Converting Microglia to Neurons Has Therapeutic Potential Following Stroke

October 24, 2023 by Leigh Christopher

The takeaway

In adult mammals, most neurons cannot proliferate, which means that neuronal loss following stroke and other brain injuries is irreversible. Microglia, the immune cells of the brain, maintain their capacity to divide and can be converted into neurons in mice with stroke, leading to improved neurological function.

What's the science?

Neuronal loss is one of the major pathological effects of stroke that contributes to disability and poor health outcomes. The mammalian brain maintains limited ability for adult neurogenesis, adding to the negative effects of neuronal loss due to stroke and other brain injuries. The conversion of other cell types to neurons at the site of injury therefore presents a therapeutic opportunity that could improve functional recovery. Some researchers have had success in converting astrocytes to neurons, leading to functional improvement. In the most common cause of stroke, however, both astrocytes and neurons are depleted at the site of injury while microglia and macrophages infiltrate the injured area, making them a better target for conversion following ischemic stroke. This week in PNAS, Irie and colleagues converted microglia and macrophages into neurons in the striatum of stroke mice using a single transcription factor and measured their functional improvements over time.

How did they do it?

The authors induced ischemic stroke using transient middle cerebral artery occlusion (tMCAO), and performed immunohistochemistry to analyze the lesioned area and the cell types located throughout the injured tissue. A week following stroke, they injected a virus carrying the NeuroD1 (ND1) transcription factor driven by a microglia-specific promoter into the injured brain area to convert infiltrating microglia and macrophages into neurons. Next, to determine whether the ND1-converted neurons became functionally integrated into the striatum, they used immunohistochemistry to stain striatal projection neurons in control and tMCAO mice and patch-clamp electrophysiology to record neuronal activity from these cells. To quantify how many microglia/macrophages were effectively transformed into neurons, they utilized a transgenic mouse line expressing cre-inducible diphtheria toxin receptor (DTR). By injecting a Cre virus with a microglia-specific promoter, they could permanently express DTR in microglia, and then count the number of DTR-expressing cells that became neurons at different time points. The authors then tested whether the conversion of microglia into neurons had functional outcomes on stroke recovery, by comparing multiple motor behaviors in injured and control mice. Finally, they ablated the ND1-converted neurons to examine whether these cells were responsible for functional improvements.

What did they find?

They showed that following stroke, there is a significant neuronal loss in the striatum, and that while astrocytes remain at the border of the lesioned area, microglia and macrophages infiltrate into the core of the lesion. Two weeks following the injection of their virally packaged transcription factor, they showed a reduction in the microglial population and an increase in neuronal markers, which means that cells at the lesion site were reprogrammed from a microglial identity into a neuronal one. They also showed that when microglia were depleted prior to injection of ND1, they no longer observed the increase in neuronal cells at the lesion site, indicating it is likely mostly microglia that are successfully converted into neurons. Using immunohistochemistry, they demonstrated that striatal projection neurons, which are largely depleted in the lesioned area following tMCAO, show recovery following ND1 transduction. Their ND1-transduced cells became positive for a striatal neuron marker and showed functional activity that mimicked that of native striatal neurons.

They next found that one week after labeling microglia and initiating their conversion into neurons, very few labeled cells expressed neuronal markers, indicating they hadn’t yet converted to neurons at this early stage. At the eight week timepoint, however, a large number of the permanently labeled DTR cells also expressed striatal neuron markers and showed anatomically relevant connections with other neurons. This means that their strategy to convert microglia at the lesion site into neurons that would be integrated into the native circuitry was successful. Finally, they showed that following the conversion of microglia to neurons at the lesion site one week post-injury, mice showed improvements in multiple motor behaviors impacted by stroke. Damaging ND1-converted neurons blocked these improvements, suggesting that these newly converted neurons were responsible for the functional improvements observed.

What's the impact?

This study is the first to show successful in vivo conversion of microglia into functional neurons following ischemic stroke in mice. This treatment, which led to improved neurological function in injured mice, demonstrates a promising therapeutic strategy for stroke and other injuries resulting in the loss of neurons.

Access the original scientific publication here.

Sleeping Participants Show Evidence of High-Level Cognitive Processing

October 24, 2023 by Leigh Christopher

Post by Lani Cupo

The takeaway

Participants respond to external stimuli during sleep, and responses are associated with cognitive activity, suggesting sleep is not a state of complete disconnection from the external world as previously believed.

What's the science?

