Transcranial alternating current stimulation enhances individual alpha activity in human EEG

Non-invasive electrical stimulation of the human cortex by means of transcranial direct current stimulation (tDCS) has been instrumental in a number of important discoveries in the field of human cortical function and has become a well-established method for evaluating brain function in healthy human participants. Recently, transcranial alternating current stimulation (tACS) has been introduced to directly modulate the ongoing rhythmic brain activity by the application of oscillatory currents on the human scalp. Until now the efficiency of tACS in modulating rhythmic brain activity has been indicated only by inference from perceptual and behavioural consequences of electrical stimulation. No direct electrophysiological evidence of tACS has been reported. We delivered tACS over the occipital cortex of 10 healthy participants to entrain the neuronal oscillatory activity in their individual alpha frequency range and compared results with those from a separate group of participants receiving sham stimulation. The tACS but not the sham stimulation elevated the endogenous alpha power in parieto-central electrodes of the electroencephalogram. Additionally, in a network of spiking neurons, we simulated how tACS can be affected even after the end of stimulation. The results show that spike-timing-dependent plasticity (STDP) selectively modulates synapses depending on the resonance frequencies of the neural circuits that they belong to. Thus, tACS influences STDP which in turn results in aftereffects upon neural activity.The present findings are the first direct electrophysiological evidence of an interaction of tACS and ongoing oscillatory activity in the human cortex. The data demonstrate the ability of tACS to specifically modulate oscillatory brain activity and show its potential both at fostering knowledge on the functional significance of brain oscillations and for therapeutic application.     

节律性听觉刺激下的神经振荡同步化及其应用

大脑的感觉、情绪、认知等功能与其神经振荡模式有密切的联系。通过施加节律性刺激可以调控大脑的神经振荡模式,进而影响个体感受、情绪状态和认知功能等。与近年来常见的非侵入性电刺激和磁刺激相比,同样依赖于外部刺激输入的节律性感觉刺激具有成本低、易操作等优点,被认为是一种极具潜力的神经调控手段。本文以节律性听觉刺激为例,系统综述了不同类型的节律性听觉刺激如何影响大脑的神经振荡模式,进而影响相关状态和功能;并通过总结外部节律性听觉刺激对个体感知觉、情绪与认知功能的影响,讨论其生理机制和应用前景。     

综述: 知觉相关的神经振荡-外界节律同步化现象

具有特定频率的节律性刺激能同步大脑内相应频率的神经振荡,使神经活动与外界刺激发生相位锁定,称之为神经振荡-外界节律同步化(neural entrainment).这种同步化的现象伴随着大脑内神经元集群兴奋水平的周期性波动,并与节律信息加工、知觉及注意等认知过程存在关联.得益于其非侵入、易操作以及能有效调控神经活动的特性,神经振荡-外界节律同步化成为了研究神经振荡与知觉和认知功能关系的有力手段,也为认知障碍诊断及干预提供了新的思路和方法.     

Brain stimulation competes with ongoing oscillations for control of spike timing in the primate brain

Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively. In particular, tACS is often used as a targeted intervention that enhances a neural oscillation at a specific frequency to affect a particular behavior. However, these interventions often yield highly variable results. Here, we provide a potential explanation for this variability: tACS competes with the brain’s ongoing oscillations. Using neural recordings from alert nonhuman primates, we find that when neural firing is independent of ongoing brain oscillations, tACS readily entrains spiking activity, but when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead. Consequently, tACS can yield categorically different results on neural activity, even when the stimulation protocol is fixed. Mathematical analysis suggests that this competition is likely to occur under many experimental conditions. Attempting to impose an external rhythm on the brain may therefore often yield precisely the opposite effect.

Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively; however, tACS can often yield highly variable results. This study shows that when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead of the expected enhancement.     

