Heart Rhythms and the Perception of Time

Post by Anastasia Sares

The takeaway

This study shows that our general sensitivity to internal bodily states, our ability to reproduce time intervals accurately, and the strength of heartbeat-related signals in the brain are all related—consistent with the idea that our hearts may be key to anchoring our minds in time. 

What's the science?

Researchers have long known that the brain must have some sort of timekeeper or pacemaker that helps us estimate the passage of time. Increasingly, they are proposing that this timekeeper might be connected to the heart. A heartbeat influencing our perception of time is an example of embodied cognition, the concept that our mental processes are determined (at least in part) by our bodily states. A couple of papers made headlines in early 2023 showing that, on average, the beating of the heart affected moment-to-moment time estimation. However, individuals vary in their sensitivity to internal signals from their body (also known as interoception). Could this affect how good they are at estimating the passage of time and reproducing time intervals? And how exactly do the heart and the brain communicate this information?

This week in the Journal of Neuroscience, Khoshnoud and colleagues tracked the heart, the brain, and people’s conscious perception of time to understand the relationship between them during an interval-reproduction task.

How did they do it?

The authors first measured participants’ awareness of their own internal bodily states. They did this in two ways, the first being the Self-Awareness Questionnaire, where they rated their agreement with statements like: “I feel full and bloated after eating,” “I feel pain extremely,” or “I feel my heart thudding.” The second was a heartbeat counting task, where participants were asked to count their heartbeats for an indeterminate length of time without any physical aids like a finger on the wrist.

Next came the interval-timing task. In all trials, participants heard a sound that lasted either 4 seconds, 8 seconds, or 12 seconds, and when the sound ended, they had to press a button as soon as possible. Afterward, the participants had to reproduce the interval they had just heard by pressing another button 4, 8, or 12 seconds after the start of the next sound, or they did nothing. They knew ahead of time which type of trial it would be. In other words, while listening to the first sound, the only difference between trials was the knowledge that they would have to reproduce the interval later.

During the interval timing task, participants were hooked up to an electrocardiogram (measuring electrical signals from the heart) and an electroencephalogram (measuring electrical signals from the brain). Using these devices, the authors recorded the heartbeat-evoked potential, which is the brain signal occurring after a specific peak in the heartbeat (R peak). The authors also measured an electrical signal corresponding to timing in the brain called the contingent negative variation, because it is a long negative signal leading up to an anticipated event. 

What did they find?

On average, participants tended to produce shorter time intervals than the ones they had been presented with. However, there was a lot of variability between individuals—for example, in the 12-second condition, people produced intervals ranging from around 7 seconds to around 13 seconds. Scores on the Self-Awareness Questionnaire, changes in heartbeat-evoked potential, and the size of the contingent negative variation were all correlated to the length of interval a person produced in the reproduction task. Better self-awareness and less dramatic changes in the neural signals correlated to longer intervals, which were typically more accurate.

While participants listened to a new interval and intended to reproduce it, the heartbeat-evoked potential slowly increased from negative to positive. The bigger the change in heartbeat-evoked potential, the shorter the interval the person produced on average. On the other hand, accuracy on the heartbeat counting task did not seem to be related to accurate time production, which conflicted with previous studies.

What's the impact?

This study adds to the evidence for embodied time cognition. It suggests that during time estimation, signals from the heart to the brain accumulate, helping us to know how much time has passed, and that this signal is calibrated differently across individuals. However, there is still a lot we don’t know about the causal chain of events and more exploration is needed in this relatively new research field.  

Using Brain Organoids To Model Neurodevelopmental Disorders

Post by Lila Metko

The takeaway

Neurodevelopmental Disorders (NDDs) are characterized by improper brain development and deficits in cognition and behavior. Organoids are three-dimensional cellular structures, grown from human stem cells that may provide a solution for modeling NDDs for potential human therapeutics.   

What's the science?

Research using human-induced pluripotent stem cells (iPSC) is becoming increasingly sophisticated, as it is possible to differentiate these cells into many specialized cell types. Previously, most research with iPSCs has used two-dimensional culture systems, which cannot model complex cell processes such as cell migration and high-complexity cell-cell interactions. This week in Brain, Dionne and colleagues review the ability for three-dimensional, human iPSC derived brain organoids to model many of the NDDs that are difficult to translate from animal models to humans. They discuss how organoids are not without drawbacks: genomes may be altered in the process of cell reprogramming, and there are no standardized procedures to validate the quality of new iPSC lines. Organoids are, however, becoming increasingly more advanced and are a powerful tool for studying NDDs as an alternative to animal models or clinical research in humans.  

How did they do it?

The authors investigated the role of organoids in finding treatments for several common NDDs and summarized many of the advanced experiments that have been done with organoids in recent years. Many of these NDDs have pathology that makes them difficult to model in animals. For example, microlissencephaly, a disorder characterized by lower levels of brain gyrification, is difficult to model in animals because rodent brains are normally lissencephalic. Other disorders, such as Fragile X syndrome, may necessitate organoid models because treatments that have shown high success rates in animals have proven to be untranslatable to humans. Organoids have also proved useful for disorders that are believed to develop pathology in a particular stage of cellular differentiation. Further, there are limitations to studying rodent organs because they develop differently than human organs and the developmental timeline is different. Therefore, organoids give researchers the opportunity to more accurately mimic the developmental pathways of the human brain and apply interventions at particular stages. 

