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Professor Matt Jones

Neuronal networks in cognition and disease

What kind of neuroscience do you do?

Decades ago, I fell into a pond full of mud and slime.  It so happens that the offending pond is about 150 metres from my Bristol lab and, whenever I see it, I can immediately recall the traumatic scenes of my youth.  How does my brain make this happen?  How are the different facets of my experience – its location, sensory properties and emotional consequences – integrated into memory?  Are the same neurons that were first activated when I hit the murky water still involved in storing and recalling that memory years later?  How has the impact of this pond on my brain informed my behaviour ever since?

We study how neurons distributed across functionally specialised brain regions share information over the course of experience to guide decisions.  Alongside tracking brain activity during behaviour, we are particularly interested in the roles of brain activity during sleep, which is central to fine-tuning and integrating memories (see Gardner et al. 2014 for a review in EJN and Sadowski et al. 2016 for a Cell Reports paper relating sleep to synaptic plasticity).

You can hear Matt talk about sleep here and here

Of course, we are ultimately interested in establishing how and why distributed information processing becomes impaired, including in anxiety, schizophrenia, epilepsy, Alzheimer’s disease and Down Syndrome.  Ullrich explains some of our interests in schizophrenia here

How do you do that?

We use a combination of rat or mouse models, human volunteers and patients.

In order to monitor brain activity directly and simultaneously from multiple brain regions in rodents, we implant arrays of recording electrodes into brain regions that act as core nodes during processing of memory, decision-making and aversive or rewarding information: the hippocampus, prefrontal and parietal cortex, amygdala and nucleus accumbens.

Rodent models also allow us to use optogenetics to map or silence specific connections in these circuits, or to model genetic (see Jon’s 2015 Nature Neuroscience paper on Down Syndrome, summarised here ) or neurodevelopmental disruption (see Keith and Ullrich’s 2012 Neuron paper, summarised here ) associated with disease.  Julia’s Advances in Genetics review explains how we might investigate mechanisms using rodent models (Heckenast et al. 2015).

We have recently started to use data recorded from rodent brains to help interpret human scalp EEG data recorded from healthy volunteers (recruited from ) or patients (in collaboration with Dara Manoach at MGH and Marianne van den Bree at Cardiff University).  Here’s an example of one study design: 

Who’s in the team?

We are a group of postdocs and graduate students (in roughly equal numbers) with a range of backgrounds spanning biochemistry, computer science, electrical engineering, maths, medicine, pharmacology and psychology.  Almost all projects in the lab draw on local, national and international collaborations across all these disciplines – it’s the only way to join all the dots of modern neuroscience.  We have enjoyed successful collaborations with a number of industrial partners over the years, in particular with the Lilly Centre for Cognitive Neuroscience.  Here's Matt talking with the MRC about industrial collaboration: 

Research keywords

  • Neuronal networks
  • learning
  • memory
  • oscillations

Diseases related to this field of research

  • Schizophrenia
  • Down syndrome
  • Epilepsy
  • Alzheimer's disease

Processes and functions relevant to this work

  • Learning and memory
  • Decision-making
  • Sleep

Equipment relevant to this work

  • Multi-channel electrophysiology systems
  • mazes

Research findings

Lab photo

  • Replayed place cell spike trains can induce LTP...but the details of spike timing relative to ripple onset matter (Sadowski et al., 2016)
  • Hippocampal place cell coding is unstable in the Tc1 mouse model of Down Syndrome (Witton, Padmashri, Zinyuk et al., 2015)
  • Ketamine ("Special K") suppresses cortico-limbic control - our first adventure in DCM (Moran, Jones et al., 2015)
  • What do sheep count to get to sleep?  Perhaps slow-waves and spindles (Perentos et al., 2015).
  • Read Emilie's thoughts on dopamine and Italian ice cream (Werlen and Jones, 2015)
  • Check out Marc and Nick's clever maths: 'A hidden Markov model for decoding and the analysis of replay in spike trains' (
  • If it's maths you're after, you could also check out Angela's toolbox for quantification of phase-amplitude coupling: 
  • Or Tom's toolbox designed to isolate neural data recorded on different sections of mazes:


  • Nick Whiteley (Maths)
  • Nicholas Timpson (Social and Community Medicine)
  • Rosalyn Moran (Virginia Tech / Eng Maths)
  • Jack Mellor (PPN)
  • Tony Pickering (PPN)
  • Lawrence Wilkinson (Cardiff)
  • Jeremy Hall (Cardiff)
  • Penny Lewis (Cardiff)
  • Marianne van den Bree (Cardiff)
  • Mark Humphries (Manchester)
  • David Bannerman (Oxford)
  • Eleanora Russo (Mannheim/Heidelberg)
  • Daniel Durstewitz (Mannheim/Heidelberg)
  • Paola Malerba (USCD)
  • Maxim Bazhenov (UCSD)
  • Dara Manoach (Harvard Medical School)
  • Tim Harris (HHMI)
  • Keith Phillips (Eli Lilly & Co)
  • Keith Wafford (Eli Lilly & Co)
  • Hugh Marston (Eli Lilly & Co)