Musical Memory in Autism and Williams Syndrome

Post by Anastasia Sares

What's the science?

Music has been called a “human universal,” as its presence has been found in almost every known culture. While musical instruments have an important place, the human voice is one of the most primal music-makers. In fact, people tend to remember melodies better when they are sung than when they are played on instruments: this is sometimes called the voice advantage. The voice advantage has been observed in neurotypical populations, but until now it was uncertain whether it extended to people with Autism or Williams syndrome. One of the primary diagnostic criteria for Autism is problems with communication, while people with Williams syndrome are often hyper-communicative. This week in Autism Research, Weiss and colleagues showed that, despite these differences in response to social cues in general, people with Autism and Williams syndrome still have a voice advantage for remembering melodies, just like neurotypicals.

How did they do it?

The authors performed a simple memory test in three groups of people: one typically developing group, one group with Autism, and another group with Williams syndrome. The groups were matched for mental age, so that their memory for the melodies could be compared. Each group was exposed to a variety of melodies, some played on the piano, some played on marimba, and some performed vocally. They were asked to rate how much they liked each melody. After the initial exposure task, they were exposed to more melodies, some repeated and some new, and asked if they remembered them.

What did they find?

The authors compared the “hit rate” (the number of old melodies correctly identified as old) with the “false alarm rate” (the number of new melodies incorrectly identified as old). This technique is part of signal detection theory, which accounts for some people’s tendency to say they remembered something even when they didn’t. As long as the hit rate was greater than the false alarm rate, the researchers would assume that the participants were not answering randomly and that their participants did have some memory of the melodies. All the groups had more hits than false alarms.

However, the difference between hits and false alarms was greater for vocal melodies, an indication of the voice advantage. This was present in all of the groups, not just the typically developing group.

What's the impact?

When researching conditions like Autism and Williams syndrome, it’s important to acknowledge what skills are intact, instead of just looking for differences. This research shows that the voice advantage generalizes to non-neurotypical populations. It also suggests that it might be possible to use vocal music therapeutically in these groups, especially in Autism to help with verbal communication.

Weiss et al. Enhanced Memory for Vocal Melodies in Autism Spectrum Disorder and Williams Syndrome. Autism Research (2021). Access the original scientific publication here.

Stroke Disrupts Brain Network Dynamics

Post by Anna Cranston

What's the science?

Post-stroke cognitive decline is described as the onset of memory loss and cognitive dysfunction following an ischemic stroke. However, smaller infarcts can also lead to milder cognitive deficits such as impaired attention and the inability to concentrate. Smaller infarcts can also occur in brain regions not typically associated with cognitive function. The underlying physiology of this phenomenon, known as post-stroke acute dysexecutive syndrome (PSADES), remains unclear. This week in PNAS, Marsh and colleagues used magnetoencephalography (MEG) to investigate differential activation patterns following minor strokes in patients exhibiting PSADES to determine the underlying pathophysiology.   

How did they do it?

The authors recruited a group of patients who had recently been hospitalized with MRI evidence of a small acute ischemic stroke. Due to the small size of the lesion, patients appeared almost normal, without any problems moving or speaking. Prior to study participation, all patients underwent comprehensive neurological examinations and cognitive screening using the Montreal Cognitive Assessment (MoCA). The authors also selected age-matched individuals with no prior history of stroke as a control group. They used MEG, a technique used to map brain activity, via the magnetic fields the brain generates, to determine differences in cerebral activation patterns between stroke and control groups. They recorded MEG activity during the completion of a visual comprehension task involving picture-word matching. Analysis of MEG activity at selected time points, known as epochs, were analyzed using a specific time-frequency analysis known as cluster-based permutation. The authors also used source localization analysis to map the spatiotemporal activity of each patient’s brain and then targeted their analysis to recorded activity from the occipital lobe, fusiform gyrus, and lateral temporal lobe, given their importance in visual recognition and language processing.    

What did they find?

The authors found that minor stroke patients scored significantly lower on cognitive tests compared to control patients. In addition, they displayed reaction times twice as long as those of controls during the visual comprehension tasks. Although differences in reaction times may seem subtle, they are clinically significant in the context of being able to respond or shift attention back and forth quickly during conversations. Using MEG analysis, the authors also identified group differences in activation patterns within the visual cortex, fusiform gyrus, and lateral temporal lobe. They found that stroke patients exhibited a significantly different activation pattern in the brain in response to visual stimuli. Specifically, stroke patients exhibited brain responses of smaller amplitude with less temporally distinct activation peaks following a minor infarct. These differences in activation were found to be more prominent in the fusiform gyrus and lateral temporal lobe.

