Hardware design of LIF with Latency neuron model with memristive STDP synapses

In this paper, the hardware implementation of a neuromorphic system is presented. This system is composed of a Leaky Integrate-and-Fire with Latency (LIFL) neuron and a Spike-Timing Dependent Plasticity (STDP) synapse. LIFL neuron model allows to encode more information than the common Integrate-and-Fire models, typically considered for neuromorphic implementations. In our system LIFL neuron is implemented using CMOS circuits while memristor is used for the implementation of the STDP synapse. A description of the entire circuit is provided. Finally, the capabilities of the proposed architecture have been evaluated by simulating a motif composed of three neurons and two synapses. The simulation results confirm the validity of the proposed system and its suitability for the design of more complex spiking neural network

When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks

Contains fulltext : 103890.pdf (publisher's version ) (Open Access

Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex

Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio

Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans

Pain is a complex phenomenon that is served by neural oscillations and connectivity involving different brain areas and frequencies. Here, we aimed to systematically and comprehensively assess the pattern of neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. To this end, we applied 10-min heat pain stimuli consecutively to the right and left hand of 39 healthy participants and recorded electroencephalography. We systematically analyzed global and local measures of oscillatory brain activity, connectivity, and graph theory-based network measures during tonic pain and compared them to a nonpainful control condition. Local measures showed suppressions of oscillatory activity at alpha frequencies together with stronger connectivity at alpha and beta frequencies in sensorimotor areas during tonic pain. Furthermore, sensorimotor areas contralateral to stimulation showed significantly increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies. Together, these observations indicate that the state of tonic experimental pain is associated with a sensorimotor-prefrontal network connected at alpha frequencies. These findings represent a step further toward understanding the brain mechanisms underlying long-lasting pain states in health and disease

Neurophysiological mechanisms of longer-lasting experimental pain in humans

Pain serves the protection of the body. Consequently, noxious stimuli or, more precisely, the thereby induced neurophysiological processes commonly lead to pain perception. Identical noxious stimuli, however, do not always translate into the same pain experience depending on multiple factors. To acknowledge this variability, the distinction between nociception as the neural process elicited by noxious stimuli and pain as subjective multifactorial experience is essential. During longer-lasting experimental pain and chronic pain, nociception and pain can substantially dissociate. Moreover, longer-lasting experimental pain resembles chronic pain regarding certain perceptual features such as prolonged pain duration and intensity fluctuations. Thus, longer-lasting experimental pain offers the opportunity to gain new insights into both the differential neural representation of noxious stimuli and pain and the neuronal mechanisms associated with the state of longer- lasting pain. We applied 10 minutes of painful heat stimulation to the left and right hand of 39 healthy participants while we recorded continuous pain ratings, electroencephalography (EEG), and autonomic responses. Data were analyzed in three distinct projects aiming at different aspects of neuronal mechanisms underlying longer-lasting pain. Project 1 assessed whether stimulus intensity as proxy of nociception and pain intensity relate to distinct patterns of oscillatory brain activity. EEG recordings revealed that increases in stimulus intensity were reflected by suppressions of alpha and beta oscillations in sensorimotor areas contralateral to the stimulated hand. In contrast, increases in pain intensity were associated with enhanced gamma oscillations in the medial prefrontal cortex. More importantly, the encoding of stimulus intensity by alpha and beta oscillations in the sensorimotor areas was spatially specific, i.e. depended on the stimulus location, whereas the encoding of pain intensity by gamma oscillations in the medial prefrontal cortex was independent of stimulus location. Thus, prefrontal gamma oscillations might reflect higher- order aspects of noxious stimuli, such as salience, valence, and motivational aspects rather than precise sensory features. Project 2 investigated the relationship between stimulus intensity, pain intensity, autonomic responses, and brain activity. Skin conductance measures, as markers of sympathetic activity, co-varied more closely with stimulus intensity than with pain intensity. Correspondingly, skin conductance measures were related to suppressions of alpha and beta oscillations in the sensorimotor area contralateral to the stimulated hand. These finding suggest that skin conductance measures are in part directly elicited by nociceptive processes and, thus, at least partially independent of perceptual processes during longer-lasting pain. Hence, these observations corroborate concepts of pain in which sensory, motivational, and autonomic processes partially independently contribute to the experience of pain. Finally, project 3 incorporated the systematic and comprehensive assessment of oscillatory brain activity, functional connectivity, and graph- theory based network measures during the state of longer-lasting pain. Longer-lasting pain was associated with suppressions of oscillatory brain activity at alpha frequencies in addition to stronger connectivity at alpha and beta frequencies in sensorimotor areas. Furthermore, sensorimotor areas contralateral to stimulation showed increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies and built a sensorimotor-prefrontal network during longer-lasting pain. This network might be involved in the integration of sensory, cognitive, and motivational-affective information and, consequently, in the translation of a noxious stimulus into a subjective pain experience. All three projects contribute to a better understanding of neuronal mechanisms underlying longer-lasting experimental pain, which serves as an experimental model for chronic pain. Since the treatment of chronic pain has remained insufficient and unsatisfactory, the current results might provide EEG-based targets for urgently needed new treatment approaches, such as non-invasive brain stimulation and neurofeedback

