefly neonatal scanner was highlighted on BBC. It’s a great, little scanner and I’m thrilled to be involved with this research. (Link to the post on our group’s blog.)

Building on previous work, Professor Martyn Paley has developed the concept of a bespoke MRI scanner for newborn babies (neonates) along with Professor Paul Griffiths. The result is a unique, full-strength neonate scanner, built by GE Healthcare and installed in the Neonatal Intensive Care Unit in the Jessop Wing. Named ‘Firefly’, the scanner is one of only two such prototype scanners in the world, and uniquely marries diagnostic imaging with easy access to our neonatal unit.

Featured last week on the BBC, the Firefly scanner has gained deserved attention. The BBC’s video of the scanner in action shows how important it is for the healthcare of newborn babies to have powerful scanning facilities within quick and easy reach. Tiny compared to adult scanners (which can easily weigh several tons), the Firefly would be able to fit in many small Neonatal Intensive Care Units. This is a major advantage over the more commonly used ultrasound imaging in providing ready access to high quality brain imaging.

Babies can be difficult to image as they rarely stay still. Our group have also recently published one of the first research papers with data collected using the Firefly scanner, in which we discuss a potential new way of correcting motion during MRI in babies. The paper is titled “Wireless Accelerometer for Neonatal MRI Motion Artifact Correction” and freely available.

We are delighted to have the Firefly scanner in Sheffield. It is an important clinical development and opens up exciting new possibilities for linking research on reproduction and development with the health of newborn babies.

technologies-05-00006-g001The Firefly 3-Tesla neonate MRI scanner in the Jessop Wing. Image from Paley et al. 2017. Technologies, 5(1); 6. (CC BY 4.0)

Reblog: Success in academia involves a lot of failure

Eric Weiskott, an Associate Professor of English at Boston College, has written a CV of his failures here. Whilst it is not often published, I don’t know a single academic or researcher who doesn’t have a similar list. I certainly do. There are rejected applications, failed experiments, unpublished papers and unfunded grants. The list is long. Incidentally, most researchers I’ve met have all echoed the same sentiment: the key to success is try and try again. The best researchers also add that it’s important to not let rejection bog you down. A few years ago, I attended an early career talk by Russell Foster, a neuroscientist who discovered photosensitive ganglion cells in the retina and by most measures a successful scientist. Based on his own experience, he listed the approximate number of applications required to land funding. As a young researcher, it was a sobering talk. However, it was also oddly encouraging to be told that as long as you do good work, it’s probably only a numbers game.

Prof Weiskott’s post is reblogged below, and it is definitely worth a read:

Eric Weiskott

When I think about my career so far, I’m humbled by the generosity of friends and colleagues. I’m also acutely aware of the odds stacked against anyone who tries to enter this profession. My own success, such as it is, was the direct result of a lot of failure. Maybe there is someone out there who succeeds in academia without failing. I am not that person. I want to talk about my experience in the hope that it smashes a few unhelpful myths about academia, publishing, and job-seeking. This is my version of a CV of failures.

Failing to get into grad school

As a senior in college, I applied to MPhil and PhD programs. Most of them rejected me. Programs that rejected me were Brown University, Harvard University, the Marshall Scholarship, Stanford University, University of Connecticut, University of Michigan, and University of Oxford. New York University and the University of Virginia waitlisted me. The University of Cambridge accepted me…

View original post 1,116 more words

Breathlessness and opioids

We’ve recently published a paper on how opioids can modulate breathlessness. (The whole manuscript is open access here). Low-dose opioids can be used for treating chronic breathlessness, but we don’t know exactly how they work.

Opioid receptors exist across the brain. These are part of the internal opioid system (endogenous opioid system) for natural pain relief. When opioids are used in the clinical setting to treat negative stimuli, such as pain, they influence the unpleasantness and the intensity of the stimulus in different ways(1). In terms of breathing, opioids lower breathing by influencing brainstem respiratory centres(2), causing breathing to stop completely in high doses, and they can also affect higher brain centres(3).

Opioids also have behavioural effects, and may, amongst other things, influence associative learning. Associative learning is when an association between two stimuli is learnt by pairing these together. For example, in chronic breathlessness this could be previously neutral stimuli (e.g. a flight of stairs) and breathlessness. This could create an anticipatory threat response, which means that simply seeing a flight of stairs is enough to bring about breathlessness or the fear associated with breathlessness. This can worsen the breathlessness for the patient in the long run.

