The temporal binding deficit hypothesis of autism

Frith has argued that people with autism show “weak central coherence,” an unusual bias toward piecemeal rather than configurational processing and a reduction in the normal tendency to process information in context. However, the precise cognitive and neurological mechanisms underlying weak central coherence are still unknown. We propose the hypothesis that the features of autism associated with weak central coherence result from a reduction in the integration of specialized local neural networks in the brain caused by a deficit in temporal binding. The visuoperceptual anomalies associated with weak central coherence may be attributed to a reduction in synchronization of high-frequency gamma activity between local networks processing local features. The failure to utilize context in language processing in autism can be explained in similar terms. Temporal binding deficits could also contribute to executive dysfunction in autism and to some of the deficits in socialization and communication

Rhythmic inhibition allows neural networks to search for maximally consistent states

Gamma-band rhythmic inhibition is a ubiquitous phenomenon in neural circuits yet its computational role still remains elusive. We show that a model of Gamma-band rhythmic inhibition allows networks of coupled cortical circuit motifs to search for network configurations that best reconcile external inputs with an internal consistency model encoded in the network connectivity. We show that Hebbian plasticity allows the networks to learn the consistency model by example. The search dynamics driven by rhythmic inhibition enable the described networks to solve difficult constraint satisfaction problems without making assumptions about the form of stochastic fluctuations in the network. We show that the search dynamics are well approximated by a stochastic sampling process. We use the described networks to reproduce perceptual multi-stability phenomena with switching times that are a good match to experimental data and show that they provide a general neural framework which can be used to model other 'perceptual inference' phenomena

Characterizing global evolutions of complex systems via intermediate network representations

Recent developments in measurement techniques have enabled us to observe the time series of many components simultaneously. Thus, it is important to understand not only the dynamics of individual time series but also their interactions. Although there are many methods for analysing the interaction between two or more time series, there are very few methods that describe global changes of the interactions over time. Here, we propose an approach to visualise time evolution for the global changes of the interactions in complex systems. This approach consists of two steps. In the first step, we construct a meta-time series of networks. In the second step, we analyse and visualise this meta-time series by using distance and recurrence plots. Our two-step approach involving intermediate network representations elucidates the half-a-day periodicity of foreign exchange markets and a singular functional network in the brain related to perceptual alternations

Brain and Mind

Le débat sur les relations esprit–cerveau a été centré sur des questions relatives au libre arbitre. J’examine ce débat et conclus que les neurosciences n’ont pas de raisons méthodologiques, ontologiques ou théoriques convaincantes, pas plus que de raisons empiriques, pour rejeter la notion de libre arbitre. Parallèlement, je reconnais que la question est très controversée, à la fois en science et dans la société. Le problème se situe dans l’incompatibilité entre notions scientifiques du cerveau et notions pré-scientifiques de l’esprit. Par conséquent, je propose d’envisager les relations esprit–cerveau sur une base empirique plus profonde et incontestée que l’on peut trouver dans la psychophysique. Je discute deux cas dans lesquels le contenu d’une expérience psychophysique, et sa dynamique, correspondent à la dynamique cérébrale. Dans un cas, la correspondance est une identité de type; dans l’autre, il s’agit d’une instanciation multiple : plusieurs types radicalement différents d’activités donnent lieu à la même dynamique perceptive. Ces deux exemples illustrent que, bien que l’identité des types soit possible, elle peut être souvent hautement contextualisée. Par conséquent, on doit appréhender les relations esprit–cerveau une par une plutôt que les fonder d’un seul bloc.The debate on mind–brain relationships has been centered on issues of free will. I investigate the debate and conclude that the neurosciences neither have compelling methodological, ontological, theoretical reasons, nor empirical reasons to reject the notion of free will. At the same time, I concede that the issue is highly contentious, both in science and society. The problem resides in the clash between scientific notions of the brain and pre-scientific notions of mind. I therefore propose to look at mind–brain relationships on a more sound, and uncontroversial, empirical basis, which can be found in psychophysics. I discuss two instances in which the content of a psychophysical experience, and its dynamics, correspond to brain dynamics. In one case, the correspondence is a one:one type-identity, in the other it is a case of radical multiple instantiation: several radically different types of brain activity give rise to the same perceptual dynamics. These two examples illustrate that although type identity is possible, it may often be highly contextualized. Mind–brain relationships are therefore more likely to be conquered one by one rather than established wholesale

Ambiguous Figures – What Happens in the Brain When Perception Changes But Not the Stimulus

