Ripples in the Hippocampus are Linked to Visual Memory Recall

Post by Anastasia Sares 

What's the science?

The hippocampus is the ‘seat’ of memory. From experiments with animals, scientists have been able to determine many aspects of its function, including the roles of its different cell layers and the growth of new cells over time. One interesting element of memory formation is called the sharp-wave ripple complex; a burst of synchronized neuronal activity that happens during memory consolidation and also during memory retrieval. However, animals can’t communicate their cognitive experience in detail, so we can’t be sure whether these retrieval-related ripples are accompanied by conscious memories. This week in Science, Norman and colleagues were able to connect these sharp-wave ripple complexes to reported memories in humans. 

How did they do it?

The authors used intracranial electroencephalography, a rare opportunity to measure human brain activity in patients with electrodes directly implanted into the brain tissue. These patients have the electrodes implanted for unrelated medical reasons, often to monitor brain activity before surgery. The participants in this experiment had electrodes in both the hippocampus and the visual cortex, so the sharp-wave ripples could be measured along with visual activity.

Participants saw a series of images, then were blindfolded and asked to recall as many of the images as possible (there was another task in between these learning and recall sessions to prevent people from mentally rehearsing what they had just seen). This is known as a “free recall” task. The entire time, the electrodes were recording brain activity and a microphone was recording what the participant said.

What did they find?

The rate of ripples was highest when participants were initially viewing the images and while at rest (presumably, at rest, memories are being consolidated). During the free recall, there was a very specific increase in the rate of ripple events about one second before the participant verbally recalled a memory. On top of this, images that produced a higher number of ripples when viewing them for the first time were more likely to be successfully recalled. The number of ripples elicited during this initial viewing stage predicted the participants' performance in the subsequent free recall stage.

The authors also identified sites in the visual cortex that had a preference for (i.e. responded to) certain types of images during viewing (for example, preferring faces over places). Then, during recall, when the participant reported an image, they observed that the ripples from the hippocampus were coupled with activity in the visual sites that were selective to that image. The authors interpreted this as a “reactivation” of the visual memory. They could even train an algorithm to predict the image based on the neural activity of these two areas alone. The authors argue that this is consistent with a two-stage recollection process, involving a fast subconscious stage (the ripple) and a slower conscious one, in which the brain uses the retrieved content to re-create an experience.

What's the impact?

Because this study was able to use human reports of memories along with precise measurements of neuronal activity, it presents a strong case that these sharp-wave ripple complexes from the hippocampus are indeed involved in conscious memory retrieval. More work is needed to explain exactly how the hippocampus interacts with the rest of the brain during this process, however, these findings represent an important step forward in understanding the role of sharp-wave ripples in visual memory.

Norman et al. Hippocampal sharp-wave ripples linked to visual episodic recollection in humans. Science (2019). Access the original scientific publication here.

High Blood Pressure Is Associated with Late-Life Brain Pathology

Post by Deborah Joye

What's the science?

High blood pressure, also known as hypertension, is a common health issue in adults that tends to get worse with age. Hypertension in midlife (between 40 and 70 years of age) is also associated with increased risk for brain pathology later in life, including cerebrovascular disease (disorders that affect blood supply to the brain) and Alzheimer’s disease. But how might changes in blood pressure result in late-life brain pathology, and at what age are people most sensitive to these changes? This week in The Lancet Neurology, Lane and colleagues study longitudinal blood pressure changes and late-life brain scans, revealing that increases in blood pressure from early adulthood into midlife are associated with increased white matter hyperintensity volume and smaller brain volumes in late-life (around age 70).

How did they do it?

The authors analyzed data from Insight 46, a neuroscience substudy of over 5000 individuals born throughout mainland Britain during one week in 1946. Over the course of the study, blood pressure measurements were collected at ages 36, 43, 53, 60-64, and 69 years. From 2015 through 2018, the authors recruited close to 500 participants of Insight 46 (mean age 70.7 years) to undergo brain-imaging MRI scans and determine possible neurological changes. The primary measures were white matter hyperintensity volume, a marker of vascular disease in the brain; presence of amyloid-beta, a hallmark pathology in Alzheimer’s disease; whole-brain and hippocampal volumes, to determine possible reductions in brain size; and tests of episodic memory, processing speed, and global cognition using the Preclinical Alzheimer Cognitive Composite.

What did they find?

The authors found that increased systolic and diastolic blood pressure were associated with greater white matter hyperintensity volume at all measured ages, with a stronger association after 53 years of age. Higher systolic blood pressure across time points was associated with smaller whole-brain volume, and greater increases in systolic blood pressure between 36 and 43 years old were associated with smaller hippocampal volume. Interestingly, blood pressure at any age was not associated with the presence of amyloid-beta, and there were no consistent associations between blood pressure and scores on cognitive tests.

What's the impact?