A Generalized Framework for Quantifying the Dynamics of EEG Event-Related Desynchronization

Brains were built by evolution to react swiftly to environmental challenges. Thus, sensory stimuli must be processed ad hoc, i.e., independent—to a large extent—from the momentary brain state incidentally prevailing during stimulus occurrence. Accordingly, computational neuroscience strives to model the robust processing of stimuli in the presence of dynamical cortical states. A pivotal feature of ongoing brain activity is the regional predominance of EEG eigenrhythms, such as the occipital alpha or the pericentral mu rhythm, both peaking spectrally at 10 Hz. Here, we establish a novel generalized concept to measure event-related desynchronization (ERD), which allows one to model neural oscillatory dynamics also in the presence of dynamical cortical states. Specifically, we demonstrate that a somatosensory stimulus causes a stereotypic sequence of first an ERD and then an ensuing amplitude overshoot (event-related synchronization), which at a dynamical cortical state becomes evident only if the natural relaxation dynamics of unperturbed EEG rhythms is utilized as reference dynamics. Moreover, this computational approach also encompasses the more general notion of a “conditional ERD,” through which candidate explanatory variables can be scrutinized with regard to their possible impact on a particular oscillatory dynamics under study. Thus, the generalized ERD represents a powerful novel analysis tool for extending our understanding of inter-trial variability of evoked responses and therefore the robust processing of environmental stimuli.     

Frequency Band-Specific Electrical Brain Stimulation Modulates Cognitive Control Processes

A large body of findings has tied midfrontal theta-band (4–8 Hz) oscillatory activity to adaptive control mechanisms during response conflict. Thus far, this evidence has been correlational. To evaluate whether theta oscillations are causally involved in conflict processing, we applied transcranial alternating current stimulation (tACS) in the theta band to a midfrontal scalp region, while human subjects performed a spatial response conflict task. Conflict was introduced by incongruency between the location of the target stimulus and the required response hand. As a control condition, we used alpha-band (8–12 Hz) tACS over the same location. The exact stimulation frequencies were determined empirically for each subject based on a pre-stimulation EEG session. Behavioral results showed general conflict effects of slower response times (RT) and lower accuracy for high conflict trials compared to low conflict trials. Importantly, this conflict effect was reduced specifically during theta tACS, which was driven by slower response times on low conflict trials. These results show how theta tACS can modulate adaptive cognitive control processes, which is in accordance with the view of midfrontal theta oscillations as an active mechanism for cognitive control.     

