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Scientific Understanding of Consciousness |
Cognition and the Brain's Ability to Self-Generate Sequential Neuronal Activity
Science 5 September 2008: Vol. 321. no. 5894, pp. 1322 - 1327 Internally Generated Cell Assembly Sequences in the Rat Hippocampus Eva Pastalkova, Vladimir Itskov, Asohan Amarasingham, György Buzsáki Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, 197 University Avenue, Newark, NJ 07102, USA. A long-standing conjecture in neuroscience is that aspects of cognition depend on the brain's ability to self-generate sequential neuronal activity. We found that reliably and continually changing cell assemblies in the rat hippocampus appeared not only during spatial navigation but also in the absence of changing environmental or body-derived inputs. During the delay period of a memory task, each moment in time was characterized by the activity of a particular assembly of neurons. Identical initial conditions triggered a similar assembly sequence, whereas different conditions gave rise to different sequences, thereby predicting behavioral choices, including errors. Such sequences were not formed in control (nonmemory) tasks. We hypothesize that neuronal representations, evolved for encoding distance in spatial navigation, also support episodic recall and the planning of action sequences. Hippocampal networks can produce sequential firing patterns in two possibly interacting ways: under the influence of environmental/idiothetic cues or by self-organized internal mechanisms. The high-dimensional and largely random (nontopographical) connectivity of the CA3 axonal system and its inputs makes the hippocampus an ideal candidate for internal sequence generation. The parameters of cell-assembly dynamics (including their trajectory and lifetimes) are probably affected by a number of factors, including experience-dependent and short-term synaptic plasticity; asymmetric inhibition; brain state; and, fundamentally, the character and context of the input. The evolving trajectory can be effectively perturbed, or updated, by external inputs in every theta cycle. Because of this flexibility in the sources of cell-assembly control, we hypothesize that neuronal algorithms, having evolved for the computation of distances, can also support the episodic recall of events and the planning of action sequences and goals. During learning, the temporal order of external events is instrumental in specifying and securing the appropriate neuronal representations, whereas during recall, imagination, or action planning, the sequence identity is determined by the intrinsic dynamics of the network.
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