Novelty-induced correlation between visual neurons and the hippocampal theta rhythm in sleep and wakefulness

www.elsevier.com/locate/brainres

Brain Research 106

Research Report

Novelty-induced correlation between visual neurons and the hippocampal

theta rhythm in sleep and wakefulness

Marisa Pedemonte*, Juan P. Gambini, Ricardo A. Velluti

Neurofisiologıa, Departamento de Fisiologıa, Facultad de Medicina, Universidad de la Republica, Ave. General Flores 2125,

11800 Montevideo, Uruguay

Accepted 29 July 2005

Available online 24 October 2005

Abstract

Various rhythms have been shown to affect sensory processing such as the waking–sleep cycle and the hippocampal theta waves.

Changes in the firing of visual lateral geniculate nucleus neurons have been reported to be dependent on the animal’s behavioral state. The

lateral geniculate extracellular neuronal firing and hippocampal field activity were recorded in chronically implanted animals to analyze the

relationship during quiet wakefulness and sleep associated with stimulation shifts that may introduce novelty. During wakefulness, a change

in light flash stimulation pattern (stimuli frequency shift, stimuli on and off) caused an increment in the theta band power in 100% of the

cases and a phase-locking of the spikes in 53% of the recorded neurons. During slow wave sleep, there were no consistent changes in the

theta power notwithstanding 13% of the neurons exhibited phase-locking, i.e., novelty may induce changes in the temporal correlation of

visual neuronal activity with the hippocampal theta rhythm in sleep. The present results suggest that visual processing in slow wave sleep

exists, while auditory information and learning were reported during slow wave sleep in animals and newborn humans. The changes in the

theta power as well as in the neuronal phase-locking amount indicate that in slow wave sleep, the ability of the hippocampus to detect/process

novelty, although present, may be decreased. This is consistent with the noticeable decrease in awareness of the environment during sleep.

D 2005 Elsevier B.V. All rights reserved.

Theme: Sensory systems

Topic: Visual psychophysics and behavior

Keywords: Sensory processing; Attention; Visual unit; Phase-locking; Lateral geniculate; Sleep–wakefulness

1. Introduction

Neuronal activity in sensory systems is dependent on

several factors that modulate incoming information from

specific environmental and body channels. These neurons

may be part of different brain networks/cell assemblies that

shape their activity, of which a meaningful modulator is the

animal’s behavioral state. The central nervous system (CNS)

is continuously receiving sensory inputs during the 24-h

waking–sleep cycle [37,38]. Although sensory processing

occurs without interruptions, it is known that neuronal

0006-8993/$ - see front matter D 2005 Elsevier B.V. All rights reserved.

doi:10.1016/j.brainres.2005.07.069

* Corresponding author. Fax: +598 2 924 87 84.

E-mail address: [email protected] (M. Pedemonte).

activity, unitary and field evoked, in every sensory system

can change depending on the sleeping or waking brain [36].

In the visual system, lateral geniculate nucleus (LGn)

neuronal activity shifts were reported to be sleep state-

dependent [7,20,21,24].

Within the waking–sleep rhythm, other cycles exist that

modulate neuronal activity with a different temporal scale,

the ultradian hippocampal theta rhythm being a conspicuous

example. Theta activity, 4 to 10–12 cycles per second (cps),

is always present in the CNS electrophysiological activity

even in slow wave sleep as shown by Fourier analysis

[12,37]. Furthermore, it has been related to several brain

processes; it was found to be involved in motor activities

during both wakefulness and paradoxical sleep [4,11,19], as

well as in sensory processing related to the motor context

2 (2005) 9 – 15

M. Pedemonte et al. / Brain Research 1062 (2005) 9–1510

[13,18]. It was also found to be involved in spatio-temporal

learning [27,42], association of discontiguous events [41],

and learning of temporal sequences [22,25]. A role of the

theta rhythm in learning and memory has been proposed

from different viewpoints [1,5,8,15,17,40]. This hippo-

campal rhythm has also been linked to modulation of

autonomic processes such as heart rate [29,31].