Modulating Brain Oscillations to Drive Brain Function

Do neuronal oscillations play a causal role in brain function? In a study in this issue of PLOS Biology, Helfrich and colleagues address this long-standing question by attempting to drive brain oscillations using transcranial electrical current stimulation. Remarkably, they were able to manipulate visual perception by forcing brain oscillations of the left and right visual hemispheres into synchrony using oscillatory currents over both hemispheres. Under this condition, human observers more often perceived an inherently ambiguous visual stimulus in one of its perceptual instantiations. These findings shed light on the mechanisms underlying neuronal computation. They show that it is the neuronal oscillations that drive the visual experience, not the experience driving the oscillations. And they indicate that synchronized oscillatory activity groups brain areas into functional networks. This points to new ways for controlled experimental and possibly also clinical interventions for the study and modulation of brain oscillations and associated functions.How does the brain work? How does it code, transfer, and store information? How are conscious experiences generated? These, among others, are long-standing questions neuroscientists try to answer. One way to approach this is to study how the brain orchestrates behaviour, for instance, by measuring brain activity and relating it to behaviour. Yet, studying the brain–behaviour relationship raises another series of questions: What type of brain activity should one look at? Do we need to record directly from single neurons? Or can we make inferences also by recording from larger pools of neurons? And importantly, do these measures of brain activity provide mechanistic accounts of how the brain implements function, or are they just inevitable side-products, with limited explanatory power for the neural mechanisms underlying our experiences, thoughts, or actions?Certainly, one would have a good argument for brain activity causally underlying brain function if (i) this brain activity not only relates to sensory experiences or behavioural performance measures (revealing a correlative brain-behaviour relationship), but (ii) interventions into this brain activity would also modulate our experiences or performance (revealing a causal link). Recent developments allow addressing these central points for oscillatory brain activity, which is what Helfrich et al. [1] did in their study published in this issue of PLOS Biology.At the basis of Helfrich et al.''s study are two lines of research, one of which is concerned with the interpretation of a special type of brain activity, namely, brain oscillations. This type of brain activity represents voltage fluctuations of neuronal elements and was initially observed from one scalp electrode by Hans Berger [2]. Today, brain oscillations are typically recorded from multiple sensors distributed over the scalp or brain, for instance using electro- or magneto-encephalography (EEG/MEG), in order to make inferences about the orchestration of brain activity across distinct neuronal elements [3]. A prominent view is that these oscillations represent essential network activity. They become visible when neuronal elements of a network start to synchronize their oscillatory activity, i.e., temporarily couple together [4]. Notably, brain oscillations vary in frequencies depending on the task that is being executed and the region of the brain they are recorded from [3] (see Box 1 for example frequencies relevant for Helfrich et al.''s study). It is understood that this may reflect nested networks that oscillate at different frequencies and spatial scales [4] and that define functional architecture not only by synchronizing at the same frequency but also through complex cross-frequency interactions; this to allow for integration of processes at different temporal and spatial scales [5]–[7]. With respect to the above questions on how the brain operates, the most exciting aspect of oscillatory brain activity is probably that it offers mechanistic accounts. One example is the communication-through-coherence theory [8], which states that the relative timing of oscillatory activity of two neuronal elements enables the control of information transfer, with communication being maximal when phases of high excitability of these elements cycle in synchrony, and minimal when they cycle out of synchrony (see Fig. 1B Model).Open in a separate windowFigure 1Schematic representation of design, objectives, and insights from the study by Helfrich et al. A. Design and questions: Participants viewed an apparent motion stimulus, which elicits a bistable percept consisting of either horizontal (percept 1) or vertical motion (percept 2). A bi-hemispheric network of two posterior areas (blue and red squares) was interrogated as to the functionality of inter-area synchrony (see “?”) in generating these percepts, by recording of brain oscillations through electro-encephalography (EEG), and interventions into these oscillations through transcranial alternating current stimulation (tACS). B. Results and conclusion: EEG revealed that the horizontal motion percept was associated with enhanced synchrony (coherence) between oscillatory brain activity of the two posterior areas (as compared to vertical motion percept), in line with coupling of the two areas to a functional network by synchronization of their respective phases of high excitability (see Model). This provides information on a correlative relationship between network activation and function but cannot disentangle whether it is the percept that drives the network, or the network that drives the percept. Intervention with tACS supports the latter. Applying tACS in synchrony over the two areas enhances inter-area coherence of oscillatory activity as well as the horizontal motion percept (as opposed to applying tACS out of synchrony). Hence, synchrony of oscillatory brain activity underlies the formation of functional networks and mediates its associated functions.

