How Neurons in the Human Brain Encode the “When” of Experiences

Post by Meagan Marks

The takeaway

Neurons in the medial temporal lobe help distinguish temporal patterns within recurring experiences, influencing the implicit prediction of future events and guiding subsequent behavior.

What's the science?

Whether performing a daily routine or learning a new task, the human brain is constantly integrating aspects of experience—specifically, the “what” (objects/events), “where” (spatial location), and “when” (temporal structure)—to create a cohesive understanding of the world. 

Temporal structure—the “when” of an experience—allows the brain to organize information based on order in time. Encoding information in such a manner is crucial to memory formation, sequential learning, and decision making. By recognizing subtle sequences and patterns in time, the brain can predict future outcomes and adapt behavior accordingly. This process is needed for everyday tasks, like comprehending the words on a book page or responding to the flow of ideas during a conversation.  

Temporal structure is vital for survival and success, but the specific neuronal mechanisms behind this cognitive process remain unclear. This week in Nature, Tacikowski and colleagues explore how neurons encode the temporal structure of experiences into memory by observing the neural activity of human participants. 

How did they do it?

To determine how human neurons encode temporal structure, the authors recruited 17 participants, all of whom had intracranial electrodes implanted for clinical reasons. The authors then recorded the activity of individual neurons within the medial temporal lobe (MTL)—a region of the brain known for its role in memory and spatial cognition. A complex behavioral task was also created to ensure that subtle temporal patterns were presented to the participants as neuronal activity was recorded.   

The behavioral task consisted of three phases. During the first, participants were repeatedly shown six images of people that elicited a strong response from neurons in the MTL. These images were displayed at random and participants were asked to identify the gender of each person shown. 

During the second phase, the same six images were repeatedly presented over the course of six trial rounds, but this time in a predetermined sequence. This sequence was based on a pyramidal structure established behind the scenes, where one image was assigned the top of the pyramid, two were assigned to the middle, and three were assigned to the bottom. Although the participants were only shown one image at a time, these images were shown in alignment to this pyramidal arrangement, so that only images “touching” each other on the pyramid could follow each other in the display line up. During these trials, the participants were engaged in a separate task—determining if the images had been flipped—and were not aware of the display pattern. 

The third and final phase mimicked the first, however, the participants had been sufficiently exposed to the display sequence. 

What did they find?

During the first phase of the behavioral experiment, the researchers noticed that certain neurons in the MTL exhibited a significantly stronger response to one particular image compared to the others. As the experiment progressed, these neurons adjusted their activity based on the display pattern. With continued exposure, some of the initially selective neurons began responding more strongly to images that were connected on the pyramid to the original image they had favored (i.e., images connected within the sequence). This strengthening of neuronal activity directly aligned with exposure to the pattern, indicating that these adaptable neurons made associations between images and embedded the sequence into memory. The sequence was even ‘replayed’ by the neurons spontaneously during study breaks, strengthening the memory of the pattern. These neurons were distributed across the hippocampus and entorhinal cortex, suggesting that the hippocampal-entorhinal system plays a key role in encoding temporal structure.

Participants also exhibited delayed behavioral responses in the final phase when an image broke the learned sequential pattern. Given that participants remained unaware of the display pattern, it can be inferred that their recognition and memorization of the sequence occurred largely implicitly.

What's the impact?

This study is the first to show that neurons in the hippocampus and entorhinal cortex work together to encode the temporal structure of experience. These neurons play a crucial role in recognizing and memorizing patterns, influencing the implicit prediction of future events, and guiding subsequent behaviors. These findings offer a deeper understanding of the neuronal mechanisms that underlie human behavior and experience. 

Oligodendrocytes Provide Energy Reserves to Axons

Post by Laura Maile

The takeaway

When the brain is exposed to low glucose and decreased metabolism, as it is in diseases like Alzheimer’s, myelin slowly breaks down. Oligodendrocytes - cells that create myelin - can provide a reserve of energy for the axons of neurons, supporting them through periods of disease or other insults.   