In this study, we hypothesized that opioids improve breathlessness in part through changing the anticipatory response to breathlessness. We focused on two brain regions in particular: the amygdala and hippocampus. Both are strongly involved in associative learning(4) and are rich in opioid receptors(5,6).

What did we do? First, we asked healthy volunteers to do a breathing test where we paired three different degrees of breathlessness and three symbols. The symbols were presented immediately before the volunteer was made breathless and were matched to the level of breathlessness that they signified. We invited those volunteers who learnt to associate each different symbol and its corresponding breathlessness to undertake two MRI scans in random order. Before one scan they received a low-level opioid (remifentanil) infusion, and before the other they received a control (saline) infusion. During the scans, the volunteers repeated the breathlessness/symbol task. Below is a schematic of the breathing circuit used for the study, showing how different levels of breathlessness was induced.

breathingsystemFigure 1. Breathing circuit for inducing breathlessness

What did we find? We were able to show that breathlessness anticipation in the control condition was processed in the right anterior insula and operculum, and that the breathlessness itself was processed in the insula, operculum, dorsolateral prefrontal cortex, anterior cingulate cortex, primary sensory cortices and motor cortices. These regions have been identified in other studies on breathlessness (as discussed in a previous blogpost).

However, in the opioid condition, we saw the following:
1. Opioids reduced breathlessness unpleasantness (Figure 2)
2. This reduction correlated with reduced activity in the amygdala and hippocampus during anticipation of breathlessness (Figure 3)
3. This reduction also correlated with increased activity in the anterior cingulate cortex and nucleus accumbens during the actual breathlessness (Figure 3)
4. During the actual breathlessness, the opioid infusion directly reduced activity in the anterior insula, anterior cingulate cortex and sensory motor cortices (Figure 4).

opioid_res1Figure 2. Ratings of breathlessness and intensity. Abbreviation: Remi=remifentanil

Reduction in unpleasantness. The reduction in unpleasantness with opioids was expected – the different effect of opioids on intensity and unpleasantness has been shown in many other negative conditions, including pain(1). Interestingly, we could confirm that this lowered unpleasantness correlated with reduced activity in brain regions linked with associative learning and memory (amygdala and hippocampus) before the breathlessness began (Figure 3, bottom). This reduced activation in the amygdala and hippocampus, regions that are needed for formation of unpleasant memories, may explain how low-dose opioids gradually become more efficient as a therapy over the first week of administration. The reduction in amygdala/hippocampus activation may mean that fewer new negative memories and reaction patterns are formed.

opioid_res2.jpgFigure 3. Brain activity linked to lowered unpleasantness, relating to breathlessness (top) and anticipation of breathlessness (bottom). NA=nucleus accumbens, paraCC=paracingulate cortex, ACC=anterior cingulate cortex, PC=precuneus, ant hipp=anterior hippocampus, amyg=amygdala. 

We also see that the reduced unpleasantness correlates with activation during the actual breathlessness in the anterior cingulate cortex and nucleus accumbens (Figure 3, top). These are parts of the endogenous opioid system which reduces the perception of negative stimuli. This means that the reduced unpleasantness our volunteers felt is linked with these regions being more active. In other words, they may act to further dampen the negative sensation. Less unpleasantness during the breathlessness means that even less negative memories are likely to be formed.

Reduction in breathlessness activation. Finally, opioids directly reduced activity in the anterior insula, anterior cingulate cortex, sensory motor cortices and brainstem (Figure 4). The activation during control (saline) in the figure below is typical of breathlessness, and has been found in several other studies using breathing challenges.


Figure 4. Brain activity during breathlessness in the control (saline) condition (top) and where it is reduced by the opioid (remifentanil, bottom). Increased activation is shown in red-yellow, and decreased in blue. M1/S1=primary motor & sensory cortices, OP=operculum, dlPFC=dorsolateral prefrontal cortex, Thal=thalamus, ACC=anterior cingulate cortex, vmPFC=ventromedial prefrontal cortex, PAG=periaqueductal grey, SMG=supramarginal gyrus.

