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Synchronous firing of a neuronal ensemble A familiar object is represented in the brain by thousands of neurons dispersed throughout the posterior cortex. When you recall an apple, the neuronal ensemble of the apple is firing in synchrony. II. Neocortex: The role of the neocortex is to store and manipulate memories 1. Frontal lobe controls movement: (in all animals - movement of muscles. Evolved in primates: purposeful movement of thoughts. We can look at conscious purposeful movement of thoughts as internalization of movement). Frontal lobe controls the timing of neuronal firing: it schedules movement routines and thoughts in time. Frontal 2. Dorsal cortex: encodes sensory memories. More specifically, encodes sensory experiences into ensembles of neurons capable of self-activation Parietal lobe lobe Temporal lobe Occipital lobe 1. How is sensory information is encoded by neurons? • Sensory information is coded by the rate of firing of action potentials (number of action potentials per second) 2. How motor information is encoded by a motor neuron? • Again, information is coded in frequency of action potentials: the greater the firing rate the greater the tension • In addition CNS can recruit more motor units • What is the range of firing rate? • Is every motor neuron action potential followed by a muscle contraction? 3. How the information about your speed of movement is encoded in the brain? • Speed cells in entorhinal cortex fire action potentials at a rate proportional to animal speed of movement. • This information is feeding their info to grid cells. In the brain… Action potential 1. Is every presynaptic action potential in the Postsynaptic brain followed by a postsynaptic action potential? potential 2. No. Most postsynaptic potentials are too small to elicit a postsynaptic action potential. Why? 3. Postsynaptic potentials are local potentials – they are not usually amplified 4. Postsynaptic potentials are graded potentials: the more APs arrived the greater EPSP (as opposed to all-or-none APs) 5. Since postsynaptic potentials are not amplified, postsynaptic potentials as decreasing in amplitude as one measures change in Em away from a synapse Em 10mV 5mV 3mV 1mV synapse dendrite AP in presynaptic cell axon • Reasons for synchronous action potentials: 1. Spatial summation • It usually requires many presynaptic neurons to fire action potentials that arrive at the postsynaptic neuron at the same time to depolarize the postsynaptic membrane potential above threshold and trigger an action potential in the postsynaptic cell. Reasons for synchronous action potentials: 2. LTP 1 3 Ca++ 3 4 5 Influx of Ca++ Synapse is modified by displacing Mg2+ Presynaptic neuron A 6 Presynaptic neuron A 2 postsynaptic neuron B postsynaptic neuron B Increase of the number of synapses between presynaptic axon A and postsynaptic neuron B Reasons for synchronous action potentials: 2. LTP • If a presynaptic axon and a postsynaptic cell are to enhance their connection they have to fire an action potential at the same time • Hebbian principle: fire together wire together • This is the only way to develop memory The neuronal ensemble binding mechanism is based on the Hebbian principle: “neurons that fire together, wire together” (Hebb, 1949). Hebb wrote: “… any two cells or systems of cells that are repeatedly active at the same time will tend to become ‘associated,’ so that activity in one facilitates activity in the other. … When one cell repeatedly assists in firing another, the axon of the first cell develops synaptic knobs (or enlarges them if they already exist) in contact with the soma of the second cell.” (Hebb, 1949). What is the mechanism of Hebbian learning? Method to achieve synchronization in a group of neurons: depolarization wave • Name examples of pacemaker cells outside of CNS? • Heart • Gastrointestinal tract Examples • Heart synchronous beating (outside of CNS) • Slow wave sleep (1Hz) • Tremor, such as essential tremor or Parkinsonian tremor • Epilepsy: seizures are transient hypersynchronous neuronal activity in the Generalized 3 Hz spike and wave brain discharges reflecting seizure activity • In epileptic seizures a group of neurons begins firing in an abnormal, excessive, and synchronized manner. Neuronal binding by synchronization • Until recently, the brain was viewed as a collection of neurons that fire in asynchrony. • The synchronous firing of cortical neurons was only associated with epileptic seizures: wavelike electrical activity of a large number of neurons, often associated with loss of consciousness and involuntary body movement. • New evidence indicates that neurons often communicate by firing near synchronous action potentials. • In fact, there is evidence that de-synchronization is associated with disorders such as schizophrenia and ADHD. • The solution to the binding problem: • The synchronous firing is thought to be involved in binding neurons of a neuronal ensemble together (following the principle of “fire together - wire together”). • This hypothesis is referred to as “binding-by-synchronization” (Singer & Gray, 1995). binding-by-synchronization “Neuronal synchronization is a ubiquitous phenomenon in cortical networks and likely to serve a variety of different functions in addition to feature binding at early levels of sensory processing.” -- PETER J. UHLHAAS et al., Neural synchrony in cortical networks (2009) Experiments: Direct observation of synchronicity of neurons belonging to a single object JC- 1_1991_Engel_Direct