Neurophysiological mechanisms of longer-lasting experimental pain in humans

Pain serves the protection of the body. Consequently, noxious stimuli or, more precisely, the thereby induced neurophysiological processes commonly lead to pain perception. Identical noxious stimuli, however, do not always translate into the same pain experience depending on multiple factors. To acknowledge this variability, the distinction between nociception as the neural process elicited by noxious stimuli and pain as subjective multifactorial experience is essential. During longer-lasting experimental pain and chronic pain, nociception and pain can substantially dissociate. Moreover, longer-lasting experimental pain resembles chronic pain regarding certain perceptual features such as prolonged pain duration and intensity fluctuations. Thus, longer-lasting experimental pain offers the opportunity to gain new insights into both the differential neural representation of noxious stimuli and pain and the neuronal mechanisms associated with the state of longer- lasting pain. We applied 10 minutes of painful heat stimulation to the left and right hand of 39 healthy participants while we recorded continuous pain ratings, electroencephalography (EEG), and autonomic responses. Data were analyzed in three distinct projects aiming at different aspects of neuronal mechanisms underlying longer-lasting pain. Project 1 assessed whether stimulus intensity as proxy of nociception and pain intensity relate to distinct patterns of oscillatory brain activity. EEG recordings revealed that increases in stimulus intensity were reflected by suppressions of alpha and beta oscillations in sensorimotor areas contralateral to the stimulated hand. In contrast, increases in pain intensity were associated with enhanced gamma oscillations in the medial prefrontal cortex. More importantly, the encoding of stimulus intensity by alpha and beta oscillations in the sensorimotor areas was spatially specific, i.e. depended on the stimulus location, whereas the encoding of pain intensity by gamma oscillations in the medial prefrontal cortex was independent of stimulus location. Thus, prefrontal gamma oscillations might reflect higher- order aspects of noxious stimuli, such as salience, valence, and motivational aspects rather than precise sensory features. Project 2 investigated the relationship between stimulus intensity, pain intensity, autonomic responses, and brain activity. Skin conductance measures, as markers of sympathetic activity, co-varied more closely with stimulus intensity than with pain intensity. Correspondingly, skin conductance measures were related to suppressions of alpha and beta oscillations in the sensorimotor area contralateral to the stimulated hand. These finding suggest that skin conductance measures are in part directly elicited by nociceptive processes and, thus, at least partially independent of perceptual processes during longer-lasting pain. Hence, these observations corroborate concepts of pain in which sensory, motivational, and autonomic processes partially independently contribute to the experience of pain. Finally, project 3 incorporated the systematic and comprehensive assessment of oscillatory brain activity, functional connectivity, and graph- theory based network measures during the state of longer-lasting pain. Longer-lasting pain was associated with suppressions of oscillatory brain activity at alpha frequencies in addition to stronger connectivity at alpha and beta frequencies in sensorimotor areas. Furthermore, sensorimotor areas contralateral to stimulation showed increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies and built a sensorimotor-prefrontal network during longer-lasting pain. This network might be involved in the integration of sensory, cognitive, and motivational-affective information and, consequently, in the translation of a noxious stimulus into a subjective pain experience. All three projects contribute to a better understanding of neuronal mechanisms underlying longer-lasting experimental pain, which serves as an experimental model for chronic pain. Since the treatment of chronic pain has remained insufficient and unsatisfactory, the current results might provide EEG-based targets for urgently needed new treatment approaches, such as non-invasive brain stimulation and neurofeedback

Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes

Functional connectivity (FC), thought to provide a window into neural communication, has become a core focus in the study of brain function and cognition. However, there is no consensus on how to conceptualize large-scale FC in electrophysiology. Phase coupling (PhC), defined as coupling between the phases of two signals, reflects the synchronization of rhythmic oscillation cycles. Conversely, amplitude coupling (AmpC), defined as coupling between the envelopes of two signals, reflects correlation of activation amplitude. Despite quantifying different electrophysiological properties, the relationship between PhC and AmpC remains largely unknown. We assessed spatial and temporal correspondence between PhC and AmpC over 5 canonical frequency bands during a cue-based motor task using electrocorticography (ECoG) in 18 patients (8 females) undergoing presurgical monitoring. Significant correspondence between the spatial pattern of PhC and AmpC was detected during stimulus processing across all subjects and frequency bands (R≈0.50 for theta, decreasing with increasing frequency). The cross-measure spatial correlation vanished almost entirely when accounting for the portion of FC equally present during pre- and post-stimulus intervals, suggesting that the spatial correlations reflect intrinsic FC independent of stimulus processing. Stimulus-related processing modulated both PhC and AmpC, however in a spatially independent manner. Examining the linear temporal correlation, we found no evidence for linear dependence between PhC and AmpC. Supporting the robustness of our findings, results extended to a verb generation task in a second ECoG dataset of 6 subjects. We conclude that PhC and AmpC reflect intrinsic FC similarly across space, but exhibit divergent stimulus-related FC changes over space and time

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned “word” forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful “word” and novel, senseless “pseudoword” patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience