Contrasting Effects of LSD and Psilocybin on Brain Connectivity and Blood Flow

Post by Shalana Atwell

The takeaway

Although LSD and psilocybin act primarily through the same serotonin receptor (5-HT2AR), their differing effects on brain function remain poorly understood. Researchers found that LSD produced a delay before participants experienced the strongest effects, increased brain blood flow, and decreased global brain connectivity. These findings contrast with psilocybin’s effects and suggest distinct underlying mechanisms.

What’s the science?

As LSD and psilocybin are increasingly being studied in clinical trials for anxiety and depressive symptoms, it is important to understand how these psychedelics act in the brain. Previous research has found a delay between peak LSD concentrations in the blood and peak subjective effects, as well as changes in brain connectivity. However, it remains unclear how these effects relate to LSD’s interaction with its primary target, the serotonin 2A receptor (5-HT2AR). Recently in Nature Neuroscience, McCulloch and colleagues utilized simultaneous brain imaging techniques to investigate how LSD binds to this receptor and influences subjective effects, brain connectivity, and brain blood flow, compared to psilocybin.

How did they do it?

1. LSD administration and subjective effects: Eleven healthy adults received a single oral dose of LSD (25-200 µg), with the dose concealed from participants. The authors collected blood samples to measure LSD concentrations and asked participants to rate the intensity of their psychedelic experience on a scale of 0-10 throughout the session, allowing them to compare changes in subjective effects with circulating drug levels.

2. Receptor binding and brain imaging: To track LSD’s binding to 5-HT2AR, participants were injected with a radioactive tracer ([¹¹C]Cimbi-36) and underwent simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) scans. These techniques allowed them to estimate receptor occupancy (the proportion of receptors occupied by LSD) and examine how receptor binding related to drug concentrations and subjective effects.

3. Brain blood flow and connectivity: Using specialized MRI techniques, they measured cerebral blood flow, or the amount of blood flowing through the brain, and blood flow through the internal carotid arteries, which supply blood to the brain. They also used functional MRI (fMRI) to assess global functional connectivity, a measure of how strongly activity patterns across different brain regions fluctuate together.

4. Comparison with psilocybin: Finally, they compared LSD-induced changes in brain blood flow and functional connectivity with previously collected data from healthy volunteers who received psilocybin. This comparison allowed them to investigate whether two psychedelics acting primarily through the same receptor produce similar or distinct effects on brain function.

What did they find?

1. LSD concentrations and subjective effects: Investigators found that LSD concentrations in the blood peaked approximately 30 minutes before participants reported their strongest subjective effects. Interestingly, participants reported weaker effects while LSD concentrations were increasing than when they were decreasing, even at equivalent concentrations in the blood (a phenomenon known as a counterclockwise hysteresis loop). This suggests that LSD’s subjective effects are delayed relative to its concentration in the blood, a pattern not observed with psilocybin.

2. Receptor binding and subjective effects: They demonstrated that greater LSD occupancy of 5-HT2AR in the neocortex (the outer region of the brain involved in higher-order functions) was generally associated with stronger subjective effects, meaning participants generally reported more intense effects when more receptors were occupied by LSD. However, one participant continued to show high receptor occupancy even after their subjective effects had substantially diminished.

3. Brain blood flow and connectivity: LSD increased global cerebral blood flow by 19.3%, with the strongest increases observed in the occipital cortex and thalamus and more modest increases in the hippocampus and amygdala. Additionally, blood flow through the internal carotid arteries increased by 28% without substantial changes in artery diameter. LSD also decreased global brain connectivity across most of the neocortex, particularly in visual regions and posterior default mode network regions. These decreases in connectivity were associated with increases in brain blood flow and greater 5-HT2AR occupancy. In contrast, psilocybin increased global brain connectivity while decreasing cerebral blood flow, suggesting that these psychedelics have distinct effects on brain function.

What’s the impact?

