One day CNS 2018 workshop


Models for perceiving and learning time intervals and rhythms

This workshop will take place on July 17, as part of the Annual Computational Neuroscience Meeting in Seattle. Full schedule to follow.


Workshop overview

Accurate time estimation is essential for survival, yet the neural bases remain elusive. Time processing has been widely studied in the context of decision making, language, memory and perception. Research on interval-timing, for sub to suprasecond scales, ranges from psychophysical experiments and imaging studies to theoretical models. Beat perception in music is particularly compelling, fast perception and learning of repetitive time intervals from 100 to 2000 ms. The abilities to recognize and predict rhythms appear inherent to humans. Hypotheses of neural mechanism involve sensory and motor area interaction (eg, listening and finger-tapping). We will bring together researchers that are developing models of timing and of prediction with frameworks that include drift-diffusion, neural resonance, coincidence detection and adapting neuronal oscillator circuits. We seek to promote discussion and linkage between the timing and prediction fields, both important for understanding beat perception.


Speakers

  1. Áine Byrne - New York University
  2. Jessica Grahn - Western University, Canada
  3. John Iversen - University of California San Diego
  4. Edward Large - University of Connecticut
  5. Hugo Merchant - National Autonomous University of Mexico
  6. Sorinel Oprisan - College of Charleston
  7. Patrick Simen - Oberlin College
  8. Sundeep Teki - University of Oxford, UK

Organisers

  1. Áine Byrne - New York University
  2. John Rinzel - New York University
  3. Amitabha Bose - New Jersey Institute of Technology

Program

08:55 - 09:00Opening Remarks
09:00 - 09:45 Jessica Grahn "The role of beat perception in auditory sequence processing"
09:45 - 10:30 Sorinel Oprisan "Models of Interval Timing"
10:30 - 11:00Coffee Break
11:00 - 11:45 John Iversen "Audiomotor interactions in beat perception"
11:45 - 12:30 Edward Large "How you got your groove: Modeling rhythm learning, perceptual narrowing, and enculturation"
12:30 - 14:00Lunch
14:00 - 14:45 Sundeep Teki "Contextual representation of time intervals in rhythmic sound sequences"
14:45 - 15:30 Áine Byrne "A neuromechanisic model for beat generation"
15:30 - 16:00Coffee Break
16:00 - 16:45 Hugo Merchant "Neural population dynamics in the primate supplementary motor area during rhythmic tapping"
16:45 - 17:30 Patrick Simen "A drift-diffusion model of complex motor timing without a reset problem"
17:30 - 17:40Closing Remarks

Registration

Attendance to all CNS workshops is subject to registration at the conference webpage.

Location

Workshop will be held at the Allen Institute, room number TBA.

Abstracts

Áine Byrne - A neuromechanisic model for beat generation

Humans can recognize rhythmicity and reproduce it with ease. There are many behavioural studies on such sensorimotor synchronization tasks, yet the underlying neural mechanisms remain poorly understood. We introduce an idealized neuromechanstic model which, in its most basic form, consists of a single beat generator neuron (BG) and set of clocks derived from naturally occurring gamma frequency oscillations. These clocks are used to compare the period and firing times of the BG with that of an external isochronous stimulus. A set of plasticity rules iteratively updates a biophysical parameter that controls the excitability of the neural system to adjust and align the BG period and firing times with the stimulus. The model quickly learns new rhythms, within a few cycles, as found in human behaviour, and, additionally, performs well in synchronization-continuation tasks. The model makes predictions for the transient response to deviants, distractors and omissions. Our modelling paradigm combines ideas from entrainment, information processing and interval timing models to propose neural mechanisms not just for the perception of a beat, but also for an internal neural time-keeper to produce a rhythmic beat.

Jessica Grahn - The role of beat perception in auditory sequence processing

TBA

John Iversen - Audiomotor interactions in beat perception

Every human culture has some form of music that evokes in listeners a feeling of beat: a perceived periodic pulse that structures the perception of temporal rhythms. It is widely understood that the beat is not uniquely determined by sound, but is an endogenous temporal response that can be shaped at will by the listener, often dramatically changing the perceptual experience of a rhythmic pattern. It has been suggested that the motor system plays a necessary role in beat perception, dynamically shaping our perception of rhythm through bidirectional auditory-motor signaling, for example as laid out in the ASAP (action simulation for auditory perception) hypothesis. We will present studies exploring the role of motor systems in beat perception. The first used a 'beat shift' paradigm to temporally disentangle auditory and endogenous beat-related responses in order to localize them in the brain. Brain recordings analyzed with ICA identified multiple cortical effective sources of activity in each participant, enabling the differentiation of beat- and sound-responsive regions in premotor and superior temporal cortex respectively, consistent with motor involvement in beat representation. Recent studies used neurostimulation to more directly test the role of the motor system in beat perception. Transient reduction of activity in parietal cortex, a link between auditory and motor systems, was associated with reduction of beat-perception performance. The finding is consistent with the hypothesized causal role of the dorsal audiomotor pathway in beat perception. Interestingly, only some aspects of beat-perception performance were disrupted, suggesting that a view of beat perception as a unitary mechanism may be overly simplistic.

