Aligning the Brain in a Rhythmic World

Introduction: Internal and
External Rhythms
Rhythm in the brain
Except under extreme conditions, such as anesthesia,
electrical recordings from the brain invariably reveal
robust oscillatory activity (fluctuations of voltage). In
pursuit of the idea that these oscillations are actually
relevant to adaptive brain functioning, increasingly
specific relationships have been proposed between
neuronal oscillations and numerous cognitive
functions. These relationships include: (1) theta
oscillations and encoding of spatial information in
the hippocampus (Maurer and McNaughten, 2007);
(2) theta oscillations and the formation of mnemonic
neuronal representations (Jensen et al., 2007);
(3) alpha oscillations and “internally directed”
cognition (Palva and Palva, 2008); and (4) gamma
oscillations and both attention/sensory selection
(Fries et al., 2002) and feature binding (Singer and
Gray, 1995). See the short course chapter Rhythms
in Cognitive Processing by C. Tallon-Baudry, for
in-depth discussion of this subject. Thus, consensus is
building that neuronal oscillations are instrumental
rather than incidental to brain function and
dysfunction (Buzsaki and Draguhn, 2004; Uhlhaas
and Singer, 2006; Buzsaki, 2007; Borgers and Kopell,
2008; Schroeder and Lakatos, 2009a).
Rhythm in the sensorium
When considering the functional significance of
neuronal oscillations, it is worth keeping in mind
just how rhythmic our sensory world is. Under
natural conditions, for example, stimulating the
hand typically involves moving the fingers across
surfaces or manipulating objects. Because the motor
routines that drive arm, hand, and finger movements
are modulated by oscillations in the delta, theta, mu,
and beta bands (McAuley et al., 1999a; Pfurtscheller
et al., 2000; Pineda, 2005; Birbaumer et al., 2006;
Wolpaw, 2007; Hatsopoulos and Donoghue, 2009),
rhythm is imposed on somatosensory inflow. (See the
chapter Rhythms in Motor Processing: Functional
Implications for Motor Behavior by N. Hatsopoulos,
in this short course.) In the visual domain, many
stimuli considered “biologically significant” stem
from observing the motion of conspecifics or other
animals; here too, because of the oscillatory patterning
mechanisms (above), the sensory inflow has a strong
rhythmic component. Although a visual scene may
be completely static, the sequence of fixations used
to encode the scene is generally rhythmic, with a rate
of ~3 Hz (McAuley et al., 1999b; Otero-Millan et
al., 2008). Even when a subject is fixated on a static
stimulus, microsaccades (also occurring at ~3 Hz)
© 2009 Schroeder
Aligning the Brain in a Rhythmic World
impose a strong rhythm on visual processing (Bosman
et al., 2009).
Interaction of neuronal oscillations
and input rhythms
The striking similarity between the brain’s oscillatory
rhythms and those in the sensorium is unlikely to
be an accident. Several other presentations in this
short course will deal with the precise physiological
mechanisms that generate neuronal oscillations
(see chapters Modeling Rhythms: from Physiology
to Function by N. Kopell, and Modeling Rhythms:
Detailed Cellular Mechanisms of In Vitro Oscillations,
with Emphasis on Very Fast Oscillations by
R. Traub). This chapter will explore the relationship
between neuronal oscillations and environmental
rhythms. We will consider the manner in which the
brain may use neuronal oscillations as instruments
of adaptive brain operations, by aligning them with
relevant environmental rhythms (Schroeder and
Lakatos, 2009a).
Oscillations Control
Neuronal Excitability
Current source density (CSD) analysis of local field
potential (LFP) distributions across cortical layers
shows that fluctuations or “oscillations” of voltage
in the extracellular medium reflect rhythmic,
synchronous alternation of inward and outward
transmembrane current flow in the local neuronal
ensembles (Lakatos et al., 2005). In agreement with
Bishop’s fundamental proposition (Bishop, 1933),
analysis of concomitant local neuronal firing (lower
trace multiunit activity [MUA]) indicates that this
current flow alternation reflects a shift between
net depolarized and hyperpolarized states in the
local neuronal ensemble (Lakatos et al., 2005).
Systematic relationships between oscillatory phase
and excitability have been substantiated for the very
low (