People with autism often experience hypersensitivity to noise and other sensory input.
MIT neuroscientists have now identified two brain circuits that help tune out distracting sensory information, and they have found a way to reverse noise hypersensitivity in mice by boosting the activity of those circuits.
One of the circuits the researchers identified is involved in filtering noise, while the other exerts top-down control by allowing the brain to switch its attention between different sensory inputs.
The researchers showed that restoring the function of both circuits worked much better than treating either circuit alone.
This demonstrates the benefits of mapping and targeting multiple circuits involved in neurological disorders, says Michael Halassa, an assistant professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research.
“We think this work has the potential to transform how we think about neurological and psychiatric disorders, [so that we see them] as a combination of circuit deficits,” says Halassa, the senior author of the study.
“The way we should approach these brain disorders is to map, to the best of our ability, what combination of deficits are there, and then go after that combination.”
MIT postdoc Miho Nakajima and research scientist L. Ian Schmitt are the lead authors of the paper, which appears in Neuron on Oct. 21. Guoping Feng, the James W. and Patricia Poitras Professor of Neuroscience and a member of the McGovern Institute, is also an author of the paper.
Many gene variants have been linked with autism, but most patients have very few, if any, of those variants. One of those genes is ptchd1, which is mutated in about 1 percent of people with autism. In a 2016 study, Halassa and Feng found that during development this gene is primarily expressed in a part of the thalamus called the thalamic reticular nucleus (TRN).
That study revealed that neurons of the TRN help the brain to adjust to changes in sensory input, such as noise level or brightness.
In mice with ptchd1 missing, TRN neurons fire too fast, and they can’t adjust when noise levels change. This prevents the TRN from performing its usual sensory filtering function, Halassa says.
“Neurons that are there to filter out noise, or adjust the overall level of activity, are not adapting. Without the ability to fine-tune the overall level of activity, you can get overwhelmed very easily,” he says.
In the 2016 study, the researchers also found that they could restore some of the mice’s noise filtering ability by treating them with a drug called EBIO that activates neurons’ potassium channels.
EBIO has harmful cardiac side effects so likely could not be used in human patients, but other drugs that boost TRN activity may have a similar beneficial effect on hypersensitivity, Halassa says.
In the new Neuron paper, the researchers delved more deeply into the effects of ptchd1, which is also expressed in the prefrontal cortex.
To explore whether the prefrontal cortex might play a role in the animals’ hypersensitivity, the researchers used a task in which mice have to distinguish between three different tones, presented with varying amounts of background noise.
Normal mice can learn to use a cue that alerts them whenever the noise level is going to be higher, improving their overall performance on the task.
A similar phenomenon is seen in humans, who can adjust better to noisier environments when they have some advance warning, Halassa says. However, mice with the ptchd1 mutation were unable to use these cues to improve their performance, even when their TRN deficit was treated with EBIO.
This suggested that another brain circuit must be playing a role in the animals’ ability to filter out distracting noise.
To test the possibility that this circuit is located in the prefrontal cortex, the researchers recorded from neurons in that region while mice lacking ptch1 performed the task. They found that neuronal activity died out much faster in these mice than in the prefrontal cortex of normal mice.
That led the researchers to test another drug, known as modafinil, which is FDA-approved to treat narcolepsy and is sometimes prescribed to improve memory and attention.
MIT neuroscientists have identified two brain circuits that help tune out distracting sensory information. The image is credited to MIT News.
The researchers found that when they treated mice missing ptchd1 with both modafinil and EBIO, their hypersensitivity disappeared, and their performance on the task was the same as that of normal mice.
This successful reversal of symptoms suggests that the mice missing ptchd1 experience a combination of circuit deficits that each contribute differently to noise hypersensitivity.
One circuit filters noise, while the other helps to control noise filtering based on external cues. Ptch1 mutations affect both circuits, in different ways that can be treated with different drugs.
Both of those circuits could also be affected by other genetic mutations that have been linked to autism and other neurological disorders, Halassa says. T
argeting those circuits, rather than specific genetic mutations, may offer a more effective way to treat such disorders, he says.
“These circuits are important for moving things around the brain — sensory information, cognitive information, working memory,” he says. “We’re trying to reverse-engineer circuit operations in the service of figuring out what to do about a real human disease.”
He now plans to study circuit-level disturbances that arise in schizophrenia. That disorder affects circuits involving cognitive processes such as inference — the ability to draw conclusions from available information.
Funding: The research was funded by the Simons Center for the Social Brain at MIT, the Stanley Center for Psychiatric Research at the Broad Institute, the McGovern Institute for Brain Research at MIT, the Pew Foundation, the Human Frontiers Science Program, the National Institutes of Health, the James and Patricia Poitras Center for Psychiatric Disorders Research at MIT, a Japan Society for the Promotion of Science Fellowship, and a National Alliance for the Research of Schizophrenia and Depression Young Investigator Award.
Auditory sensitivities are common among people with autism spectrum disorder diagnoses (ASD). As underlying factors are unknown, we examined whether ASD adults (NASD = 33; NTypically Developing = 31; 25–45 years; IQ > 70): (1) habituated slower to auditory stimuli; (2) had lower auditory detection thresholds; and (3) whether these mechanisms related to self-reported auditory sensitivities.
Two auditory stimuli (tone, siren) were repeated, whilst skin conductance responses were recorded to measure habituation. Detection thresholds were measured by stepwise reductions in tone volume. We found no evidence in favor of our hypotheses, but ASD adults did rate the auditory stimuli as more arousing. Based on explorative analyses, we argue that studying the strength of physiological responses to auditory stimuli is needed to understand auditory sensitivities.
It is well known that many people with an autism spectrum disorder (ASD) diagnosis experience sensory sensitivities. Sensory sensitivities were already reported in the first descriptions of autism by Leo Kanner (Kanner 1943). Nowadays, sensory sensitivities are included as a criterion for the classification of ASD in the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5; APA 2013).
Even though someone can meet the criteria for an ASD classification without meeting the sensory sensitivity criterion, the reported prevalence of sensory sensitivities in people with ASD is high (60 to 96%; for review see Schauder and Benneto 2016).
Besides this relatively high prevalence, sensory sensitivities are recently described to be related to other characteristics of ASD. For instance, sensory sensitivity has been related to social difficulties and the presence of more repetitive behavior (e.g., Deschrijver et al. 2017; for review see Jiujias et al. 2017).
These findings make it even more crucial to examine possible underlying mechanisms of sensory sensitivity in ASD, as this might provide us with information we need to develop successful treatments for sensory sensitivities that are perceived as problematic by those with ASD. In the current paper, we will focus on two possible underlying factors that might play a role in auditory sensitivity in ASD adults, namely habituation and detection thresholds.
One of the most commonly reported sensory sensitivities in ASD is sensitivity to sounds (Baranek et al. 2006; Haesen et al. 2011; Jones et al. 2009; Kern et al. 2006; Kientz and Dunn 1997; Tomchek and Dunn 2007).
Studies, clinical observations, and autobiographies show that people with ASD perceive certain sounds as more intense. For instance, certain frequencies can be extremely annoying (e.g., computer fan), loud noises can be painful (e.g., fog horn) and combined sounds such as multiple people talking to each other at once can be overwhelming (e.g., for review see Elwin et al. 2012; Robertson et al. 2015).
Moreover, some ASD adults expressed that they were not able to get used to certain sensory stimuli as other people without ASD seemed to do (Robertson et al. 2015). This description is similar to what experimental studies on learning call “habituation”. Habituation refers to response distinction after a stimulus has repeatedly been presented (Houtveen et al. 2001).
In other words, when a stimulus is repeated multiple times the physiological response to the stimulus slowly decreases or will get extinct. Habituation is an automatic form of learning in which the body learns not to physiologically respond to stimuli that are familiar, predictable or not relevant anymore (McDiarmid et al. 2017).
The habituation description of people with ASD (Robertson et al. 2015) is in line with a hypothesis that states that some people with ASD might not or only slowly habituate to sensory stimuli (e.g., Hutt et al. 1964; Schoen et al. 2008; for review see; McDiarmid et al. 2017). These habituation difficulties to certain stimuli would lead to a “sensory overload” and hyper-reactions, which is commonly seen in people with ASD.
So far, studies on habituation in people with ASD show mixed results (for reviews see Lydon et al. 2016; McDiarmid et al. 2017). Studies use different measurements and stimuli to examine habituation, which might be a reason why mixed results are found (McDiarmid et al. 2017). For instance, habituation can be measured by determining the acoustic startle reflex and/or event-related potentials (ERP), by measuring electrodermal activity (EDA), or by means of functional magnetic resonance imaging (fMRI; McDiarmid et al. 2017).
Studies using fMRI to study habituation in people with ASD have, so far, only focused on social stimuli (McDiarmid al. 2017).