In previous reports, we found that LGn visual units show

phase-locking to the theta rhythm during short periods of

wakefulness, slow wave sleep, and paradoxical sleep

[10,37]. Moreover, other sensory neurons such as auditory

ones also showed phase-locking with theta rhythm at

different levels of the auditory pathway including the

primary cortex. Thus, the theta rhythm was postulated as a

temporal organizer of sensory processing [28,30]. Proces-

sing of many sensory modalities were also related to the

theta rhythm, e.g., tactile [26], pain [39], and olfactory [23].

The notion that theta rhythm changes are dependent on

the animal’s attention state during behavior was suggested

by Kemp and Kaada (1975) [16]. Vinogradova (2001) [40]

summarizes the modulating influences of theta rhythm in

two ways: (1) as a regulatory pattern, linking the hippo-

campus to the brain-stem structures, sensing the attention

level, and introducing primary information about the

changes in the environment; and (2) as an informational

pattern acting on specific systems with reciprocal inter-

actions with the neocortex.

The available information, cross-correlating visual neu-

rons activity to the theta rhythm – phase-locking – leads us

to analyze changes in response to varying visual stimuli.

The main hypothesis proposes the hippocampal theta

participating in the visual unitary input temporal processing

(as an internal zeitgeber), i.e., phase-locking linked with

stimulus shifts – frequency, stim on, stim off – in

wakefulness and particularly during slow wave sleep.

2. Materials and methods

Adult guinea pigs (Cavia porcellus, n = 12) weighing

450–550 g were chronically implanted under pentobarbital

anesthesia (35 mg/kg, ip) with macroelectrodes to record the

CA1 hippocampus electrogram (Hipp: A = 6; L = 2; H =

�4), electrocorticogram (ECoG), and electromyogram of

the neck muscles (EMG), for behavioral control. Two light

metal bars were cemented to the animal’s skull. This

procedure permitted, after a week of recovery, the painless

reproduction of the stereotaxic position for unit assessment

during physiological behavior. The animal’s head was thus

firmly held, with the body hanging on a canvas, during the

recording sessions. A small hole (2 mm diameter) was

drilled in the skull over the LGn (A = 5–7; L = 4–6; H = 5–

9), covered with antibiotic cream and left open for glass

microelectrode penetrations. After a week of recovery,

animals were trained to be placed on a hammock during

2–3 days, when they showed to have normal sleep–waking

cycles. All experimental procedures were conducted in

accordance with the Medical School Committee for Animal

Research (Montevideo) and with the NIH Guide for the

Care and Use of Laboratory Animals.

During the recording sessions, flashes of light (Grass

Photo-stimulator TS 22; 2–16/s, 30 cm distant) were

applied as visual stimuli, e.g., changing stimulus frequency,

stopping or initiating it. The pupils were dilated by atropine,

the eyelids were always open, even during sleep as it

normally occurs in these animals. A glass micropipette –

filled with 3 M sodium acetate and Sky-blue solution – was

advanced through the skull hole using a micro-manipulator

(Narishige MO-8) searching for evoked extracellular unit

firing. Flash synchronizing signal, neuronal discharge,

ECoG, EMG, and Hipp were amplified, acquired, and

stored for off-line processing by computer software (Spike2,

Cambridge Electronic Design). Light stimulation frequency

ranged from 1 to 20/s; light on and light off were also an

applied pattern. Flash light frequency shifts (120 changes

recorded in 32 neurons) were analyzed; 60 of them during

wakefulness and 60 during slow wave sleep. Sixty percent

of the light stimulation shifts increased the frequency, 25%

decreased, and 15% were shifts from stimulus on to off.

Epochs without any movement and for which there was no

change in the behavioral state before and after light

frequency change were considered for processing.

Three successive temporal windows (5 s duration each)

were selected for subsequent processing: the first one,

immediately prior to the flash frequency change; the second

and the third are successive windows immediately after the

stimulus shifts. Neuronal firing was digitized with a voltage

window level and analyzed with peri-stimulus time histo-

grams to be characterized as a visual one. The hippocampal

electrogram was band-pass filtered (between 0.5 and 100

Hz), sampled at 500 Hz, and processed using autocorrela-

tion and power spectrum analysis. The cross-correlation

between hippocampal field activity and spikes was assessed

by spike-triggered averaging. In order to analyze the theta

band power shifts, the power spectra before flash stimula-

tion rate changes were taken as the reference (100%). The

Student’s t test was used for statistical validation of the

observed changes immediately before and after the stimulus

shifts.