Box 1. Glossary

Brain oscillations in the gamma frequency band (gamma-oscillations): This is a class of brain oscillations cycling at rapid frequencies (35–100 Hz). Gamma-oscillations are prominent in visual cortex (among other areas) and become evident also in scalp recordings when participants view specific types of visual stimuli. Alpha-band brain oscillations cycle at 8–12 Hz. Alpha-oscillations can co-occur with gamma-oscillations in visual areas, where these two classes of oscillations show an inverse relationship in terms of amplitude. Transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) use electrical currents applied through two or more scalp electrodes for transient, non-invasive brain stimulation, whereas transcranial magnetic stimulation (TMS) uses the principle of electromagnetic induction. In tACS, the currents are modulated in an oscillatory (sinusoidal) pattern, and can therefore be frequency-tuned to underlying brain oscillations. Likewise, TMS in its rhythmic form (rhythmic TMS) allows for periodic brain stimulation at frequencies of brain oscillations.The other line of research that is at the heart of Helfrich et al.''s study is concerned with interventions into brain activity by non-invasive brain stimulation techniques; this to probe the brain–behaviour relationship along a more causal dimension [9]. Such techniques are widely used in cognitive and clinical neuroscience, and employ either magnetic or electric fields to stimulate neurons directly (i.e., transcranially) to then test the behavioural consequences. Currently available techniques use transcranial magnetic stimulation (TMS), or a variety of electrical currents such as with transcranial direct current stimulation (tDCS) or transcranial alternating current stimulation (tACS) (see Box 1) [10]. While these techniques have been successfully employed in numerous studies, a recurrent question is how to improve specificity of effects in terms of enhancing focality [11] or targeting specific subpopulations within the stimulated neuronal pool [12]. In addition, simultaneous neuroimaging studies have revealed that the effect of the magnetic or electric field on the stimulated area (under the TMS coil or the stimulation electrode) is spreading to other areas, in many instances along anatomical connections [13],[14]. Hence, any behavioural outcome needs to be interpreted in the context of network effects. Intriguingly, and relevant for interactions with oscillatory brain activity, recent findings indicate that the specificity of these interventions into functionally relevant brain activity may be improved by taking into account not only the spatial dimension (i.e., what anatomical network to stimulate) but also the temporal dimension (what frequency to apply). This is suggested by recent studies using periodic transcranial stimulation protocols (such as tACS or rhythmic TMS) allowing a frequency tuning of stimulation (see Box 1). These studies demonstrate an immediate behavioural effect at specific stimulation frequencies, namely those that match the frequencies of intrinsic brain oscillations[15]–[21]; which may be caused by the periodic stimulation promoting the intrinsic oscillations [22]–[24].Capitalizing on the above, Helfrich et al. convincingly address in healthy human volunteers the long-standing issue of whether oscillatory brain activity indeed coordinates functional brain architecture, as opposed to representing a mere by-product, and thereby bridge a gap between recordings and interventional studies into brain oscillations (see Fig. 1 for a schematic representation of design, objectives, and insights of the study). They do so by examining the link between visual network activity and specific sensory experiences. To manipulate sensory experience (without changing sensory input), Helfrich et al. employed a visual motion paradigm (see Fig. 1A), in which pairs of diagonally opposed dots are presented on a screen in two alternating configurations (upper left/lower right dots followed by lower left/upper right dots, etc.). This leads to a bistable percept, consisting of time periods during which the two dots are perceived as moving horizontally (see Fig. 1A, apparent motion percept 1), alternating with time periods during which the same dots are perceived as moving vertically (Fig. 1A, apparent motion percept 2). Interestingly, recordings of brain oscillations from left and right occipito-parietal EEG sensors, i.e., from areas processing the right- versus left-sided dots respectively, revealed a temporally stable pattern of relative timing between these oscillations, depending on the percept (replicating [25]): during horizontal motion percepts when the demands for interhemispheric communication can be assumed to be high (as opposed to vertical percepts where motion integration can be resolved within each hemisphere) [26], these left and right oscillations show high coherence in the gamma frequency band (at approximately 35–100 Hz) (Fig. 1B EEG). In other words, oscillations in the left and right occipito-parietal areas are synchronized. This is suggestive of these areas forming a temporally stable network during horizontal as opposed