During observation of ambiguous figures our perception reverses spontaneously although the visual information stays unchanged. Research on this phenomenon so far suffered from the difficulty to determine the instant of the endogenous reversals with sufficient temporal precision. A novel experimental paradigm with discontinuous stimulus presentation improved on previous temporal estimates of the reversal event by a factor of three. It revealed that disambiguation of ambiguous visual information takes roughly 50 ms or two loops of recurrent neural activity. Further, the decision about the perceptual outcome has taken place at least 340 ms before the observer is able to indicate the consciously perceived reversal manually. We provide a short review about physiological studies on multistable perception with a focus on electrophysiological data. We further present a new perspective on multistable perception that can easily integrate previous apparently contradicting explanatory approaches. Finally we propose possible extensions toward other research fields where ambiguous figure perception may be useful as an investigative tool

Binding Mechanisms in Visual Perception and Their Link With Neural Oscillations: A Review of Evidence From tACS

Neurophysiological studies in humans employing magneto- (MEG) and electro- (EEG) encephalography increasingly suggest that oscillatory rhythmic activity of the brain may be a core mechanism for binding sensory information across space, time, and object features to generate a unified perceptual representation. To distinguish whether oscillatory activity is causally related to binding processes or whether, on the contrary, it is a mere epiphenomenon, one possibility is to employ neuromodulatory techniques such as transcranial alternating current stimulation (tACS). tACS has seen a rising interest due to its ability to modulate brain oscillations in a frequency-dependent manner. In the present review, we critically summarize current tACS evidence for a causal role of oscillatory activity in spatial, temporal, and feature binding in the context of visual perception. For temporal binding, the emerging picture supports a causal link with the power and the frequency of occipital alpha rhythms (8–12 Hz); however, there is no consistent evidence on the causal role of the phase of occipital tACS. For feature binding, the only study available showed a modulation by occipital alpha tACS. The majority of studies that successfully modulated oscillatory activity and behavioral performance in spatial binding targeted parietal areas, with the main rhythms causally linked being the theta (~7 Hz) and beta (~18 Hz) frequency bands. On the other hand, spatio-temporal binding has been directly modulated by parieto-occipital gamma (~40–60 Hz) and alpha (10 Hz) tACS, suggesting a potential role of cross-frequency coupling when binding across space and time. Nonetheless, negative or partial results have also been observed, suggesting methodological limitations that should be addressed in future research. Overall, the emerging picture seems to support a causal role of brain oscillations in binding processes and, consequently, a certain degree of plasticity for shaping binding mechanisms in visual perception, which, if proved to have long lasting effects, can find applications in different clinical populations

Dynamic Effective Connectivity of Inter-Areal Brain Circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities

Oscillatory Control over Representational States in Working Memory

In the visual world, attention is guided by perceptual goals activated in visual working memory (VWM). However, planning multiple-task sequences also requires VWM to store representations for future goals. These future goals need to be prevented from interfering with the current perceptual task. Recent findings have implicated neural oscillations as a control mechanism serving the implementation and switching of different states of prioritization of VWM representations. We review recent evidence that posterior alpha-band oscillations underlie the flexible activation and deactivation of VWM representations and that frontal delta-to-theta-band oscillations play a role in the executive control of this process. That is, frontal delta-to-theta appears to orchestrate posterior alpha through long-range oscillatory networks to flexibly set up and change VWM states during multitask sequences

Nonlinear brain dynamics as macroscopic manifestation of underlying many-body field dynamics

Neural activity patterns related to behavior occur at many scales in time and space from the atomic and molecular to the whole brain. Here we explore the feasibility of interpreting neurophysiological data in the context of many-body physics by using tools that physicists have devised to analyze comparable hierarchies in other fields of science. We focus on a mesoscopic level that offers a multi-step pathway between the microscopic functions of neurons and the macroscopic functions of brain systems revealed by hemodynamic imaging. We use electroencephalographic (EEG) records collected from high-density electrode arrays fixed on the epidural surfaces of primary sensory and limbic areas in rabbits and cats trained to discriminate conditioned stimuli (CS) in the various modalities. High temporal resolution of EEG signals with the Hilbert transform gives evidence for diverse intermittent spatial patterns of amplitude (AM) and phase modulations (PM) of carrier waves that repeatedly re-synchronize in the beta and gamma ranges at near zero time lags over long distances. The dominant mechanism for neural interactions by axodendritic synaptic transmission should impose distance-dependent delays on the EEG oscillations owing to finite propagation velocities. It does not. EEGs instead show evidence for anomalous dispersion: the existence in neural populations of a low velocity range of information and energy transfers, and a high velocity range of the spread of phase transitions. This distinction labels the phenomenon but does not explain it. In this report we explore the analysis of these phenomena using concepts of energy dissipation, the maintenance by cortex of multiple ground states corresponding to AM patterns, and the exclusive selection by spontaneous breakdown of symmetry (SBS) of single states in sequences.Comment: 31 page