At the end of the recording sessions, sites were

iontophoretically injected with Sky-blue; after no more than

three successful recordings, the animals were perfused with

10% formalin solution and the brains were removed for

micro-anatomical analysis.

3. Results

Epochs during which changes in the visual stimulation

rate occurred were analyzed in 32 neurons: 14 units during

both quiet wakefulness and slow wave sleep, 9 units during

quiet wakefulness and 9 units during slow wave sleep.

M. Pedemonte et al. / Brain Research 1062 (2005) 9–15 11

All the flash frequency stimulation rate changes present

during quiet wakefulness (n = 60) provoked increments in

the theta band power ranging between 110% and 553%

(mean = 183 T 102%). The power spectra at 100%

correspond to the period just previous to the light

stimulation change (Fig. 1, arrows A). The animal was

head-restrained while any possible movements were con-

trolled through the neck muscles EMG and direct observa-

tion. Periods with movements were discarded from the

analysis.

Results were different during slow wave sleep: 60 flash

stimulation shifts provoked changes in the theta band power

spectra, incrementing the power in 57% (34 out of 60),

while 43% (26 out of 60) of the light stimulation shifts

induced power decrements. The power of the theta band

after flash frequency changes varied from 34% to 372%

(mean = 106 T 48%; Fig. 1, slow wave sleep, arrow B).

Averages and their standard deviation both during quiet

wakefulness and slow wave sleep are shown in the Fig. 1

inset (bars) showing only significant changes in wakefulness

(P < 0.005).

The temporal correlation between visual units and theta

rhythm (phase-locking) was different in quiet wakefulness

compared to slow wave sleep. Fifty-three percent (32 out of

60) of the light stimulation changes evoked a cross-

correlation (phase-locking) between the LGn neuronal firing

and the Hipp theta rhythm during wakefulness. On the other

hand, only 13% of the flash stimulation changes (8 out of

Fig. 1. Hippocampal theta band power spectra shifts (4–12 Hz) evoked by flash f

(SWS). Sixty episodes of light stimulation rate changes were studied during wak

windows around the beginning of the stimulation change. Arrows A, theta power s

as 100%. Arrows B, each black point represents the percentage of the theta power

ones. During wakefulness, all the stimulation changes provoke a significant ( P <

during slow wave sleep, no significant shift appears (ranging from 34% to 372%). U

nucleus recording loci and the electrode positioning. Lower insert shows the pow

60) evoked a phase-locking of the neuronal discharge with

the theta rhythm during slow wave sleep.

Fig. 2 shows an example of neuronal discharge during

wakefulness throughout two light stimulation frequency

shifts. The post-stimulus time histogram (PSTH) character-

izes the neuron as a visual one. The theta waves increased

their amplitude and power after the flash rate changed

(windows B and E, raw recording, power spectra, and Hipp

autocorrelation) and the unit firing showed the correspond-

ing phase-locking (windows B and E, cross-correlation).

The same stimulation paradigm was applied 25 times to

study the unit discharge related to theta rhythm and the

rhythm power spectrum. The same light stimulation

frequency shifts (2 to 4 and 4 to 8 flashes/s) were applied

21 times during slow wave sleep with different quantitative

results exhibiting both lower theta phase-locking and

increasing/decreasing theta power. These results are indica-

tive that the changes are related to the behavioral shift and

not to the stimulation frequency variations.

An example during slow wave sleep – evoked and

spontaneous activity – is shown in Fig. 3 in which phase-

locking appeared when the light stimulation was off.