to vertical motion integration, in line with models of network coordination by synchronization of brain oscillations (Fig. 1B Model) [8],[27]. Importantly, applying rhythmic brain stimulation in synchrony over the left and right occipito-parietal cortex using tACS at gamma frequency enhances both the gamma-band EEG coherence between the two hemispheres (without affecting gamma-power) and its associated percept (i.e., horizontal motion), as opposed to applying gamma-tACS out of synchrony (Fig. 1B tACS). See also Polania et al. [19] for a conceptually similar tACS result, without the direct evidence for concurrently enhanced EEG synchrony. This shows that in-synchrony tACS versus out-of-synchrony tACS over two elements of an oscillatory visual network can be used to stabilize/destabilize this network, and with meaningful perceptual consequences. This is in accord with brain oscillations not only indexing network coordination and associated functions, but causing them.The findings of Helfrich et al. make an important contribution. They more firmly link the dynamics of oscillatory brain activity to the formation of functional networks, as well as the orchestration of brain function (here phenomenological experience) and this along a causal dimension. This corroborates and extends a growing number of studies showing that brain oscillations can serve as targets for controlled interventions into brain activity and function, by non-invasive brain stimulation in periodic patterns [22]–[24]. The principle idea is to promote brain oscillations that have been associated with specific functions (as inferred from correlative brain-behavioural links) to cause performance changes, provided a causal relationship underlies the correlative data. For instance, it has been shown that promoting oscillations of the parietal cortex known to be related to attentional selection using frequency-tuned rhythmic TMS [22] biases perception towards the expected stimulus dimension [17],[20]. Likewise, tACS (or oscillatory tDCS) tuned to fronto-temporal oscillations, which have been associated with memory consolidation during slow-wave sleep or dream patterns during REM-sleep (e.g., lucid dreaming), have been shown to enhance memory or lucid dream content, respectively [15],[21]. And equivalent effects have been found for oscillatory motor system activity [16],[18]. This opens powerful opportunities for neuroscience and clinical interventions, not only allowing to test models of how brain activity implements function but also how it relates to dysfunction, to inform controlled intervention into the brain–behaviour relationship.These findings are exciting and indicate that it is promising to study brain oscillations, even at a macroscopic scale (such as measured with EEG/MEG), to answer some of the long-standing questions of how the brain works. They also take the emerging new approach of using periodic transcranial stimulation to interact with brain oscillations and function beyond the proof-of-principle stage. However, the usefulness of this approach will depend on the extent to which its specificity can be improved (e.g., up- versus down-regulating oscillations, tailoring to individual differences) and its mechanisms of actions understood. One unresolved point is the spatial extent of stimulation. With tACS, the conventional stimulation electrodes are large (several cm²) and require a “return” electrode which excites widespread areas. To render stimulation more focal, special electrode montages have been proposed [11], as also used by Helfrich et al., and which may explain some of the differences to a previous study of the same group using a less focal electrode montage [28]. Other developments are underway to funnel stimulation to specific target areas by the use of multichannel electrode configurations and computational (forward) models of electrical field distributions [29]. In this context, it will be of interest to compare the efficiency of frequency-tuned tACS with frequency-tuned rhythmic TMS, the latter thought to be more focal, but also more superficial. In addition, it is still largely unknown how these forms of rhythmic stimulation interact with intrinsic brain oscillations. There is growing evidence that the periodic electric or magnetic force may entrain the underlying oscillations during stimulation [22],[23], and that long-lasting effects may arise from this entrainment, possibly by inducing plasticity effects via spike-timing dependent plasticity in the circuits generating these oscillations [30]. It is the former, short-term effects that are of interest for experimental interventions in cognitive neuroscience for testing theory (because of their limited duration), but the latter, longer-lasting effects that are of relevance for clinical interventions. Finally, while Helfrich et al. report cross-frequency effects of gamma-tACS, in particular in the alpha frequency band (8–12 Hz), it remains to be studied in detail how the induced oscillations resonate in other, nested oscillatory networks. These and other points will need to be resolved in future work to be able to fully assess the extent of the impact of this emerging approach.     