These studies (n = 5) showed that the amygdala of people with ASD habituated slower to faces compared to TD people (McDiarmid et al. 2017). Studies that have examined habituation to auditory stimuli (n = 7) focused mainly on children with ASD (Lydon et al. 2016) and all used EDA as measure for habituation. Results showed that children with ASD habituated either slower (e.g., Barry and James 1988; James and Barry 1984; Schoen et al. 2008; Stevens and Gruzelier 1984), or faster (e.g., Schoen et al. 2008), or there was no difference in habituation compared to a typical developing (TD) group (e.g., Chang et al. 2012; McCormick et al. 2014; van Engeland 1984).
A study that both found slower and faster habituation in the ASD group (Schoen et al. 2008) suggested that it depended on the baseline skin conductance levels (SCL) of participants whether children with ASD habituated slower or faster. ASD children with high baseline SCL tended to habituate slower and ASD children with low baseline SCL tended to habituate faster. Baseline SCL is considered a proxy for sympathetic nerve activity (Dawson et al. 2007), with a higher SCL suggesting more physiological arousal.
The only auditory habituation study that focused on adults showed that the ASD group did not differ from the TD group on habituation to a simple tone (e.g., Zahn et al. 1987). This study, however, had a small number of participants in each group (nASD =13, nTD = 19, nschizophrenia = 13). Given that auditory sensitivity persists into adulthood (e.g., Robertson et al. 2015), more knowledge on habituation in ASD adults is required.
Besides possible habituation abnormalities, lower auditory detection thresholds might also play a role in auditory sensitivities in people with ASD as they often report to hear sound sooner than TD people (e.g., Elwin et al. 2012; Talay-Ongan and; Wood 2000). Moreover, the enhanced perceptual functioning model (EPF) of Mottron and Burack (2001, 2006) suggests that in people with ASD information processing systems that are involved in detection, categorization, and discrimination of perceptual stimuli (a.k.a., visual and auditory stimuli) are enhanced (Mottron and Burack 2001; Mottron et al. 2006).
This means that people with ASD will perform superior on tasks that are designed to measure these variables. Previous research showed indeed that adolescents and young adults with ASD performed superior compared to a TD group on an auditory discrimination and categorization task (e.g., Bonnel et al. 2003; Mottron et al. 2006). People with ASD also seemed to be faster in detecting a visual target and are more accurate in detecting hierarchical auditory stimuli (Mottron et al. 2006).
There is also evidence for the opposite, namely that people with ASD are less able to detect a sensory stimulus. For instance, it is suggested that the more ASD traits one has, the higher their detection threshold is for tactile stimuli (e.g., Tavasolli et al. 2016). Also with regard to odor detection thresholds it seems that ASD children were less able to detect the stimuli than TD children did (Dudova et al. 2011).
An auditory detection threshold refers to a minimum level of sound that is detectable for a person. Humans are able to perceive frequencies in the range from 20 to 20,000 Hz, and are most sensitive for auditory stimuli in the range from 2000 to 4000 Hz (Goldstein 2010), which is precisely the range that is important for understanding speech (Goldstein 2010).
Sounds with an amplitude above 120–140 decibel (dB) are suggested to cause pain and be potentially damaging to the auditory system (Newman 1972). To our knowledge, studies on auditory detection thresholds in people with ASD are scarce. One small study showed that 11 ASD children did not differ from 11 children without ASD on auditory detection thresholds regardless of frequency (i.e., 0.25 kHz, 0.5 kHz, 1 kHz, 4 kHz and 8 kHz; Khalfa et al. 2004).
In another small study, with only 12 young adults in each group, it was mentioned that the ASD participants did not have lower auditory thresholds compared to the TD participants (Bonnel et al. 2003).
Therefore, in the current study, we will include a much larger ASD adult sample while we follow the method of Khalfa et al. (2004).
In this study, we will test three hypotheses. We hypothesize that (1) ASD adults habituate slower than TD adults; (2) ASD adults have lower auditory detection thresholds than TD adults; and (3) habituation and auditory detection threshold are underlying factors of the often reported auditory sensitivities.
Based on this third hypothesis, we expect a negative correlation of habituation as well as auditory detection threshold with self-reported auditory sensitivity. Additionally, we explored the hypothesis of Schoen et al. (2008) that baseline arousal [as indicated by baseline SCL and heart rate variability (HRV)] is related to habituation and auditory detection thresholds.
Anne Trafton – MIT
The image is credited to MIT News.
Original Research: Closed access
“Combinatorial Targeting of Distributed Forebrain Networks Reverses Noise Hypersensitivity in a Model of Autism Spectrum Disorder”. Michael Halassa et al.