This study is the first direct characterization of LSD’s receptor occupancy in the human brain and its relationship with subjective effects, brain connectivity, and blood flow. The authors also highlight a disconnect between LSD concentrations in the blood, receptor occupancy, and subjective effects that were not observed with psilocybin, suggesting differences in downstream or off-target mechanisms. These findings provide valuable insight into LSD’s pharmacological effects and may help guide future dosing in clinical populations while advancing our understanding of the neural mechanisms underlying its effects.

Access the original scientific publication here.

How The Brain Determines Controllability of an Outcome

Post by Shalana Atwell

The takeaway

Determining whether an outcome is within our control relies on combining decision confidence with learned expectations about control. The dorsomedial prefrontal cortex (dmPFC) tracks confidence in decisions and interacts with the dorsal raphe nucleus (DRN) to estimate the controllability of an outcome.

What's the science?

Understanding the level of control we have over an outcome is crucial for motivation, decision-making, and learning. While prior research demonstrates that beliefs about control alter learning strategies and affective states, how the brain establishes an estimation of environmental controllability and how that influences learning is poorly understood. 

Recently in Neuron, Liu and colleagues investigated how human participants construct dynamic estimates of environmental controllability, how post-decision confidence contributes to outcome attribution, and which prefrontal-subcortical pathways mediate these processes.

How did they do it?

The authors designed a behavioral task paired with high-resolution 7T functional magnetic resonance imaging (fMRI) to measure neural activity in small, deep brain areas like the DRN and midbrain dopaminergic (MBD). 

Healthy participants completed visual minigames varying in perceptual difficulty (10%, 40%, or 80% visible dots). On each trial, participants reported: 

1. Decision confidence on a continuous scale

2. Outcome attribution – whether feedback came from a “neutral committee” based on their performance or a “random committee” producing arbitrary outcomes

3. Overall environmental controllability estimates for the block

Blocks were pseudo-randomly assigned as controllable (90% neutral trials) or uncontrollable (10% neutral trials). Identical test trials were integrated throughout to assess how prior beliefs biased attribution under ambiguous conditions. Computational modeling was used to capture trial-by-trial updates in confidence, expectation, and control. To evaluate causality, the authors conducted a separate experiment applying continuous theta-burst stimulation (cTBS) – a form of TMS that transiently disrupts cortical activity – targeted at the dmPFC, a control area (vertex), or a sham condition. 

What did they find? 

Behaviorally, participants updated controllability estimates in response to task contingencies. High-confidence positive outcomes were consistently attributed to self-performance, whereas high-confidence negative outcomes were attributed to external randomness. Prior block experiences significantly biased how participants interpreted identical test trials. Neuroimaging and brain stimulation identified two distinct underlying functional networks: 

Controllability Estimation Circuit: 

• Neural activity in the dmPFC represented decision confidence, outcome attribution, and block-wise controllability estimates. 

• Updates to controllability estimates corresponded with activity within the DRN, accompanied by enhanced functional connectivity between dmPFC and DRN during major updates.

• Individual differences in dmPFC and DRN signal strength predicted overall attribution accuracy. 

Feedback modulation circuit:

• Reward prediction error signals in the MBD nuclei adjusted based on perceived control: MBD activity correlated positively with positive outcomes when attributed to self-performance, but negatively when attributed to random chance.

• Functional interaction between ventrolateral prefrontal-orbitofrontal cortex (47/12o) and MBD regulated these credit-assignment signals. 

Causal role of dmPFC: 

• Applying cTBS over the dmPFC significantly delayed controllability estimate updating across blocks and reduced attribution accuracy compared to control area stimulation or shams, without altering basic task performance or confidence reporting. 

What's the impact?

This study demonstrates that the brain relies on two distinct prefrontal-subcortical circuits to estimate environmental control and adjust downstream reinforcement learning, providing a mechanistic model for how beliefs shape outcome processing. These insights provide a neurobiological framework for understanding clinical conditions. Altered connectivity within these prefrontal-subcortical circuits may underlie psychiatric disorders characterized by distorted agency or learned helplessness, such as depression and anxiety. 

