EEG correlates of auditory rise time processing: A systematic review

This systematic review of 37 EEG studies establishes that auditory rise time prolongation generally reduces the amplitude and increases the latency of event-related potential components, while highlighting how these neural markers vary based on stimulus characteristics, participant age, and clinical status.

The Gist

Imagine your brain is a highly sophisticated sound engineer working in a recording studio. Its job is to take the raw audio of the world—especially speech—and figure out what it means. One of the most critical tools this engineer uses is something called Rise Time (RT).

What is Rise Time?

Think of a sound like a light switch.

• Fast Rise Time: You flip the switch on instantly. The light snaps to full brightness immediately. In sound, this is a sharp, percussive "click" or a hard consonant like "ba" or "ta." It's abrupt and energetic.
• Slow Rise Time: You slowly slide a dimmer switch up. The light fades in gradually. In sound, this is a soft, mellow onset, like the sound of "wa" or a gentle hum.

This paper is a systematic review, which means the authors didn't run a new experiment. Instead, they acted like detectives, gathering and organizing 37 different studies from the last 50+ years to see what we know about how the brain reacts to these "fast" vs. "slow" sound starts.

The Main Discovery: The "Sluggish" Brain

The authors found a very consistent pattern across almost all the studies:

When a sound starts slowly (Long Rise Time), the brain's electrical reaction gets "sluggish."

• The Volume Drops: The brain's electrical signal (the "volume" of the reaction) gets quieter.
• The Delay Increases: The brain takes longer to react (the "latency" gets longer).

Analogy: Imagine you are waiting for a friend to arrive.

• If they burst through the door (Fast RT), you jump up immediately and shout "Hey!" (Big, fast brain signal).
• If they slowly creep through the door (Slow RT), you might not notice them right away, and when you do, your reaction is a quiet "Oh, hi" (Small, delayed brain signal).

The Brain's Three Layers of Processing

The paper breaks down how different parts of the auditory system handle this, like a relay race with three runners:

1. The Brainstem (The Instant Reflex):
   • What it does: This is the oldest part of the auditory system, located deep in the brain. It reacts in microseconds.
   • The finding: It is incredibly sensitive. It can tell the difference between a rise time of 0.01 milliseconds and 0.5 milliseconds. It's like a security camera that detects the tiniest movement instantly.
2. The Middle Cortex (The Early Processor):
   • What it does: This layer starts processing a bit later (10–80 milliseconds).
   • The finding: It also slows down when the sound starts slowly, but it needs a slightly bigger difference in speed to notice it.
3. The Late Cortex (The High-Level Thinker):
   • What it does: This is the outer layer of the brain responsible for understanding complex sounds and language. It reacts later (100+ milliseconds).
   • The finding: This part needs a big difference to notice. If the rise time changes by just a tiny bit, the brain might ignore it. It needs the sound to start "much slower" to trigger a change in its electrical signal.

Why Does This Matter? (The Dyslexia Connection)

The review looked at people with dyslexia (a learning difficulty that affects reading and spelling). The results here are a bit messy, like a puzzle with missing pieces, but there are some clues:

• The "Tuning" Problem: Some studies suggest that people with dyslexia have brains that are "out of tune" when it comes to these fast sound starts. They might miss the subtle differences that help us distinguish between similar-sounding words (like "bat" vs. "pat").
• The "Over-Compensation" Theory: Other studies found that the dyslexic brain actually reacts too much or in a weird way to these slow starts, perhaps trying too hard to figure out what it's hearing.
• The Takeaway: It seems that the ability to process these rapid sound changes is a key building block for learning to read. If the brain struggles to hear the "snap" of a sound, it might struggle to connect that sound to a letter on a page.

The "Missing Pieces" in the Puzzle

The authors point out that while we know what happens, we don't fully know why yet. They also found some gaps in our knowledge:

• Old Tech: Many of the studies on the brainstem (the instant reflex) are very old (from the 1970s and 80s). We need to redo these with modern, high-tech equipment.
• Kids are Different: The brain changes as we grow. A 4-year-old's brain reacts differently to sound than a 10-year-old's or an adult's. We need more studies specifically on children to see how this skill develops.
• Other Disorders: We mostly studied dyslexia, but what about Autism Spectrum Disorder (ASD)? The authors suggest we should check if people with ASD also have trouble with these "sound starts."

