Noise Correlations Study for Dyslexia
Recruiting in Palo Alto (17 mi)
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Brown University
Must not be taking: Neuroleptics
Disqualifiers: Claustrophobia, Color blindness, Stroke, others
No Placebo Group
Trial Summary
What is the purpose of this trial?A fundamental problem in neuroscience is how the brain computes with noisy neurons. An advantage of population codes is that downstream neurons can pool across multiple neurons to reduce the impact of noise. However, this benefit depends on the noise associated with each neuron being independent. Noise correlations refer to the covariance of noise between pairs of neurons, and such correlations can limit the advantages gained from pooling across large neural populations. Indeed, a large body of theoretical work argues that positive noise correlations between similarly tuned neurons reduce the representational capacity of neural populations and are thus detrimental to neural computation. Despite this apparent disadvantage, such noise correlations are observed across many different brain regions, persist even in well-trained subjects, and are dynamically altered in complex tasks. The investigators have advanced the hypothesis that noise correlations may be a neural mechanism for reducing the dimensionality of learning problems. The viability of this hypothesis has been demonstrated in neural network simulations where noise correlations, when embedded in populations with fixed signal-to-noise ratio, enhance the speed and robustness of learning. Here the investigators aim to empirically test this hypothesis, using a combination of computational modeling, fMRI and pupillometry. Establishing a link between noise correlations and learning would open the door to an investigation into how brains navigate a tradeoff between representational capacity and the speed of learning.
Will I have to stop taking my current medications?
The trial excludes participants taking neuroleptic medications, so if you are on these, you would need to stop. For other medications, the protocol does not specify any requirements.
What data supports the effectiveness of the treatment Dynamic perceptual discrimination task for dyslexia?
Research shows that children with dyslexia can improve their brain connectivity and reading skills after receiving targeted instructional treatment, which suggests that specific training tasks can help rewire the brain to better handle reading challenges.
12345How does the Dynamic perceptual discrimination task treatment differ from other treatments for dyslexia?
The Dynamic perceptual discrimination task is unique because it focuses on improving the ability to filter out irrelevant noise, which is a specific challenge for individuals with dyslexia. This approach targets the underlying sensory processing deficits, particularly in noise exclusion, rather than just addressing reading skills directly.
678910Eligibility Criteria
This trial is for individuals with dyslexia or tinnitus. Specific eligibility criteria are not provided, but typically participants would need to be in good health and able to perform the tasks required by the study.Inclusion Criteria
My vision is normal or can be corrected with glasses or contacts.
I am over 18 years old.
Exclusion Criteria
Conditions contraindicated for MRI such as surgical implant that is not MRI compatible, metal fragments in the body, tattoo with metallic ink
Claustrophobia
History of drug abuse and/or alcoholism
+5 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Experimental Task
Participants engage in a dynamic perceptual discrimination task involving motion and color information, requiring adaptation to intra-dimensional shifts.
1 week
1 visit (in-person)
Scanning and Analysis
Participants undergo fMRI scanning to measure noise correlations and pupillometry as a proxy for neuromodulatory signaling.
6 months
Follow-up
Participants are monitored for safety and effectiveness after the experimental tasks and scanning sessions.
4 weeks
Participant Groups
The study investigates how 'noise correlations' between neurons affect learning. Participants will undergo a dynamic perceptual discrimination task while their brain activity is monitored using fMRI and pupillometry techniques.
1Treatment groups
Experimental Treatment
Group I: Dynamic perceptual discrimination taskExperimental Treatment2 Interventions
The task featured two task conditions, each of which required the integration of information from both stimulus dimensions. In each condition, participants viewed a stimulus containing motion and color information and were required to specify one of two possible responses. Within each condition, rules and the response mapping changed occasionally, but always by changing on a fixed feature dimension (ie. rightward/purple, leftward/orange). These uncued intra-dimensional shifts involved translational shifts in the learning boundary, requiring them to adapt their decision making within a familiar dimension. These shifts compelled participants to continuously adjust their learning strategies by focusing on the most relevant feature dimension.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Brown UniversityProvidence, RI
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Who Is Running the Clinical Trial?
