Neuronal Processing

Dr Per Jesper Sjöström
MRC Research Fellow
Tel: +44 (0)20 7679 6381
Jesper Sjöström biography

How does the visual cortex learn to “see” and interpret visual information from the outside world? How is information stored in the brain? After all, the brain has no central processing unit to control actions and no memory storage banks to keep track of information. There is only a vast network of interconnected neurons.

Today, there is good evidence in support of the notion that learning and memory occur at the synaptic connections that exist between neurons of the brain. The idea is that events in the outside world cause particular patterns of activity in populations of neurons in the cortex. In turn, these activity patterns bring about changes in connective strengths among cortical neurons. Such changes, which are known under the name of synaptic plasticity, are a means of storing information in neuronal circuits. Synaptic plasticity may thus ensure that subsequent presentations of similar although perhaps non-identical stimuli elicit more or less the same activity patterns, thus resulting in a form of recall and detection mechanism.

It follows then that to understand how the brain works, it is essential to understand the properties, the mechanistic underpinnings, and the functional impact of synaptic plasticity in the brain. My lab focuses on the synaptic plasticity learning rules of neocortex. In particular, my group investigates Spike-Timing-Dependent Plasticity (STDP) in visual cortical microcircuits. In the STDP learning paradigm, whether synaptic strengthening and weakening is brought about depends critically on the relative millisecond timing of spiking activity in connected pairs of cells (Fig. 1). Although the precise outcome depends on the brain region that is investigated, typically pre before postsynaptic spiking activity repeated within a couple of tens of milliseconds results in synaptic strengthening, whereas the opposite temporal order evokes weakening of synaptic connections (Fig. 1).

To understand synaptic plasticity in visual cortical circuits, my lab employs several state-of-the-art approaches: quadruple whole-cell recordings (Fig. 2 and animation above), two-photon laser scanning microscopy of synaptic calcium signals (Fig. 3), and computer simulations.

Our research is not limited to the mechanisms and impact of STDP; indeed, several forms of plasticity do not depend on global spikes but on local dendritic spikes. In addition, we cover topics such as cortical circuit connectivity patterns, neocortical information storage, and the impact of synaptic plasticity in vivo. My group also collaborates with researchers both at UCL as well as internationally.


Figure 1 – Timing curve for STDP obtained from visual cortical layer-5 neurons. A pair of connected layer-5 neurons is illustrated to the left. If the presynaptic cell repeatedly fires within a narrow temporal window just before the postsynaptic cell, the synaptic connection is strengthened (green, “LTP”). With the opposite temporal order, however, synaptic weakening ensues (red, “LTD”). Adapted from Sjöström et al, Neuron 2001.


Figure 2 – Sample quadruple recording, showing a synaptically connected pair of neocortical layer-5 pyramidal neurons. An action potential in cell #3 results in an EPSP in cell #2. Adapted from Sjöström et al, Neuropharmacology, 2007.


Figure 3 – Two-photon laser scanning imaging of dendritic calcium signals in a neocortical layer-5 neuron from which dual somatic and dendritic whole-cell recordings were obtained. When a 50-Hz train of somatically evoked spikes back-propagate into the apical dendrite, a decrementing fluorescent signal is evoked (green traces). If the apical dendrite is weakly depolarized using the dendritic whole-cell recording electrode, however, then a strong supralinear summation ensues (yellow traces), thus resulting in strong promotion of action potential backpropagation under depolarizing conditions. This dendritic switch of the reliability of action potential back-propagation strongly impacts the plasticity of synaptic inputs in the dendritic tree (for additional information, see Sjöström & Häusser, Neuron, 2006).

Selected publications:

  • Sjöström, PJ, Turrigiano, GG & Nelson, SB (2007) Multiple forms of long-term plasticity at unitary neocortical layer 5 synapses. Neuropharmacology 52, 176-84
  • Duguid, I & Sjöström, PJ (2006) Novel presynaptic mechanisms for coincidence detection in synaptic plasticity. Curr Opin Neurobiol 16, 312-22
  • Sjöström, PJ & Häusser, M (2006) A cooperative switch determines the sign of synaptic plasticity in distal dendrites of neocortical pyramidal neurons. Neuron 51, 227-38
  • Varshney, LR, Sjöström, PJ & Chklovskii, DB (2006) Optimal Information Storage in Noisy Synapses under Resource Constraints. Neuron 52, 409-23
  • Song, S, Sjöström, PJ, Reigl, M, Nelson, S & Chklovskii, DB (2005) Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol 3, e68
  • Sjöström, PJ, Turrigiano, GG & Nelson, SB (2004) Endocannabinoid-dependent neocortical layer-5 LTD in the absence of postsynaptic spiking. J Neurophysiol 92, 3338-43
  • Watt, AJ, Sjöström, PJ, Häusser, M, Nelson, SB & Turrigiano, GG (2004) A proportional but slower NMDA potentiation follows AMPA potentiation in LTP. Nat Neurosci 7, 518-24
  • Sjöström, PJ, Turrigiano, GG & Nelson, SB (2003) Neocortical LTD via coincident activation of presynaptic NMDA and cannabinoid receptors. Neuron 39, 641-54
  • Nelson, SB, Sjöström, PJ & Turrigiano, GG (2002) Rate and timing in cortical synaptic plasticity. Philos Trans R Soc Lond B Biol Sci 357, 1851-7
  • Sjöström, PJ & Nelson, SB (2002) Spike timing, calcium signals and synaptic plasticity. Curr Opin Neurobiol 12, 305-14
  • Sjöström, PJ, Turrigiano, GG & Nelson, SB (2001) Rate, timing, and cooperativity jointly determine cortical synaptic plasticity Neuron 32, 1149-64
  • Sjöström, PJ, Frydel, BR & Wahlberg, LU (1999) Artificial neural network-aided image analysis system for cell counting. Cytometry 36, 18-26