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1.  Sleep and the Price of Plasticity: From Synaptic and Cellular Homeostasis to Memory Consolidation and Integration 
Neuron  2014;81(1):12-34.
Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the off-line, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This review considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity.
PMCID: PMC3921176  PMID: 24411729
2.  Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity 
PLoS Computational Biology  2014;10(12):e1003966.
Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure. We investigated the evolution of small, adaptive logic-gate networks (“animats”) in task environments where falling blocks of different sizes have to be caught or avoided in a ‘Tetris-like’ game. Solving these tasks requires the integration of sensor inputs and memory. Evolved networks were evaluated using measures of information integration, including the number of evolved concepts and the total amount of integrated conceptual information. The results show that, over the course of the animats' adaptation, i) the number of concepts grows; ii) integrated conceptual information increases; iii) this increase depends on the complexity of the environment, especially on the requirement for sequential memory. These results suggest that the need to capture the causal structure of a rich environment, given limited sensors and internal mechanisms, is an important driving force for organisms to develop highly integrated networks (“brains”) with many concepts, leading to an increase in their internal complexity.
Author Summary
The capacity to integrate information is a prominent feature of biological brains and has been related to cognitive flexibility as well as consciousness. To investigate how environment complexity affects the capacity for information integration, we simulated the evolution of artificial organisms (“animats”) controlled by small, adaptive neuron-like networks (“brains”). Task environments varied in difficulty due primarily to the requirements for internal memory. By applying measures of information integration, we show that, under constraints on the number of available internal elements, the animats evolved brains that were the more integrated the more internal memory was required to solve a given task. Thus, in complex environments with a premium on context-sensitivity and memory, integrated brain architectures have an evolutionary advantage over modular ones.
PMCID: PMC4270440  PMID: 25521484
3.  Disrupted directed connectivity along the cingulate cortex determines vigilance after sleep deprivation 
NeuroImage  2013;79:213-222.
The cingulate cortex is regarded as the backbone of structural and functional connectivity of the brain. While its functional connectivity has been intensively studied, little is known about its effective connectivity, its modulation by behavioral states, and its involvement in cognitive performance. Given their previously reported effects on cingulate functional connectivity, we investigated how eye-closure and sleep deprivation changed cingulate effective connectivity, estimated from resting-state high-density electroencephalography (EEG) using a novel method to calculate Granger Causality directly in source space.
Effective connectivity along the cingulate cortex was dominant in the forward direction. Eyes-open connectivity in the forward direction was greater compared to eyes-closed, in well-rested participants. The difference between eyes-open and eyes-closed connectivity was attenuated and no longer significant after sleep deprivation. Individual variability in the forward connectivity after sleep deprivation predicted subsequent task performance, such that those subjects who showed a greater increase in forward connectivity between the eyes-open and the eyes-closed periods also performed better on a sustained attention task. Effective connectivity in the opposite, backward, direction was not affected by whether the eyes were open or closed or by sleep deprivation.
These findings indicate that the effective connectivity from posterior to anterior cingulate regions is enhanced when a well-rested subject has his eyes open compared to when they are closed. Sleep deprivation impairs this directed information flow, proportional to its deleterious effect on vigilance. Therefore, sleep may play a role in the maintenance of waking effective connectivity.
PMCID: PMC3703622  PMID: 23643925
Effective connectivity; EEG; cingulate cortex; resting state; sleep deprivation; vigilance
4.  Prolonged wakefulness alters neuronal responsiveness to local electrical stimulation of the neocortex in awake rats 
Journal of sleep research  2012;10.1111/jsr.12009.
Prolonged wakefulness or a lack of sleep lead to cognitive deficits, but little is known about the underlying cellular mechanisms. We recently found that sleep deprivation affects spontaneous neuronal activity in the neocortex of sleeping and awake rats. While it is well known that synaptic responses are modulated by ongoing cortical activity, it remains unclear whether prolonged waking affects responsiveness of cortical neurons to incoming stimuli. By applying local electrical microstimulation to the frontal area of the neocortex, we found that after a 4-hour period of waking the initial neuronal response in the contralateral frontal cortex was stronger and more synchronous, and was followed by a more profound inhibition of neuronal spiking as compared to the control condition. These changes in evoked activity suggest increased neuronal excitability and indicate that after staying awake cortical neurons become transiently bistable. We propose that some of the detrimental effects of sleep deprivation may be a result of altered neuronal responsiveness to incoming intrinsic and extrinsic inputs.