Brown UniversityLead Sponsor
National Institute of General Medical Sciences (NIGMS)Collaborator
References
Abnormal fMRI Connectivity in Children with Dyslexia During a Phoneme Task: Before But Not After Treatment . [2022]Brains of 18 children with dyslexia (5 girls, 13 boys) and 21 and without dyslexia (8 girls, 13 boys) were scanned before and after the children with dyslexia received instructional treatment. Both at Time 1 and Time 2 all children performed an fMRI phoneme mapping task during brain scanning-deciding whether letter(s) in pair of pronounceable nonwords could stand for the same sound. Results were analyzed with a seed point correlational method for functional connectivity from four seed points based on prior studies: inferior frontal gyrus, middle frontal gyrus, the occipital region, and cerebellum. At Time 1 before treatment, a significant difference in fMRI connectivity occurred between children with dyslexia and normal reading controls in the left inferior frontal gyrus and its correlations with right and left middle frontal gyrus, right and left supplemental motor area, left precentral gyrus, and right superior frontal gyrus. There were no significant differences for the seed regions placed in the middle frontal gyrus, occipital gyrus or cerebellum. Children with dyslexia had greater functional connectivity from the left inferior frontal gyrus seed point to the right inferior frontal gyrus than did the children without dyslexia. Compared to adults with and without dyslexia who differed in bilateral connectivity from left inferior frontal gyrus on the same task, the children with and without dyslexia differed in left side connectivity from left inferior frontal gyrus. At Time 2 after treatment, the children with dyslexia, who had participated in a three-week instructional program that provided explicit instruction in linguistic awareness, alphabetic principle (taught in a way to maximize temporal contiguity of grapheme-phoneme associations), decoding and spelling, and a writers' workshop, did not differ from the children without dyslexia in any of the clusters in the group difference map identifying differences between dyslexics and good readers, showing that functional connectivity (and not just regions of interest) may normalize following instructional treatment.
Dyslexia and the failure to form a perceptual anchor. [2022]In a large subgroup of dyslexic individuals (D-LDs), reading difficulties are part of a broader learning and language disability. Recent studies indicate that D-LDs perform poorly in many psychoacoustic tasks compared with individuals with normal reading ability. We found that D-LDs perform as well as normal readers in speech perception in noise and in a difficult tone comparison task. However, their performance did not improve when these same tasks were performed with a smaller stimulus set. In contrast to normal readers, they did not benefit from stimulus-specific repetitions, suggesting that they have difficulties forming perceptual anchors. These findings are inconsistent with previously suggested static models of dyslexia. Instead, we propose that D-LDs' core deficit is a general difficulty in dynamically constructing stimulus-specific predictions, deriving from deficient stimulus-specific adaptation mechanisms. This hypothesis provides a direct link between D-LDs' high-level difficulties and mechanisms at the level of specific neuronal circuits.
Sound localization and word discrimination in reverberant environment in children with developmental dyslexia. [2015]Compare if localization of sounds and words discrimination in reverberant environment is different between children with dyslexia and controls.
Understanding the biological basis of dyslexia at a neural systems level. [2020]We examined the naming speed performance of 18 typically achieving and 16 dyslexic adults while simultaneously recording eye movements, articulations and fMRI data. Naming speed tasks, which require participants to name a list of letters or objects, have been proposed as a proxy for reading and are thought to recruit similar reading networks in the left hemisphere of the brain as more complex reading tasks. We employed letter and object naming speed tasks, with task manipulations to make the stimuli more or less phonologically and/or visually similar. Compared to typically achieving readers, readers with dyslexia had a poorer behavioural naming speed task performance, longer fixation durations, more regressions and increased activation in areas of the reading network in the left-hemisphere. Whereas increased network activation was positively associated with performance in dyslexics, it was negatively related to performance in typically achieving readers. Readers with dyslexia had greater bilateral activation and recruited additional regions involved with memory, namely the amygdala and hippocampus; in contrast, the typically achieving readers additionally activated the dorsolateral prefrontal cortex. Areas within the reading network were differentially activated by stimulus manipulations to the naming speed tasks. There was less efficient naming speed behavioural performance, longer fixation durations, more regressions and increased neural activity when letter stimuli were both phonologically and visually similar. Discussion focuses on the differences in activation within the reading network, how they are related to behavioural task differences, and how progress in furthering the understanding of the relationship between behavioural performance and brain activity can change the overall trajectories of children with reading difficulties by contributing to both early identification and remediation processes.
Neural changes following remediation in adult developmental dyslexia. [2022]Brain imaging studies have explored the neural mechanisms of recovery in adults following acquired disorders and, more recently, childhood developmental disorders. However, the neural systems underlying adult rehabilitation of neurobiologically based learning disabilities remain unexplored, despite their high incidence. Here we characterize the differences in brain activity during a phonological manipulation task before and after a behavioral intervention in adults with developmental dyslexia. Phonologically targeted training resulted in performance improvements in tutored compared to nontutored dyslexics, and these gains were associated with signal increases in bilateral parietal and right perisylvian cortices. Our findings demonstrate that behavioral changes in tutored dyslexic adults are associated with (1) increased activity in those left-hemisphere regions engaged by normal readers and (2) compensatory activity in the right perisylvian cortex. Hence, behavioral plasticity in adult developmental dyslexia involves two distinct neural mechanisms, each of which has previously been observed either for remediation of developmental or acquired reading disorders.