The areas that are reduced in activation with opioids are commonly activated in breathlessness and central to respiratory sensation. For example, the anterior insula, the most commonly activated brain region during breathlessness, is believed to assess the quality of the stimulus and help control interpretation. The anterior cingulate cortex, which is also commonly activated in breathlessness, is similarly involved in control of negative emotions. These regions may be part of an interpretation process that is shaped by expectation and learning(7) similar to other control systems in the body (e.g.(8)).

Summary: Opioids manipulate brain regions associated with learning, negative memory formation and negative stimulus control. We have shown that the opioid remifentanil may alter breathlessness perception and the brain regions associated both with anticipation of and actual breathlessness. This suggests that opioids work to reduce breathlessness in part through direct effects on respiratory control mechanisms in the brainstem, insula and anterior cingulate cortex, and in part through changes in how breathlessness is anticipated, by changing associative learning processes in the amygdala/hippocampus.

1. Pain, 22 (1985), pp. 261–269
2. Br J Anaesth, 100 (2008), pp. 747–758
3. J Neurosci, 29 (2009), pp. 8177–8186
4. Curr Opin Neurobiol, 14 (2004), pp. 198–202
5. Life Sci, 83 (2008), pp. 644–650
6. Pain, 96 (2002), pp. 153–162
7. Nat Rev Neurosci, 16 (2015), pp. 419-429
8. Exp Physiol, 92 (2007), pp. 695-704

All images presented with permission, creative commons licence.

Breathlessness & the Brain

Breathlessness can be many things. For example, it can be the shortness of breath after exercise – short-lived and laced with endorphins – or it can be the frightening gasping for breath experienced by patients with a range of diseases from cardiac failure and cancer to respiratory disease. From a physiological point of view, these may look quite similar, but they are not really the same thing. Breathlessness is the sensation produced by sensory input evaluated within the context of psychological and environmental factors. In short, the quality of breathlessness depends on why, who and where it is experienced – it’s situational and subjective. This means it cannot be approached, from a medical point of view, with a one size fits all solution. It’s important to understand its nuances.

So, which parts of the brain are involved in processing breathlessness? The answer is quite simple: we don’t know yet. To date, studies are few and far between, with the majority being on breathlessness in healthy controls which may or may not translate to various patient groups. While we don’t know anything for certain, particularly for patients, we do however have a few likely suspects.


The usual suspects. The first is the insular cortex. This is a region of the brain that has been identified in the majority of neuroimaging studies on breathlessness. It plays a role in the conscious awareness of body state and is involved in the perception of other unpleasant sensations, such as pain. The role of the insula is two-fold, with the posterior (towards the back) part processing the physical aspects and the anterior (towards the front) part processing the affective (relating to moods and feelings) aspects of the sensation 1. This anterior-posterior division may also be present in breathlessness, as the anterior insula appears to be more associated with the unpleasantness of breathlessness.

The next on the list of likely suspects are somatosensory and motor regions (e.g. 2), which are also activated in a number of breathlessness studies. This is not surprising, given the added work of breathing harder than normal when you’re breathless. In addition to cortical somatosensory/motor regions, we also see activation in the brainstem (particularly in the brainstem respiratory centres) and in the cerebellum (a region associated with motor function). Some of these areas may be mostly involved with breathing itself and not with breathlessness specifically, as they appear frequently in studies looking at simple breathing responses without any breathlessness.

Then there are regions that sometimes appear and sometimes don’t: the prefrontal cortex, the periaqueductal grey (PAG), the amygdala and the anterior cingulate cortex (ACC). In the case of the PAG, which is a structure in the midbrain involved in pain processing and fight-or-flight responses, this may simply be because it is small and hard to image. Recent studies using high resolution imaging have found that the PAG is involved with unpleasant respiratory sensations, and that parts of the PAG have different roles in processing respiratory threat (see Figure 1 below) 3. Looking further into its sub-divisions, the lateral PAG is downregulated during restricted breathing, and the ventrolateral PAG is upregulated. This is interesting as the lateral PAG has been associated with active coping strategies for stressful situations that can be escaped, and the ventrolateral PAG with passive coping strategies for stressful situations that cannot be escaped. In short, it seems as if different parts of the PAG are involved in different aspects of breathlessness.

elife-12047-fig2-v3-480wFig 1. 7T FMRI of respiratory threat in the PAG. Faull et al. 2016.

