Statistics of Decision Making in the Leech

Abstract

Animals continuously decide among different behaviors, but, even in invertebrates, the mechanisms underlying choice and decision are unknown. In this article, leech spontaneous behavior was tracked and quantified for up to 12 h. We obtained a statistical characterization, in space and time domains, of the decision processes underlying selection of behavior in the leech. We found that the spatial distribution of leech position in a uniform environment is isotropic (the same in all directions), but this isotropy is broken in the presence of localized external stimuli. In the time domain, transitions among behaviors can be described by a Markov process, the structure of which (allowed states and transitions) is highly conserved across individuals. Finally, a wide range of recurrent, deterministic motifs was identified in the apparently irregular and unstructured exploratory behavior. These results provide a rigorous description of the inner dynamics that control the spontaneous and continuous flow of behavioral decisions in the leech.

Beyond the central pattern generator: amine modulation of decision-making neural pathways descending from the brain of the medicinal leech

“…Clearly, a differential upregulation of 5-HT secretion from the Retzius neurons in the head brain could account for the swim-inhibitory effects that we observed during focal application of 5-HT to the brain. Because brain neurons Tr1 and Tr2 can also induce a gradual and sustained excitation of the serotonergic Retzius cells (Brodfuehrer and Friesen, 1986b), descending command-like neurons also have the potential to contribute to the release of 5-HT and other amines in the brain that, in turn, may modulate the state of decision-making systems for on-going and subsequent behaviors (Crisp and Mesce, 2004;Garcia-Perez et al, 2005).…”

“…During spontaneous swimming, or when a swim-related stimulus arrives, the decision to swim or not to swim appears to depend on the 'state' of the brain and segmental swimrelated neural networks (Briggman et al, 2005;Garcia-Perez et al, 2005). What defines this state is complex, although our studies of aminergic modulation have attempted to contribute some insights.…”

“…What defines this state is complex, although our studies of aminergic modulation have attempted to contribute some insights. Because locomotory behaviors tend to be expressed on the order of tens of seconds, the operation of these networks may define their own and subsequent states (Garcia-Perez et al, 2005), and may influence the operation of related circuits over short and longer time periods. Altogether, our observations support the conclusion that a full understanding of the dynamics underlying decision-making processes will require a greater understanding of the modulatory processes that occur during the activation of individual behavioral routines.…”

“…swimming vs crawling) (Briggman et al, 2005;Esch et al, 2002;Garcia-Perez, 2005;Kristan, Jr et al, 2005). In the leech, central neural networks and sensory-to-motor pathways underlying swimming have been mapped to an unparalleled level of cellular detail (Ort et al, 1974;Willard, 1981;Friesen, 1989;Hashemzadeh-Gargari and Friesen, 1989;Eisenhart et al, 2000;Brodfuehrer and Thorogood, 2001) (for a review, see Kristan, Jr et al, 2005).…”

Characterization of the rat exploratory behavior in the elevated plus-maze with Markov chains

“…Markov chains are widely used to describe and model sequential animal behavior in different environments (Espejo, 1997;Borisyuk and Hoppensteadt, 1998;Garcia-Perez et al, 2005;Maubourguet et al, 2008). A Markov chain describes the behavior of a system by assuming that its state belongs to a set of discrete states.…”