The Visual Priming of Motion-Defined 3D Objects

The perception of a stimulus can be influenced by previous perceptual experience, a phenomenon known as perceptual priming. However, there has been limited investigation on perceptual priming of shape perception of three-dimensional object structures defined by moving dots. Here we examined the perceptual priming of a 3D object shape defined purely by motion-in-depth cues (i.e., Shape-From-Motion, SFM) using a classic prime-target paradigm. The results from the first two experiments revealed a significant increase in accuracy when a “cloudy” SFM stimulus (whose object structure was difficult to recognize due to the presence of strong noise) was preceded by an unambiguous SFM that clearly defined the same transparent 3D shape. In contrast, results from Experiment 3 revealed no change in accuracy when a “cloudy” SFM stimulus was preceded by a static shape or a semantic word that defined the same object shape. Instead, there was a significant decrease in accuracy when preceded by a static shape or a semantic word that defined a different object shape. These results suggested that the perception of a noisy SFM stimulus can be facilitated by a preceding unambiguous SFM stimulus—but not a static image or a semantic stimulus—that defined the same shape. The potential neural and computational mechanisms underlying the difference in priming are discussed.     

综述与专论: 外源节律性脑刺激技术在精神神经类疾病治疗中的应用

神经振荡是中枢神经系统中一种节律性神经活动模式，研究发现精神神经类疾病患者存在神经振荡异常。外源节律性刺激能够通过“夹带”效应以及可塑性变化机制有效调节异常的神经振荡，具有治疗精神神经类疾病的潜在可能性。目前，外源节律性脑刺激技术主要包括经颅交流电刺激、经颅时间相干刺激、节律性感觉刺激等方式。本文从外源节律性脑刺激技术原理以及目前不同技术在临床上治疗精神神经类疾病的刺激策略、研究进展以及治疗效果等角度展开综述，提出这一类调控技术可能成为未来临床治疗精神神经疾病症状的无创高效新型治疗方案，并对其未来的发展方向进行展望。     

Concurrent Electroencephalography Recording During Transcranial Alternating Current Stimulation (tACS)

Oscillatory brain activities are considered to reflect the basis of rhythmic changes in transmission efficacy across brain networks and are assumed to integrate cognitive neural processes. Transcranial alternating current stimulation (tACS) holds the promise to elucidate the causal link between specific frequencies of oscillatory brain activity and cognitive processes. Simultaneous electroencephalography (EEG) recording during tACS would offer an opportunity to directly explore immediate neurophysiological effects of tACS. However, it is not trivial to measure EEG signals during tACS, as tACS creates a huge artifact in EEG data. Here we explain how to set up concurrent tACS-EEG experiments. Two necessary considerations for successful EEG recording while applying tACS are highlighted. First, bridging of the tACS and EEG electrodes via leaking EEG gel immediately saturates the EEG amplifier. To avoid bridging via gel, the viscosity of the EEG gel is the most important parameter. The EEG gel must be viscous to avoid bridging, but at the same time sufficiently fluid to create contact between the tACS electrode and the scalp. Second, due to the large amplitude of the tACS artifact, it is important to consider using an EEG system with a high resolution analog-to-digital (A/D) converter. In particular, the magnitude of the tACS artifact can exceed 100 mV at the vicinity of a stimulation electrode when 1 mA tACS is applied. The resolution of the A/D converter is of importance to measure good quality EEG data from the vicinity of the stimulation site. By following these guidelines for the procedures and technical considerations, successful concurrent EEG recording during tACS will be realized.     

Alpha-Band Rhythms in Visual Task Performance: Phase-Locking by Rhythmic Sensory Stimulation

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8–12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles.     

Stimulus-dependent oscillations and evoked potentials in chinchilla auditory cortex

Besides the intensity and frequency of an auditory stimulus, the length of time that precedes the stimulation is an important factor that determines the magnitude of early evoked neural responses in the auditory cortex. Here we used chinchillas to demonstrate that the length of the silent period before the presentation of an auditory stimulus is a critical factor that modifies late oscillatory responses in the auditory cortex. We used tetrodes to record local-field potential (LFP) signals from the left auditory cortex of ten animals while they were stimulated with clicks, tones or noise bursts delivered at different rates and intensity levels. We found that the incidence of oscillatory activity in the auditory cortex of anesthetized chinchillas is dependent on the period of silence before stimulation and on the intensity of the auditory stimulus. In 62.5% of the recordings sites we found stimulus-related oscillations at around 8-20 Hz. Stimulus-induced oscillations were largest and consistent when stimuli were preceded by 5 s of silence and they were absent when preceded by less than 500 ms of silence. These results demonstrate that the period of silence preceding the stimulus presentation and the stimulus intensity are critical factors for the presence of these oscillations.     