Summary

In simple terms, this paper tells us that how quickly a sound starts is a huge deal for the brain.

• Fast starts = Big, fast brain reactions.
• Slow starts = Small, slow brain reactions.
• Dyslexia might be linked to a brain that has trouble catching these fast starts, making it harder to learn to read.

The authors are calling for more modern research to fill in the gaps, especially for children and other groups, to help us better understand and support people with speech and learning challenges.

Technical Summary

1. Problem Statement

Auditory Rise Time (RT)—the rate at which the amplitude or frequency of a sound increases—is a critical acoustic feature for speech perception, particularly for distinguishing consonants and processing the speech envelope. Deficits in RT processing are strongly linked to speech and language disorders, most notably dyslexia.

Despite a substantial accumulation of data regarding the neurophysiological mechanisms of RT processing across different populations (typically developing children, adults, and clinical groups) and methodologies (ERP, ABR, ASSR), these findings have remained fragmented and inconsistent. There was a lack of a comprehensive synthesis that:

• Systematizes EEG markers of RT sensitivity across the entire auditory processing hierarchy (from brainstem to cortex).
• Clarifies how experimental parameters (stimulus type, intensity, inter-stimulus interval) influence these markers.
• Addresses the developmental trajectory of RT processing and its specific alterations in clinical populations.

2. Methodology

The authors conducted a systematic review adhering to the PRISMA 2020 guidelines.

• Data Sources: PubMed, Web of Science, and APA PsycInfo.
• Search Strategy: Queries combined "Rise time" with terms related to evoked potentials (ERP, AEP, EEG, etc.) and "humans." The search covered literature up to January 25, 2024, with an update performed on February 15, 2026.
• Eligibility Criteria:
  • Empirical human studies published in English in peer-reviewed journals.
  • Studies must measure EEG/ERP responses to auditory stimuli with varied amplitude or formant rise times.
  • Studies with only a single RT condition were excluded.
• Selection Process:
  • Initial identification: 281 articles.
  • After duplicate removal and screening (title/abstract and full-text): 37 studies were included.
  • Exclusions were primarily due to lack of full text availability (older studies) or failure to meet inclusion criteria (e.g., no RT variation).
• Data Extraction & Quality Assessment:
  • Data extracted included sample demographics, experimental paradigms (oddball, block design), stimulus parameters, and specific EEG outcomes (amplitude/latency changes).
  • Risk of bias was assessed using the OHAT (Office of Health Assessment and Translation) tool.

3. Key Contributions

This review provides the first comprehensive mapping of RT processing across the entire auditory system using EEG markers. Key contributions include:

• Hierarchical Processing Model: It delineates how different stages of the auditory system respond to RT changes, distinguishing between brainstem (ABR), middle latency, and cortical (ERP) responses.
• Parameter Optimization: It identifies optimal stimulation parameters (e.g., Inter-Stimulus Intervals, stimulus types) required to detect RT effects, noting that effects vary significantly based on whether the stimulus is a tone, noise, or speech token.
• Developmental Trajectory: It synthesizes evidence showing that the neural markers of RT processing shift with age (e.g., from P1/N2 dominance in young children to N1/P2 dominance in adults) and that the latency of mismatch responses decreases with maturation.
• Clinical Nuance: It highlights the complexity of using RT as a biomarker for dyslexia, revealing that results are often contradictory depending on the specific RT type (Amplitude vs. Formant) and the age of the participant.

4. Results

A. General Neurophysiological Trends

The primary finding across the majority of studies is a consistent relationship between RT prolongation and EEG markers:

• Amplitude: Prolonged RT leads to a decrease in the amplitude of main ERP components.
• Latency: Prolonged RT leads to an increase (delay) in the latency of these components.