PMCID: PMC3723708  PMID: 23607417
sleep; LFP; evoked responses; cerebral cortex; multi-unit recording; prolonged wakefulness
5.  From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0 
PLoS Computational Biology  2014;10(5):e1003588.
This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific – it is what it is by how it differs from alternative experiences; integration says that it is unified – irreducible to non-interdependent components; exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as “differences that make a difference” within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information ΦMax its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes; the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment; anatomical connectivity influences complexes and associated MICS; a complex can generate a MICS even if its elements are inactive; simple systems can be minimally conscious; complicated systems can be unconscious; there can be true “zombies” – unconscious feed-forward systems that are functionally equivalent to conscious complexes.
Author Summary
Integrated information theory (IIT) approaches the relationship between consciousness and its physical substrate by first identifying the fundamental properties of experience itself: existence, composition, information, integration, and exclusion. IIT then postulates that the physical substrate of consciousness must satisfy these very properties. We develop a detailed mathematical framework in which composition, information, integration, and exclusion are defined precisely and made operational. This allows us to establish to what extent simple systems of mechanisms, such as logic gates or neuron-like elements, can form complexes that can account for the fundamental properties of consciousness. Based on this principled approach, we show that IIT can explain many known facts about consciousness and the brain, leads to specific predictions, and allows us to infer, at least in principle, both the quantity and quality of consciousness for systems whose causal structure is known. For example, we show that some simple systems can be minimally conscious, some complicated systems can be unconscious, and two different systems can be functionally equivalent, yet one is conscious and the other one is not.
PMCID: PMC4014402  PMID: 24811198
6.  Effects of Sleep and Wake on Oligodendrocytes and Their Precursors 
The Journal of Neuroscience  2013;33(36):14288-14300.
Previous studies of differential gene expression in sleep and wake pooled transcripts from all brain cells and showed that several genes expressed at higher levels during sleep are involved in the synthesis/maintenance of membranes in general and of myelin in particular, a surprising finding given the reported slow turnover of many myelin components. Other studies showed that oligodendrocyte precursor cells (OPCs) are responsible for the formation of new myelin in both the injured and the normal adult brain, and that glutamate released from neurons, via neuron–OPC synapses, can inhibit OPC proliferation and affect their differentiation into myelin-forming oligodendrocytes. Because glutamatergic transmission is higher in wake than in sleep, we asked whether sleep and wake can affect oligodendrocytes and OPCs. Using the translating ribosome affinity purification technology combined with microarray analysis in mice, we obtained a genome-wide profiling of oligodendrocytes after sleep, spontaneous wake, and forced wake (acute sleep deprivation). We found that hundreds of transcripts being translated in oligodendrocytes are differentially expressed in sleep and wake: genes involved in phospholipid synthesis and myelination or promoting OPC proliferation are transcribed preferentially during sleep, while genes implicated in apoptosis, cellular stress response, and OPC differentiation are enriched in wake. We then confirmed through BrdU and other experiments that OPC proliferation doubles during sleep and positively correlates with time spent in REM sleep, whereas OPC differentiation is higher during wake. Thus, OPC proliferation and differentiation are not perfectly matched at any given circadian time but preferentially occur during sleep and wake, respectively.
PMCID: PMC3874087  PMID: 24005282
7.  Concomitant BDNF and sleep slow wave changes indicate ketamine-induced plasticity in major depressive disorder 
The N-methyl-d-aspartate (NMDA) receptor antagonist ketamine has rapid antidepressant effects in treatment-resistant major depressive disorder (MDD). In rats, ketamine selectively increased electro-encephalogram (EEG) slow wave activity (SWA) during non-rapid eye movement (REM) sleep and altered central brain-derived neurotrophic factor (BDNF) expression. Taken together, these findings suggest that higher SWA and BDNF levels may respectively represent electrophysiological and molecular correlates of mood improvement following ketamine treatment. This study investigated the acute effects of a single ketamine infusion on depressive symptoms, EEG SWA, individual slow wave parameters (surrogate markers of central synaptic plasticity) and plasma BDNF (a peripheral marker of plasticity) in 30 patients with treatment-resistant MDD. Montgomery–Åsberg Depression Rating Scale scores rapidly decreased following ketamine. Compared to baseline, BDNF levels and early sleep SWA (during the first non-REM episode) increased after ketamine. The occurrence of high amplitude waves increased during early sleep, accompanied by an increase in slow wave slope, consistent with increased synaptic strength. Changes in BDNF levels were proportional to changes in EEG parameters. Intriguingly, this link was present only in patients who responded to ketamine treatment, suggesting that enhanced synaptic plasticity–as reflected by increased SWA, individual slow wave parameters and plasma BDNF–is part of the physiological mechanism underlying the rapid antidepressant effects of NMDA antagonists. Further studies are required to confirm the link found here between behavioural and synaptic changes, as well as to test the reliability of these central and peripheral biomarkers of rapid antidepressant response.