The influence of contrast on coherent motion processing in dyslexia. [2022]The aim of the experiments was to investigate how manipulating the contrast of the signal and noise dots in a random dot kinematogram (RDK), influenced on motion coherence thresholds in adults with dyslexia. In the first of two experiments, coherent motion thresholds were measured when the contrasts of the signal and noise dots in an RDK were manipulated. A significantly greater processing benefit was found for the group with dyslexia than a control group when the signal dots were of higher contrast than the noise dots. However, a significant processing disadvantage was found for the group with dyslexia relative to the control group when the signal dots were of lower contrast than the noise dots. These findings were interpreted as supporting evidence for the noise exclusion hypothesis of dyslexia. In Experiment 2, the effect on coherent motion thresholds of presenting a cue that alerted observers to which stimuli, high or low contrast contained the signals dots was investigated. When the cue directed attention to low contrast signal dots presented in high contrast noise, coherent motion thresholds were only enhanced for the group with dyslexia. This manipulation produced equivalent coherent motion thresholds in the reader groups. In other conditions, the group with dyslexia had significantly higher coherent motion thresholds than the control group. It was concluded that adults with dyslexia who show evidence of a coherent motion deficit (37% of the dyslexia group in each experiment), have a specific difficulty in noise exclusion. This appears to occur as consequence of a sensory processing deficit in the magnocellular or dorsal stream.
Deficits in perceptual noise exclusion in developmental dyslexia. [2022]We evaluated signal-noise discrimination in children with and without dyslexia, using magnocellular and parvocellular visual stimuli presented either with or without high noise. Dyslexic children had elevated contrast thresholds when stimuli of either type were presented in high noise, but performed as well as non-dyslexic children when either type was displayed without noise. Our findings suggest that deficits in noise exclusion, not magnocellular processing, contribute to the etiology of dyslexia.
Integration of visual motion and orientation signals in dyslexic children: an equivalent noise approach. [2022]Dyslexic individuals have been reported to have reduced global motion sensitivity, which could be attributed to various causes including atypical magnocellular or dorsal stream function, impaired spatial integration, increased internal noise and/or reduced external noise exclusion. Here, we applied an equivalent noise experimental paradigm alongside a traditional motion-coherence task to determine what limits global motion processing in dyslexia. We also presented static analogues of the motion tasks (orientation tasks) to investigate whether perceptual differences in dyslexia were restricted to motion processing. We compared the performance of 48 dyslexic and 48 typically developing children aged 8 to 14 years in these tasks and used equivalent noise modelling to estimate levels of internal noise (the precision associated with estimating each element's direction/orientation) and sampling (the effective number of samples integrated to judge the overall direction/orientation). While group differences were subtle, dyslexic children had significantly higher internal noise estimates for motion discrimination, and higher orientation-coherence thresholds, than typical children. Thus, while perceptual differences in dyslexia do not appear to be restricted to motion tasks, motion and orientation processing seem to be affected differently. The pattern of results also differs from that previously reported in autistic children, suggesting perceptual processing differences are condition-specific.
A Computational Model of Implicit Memory Captures Dyslexics' Perceptual Deficits. [2022]Dyslexics are diagnosed for their poor reading skills, yet they characteristically also suffer from poor verbal memory and often from poor auditory skills. To date, this combined profile has been accounted for in broad cognitive terms. Here we hypothesize that the perceptual deficits associated with dyslexia can be understood computationally as a deficit in integrating prior information with noisy observations. To test this hypothesis we analyzed the performance of human participants in an auditory discrimination task using a two-parameter computational model. One parameter captures the internal noise in representing the current event, and the other captures the impact of recently acquired prior information. Our findings show that dyslexics' perceptual deficit can be accounted for by inadequate adjustment of these components; namely, low weighting of their implicit memory of past trials relative to their internal noise. Underweighting the stimulus statistics decreased dyslexics' ability to compensate for noisy observations. ERP measurements (P2 component) while participants watched a silent movie indicated that dyslexics' perceptual deficiency may stem from poor automatic integration of stimulus statistics. This study provides the first description of a specific computational deficit associated with dyslexia.
Neural Noise Hypothesis of Developmental Dyslexia. [2018]Developmental dyslexia (decoding-based reading disorder; RD) is a complex trait with multifactorial origins at the genetic, neural, and cognitive levels. There is evidence that low-level sensory-processing deficits precede and underlie phonological problems, which are one of the best-documented aspects of RD. RD is also associated with impairments in integrating visual symbols with their corresponding speech sounds. Although causal relationships between sensory processing, print-speech integration, and fluent reading, and their neural bases are debated, these processes all require precise timing mechanisms across distributed brain networks. Neural excitability and neural noise are fundamental to these timing mechanisms. Here, we propose that neural noise stemming from increased neural excitability in cortical networks implicated in reading is one key distal contributor to RD.