What's the science?

Oligodendrocytes are the cells of the central nervous system that create myelin, the fatty substance that surrounds the axons of neurons and helps action potentials propagate down the axon. In addition to creating myelin, oligodendrocytes also support the production of ATP, the energy-associated molecule necessary for many cellular processes. This is important because myelin insulates axons, blocking their access to metabolic molecules in the extracellular space. As we age, myelin must be maintained by the constant turnover and production of new myelin proteins and fatty acids. Fatty acid oxidation is the process that occurs in the mitochondria and peroxisomes where fatty acids are broken down into acetyl-CoA, which can then be used in the production of ATP or of new fatty acids. In disorders associated with loss of myelin such as Alzheimer’s Disease, there is also reduced glucose metabolism in the brain. Scientists don’t yet know whether fatty acid and myelin production are connected to metabolism in oligodendrocytes. This week in Nature Neuroscience, Asadollahi and colleagues studied isolated optic nerves to determine whether axons depend on oligodendrocyte energy metabolism and whether myelin is disrupted when glucose is low.

How did they do it?

The authors studied the optic nerve of young adult mice because of its long, isolated axons. They used transgenic mice bred to express fluorescent proteins in oligodendrocytes. After isolating the optic nerves, they were exposed to different amounts of glucose, and fluorescent staining was used to analyze the total number and identity of surviving and dying cells. Next, they determined whether fatty acid metabolism provides an energy store by starving optic nerves of glucose and exposing them to a drug that blocks fatty acid oxidation in the mitochondria. They also used a high-resolution technique called electron microscopy to examine myelin structure in low glucose environments. 

Next, the authors sought to determine whether fatty acid metabolism in oligodendrocytes is important for axon function. They electrically stimulated isolated optic nerves while measuring the size of the evoked action potentials.  By increasing the frequency of stimulation, they could observe enhanced firing frequency of axons and measure the area of the resulting action potentials. They next disrupted fatty acid oxidation specifically in the peroxisomes of oligodendrocytes through a genetic mouse model that knocked out a specific gene. Using the same electrical stimulation experiment, they measured the action potential area of stimulated axons that were starved of glucose. Finally, to determine the role of oligodendrocytes in long-term glucose deprivation, the authors generated transgenic mice with an inducible knockout of the GLUT1 glucose transporter in oligodendrocytes. Using this model, they could disrupt glucose availability in oligodendrocytes in adult mice and then observe behavior and myelin structure using electron microscopy.  

What did they find?

The authors found that after 24 hours of low glucose exposure, oligodendrocytes and other glial cells suffered little to no cell death in the optic nerve, meaning they had access to some additional energy store.  When the optic nerve was exposed to an environment with no glucose and an inhibitor of fatty acid metabolism, 70% of cells died. After 24 hours of low glucose exposure, cells showed signs of cell death and loss of myelin integrity. When optic nerves were deprived of glucose and then electrically stimulated in the presence of a fatty acid oxidation blocker, their evoked action potentials decayed quicker than controls that had normal fatty acid oxidation. This shows that in low glucose environments, axonal function is supported by fatty acid metabolism. In transgenic mice that had a genetic block of fatty acid oxidation in oligodendrocyte peroxisomes, a similar decay in action potential area was observed, indicating that axonal function is supported specifically by oligodendrocytes. Finally, in mice that lacked the GLUT1 glucose transporter in oligodendrocytes, the authors observed loss of myelin even in the absence of behavioral deficits. This suggests that when glucose uptake by oligodendrocytes is low, normal myelin metabolism continues. 

What's the impact?

This study found that when neurons are exposed to low glucose, myelin loss, and oligodendrocyte fatty acid breakdown continues, providing support to axons and possibly avoiding permanent axon degeneration. This suggests that oligodendrocytes are important for providing energy reserves for neuronal axons and additionally, that in diseases associated with axonal degeneration and in normal aging, the imbalance between myelin production and degradation may be responsible for progressive loss of myelin.   

Access the original scientific publication here.

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.