Cell groups reveal structure of stimulus space

An important task of the brain is to represent the outside world. It is unclear how the brain may do this, however, as it can only rely on neural responses and has no independent access to external stimuli in order to “decode” what those responses mean. We investigate what can be learned about a space of stimuli using only the action potentials (spikes) of cells with stereotyped—but unknown—receptive fields. Using hippocampal place cells as a model system, we show that one can (1) extract global features of the environment and (2) construct an accurate representation of space, up to an overall scale factor, that can be used to track the animal's position. Unlike previous approaches to reconstructing position from place cell activity, this information is derived without knowing place fields or any other functions relating neural responses to position. We find that simply knowing which groups of cells fire together reveals a surprising amount of structure in the underlying stimulus space; this may enable the brain to construct its own internal representations.     

Differential Entrainment of Neuroelectric Delta Oscillations in Developmental Dyslexia

Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.     

Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

Even in the absence of sensory stimulation the brain is spontaneously active. This background “noise” seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network’s spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network’s behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms.     

Power and phase properties of oscillatory neural responses in the presence of background activity

Natural sensory inputs, such as speech and music, are often rhythmic. Recent studies have consistently demonstrated that these rhythmic stimuli cause the phase of oscillatory, i.e. rhythmic, neural activity, recorded as local field potential (LFP), electroencephalography (EEG) or magnetoencephalography (MEG), to synchronize with the stimulus. This phase synchronization, when not accompanied by any increase of response power, has been hypothesized to be the result of phase resetting of ongoing, spontaneous, neural oscillations measurable by LFP, EEG, or MEG. In this article, however, we argue that this same phenomenon can be easily explained without any phase resetting, and where the stimulus-synchronized activity is generated independently of background neural oscillations. It is demonstrated with a simple (but general) stochastic model that, purely due to statistical properties, phase synchronization, as measured by ‘inter-trial phase coherence’, is much more sensitive to stimulus-synchronized neural activity than is power. These results question the usefulness of analyzing the power and phase of stimulus-synchronized activity as separate and complementary measures; particularly in the case of attempting to demonstrate whether stimulus-synchronized neural activity is generated by phase resetting of ongoing neural oscillations.     

Source Space Estimation of Oscillatory Power and Brain Connectivity in Tinnitus

Tinnitus is the perception of an internally generated sound that is postulated to emerge as a result of structural and functional changes in the brain. However, the precise pathophysiology of tinnitus remains unknown. Llinas’ thalamocortical dysrhythmia model suggests that neural deafferentation due to hearing loss causes a dysregulation of coherent activity between thalamus and auditory cortex. This leads to a pathological coupling of theta and gamma oscillatory activity in the resting state, localised to the auditory cortex where normally alpha oscillations should occur. Numerous studies also suggest that tinnitus perception relies on the interplay between auditory and non-auditory brain areas. According to the Global Brain Model, a network of global fronto—parietal—cingulate areas is important in the generation and maintenance of the conscious perception of tinnitus. Thus, the distress experienced by many individuals with tinnitus is related to the top—down influence of this global network on auditory areas. In this magnetoencephalographic study, we compare resting-state oscillatory activity of tinnitus participants and normal-hearing controls to examine effects on spectral power as well as functional and effective connectivity. The analysis is based on beamformer source projection and an atlas-based region-of-interest approach. We find increased functional connectivity within the auditory cortices in the alpha band. A significant increase is also found for the effective connectivity from a global brain network to the auditory cortices in the alpha and beta bands. We do not find evidence of effects on spectral power. Overall, our results provide only limited support for the thalamocortical dysrhythmia and Global Brain models of tinnitus.     

