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 sequential temporal patterns. Accordingly, the brain is spectacularly good at deciphering and remembering temporal patterning over hundreds of ms or more. Yet despite the importance and ubiquity of sequence selectivity in the brain, surprisingly little is known about its neuronal substrates. How a sequence is reflected in spiking activity across populations of neurons, integrated over time, and classified as a meaningful entity is unknown.

Our lab has developed a novel sequence recognition task that can be performed by mice and humans. Participants report whether they recognise a particular tactile or auditory ordered sequence – an artificial “song” or “word”. In mice, we can determine sensory input, behavioural output and neuronal responses under controlled conditions, using in vivo electrophysiology and 2-photon fluorescence microscopy. This allows us to establish how representations of sensory sequences emerge from the activity of populations of neurons. Comparing humans with mice, we seek to analyse whether both species use similar cues for sequence recognition.

Projects in the lab can address many exciting questions related to this overall programme. What are the limits of animals’ performance on the task? How do sequence representations change from stage to stage? Can we design novel analyses to resolve the participation of particular neurons in the task?

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.