B. Processing Stages and Sensitivity

The review categorizes findings by the latency of the response:

1. Auditory Brainstem Response (ABR):

   • Sensitivity: Extremely high; detects differences as small as tens of microseconds.
   • Findings: Wave V latency increases and amplitude decreases with longer RT. This effect is robust across noise bursts, tone pips, and clicks.
   • Limitation: Most studies are dated (1970s–1990s); no modern ABR studies on RT were found.

2. Middle Latency Components (Na, Pa, Nb):

   • Sensitivity: Detects differences in the range of 0.5 ms to 25 ms.
   • Findings: Amplitude of Na-Pa and Pa-Nb decreases with RT prolongation.

3. Late Latency Components (P1, N1, P2, N2, P3):

   • Sensitivity: Requires larger RT differences, typically >15 ms (optimal range 15–500 ms).
   • N1/P2: The most studied components. N1 amplitude decreases and latency increases with longer RT.
   • P2: Similar amplitude reduction and latency delay.
   • Developmental Note: In young children (4–6 years), N1/P2 are not fully developed; RT effects are often observed in P1 and N2 instead.

4. Difference Waves (MMN/MMR/LDN):

   • MMN (Mismatch Negativity): Typically observed in adults (150–350 ms) for RT deviants.
   • MMR (Mismatch Response): In children and infants, the response is often positive (MMR) rather than negative (MMN).
   • Formant vs. Amplitude RT: Neurotypical adults show stronger MMN to Formant RT (FRT) changes than Amplitude RT (ART) changes. This sensitivity to FRT matures around age 10.

C. Clinical Findings (Dyslexia)

Results regarding dyslexia are controversial and heterogeneous:

• Some studies show reduced MMN or altered N1/P2 modulation in dyslexic groups compared to controls.
• Other studies show enhanced or atypical responses (e.g., larger MMN in dyslexic children under specific timing conditions).
• Key Insight: The utility of RT as a biomarker depends heavily on the specific RT type (FRT vs. ART) and the developmental stage. Children with familial risk of dyslexia may lack the MMR seen in typical children as early as age 3.

D. Influence of Experimental Parameters

• Inter-Stimulus Interval (ISI): Short ISIs (<250 ms) can mask RT effects due to neural adaptation or overlap of offset/onset responses. An ISI of 250–500 ms is recommended for cortical components.
• Stimulus Type: Effects are generally consistent across tones and speech, though speech tokens (specifically FRT) often yield more robust effects in neurotypical populations.
• Intensity: While intensity affects overall ERP amplitude, RT effects (latency/amplitude modulation) are detectable even at low intensities, provided the RT difference is sufficient.

5. Significance and Future Directions

Significance:

• Standardization: The review establishes that 15 ms is a critical lower-bound threshold for cortical RT discrimination tasks, balancing the need to avoid spectral splatter while maintaining temporal precision.
• Clinical Application: It suggests that RT processing deficits are a core feature of dyslexia but warns against using a single ERP marker (like MMN) as a definitive diagnostic tool without considering age and stimulus type.
• Methodological Guidance: It provides a framework for designing future experiments, emphasizing the need for appropriate ISIs and the selection of age-appropriate ERP components (e.g., focusing on P1/N2 for young children).

Limitations & Future Research:

• Gap in Modern ABR: The field relies on outdated ABR studies; modern replication with high-density EEG is needed.
• Pediatric Data: There is a scarcity of studies on basic ERP components (P1, N1, P2, N2) in children outside of oddball paradigms.
• Clinical Diversity: Research is limited to dyslexia. Future studies should investigate RT processing in Autism Spectrum Disorder (ASD) and other language disorders.
• Paradigm Shift: The field is dominated by the oddball paradigm. Future research should utilize repetitive stimulation paradigms to better analyze main ERP components and improve signal-to-noise ratios.

In conclusion, this review confirms that RT is a fundamental acoustic cue processed hierarchically by the auditory system, with distinct neurophysiological signatures at each stage. However, the interpretation of these markers requires careful consideration of developmental age, stimulus parameters, and the specific nature of the RT change.