Although the theta power spectrum did not increase after

light stimulation went off (B, power spectra), the LGn unit

began to show phase-locking with the theta rhythm (B,

cross-correlation). This figure is intended to show that

phase-locking is not only provoked by flash stimulating

frequency shifts but also associated to flash stimulation off.

requency stimulation changes during wakefulness (W) and slow wave sleep

efulness and sixty during slow wave sleep. An analysis was made with 5-s

pectrum in the windows previous to the flash stimulus change is considered

spectra in the windows after stimulus changes, compared with the previous

0.005) increment in the theta power (ranging from 110% to 553%), while

pper inset: drawing showing the hippocampus (Hipp) and lateral geniculate

er values averaged with the corresponding standard error.

Fig. 2. Lateral geniculate nucleus (LGn; #14) visual unit discharge and hippocampal theta rhythm pre- and post-changes in the flashes of light frequency

stimulation during wakefulness. Top, post-stimulus time histogram (PSTH) to characterize the unit as a visual one and traces showing from top to bottom: flash

stimulation changing from 2/s to 4/s and, after 5 min of recording, shifting from 4/s to 8/s. Hippocampal field activity (Hipp); electromyogram (EMG);

extracellular unitary discharge (digitized below). The figure shows a quiet wakefulness characteristic recording. Six epochs (5 s each) were selected for

processing (A to F, divided by vertical lines). A and D are immediately prior to the frequency stimulation changes, whereas B–C and E–F are successive

windows after the light rate stimulation changes. Bottom, each column corresponds to the temporal window shown at the top. Cross-correlation between

hippocampal field activity and spikes was calculated by spike-triggered averaging. Temporal correlation (phase-locking) between unitary activity and theta

rhythm appears after changing the flash rate (windows B and E) and disappears ¨5 s later (windows C and F). Hippocampal electrogram power spectra (theta

rhythm range shown as black bars) and autocorrelation show an increment in theta rhythm simultaneous with the phase-locking.

M. Pedemonte et al. / Brain Research 1062 (2005) 9–1512

Hippocampal theta increment and phase-locking lasted

only for a short time (¨5 s) after stimulation shifts in

wakefulness (Fig. 2, windows B and E) and during slow

wave sleep (Fig. 3, window B).

Eleven out of the 14 neurons recorded during both

wakefulness and slow wave sleep showed changes in

temporal correlation with theta rhythm after flash stimula-

tion shifts, depending on the behavioral state. Ten units

exhibited phase-locking in wakefulness but not during slow

wave sleep, while one neuron appeared phase-locked only

in slow wave sleep. Two of the remaining units showed

phase-locking with theta rhythm in both behavioral states,

while one unit never exhibited temporal correlation with the

hippocampal rhythm.

4. Discussion

The aim of this study was to investigate the hippocampal

theta participation in the visual temporal processing as a

possible time giver – internal zeitgeber – during wakeful-

ness and sleep. Moreover, the question if novelty, i.e., shifts

in the light stimulation, may induce changes in the temporal

correlation of visual neuronal activity with the hippocampal

theta rhythm and theta power shifts in both behavioral states

abovementioned, could be another approach to information

processing.

Differences were observed in the power of the theta band

and the phase-locking of the spikes to this rhythm when a

change in the stimulation rate occurred. Whereas during

Fig. 3. Lateral geniculate nucleus (LGn; #17) visual unit discharge and the hippocampal theta rhythm associated to a light stimulation shift during slow wave

sleep. Top, post-stimulus time histogram (PSTH) characterizes the unit as a visual one and traces showing from top to bottom are: flash synchronizing signal,

changing from 16/s to no stimulation (spontaneous activity); hippocampal electrogram (Hipp); electromyogram (EMG); extracellular unitary discharges (with

their corresponding digitized traces below). This recording is characteristic of slow wave sleep because of the high amplitude and low frequency in the Hipp

field activity and the EMG low activity. As in Fig. 2, three epochs (5 s each) were selected for processing (A to C, divided by vertical lines); A is immediately

previous to the end of flash stimulation while B–C are successive windows without flashes (spontaneous firing). In the lower part, each column corresponds to

the temporal window shown above. Cross-correlation between hippocampal field activity and spikes was calculated by spike-triggered averaging. Temporal

correlation (phase-locking) between unitary discharge and theta rhythm appears after changing the flash stimulation (window B) and disappears some seconds

(¨5 s) later (window C). Hipp power spectra (theta rhythm range as black bars) exhibit two frequency peaks after the flash shift. Hipp wave autocorrelogram

does not show any dominant frequency after stimulation shift.