The prefrontal cortex has been implicated in the processing of breathlessness cues (i.e. a non-physical stimulus) in COPD patients (medial prefrontal cortex, mPFC), as has the ACC (see Figure 2 below) 4. The latter has also been identified in many studies on breathlessness in healthy volunteers, and the former is an area of the prefrontal cortex involved in emotion processing, and particularly associated with responses to fear and threat. In the above study, both patients and controls showed activation in the insula (labelled ‘Conjunction’). Opioids, which can cause make breathlessness less unpleasant, dampens brain responses to breath holding in the prefrontal and anterior cingulate cortices as well as in the insula 5. So, it’s a good guess that the prefrontal cortex and ACC are involved in the modulation of breathlessness.

chestpaperFig 2. COPD patients and control. Response to breathlessness cues. From Herigstad et al. 2015.

Similarly, the amygdala, which is frequently identified in a whole range of studies relating to emotion, threat appraisal and fight-or-flight responses, is also activated in some studies of breathlessness. The amygdala is strongly connected to the anterior insula, and breathlessness studies that have seen activation in the amygdala also show large activation in the insula.

There are also another few regions that are occasionally found and we don’t quite know how they fit in. These include the before-mentioned cerebellum, the dorsolateral prefrontal cortex and the precuneus.

The cerebellum is probably mostly involved in the motoric response to breathlessness, as it is a centre for coordination of motor function, but as the cerebellum has also been associated with cognitive function, we can’t yet determine its role in breathlessness. The dorsolateral prefrontal cortex may be part of the cognitive evaluation of breathlessness, as this is a structure that is associated with attention and working memory. The precuneus could be involved in both sensory and cognitive aspects of breathlessness, depending on which part of the precuneus is active. It is a poorly mapped structure, but in general it has a sensorimotor anterior region which links to sensory/motor areas of the brain and the insula, and a cognitive central region which links to prefrontal regions, including the dorsolateral prefrontal cortex. It also links to the thalamus, which is a subcortical structure that relays a vast range of information between the brainstem and the higher brain areas.

Linking it all together. We don’t know how this all ties together. However, one could speculate ways in which breathlessness is processed in the brain:

Brainstem breathing control. We know that respiratory centres in the brainstem receive peripheral input (input from the rest of the body) and adjust the breathing pattern in response to this. The brainstem is crucial for breathing – without it, no breathing occurs – and it almost certainly plays a part in the actual breathing response to breathlessness. The cerebellum, which is probably involved in the motor response to breathlessness, connects to the higher brain areas through the brainstem. So far so good.

PAG as a gateway. Peripheral input is also believed to be received in the PAG, which could act as a gateway of sorts. The lateral PAG relays signal directly to primary motor/sensory cortices and the (posterior?) insula, and this path may be processing breathlessness intensity. The ventrolateral PAG relays signal directly to the prefrontal cortex, (anterior?) insula and also to motor regions of the brain, and this path may be processing the threat and/or possible responses to the breathlessness. The PAG probably also connects with the thalamus, which in turn acts as a hub (see below).

Thalamus as a hub. Finally, signal could also be relayed via the PAG (or directly) to the thalamus, which has been identified in a range of breathlessness studies and is a common hub for cortical communication. From the thalamus, signal is transmitted to a range of cortical areas (including prefrontal regions and the amygdala via the medial/frontal thalamus, and somatosensory and motor regions via the ventroposterior thalamus). Breathlessness is likely modulated by several of these cortical areas and how they interact.

The complexity of the interactions may be best explained by an example:

Anxiety relating to threat is modulated by activation in both the medial prefrontal cortex (mPFC) and the amygdala. The mPFC possibly influences threat by dampening activation in the amygdala. So far, so good. The prefrontal cortex receives signal from the PAG, and may also receive input from the ACC. Both the ACC and PAG are in turn linked to the anterior insula. The anterior insula also receives input from the thalamus, which relays signal to the amygdala. The thalamus also receives input from the PAG. So now we have a network of interconnected regions which may all influence each other and work to fine-tune the anxiety response. Furthermore, the anterior insula may also receive and integrate information on the physical sensation from the posterior insula, which is linked to the ventroposterior thalamus. This part of the thalamus is connected with somatosensory and motor cortices. These are also influenced by the PAG. The thalamus and somatosensory/motor cortices also relay signal to the precuneus, which in turn could connect to the dorsolateral prefrontal cortex, thus incorporating cognitive processing. And so on. It can get a bit complex.