What did they find?

Among the organoid models used for disorders discussed, many produced new data that could not be found in animal models. For example, in research of Fragile X Syndrome, a NDD caused by abnormal translation regulation, animal models showed that mGluR5 inhibition (excitatory) or enhancement of GABAergic signaling (inhibitory) reversed cellular and behavioral deficits. However, these therapies did not show promising results in clinical trials. Organoid models of Fragile X syndrome showed that within targets of the primary protein that is absent in the disorder, FMRP, 66% were human specific. This means that the majority of the targets that the missing protein in Fragile X Syndrome acts on are found only in humans. 

Additionally, there are promising results for using organoid models to map out a more human-like developmental timescale. Angelman Syndrome (AS), is an NDD in which a mutation causes a loss of function in a specific protein, UBE3A, leading to intellectual disabilities and seizures. Organoid models developed from patients with AS, have shown that in these specific organoids, UBE3A localizes to the cytoplasm at a different developmental stage than in a typically developing human. Another instance of organoids better mimicking the development of humans is in Tuberous Sclerosis Complex (TSC). In this disorder, cortical tubers, malformed regions within the cortex, are a major part of the disease pathology but do not develop in mouse models. Research with human-based organoids showed that TSC organoids had a different ratio of glial (supporting) cells to neurons than those in a typically developing human. 

What's the impact?

This review highlights a technology that has the potential to make huge gains in expanding our translational knowledge of neurodevelopmental disorders. These findings suggest that human iPSC organoids have already made big strides towards developing therapeutics for NDDs and will likely continue to in the future. Based on these findings, there is a high likelihood that future neuroscience research will be increasingly dependent upon organoid models as a route to finding effective therapies. 

Access the original scientific publication here.

The Nuanced Relationship Between Neuronal Activity and Blood Flow

Post by Shahin Khodaei

The takeaway

Increased neuronal activity in a brain region increases blood flow to that area. When neurons in a region are active, the signal gets sent up along the vessels that supply blood to that region, causing them to dilate upstream. 

What's the science?

When there is increased neuronal activity in a region of the brain, more blood flows to that area – a process called neurovascular coupling (NVC). This coupling is the basis for functional magnetic resonance imaging (fMRI), which measures blood flow to a brain region as a surrogate for neuronal activity. The regulation of NVC at the spatial level is not well understood – does increased neuronal activity in a small brain area lead to dilation of blood vessels in the same region? Or is the relationship more nuanced? This week in Nature Neuroscience, Martineau and colleagues addressed these questions by studying neuronal activity and blood vessel dilation in small regions of the mouse brain using microscopy.

How did they do it?

The authors used a mouse model and focused on a brain region called the sensory cortex, which is active in response to physical stimulation. Within the rodent sensory cortex, there are cortical “barrels” which become active in response to stimulation of each of the mouse’s whiskers – a cortical barrel for whisker W1, a barrel for the next whisker W2, then W3, and so on. To study the relationship between neuronal activity and blood flow in the brain of mice, the authors removed a portion of the skull directly over the sensory cortex and surgically replaced it with glass. This gave them a window through which they could study the sensory cortex, using microscopes.

The authors performed their experiments on mice whose neurons expressed a fluorescent calcium indicator, meaning that active neurons emitted red light. They then stimulated the whiskers of mice, and used wide field imaging to locate the corresponding barrel for each whisker. Simultaneously, they made use of the fact that oxygenated and de-oxygenated hemoglobin scatters the microscope’s light differently, and were able to characterize blood flow to each barrel. They also used a very high-resolution technique called two-photon microscopy to study the dilation and blood flow through individual vessels in each barrel, and how it changed due to whisker stimulation and neuronal activity.

What did they find?

As expected, when each whisker was stimulated, the corresponding barrel in the sensory cortex showed increased neuronal activity and increased blood flow. Then the authors used higher resolution imaging techniques to study blood vessel dilation in response to whisker stimulation in each barrel. They found that the response of blood vessels to was very heterogeneous: some vessels in barrel W1 dilated when whisker W1 was stimulated, some did not, and some actually dilated when whisker W2 was stimulated. Further experiments showed that blood vessels were not dilating due to increased neuronal activity in their immediate surroundings. Instead, downstream neuronal activity sent a signal up the vessel, causing dilation; meaning that blood vessels dilated in response to downstream neuronal activity. So, in the example above, a blood vessel that was imaged in barrel W1, but was in fact carrying blood toward W2, would dilate in response to neuronal activity in W2 and not W1. 

What's the impact?

This study shed light on the spatial regulation of neurovascular coupling. As the spatial resolution of imaging techniques such as fMRI increase, these findings are incredibly relevant: they suggest that at high resolutions, changes in blood vessels do not report neuronal activity of their surroundings, but instead reflect an integration of neuronal activity downstream. 

Access the original scientific publication here.