Scientists have classically considered sleep a state with no reactivity to external stimuli, however, recent evidence suggests that stimuli can be processed on different cognitive levels during sleep, even to the point of learning new material. Nevertheless, few sleep studies attempt to elicit behavioral responses, as researchers consider them uniquely associated with wakefulness. This week in Nature Neuroscience, Türker and colleagues examined responsiveness to external stimuli during different sleep states, as well as lucid compared to non-lucid dreaming with an auditory decision task.

How did they do it?

The authors recruited two groups of participants: participants with narcolepsy who often lucid dream (N = 27), and healthy controls (N = 21). Participants napped in the laboratory during daytime hours while the authors spoke a combination of words and pseudowords. Participants were instructed to frown briefly three times in a row if they heard a pseudoword or smile briefly three times if they heard a real word. Facial muscle contractions were monitored with electromyography (EMG), and sleep/wake stage was assessed with a combination of electroencephalography (EEG) and electrooculography (EOG) which respectively measure electrical impulses from the brain and eye movements. After each nap, the participants reported if they dreamed, whether the dream was lucid, and whether they recalled performing the task.

In addition to the frequency of responses, response accuracy, and response rate on the task, the authors examined local brain activity associated with responses from EEG, and how well cognitive activity, measured with EEG, predicts responsiveness.

What did they find?

In terms of responsiveness, the authors found that participants could perform the task across almost any sleep state (except N3, deep sleep, in the healthy participants), meaning regardless of whether they were awake, in the lighter stages of sleep, or dreaming, they would respond to stimuli with smiles or frowns when they were presented and would not respond when no stimulus was presented. Interestingly, participants with narcolepsy responded more to stimuli across all sleep stages than healthy participants, including N3, and they reported lucid dreaming. As sleep deepened, the response rate decreased, although it increased slightly during rapid-eye movement (REM, dreaming sleep) in healthy participants. In participants with narcolepsy, the response rate increased greatly in non-lucid REM sleep and even further increased in lucid REM sleep. Examining accuracy, the authors found that all participants were more accurate than chance in responses, but healthy controls were more accurate than participants with narcolepsy, and increased depth of sleep was correlated with decreased performance. Regarding response time, as in wakefulness, during sleep participants were slower to respond to pseudowords than words, and participants were slower to respond overall while asleep than awake. Lucid dreaming was associated with significantly slower response times than non-lucid dreaming.

Using the EEG data, the authors found a signature of brain activity localized in frontal sites associated with responsiveness to stimuli across participants and sleep states. The authors computed markers of cognitive activity from all the electrophysiological data and compared these markers between responsive and nonresponsive trials, finding trials in which participants responded to the stimulus were associated with increased cognitive activity. The predictions were more accurate when tested on correct-only responses than incorrect-only responses, which provides evidence that the markers truly indicate cognitive activity, rather than merely motor activity. In contrast, lucid dreaming was associated with higher cognitive activity regardless of the response to stimuli.

What's the impact?

The results of this study demonstrate that humans maintain sensory connections to external stimuli while asleep and that they can process these external stimuli at a high cognitive level and physically respond to them. These results could precede further investigations of sleepers’ cognitive capacity and abilities, including the sleeping brain’s ability to learn new information.

Access the original scientific publication here

Do You Have a Voice Inside Your Head?

October 17, 2023 by Leigh Christopher

Post by Shireen Parimoo

Our inner auditory world

Inner speech - also known as the "voice inside our head" or an internal dialogue - is a part of our subjective experience of thinking that is often taken for granted. Much like mental visual imagery (often referred to as ‘the mind’s eye’), those of us who have experienced inner speech may find it difficult to imagine a time without this form of internal auditory imagery. So, why do we have inner speech at all? According to Vygotsky’s social origin theory of inner speech, speech is initially social in nature during childhood and its main purpose is communication, typically with parents. Over time, children develop egocentric or private speech where they verbalize their thoughts out loud, often while engaging in problem-solving activities. In late childhood, egocentric speech is internalized and transforms into inner speech that children can use flexibly for various cognitive functions. Inner speech is therefore separate from private speech, or “talking to ourselves out loud”, even though both are forms of language directed toward the self rather than toward others.

Theoretical perspectives vary in the extent to which inner speech is thought to differ from outer speech. Motor simulation theories state that inner speech shares all the same characteristics of outer speech production except for the actual articulation of speech. This view is supported by studies showing the activation of muscles that would be used to produce those words out loud. Alternatively, abstraction theories take the view that the processes underlying inner speech are independent of articulatory processes associated with outer speech, as inner speech first occurs with the activation of abstract linguistic concepts. This idea is supported by the fact that silent reading is faster than reading aloud and that articulatory suppression does not necessarily impact inner speech.