physiological evidence for scene segmentation • recorded from multiple neurons in the primary visual cortex of a cat. • observed that two neurons synchronized their firing only when their activating stimulus belonged to a single object. • In other words, neurons synchronized only when they were part of the same neuronal ensemble. • Stimulation with single light bars of different orientations (a single object) yielded a synchronization of oscillatory responses between all sites activated by the respective orientation (==a single neuronal ensemble). • Two different objects moving separately result in two neuronal ensembles • Cells 1 and 3 belong to one neuronal ensemble and cells 2 and 4 belong to another neuronal ensemble. • The ensembles are asynchronous between themselves. • Hirabayashi & Miyashita, 2005 (JC-Th): Record from pairs of neurons located in the inferior temporal cortex (responsible for face recognition) in alert monkeys. • The neurons were selected in such a way that both cells in a pair responded significantly to facial fragments shown one at a time. • monkeys were shown pictures from two different sets. In the first set, the nose, mouth, and eyes were organized into a face-like combination. • In the second set, the facial fragments - nose, mouth, and eyes - were shown scrambled up (e.g. mouth could be on top, nose on the left, one eye on the bottom, and another eye on the right). • Thus both neurons would significantly increase their activity when presented with either the face-like pictures or the scrambled face pictures. • Was there any difference in the neuronal activity between the face-like pictures and a scrambled collection of facial features? • The study found that there was no difference in terms of firing rate, • but a clear difference was observed in the timing of the neuronal firing: • neurons responding to the features transiently synchronized their responses when the monkeys recognized that the component features of a face actually formed a face. • Face perception, i.e. actual recognition that component features of a face formed an actual face was associated with the synchronization of neurons encoding the individual facial features (=perceptual closure =activation of complete neuronal ensemble.) • On the local level: groups of neurons within one cortical area often synchronize in order to “vote on a particular issue.” • In this case, local groups of neurons undergo low amplitude depolarization waves with a frequency of 30 to 100 Hz. • These waves are called gamma-frequency waves. Global synchronization Neurons tend to fire action potentials on the upswing of the depolarization wave • • • • In addition to the local depolarization wave, a global wave with a frequency of 15 to 25 Hz ensures effective communication between neurons in different cortical areas (analogous to a company-wide meeting). This wave is called a beta-frequency wave. Both beta-frequency and gamma-frequency cortical neuron synchronizations are observed for consciously perceived stimuli (Meador, 2002; Gross, 2004; Nakatani, 2005; Palva, 2005) and for conscious perception in binocular rivalry (Fries, 1997; Srinivasan, 1999; Fries, 2002; Doesburg, 2005). These findings have inspired the hypotheses that synchronized oscillations play a role in consciousness (e.g., Crick and Koch, 1990; Llinas et al., 1998; Buzsaki, 2004). Experimental evidence • Pejman Sehatpour et al. (2008) (JC-Th) used intracranial electrodes to record from three human subjects (who were undergoing medical tests for intractable epilepsy) as they performed a challenging visual object recognition task that required them to identify barely recognizable fragmented line-drawings of common objects. • Neuronal activity recorded during the “recognition” moment (also called perceptual closure) was compared to the “nonrecognition” event when scrambled (nonsensical) versions of the same images were shown. only the difference between scrambles and unscrambled • Sehatpour and colleagues simultaneously recorded from several areas involved in visual recognition: the occipitotemporal cortex, the prefrontal cortex, and the hippocampus. • The analysis showed a robust coherence in the beta-band between all three brain areas when participants recognized the fragmented images. • In contrast, when scrambled versions of the same images were presented, a significantly lower coherence was observed. • These results suggest that object-encoding neuronal ensembles are distributed through several cortical regions (in this case, all the regions where electrodes were placed) and that neurons of the ensemble do synchronize when the encoded object is consciously perceived. Eugenio Rodríguez et al. (1999) (JC-Th) • Study focused on the perception of 'Mooney' faces, high-contrast pictures of a human faces which are easily recognized as faces when presented upright orientation, but usually seen as meaningless black and white shapes when presented upside-down. • An electroencephalogram (EEG) was used to record from healthy human subjects. • A consistent pattern of synchrony between left occipital, left parietal and left frontal cortices was established during face recognition around 200 ms after presentation of an upright face. • When the faces were presented scrambled up, no synchrony was observed. Synchrony between electrode pairs is indicated by lines, which are drawn only if the synchrony value is beyond the distribution of shuffled data sets (P < 0.01). Black lines correspond to a significant increase in synchrony. Green lines = a significant decrease