Oscillations in the central brain of Drosophila are phase locked to attended visual features

Inferring Consciousness in Phylogenetically Distant Organisms

The neural dynamics of subjectivity (NDS) approach to the biological explanation of consciousness is outlined and applied to the problem of inferring consciousness in animals phylogenetically distant from ourselves. The NDS approach holds that consciousness or felt experience is characteristic of systems whose nervous systems have been shaped to realize subjectivity through a combination of network interactions and large-scale dynamic patterns. Features of the vertebrate brain architecture that figure in other accounts of the biology of consciousness are viewed as inessential. Deep phylogenetic branchings in the animal kingdom occurred before the evolution of complex behavior, cognition, and sensing. These capacities arose independently in brain architectures that differ widely across arthropods, vertebrates, and cephalopods, but with conservation of large-scale dynamic patterns of a kind that have an apparent link to felt experience in humans. An evolutionary perspective also motivates a strongly gradualist view of consciousness; a simple distinction between conscious and nonconscious animals will probably be replaced with a view that admits differences of degree, perhaps on many dimensions.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Identifying different sleep stages in humans and other mammals has traditionally relied on electroencephalograms. Such an approach is not feasible in certain animals such as invertebrates, although these animals could also be sleeping in stages. Here, we perform long-term multichannel local field potential recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We acquired consistent spatial recordings of local field potentials across multiple flies, allowing us to compare brain activity across awake and sleep periods. Using machine learning, we uncover distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of microbehaviors associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Sleep is observed in most animals, which suggests it subserves a fundamental process associated with adaptive biological functions. However, the evidence to directly associate sleep with a specific function is lacking, in part because sleep is not a single process in many animals. In humans and other mammals, different sleep stages have traditionally been identified using electroencephalograms (EEGs), but such an approach is not feasible in different animals such as insects. Here, we perform long-term multichannel local field potential (LFP) recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We developed protocols to allow for consistent spatial recordings of LFPs across multiple flies, allowing us to compare the LFP activity across awake and sleep periods and further compare the same to induced sleep. Using machine learning, we uncover the existence of distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of micro-behaviours associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

Insect visuomotor delay adjustments in group flight support swarm cohesion

Flying insects routinely demonstrate coordinated flight in crowded assemblies despite strict communication and processing constraints. This study experimentally records multiple flying insects tracking a moving visual stimulus. System identification techniques are used to robustly identify the tracking dynamics, including a visuomotor delay. The population delay distributions are quantified for solo and group behaviors. An interconnected visual swarm model incorporating heterogeneous delays is developed, and bifurcation analysis and swarm simulation are applied to assess swarm stability under the delays. The experiment recorded 450 insect trajectories and quantified visual tracking delay variation. Solitary tasks showed a 30ms average delay and standard deviation of 50ms, while group behaviors show a 15ms average and 8ms standard deviation. Analysis and simulation indicate that the delay adjustments during group flight support swarm formation and center stability, and are robust to measurement noise. These results quantify the role of visuomotor delay heterogeneity in flying insects and their role in supporting swarm cohesion through implicit communication.

Neural Ensemble Fragmentation in the Anesthetized Drosophila Brain

General anesthetics cause a profound loss of behavioral responsiveness in all animals. In mammals, general anesthesia is induced in part by the potentiation of endogenous sleep-promoting circuits, although "deep" anesthesia is understood to be more similar to coma (Brown et al., 2011). Surgically relevant concentrations of anesthetics, such as isoflurane and propofol, have been shown to impair neural connectivity across the mammalian brain (Mashour and Hudetz, 2017; Yang et al., 2021), which presents one explanation why animals become largely unresponsive when exposed to these drugs. It remains unclear whether general anesthetics affect brain dynamics similarly in all animal brains, or whether simpler animals, such as insects, even display levels of neural connectivity that could be disrupted by these drugs. Here, we used whole-brain calcium imaging in behaving female Drosophila flies to investigate whether isoflurane anesthesia induction activates sleep-promoting neurons, and then inquired how all other neurons across the fly brain behave under sustained anesthesia. We were able to track the activity of hundreds of neurons simultaneously during waking and anesthetized states, for spontaneous conditions as well as in response to visual and mechanical stimuli. We compared whole-brain dynamics and connectivity under isoflurane exposure to optogenetically induced sleep. Neurons in the Drosophila brain remain active during general anesthesia as well as induced sleep, although flies become behaviorally inert under both treatments. We identified surprisingly dynamic neural correlation patterns in the waking fly brain, suggesting ensemble-like behavior. These become more fragmented and less diverse under anesthesia but remain wake-like during induced sleep.SIGNIFICANCE STATEMENT When humans are rendered immobile and unresponsive by sleep or general anesthetics, their brains do not shut off - they just change how they operate. We tracked the activity of hundreds of neurons simultaneously in the brains of fruit flies that were anesthetized by isoflurane or genetically put to sleep, to investigate whether these behaviorally inert states shared similar brain dynamics. We uncovered dynamic patterns of neural activity in the waking fly brain, with stimulus-responsive neurons constantly changing through time. Wake-like neural dynamics persisted during induced sleep but became more fragmented under isoflurane anesthesia. This suggests that, like larger brains, the fly brain might also display ensemble-like behavior, which becomes degraded rather than silenced under general anesthesia.