PMCID: PMC3510337  PMID: 22676966
biomarker; brain derived neurotrophic factor; major depressive disorder; N-methyl-d-aspartate receptor; sleep slow wave activity
8.  Human Cortical Excitability Increases with Time Awake 
Cerebral Cortex (New York, NY)  2012;23(2):332-338.
Prolonged wakefulness is associated not only with obvious changes in the way we feel and perform but also with well-known clinical effects, such as increased susceptibility to seizures, to hallucinations, and relief of depressive symptoms. These clinical effects suggest that prolonged wakefulness may be associated with significant changes in the state of cortical circuits. While recent animal experiments have reported a progressive increase of cortical excitability with time awake, no conclusive evidence could be gathered in humans. In this study, we combine transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to monitor cortical excitability in healthy individuals as a function of time awake. We observed that the excitability of the human frontal cortex, measured as the immediate (0–20 ms) EEG reaction to TMS, progressively increases with time awake, from morning to evening and after one night of total sleep deprivation, and that it decreases after recovery sleep. By continuously monitoring vigilance, we also found that this modulation in cortical responsiveness is tonic and not attributable to transient fluctuations of the level of arousal. The present results provide noninvasive electrophysiological evidence that wakefulness is associated with a steady increase in the excitability of human cortical circuits that is rebalanced during sleep.
PMCID: PMC3539451  PMID: 22314045
compensatory tracking task; EEG; human cortical excitability; sleep deprivation; transcranial magnetic stimulation
Journal of neurochemistry  2012;124(1):79-89.
Most of the energy in the brain comes from glucose and supports glutamatergic activity. The firing rate of cortical glutamatergic neurons, as well as cortical extracellular glutamate levels, increase with time spent awake and decline throughout non rapid eye movement (NREM) sleep, raising the question whether glucose levels reflect behavioral state and sleep/wake history. Here chronic (2–3 days) electroencephalographic (EEG) recordings in the rat cerebral cortex were coupled with fixed-potential amperometry to monitor the extracellular concentration of glucose ([gluc]) on a second-by-second basis across the spontaneous sleep-wake cycle and in response to 3 hours of sleep deprivation. [Gluc] progressively increased during NREM sleep and declined during REM sleep, while during wake an early decline in [gluc] was followed by an increase 8–15 minutes after awakening. There was a significant time of day effect during the dark phase, when rats are mostly awake, with [gluc] being significantly lower during the last 3–4 hours of the night relative to the first 3–4 hours. Moreover, the duration of the early phase of [gluc] decline during wake was longer after prolonged wake than after consolidated sleep. Thus, the sleep/wake history may affect the levels of glucose available to the brain upon awakening.
PMCID: PMC3518620  PMID: 23106535
glucose; in vivo amperometry; sleep; rat; cerebral cortex; EEG; slow wave activity
10.  Enhancement of sleep slow waves: underlying mechanisms and practical consequences 
Even modest sleep restriction, especially the loss of sleep slow wave activity (SWA), is invariably associated with slower electroencephalogram (EEG) activity during wake, the occurrence of local sleep in an otherwise awake brain, and impaired performance due to cognitive and memory deficits. Recent studies not only confirm the beneficial role of sleep in memory consolidation, but also point to a specific role for sleep slow waves. Thus, the implementation of methods to enhance sleep slow waves without unwanted arousals or lightening of sleep could have significant practical implications. Here we first review the evidence that it is possible to enhance sleep slow waves in humans using transcranial direct-current stimulation (tDCS) and transcranial magnetic stimulation. Since these methods are currently impractical and their safety is questionable, especially for chronic long-term exposure, we then discuss novel data suggesting that it is possible to enhance slow waves using sensory stimuli. We consider the physiology of the K-complex (KC), a peripheral evoked slow wave, and show that, among different sensory modalities, acoustic stimulation is the most effective in increasing the magnitude of slow waves, likely through the activation of non-lemniscal ascending pathways to the thalamo-cortical system. In addition, we discuss how intensity and frequency of the acoustic stimuli, as well as exact timing and pattern of stimulation, affect sleep enhancement. Finally, we discuss automated algorithms that read the EEG and, in real-time, adjust the stimulation parameters in a closed-loop manner to obtain an increase in sleep slow waves and avoid undesirable arousals. In conclusion, while discussing the mechanisms that underlie the generation of sleep slow waves, we review the converging evidence showing that acoustic stimulation is safe and represents an ideal tool for slow wave sleep (SWS) enhancement.