in synchrony. Phase synchrony is markedly regional and differs between conditions. • Singer, 2006: (C) shows the topography of phase synchrony between 20–30 Hz. Synchrony between electrodes is indicated by lines, which are drawn only if the synchrony value is beyond a two-tailed probability of p < 0.0005. • Notice the widespread network of synchronized neurons in controls Hipp et al. (2011) (JC-Th) • High-density EEG recordings from human subjects • The subjects’ task was to judge the configuration of an ambiguous stimulus which consisted of two bars that approach, briefly overlap and move apart from each other. • The perception of this stimulus spontaneously alternates between two distinct alternatives. • In half of the trials, the two bars are perceived as two independent objects passing one another (==two independent neuronal ensembles = no synchronization). • In the other half of trials, the two bars are perceived as a single object with bouncing sides (think of a slinky; a single neuronal ensemble neurons synchronize in time). • the extrastriate cortex, the posterior parietal, temporal and prefrontal cortex, showed enhanced beta rhythm synchrony during stimulus processing. • the synchronicity between regions in beta frequency predicted the subjects’ perception of the stimulus even on a single-trial level! • when beta frequency synchronization was enhanced, subjects were more likely to perceive the same sensory stimulus as a single bouncing object (encoded by a single synchronized neuronal ensemble) rather than two bars passing each other (encoded by two independent unsynchronized neuronal ensembles). Counter-example • 2008 - Synchrony and the binding problem in macaque visual cortex • They did not find strong synchrony • “A limitation of our study is also the use of a behavioral task that engaged attention at the fixation target” – were the monkeys perceiving two objects? When I attend to the fixation point, it is much harder for me to tell whether there is one figure or two figures present Theta rhythms in hippocampus • Neural oscillations, in particular theta (4–7 Hz) activity, are extensively linked to memory function. Theta rhythms are very strong in rodent hippocampi and entorhinal cortex during learning and memory retrieval. • Theta rhythms are believed to be vital to the induction of long-term potentiation, a cellular mechanism for learning and memory. • When people are finding their way or looking at something novel (when they are learning), the theta rhythm is particularly strong . • The stronger theta oscillations are, the better the person will remember the new material. Theta in human hippocampus • EXPERIMENT: Rutishauser team used the implanted microelectrodes to track electrical activity in the hippocampus and the amygdala as well as local field potential in nine epileptics. • Patients viewed 100 slides, each of which showed an image of a person, an animal, or an everyday object such as a car or a tool. The patients had 1s to remember each picture as best they could before the next one appeared. • prominent theta activity when the patients were memorizing the images. • The team later tested the patients’ recall by showing them a second set of 100 photographs, half of which were novel and half of which were repeats. • On average, participants recognized 60% of the initial pictures. • What predicted successful recall? • The firing rate while a subject viewed an image during learning phase did not predict whether or not the patient would later recall it. • However, if a picture flashed on the screen at a moment when neuronal spikes in the hippocampus lined up with the local theta rhythm, patients were more likely to remember the image! • Common knowledge: memory formation is influenced by – attention – novelty – emotional impact • TIMING! • Neurons always spike in response to new images and experiences. • But when the spikes happen to coincide with the theta rhythm, this coordinated electrical activity alters the brain’s synapses, enabling memories to form. • How widespread can neuronal ensemble be? In the past, fMRI studies have depicted the cortex as a patchwork of function-specific regions. How widespread can neuronal ensemble be? • Siegel & Buschman & Miller, 2015 - found significant encoding for all information across all regions multiple cortical regions work together simultaneously to process sensorimotor information • 108 electrodes that measured neural spikes in 2,694 sites across six cortical regions: [middle temporal area (MT/V5), visual area four (V4), inferior temporal cortex (IT), lateral intraparietal area (LIP), prefrontal cortex (PFC), and frontal eye fields (FEF)] • Neural activity, near simultaneously: Sensory information — for cue, and color or motion — started in the MT and V4, but flowed to the LIP, IT, FEF, and PFC. • Task information started in V4 and IT, but flowed forward to PFC and LIP, and onward to the FEF and back to the V4. • Choice signals built up in PFC and LIP, before flowing forward and backward to FEF and the V4. • In short, despite neural spikes in specific areas, all information was shared widely. • Conclusion by Miller: Previously, it was thought that decisions rise solely in specific cortical areas. “But you see the decision percolating up all over many parts of the cortex simultaneously, so even decision-making is more of an emerging property of many cortical areas” . Summary of different rythms • Delta wave – (0.1 – 3 Hz) - associated with the deep non-REM slow wave sleep (training of neuronal ensembles by hippocampus). Pacemaker