Sussex Neuroscience

Professor Miguel Maravall

Miguel MaravallNeuronal activity underlying sequence recognition

The world around us is full of patterns that unfold over time, such as speech or melodies. Making sense of our environment requires the capacity to recognise these. Accordingly, the brain is spectacularly good at deciphering and identifying temporally sequenced stimuli – think of how easily you can identify a favourite song by its first notes or rhythms, or of how Braille alphabet is read by running one’s fingertips along the surface.

Little is known about how neuronal population activity reflects the identity of a recognised sequence. To investigate this, our lab has developed novel sequence recognition tasks that can be performed by mice and humans. Participants report whether they recognise a particular tactile or auditory sequence – an artificial “song” or “word”. In mice, we can precisely determine sensory input and behavioural output, as well as neuronal responses using in vivo electrophysiology and 2-photon fluorescence microscopy. This allows us to establish how sensory sequences are reflected in the activity of populations of neurons. Comparing humans with mice, we can analyse whether both species use similar cues for sequence recognition.

We have found multiple exciting results that rotation projects can follow up on:

- When a mouse is performing sequence recognition, neurons in its somatosensory cortex convey sensory information but also predict and respond to the animal’s own behaviour. What do these intriguing responses contribute and where do they come from? How do responses change between different parts of the cortex?

- In humans, we see that sequence learning transfers very quickly from one sensory modality to another, e.g. if I learn a sequence of vibrations on my fingertip I can recognise it played back as sounds. How does this interaction work and what does it tell us about how our brain is organised?

- Our preliminary data show that people with dyslexia perform differently than others at sequence recognition, even when the task is tactile rather than auditory. What does this imply for the mechanisms underlying sensory processing in dyslexia?

This work would suit students with a range of backgrounds, including biology, biological or experimental psychology, or a quantitative subject (mathematics, physics, engineering). Students will need a strong quantitative background or a keen interest in learning quantitative approaches for sensory, systems and behavioural neuroscience. The project can involve a flexible blend of experimental and computational techniques, in mice or humans, depending on the student’s interests.

Relevant publications

For further details about the lab and a full list of publications, please see the Maravall lab homepage.

Bale MR, Maravall M (2018) Organization of sensory feature selectivity in the whisker system. Neuroscience 368: 70-80. doi: 10.1016/j.neuroscience.2017.09.014.

Bale MR, Bitzidou M, Pitas A, Brebner L, Khazim L, Anagnou S, Stevenson C, Maravall M (2017) Learning and recognition of tactile temporal sequences by mice and humans. eLife doi: 10.7554/eLife.27333

Martini FJ, Molano-Mazón M, Maravall M (2017) Interspersed distribution of selectivity to kinematic stimulus features in supragranular layers of mouse barrel cortex. Cereb Cortex 27: 3782-3789. doi: 10.1093/cercor/bhx019

Pitas A, Albarracín AL, Molano-Mazón M, Maravall M (2017) Variable temporal integration of stimulus patterns in the mouse barrel cortex. Cereb Cortex 27: 1758-1764. doi: 10.1093/cercor/bhw006

Maravall M, Diamond ME (2014) Algorithms of whisker-mediated touch perception. Curr Opin Neurobiol 25: 176-186.

Safaai H, von Heimendahl M, Sorando JM, Diamond ME, Maravall M (2013) Coordinated population activity underlying texture discrimination in rat barrel cortex. J Neurosci 33: 5843-5855.