PMCID: PMC4211398  PMID: 25389394
EEG; acoustic stimulation; arousal systems; closed-loop; NREM sleep
11.  Conserved Functional Connectivity but Impaired Effective Connectivity of Thalamocortical Circuitry in Schizophrenia 
Brain Connectivity  2012;2(6):311-319.
Schizophrenia is a severe mental illness with neurobiological bases that remain elusive. One hypothesis emphasizes disordered thalamic function. We previously used concurrent single pulse transcranial magnetic stimulation (spTMS) and functional magnetic resonance imaging (fMRI) to show that individuals with schizophrenia have a decreased spTMS-evoked response in the thalamus, and decreased effective connectivity between thalamus and insula and thalamus and superior frontal gyrus. To better understand the factors that may accompany or account for these findings, we investigated, in the same participants, resting state functional connectivity, white matter structural connectivity, and grey matter integrity. Patients with schizophrenia did not differ from healthy control subjects in resting state functional- or white matter structural connectivity, although they did show decreased measures of grey matter integrity in the insula. However, in this region, the spTMS-evoked response did not differ between groups. In a region of the thalamus that also had grey matter intensity abnormalities, although not at a level that survived correction for multiple comparisons, the spTMS-evoked response in patients was deficient. These results suggest that measures of structure and function are not necessarily complementary. Further, given its sensitivity for identifying deficits not evident with traditional imaging methods, these results highlight the utility of spTMS-fMRI, a method that directly and causally probes effective connectivity, as a tool for studying brain-based disorders.
PMCID: PMC3621336  PMID: 23020103
connectivity; DTI; fMRI; thalamus; schizophrenia; VBM
12.  Sleep-Dependent Synaptic Down-Selection (II): Single-Neuron Level Benefits for Matching, Selectivity, and Specificity 
In a companion paper (1), we used computer simulations to show that a strategy of activity-dependent, on-line net synaptic potentiation during wake, followed by off-line synaptic depression during sleep, can provide a parsimonious account for several memory benefits of sleep at the systems level, including the consolidation of procedural and declarative memories, gist extraction, and integration of new with old memories. In this paper, we consider the theoretical benefits of this two-step process at the single-neuron level and employ the theoretical notion of Matching between brain and environment to measure how this process increases the ability of the neuron to capture regularities in the environment and model them internally. We show that down-selection during sleep is beneficial for increasing or restoring Matching after learning, after integrating new with old memories, and after forgetting irrelevant material. By contrast, alternative schemes, such as additional potentiation in wake, potentiation in sleep, or synaptic renormalization in wake, decrease Matching. We also argue that, by selecting appropriate loops through the brain that tie feedforward synapses with feedback ones in the same dendritic domain, different subsets of neurons can learn to specialize for different contingencies and form sequences of nested perception-action loops. By potentiating such loops when interacting with the environment in wake, and depressing them when disconnected from the environment in sleep, neurons can learn to match the long-term statistical structure of the environment while avoiding spurious modes of functioning and catastrophic interference. Finally, such a two-step process has the additional benefit of desaturating the neuron’s ability to learn and of maintaining cellular homeostasis. Thus, sleep-dependent synaptic renormalization offers a parsimonious account for both cellular and systems level effects of sleep on learning and memory.
PMCID: PMC3790262  PMID: 24151486
neurons; plasticity and learning; sleep; homeostatic regulation; information
13.  Sleep-Dependent Synaptic Down-Selection (I): Modeling the Benefits of Sleep on Memory Consolidation and Integration 
Sleep can favor the consolidation of both procedural and declarative memories, promote gist extraction, help the integration of new with old memories, and desaturate the ability to learn. It is often assumed that such beneficial effects are due to the reactivation of neural circuits in sleep to further strengthen the synapses modified during wake or transfer memories to different parts of the brain. A different possibility is that sleep may benefit memory not by further strengthening synapses, but rather by renormalizing synaptic strength to restore cellular homeostasis after net synaptic potentiation in wake. In this way, the sleep-dependent reactivation of neural circuits could result in the competitive down-selection of synapses that are activated infrequently and fit less well with the overall organization of memories. By using computer simulations, we show here that synaptic down-selection is in principle sufficient to explain the beneficial effects of sleep on the consolidation of procedural and declarative memories, on gist extraction, and on the integration of new with old memories, thereby addressing the plasticity-stability dilemma.