What are the components of inner speech?

Vygotsky originally differentiated inner speech from outer speech based on four main characteristics:

1. Word sense: words used in inner speech capture the overarching context and sentiments rather than precise meanings (e.g., the statement, “waves!” alone can capture the sense of awe at watching big waves while on the beach).

2. Agglutination: individual words are combined into complex new ideas while retaining the meaning of the individual words (e.g., help-less-ness).

3. Word senses flow from and influence each other during inner speech.

4. Predication: the absence of subjects from the contents of inner speech (e.g., “waves!” as opposed to “wow, I am so in awe of these huge waves!”).

Newer perspectives on inner speech have also included a distinction between inner speaking (e.g., self-talk) which is intentional and strategic in nature as the individual ‘produces’ the speech, and inner hearing (e.g., remembering something), which occurs passively as the individual ‘receives’ the contents of speech. Similarly, inner speech is now thought to include distinct speaker positions (e.g., voices of other people during an internal dialogue), rather than a self-referential perspective alone.

Inner speech is notoriously difficult to study because its study relies mainly on self-report and experience sampling measures. For example, the Descriptive Experience Sampling approach involves prompting individuals at random time points to note down what they were thinking at that moment, which is later followed by an interview that probes the contents of their thoughts in more detail. This method has been useful in providing insights into the phenomenological characteristics of inner speech, such as the distinction between inner speaking and inner hearing. In contrast, the Varieties of Inner Speech Questionnaire-Revised measures the quality of inner speech according to five dimensions:

1. Dialogicity, or the extent to which inner speech is conversational.

2. Condensation, or the use of abbreviations that are normally absent in overt speech (such as the “waves!” example above).

3. The degree to which other voices are present in the inner speech.

4. Critical or evaluative quality.

5. Positive or regulatory quality.

Is inner speech useful?

Different dimensions of inner speech are related to different aspects of the self. For example, the evaluative component is associated with lower self-esteem, depression, anxiety, and generally a negative self-concept. Individuals with a higher frequency of evaluative or critical inner speech are also likely to show perfectionistic and ruminative tendencies. On the other hand, higher rates of regulatory inner speech correspond to increased motivational self-talk and a positive self-concept, which may benefit individuals in performance-related domains like sports and public speaking. Indeed, inner speech is important for the formation and evolution of our self-concept. Thinking about the past and imagining the future can involve both inner speaking and inner hearing, which in turn, are related to the cognitive processes of metacognition and introspection that all contribute to our sense of self.

Inner speech also serves various cognitive functions. Positive or regulatory inner speech, for instance, likely supports the ability to regulate emotions as people process their feelings through an inner monologue. Relatedly, self-talk during sports boosts performance by increasing motivation and maintaining engagement with the actions required to play. Inner speech is also useful for planning actions (e.g., thinking through the steps required to complete a task), problem-solving (e.g., considering different outcomes), creative thinking, cognitive flexibility, and language learning. During development, children can use inner speech to build upon their knowledge base by adding newly acquired words and concepts through a process known as linguistic bootstrapping. Similarly, internal monitoring of dialogue is beneficial for perceptual discrimination and categorization when it involves processing abstract concepts.

However, not everyone has the experience of inner speech. Anendophasia is the lack of inner speech and is associated with lower verbal working memory, but only when participants are not allowed to process the words out loud. The use of inner speech is also not related to task-switching ability or perceptual discrimination performance, suggesting that it may not be necessary for cognitive functioning or that individuals with anendophasia may have developed compensatory strategies for carrying out these cognitive functions that otherwise rely on inner speech.

Lastly, patterns of inner speech are related to psychopathological symptoms. In autism spectrum conditions, there is a lower frequency of inner speech overall. This pattern is thought to underlie lower performance on executive functioning tasks such as planning and cognitive flexibility, as well as emotional regulation. On the other hand, individuals with schizophrenia who experience auditory hallucinations tend to report a higher frequency of intrusive inner speech which, in turn, is related to worse executive functioning because it interferes with cognitive processing. Thus, inner speech is not only important for helping us maintain our sense of self but also supports various cognitive functions and provides numerous benefits to aspects of our day-to-day lives.

The takeaway

What's the science?

How did they do it?

What did they find?

What's the impact?

The takeaway

What's the science?

How did they do it?

What did they find?

What's the impact?

Our inner auditory world

What are the components of inner speech?

Is inner speech useful?

References +