Access the original scientific publication here.

Brain Ripple Oscillations Synchronize Distant Regions During Memory

Post by Amanda Engstrom

The takeaway

Ripple oscillations are brief bursts of high-frequency brain activity associated with memory in the cortex. This study shows that when ripples occur simultaneously across different brain regions, neurons there fire together more strongly in a context-specific manner, and this coordination strengthens with mental effort.

What's the science?

Cognition and memory in the mammalian brain rely on effective communication between distinct brain regions. Still, the mechanisms that facilitate binding of neuronal activity across regions during a task remain unclear. High-frequency (~90-Hz) ripple oscillations were first identified as components of hippocampal sharp-wave ripples associated with memory consolidation, but subsequent research shows that they occur widely across the cortex, sometimes in the absence of sharp-wave activity, and that local firing coordinates with these ripples during behavior and memory retrieval. This week in Nature Neuroscience, Verzhbinsky and colleagues measure brain activity in humans during a complex memory task to determine whether ripple oscillations coordinate neuronal firing across brain regions that scales with cognitive demand.

How did they do it?

The authors analyzed an open-access dataset of 35 patients implanted with intracranial Behnke-Fried microwires from five brain regions: hippocampus, amygdala, ventromedial prefrontal cortex, anterior cingulate cortex, and pre-supplementary motor area. Electrodes recorded simultaneous individual neuron spikes and local field potential (LFP) readings while patients performed a modified Sternberg working memory (WM) test. The WM test had varying memory loads. First, in the encoding phase, they had to remember a set of images (1 for lighter load and 3 for greater load), then maintained the memory during a delay period in the maintenance phase (2.5–2.8 seconds), and identified whether a probe image was part of the original set during the retrieval phase.

The authors detected ripple oscillations from the LFP using standard amplitude and duration thresholds, then defined a "co-ripple" whenever two regions showed overlapping ripples for at least 25 milliseconds. They separately defined "co-firing" whenever two neurons in different regions spiked within that same 25-millisecond window. Using these metrics, they measured how often co-ripples and co-firing occurred across the five brain regions and how strongly individual neurons in different brain regions fired together within narrow time windows. They then compared these measurements across each phase of the task and between levels of task difficulty (lighter vs. greater load).

What did they find?

Through this analysis, the authors reached three main conclusions. First, whenever there was a co-ripple, even between distant brain regions (over 220 mm apart), neurons in those regions “co-fired” together roughly 30% more than usual. The cross-region coordination didn’t weaken with distance, and reflected precisely timed coordination between the brain regions, not just an increase in activity in both regions. This coordinated co-firing and co-ripple effect was observed in all three phases of the task. Second, they observed that when a participant was asked to remember three images, there were more cross-region ripples and neuronal co-firing compared to when they only had to remember one image. This shows that, at the level of individual neurons, ripple-driven co-firing between brain regions increases with mental load. Finally, they found that the pattern of cross-region co-firing evoked by a specific stimulus during encoding reappeared during retrieval of the same stimulus, and that during high-load trials, co-firing during co-ripples was significantly greater on trials with faster response times compared to slower ones. This demonstrates that co-ripple-mediated repetition (co-firing of the same neurons in each brain region) is associated with more efficient responses in a WM task, suggesting that ripples don’t just increase general neuronal activity, but carry context-specific content and coordinate better memory recall.

What's the impact?

This study is the first to analyze simultaneous single-unit firing and LFP across the brain during memory formation. They showed that ripple oscillations synchronize neuronal firing, coordinating long-range, stimulus-specific activation that increases with mental effort. This work lends support to the “interactive” over “hierarchical” model of cognition, providing evidence and a new method of studying this framework. Beyond immediate memory, establishing ripples as a demand-sensitive, context-carrying signal allows for further investigation or therapeutic targeting in memory loss disorders such as dementia.

Access the original scientific publication here.