A suggested network is presented in the figure below.

brain3 Fig 3. Possible breathlessness network. Purple=connected cortical regions, black= signal to/from periphery, blue=signal from PAG. ‘Hubs’ are shown in green. PFC = prefrontal cortex (encompasses both medial (emotional/threat processing) and dorsolateral (cognitive processing) PFC)

In short, various studies have shown that a range of brain regions are activated during breathlessness, but we don’t yet know exactly how they are involved in processing the sensation. We may still only guess at the full picture, based on breathlessness work as well as studies on other unpleasant sensations (pain, mostly), threat or emotional processing. Much of the same processing mechanisms are likely to be found in these similar sensations. While the above figure outlines some possible networks for the processing of breathlessness, based on our current understanding of breathlessness and related conditions, (much) more information is needed.

1. Oertel, B., Preibisch, C., et al. Clin Pharmacol Ther 2008; 83:577–588.
2. Hayen, A., Herigstad, M., et al. NeuroImage 2012; 66: 479-488.
3. Faull, O., Jenkinson, M., et al. eLife 2016; 5: e12047
4. Herigstad, M., Hayen, A., et al. Chest 2015; 148(4): 953-61
5. Harvey, A., Pattinson, K., et al. J Magn Reson Imaging 2008; 28:1337–1344.

Predicting trouble: EEG, NO and stroke

We’ve recently published a paper titled “Electroencephalographic Response to Sodium Nitrite May Predict Delayed Cerebral Ischemia After Severe Subarachnoid Hemorrhage” on how electroencephalography (EEG for short) can be used to figure out which patients with a certain type of stroke (subarachnoid hemorrhage) will develop a complication after the initial brain bleed and which will not.

Subarachnoid hemorrhage is a type of stroke that can happen at any age. It is a bleed on the surface of the brain, in a space between the arachnoid membrane and the pia mater surrounding the brain (see figure below).


The bleed is usually caused by an aneurysm (a bulging, weak section of a blood vessel) bursting, causing blood to escape into the subarachnoid space. Here, it puts pressure on the brain tissue (causing tissue damage) which can also reduce blood flow to other parts of the brain (causing lack of oxygen and cell death). The released blood may be toxic to the brain tissue and could cause inflammation. At worst, a subarachnoid hemorrhage results in death or severe brain damage.

Some of the damage is caused directly by the bleed (e.g. the pressure on the brain), and some is caused by how the bleed disrupts the normal control of blood flow in the brain. In particular, it is bad when the nitric oxide pathway stops functioning properly. Nitric oxide helps preserve the circulation in small blood vessels in the brain, partly through enlarging the blood vessels (vasodilation) and lowering the gathering of blood-clot forming platelets. After a bleed, nitric oxide levels in the brain are often reduced. This could be because hemoglobin in the blood stops enzymes responsible for producing nitric oxide from working properly. Another contributing factor is that the nitric oxide that is already present in the brain reacts with superoxide (part of the immune response) which leads to the levels of nitric oxide being even further lowered.

Nitric oxide disruption appears to be involved in delayed cerebral ischemia, which is the most common complication after a subarachnoid hemorrhage. For example, people with genetically lower activity in an enzyme that produces nitric oxide have a higher risk of this complication. Delayed cerebral ischemia is the unpredictable lack of oxygen to the brain leading to severe, even fatal, brain damage. This typically happens 3-14 days after the initial subarachnoid hemorrhage.

Which brings us to our question:

Patients who have the same clinical severity, no measurable genetic differences in nitric oxide production, and who seem exactly the same can go on to show very different outcomes. One can develop ischemia and suffer devastating new brain injuries, and the other return to normal without complications. How can we tell who will get it and who will not?

EEG measures neuronal (electrical) activity using electrodes placed on your scalp. It picks up fluctuations in voltage from the electric currents in the neurons, and in the clinical setting it is used to measure the spontaneous electrical activity in a brain over time. Different parts of the brain generate different signals. Some parts show signal with low frequencies (long waves, delta and theta frequencies) and some with short frequencies (rapid waves, alpha frequencies). The signal is linked to blood flow. In subarachnoid hemorrhage, it can be used to see cerebral ischemia develop naturally at an early stage, because as the blood flow is reduced, short frequencies begin to fade and long frequencies steadily increase. In short, the ratio of alpha to delta (for example), will be reduced in the ischemic patients. However, it can take several days of recording to get a result with this method. It is possible, but not practical.