cells are in subcortical structures thalamus, reticular formation, suprachiasmatic nuclei in the hypothalamus. Right hemisphere dominance during sleep. • Theta wave – (4 – 7 Hz) – associated with learning and memory (training of neuronal ensembles by hippocampus). Pacemakers in the CA1 layer of hippocampus. • Alpha wave – (8 – 15 Hz) – e.g. originates from the occipital lobe during wakeful relaxation with closed eyes, hence its use in biofeedback during meditation. Pacemaker cells are in the thalamus. • Beta wave – (16 – 31 Hz) - associated with active thinking and active concentration, formation of global neuronal ensembles. • Gamma wave – (32 – 100 Hz) - associated with formation of local neuronal ensembles. Pacemakers are inhibitory interneurons releasing GABA. Normally we have meditation • • • • • • 10 novice vs. 8 long-term meditators – energy in gamma-band activity (relative to more slowly changing brain waves). Meditators were asked to attain a state of “unconditional loving-kindness and compassion” Experienced meditators (monks) produce increased gamma waves in the brain (25-42Hz) synchronized across the frontal and parietal cortices Such activity is thought to be the hallmark of focusing attention that involves synchronization of spatially dispersed groups of neurons. gamma activity in monks is the largest seen in nonpathological conditions and 30 times greater than in the novices. The more years the monks had been practicing meditation, the stronger the gamma activity. Normally: all different departments activate spontaneously (most of them subconsciously) EEG waves cancelling each other. From time to time a neuronal ensemble achieves greater synchronization and gets conscious attention to itself this spontaneous activation of neuronal ensembles produces thought clutter. Experienced meditators can synchronize all departments significant increase in EEG amplitude no thought clutter Conclusions • There is significant experimental evidence that long-range synchronization of neurons encoding an object plays an important role in the binding of multiple features into one integrated percept. • This integration is involuntary. It is driven by the resonant activation of the object’s neuronal ensemble stored in memory as enhanced connections between neurons of the ensemble. • The complete neuronal ensemble of an object is automatically activated and the object is perceived whether the recollection is triggered by seeing a partially visible object, hearing about the object, or just thinking of the object. • The complete neuronal ensemble of the object is activated because the neurons of the ensemble have preexisting enhanced connections (greater number of synapses). II. Neocortex: The role of the neocortex is to store and manipulate memories 1. Frontal lobe controls movement: (in all animals - movement of muscles. Evolved in primates: purposeful movement of thoughts. We can look at conscious purposeful movement of thoughts as internalization of movement). Frontal lobe controls the timing of neuronal firing: it schedules movement routines and thoughts in time. Frontal 2. Dorsal cortex: encodes sensory memories. More specifically, encodes sensory experiences into ensembles of neurons capable of self-activation Parietal lobe lobe Temporal lobe Occipital lobe • Wolf Singer (1h, 2013; start on 27min to avoid philosophy): https://www.youtube.com/watch?v=WgEWMdV1 Q4w • stop here • synchronicity has to be understood in terms of synchronicity of the arrival of action potentials to a target neuron rather than absolute equality of action potential conduction times over different paths. Consider the following example: suppose neuron A is receiving excitatory input from neurons B and C via two different pathways (neuron A is the target neuron for both neurons B and C). Suppose that the action potential conduction time is 2ms from neuron B to neuron A and 22ms from neuron C to neuron A (i.e. the axonal pathway B-A has a significantly shorter conduction time than the axonal pathway C-A). Does it mean that the connections B-A and C-A are always asynchronous? The answer depends on the predominant neural activity rhythm in this network. At the firing rate of 50Hz (inter-spike interval of 20ms that correspond to Gamma rhythm), neurons B and C can actually be considered isochronous in relationship to neuron A: consider a train of action potentials synchronously fired by neurons B and C. The first action potential from neuron B will reach neuron A in 2ms and the first action potential from neuron C will reach neuron A in 22ms. Obviously, there would be no coincidence in the arrival times of the 1st action potentials from neurons B and C. However the second action potential from neuron B will arrive to neuron A in 22ms, concurrently with the 1st action potential from neuron C. Thus, starting with the second action potential, neuron A will receive isochronous activation from neurons B and C. The synchronous activation has a significantly greater probability of enhancing synaptic connections between neurons A and B, and A and C (Hebbian learning: ‘neurons that fire together, wire together’ (Hebb, 1949)). Thus, isochronicity does not need to imply absolute equality in the conduction time over different pathways. Rather isochronicity implies near-zero phase-shift between the two firing trains of action potentials at the postsynaptic cells. The phase-shift, of course, depends on both conduction times over each pathway and the dominant firing frequency in the neural network. Long-term potentiation (LTP)