M. Pedemonte et al. / Brain Research 1062 (2005) 9–15 13

wakefulness 100% of the cases showed an increase in the

theta band power, the changes observed during slow wave

sleep were different exhibiting increasing and decreasing

theta power. In addition, 53% of the neurons showed theta

phase-locking during quiet wakefulness whereas this phe-

nomenon was observed in only 13% of the neurons during

slow wave sleep.

The type 2 theta in the restrained guinea pig, i.e., the

theta we are recording, occurs during sensory processing in

an alert animal [33]; it can be recorded in slow wave sleep

during which theta rhythm is present as shown in the

literature [12] as well as in our previous [30,37] and in the

present report power spectra analysis in slow wave sleep.

Moreover, in addition to the well-established relationship

between theta and motor activity, a non-motor process

appears as contributing to theta of which a much likely

candidate is a sensory process [35].

The consistent increment of theta power when the

stimulus changes occurred in quiet wakefulness is in

accordance with the idea that the hippocampal theta senses

and expresses a different level of attention, considering the

hippocampus as a novelty detector and comparator [9,14,40].

A double interconnected function has been postulated for

this rhythm, i.e., selective attention and protection from

interference, and the global function of selective information

transfer into cortical memory storage [34,43].

M. Pedemonte et al. / Brain Research 1062 (2005) 9–1514

The present results showing an induction of phase-

locking (temporal correlation) as a consequence of the

stimulation change supports the notion that the theta rhythm

serves as a temporal organizer for specific sensory process-

ing as previously postulated for the auditory and visual

systems [10,28,30,37,38]. In support of our proposal for

theta rhythm acting as a temporal organizer, oscillatory

influences have been reported transforming an asymmetric

rate code into a temporal code, playing a critical role in

temporal sequence learning by compressing and replaying

in a relevant temporal order [25].

Theta power increment and phase-locking are maintained

for approximately 5 s after stimulus shift (see windows B

and E in Fig. 2). This duration, about 5 s, is in accordance

with previous results showing a few seconds (5–10 s)

duration epochs with theta increment and LGn neuronal

firing phase-locked with it, appearing at random without any

known significant environmental change [37]. Furthermore,

Vinogradova (2001) [40] showed inhibitory responses of

hippocampal CA3 neurons after auditory stimulation that

disappeared after 4–6 s because of gradual habituation, a

well-known theta-associated phenomenon.

The present results suggest that visual processing in slow

wave sleep exists, to some extent, although different than

during wakefulness. The changes in the theta power as well

as in the neuronal phase-locking amount indicate that in

slow wave sleep, the ability of the hippocampus to detect

novelty, although present, may be decreased. This is

consistent with the noticeable decrease in awareness of the

environment during sleep while auditory learning was

reported during slow wave sleep in newborn humans [6],

supporting the slow wave sleep capacity to process

information [37].

The differences we observed between the quiet wakeful-

ness and sleep, recording from the same neuron, agree with

the hypothesis that induced activity, the theta rhythm in this

particular case, plays a functional role reflecting changes in

the parameters controlling dynamic interactions within and

between brain structures [2,3,32].

Since visual LGn and auditory neuronal firing do not

cease in wakefulness nor in slow wave sleep [10,37],

either analyzing the evoked activity (Fig. 3, window A) or

the spontaneous one (Fig. 3, windows B and C), we

postulate that the temporal pattern of spikes and theta

phase-locking are important factors that may reflect

whether or not the brain is aware of temporal changes in

the environment, i.e., processing information, even during

slow wave sleep.

Acknowledgments

We are grateful to Prof. Peter M. Narins (UCLA) and Dr.

Jose L. Pena (Caltech) for reading the manuscript and their

very valuable suggestions. Grants: Partially supported by the

Program for Basic Science Development (PEDECIBA),

Ministerio de Educacion y Cultura—Universidad de la

Republica—United Nations Development Program (UNDP).

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