Dynamic representation of odours by oscillating neural assemblies

Stimulus evoked oscillatory synchronization of neural assemblies has been most clearly documented in the olfactory and visual systems. Recent results with the olfactory system of locusts show that information about odour identity is contained in spatial and temporal aspects of an oscillatory population response. This suggests that brain oscillations may reflect a common reference for messages encoded in time. Although stimulus-evoked oscillatory phenomena are reliable, their roles in perception, memory and pattern recognition remain to be demonstrated. Using honey bees, we demonstrated that odour encoding involves, as in locusts, the oscillatory synchronization of assemblies of neurons, and that this synchronization is, here also, selectively abolished by the GABA receptor antagonist picrotoxin. In collaboration with Dr Brian Smith's laboratory, we showed, using a behavioural learning paradigm, that picrotoxin-induced desynchronization impairs the discrimination of molecularly similar odourants, but not that of dissimilar odours. It appears, therefore, that oscillatory synchronization of neuronal assemblies is relevant, and essential for fine odour discrimination. Finally, experiments with locust mushroom body neurons, two synapses downstream from the antennal lobe, indicate that their responses to odours become less specific when antennal lobe neurons are desynchronized by picrotoxin injection. These results suggest that oscillatory synchronization and the kind of temporal encoding it affords provide an additional dimension by which the brain can segment spatially overlapping stimulus representations.     

What are lightness illusions and why do we see them?

Lightness illusions are fundamental to human perception, and yet why we see them is still the focus of much research. Here we address the question by modelling not human physiology or perception directly as is typically the case but our natural visual world and the need for robust behaviour. Artificial neural networks were trained to predict the reflectance of surfaces in a synthetic ecology consisting of 3-D “dead-leaves” scenes under non-uniform illumination. The networks learned to solve this task accurately and robustly given only ambiguous sense data. In addition—and as a direct consequence of their experience—the networks also made systematic “errors” in their behaviour commensurate with human illusions, which includes brightness contrast and assimilation—although assimilation (specifically White's illusion) only emerged when the virtual ecology included 3-D, as opposed to 2-D scenes. Subtle variations in these illusions, also found in human perception, were observed, such as the asymmetry of brightness contrast. These data suggest that “illusions” arise in humans because (i) natural stimuli are ambiguous, and (ii) this ambiguity is resolved empirically by encoding the statistical relationship between images and scenes in past visual experience. Since resolving stimulus ambiguity is a challenge faced by all visual systems, a corollary of these findings is that human illusions must be experienced by all visual animals regardless of their particular neural machinery. The data also provide a more formal definition of illusion: the condition in which the true source of a stimulus differs from what is its most likely (and thus perceived) source. As such, illusions are not fundamentally different from non-illusory percepts, all being direct manifestations of the statistical relationship between images and scenes.     

The Right Planum Temporale Is Involved in Stimulus-Driven,Auditory Attention – Evidence from Transcranial Magnetic Stimulation

It is well known that the planum temporale (PT) area in the posterior temporal lobe carries out spectro-temporal analysis of auditory stimuli, which is crucial for speech, for example. There are suggestions that the PT is also involved in auditory attention, specifically in the discrimination and selection of stimuli from the left and right ear. However, direct evidence is missing so far. To examine the role of the PT in auditory attention we asked fourteen participants to complete the Bergen Dichotic Listening Test. In this test two different consonant-vowel syllables (e.g., “ba” and “da”) are presented simultaneously, one to each ear, and participants are asked to verbally report the syllable they heard best or most clearly. Thus attentional selection of a syllable is stimulus-driven. Each participant completed the test three times: after their left and right PT (located with anatomical brain scans) had been stimulated with repetitive transcranial magnetic stimulation (rTMS), which transiently interferes with normal brain functioning in the stimulated sites, and after sham stimulation, where participants were led to believe they had been stimulated but no rTMS was applied (control). After sham stimulation the typical right ear advantage emerged, that is, participants reported relatively more right than left ear syllables, reflecting a left-hemispheric dominance for language. rTMS over the right but not left PT significantly reduced the right ear advantage. This was the result of participants reporting more left and fewer right ear syllables after right PT stimulation, suggesting there was a leftward shift in stimulus selection. Taken together, our findings point to a new function of the PT in addition to auditory perception: particularly the right PT is involved in stimulus selection and (stimulus-driven), auditory attention.