Atomic Magnetometer Achieves Visual Salience Analysis in Drosophila

An atomic magnetometer (AM) was used to non-invasively detect the tiny magnetic field generated by the brain of a single Drosophila. Combined with a visual stimulus system, the AM was used to study the relationship between visual salience and oscillatory activity of the Drosophila brain by analyzing changes in the magnetic field. Oscillatory activity of Drosophila in the 1-20 Hz frequency band was measured with a sensitivity of 20 fT/Hz. The field in the 20-30 Hz band under periodic light stimulation was used to explore the correlation between short-term memory and visual salience. Our method opens a new path to a more flexible method for the investigation of brain activity in Drosophila and other small insects.

Why art? The role of arts in arts and health

This article is an answer to a report called "What is the evidence on the role of the arts in improving health and well-being?" The authors conclude that the arts have an impact on mental and physical health. Yet, the question of the role of the arts remains unanswered. What is and what is not an art effect? Recently, embodied theory has inspired articles on the perception of art. These articles have not yet received attention in the field of Arts and Health. Scholars in psychosomatic medicine have argued for an approach based on recent work in enactive embodied theory to investigate the connection between the body and the mind. The present article examines how key concepts in this theory relate to art. This leads to a discussion of art in terms of empathy-the relation between the internal state of the artist and the internal state of the beholder. I exemplify with a conceptual framework of musical empathy. Implications for health are addressed.

Awareness and consciousness in humans and animals – neural and behavioral correlates in an evolutionary perspective

Awareness or consciousness in the context of stimulus perception can directly be assessed in well controlled test situations with humans via the persons’ reports about their subjective experiences with the stimuli. Since we have no direct access to subjective experiences in animals, their possible awareness or consciousness in stimulus perception tasks has often been inferred from behavior and cognitive abilities previously observed in aware and conscious humans. Here, we analyze published human data primarily on event-related potentials and brain-wave generation during perception and responding to sensory stimuli and extract neural markers (mainly latencies of evoked-potential peaks and of gamma-wave occurrence) indicating that a person became aware or conscious of the perceived stimulus. These neural correlates of consciousness were then applied to sets of corresponding data from various animals including several species of mammals, and one species each of birds, fish, cephalopods, and insects. We found that the neural markers from studies in humans could also successfully be applied to the mammal and bird data suggesting that species in these animal groups can become subjectively aware of and conscious about perceived stimuli. Fish, cephalopod and insect data remained inconclusive. In an evolutionary perspective we have to consider that both awareness of and consciousness about perceived stimuli appear as evolved, attention-dependent options added to the ongoing neural activities of stimulus processing and action generation. Since gamma-wave generation for functional coupling of brain areas in aware/conscious states is energetically highly cost-intensive, it remains to be shown which animal species under which conditions of lifestyle and ecological niche may achieve significant advantages in reproductive fitness by drawing upon these options. Hence, we started our discussion about awareness and consciousness in animals with the question in how far these expressions of brain activity are necessary attributes for perceiving stimuli and responding in an adaptive way.

Gamma rhythms in the visual cortex: functions and mechanisms

Gamma-band activity, peaking around 30–100 Hz in the local field potential's power spectrum, has been found and intensively studied in many brain regions. Although gamma is thought to play a critical role in processing neural information in the brain, its cognitive functions and neural mechanisms remain unclear or debatable. Experimental studies showed that gamma rhythms are stochastic in time and vary with visual stimuli. Recent studies further showed that multiple rhythms coexist in V1 with distinct origins in different species. While all these experimental facts are a challenge for understanding the functions of gamma in the visual cortex, there are many signs of progress in computational studies. This review summarizes and discusses studies on gamma in the visual cortex from multiple perspectives and concludes that gamma rhythms are still a mystery. Combining experimental and computational studies seems the best way forward in the future.

Neuroplastic Changes in the Superior Colliculus and Hippocampus in Self-rewarding Paradigm: Importance of Visual Cues

Coincident excitation via different sensory modalities encoding objects of positive salience is known to facilitate learning and memory. With a view to dissect the contribution of visual cues in inducing adaptive neural changes, we monitored the lever press activity of a rat conditioned to self-administer sweet food pellets in the presence/absence of light cues. Application of light cues facilitated learning and consolidation of long-term memory. The superior colliculus (SC) of rats trained on light cue showed increased neuronal activity, dendritic branching, and brain-derived neurotrophic factor (BDNF) protein and mRNA expression. Concomitantly, the hippocampus showed augmented neurogenesis as well as BDNF protein and mRNA expression. While intra-SC administration of U0126 (inhibitor of ERK 1/2 and long-term memory) impaired memory formation, lidocaine (local anaesthetic) hindered memory recall. The light cue-dependent sweet food pellet self-administration was coupled with increased efflux of dopamine (DA) and 3,4-dihydroxyphenylacetic acid (DOPAC) in the nucleus accumbens shell (AcbSh). In conditioned rats, pharmacological inhibition of glutamatergic signalling in dentate gyrus (DG) reduced lever press activity, as well as DA and DOPAC secretion in the AcbSh. We suggest that the neuroplastic changes in the SC and hippocampus might represent memory engrams sculpted by visual cues encoding reward information.