PMCID: PMC3786405  PMID: 24137153
neurons; plasticity and learning; sleep; homeostatic regulation; declarative memory; procedural memory
14.  Experienced Mindfulness Meditators Exhibit Higher Parietal-Occipital EEG Gamma Activity during NREM Sleep 
PLoS ONE  2013;8(8):e73417.
Over the past several years meditation practice has gained increasing attention as a non-pharmacological intervention to provide health related benefits, from promoting general wellness to alleviating the symptoms of a variety of medical conditions. However, the effects of meditation training on brain activity still need to be fully characterized. Sleep provides a unique approach to explore the meditation-related plastic changes in brain function. In this study we performed sleep high-density electroencephalographic (hdEEG) recordings in long-term meditators (LTM) of Buddhist meditation practices (approximately 8700 mean hours of life practice) and meditation naive individuals. We found that LTM had increased parietal-occipital EEG gamma power during NREM sleep. This increase was specific for the gamma range (25–40 Hz), was not related to the level of spontaneous arousal during NREM and was positively correlated with the length of lifetime daily meditation practice. Altogether, these findings indicate that meditation practice produces measurable changes in spontaneous brain activity, and suggest that EEG gamma activity during sleep represents a sensitive measure of the long-lasting, plastic effects of meditative training on brain function.
PMCID: PMC3756031  PMID: 24015304
15.  Assessing sleep consciousness within subjects using a serial awakening paradigm 
Dreaming—a particular form of consciousness that occurs during sleep—undergoes major changes in the course of the night. We aimed to outline state-dependent features of consciousness using a paradigm with multiple serial awakenings/questionings that allowed for within as well as between subject comparisons. Seven healthy participants who spent 44 experimental study nights in the laboratory were awakened by a computerized sound at 15–30 min intervals, regardless of sleep stage, and questioned for the presence or absence of sleep consciousness. Recall without content (“I was experiencing something but do not remember what”) was considered separately. Subjects had to indicate the content of the most recent conscious experience prior to the alarm sound and to estimate its duration and richness. We also assessed the degree of thinking and perceiving, self- and environment-relatedness and reflective consciousness of the experiences. Of the 778 questionings, 5% were performed during wakefulness, 2% in stage N1, 42% in N2, 33% in N3, and 17% in rapid eye movement (REM) sleep. Recall with content was reported in 34% of non-REM and in 77% of REM sleep awakenings. Sleep fragmentation inherent to the study design appeared to only minimally affect the recall of conscious experiences. Each stage displayed a unique combination of characteristic features of sleep consciousness. In conclusion, our serial awakening paradigm allowed us to collect a large and representative sample of conscious experiences across states of being. It represents a time-efficient method for the study of sleep consciousness that may prove particularly advantageous when combined with techniques such as functional MRI and high-density EEG.
PMCID: PMC3747360  PMID: 23970876
consciousness; sleep; dreaming; wakefulness; EEG
16.  Reduced natural oscillatory frequency of frontal thalamo-cortical circuits in schizophrenia 
Archives of general psychiatry  2012;69(8):766-774.
Converging evidence from electrophysiological studies suggests that in individuals with schizophrenia EEG fast frontal oscillations are reduced. It is still unclear whether this reduction reflects an intrinsic deficit of underlying cortical/thalamo-cortical circuits, and whether this deficit is specific for frontal regions. Recent electrophysiological studies in healthy individuals have established that, when perturbed, different brain regions oscillate at a specific, intrinsically generated dominant frequency, the natural frequency.
To assess the natural frequency of posterior parietal, motor, premotor, and prefrontal cortices, in schizophrenic and healthy controls.
High-density electroencephalogram (Hd-EEG) recordings during Transcranial Magnetic Stimulation (TMS) of four cortical areas were performed. Several TMS-evoked EEG oscillation parameters, including synchronization, amplitude, and natural frequency were compared across the schizophrenia and healthy control groups.
Wisconsin Psychiatric Institute & Clinic, University of Wisconsin-Madison
Twenty patients with schizophrenia and twenty age-matched healthy controls.
Main Outcome Measures
Hd-EEG measurements of TMS-evoked activity in four cortical areas, the positive and negative syndrome scale (PANSS), and performance scores (reaction time, accuracy) in two computerized tasks: the word memory (CPW) and the facial memory (CPF) tests.
Schizophrenia patients showed a slowing in the natural frequency of frontal/prefrontal regions compared to healthy controls (from an average of 2 Hz decrease for the motor area, to almost 10 Hz for the prefrontal cortex). The prefrontal natural frequency of individuals with schizophrenia was slower than in any healthy comparison subject, and correlated with both positive PANSS scores and reaction time in the CPW.