However, we know that nitric oxide disruption seems to be critically involved in delayed cerebral ischemia. This means that we can give patients a nitric oxide donor (sodium nitrite) to stimulate the nitric oxide pathway, and use EEG to measure how well they respond. By doing this, we can speed the process up. We can see if the patient responds well to the sodium nitrite, or not. This means, in short, that we can see which patients show nitric oxide pathway disruption.

Using this method, we showed in our paper that patients who later went on to develop delayed cerebral ischemia showed no change (or a decrease) in the EEG signal whilst infused with sodium nitrite. Those that did not develop delayed cerebral ischemia did the exact opposite, and showed a strong increase in EEG signal.

temp3EEG spectrograms from a patient that did not develop delayed cerebral ischemia, and one who did, plus a scatter plot with the group differences in spectrogram ratio (alpha delta ratio (ADR))

So we have not only shown how the nitric oxide pathway is important in the development of delayed cerebral ischemia, but this also means we now quite possibly may be able to relatively quickly determine who is at risk for this life-threatening complication, and who is not.

Reference: Garry, P.S., Rowland, M.J., Ezra, M., Herigstad, M., Hayen, A., Sleigh, J.W., Westbrook. J., Warnaby, C.E. and Pattinson, K.T.S. (2016) Electroencephalographic Response to Sodium Nitrite May Predict Delayed Cerebral Ischemia After Severe Subarachnoid Hemorrhage. doi: 10.1097/CCM.0000000000001950

This week in the lab…

…has been pretty much like this:


So it’s back to the drawing board, remembering to file the things that did not work under ‘learning experiences’ and try not to get too frustrated. As my job might be best described in two words: “problem” and “solving”, weeks like this are to be expected. Weeks when the gas delivery tubing loses heat too fast and the connections somehow don’t fit, when the new computer doesn’t arrive and all the crunched up paper balls miss the bin. Might spend the rest of the week looking at insulation materials and scouring plumbing shop websites for odd-sized plastic tubing.

Brainstem? Brainstem!

Revisiting brain regions, courtesy  of Pinky and the Brain.


(Incidentally, I named my first neuroscience review paper “Dyspnoea and the Brain” partly in honour of this comic, fully expecting the title to be dismissed by colleagues and journal alike. It wasn’t. Nobody has spotted the connection yet, sadly.)

Breathing on the brain

As easy as breathing? It may seem like it, but breathing is actually no easy process. It involves the precise integration of several systems, including, of course, the pulmonary and cardiovascular systems (gas exchange and transport, respectively). However, it also requires the direct involvement of the central nervous system: the brain.

The drive to breathe is generated in the brainstem. In a study published almost 100 years ago, the crucial role of the different parts of the brainstem was demonstrated in a somewhat gruesome way by sectioning the brainstem of an anaesthetised cat (Lumsden, 1923). The main areas of interest are in the medulla and pons. Cut above this, and the breathing continue. Cut below this, and it will cease.


The brainstem is the part of the brain that connects to the spinal cord. The figure above shows an MRI image of a human brainstem, with the pons (A) and medulla (B) labelled.

The Medulla

On each side of the medulla we find neurons that are grossly organised in vertical columns. These can be divided into dorsal and ventral columns – that means columns situated towards the back of the medulla, and columns that are towards the front.

On the dorsal side of the medulla (towards the back), we find neurons that primarily govern inspiration (as opposed to expiration). These neurons fire when you breathe in. One of the most important clusters of neurons in this area is the nucleus tractus solitarius (NTS), which is an area that receives sensory input from the chest. It is thought that the NTS integrates sensory information from the body and relays this to other regions in the brainstem. In short, it could be viewed as a communication hub. The NTS is involved in a range of important functions as well as respiratory control, including for example the control of blood pressure.