This study is the first to examine blood pressure at multiple timepoints and associate blood pressure changes with systematically measured brain pathologies and volumes. The authors show that early adulthood into midlife may present a sensitive period where rapid increases in blood pressure can affect brain pathologies such as white matter hyperintensities in later life. It should be noted that the participants of this study were exclusively white British participants broadly representative of the population of mainland Britain born in 1946; however, this may reduce generalizability to other ageing populations. These findings suggest that blood pressure management may need to begin at or before age 40 to prevent negative impacts on late-life brain health.

Lane et al., Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): an epidemiological study, The Lancet Neurology (2019). Access the original scientific publication here.

Antidepressant Efficacy Is Linked to Functional Connectivity of Brain Regions Involved in Cognitive Control

Post by Shireen Parimoo

What's the science?

Major depressive disorder (MDD) includes symptoms like difficulty concentrating, changes in sleep and appetite, and reductions in cognitive control. Many medications for depression exist, but the treatment process is often complicated, due to the heterogeneity in patients’ responses. Moreover, different classes of antidepressant medications have different neurobiological effects on the brain. Depression is associated with altered neural connectivity, including between brain regions involved in cognitive control like the dorsolateral prefrontal cortex (DLPFC) and the supramarginal gyrus (SMG). This altered connectivity is related to performance on tasks where inhibiting a response is needed, or flexible, adaptable behavior is required. Past research suggests that the functional connectivity of cognitive control regions may be related to the efficacy of different medications. This week in Biological Psychiatry, Tozzi and colleagues used functional magnetic resonance imaging (fMRI) during a clinical trial to examine the relationship between functional connectivity and the efficacy of different classes of antidepressants.

How did they do it?

Participants included 124 patients diagnosed with MDD and 59 healthy controls matched on age and sex. Patients were randomly assigned to receive one of three antidepressants: sertraline, venlafaxine-extended release, or escitalopram. All participants performed a go/no-go task (see below) while undergoing fMRI scanning during both a baseline session and a post-treatment session 8 weeks later. Patients were additionally assessed on the severity of their depressive symptoms at two different time points to determine whether their symptoms improved following the treatment. Those who showed greater than 50% improvement in symptom severity were classified as “responders”, and those who didn’t were classified as “non-responders”.

In the go/no-go task, participants were instructed to respond to the word “PRESS” by pressing a button when the word was shown in a green font (“go” trials) but withhold their response when the font was red (“no-go” trials). A comparison of brain activity during no-go and go trials revealed greater activation in cognitive control regions like the right SMG, the left orbitofrontal cortex (OFC), and the right middle temporal gyrus (MTG). The authors used generalized psychophysiological interaction analysis to examine the functional connectivity between these regions. They compared the findings across the patient and control groups, within participants at the different time points, and between responders and non-responders within each treatment group.  

What did they find?

Task performance was similar in MDD patients and healthy controls, and across the three treatment groups. Sertraline responders had higher connectivity between the SMG and the MTG and between the DLPFC and the SMG on no-go trials at baseline compared to healthy controls, whereas venlafaxine responders had lower connectivity between these pairs of regions. Sertraline responders also had greater connectivity between the DLPFC-SMG and the SMG-MTG compared to non-responders and higher connectivity between the cerebellum and anterior insula compared to non-responders and healthy controls. The enhanced connectivity in sertraline responders was associated with greater symptom improvement following treatment. The opposite pattern was observed among venlafaxine responders, who had reduced connectivity between these regions, which was related to a larger improvement in symptom severity. Thus, patients with higher connectivity between cognitive control regions responded better to sertraline, whereas those with lower connectivity responded more to venlafaxine. Functional connectivity in the escitalopram group did not differ from healthy controls at baseline and was not associated with response outcome. 

Functional connectivity at baseline was related to improvement in symptom severity in the sertraline and venlafaxine groups. Compared to baseline, sertraline responders showed a reduction in the connectivity between the left precentral gyrus and the left superior temporal gyrus at the post-treatment scan. In contrast, venlafaxine responders had increased connectivity between the left OFC and the brainstem, and between the left OFC and the left caudate nucleus. Importantly, functional connectivity changes among sertraline and venlafaxine responders were linked to symptom improvement and were only observed on no-go trials, suggesting that the antidepressants had a specific effect on the brain regions involved in response inhibition.

What's the impact?

This study is the first to show that individual differences in the connectivity of the cognitive control network during response inhibition are linked to the efficacy of different classes of antidepressant medications. These findings have important implications for how clinicians might prescribe antidepressants in the future and open the door for exciting new research on the development of targeted treatment plans for MDD patients.

Tozzi et al. Connectivity of the cognitive control network during response inhibition as a predictive and response biomarker in major depression: evidence from a randomized clinical trial. Biological Psychiatry (2019). Access the original scientific publication here.