These findings suggest that patients with schizophrenia have an intrinsic slowing in the natural frequency of frontal cortical/thalamo-cortical circuits, that this slowing is not present in parietal areas, and that the prefrontal natural frequency can predict some of the symptoms as well as the cognitive dysfunctions of schizophrenia.
PMCID: PMC3394893  PMID: 22474071
17.  The Minimal Complexity of Adapting Agents Increases with Fitness 
PLoS Computational Biology  2013;9(7):e1003111.
What is the relationship between the complexity and the fitness of evolved organisms, whether natural or artificial? It has been asserted, primarily based on empirical data, that the complexity of plants and animals increases as their fitness within a particular environment increases via evolution by natural selection. We simulate the evolution of the brains of simple organisms living in a planar maze that they have to traverse as rapidly as possible. Their connectome evolves over 10,000s of generations. We evaluate their circuit complexity, using four information-theoretical measures, including one that emphasizes the extent to which any network is an irreducible entity. We find that their minimal complexity increases with their fitness.
Author Summary
It has often been asserted that as organisms adapt to natural environments with many independent forces and actors acting over a variety of different time scales, they become more complex. We investigate this question from the point of view of information theory as applied to the nervous systems of simple creatures evolving in a stereotyped environment. We performed a controlled in silico evolution experiment to study the relationship between complexity, as measured using different information-theoretic measures, and fitness, by evolving animats with brains of twelve binary variables over 60,000 generations. We compute the complexity of these evolved networks using three measures based on mutual information and one measure based on the extent to which their brain contain states that are both differentiated and integrated. All measures show the same trend - the minimal complexity at any one fitness level increases as the organisms become more adapted to their environment, that is, as they become fitter. Above this minimum, there exists a large degree of degeneracy in evidence.
PMCID: PMC3708884  PMID: 23874168
18.  Probing thalamic integrity in schizophrenia using concurrent transcranial magnetic stimulation and functional magnetic resonance imaging 
Archives of general psychiatry  2012;69(7):662-671.
Schizophrenia is a devastating illness with an indeterminate pathophysiology. Several lines of evidence implicate dysfunction in the thalamus, a key node in the distributed neural networks underlying perception, emotion, and cognition. Existing evidence of aberrant thalamic function is based on indirect measures of thalamic activity, but dysfunction has not yet been demonstrated with a causal method.
Test the hypothesis that direct physiological stimulation of cortex will produce an abnormal thalamic response in individuals with schizophrenia.
We stimulated the precentral gyrus with single-pulse transcranial magnetic stimulation (spTMS) and measured the response to this pulse in synaptically-connected regions (thalamus, medial superior frontal cortex [mSFG], insula) using concurrent functional magnetic resonance imaging (fMRI). The mean hemodynamic response from these regions was fit with the sum of two gamma functions and response parameters were compared across groups.
Academic research laboratory.
Patients with schizophrenia and sex- and age- matched psychiatrically healthy subjects were recruited from the community.
Main Outcome Measures
Peak amplitude of the thalamic hemodynamic response to spTMS of precentral gyrus.
spTMS-evoked responses did not differ between groups at the cortical stimulation site. Compared to healthy subjects, schizophrenia patients showed a reduced response to spTMS in the thalamus (P=1.86 × 10−9) and mSFG (P=.02). Similar results were observed in the insula. Sham TMS indicated that these results could not be attributed to indirect effects of TMS coil discharge. Functional connectivity analyses revealed weaker thalamus-mSFG and thalamus-insula connectivity in schizophrenia patients compared to control subjects.
Individuals with schizophrenia showed reduced thalamic activation in response to direct perturbation delivered to the cortex. These results extend prior work implicating the thalamus in the pathophysiology of schizophrenia and suggest that the thalamus contributes to the patterns of aberrant connectivity characteristic of this disease.
PMCID: PMC3411883  PMID: 22393203
19.  Sleep Patterns and Homeostatic Mechanisms in Adolescent Mice 
Brain sciences  2013;3(1):318-343.
