The neural basis of perceptual sensitivity to sound in auditory cortex of the mouse.
Lead Research Organisation:
Imperial College London
Department Name: Bioengineering
Abstract
The auditory world is noisy and full of distractions, but our brains are remarkably good at detecting, and extracting important sounds while ignoring the background. If a person mentions your name at the other end of a noisy room, it is quite likely that you will stop what you‘re doing, and listen to the speaker‘s words. As you do this, you lose awareness of the other noisy goings on around you. How the brain performs this amazing task is the subject of my research.
My goals are to determine:
- How the brain responds to important sounds when they occur in noisy environments.
- How the brain improves sound detection in noisy environments using the natural properties of sound.
- How the brain signals that it has heard an important sound.
To do this, I‘m going to present sounds to mice and record brain activity in auditory cortex, which is thought to be involved in higher-level processing of sound. I will train mice to perform a task where they must listen and indicate when they have heard a particular sound. I will explore whether their brain activity differs between occasions when indicate they have or have not heard the sound.
My goals are to determine:
- How the brain responds to important sounds when they occur in noisy environments.
- How the brain improves sound detection in noisy environments using the natural properties of sound.
- How the brain signals that it has heard an important sound.
To do this, I‘m going to present sounds to mice and record brain activity in auditory cortex, which is thought to be involved in higher-level processing of sound. I will train mice to perform a task where they must listen and indicate when they have heard a particular sound. I will explore whether their brain activity differs between occasions when indicate they have or have not heard the sound.
Technical Summary
The natural world consists of many separate and interfering sound sources. In animals, these sounds converge at the cochlea, which reports sound frequency to the brain. Somehow, the brain is able to separate and group frequency information into distinct auditory objects in order to build accurate perceptions of the world. The ability to detect salient sounds in the environment is critically important to the survival of many animal species, and is a key factor in human communication. Such sounds are often embedded within noisy backgrounds, reducing the signal-to-noise ratio at which the auditory system must operate, and making detection more difficult. The brain is known to exploit certain features of natural sounds in order to improve signal detection, but the mechanisms by which it performs these tasks remain largely unknown.
Therefore, the overall aim of this project is to understand how activity in auditory cortex influences signal perception in the presence of background noise. By modulating the amplitude of background noise coherently, it is possible to improve signal detection. This is a well-characterised psychoacoustic phenomenon called co-modulation masking release, the mechanism of which I shall investigate using electrophysiological recordings in the auditory cortex of anaesthetised and awake-behaving mice.
My key goals are:
1. To determine how modulations in background noise influence the representation of acoustic signals in auditory cortex.
2. To determine how the perceptual interpretation of a stimulus is influenced by auditory cortical activity.
First, using extracellular population recordings, I will establish how patterns of firing within populations of auditory cortical neurons are affected by noise modulations. Second, using whole cell recordings from single cells, I will determine the mechanisms that underlie these changes. Subsequently, mice will be trained to detect pure tones embedded in modulated background noise in a behavioural task. I will then record neuronal activity in auditory cortex whilst they perform this task, and therefore directly relate neuronal activity to perceptual outcome. Finally, I will determine whether single neuron stimulation in auditory cortex can influence task outcome.
Having characterised the mechanisms underlying signal detection in the brain, they may then be applied to improve synthetic listening devices: both cochlear implant technology for the hearing impaired, and other machine listening systems (e.g. for accurate speech recognition in noisy environments). Furthermore, by studying how complex sound information is processed in the auditory cortex, we may uncover fundamental principles about how neural networks perform sensory discriminations.
Therefore, the overall aim of this project is to understand how activity in auditory cortex influences signal perception in the presence of background noise. By modulating the amplitude of background noise coherently, it is possible to improve signal detection. This is a well-characterised psychoacoustic phenomenon called co-modulation masking release, the mechanism of which I shall investigate using electrophysiological recordings in the auditory cortex of anaesthetised and awake-behaving mice.
My key goals are:
1. To determine how modulations in background noise influence the representation of acoustic signals in auditory cortex.
2. To determine how the perceptual interpretation of a stimulus is influenced by auditory cortical activity.
First, using extracellular population recordings, I will establish how patterns of firing within populations of auditory cortical neurons are affected by noise modulations. Second, using whole cell recordings from single cells, I will determine the mechanisms that underlie these changes. Subsequently, mice will be trained to detect pure tones embedded in modulated background noise in a behavioural task. I will then record neuronal activity in auditory cortex whilst they perform this task, and therefore directly relate neuronal activity to perceptual outcome. Finally, I will determine whether single neuron stimulation in auditory cortex can influence task outcome.
Having characterised the mechanisms underlying signal detection in the brain, they may then be applied to improve synthetic listening devices: both cochlear implant technology for the hearing impaired, and other machine listening systems (e.g. for accurate speech recognition in noisy environments). Furthermore, by studying how complex sound information is processed in the auditory cortex, we may uncover fundamental principles about how neural networks perform sensory discriminations.