Balancing Prediction and Surprise: A Role for Active Sleep at the Dawn of Consciousness?

The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising, and this typically evokes prediction error signatures in mammalian brains. In humans such mismatched expectations are often associated with an emotional response as well, and emotional dysregulation can lead to cognitive disorders such as depression or schizophrenia. Emotional responses are understood to be important for memory consolidation, suggesting that positive or negative 'valence' cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolishing error detection and surprise entirely (as could happen by generalization or habituation) is probably maladaptive, as this might undermine the very mechanism that brains use to become better prediction machines. This paradoxical view of brain function as an ongoing balance between prediction and surprise suggests a compelling approach to study and understand the evolution of consciousness in animals. In particular, this view may provide insight into the function and evolution of 'active' sleep. Here, we propose that active sleep - when animals are behaviorally asleep but their brain seems awake - is widespread beyond mammals and birds, and may have evolved as a mechanism for optimizing predictive processing in motile creatures confronted with constantly changing environments. To explore our hypothesis, we progress from humans to invertebrates, investigating how a potential role for rapid eye movement (REM) sleep in emotional regulation in humans could be re-examined as a conserved sleep function that co-evolved alongside selective attention to maintain an adaptive balance between prediction and surprise. This view of active sleep has some interesting implications for the evolution of subjective awareness and consciousness in animals.

Fly seizure EEG: field potential activity in the Drosophila brain

Hypersynchronous neural activity is a characteristic feature of seizures. Although many Drosophila mutants of epilepsy-related genes display clear behavioral spasms and motor unit hyperexcitability, field potential measurements of aberrant hypersynchronous activity across brain regions during seizures have yet to be described. Here, we report a straightforward method to observe local field potentials (LFPs) from the Drosophila brain to monitor ensemble neural activity during seizures in behaving tethered flies. High frequency stimulation across the brain reliably triggers a stereotypic sequence of electroconvulsive seizure (ECS) spike discharges readily detectable in the dorsal longitudinal muscle (DLM) and coupled with behavioral spasms. During seizure episodes, the LFP signal displayed characteristic large-amplitude oscillations with a stereotypic temporal correlation to DLM flight muscle spiking. ECS-related LFP events were clearly distinct from rest- and flight-associated LFP patterns. We further characterized the LFP activity during different types of seizures originating from genetic and pharmacological manipulations. In the 'bang-sensitive' sodium channel mutant bangsenseless (bss), the LFP pattern was prolonged, and the temporal correlation between LFP oscillations and DLM discharges was altered. Following administration of the pro-convulsant GABA_A blocker picrotoxin, we uncovered a qualitatively different LFP activity pattern, which consisted of a slow (1-Hz), repetitive, waveform, closely coupled with DLM bursting and behavioral spasms. Our approach to record brain LFPs presents an initial framework for electrophysiological analysis of the complex brain-wide activity patterns in the large collection of Drosophila excitability mutants.

Integrated information structure collapses with anesthetic loss of conscious arousal in Drosophila melanogaster

The physical basis of consciousness remains one of the most elusive concepts in current science. One influential conjecture is that consciousness is to do with some form of causality, measurable through information. The integrated information theory of consciousness (IIT) proposes that conscious experience, filled with rich and specific content, corresponds directly to a hierarchically organised, irreducible pattern of causal interactions; i.e. an integrated informational structure among elements of a system. Here, we tested this conjecture in a simple biological system (fruit flies), estimating the information structure of the system during wakefulness and general anesthesia. Consistent with this conjecture, we found that integrated interactions among populations of neurons during wakefulness collapsed to isolated clusters of interactions during anesthesia. We used classification analysis to quantify the accuracy of discrimination between wakeful and anesthetised states, and found that informational structures inferred conscious states with greater accuracy than a scalar summary of the structure, a measure which is generally championed as the main measure of IIT. In stark contrast to a view which assumes feedforward architecture for insect brains, especially fly visual systems, we found rich information structures, which cannot arise from purely feedforward systems, occurred across the fly brain. Further, these information structures collapsed uniformly across the brain during anesthesia. Our results speak to the potential utility of the novel concept of an “informational structure” as a measure for level of consciousness, above and beyond simple scalar values.

The physical basis of consciousness remains elusive. Efforts to measure consciousness have generally been restricted to simple, scalar quantities which summarise the complexity of a system, inspired by integrated information theory, which links a multi-dimensional, informational structure to the contents of experience in a system. Due to the complexity of the definition of the structure, assessment of its utility as a measure of conscious arousal in a system has largely been ignored. In this manuscript we evaluate the utility of such an information structure in measuring the level of arousal in the fruit fly. Our results indicate that this structure can be more informative about the level of arousal in a system than even the single-value summary proposed by the theory itself. These results may push consciousness research towards the notion of multi-dimensional informational structures, instead of traditional scalar summaries.