Sleep changes were studied in mice (n = 59) from early adolescence to adulthood (postnatal days P19–111). REM sleep declined steeply in early adolescence, while total sleep remained constant and NREM sleep increased slightly. Four hours of sleep deprivation starting at light onset were performed from ages P26 through adulthood (>P60). Following this acute sleep deprivation all mice slept longer and with more consolidated sleep bouts, while NREM slow wave activity (SWA) showed high interindividual variability in the younger groups, and increased consistently only after P42. Three parameters together explained up to 67% of the variance in SWA rebound in frontal cortex, including weight-adjusted age and increase in alpha power during sleep deprivation, both of which positively correlated with the SWA response. The third, and strongest predictor was the SWA decline during the light phase in baseline: mice with high peak SWA at light onset, resulting in a large SWA decline, were more likely to show no SWA rebound after sleep deprivation, a result that was also confirmed in parietal cortex. During baseline, however, SWA showed the same homeostatic changes in adolescents and adults, declining in the course of sleep and increasing across periods of spontaneous wake. Thus, we hypothesize that, in young adolescent mice, a ceiling effect and not the immaturity of the cellular mechanisms underlying sleep homeostasis may prevent the SWA rebound when wake is extended beyond its physiological duration.
PMCID: PMC3682503  PMID: 23772316
adolescence; cerebral cortex; sleep deprivation; slow wave activity
20.  Neural Activations during Visual Sequence Learning Leave a Trace in Post-Training Spontaneous EEG 
PLoS ONE  2013;8(6):e65882.
Recent EEG studies have shown that implicit learning involving specific cortical circuits results in an enduring local trace manifested as local changes in spectral power. Here we used a well characterized visual sequence learning task and high density-(hd-)EEG recording to determine whether also declarative learning leaves a post-task, local change in the resting state oscillatory activity in the areas involved in the learning process. Thus, we recorded hd-EEG in normal subjects before, during and after the acquisition of the order of a fixed spatial target sequence (VSEQ) and during the presentation of targets in random order (VRAN). We first determined the temporal evolution of spectral changes during VSEQ and compared it to VRAN. We found significant differences in the alpha and theta bands in three main scalp regions, a right occipito-parietal (ROP), an anterior-frontal (AFr), and a right frontal (RFr) area. The changes in frontal theta power during VSEQ were positively correlated with the learning rate. Further, post-learning EEG recordings during resting state revealed a significant increase in alpha power in ROP relative to a pre-learning baseline. We conclude that declarative learning is associated with alpha and theta changes in frontal and posterior regions that occur during the task, and with an increase of alpha power in the occipito-parietal region after the task. These post-task changes may represent a trace of learning and a hallmark of use-dependent plasticity.
PMCID: PMC3683043  PMID: 23799058
21.  Overnight changes in waking auditory evoked potential amplitude reflect altered sleep homeostasis in major depression 
Acta Psychiatrica Scandinavica  2011;125(6):468-477.
Sleep homeostasis is altered in major depressive disorder (MDD). Pre-to post-sleep decline in waking auditory evoked potential (AEP) amplitude has been correlated with sleep slow wave activity (SWA), suggesting that overnight changes in waking AEP amplitude are homeostatically regulated in healthy individuals. This study investigated whether the overnight change in waking AEP amplitude and its relation to SWA is altered in MDD.
Using 256-channel high-density electroencephalography, all-night sleep polysomnography and single-tone waking AEPs pre-and post-sleep were collected in 15 healthy controls (HC) and 15 non-medicated individuals with MDD.
N1 and P2 amplitudes of the waking AEP declined after sleep in the HC group, but not in MDD. The reduction in N1 amplitude also correlated with fronto-central SWA in the HC group, but a comparable relationship was not found in MDD, despite equivalent SWA between groups. No pre-to post-sleep differences were found for N1 or P2 latencies in either group. These findings were not confounded by varying levels of alertness or differences in sleep variables between groups.
MDD involves altered sleep homeostasis as measured by the overnight change in waking AEP amplitude. Future research is required to determine the clinical implications of these findings.
PMCID: PMC3303968  PMID: 22097901
major depressive disorder; auditory evoked potentials; sleep; homeostasis; slow-wave sleep
22.  Altered slow wave activity in major depressive disorder with hypersomnia: a high density EEG pilot study 
Psychiatry Research  2012;201(3):240-244.
Hypersomnolence in major depressive disorder (MDD) plays an important role in the natural history of the disorder, but the basis of hypersomnia in MDD is poorly understood. Slow wave activity (SWA) has been associated with sleep homeostasis, as well as sleep restoration and maintenance, and may be altered in MDD. Therefore, we conducted a post-hoc study that utilized high density electroencephalography (hdEEG) to test the hypothesis that MDD subjects with hypersomnia (HYS+) would have decreased SWA relative to age and sex-matched MDD subjects without hypersomnia (HYS−) and healthy controls (n=7 for each group). After correcting for multiple comparisons using statistical non-parametric mapping, HYS+ subjects demonstrated significantly reduced parieto-occipital all-night SWA relative to HYS− subjects. Our results suggest hypersomnolence may be associated with topographic reductions in SWA in MDD. Further research using adequately powered prospective design is indicated to confirm these findings.