Of particular interest, each of the stroke patients tested in the study exhibited small acute infarcts in regions of the brain not typically associated with cognitive dysfunction. The activation patterns in these non-cognitive regions suggest that a disconnect in the processing loops in the brain, or network dysfunction, may be responsible for the observed PSADES symptoms in the stroke patient group. The authors also found that while control patients were able to modulate the amplitude of their brain activation in response to words, stroke patients displayed a consistently low amplitude for all stimuli. These differences remained for up to 6 months later in stroke patients, which may help to explain why patients demonstrate cognitive fatigue in the initial months after stroke.

What's the impact?

This study found that patients with minor strokes had cognitive deficits and slowed reaction times that corresponded to abnormal activation patterns of brain activity, independent of stroke location. The authors suggest that a dysregulation of brain network dynamics may be responsible for the observed long-term deficits that occur in PSADES following minor strokes. These findings highlight the importance of brain network dynamics, even in simple tasks, such as word processing. This work provides the basis for future studies to investigate the exact underpinnings of PSADES, with the hope that this can eventually be targeted for therapeutic purposes.

Marsh et al. Poststroke acute dysexecutive syndrome, a disorder resulting from minor stroke due to disruption of network dynamics. PNAS (2020). Access the original scientific publication here.

The ‘Global Workspace’ of the Human Brain

Post by Lani Cupo

What's the science?

Previous research suggests that there are brain regions central to controlling the flow of information throughout the brain. This flow of information allows for the orchestration of human behaviour and has been proposed to be essential for consciousness. These brain regions can be thought of as a ‘global workspace’ that integrates lower-level sensory information and memory before broadcasting back to the whole brain. However, which brain regions comprise this ‘global workspace’ of the brain remain unclear. This week in Nature Human Behaviour, Deco and colleagues identified these brain regions using a large functional magnetic resonance imaging (fMRI) data set, examining which areas were involved while participants executed seven different behavioural tasks versus during rest.  

How did they do it?

The authors included fMRI scans from 1,003 participants, including both men and women. The scans comprised the resting brain, as well as seven behavioural tasks assessing working memory, motor skills, reward processing, language processing, social cognition, emotional processing, and relational processing. The authors’ first step was to compute information flow between regions by mathematically modelling (normalized directed transfer entropy framework) how brain activity in a given region is causally related to other areas over time. Specifically, they sought to establish the hierarchy of information flow, including the identification of the top-level regions with a lot of incoming information and communication between them but relatively little outgoing information. This allowed them to locate regions that orchestrate brain function across tasks. They identified areas in the so-called ‘functional rich club’ (i.e., brain regions highly connected to one another) that were involved in this high-level processing role across all the tasks and during rest. Next, they created a computational model of the whole brain fitting the information flow between brain regions. To confirm they had identified core functional rich club areas central to processing, they removed the identified brain regions from the computational model, examining the extent to which the model was altered when each region was removed. The more information flow was altered after removing a region, the greater this brain region’s executive functioning proved to be.

What did they find?

Eight brain areas were identified within the central core of those regions organizing behaviour. These included the left precuneus, left nucleus accumbens, left putamen, left posterior cingulate cortex, right hippocampus, right amygdala, and left and right isthmus cingulate. These brain regions comprise both areas in the cerebral cortex, such as the precuneus, and deeper subcortical structures, like the amygdala. The authors suggest that these regions in the global workspace are ideally located to integrate information from the senses, long-term memory, value judgments, and attention devoted to controlling behavior. By simulating lesions to these areas, they demonstrated that removing all of the identified functional rich club areas impacted information flow significantly more than when they removed brain areas outside of the functional rich club.

What's the impact?

This study provides evidence that the brain is organized in a hierarchy, with certain lower-level regions performing low-level processing while other higher-order regions integrate information from multiple sources, orchestrating human behavior and consciousness. By identifying the set of regions that fulfill high-level processing roles in the brain, the authors helped to characterize the structure and direction of information flow in the brain while quantifying the global workspace. 

Deco et al. Revisiting the Global Workspace Orchestrating the Hierarchical Organization of the Human Brain. Nature Human Behaviour (2021). Access the original scientific publication here.