Edward Large - How you got your groove: Modeling rhythm learning, perceptual narrowing, and enculturation

Ontogeny is a complex, emergent process that arises from interactions between the developing organism and the structures present in the rearing environment. In the field of infant development, one of the most well known consequences of organism-environment interactions is the adaption and re-organization of perception-action systems to structural regularities in the environment, a phenomenon called “perceptual narrowing” or “perceptual fine tuning.” Previous work suggests that infants’ perception of musical rhythms is gradually fine-tuned to culture-specific musical structures over the first post-natal year. To date, however, little is known about the neurobiological principles that underlie this process. In the current study, we modeled infants’ perceptual narrowing to culture-specific musical rhythms using oscillatory neural networks with Hebbian synaptic plasticity. We demonstrate that, during a period of unsupervised learning, oscillatory networks adapt to the rhythmic structure of Western and Balkan musical rhythms through the self-organization of network connections. We show that these learned connections affect the ability of the network to discriminate between native and non-native rhythms, a pattern of findings that mirrors the behavioral data on infants’ perceptual narrowing to musical rhythms. We develop an overall framework for modeling rhythm learning and development, and discuss how this may account for the process of enculturation to the rhythms of one’s musical environment.

Hugo Merchant - Neural population dynamics in the primate supplementary motor area during rhythmic tapping

The ability to generate rhythms with different tempos is a hallmark of musical cognition. We know that tapping to a regular beat engages neurons from the medial premotor cortices (MPC). Yet, the neuronal population code behind rhythmic tapping remains elusive. Here we found that the activity of hundreds of primate MPC neurons show a strong periodic pattern that becomes evident when its activity is projected into a lower dimensional state space. We show that different tempos are encoded by circular trajectories of different radii. In addition, the intertrial variability of neural trajectories increased as a function of the interval, accounting for a key feature of timing behavior: the scalar property, which states that the variability of produced or estimated intervals increases linearly as a function of interval duration. Crucially, the oscillatory dynamics in neuronal state space is a signature of cognitive timing under metronome guidance or when is internally controlled, and is not the result of repetitive motor commands. Our results support the notion that rhythmic behaviors are encoded by the dynamic state of MPC neural populations.

Sorinel Oprisan - Models of Interval Timing

Time perception in the supra-second range is crucial for fundamental cognitive processes like decision making, rate calculation, and planning. In the vast majority of species, behavioral and neurophysiological manipulations, interval timing is scale invariant: the time-estimation error is proportional to the estimated duration. The origin and mechanisms of this fundamental property are unknown. We suggested a computational model consisting of a large number of (input) neural oscillators projecting on a small number of (output) coincidence detector neurons, which allows time to be coded by the pattern of coincidental activation of its inputs. We showed that time-scale invariance emerges from the neural noise, such as small fluctuations in the firing patterns of its input neurons and in the errors with which information is encoded and retrieved by its output neurons. In this architecture, time-scale invariance is resistant to manipulations as it depends neither on the details of the input population, nor on the distribution probability of noise. A step closer to the learning mechanism for interval timing has been offered by the model of hippocampus lesions. We showed that a spatial localization of temporal memory could be a possible explanation of the experimentally observed shifts of the peak responses due to hippocampus lesions.

Patrick Simen - A drift-diffusion model of complex motor timing without a reset problem

Laje, Cheng & Buonomano (Frontiers, 2011) claimed that one problem for timing circuits consisting of simple, climbing activation networks, or pacemaker-accumulators, or drift-diffusion processes, was their inability to predict what they termed "continuous" timing patterns in complex sequential movements. Instead, simple pacemaker-accumulator-style models would necessarily produce a "reset timing" pattern, in which an internal timer resets and starts over again at each element of a sequence. In contrast, a "population clock model" produces the empirically observed "continuous" pattern. I review what this claim means, and I offer a pacemaker-accumulator-style model that does not appear to suffer from the reset timing problem. I also address some additional virtues in terms of learning speed of the simple, pacemaker-accumulator/drift-diffusion approach to timing, in the context of complex sequential movements.

Sundeep Teki - Contextual representation of time intervals in rhythmic sound sequences

TBA