PMCID: PMC3361575  PMID: 22512951
sleep; depression; spectral analysis
23.  Unresponsiveness ≠ Unconsciousness 
Anesthesiology  2012;116(4):946-959.
Consciousness is subjective experience. During both sleep and anesthesia consciousness is common, evidenced by dreaming. A defining feature of dreaming is that, while conscious, we do not experience our environment – we are disconnected. Besides inducing behavioral unresponsiveness, a key goal of anesthesia is to prevent the experience of surgery (connected consciousness), by inducing either unconsciousness or disconnection of consciousness from the environment. Review of the isolated forearm technique demonstrates that consciousness, connectedness and responsiveness uncouple during anesthesia; in clinical conditions, a median 37% of patients demonstrate connected consciousness. We describe potential neurobiological constructs that can explain this phenomenon: during light anesthesia the subcortical mechanisms subserving spontaneous behavioral responsiveness are disabled but information integration within the corticothalamic network continues to produce consciousness, and unperturbed norepinephrinergic signaling maintains connectedness. These concepts emphasize the need for developing anesthetic regimens and depth of anesthesia monitors that specifically target mechanisms of consciousness, connectedness and responsiveness.
PMCID: PMC3311716  PMID: 22314293
24.  Sleep Patterns and Homeostatic Mechanisms in Adolescent Mice 
Brain Sciences  2013;3(1):318-343.
Sleep changes were studied in mice (n = 59) from early adolescence to adulthood (postnatal days P19–111). REM sleep declined steeply in early adolescence, while total sleep remained constant and NREM sleep increased slightly. Four hours of sleep deprivation starting at light onset were performed from ages P26 through adulthood (>P60). Following this acute sleep deprivation all mice slept longer and with more consolidated sleep bouts, while NREM slow wave activity (SWA) showed high interindividual variability in the younger groups, and increased consistently only after P42. Three parameters together explained up to 67% of the variance in SWA rebound in frontal cortex, including weight-adjusted age and increase in alpha power during sleep deprivation, both of which positively correlated with the SWA response. The third, and strongest predictor was the SWA decline during the light phase in baseline: mice with high peak SWA at light onset, resulting in a large SWA decline, were more likely to show no SWA rebound after sleep deprivation, a result that was also confirmed in parietal cortex. During baseline, however, SWA showed the same homeostatic changes in adolescents and adults, declining in the course of sleep and increasing across periods of spontaneous wake. Thus, we hypothesize that, in young adolescent mice, a ceiling effect and not the immaturity of the cellular mechanisms underlying sleep homeostasis may prevent the SWA rebound when wake is extended beyond its physiological duration.
PMCID: PMC3682503  PMID: 23772316
adolescence; cerebral cortex; sleep deprivation; slow wave activity
25.  Functional connectivity in slow-wave sleep: identification of synchronous cortical activity during wakefulness and sleep using time series analysis of electroencephalographic data 
Journal of sleep research  2011;20(4):496-505.
Sleep is a behavioral state ideal for studying functional connectivity because it minimizes many sources of between-subject variability that confound waking analyses. This is particularly important for potential connectivity studies in mental illness where cognitive ability, internal milieu and active psychotic symptoms can vary widely across subjects. We, therefore, sought to adapt techniques applied to magnetoencephalography for use in high-density electroencephalography (EEG), the gold-standard in brain-recording methods during sleep. Autoregressive integrative moving average modeling was used to reduce spurious correlations between recording sites (electrodes) in order to identify functional networks. We hypothesized that identified network characteristics would be similar to those found with magnetoencephalography, and would demonstrate sleep stage-related differences in a control population. We analysed 60-s segments of low-artifact data from seven healthy human subjects during wakefulness and sleep. EEG analysis of eyes-closed wakefulness revealed widespread nearest-neighbor positive synchronous interactions, similar to magnetoencephalography, though less consistent across subjects. Rapid eye movement sleep demonstrated positive synchronous interactions akin to wakefulness but weaker. Slow-wave sleep (SWS), instead, showed strong positive interactions in a large left fronto-temporal-parietal cluster markedly more consistent across subjects. Comparison of connectivity from early SWS to SWS from a later sleep cycle indicated sleep-related reduction in connectivity in this region. The consistency of functional connectivity during SWS within and across subjects suggests this may be a promising technique for comparing functional connectivity between mental illness and health.
PMCID: PMC3134541  PMID: 21281369
electroencephalography; functional connectivity; sleep; synchrony

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