On the ventral side of the medulla (towards the front), we find both inspiratory and expiratory neurons. We also find motor neurons that connect with muscles in the throat and chest. The respiratory column on the ventral side can be grossly divided into three regions: rostral (top/front), intermediate (middle) and caudal (bottom//back). The rostral part holds expiratory neurons. The intermediate part contains mostly inspiratory neurons plus the assumed ‘pacemaker’ of breathing: the pre-Bötzinger complex*. This complex contains pacemaker neurons capable of setting a breathing rhythm, and it can generate different rhythms depending on the level of oxygenation. We don’t yet know if the pre-Bötzinger complex sets the pace on its own, or if uses input from other regions as well. Typically, if not influenced by other factors, this region is ‘on’ for two seconds (inspiration) and ‘off’ for three seconds (expiration). Finally, the caudal regions hold expiratory neurons (that connect with motor neurons controlling expiration).


So to summarise, it is thought that sensory  input relevant to respiration is received in the dorsal medulla, specifically the NTS, and relayed to the ventral side, where we find both expiratory and inspiratory neurons, a ‘pacemaker’ and motor neuron connections to the body. So far so good.

At normal, ‘relaxed’ breathing, we see heightened activity in inspiratory motor neurons during inspiration, but the expiratory phase is silent. This is because we normally exhale by passive recoil (i.e. by simply letting the lung return to its non-stretched state after breathing in). During heavy breathing, such as during exercise, expiration is active. This means that the expiratory muscle neurons will fire whenever we breathe out, forcing a faster and stronger expiration than normal (puffing). Which leads us to one crucial point: the activity in the medulla can be modulated, and even overridden.

The Pons

Further up in brainstem, we find clusters of respiratory neurons in the pons. If the brainstem is cut between the medulla and the pons, the breathing will (most likely) continue, but it will be irregular. The part of the pons involved in the control of breathing is the pneumotaxic centre (or, as it is currently often named: the pontine respiratory group). This is a selection of clusters that modulates breathing through connections to the medulla (i.e. through causing the medulla to change its activity). It controls the timing of breaths through switching the duration of the respiratory phases. For example, stimulation of the pontine respiratory groups can cause your breathing to switch more quickly from inspiration to expiration. It also receives input from receptors in the lung. This input acts to dampen its activity, so that the lungs aren’t made to inflate too much (or too little). In short, the pontine respiratory groups fine-tune how quick and deep you breathe.

A second region of the pons is also often discussed in terms of respiratory control, but this centre – the apneustic centre – has not been found yet. All we know is that cutting the pons in the general region where we believe the apneustic centre is located causes excessively long inspirations with only the occasional expiration (apneustic breathing). We therefore guess that this area is important for stopping inspirations (generating the inspiratory cut-off). Again, it is thought that this region acts by sending signals to the medulla.

So to summarise, the pons is necessary for the finer regulation of our breathing patterns to fit the needs of the body, say, for example, if we need to breathe faster or take deeper breaths. Without the pons, the medulla generates a rhythmic, but slightly gasping, type of breathing.

The higher brain regions

In addition, we have higher brain regions that can modulate breathing. Speaking, holding your breath, eating, being in pain or startled, emotional states – these can all change your breathing, either voluntarily or involuntarily. Generally speaking, voluntary breathing alterations (e.g. speaking, eating, holding your breath) bypass brainstem centres and act directly on spinal motor neurons, while involuntary breathing alterations (e.g. pain, startle) can act both on the spinal motor neurons and through the brainstem nuclei, thus changing the respiratory pattern generation directly.


The higher brain regions involved in breathing modulation are not fully described, and it is likely that each of the situations mentioned above may recruit different higher brain regions. For example, being out of breath can induce activation in sensorimotor brain regions and/or emotional regions (like the limbic system) and/or areas associated with cognition (prefrontal regions), each to varying degrees, depending on the level and origin of the breathlessness (Herigstad et al. 2011).


In conclusion, we are still some way away from fully characterizing how the brain governs breathing, and it’s not likely to be a simple process. As with many of the important bodily functions, there are several layers of control, both to fine-tune our responses and make it possible for us to adapt to different environments and situations, but also to provide redundancies (‘backup systems’) to ensure that the body keeps on functioning even if one system is not working precisely the way it should. It’s never as easy as breathing.


Caveat: This is meant as a brief summary of breathing in the brain. It doesn’t include all the details, mechanisms or exceptions by a long stretch. Squeezing that kind of detail into a single blog post is not really feasible.

* The pre-Bötzinger complex is a projection of the Bötzinger complex, which was named after a bottle of reasonably-priced white wine that happened to be served at the scientific workshop when its discovery was discussed.

References: Lumsden, T. J Physiol (1923), 57: 153-160; Pattinson, K.T.S. Br J Anaesth (2008), 100(6): 747-758; Herigstad, M. et al. Respir Med (2011), 105(6): 809-18.

P-values for correlations in Excel

This is just a quick post to describe how to calculate p-values for two-variable correlations in Excel. Annoyingly, there is no direct way of doing this. Excel will give you the correlation, but not its associated p-value. It can be done, however, in a slightly roundabout way.

First, calculate the correlation between your groups:

=correl(variable1, variable2)

This gives you the sample test statistic r, which can be converted to t with the following formula:


where r is the correlation obtained above and n is your number of observations. Say you have 30 samples for two groups, and a r of 0.5. The calculation to obtain t is then (in excel terms):


Then to assess the significance value associated with this t, simply use the tdist function (Student T distribution output):

=t.dist.2t(t, degrees of freedom)

This gives us results for a two-tailed distribution. Alternatively, the old tdist function can still be used, which requires the user to specify the number of tails (=tdist(t, degrees of freedom, #tails)).

Our calculation thus looks like this:

=t.dist.2t(3.05505, 30-2)

Which is the p-value for the correlation. Done!


MATLAB for physiological analysis

I use MATLAB for my number crunching. While data acquisition and analysis programs such as Spike and LabChart have analysis functions that are good, they are not always appropriate for the type of analysis required. Also, I like to know all the calculations made on my raw data, and so my analysis tends to gravitate towards custom-made code. Dealing with time series for the most part, I’ve found MATLAB very useful, but it’s also handy for other types of data.

I therefore thought I’d compile a small list of things that has worked for me for the MATLAB novice looking to start using the program.

Learning MATLAB:

  1. Start small. Create a small matrix (e.g.20×20). Write code for processing your small matrix and make sure that it does what you expect it to do. Learn the basics on this matrix before touching real data.
  2. Break it. Error messages are great. Each message will lead to a better understanding of how to use MATLAB, so make sure you understand what they mean.
  3. Use the forum. MATLAB central will have many (if not all) the answers you can wish for (including: “what does my error message mean”). It’s a great resource! Link:


  1. Remember that MATLAB is only as good as its user. In many cases, you’ll get a number which might appear reasonable, but errors in your code can still be present. Getting an output does not mean that your code works the way you want.
  2. Learn to plot your data. Plot raw data and superimpose your calculations along the way. Mistakes should be easy to visualise, at least when working with time series. This is an easy quality check and has spared me some embarrassing mistakes in the past. Also, the figures you get can be made quite attractive for publication purposes. Certainly prettier than MS Excel, at least.
  3. Run the code on a known data set first. Make sure that the code produces the results you would expect. Again, this is a simple thing that can spare you a lot of grief. Compare with in-built programs if possible (such as spike detection in LabChart versus custom-written spike detection in MATLAB).
  4. Understand which computations are better done manually. Small, one-off computations could require more work coding up than just processing manually. The point of the exercise is to make things easier, not harder.
  5. Learn how to run a series of analyses with one click. Sometimes you’ll need to run many subjects in quick succession. Writing code that reads a list of subject numbers (one click) and automatically loops through the analysis process for each line on the list is one way of doing this that has saved me some time in the past.

Automated analysis can be very useful as it is less time consuming in the long run and you reduce the risk of silly, manual mistakes (typos etc.). With a few clicks, you could run all your number crunching in the background whilst you have your morning coffee and try to wake up your brain. Sounds good, eh? It also helps you understand the data better. For example, if you want to calculate a waveform mean, you have to know the mathematical formula for doing so. In an in-built program, this would not be needed. In short, it can be very helpful, when done right.

A few other things:

  1. Text files are good. Text files (.txt or .dat) are quite easy to work with in MATLAB. Save raw data in one of these simple formats as well as the custom format.
  2. Company is better. If there is someone else around that knows or wants to learn, join forces. It’s much more fun that way.
  3. Annotation is the best. Annotate and annotate well. Your future self thanks you! Trust me on this. A few simple %this-is-what-this-line-does will make your life infinitely easier.

If you’re not certain about using MATLAB, there’s a 30-day trial version available that you can play with to figure out if it is for you. It’ll take a little while to get to grips with if you’re not used to this type of program, but it’s worth the time.